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Name
Label
Description
DataType
Groups
120 Sample Arm
Phase 2 data. Arm from which 120 minute blood sample was taken.
Text
120 Sample by
Phase 2 data. Initials/ID of staff member 120 minute blood sample was taken by
Text
120 Sample Site
Phase 2 data. Site of 120 minute sample blood sample taken
Text
whether there was 35 hrs of good quality daytime d
35 daytime hours
None
Phase 2 data. 35 daytime hours for Phase 2? (frist wear of Actiheart only). Used for Study cooridination purposes not for analysis. Use wear varibles in main AH dataset for analysis. 0 = no; 1 = yes;
Categorical
Eat when lonely
When I feel lonely I console myself by eating.
Categorical
Feeling lonely console by eating
Phase 2 data. When I feel lonely; I console myself by eating. 1 = Definitely true; 2 = Mostly true; 3 = Mostly false; 4 = Definitely false;
Categorical
Eat when lonely_rescored
New in R8. derived by re-scoring item 3FEQ_10lonelyconsoleeating; score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n=4810). When I feel lonely; I console myself by eating.
Categorical
Re-scored item 3FEQ_10lonelyconsoleeating_P2
Phase 2 data. Derived by re-scoring item 3FEQ_10lonelyconsoleeating_P2; score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n = 4810). When I feel lonely; I console myself by eating. 1 = Definitely false; 2 = Mostly false; 3 = Mostly true; 4 = Definitely true (a decimal value was allowed for answers with a range); -1 = missing data; -9 = questionnaire not completed;
Categorical
Hold back on meals so not to gain weight
I consciously hold back at meals in order not to gain weight.
Categorical
Hold back on eating control weight
Phase 2 data. I consciously hold back at meals in order not to gain weight. 1 = Definitely true; 2 = Mostly true; 3 = Mostly false; 4 = Definitely false;
Categorical
Hold back on meals so not to gain weight_rescored
New in R8. derived by re-scoring item 3FEQ_11holdbackatmeals; score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n=4810).I consciously hold back at meals in order not to gain weight.
Categorical
Re-scored item 3FEQ_11holdbackatmeals
Phase 2 data. Derived by re-scoring item 3FEQ_11holdbackatmeals_P2; score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n = 4810).I consciously hold back at meals in order not to gain weight. 1 = Definitely false; 2 = Mostly false; 3 = Mostly true; 4 = Definitely true (a decimal value was allowed for answers with a range); -1 = missing data; -9 = questionnaire not completed;
Categorical
Avoid foods that make me fat
I do not eat some foods because they make me fat.
Categorical
Do not eat some food make me fat
Phase 2 data. I do not eat some foods because they make me fat. 1 = Definitely true; 2 = Mostly true; 3 = Mostly false; 4 = Definitely false;
Categorical
Avoid foods that make me fat_rescored
New in R8. derived by re-scoring item 3FEQfeq_12foodmakemefat; score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n=4810).I do not eat some foods because they make me fat.
Categorical
Re-scored item 3FEQfeq_12foodmakemefat_P2
Phase 2 data. Derived by re-scoring item 3FEQfeq_12foodmakemefat_P2; score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n = 4810).I do not eat some foods because they make me fat. 1 = Definitely false; 2 = Mostly false; 3 = Mostly true; 4 = Definitely true (a decimal value was allowed for answers with a range); -1 = missing data; -9 = questionnaire not completed;
Categorical
Hungry enough to eat any time
I am always hungry enough to eat at any time.
Categorical
Always hungry to eat any time
Phase 2 data. I am always hungry enough to eat at any time. 1 = Definitely true; 2 = Mostly true; 3 = Mostly false; 4 = Definitely false;
Categorical
Hungry enough to eat any time_rescored
New in R8. derived by re-scoring item 3FEQ_13hungryeatanytime; score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n=4810).I am always hungry enough to eat at any time.
Categorical
Re-scored item 3FEQ_13hungryeatanytime_P2
Phase 2 data. Derived by re-scoring item 3FEQ_13hungryeatanytime_P2; score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n = 4810).I am always hungry enough to eat at any time. 1 = Definitely false; 2 = Mostly false; 3 = Mostly true; 4 = Definitely true (a decimal value was allowed for answers with a range); -1 = missing data; -9 = questionnaire not completed;
Categorical
How often hungry
How often do you feel hungry?
Categorical
Often feel hungry frequency
Phase 2 data. How often do you feel hungry? 1 = Only at meal times; 2 = Sometimes between meals; 3 = Often between meals; 4 = Almost always;
Categorical
How often hungry_rescored
New in R8. derived from item 3FEQ_14oftenfeelhungry (assessed and cleaned only in the subset n=4810). Note all scores were left the same apart from -1 scores which were removed. How often do you feel hungry? Please note that rarely and never have been recoded as 1.
Categorical
Derived from 3FEQ_14oftenfeelhungry_P2
Phase 2 data. Derived from item 3FEQ_14oftenfeelhungry_P2 (assessed and cleaned only in the subset n = 4810). Note all scores were left the same apart from -1 scores which were removed. How often do you feel hungry? Please note that rarely and never have been recoded as 1. 1 = Only at meal times; 2 = Sometimes between meals; 3 = Often between meals; 4 = Almost always; -1 = missing data; -9 = questionnaire not completed;
Categorical
Avoid stocking up on tempting foods
Phase 2 data. How frequently do you avoid stocking up on tempting foods? 1 = Almost never; 2 = Seldom; 3 = Usually; 4 = Almost always;
Categorical
Avoid stocking up on tempting foods
How frequently do you avoid -stocking up?½ on tempting foods?
Categorical
Avoid stocking up on tempting foods_rescored
New in R8. derived from item 3FEQ_15stockinguptemptingfoods (assessed and cleaned only in the subset n=4810). Note all scores were left the same apart from -1 scores which were removed. How frequently do you avoid stocking up?½ on tempting foods?
Categorical
Derived from 3FEQ_15stockinguptemptingfoods_P2
Phase 2 data. Derived from item 3FEQ_15stockinguptemptingfoods_P2 (assessed and cleaned only in the subset n = 4810). Note all scores were left the same apart from -1 scores which were removed. How frequently do you avoid stocking up® on tempting foods? 1 = Almost never; 2 = Seldom; 3 = Usually; 4 = Almost always; -9 = questionnaire not completed;
Categorical
Conciously eat less than want
How likely are you to consciously eat less than you want?
Categorical
Consciously eat less food
Phase 2 data. How likely are you to consciously eat less than you want? 1 = Unlikely; 2 = Slightly likely; 3 = Moderately likely; 4 = Very likely;
Categorical
Conciously eat less than want_rescored
New in R8. derived from item 3FEQ_16consciouslyeatless (assessed and cleaned only in the subset n=4810). Note all scores were left the same apart from -1 scores which were removed.
Categorical
Derived from 3FEQ_16consciouslyeatless_P2
Phase 2 data. Derived from item 3FEQ_16consciouslyeatless_P2 (assessed and cleaned only in the subset n = 4810). Note all scores were left the same apart from -1 scores which were removed. 1 = Unlikely; 2 = Slightly likely; 3 = Moderately likely; 4 = Very likely; -9 = questionnaire not completed;
Categorical
Binge eating
Phase 2 data. Do you go on eating binges though you are not hungry? 1 = Never; 2 = Rarely; 3 = Sometimes; 4 = At least once a week;
Categorical
Eating binges when not hungry
Do you go on eating binges though you are not hungry?
Categorical
Eating binges when not hungry_rescored
New in R8. derived from item 3FEQ_17eatingbingeswhennothungry (assessed and cleaned only in the subset n=4810). Note all scores were left the same apart from -1 scores which were removed. Do you go on eating binges though you are not hungry?
Categorical
Derived from 3FEQ_17eatingbingeswhennothungry_P2
Phase 2 data. Derived from item 3FEQ_17eatingbingeswhennothungry_P2 (assessed and cleaned only in the subset n = 4810). Note all scores were left the same apart from -1 scores which were removed. Do you go on eating binges though you are not hungry? 1 = Never; 2 = Rarely; 3 = Sometimes; 4 = At least once a week; -1 = missing data; -9 = questionnaire not completed;
Categorical
How restrained when eating
On a scale of 1 to 8 with regards to restraint in eating what number would you give yourself? Where 1 means no restraint in eating and 8 means total restraint.
Categorical
Scale of restraint on eating
Phase 2 data. On a scale of 1 to 8 where 1 means no restraint in eating (eating whatever you want whenever you want it) and 8 means total restraint (constantly limiting food intake and never giving in); what number would you give yourself? 1 = 1 (no restraint in eating ie eating whatever you want and whenever you want it); 2 = 2; 3 = 34 = 4; 5 = 5; 6 = 6; 7 = 7; 8 = 8 (total restraint ie constantly limiting food and never giving in);
Categorical
How restrained when eating_rescored
New in R8. derived by re-scoring item 3FEQ_ 18scaleofrestraint; score of 1 or 2 as 1; 3 or 4 as 2; 5 or 6 as 3 and 7 or 8 as 4 (assessed and cleaned only in the subset n=4810). On a scale of 1 to 4 with regards to restraint in eating what number would you give yourself? Where 1 means no restraint in eating and 4 means total restraint.
Categorical
Re-scored item 3FEQ_ 18scaleofrestraint_P2
Phase 2 data. Derived by re-scoring item 3FEQ_ 18scaleofrestraint_P2; score of 1 or 2 as 1; 3 or 4 as 2; 5 or 6 as 3 and 7 or 8 as 4 (assessed and cleaned only in the subset n = 4810). On a scale of 1 to 4 with regards to restraint in eating what number would you give yourself? Where 1 means no restraint in eating and 4 means total restraint. 1 = 1; 2 = 2; 3 = 3; 4 = 4; -9 = questionnaire not completed; -1 = missing data (this also includes answers which were not consecutive);
Categorical
Smell of meat dfficult to keep from eating even after a meal
When I smell a sizzling steak or juicy piece of meat I find it very difficult to keep from eating even if I have just finished a meal.
Categorical
Smell of meat makes eating more
Phase 2 data. When I smell a sizzling steak or juicy piece of meat I find it very difficult to keep from eating even if I have just finished a meal. 1 = Definitely true; 2 = Mostly true; 3 = Mostly false; 4 = definitely false; -1 = left blank; -5 = more than one selected; -10 = does not fit with any other instruction;
Categorical
Smell of meat dfficult to keep from eating even after a meal_rescored
New in R8. Derived by re-scoring item 3FEQ_1smellofmeat score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n=4810). When I smell a sizzling steak or juicy piece of meat I find it very difficult to keep from eating even if I have just finished a meal.
Categorical
Re-scored item 3FEQ_1smellofmeat_P2
Phase 2 data. Derived by re-scoring item 3FEQ_1smellofmeat_P2 score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n = 4810). When I smell a sizzling steak or juicy piece of meat I find it very difficult to keep from eating even if I have just finished a meal. 1 = Definitely false; 2 = Mostly false; 3 = Mostly true; 4 = Definitely true (a decimal value was allowed for answers with a range); -1 = missing data; -9 = questionnaire not completed;
Categorical
Small helpings to control weight
I deliberately take small helpings as a means of controlling my weight.
Categorical
Small helpings to control weight
Phase 2 data. I deliberately take small helpings as a means of controlling my weight. 1 = Definitely true; 2 = Mostly true; 3 = Mostly false; 4 = Definitely false;
Categorical
Small helpings to control weight_rescored
New in R8. derived by re-scoring item 3FEQ_2smallhelpings score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n=4810).I deliberately take small helpings as a means of controlling my weight.
Categorical
Re-scored item 3FEQ_2smallhelpings_P2
Phase 2 data. Derived by re-scoring item 3FEQ_2smallhelpings_P2 score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n = 4810).I deliberately take small helpings as a means of controlling my weight. 1 = Definitely false; 2 = Mostly false; 3 = Mostly true; 4 = Definitely true (a decimal value was allowed for answers with a range); -1 = missing data; -9 = questionnaire not completed;
Categorical
Eat when anxious
When I feel anxious I find myself eating.
Categorical
Eating when anxious
Phase 2 data. When I feel anxious; I find myself eating. 1 = Definitely true; 2 = Mostly true; 3 = Mostly false; 4 = Definitely false;
Categorical
Eat when anxious_rescored
New in R8. derived by re-scoring item 3FEQ_3anxiousandeating score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n=4810).When I feel anxious I find myself eating.
Categorical
Re-scored item 3FEQ_3anxiousandeating_P2
Phase 2 data. Derived by re-scoring item 3FEQ_3anxiousandeating_P2 score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n = 4810).When I feel anxious I find myself eating. 1 = Definitely false; 2 = Mostly false; 3 = Mostly true; 4 = Definitely true (a decimal value was allowed for answers with a range); -1 = missing data; -9 = questionnaire not completed;
Categorical
Can't stop eating when started
Sometimes when I start eating I just can-t seem to stop.
Categorical
Cant stop eating
Phase 2 data. Sometimes when I start eating; I just can't seem to stop. 1 = Definitely true; 2 = Mostly true; 3 = Mostly false; 4 = Definitely false;
Categorical
Can't stop eating when started_rescored
New in R8. derived by re-scoring item 3FEQ_4startedeatingcantstop score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n=4810).Sometimes when I start eating I just cannot seem to stop.
Categorical
Re-scored item 3FEQ_4startedeatingcantstop_P2
Phase 2 data. Derived by re-scoring item 3FEQ_4startedeatingcantstop_P2 score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n = 4810).Sometimes when I start eating I just cannot seem to stop. 1 = Definitely false; 2 = Mostly false; 3 = Mostly true; 4 = Definitely true (a decimal value was allowed for answers with a range); -1 = missing data; -9 = questionnaire not completed;
Categorical
Hungry enough to eat when with someone who is eating
Being with someone who is eating often makes me hungry enough to eat also.
Categorical
When with someone eat more
Phase 2 data. Being with someone who is eating often makes me hungry enough to eat also. 1 = Definitely true; 2 = Mostly true; 3 = Mostly false; 4 = Definitely false;
Categorical
Hungry enough to eat when with someone who is eating_rescored
New in R8. derived by re-scoring item 3FEQ_5withsomeoneeating score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n=4810).Being with someone who is eating often makes me hungry enough to eat also.
Categorical
Re-scored item 3FEQ_5withsomeoneeating_P2
Phase 2 data. Derived by re-scoring item 3FEQ_5withsomeoneeating_P2 score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n = 4810).Being with someone who is eating often makes me hungry enough to eat also. 1 = Definitely false; 2 = Mostly false; 3 = Mostly true; 4 = Definitely true (a decimal value was allowed for answers with a range); -1 = missing data; -9 = questionnaire not completed;
Categorical
Overeat when feeling blue
When I feel blue I often overeat.
Categorical
Overeat when feeling down
Phase 2 data. When I feel blue; I often overeat. 1 = Definitely true; 2 = Mostly true; 3 = Mostly false; 4 = Definitely false;
Categorical
Overeat when feeling blue_rescored
New in R8. derived by re-scoring item 3FEQ_6blueandovereating score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n=4810).When I feel blue I often overeat.
Categorical
Re-scored item 3FEQ_6blueandovereating_P2
Phase 2 data. Derived by re-scoring item 3FEQ_6blueandovereating_P2 score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n = 4810).When I feel blue I often overeat. 1 = Definitely false; 2 = Mostly false; 3 = Mostly true; 4 = Definitely true (a decimal value was allowed for answers with a range); -1 = missing data; -9 = questionnaire not completed;
Categorical
Eat delicacy straight away
When I see a real delicacy I often get so hungry that I have to eat right away.
Categorical
Delicacy eat right away
Phase 2 data. When I see a real delicacy; I often get so hungry that I have to eat right away. 1 = Definitely true; 2 = Mostly true; 3 = Mostly false; 4 = Definitely false;
Categorical
Eat delicacy straight away_rescored
New in R8. derived by re-scoring item 3FEQ_7delicacyandeatingrightaway; score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n=4810).When I see a real delicacy I often get so hungry that I have to eat right away.
Categorical
Re-scored item 3FEQ_7delicacyandeatingrightaway_P2
Phase 2 data. Derived by re-scoring item 3FEQ_7delicacyandeatingrightaway_P2; score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n = 4810).When I see a real delicacy I often get so hungry that I have to eat right away. 1 = Definitely false; 2 = Mostly false; 3 = Mostly true; 4 = Definitely true (a decimal value was allowed for answers with a range); -1 = missing data; -9 = questionnaire not completed;
Categorical
Stomach feels like bottomless pit
I get so hungry that my stomach often seems like a bottomless pit.
Categorical
Hungry bottomless pit
Phase 2 data. I get so hungry that my stomach often seems like a bottomless pit. 1 = Definitely true; 2 = Mostly true; 3 = Mostly false; 4 = Definitely false;
Categorical
Stomach feels like bottomless pit_rescored
New in R8. derived by re-scoring item 3FEQ_8hungrybottomlesspit; score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n=4810).I get so hungry that my stomach often seems like a bottomless pit.
Categorical
Re-scored item 3FEQ_8hungrybottomlesspit_P2
Phase 2 data. Derived by re-scoring item 3FEQ_8hungrybottomlesspit_P2; score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n = 4810).I get so hungry that my stomach often seems like a bottomless pit. 1 = Definitely false; 2 = Mostly false; 3 = Mostly true; 4 = Definitely true (a decimal value was allowed for answers with a range); -1 = missing data; -9 = questionnaire not completed;
Categorical
Stop eating before finished food on plate
I am always hungry so it is hard for me to stop eating before I finish the food on my plate.
Categorical
Hunger stops finish food on plate
Phase 2 data. I am always hungry so it is hard for me to stop eating before I finish the food on my plate. 1 = Definitely true; 2 = Mostly true; 3 = Mostly false; 4 = Definitely false;
Categorical
Stop eating before finished food on plate_rescored
New in R8. derived by re-scoring item 3FEQ_9finishfoodonplate; score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n=4810).I am always hungry so it is hard for me to stop eating before I finish the food on my plate.
Categorical
Re-scored item 3FEQ_9finishfoodonplate_P2
Phase 2 data. Derived by re-scoring item 3FEQ_9finishfoodonplate_P2; score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n = 4810).I am always hungry so it is hard for me to stop eating before I finish the food on my plate. 1 = Definitely false; 2 = Mostly false; 3 = Mostly true; 4 = Definitely true (a decimal value was allowed for answers with a range); -1 = missing data; -9 = questionnaire not completed;
Categorical
Date finished to fill in e3FEQ qnr
Phase 2 data. Date the participant finished filling in the Electronic Online 3FEQ questionnaire.
Date
Date started to fill in e3FEQ qnr
Phase 2 data. Date the participant started to fill in the Electronic Online 3FEQ questionnaire.
Date
None
Phase 2 data. Data status variable to log user progress. Has the volunteer started filling in the eForm? 0 = no; 1 = yes;
Categorical
None
Phase 2 data. Data status variable to log user progress. Has the volunteer finished filling in the eForm? 0 = no; 1 = yes;
Categorical
e3FEQ questionnaire participant ID
Phase 2 data. Electronic 3FEQ questionnaire-specicifc participant ID number.
Text
e3FEQ questionnaire ID number
Phase 2 data. Electronic 3FEQ questionnaire ID number for version control.
Text
e3FEQ questionnaire ID name
Phase 2 data. Electronic 3FEQ questionnaire ID name for version control.
Text
Study phase e3FEQ questionnaire
Phase 2 data. Study phase the Electronic 3FEQ questionnaire was used for.
Text
Time finished to fill in e3FEQ qnr
Phase 2 data. Time the participant finished filling in the Electronic Online3FEQ questionnaire.
Time
Time started to fill in e3FEQ qnr
Phase 2 data. Time the participant started to fill in the Electronic Online 3FEQ questionnaire.
Time
None
Phase 2 data. Please enter your 3-digit pin (on electronic form).
Integer
e3FEQ questionnaire version date
Phase 2 data. Electronic 3FEQ questionnaire version date for version control.
Text
e3FEQ questionnaire version no
Phase 2 data. Electronic 3FEQ questionnaire version number for version control.
Integer
e3FEQ qnr web form version no
Phase 2 data. Electronic 3FEQ questionnaire web form version number for version control.
Text
Emotional eating
New in R8. raw score for Emotional Eating subscale of TFEQ-18 score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n=4810).Data derived by calculating (mean of 3FEQ_Z_Rescored items where Z=3; 6 or10)*3.
Real
Emotional eating
New in R8. Score for Emotional Eating subscale of 3FEQ_EmotionalRAW on a scale of 0-100 [(raw score - lowest possible raw score)/possible raw score range) * 100] (assessed and cleaned only in the subset n=4810).Derived by calculating ((3FEQ_EmotionalRAW-3)/9)*100.
Categorical
Score for emotional eating
Phase 2 data. Score for Emotional Eating subscale of 3FEQ_EmotionalRAW_P2 on a scale of 0-100 (raw score - lowest possible raw score)/possible raw score range) * 100 (assessed and cleaned only in the subset n = 4810).Derived by calculating ((3FEQ_EmotionalRAW-3)/9)*100. -1 = missing data; number = score; -9 = questionnaire not completed;
Categorical
Three-Factor Eating Questionnaire version
Three-Factor Eating Questionnaire version number.
Categorical
Restrained eating
New in R8. Score for Restrained Eating subscale of 3FEQ_RestraintRAW on a scale of 0-100 (assessed and cleaned only in the subset n=4810).Derived by calculating [(raw score - lowest possible raw score)/possible raw score range) * 100] ((3FEQ_RestraintRAW-6)/18)*100.
Real
Score for restrained eating
Phase 2 data. Score for Restrained Eating subscale of 3FEQ_RestraintRAW_P2 on a scale of 0-100 (assessed and cleaned only in the subset n = 4810).Derived by calculating (raw score - lowest possible raw score)/possible raw score range) * 100 ((3FEQ_RestraintRAW-6)/18)*100. -1 = missing data; -9 = questionnaire not completed;
Categorical
Restrained eating
New in R8. raw score for Restrained Eating subscale of TFEQ-18 (assessed and cleaned only in the subset n=4810).Data derived by calculating (mean of 3FEQ_X_Rescored items where X=2; 11; 12; 15; 16 or 18)*6.
Real
Uncontrolled eating
New in R8. raw score Uncontrolled Eating subscale of TFEQ-18 score of 1 as 4; 2 as 3; 3 as 2 and 4 as 1 (assessed and cleaned only in the subset n=4810).Data derived by calculating (mean of 3FEQ_Y_Rescored items where Y = 1; 4; 5; 7; 8; 9; 13; 14 or 17)*9.
Real
Uncontrolled eating
New in R8. Score for Uncontrolled Eating subscale of 3FEQ_UncontrolledRAW on a scale of 0-100 [(raw score - lowest possible raw score)/possible raw score range) * 100] (assessed and cleaned only in the subset n=4810).Derived by calculating ((3FEQ_UncontrolledRAW-9)/27)*100.
Categorical
Score for uncontrolled eating
Phase 2 data. Score for Uncontrolled Eating subscale of 3FEQ_UncontrolledRAW on a scale of 0-100 (raw score - lowest possible raw score)/possible raw score range) * 100 (assessed and cleaned only in the subset n = 4810).Derived by calculating ((3FEQ_UncontrolledRAW-9)/27)*100. -1 = missing data; number = score; -9 = questionnaire not completed;
Categorical
Visible fat
What did you do with the visible fat on your meat? After cleaning this variable is renamed as VISIBLE_FAT which is then used by the FETA program for analysis.
Categorical
Visible fat ERROR CODES CLEANED
What did you do with the visible fat on your meat? After cleaning this variable is renamed as VISIBLE_FAT which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding down to previous whole number. This question asks about the consumption of visible fat on meat (beef pork lamb etc). Variable name prior to Release 7 is A10VisibleFat_ADWN.
Categorical
Visible fat
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads What did you do with the visible fat on your meat? 1 = Ate most of the fat; 2 = Ate some of the fat; 3 = Ate as little as possible; 4 = Did not eat meat; -1 = left blank; -5 = more than one selected;
Categorical
Grilled frequency
How often did you eat grilled or roast meat? If a decimal was provided Data entry has been told to round down if it is < 0.5 or up if it is >= 0.5. Not mapped to FETA variable since not used by FETA.
Categorical
Grilled frequency ERROR CODES CLEANED
How often did you eat grilled or roast meat? If a decimal was provided Data entry has been told to round down if it is < 0.5 or up if it is >= 0.5. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up where values are >/0.5 and down if value is <0.5. Variable name prior to Release 7 is A11GrilledFreq_ANAT.
Categorical
Grilled frequency
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads How often did you eat grilled or roast meat
Categorical
Cooked
How well cooked did you usually have grilled or roast meat? Not mapped to FETA variable since not used by FETA.
Categorical
Cooked ERROR CODES CLEANED
How well cooked did you usually have grilled or roast meat? Not mapped to FETA variable since not used by FETA. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding down to previous whole number. Variable name prior to Release 7 is A12Cooked_ADWN.
Categorical
None
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads How well cooked did you usually have grilled or roast meat? 1 = Well done/dark brown; 2 = Medium; 3 = Lightly cooked/rare; 4 = Did not eat meat; -1 = left blank; -5 = more than one selected;
Categorical
Cooking salt use
How often did you add salt to food while cooking? Not mapped to FETA variable since not used by FETA.
Categorical
Cooking salt use ERROR CODES CLEANED
How often did you add salt to food while cooking? Not mapped to FETA variable since not used by FETA. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding down to previous whole number. Variable name prior to Release 7 is A13CookingSalt_ADWN.
Categorical
Cooking salt use
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads How often did you add salt to food while cooking? 1 = Always; 2 = Usually; 3 = Sometimes; 4 = Rarely; -1 = left blank; -5 = more than one selected;
Categorical
Table salt use
How often did you add salt to any food at the table? Not mapped to FETA variable since not used by FETA.
Categorical
Table salt use ERROR CODES CLEANED
How often did you add salt to any food at the table? Not mapped to FETA variable since not used by FETA. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding down to previous whole number. Variable name prior to Release 7 is A14TableSalt_ADWN.
Categorical
Table salt use
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads How often did you add salt to any food at the table? 5 = Never; -1 = left blank; -5 = more than one selected;
Categorical
Salt substitute use
Did you regularly use a salt substitute? Not mapped to FETA variable since not used by FETA.
Categorical
Salt substitute used
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Did you regularly use a salt substitute? 2 = Yes; 3 = No; -1 = left blank; -5 = more than one selected;
Categorical
Brand of salt substitute used
Did you regularly use a salt substitute? Not mapped to FETA variable since not used by FETA. If yes (regularly use salt substitute) which brand of salt substitute? Not mapped to FETA variable since not used by FETA
Text
Brand of salt subsitute
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Brand of salt substitute
Text
Supplements use
Have you taken any vitamins minerals fish oils fibre or other food supplements during the past year? Not mapped to FETA variable since not used by FETA.
Categorical
Supplements use
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Have you taken any vitamins during the past year? 2 = Yes; 3 = No; -1 = left blank; -5 = more than one selected;
Categorical
Brand of vitamin supplement 1
If yes list name and Brand of vitamin supplement 1. Not mapped to FETA variable since not used by FETA
Text
Brand of vitamin supplement 1
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Name and brand of supplements
Text
Frequency of vitamin supplement 1
If yes list Frequency of vitamin supplement 1. Not mapped to FETA variable since not used by FETA
Text
Frequency of vitamin supplement 1
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Frequency of supplements
Text
Brand of vitamin supplement 2
If yes list name and Brand of vitamin supplement 2. Not mapped to FETA variable since not used by FETA
Text
Brand of vitamin supplement 2
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Name and brand of supplements
Text
Frequency of vitamin supplement 2
If yes list Frequency of vitamin supplement 2. Not mapped to FETA variable since not used by FETA
Text
Frequency of vitamin supplement 2
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Frequency of supplements
Text
Brand of vitamin supplement 3
If yes list name and Brand of vitamin supplement 3. Not mapped to FETA variable since not used by FETA
Text
Brand of vitamin supplement 3
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Name and brand of supplements
Text
Frequency of vitamin supplement 3
If yes list Frequency of vitamin supplement 3. Not mapped to FETA variable since not used by FETA
Text
Frequency of vitamin supplement 3
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Frequency of supplements
Text
Brand of vitamin supplement 4
If yes list name and Brand of vitamin supplement 4. Not mapped to FETA variable since not used by FETA
Text
Brand of vitamin supplement 4
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Name and brand of supplements
Text
Frequency of vitamin supplement 4
If yes list Frequency of vitamin supplement 4. Not mapped to FETA variable since not used by FETA
Text
Frequency of vitamin supplement 4
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Frequency of supplements
Text
Brand of vitamin supplement 5
If yes list name and Brand of vitamin supplement 5. Not mapped to FETA variable since not used by FETA
Text
Brand of vitamin supplement 5
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Name and brand of supplements
Text
Frequency of vitamin supplement 5
If yes list Frequency of vitamin supplement 5. Not mapped to FETA variable since not used by FETA
Text
Frequency of vitamin supplement 5
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Frequency of supplements
Text
Brand of vitamin supplement 6
If yes list name and Brand of vitamin supplement 6. Not mapped to FETA variable since not used by FETA
Text
Brand of vitamin supplement 6
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Name and brand of supplements
Text
Frequency of vitamin supplement 6
If yes list Frequency of vitamin supplement 6. Not mapped to FETA variable since not used by FETA
Text
Frequency of vitamin supplement 6
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Frequency of supplements
Text
Brand of vitamin supplement 7
If yes list name and Brand of vitamin supplement 7. Not mapped to FETA variable since not used by FETA
Text
Brand of vitamin supplement 7
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Name and brand of supplements
Text
Frequency of vitamin supplement 7
If yes list Frequency of vitamin supplement 7. Not mapped to FETA variable since not used by FETA
Text
Frequency of vitamin supplement 7
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Frequency of supplements
Text
Brand of vitamin supplement 8
If yes list name and Brand of vitamin supplement 8. Not mapped to FETA variable since not used by FETA
Text
Brand of vitamin supplement 8
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Name and brand of supplements
Text
Frequency of vitamin supplement 8
If yes list Frequency of vitamin supplement 8. Not mapped to FETA variable since not used by FETA
Text
Frequency of vitamin supplement 8
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Frequency of supplements
Text
Name of other food 1 eaten more than once per week
If yes please list Name of other food 1 eaten more than once per week. Not mapped to FETA variable since not used by FETA.
Categorical
Name of other food 1 eaten more than once per week
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Text
Number of times food 1 eaten each week
If yes please list Number of times food 1 eaten each week. Not mapped to FETA variable since not used by FETA.
Categorical
Number of times food 1 eaten each week
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Categorical
Usual serving size for food 1
If yes please list Usual serving size for food 1. Not mapped to FETA variable since not used by FETA.
Categorical
Usual serving size for food 1
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Categorical
Name of other food 2 eaten
If yes please list Name of other food 2 eaten more than once per week. Not mapped to FETA variable since not used by FETA.
Categorical
Name of other food 2 eaten more than once per week
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Text
Number of times food 2 eaten each week
If yes please list Number of times food 2 eaten each week. Not mapped to FETA variable since not used by FETA.
Categorical
Number of times food 2 eaten each week
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Categorical
Usual serving size for food 2
If yes please list Usual serving size for food 2. Not mapped to FETA variable since not used by FETA.
Categorical
Usual serving size for food 2
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Categorical
Name of other food 3 eaten
If yes please list Name of other food 3 eaten more than once per week. Not mapped to FETA variable since not used by FETA.
Categorical
Name of other food 3 eaten more than once per week
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Text
Number of times food 3 eaten each week
If yes please list Number of times food 3 eaten each week. Not mapped to FETA variable since not used by FETA.
Categorical
Number of times food 3 eaten each week
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Categorical
Usual serving size for food 3
If yes please list Usual serving size for food 3. Not mapped to FETA variable since not used by FETA.
Categorical
Usual serving size for food 3
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Categorical
Name of other food 4 eaten
If yes please list Name of other food 4 eaten more than once per week. Not mapped to FETA variable since not used by FETA.
Categorical
Name of other food 4 eaten
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Text
Number of times food 4 eaten each week
If yes please list Number of times food 4 eaten each week. Not mapped to FETA variable since not used by FETA.
Categorical
Number of times food 4 eaten each week
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Categorical
Usual serving size for food 4
If yes please list Usual serving size for food 4. Not mapped to FETA variable since not used by FETA.
Categorical
Usual serving size for food 4
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Categorical
Name of other food 5 eaten
If yes please list Name of other food 5 eaten more than once per week. Not mapped to FETA variable since not used by FETA.
Categorical
Name of other food 5 eaten
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Text
Number of times food 5 eaten each week
If yes please list Number of times food 5 eaten each week. Not mapped to FETA variable since not used by FETA.
Categorical
Number of times food 5 eaten each week
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Categorical
Usual serving size for food 5
If yes please list Usual serving size for food 5. Not mapped to FETA variable since not used by FETA.
Categorical
Usual serving size for food 5
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Categorical
Name of other food 6 eaten
If yes please list Name of other food 6 eaten more than once per week. Not mapped to FETA variable since not used by FETA.
Categorical
Name of other food 6 eaten
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Text
Number of times food 6 eaten each week
If yes please list Number of times food 6 eaten each week. Not mapped to FETA variable since not used by FETA.
Categorical
Number of times food 6 eaten each week
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Categorical
Usual serving size for food 6
If yes please list Usual serving size for food 6. Not mapped to FETA variable since not used by FETA.
Categorical
Usual serving size for food 6
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Other foods eaten
Categorical
Other foods eaten >1 per week
Are there any other foods which you ate more than once a week in the last year? Not mapped to FETA variable since not used by FETA.
Categorical
Milk used
What type of milk did you most often use? Data translated manually into new variable MILK_FOOD using the milk_Lookuplist_161111. This new variable was then used by FETA.
Categorical
Other milk used
What type of milk did you most often use? - Other Milks in the last year. Data translated manually into new variable MILK_FOOD using the milk_Lookuplist_161111. This new variable was then used by FETA.
Text
Milk amount
How much milk did you drink each day including milk with tea coffee cereals etc in the last year? Data translated manually into new variable MILK_FREQUENCY which was then used by FETA.
Categorical
Milk amount
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads How much milk did you drink each day including milk with tea coffee cereals etc? 1 = None; 2 = Quarter of a pint; 3 = Half a pint; 4 = Three quarters of a pint; 5 = One pint; 6 = More than one pint; -1 = left blank; -5 = more than one selected;
Categorical
Breakfast Cereal
Did you usually eat breakfast cereal (excluding porridge and ready break mentioned earlier) in the last year? Data translated manually into new variable CEREAL_FOOD using the cereal_Lookuplist_130812. This new variable was then used by FETA.
Categorical
Brand breakfast cereal 1
If yes which type of breakfast cereal inclusing muesli did you usually eat? Brand of breakfast cereal 1. Data translated manually into new variable CEREAL_FOOD using the cereal_Lookuplist_130812. This new variable was then used by FETA.
Text
Brand breakfast cereal 1
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Brand of breakfast cereal.
Text
Type breakfast cereal 1
If yes which type of breakfast cereal inclusing muesli did you usually eat? Type of breakfast cereal 1. Data translated manually into new variable CEREAL_FOOD using the cereal_Lookuplist_130812. This new variable was then used by FETA.
Text
Type breakfast cereal 1
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Type of breakfast cereal.
Text
Brand breakfast cereal 2
If yes which type of breakfast cereal inclusing muesli did you usually eat? Brand of breakfast cereal 2. Data translated manually into new variable CEREAL_FOOD using the cereal_Lookuplist_130812. This new variable was then used by FETA.
Text
Brand breakfast cereal 2
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Brand of breakfast cereal.
Text
Type breakfast cereal 2
If yes which type of breakfast cereal inclusing muesli did you usually eat? Type of breakfast cereal 2. Data translated manually into new variable CEREAL_FOOD using the cereal_Lookuplist_130812. This new variable was then used by FETA.
Text
Type breakfast cereal 2
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Type of breakfast cereal.
Text
Fat used for frying
What kind of fat did you most often use for frying roasting grilling etc in the last year? Select one only. Data translated manually into new variable FAT_FRYING_FOOD using the fats_Lookuplist_161111. This new variable was then used by FETA.
Categorical
Fat used for frying
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads What kind of fat did you most often use for frying roasting grilling etc
Categorical
Other frying fat
If you used vegetable oil please give type eg. Corn sunflower. Data translated manually into new variable FAT_FRYING_FOOD using the fats_Lookuplist_161111. This new variable was then used by FETA.
Text
Other frying fat
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads If you used vegetable oil please give type eg. corn sun?ower
Text
Fat used for baking
What kind of fat did you most often use for baking cakes etc? select one only. Data translated manually into new variable FAT_BAKING_FOOD using the fats_Lookuplist_161111. This new variable was then used by FETA.
Categorical
Fat used for baking
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads What kind of fat did you most often use for baking cakes etc
Categorical
Other baking fat
If you used margarine please give name or type eg Flora Stork. Data translated manually into new variable FAT_BAKING_FOOD using the fats_Lookuplist_161111. This new variable was then used by FETA.
Text
Other baking fat
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads If you used vegetable oil please give type eg. corn sun?ower
Text
Eat home fried food
How often did you eat food that was fried at home? Not mapped to FETA variable since not used by FETA.
Categorical
Eat home fried food ERROR CODES CLEANED
How often did you eat food that was fried at home? Not mapped to FETA variable since not used by FETA. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding down to previous whole number. Variable name for release prior to Release 7 is A8HomeFried_ADWN.
Categorical
Eat home fried food
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads How often did you eat food that was fried at home
Categorical
Eat away fried food
How often did you eat fried food away from home? Not mapped to FETA variable since not used by FETA.
Categorical
Eat away fried food ERROR CODES CLEANED
How often did you eat fried food away from home? Not mapped to FETA variable since not used by FETA. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding down to previous whole number. Variable name for release prior to Release 7 is A9AwayFried_ADWN.
Categorical
Eat away fried food
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads How often did you eat food that was fried at home
Categorical
OLINK assay AARSD1
Phase 1 OLINK assay data for target AARSD1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ABHD14B
Phase 1 OLINK assay data for target ABHD14B in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ABL1
Phase 1 OLINK assay data for target ABL1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ACAN
Phase 1 OLINK assay data for target ACAN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
General cmnts wrist acc day1
Phase 2 data. General comments (wrist accelerometer) on day 1 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -2 = no data entered AND wrist acc column header crossed through; -8 = text illegible
Text
General cmnts wrist acc day2
Phase 2 data. General comments (wrist accelerometer) on day 2 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -2 = no data entered AND wrist acc column header crossed through; -8 = text illegible
Text
General cmnts wrist acc day3
Phase 2 data. General comments (wrist accelerometer) on day 3 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -2 = no data entered AND wrist acc column header crossed through; -8 = text illegible
Text
General cmnts wrist acc day4
Phase 2 data. General comments (wrist accelerometer) on day 4 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -2 = no data entered AND wrist acc column header crossed through; -8 = text illegible
Text
General cmnts wrist acc day5
Phase 2 data. General comments (wrist accelerometer) on day 5 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -2 = no data entered AND wrist acc column header crossed through; -8 = text illegible
Text
General cmnts wrist acc day6
Phase 2 data. General comments (wrist accelerometer) on day 6 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -2 = no data entered AND wrist acc column header crossed through; -8 = text illegible
Text
General cmnts wrist acc day7
Phase 2 data. General comments (wrist accelerometer) on day 7 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -2 = no data entered AND wrist acc column header crossed through; -8 = text illegible
Text
Reason take off wrist acc day1
Phase 2 data. Reason for taking off (wrist accelerometer) on day 1 of wearing Actiheart and wrist accelerometer; example provided on form is CHANGE ELECTRODES. -1 = left blank or crossed through; -8 = text illegible
Text
Reason take off wrist acc day2
Phase 2 data. Reason for taking off (wrist accelerometer) on day 2 of wearing Actiheart and wrist accelerometer; example provided on form is CHANGE ELECTRODES. -1 = left blank or crossed through; -8 = text illegible
Text
Reason take off wrist acc day3
Phase 2 data. Reason for taking off (wrist accelerometer) on day 3 of wearing Actiheart and wrist accelerometer; example provided on form is CHANGE ELECTRODES. -1 = left blank or crossed through; -8 = text illegible
Text
Reason take off wrist acc day4
Phase 2 data. Reason for taking off (wrist accelerometer) on day 4 of wearing Actiheart and wrist accelerometer; example provided on form is CHANGE ELECTRODES. -1 = left blank or crossed through; -8 = text illegible
Text
Reason take off wrist acc day5
Phase 2 data. Reason for taking off (wrist accelerometer) on day 5 of wearing Actiheart and wrist accelerometer; example provided on form is CHANGE ELECTRODES. -1 = left blank or crossed through; -8 = text illegible
Text
Reason take off wrist acc day6
Phase 2 data. Reason for taking off (wrist accelerometer) on day 6 of wearing Actiheart and wrist accelerometer; example provided on form is CHANGE ELECTRODES. -1 = left blank or crossed through; -8 = text illegible
Text
Reason take off wrist acc day7
Phase 2 data. Reason for taking off (wrist accelerometer) on day 7 of wearing Actiheart and wrist accelerometer; example provided on form is CHANGE ELECTRODES. -1 = left blank or crossed through; -8 = text illegible
Text
Time wrist acc taken off day1
Phase 2 data. What time did you take off the wrist accelerometer on day 1 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time wrist acc taken off day2
Phase 2 data. What time did you take off the wrist accelerometer on day 2 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time wrist acc taken off day3
Phase 2 data. What time did you take off the wrist accelerometer on day 3 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time wrist acc taken off day4
Phase 2 data. What time did you take off the wrist accelerometer on day 4 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time wrist acc taken off day5
Phase 2 data. What time did you take off the wrist accelerometer on day 5 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time wrist acc taken off day6
Phase 2 data. What time did you take off the wrist accelerometer on day 6 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time wrist acc taken off day7
Phase 2 data. What time did you take off the wrist accelerometer on day 7 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Final date Wrist monitor taken off
Phase 2 data. Date of Final time taken off wrist accelerometer monitor dd/mm/yyyy. -1 = left blank or crossed through; -8 = text illegible
Date
Final time Wrist monitor taken off
Phase 2 data. Date of Final time taken off wrist accelerometer monitor (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Date
Time wrist acc put back on day1
Phase 2 data. What time did you put the wrist accelerometer back on on day 1 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time wrist acc put back on day2
Phase 2 data. What time did you put the wrist accelerometer back on on day 2 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time wrist acc put back on day3
Phase 2 data. What time did you put the wrist accelerometer back on on day 3 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time wrist acc put back on day4
Phase 2 data. What time did you put the wrist accelerometer back on on day 4 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time wrist acc put back on day5
Phase 2 data. What time did you put the wrist accelerometer back on on day 5 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time wrist acc put back on day6
Phase 2 data. What time did you put the wrist accelerometer back on on day 6 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time wrist acc put back on day7
Phase 2 data. What time did you put the wrist accelerometer back on on day 7 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
OLINK assay ACE2
Phase 1 OLINK assay data for target ACE2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
ace_inhibitor
Phase 2 data. Binary variable indicating whether a drug from the ace inhibitor class was prescribed. 0: No 1: Yes
Categorical
AcOrn_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable AcOrn_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. 2nd and final QC step on this var created new and final var BIOA_023.
Real
OLINK assay ACP6
Phase 1 OLINK assay data for target ACP6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Cln variable: Active comp games hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Active computer games. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Active computer games hrs
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in hours) you spent doing the activity per episode. Active computer games. -1 = left blank. DO NOT USE THIS VARIABLE. Use ActiveComputerHr_CLEAN_P2 instead.
Real
Cln variable: Active comp games min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Active computer games. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Active computer games min
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Active computer games. -1 = left blank. DO NOT USE THIS VARIABLE. Use ActiveComputerMin_CLEAN_P2 instead.
Real
Cln variable: Active computer games
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Active computer games. Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed;
Categorical
Active computer games
Phase 2 data. Questionnaire reads D14. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Active computer games. PAPER FORMS ONLY: Data entered using data entry template with 1-3-4-5-6-7-8 codes. 1 = none; 3 = once in last 4 wks; 4 = 2-3 times in last 4 wks; 5 = once a week; 6 = 2-3 times a wk; 7 = 4-5 times a week; 8 = every day; -1 = left blank; -5 = more than 1 selected; ELECTRONIC FORMS: 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; DO NOT USE THIS VARIABLE. Use ActiveComputer_CLEAN_P2 instead.
Real
Active computer games
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Active computer games. Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
ActivPALPosition
Position on body where ActivPAL was placed to perform the measurement
Text
ACTMETS
Total activity energy expenditure discounting resting [net METhrs/d]
Real
Total AEE discounting resting
Phase 2 data. Derived with method 2. Total activity energy expenditure discounting resting net METhrs/d
Real
ACTMETS_w_UNACCtime
Activity EE incl AEE for unaccounted time for active getting about [net METhrs/d]
Real
ACTMETS inc of unaccounted hrs
Phase 2 data. Derived with method 2. Activity EE inc AEE for unaccounted time for active getting about net METhrs/d
Real
Cln variable: Other activity 1 hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Other activity 1. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Other activity 1 hrs
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in hours) you spent doing the activity per episode. Other activity 1. -1 = left blank. DO NOT USE THIS VARIABLE. Use Act_Other1Hr_CLEAN_P2 instead.
Real
Cln variable: Other activity 1 min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Other activity 1. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Other activity 1 min
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Other activity 1. -1 = left blank. DO NOT USE THIS VARIABLE. Use Act_Other1Min_CLEAN_P2 instead.
Real
Name of other acitivity
Phase 2 data. Name of Other activity 1. -1 = left blank;
Text
Cln variable: Other activity 1
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Other activity 1 (with no similarity to any listed). Error codes cleaned by DMT; -10 error codes cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank;
Categorical
Other activity 1
Phase 2 data. Questionnaire reads D14. You should try and classify all the activities you do in the list above. If however you do activities which have no similarity with any of those listed above please mention here. Other activity 1. PAPER FORMS ONLY: Data entered using data entry template with 1-3-4-5-6-7-8 codes. 1 = none; 3 = once in last 4 wks; 4 = 2-3 times in last 4 wks; 5 = once a week; 6 = 2-3 times a wk; 7 = 4-5 times a week; 8 = every day; -1 = left blank; -5 = more than 1 selected; ELECTRONIC FORMS: 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; DO NOT USE THIS VARIABLE. Use Act_Other1_CLEAN_P2 instead.
Categorical
Other activity 1
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Other activity 1 (with no similarity to any listed). Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Cln variable: Other activity 2 hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Other activity 2. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Other activity 2 hrs
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in hours) you spent doing the activity per episode. Other activity 2. -1 = left blank. DO NOT USE THIS VARIABLE. Use Act_Other2Hr_CLEAN_P2 instead.
Real
Cln variable: Other activity 2 min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Other activity 2. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Other activity 2 min
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Other activity 2. -1 = left blank. DO NOT USE THIS VARIABLE. Use Act_Other2Min_CLEAN_P2 instead.
Real
Name of other acitivity
Phase 2 data. Name of Other activity 2. -1 = left blank;
Text
Cln variable: Other activity 2
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Other activity 1 (with no similarity to any listed). Error codes cleaned by DMT; -10 error codes cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank;
Categorical
Other activity 2
Phase 2 data. Questionnaire reads D14. You should try and classify all the activities you do in the list above. If however you do activities which have no similarity with any of those listed above please mention here. Other activity 2. PAPER FORMS ONLY: Data entered using data entry template with 1-3-4-5-6-7-8 codes. 1 = none; 3 = once in last 4 wks; 4 = 2-3 times in last 4 wks; 5 = once a week; 6 = 2-3 times a wk; 7 = 4-5 times a week; 8 = every day; -1 = left blank; -5 = more than 1 selected; ELECTRONIC FORMS: 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; DO NOT USE THIS VARIABLE. Use Act_Other2_CLEAN_P2 instead.
Categorical
Other activity 2
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Other activity 2 (with no similarity to any listed). Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Other Sports
Phase 2 data. Asked on electronic form only. Hence where left blank data could still exist for Act_Other1Text_P2 and Act_Other2Text_P2 as it has come from the paper questionnaire. 1 = yes; 2 = no; blank or = data not collected so instead use Act_Other1Text_P2 and Act_Other2Text_P2;
Categorical
Date of scan
Date of test/scan
Date
DEXA operator
DEXA operator. Entered by operator before DEXA scan
Categorical
Overall total bone mineral content in grams
New in R7. Overall total bone mass (bone mineral content) in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Indirectly with sum of mass. Total mass.
Real
Overall total bone mineral content
Phase 2 data. Overall total bone mass (bone mineral content) in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Overall total bone mineral content in grams
Overall total bone mass (bone mineral content) in grams. Raw data from DEXA Lunar Prodigy.
Real
Overall total bone mineral content
Phase 2 data. Overall total bone mass (bone mineral content) in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD04i_iDEXA_Total_bone_mass_P2); -9 = Missing data;
Real
Overall total tissue fat mass in grams
New in R7. Overall total fat mass (tissue fat mass) in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Indirectly with sum of mass. Total mass.
Real
Overall total tissue fat mass
Phase 2 data. Overall total fat mass (tissue fat mass) in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Overall total tissue fat mass in grams
Overall total fat mass(tissue fat mass) in grams. Raw data from DEXA Lunar Prodigy.
Real
Overall total tissue fat mass
Phase 2 data. Overall total fat mass(tissue fat mass) in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD05i_iDEXA_Total_fat_mass_P2AD05i_iDEXA_Total_fat_mass_P2); -9 = Missing data;
Real
Overall total tissue lean mass in grams
New in R7. Overall total lean mass (tissue lean mass) in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Indirectly with sum of mass. Total mass.
Real
Overall total tissue lean mass
Phase 2 data. Overall total lean mass (tissue lean mass) in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Overall total tissue lean mass in grams
Overall total lean mass(tissue lean mass) in grams. Raw data from DEXA Lunar Prodigy.
Real
Overall total tissue lean mass
Phase 2 data. Overall total lean mass (tissue lean mass) in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD06i_iDEXA_Total_lean_mass_P2); -9 = Missing data;
Real
Overall left bone mineral content in grams
New in R7. Overall left bone mineral content in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Indirectly with sum of mass. Total mass.
Real
Overall left bone mineral content
Phase 2 data. Overall left bone mineral content in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Overall left bone mineral content in grams
Overall left bone mineral content in grams. Raw data from DEXA Lunar Prodigy.
Real
Overall left bone mineral content
Phase 2 data. Overall left bone mineral content in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD07i_iDEXA_Left_total_bone_mass_P2); -9 = Missing data;
Real
Overall left tissue fat mass in grams
New in R7. Overall left tissue fat mass in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Indirectly with sum of mass. Total mass.
Real
Overall left tissue fat mass
Phase 2 data. Overall left tissue fat mass in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Overall left tissue fat mass in grams
Overall left tissue fat mass in grams. Raw data from DEXA Lunar Prodigy.
Real
Overall left tissue fat mass
Phase 2 data. Overall left tissue fat mass in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD08i_iDEXA_Left_total_fat_mass_P2); -9 = Missing data;
Real
Overall left tissue lean mass in grams
New in R7. Overall left tissue lean mass in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Indirectly with sum of mass. Total mass.
Real
Overall left tissue lean mass
Phase 2 data. Overall left tissue lean mass in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Overall left tissue lean mass in grams
Overall left tissue lean mass in grams. Raw data from DEXA Lunar Prodigy.
Real
Overall left tissue lean mass
Phase 2 data. Overall left tissue lean mass in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD09i_iDEXA_Left_total_lean_mass_P2); -9 = Missing data;
Real
Overall right bone mineral content in grams
New in R7. Overall right bone mineral content in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Overall right bone mineral content
Phase 2 data. Overall right bone mineral content in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Overall right bone mineral content in grams
Overall right bone mineral content in grams. Raw data from DEXA Lunar Prodigy
Real
Overall right bone mineral content
Phase 2 data. Overall right bone mineral content in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD10i_iDEXA_Right_total_bone_mass_P2); -9 = Missing data;
Real
Overall right tissue fat mass in grams
New in R7. Overall right tissue fat mass in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Overall right tissue fat mass
Phase 2 data. Overall right tissue fat mass in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Overall right tissue fat mass in grams
Overall right tissue fat mass in grams. Raw data from DEXA Lunar Prodigy.
Real
Overall right tissue fat mass
Phase 2 data. Overall right tissue fat mass in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD11i_iDEXA_Right_total_fat_mass_P2); -9 = Missing data;
Real
Overall right tissue lean mass in grams
New in R7. Overall right tissue lean mass in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Overall right tissue lean mass
Phase 2 data. Overall right tissue lean mass in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Overall right tissue lean mass in grams
Overall right tissue lean mass in grams. Raw data from DEXA Lunar Prodigy.
Real
Overall right tissue lean mass
Phase 2 data. Overall right tissue lean mass in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD12i_iDEXA_Right_total_lean_mass_P2); -9 = Missing data;
Real
Total bone mineral content of two arms in grams
New in R7. Total bone mineral content of two arms in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Indirectly with sum of mass. Total mass.
Real
Total bone mineral content of 2 arms
Phase 2 data. Total bone mineral content of two arms in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Total bone mineral content of two arms in grams
Total bone mineral content of two arms in grams. Raw data from DEXA Lunar Prodigy.
Real
Total bone mineral content of 2arms
Phase 2 data. Total bone mineral content of two arms in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD13i_iDEXA_arms_bone_mass_P2); -9 = Missing data;
Real
Total tissue fat mass of two arms in grams
New in R7. Total tissue fat mass of two arms in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Indirectly with sum of mass. Total mass.
Real
Total tissue fat mass of 2 arms
Phase 2 data. Total tissue fat mass of two arms in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Total tissue fat mass of two arms in grams
Total tissue fat mass of two arms in grams. Raw data from DEXA Lunar Prodigy.
Real
Total tissue fat mass of two arms
Phase 2 data. Total tissue fat mass of two arms in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD14i_iDEXA_arms_fat_mass_P2); -9 = Missing data;
Real
Total tissue lean mass of two arms in grams
New in R7. Total tissue lean mass of two arms in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Indirectly with sum of mass. Total mass.
Real
Total tissue lean mass of 2 arms
Phase 2 data. Total tissue lean mass of two arms in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Total tissue lean mass of two arms in grams
Total tissue lean mass of two arms in grams. Raw data from DEXA Lunar Prodigy.
Real
Total tissue lean mass of two arms
Phase 2 data. Total tissue lean mass of two arms in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD15i_iDEXA_arms_lean_mass_P2); -9 = Missing data;
Real
Bone mineral content in left arm in grams
New in R7. Bone mineral content in left arm in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Indirectly with sum of mass. Total mass.
Real
Bone mineral content in left arm
Phase 2 data. Bone mineral content in left arm in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Bone mineral content in left arm in grams
Bone mineral content in left arm in grams. Raw data from DEXA Lunar Prodigy.
Real
Bone mineral content in left arm
Phase 2 data. Bone mineral content in left arm in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD16i_iDEXA_Left_arm_bone_mass_P2); -9 = Missing data;
Real
Tissue fat mass in left arm in grams
New in R7. Tissue fat mass in left arm in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Indirectly with sum of mass. Total mass.
Real
Tissue fat mass in left arm
Phase 2 data. Tissue fat mass in left arm in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue fat mass in left arm in grams
tissue fat mass in left arm in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue fat mass in left arm
Phase 2 data. tissue fat mass in left arm in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD17i_iDEXA_Left_arm_fat_mass_P2); -9 = Missing data;
Real
Tissue lean mass in left arm in grams
New in R7. Tissue lean mass in left arm in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Indirectly with sum of mass. Total mass.
Real
Tissue lean mass in left arm
Phase 2 data. Tissue lean mass in left arm in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue lean mass in left arm in grams
tissue lean mass in left arm in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue lean mass in left arm
Phase 2 data. tissue lean mass in left arm in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD18i_iDEXA_Left_arm_lean_mass_P2); -9 = Missing data;
Real
Bone mineral content in right arm in grams
New in R7. Bone mineral content in right arm in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Bone mineral content in right arm
Phase 2 data. Bone mineral content in right arm in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Bone mineral content in right arm in grams
bone mineral content in right arm in grams. Raw data from DEXA Lunar Prodigy.
Real
Bone mineral content in right arm
Phase 2 data. bone mineral content in right arm in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD19i_iDEXA_Right_arm_bone_mass_P2); -9 = Missing data;
Real
Tissue fat mass in right arm in grams
New in R7. Tissue fat mass in right arm in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue fat mass in right arm
Phase 2 data. Tissue fat mass in right arm in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue fat mass in right arm in grams
tissue fat mass in right arm in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue fat mass in right arm
Phase 2 data. tissue fat mass in right arm in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD20i_iDEXA_Right_arm_fat_mass_P2); -9 = Missing data;
Real
Tissue lean mass in right arm in grams
New in R7. Tissue lean mass in right arm in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue lean mass in right arm
Phase 2 data. Tissue lean mass in right arm in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue lean mass in right arm in grams
tissue lean mass in right arm in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue lean mass in right arm
Phase 2 data. tissue lean mass in right arm in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD21i_iDEXA_Right_arm_lean_mass_P2); -9 = Missing data;
Real
Bone mineral content of trunk torso & pelvis in grams
New in R7. Bone mineral content of trunk (torso & pelvis) in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Bone mineral content trunk torso pelvis
Phase 2 data. Bone mineral content of trunk (torso and pelvis) in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Bone mineral content of trunk in grams
Bone mineral content of trunk in grams. Raw data from DEXA Lunar Prodigy.
Real
Bone mineral content of trunk
Phase 2 data. Bone mineral content of trunk in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD22i_iDEXA_Trunk_bone_mass_P2); -9 = Missing data;
Real
Tissue fat mass of trunk torso & pelvis in grams
New in R7. Tissue fat mass of trunk (torso & pelvis) in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue fat mass trunk torso pelvis
Phase 2 data. Tissue fat mass of trunk (torso and pelvis) in grams for Phase 2 data. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue fat mass of trunk
Tissue fat mass of trunk in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue fat mass of trunk
Phase 2 data. Tissue fat mass of trunk in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD23i_iDEXA_Trunk_fat_mass_P2); -9 = Missing data;
Real
Tissue lean mass of trunk torso & pelvis in grams
New in R7. Tissue lean mass of trunk (torso & pelvis) in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue lean mass trunk torso pelvis
Phase 2 data. Tissue lean mass of trunk (torso and pelvis) in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue lean mass of trunk
Tissue lean mass of trunk in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue lean mass of trunk
Phase 2 data. Tissue lean mass of trunk in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD24i_iDEXA_Trunk_lean_mass_P2); -9 = Missing data;
Real
Bone mineral content of left trunk in grams
New in R7. Bone mineral content of left trunk in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Bone mineral content left trunk
Phase 2 data. Bone mineral content of left trunk in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Bone mineral content of left trunk
bone mineral content of left trunk in grams. Raw data from DEXA Lunar Prodigy.
Real
Bone mineral content of left trunk
Phase 2 data. bone mineral content of left trunk in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD25i_iDEXA_Left_trunk_bone_mass_P2); -9 = Missing data;
Real
Tissue fat mass of left trunk in grams
New in R7. Tissue fat mass of left trunk in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue fat mass left trunk
Phase 2 data. Tissue fat mass of left trunk in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue fat mass of left trunk
Tissue fat mass of left trunk in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue fat mass of left trunk
Phase 2 data. Tissue fat mass of left trunk in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD26i_iDEXA_Left_trunk_fat_mass_P2); -9 = Missing data;
Real
Tissue lean mass of left trunk in grams
New in R7. Tissue lean mass of left trunk in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue lean mass of left trunk
Phase 2 data. Tissue lean mass of left trunk in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue lean mass of left trunk
Tissue lean mass of left trunk in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue lean mass of left trunk
Phase 2 data. Tissue lean mass of left trunk in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD27i_iDEXA_Left_trunk_lean_mass_P2); -9 = Missing data;
Real
Bone mineral content of right trunk in grams
New in R7. Bone mineral content of right trunk in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Bone mineral content right trunk
Phase 2 data. Bone mineral content of right trunk in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Bone mineral content of right trunk
Bone mineral content of right trunk in grams. Raw data from DEXA Lunar Prodigy.
Real
Bone mineral content of right trunk
Phase 2 data. Bone mineral content of right trunk in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD28i_iDEXA_Right_trunk_bone_mass_P2); -9 = Missing data;
Real
Tissue fat mass of right trunk in grams
New in R7. Tissue fat mass of right trunk in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue fat mass of right trunk
Phase 2 data. Tissue fat mass of right trunk in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue fat mass of right trunk
Tissue fat mass of right trunk in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue fat mass of right trunk
Phase 2 data. Tissue fat mass of right trunk in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD29i_iDEXA_Right_trunk_fat_mass_P2); -9 = Missing data;
Real
Tissue lean mass of right trunk in grams
New in R7. Tissue lean mass of right trunk in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue lean mass of right trunk
Phase 2 data. Tissue lean mass of right trunk in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue lean mass of right trunk
Tissue lean mass of right trunk in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue lean mass of right trunk
Phase 2 data. Tissue lean mass of right trunk in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD30i_iDEXA_Right_trunk_lean_mass_P2); -9 = Missing data;
Real
Bone mineral content of android waist area in grams
New in R7. Bone mineral content of android (waist area) in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Bone mineral content android waist area
Phase 2 data. Bone mineral content of android (waist area) in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Bone mineral content of android area
Bone mineral content of android(waist area) in grams. Raw data from DEXA Lunar Prodigy.
Real
Bone mineral content android area
Phase 2 data. Bone mineral content of android(waist area) in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD31i_iDEXA_Android_bone_mass_P2); -9 = Missing data;
Real
Tissue fat mass of android waist area in grams
New in R7. tissue fat mass of android (waist area) in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue fat mass android waist area
Phase 2 data. tissue fat mass of android (waist area) in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Bone mineral mass of android area
bone mineral mass of android(waist area) in grams. Raw data from DEXA Lunar Prodigy.
Real
Bone mineral mass of android area
Phase 2 data. bone mineral mass of android(waist area) in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD32i_iDEXA_Android_fat_mass_P2); -9 = Missing data;
Real
Tissue lean mass of android waist area in grams
New in R7. Tissue lean mass of android (waist area) in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue lean mass android waist area
Phase 2 data. Tissue lean mass of android (waist area) in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue lean mass of android area
tissue lean mass of android(waist area) in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue lean mass of android area
Phase 2 data. tissue lean mass of android(waist area) in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD33i_iDEXA_Android_lean_mass_P2); -9 = Missing data;
Real
Bone mineral content of gynoid Hip area in grams
New in R7. Bone mineral content of gynoid (Hip area) in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Bone mineral content gynoid Hip area
Phase 2 data. Bone mineral content of gynoid (Hip area) in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Bone mineral content of gynoid area
Bone mineral content of gynoid(Hip area) in grams. Raw data from DEXA Lunar Prodigy.
Real
Bone mineral content of gynoid area
Phase 2 data. Bone mineral content of gynoid(Hip area) in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD34i_iDEXA_Gynoid_bone_mass_P2); -9 = Missing data;
Real
Tissue fat mass of gynoid Hip area in grams
New in R7. tissue fat mass of gynoid (Hip area) in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue fat mass of gynoid Hip area
Phase 2 data. tissue fat mass of gynoid (Hip area) in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue fat mass of gynoid area
Tissue fat mass of gynoid (Hip area) in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue fat mass of gynoid area
Phase 2 data. Tissue fat mass of gynoid (Hip area) in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD35i_iDEXA_Gynoid_fat_mass_P2); -9 = Missing data;
Real
Tissue lean mass of gynoid Hip area in grams
New in R7. Tissue lean mass of gynoid (Hip area) in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue lean mass of gynoid Hip area
Phase 2 data. Tissue lean mass of gynoid (Hip area) in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue lean mass of gynoid area
Tissue lean mass of gynoid(Hip area) in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue lean mass of gynoid area
Phase 2 data. Tissue lean mass of gynoid(Hip area) in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD36i_iDEXA_Gynoid_lean_mass_P2); -9 = Missing data;
Real
Bone mineral content of two legs in grams
New in R7. Bone mineral content of two legs in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Bone mineral content of two legs
Phase 2 data. Bone mineral content of two legs in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Bone mineral content of two legs
Bone mineral content of two legs in grams. Raw data from DEXA Lunar Prodigy.
Real
Bone mineral content of two legs
Phase 2 data. Bone mineral content of two legs in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD37i_iDEXA_legs_bone_mass_P2); -9 = Missing data;
Real
Tissue fat mass of two legs in grams
New in R7. Tissue fat mass of two legs in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue fat mass of two legs
Phase 2 data. Tissue fat mass of two legs in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue fat mass of two legs
Tissue fat mass of two legs in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue fat mass of two legs
Phase 2 data. Tissue fat mass of two legs in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD38i_iDEXA_legs_fat_mass_P2); -9 = Missing data;
Real
Tissue lean mass of two legs in grams
New in R7. Tissue lean mass of two legs in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue lean mass of two legs
Phase 2 data. Tissue lean mass of two legs in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue lean mass of two legs
Tissue lean mass of two legs in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue lean mass of two legs
Phase 2 data. Tissue lean mass of two legs in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD39i_iDEXA_legs_lean_mass_P2); -9 = Missing data;
Real
Bone mineral content left leg in grams
New in R7. Bone mineral content left leg in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Bone mineral content left leg
Phase 2 data. Bone mineral content left leg in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Bone mineral content left leg
Bone mineral content left leg in grams. Raw data from DEXA Lunar Prodigy.
Real
Bone mineral content left leg
Phase 2 data. Bone mineral content left leg in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD40i_iDEXA_Left_leg_bone_mass_P2); -9 = Missing data;
Real
Tissue fat mass of left leg in grams
New in R7. Tissue fat mass of left leg in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue fat mass of left leg
Phase 2 data. Tissue fat mass of left leg in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue fat mass of left leg
Tissue fat mass of left leg in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue fat mass of left leg
Phase 2 data. Tissue fat mass of left leg in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD41i_iDEXA_Left_leg_fat_mass_P2); -9 = Missing data;
Real
Tissue lean mass of left leg in grams
New in R7. Tissue lean mass of left leg in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue lean mass of left leg
Phase 2 data. Tissue lean mass of left leg in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue lean mass of left leg in grams
Tissue lean mass of left leg in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue lean mass of left leg
Phase 2 data. Tissue lean mass of left leg in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD42i_iDEXA_Left_leg_lean_mass_P2); -9 = Missing data;
Real
Bone mineral content right leg in grams
New in R7. Bone mineral content right leg in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Bone mineral content right leg
Phase 2 data. Bone mineral content right leg in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Bone mineral content right leg in grams
Bone mineral content right leg in grams. Raw data from DEXA Lunar Prodigy.
Real
Bone mineral content right leg
Phase 2 data. Bone mineral content right leg in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD43i_iDEXA_Right_leg_bone_mass_P2); -9 = Missing data;
Real
Tissue fat mass of right leg in grams
New in R7. Tissue fat mass of right leg in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue fat mass of right leg
Phase 2 data. Tissue fat mass of right leg in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue fat mass of right leg in grams
Tissue fat mass of right leg in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue fat mass of right leg
Phase 2 data. Tissue fat mass of right leg in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD44i_iDEXA_Right_leg_fat_mass_P2); -9 = Missing data;
Real
Tissue lean mass of right leg in grams
New in R7. Tissue lean mass of right leg in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software.
Real
Tissue lean mass of right leg
Phase 2 data. Tissue lean mass of right leg in grams. Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Tissue lean mass of right leg in grams
Tissue lean mass of right leg in grams. Raw data from DEXA Lunar Prodigy.
Real
Tissue lean mass of right leg
Phase 2 data. Tissue lean mass of right leg in grams. Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD45i_iDEXA_Right_leg_lean_mass_P2); -9 = Missing data;
Real
Total mass in kilograms
Regenerated mass (fat mass(grams) + fat free mass(grams) + bone mineral mass(grams))/1000.
Real
Percent overall body fat from DEXA
New in R7. Percent overall body fat from DEXA. Regenerated percentage body fat (overall fat) using a 3 compartment model (fat mass; fat free mass; bone mineral mass). Calculated as (100* fat mass / (total mass * 1000). Calculation and or check: % of total fat mass from total mass. Comparison with study support data.
Real
Percent overall body fat from DEXA
Phase 2 data. Percent overall body fat from DEXA. Regenerated percentage body fat (overall fat) using a 3 compartment model (fat mass; fat free; mass bone mineral mass). Calculated as (100* fat mass / (total mass * 1000). Raw data from DEXA Lunar Prodigy processed with enhanced analysis. -9 = Missing data;
Real
Body fat percent DEXA
Regenerated percentage body fat (overall fat) using a 3 compartment model (fat mass; fat free mass; bone mineral mass). Calculated as (100* fat mass / (total mass * 1000).
Real
Body fat percent DEXA
Phase 2 data. Regenerated percentage body fat (overall fat) using a 3 compartment model (fat mass; fat free mass; bone mineral mass). Calculated as (100* fat mass / (total mass * 1000). Raw data from DEXA Lunar Prodigy processed with basic analysis. DO NOT USE THIS VARIABLE. Use iDEXA equivalent instead (AD47i_iDEXA_body_fat_percent_P2); -9 = Missing data;
Real
Which symmetry method was applied
New in R7. If symmetry method was applied it is indicated whether it was left or right. Where symmetry method was used arm was omitted from scan as volunteer was too broad for the scanner. Therefore the values of the arm within the scanner was used to recalculate overall Body composition. Calculation and or check: Identified by Fenland_Symmetry_Calculations.xls and iDEXA estimate.
Text
Symmetry method applied
Phase 2 data. If symmetry method was applied it is indicated whether it was left or right. Where symmetry method was used arm was omitted from scan as volunteer was too broad for the scanner. Therefore the values of the arm within the scanner was used to recalculate overall Body composition. Calculation and or check: Identified by Fenland_Symmetry_Calculations.xls and iDEXA estimate.
Text
Was symmetry method applied
Was symmetry method used yes or no. Where symmetry method was used arm was omitted from scan as volunteer was too broad for the scanner. Therefore the values of the arm within the scanner was used to recalculate overall Body Composition.
Categorical
DEXA comments
Comments for when there are artefacts or missing tissue from the scanning area. Do not analyse any DEXA data without reviewing these comments. Please also request variable AD58i_iDEXA_Comments.
Text
Categories of DEXA scan
Background data information code generated by Anthropometry team (scans without code should be considered to have followed standard protocol). Request with AD50_DEXA_Coding for further clarification.
Categorical
Visceral Adipose Tissue within the Android region in cm3
New in R7. Visceral Adipose Tissue (VAT) within the Android region in cm3. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. The iDEXA algorithm did not work in volunteers who were too broad or had too little fat around the abdomen so it produced an output of 0. These were changed to -7 afterwards by the Data Man team.
Real
VAT within Android region in cm3
Phase 2 data. Visceral Adipose Tissue (VAT) within the Android region in cm3. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. The iDEXA algorithm did not work in volunteers who were too broad or had too little fat around the abdomen so it produced an output of 0. These were changed to -7 afterwards by the Data Man team.
Real
Visceral Adipose Tissue within the Android region in grams
New in R7. Visceral Adipose Tissue (VAT) within the Android region in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. The iDEXA algorithm did not work in volunteers who were too broad or had too little fat around the abdomen so it produced an output of 0. These were changed to -7 afterwards by the Data Man team.
Real
VAT within Android region in grams
Phase 2 data. Visceral Adipose Tissue (VAT) within the Android region in grams. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. The iDEXA algorithm did not work in volunteers who were too broad or had too little fat around the abdomen so it produced an output of 0. These were changed to -7 afterwards by the Data Man team.
Real
Subcutaneous Adipose Tissue within the Android region in grams
New in R7. Subcutaneous Adipose Tissue within the Android region in grams. generated by the anthro team = iDEXA Android fat mass g - iDEXA VAT g. Calculation and or check: iDEXA Android fat mass - iDEXA VAT g.
Real
SCAT within Android region in grams
Phase 2 data. Subcutaneous Adipose Tissue within the Android region in grams. generated by the anthro team = iDEXA Android fat mass g - iDEXA VAT g. Calculation and or check: iDEXA Android fat mass - iDEXA VAT g.
Real
Total fat mass of leg and head areas in grams
New in R7. Total fat mass of leg and head areas in grams. Generated by the anthro team iDEXA Total fat mass g - (iDEXA Trunk fat mass g + iDEXA arms fat mass g). Calculation and or check: Total fat mass - (Trunk fat mass + Arms fat mass).
Real
Total fat mass leg and head areas
Phase 2 data. Total fat mass of leg and head areas in grams. Generated by the anthro team iDEXA Total fat mass g - (iDEXA Trunk fat mass g + iDEXA arms fat mass g). Calculation and or check: Total fat mass - (Trunk fat mass + Arms fat mass).
Real
Total bone mineral density
New in R7. Total bone mineral density. regenerated by the anthro team iDEXA total bone mineral content/iDEXA area. Calculation and or check: checked against BMD generated by the DEXA - it was recalculated where the symmetry method was applied.
Real
Total bone mineral density
Phase 2 data. Total bone mineral density. Regenerated by the anthro team iDEXA total bone mineral content/iDEXA area. Calculation and or check: checked against BMD generated by the DEXA - it was recalculated where the symmetry method was applied.
Real
Total Mass regenerated from DEXA
New in R7. Total Mass regenerated from DEXA. Regenerated mass by the anthro team (fat mass(grams) + fat free mass(grams) + bone mineral mass(grams))/1000. Calculation and or check: Sum of total bone; lean; fat masses. comparison with weight.
Real
Total Mass regenerated from DEXA
Phase 2 data. Total Mass regenerated from DEXA. Regenerated mass by the anthro team (fat mass(grams) + fat free mass(grams) + bone mineral mass(grams))/1000. Calculation and or check: Sum of total bone; lean; fat masses. comparison with weight.
Real
Categories of iDEXA scan
New in R7. Background data information code generated by Anthropometry team. Request with AD58i_DEXA_Comments for further clarification.
Categorical
Categories of iDEXA scan
Phase 2 data. Background data information code generated by Anthropometry team. Request with AD58i_DEXA_Comments for further clarification.
Categorical
iDEXA Comments
New in R7. Comments provided by Anthropometry team regarding processing the data. Variable AD49_DEXA_Comments should be requested too.
Text
iDEXA Comments
Phase 2 data. Comments provided by Anthropometry team regarding processing the data. Variable AD49_DEXA_Comments should be requested too.
Text
OLINK assay ADAM15
Phase 1 OLINK assay data for target ADAM15 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ADAM 22
Phase 1 OLINK assay data for target ADAM 22 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ADAM 23
Phase 1 OLINK assay data for target ADAM 23 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ADAM 8
Phase 1 OLINK assay data for target ADAM 8 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ADAM-TS13
Phase 1 OLINK assay data for target ADAM-TS13 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ADAM-TS 15
Phase 1 OLINK assay data for target ADAM-TS 15 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ADA
Phase 1 OLINK assay data for target ADA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ADGRE2
Phase 1 OLINK assay data for target ADGRE2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ADGRG1
Phase 1 OLINK assay data for target ADGRG1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ADGRG2
Phase 1 OLINK assay data for target ADGRG2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Serum Adiponectin RAW
Serum biomarker Adiponectin RAW in ug/ml. Raw data; cleaned data provided in variable G_Adiponectin with x_Threshold and x_Com variables provided for clarification.
Real
Any comments which are relevant to admin data or b
General comments provided on study participation study samples tests etc.
Text
Comments relevant to admin data
Phase 2 data. General comments provided on phase 2 study participation study samples tests etc.
Text
OLINK assay ADM
Phase 1 OLINK assay data for target ADM in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Hours of High impact or step aerobics
Please indicate the average length of time (in hours) you spent doing the activity per episode. High impact or step aerobics.
Integer
Hours of High impact or step aerobics CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. High impact or step aerobics. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable:Highimpactaerobics hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. High impact or step aerobics. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
High impact or step aerobics hrs
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. High impact or step aerobics. -1 = left blank. DO NOT USE THIS VARIABLE. Use AerobicsHighHr_CLEAN_P2 instead.
Real
Minutes of High impact or step aerobics
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. High impact or step aerobics.
Integer
Minutes of High impact or step aerobics CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. High impact or step aerobics. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable:Highimpactaerobics min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. High impact or step aerobics. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
High impact or step aerobics min
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. High impact or step aerobics. -1 = left blank. DO NOT USE THIS VARIABLE. Use AerobicsHighMin_CLEAN_P2 instead.
Real
Frequency of High impact or step aerobics CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. High impact or step aerobics. Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
None
New in R8. Cleaned translated frequency (per week) for High impact or step aerobics
Real
Cln variable: High impact aerobics
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. High impact or step aerobics. Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
AerobicsHigh_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. High impact or step aerobics. Data normalised to DE template 1 data.
Categorical
High impact or step aerobics
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. High impact or step aerobics. DO NOT USE THIS VARIABLE. Use AerobicsHigh_CLEAN_P2 instead.
Real
High impact or step aerobics
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. High impact or step aerobics. Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of High impact or step aerobics DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. High impact or step aerobics. Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in AerobicsHigh_T2. Instead use AerobicsHigh_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of High impact or step aerobics DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. High impact or step aerobics. Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in AerobicsHigh_T1. Instead use AerobicsHigh_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Hours of other types of aerobics
Please indicate the average length of time (in hours) you spent doing the activity per episode. Other types of aerobics.
Integer
Hours ofother types of aerobics CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Other types of aerobics. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Other aerobics hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Other types of aerobics. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Other types of aerobics hrs
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Other types of aerobics. -1 = left blank. DO NOT USE THIS VARIABLE. Use aerobicsOtherHr_CLEAN_P2 instead.
Real
Minutes of other types of aerobics
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Other types of aerobics.
Integer
Minutes of other types of aerobics CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Other types of aerobics. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Other aerobics min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Other types of aerobics. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Other types of aerobics min
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Other types of aerobics. -1 = left blank. DO NOT USE THIS VARIABLE. Use aerobicsOtherMin_CLEAN_P2 instead.
Real
Frequency of other types of aerobics CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Other types of aerobics. Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
aerobicsOther_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for other types of aerobics
Real
Cln variable: Other erobics
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Other types of aerobics. Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
aerobicsOther_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Other types of aerobics. Data normalised to DE template 1 data.
Categorical
Other types of aerobics
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Other types of aerobics. DO NOT USE THIS VARIABLE. Use aerobicsOther_CLEAN_P2 instead.
Real
Other types of aerobics
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Other types of aerobics. Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of other types of aerobics DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Other types of aerobics. Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in aerobicsOther_T2. Instead use aerobicsOther_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of other types of aerobics DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Other types of aerobics. Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in aerobicsOther_T1. Instead use aerobicsOther_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
AES Comments on sheet
ActiHeart Evaluation Sheet. Any other comments made on Actiheart evaluation sheet not in Q9 by either study staff of participant. Potentailly provides additional explanation for any answers given so should be included in EAS data releases.
Text
AES DM batch
ActiHeart Evaluation Sheet. Data Management batch number.
AES Think Measure
ActiHeart Evaluation Sheet. Q1. What do you think the ActiHeart was measuring?
Text
AES Tell from Info
ActiHeart Evaluation Sheet. Q2. What do you think the research team will be able to tell from the information stored in your ActiHeart?
Text
AES PA wearingAH
ActiHeart Evaluation Sheet. Q3. While you were wearing the ActiHeart do you think you were
Categorical
AES Change 3
ActiHeart Evaluation Sheet. Q4iii. If you were more or less physically active than usual while you were wearing the ActHeart what did you do (or not do) that was different from usual? 3rd answer.
Text
AES Change 2
ActiHeart Evaluation Sheet. Q4ii. If you were more or less physically active than usual while you were wearing the ActHeart what did you do (or not do) that was different from usual? 2nd answer.
Text
AES Change 1
ActiHeart Evaluation Sheet. Q4i. If you were more or less physically active than usual while you were wearing the ActHeart what did you do (or not do) that was different from usual? 1st answer.
Text
AES Reason change 3
ActiHeart Evaluation Sheet. Q5iii. If you were more or less physically active than usual while you were wearing the ActHeart what were the main reasons for this? 3rd answer.
Text
AES Reason change 2
ActiHeart Evaluation Sheet. Q5ii. If you were more or less physically active than usual while you were wearing the ActHeart what were the main reasons for this? 2nd answer.
Text
AES Reason change 1
ActiHeart Evaluation Sheet. Q5i. If you were more or less physically active than usual while you were wearing the ActHeart what were the main reasons for this? 1st answer. (Note to data entry: If the answer to Q3 is 3 (about the same) and as expected Q4 and 5 have not been answered do not code these as -9 leave them blank).
Text
AES Should up PA comment
ActiHeart Evaluation Sheet. Q6c. While you were wearing the ActiHeart did you feel you should increase your physical activity - please explain.
Text
AES Should up PA
ActiHeart Evaluation Sheet. Q6. While you were wearing the ActiHeart did you feel you should increase your physical activity?
Categorical
AES More aware of PA comment
ActiHeart Evaluation Sheet. Q7c. Did wearing the ActiHeart make you more aware of how physically active you are - please explain.
Text
AES More aware of PA
ActiHeart Evaluation Sheet. Q7. Did wearing the ActiHeart make you more aware of how physically active you are?
Categorical
AES Reminded to be PA comment
ActiHeart Evaluation Sheet. Q8c. Did wearing the ActiHeart remind you to be more physically active - please explain.
Text
AES Reminded to be PA
ActiHeart Evaluation Sheet. Q8. Did wearing the ActiHeart remind you to be more physically active?
Categorical
AES Other comments
ActiHeart Evaluation Sheet. Q9. If you have any other comments about the ActiHeart please write them here.
Text
AES WD Batch
ActiHeart Evaluation Sheet. Data entry company processing batch number.
Age at Test
Data as entered on Study database. Age at test as reported by participant during site visit.
AgeAtTest_DM_Attended
New in R8. Derived age at test in decimals to reflect true age (eg 35.9 instead of 35) at first visit in years and decimals. This variable replaces AgeAtTest_DM because that was calculated using AppDate. Since AppDate is the date the first visit is scheduled which is not always the date the visit took place. For AgeAtTest_DM_Attended the variable AppDate_Attended is used which is the actual date of the first visit. Please note that this is a decimal number which does not reflect months.
Real
Age at test derived
Phase 2 data. Derived age at test in decimals to reflect true age (eg 35.9 instead of 35) at phase 2 visit in years and decimals ( the actual date of the phase 2 visit). Please note that this is a decimal number which does not reflect months.
Real
Age at test as reported by pt
Phase 2 data. Data as entered on Study database. Age at test as reported by participant during phase 2 site visit.
Real
None
Phase 1 data. Age of phase 1 volunteer (a volunteer who has a phase 1 visit date) on 01 Aug 2014. This allows for coss-study population ages comparison
Real
None
Phase 2 data. Age of phase 2 volunteer (a volunteer who has a phase 2 visit date) on 01 Aug 2020. This allows for coss-study population ages comparison. age provided only if volunteer took part in phase 2
Real
OLINK assay AGR2
Phase 1 OLINK assay data for target AGR2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay AGR3
Phase 1 OLINK assay data for target AGR3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay AGRP
Phase 1 OLINK assay data for target AGRP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
AH comments
AH comments. Contains comments on treadmill test fasting information
Text
AH comments
Phase 2 data. AH comments for Phase 2 data. Contains comments on treadmill test fasting information. Cleaned information held in main AH dataset for analysis. This has not been checked for identifaible information.
Text
OLINK assay AHCY
Phase 1 OLINK assay data for target AHCY in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Cmnts diary sheet AH Wrist Mon
Phase 2 data. General comments left on Diary sheet for actiheart and Wrist accelerometer monitor. The name of the variable the comment relates to has been provided where possible. -1 = no comments provided; -8 = text illegible
Text
Date day 1 of AhAccMon Worn
Phase 2 data. Date of day 1 of wearing Actiheart and wrist accelerometer dd/mm/yyyy. -1 = left blank or crossed through; -8 = text illegible
Date
Day Name of day 1 of AhAccMon Worn
Phase 2 data. Name of day of day 1 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -8 = text illegible
Text
Date day 2 of AhAccMon Worn
Phase 2 data. Date of day 2 of wearing Actiheart and wrist accelerometer dd/mm/yyyy. -1 = left blank or crossed through; -8 = text illegible
Date
Day Name of day 2 of AhAccMon Worn
Phase 2 data. Name of day of day 2 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -8 = text illegible
Text
Date day 3 of AhAccMon Worn
Phase 2 data. Date of day 3 of wearing Actiheart and wrist accelerometer dd/mm/yyyy. -1 = left blank or crossed through; -8 = text illegible
Date
Day Name of day 3 of AhAccMon Worn
Phase 2 data. Name of day of day 3 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -8 = text illegible
Text
Date day 4 of AhAccMon Worn
Phase 2 data. Date of day 4 of wearing Actiheart and wrist accelerometer dd/mm/yyyy. -1 = left blank or crossed through; -8 = text illegible
Date
Day Name of day 4 of AhAccMon Worn
Phase 2 data. Name of day of day 4 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -8 = text illegible
Text
Date day 5 of AhAccMon Worn
Phase 2 data. Date of day 5 of wearing Actiheart and wrist accelerometer dd/mm/yyyy. -1 = left blank or crossed through; -8 = text illegible
Date
Day Name of day 5 of AhAccMon Worn
Phase 2 data. Name of day of day 5 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -8 = text illegible
Text
Date day 6 of AhAccMon Worn
Phase 2 data. Date of day 6 of wearing Actiheart and wrist accelerometer dd/mm/yyyy. -1 = left blank or crossed through; -8 = text illegible
Date
Name of day6 Ah Acc Mon Worn
Phase 2 data. Name of day of day 6 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -8 = text illegible
Text
Date day 7 of AhAccMon Worn
Phase 2 data. Date of day 7 of wearing Actiheart and wrist accelerometer dd/mm/yyyy. -1 = left blank or crossed through; -8 = text illegible
Date
Name of day7 Ah Acc Mon Worn
Phase 2 data. Name of day of day 7 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -8 = text illegible
Text
No of times AH Wrist Mon worn
Phase 2 data. Number Of times actiheart and wrist worn accelerometer diary sheets have been completed. For each time the date of completion has been entered. -1 = only one copy completed
Real
General cmnts actiheart mon on day1
Phase 2 data. General comments (actiheart monitor) on day 1 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -8 = text illegible
Text
General cmnts actiheart mon on day2
Phase 2 data. General comments (actiheart monitor) on day 2 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -8 = text illegible
Text
General cmnts actiheart mon on day3
Phase 2 data. General comments (actiheart monitor) on day 3 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -8 = text illegible
Text
General cmnts actiheart mon on day4
Phase 2 data. General comments (actiheart monitor) on day 4 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -8 = text illegible
Text
General cmnts actiheart mon on day5
Phase 2 data. General comments (actiheart monitor) on day 5 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -8 = text illegible
Text
General cmnts actiheart mon on day6
Phase 2 data. General comments (actiheart monitor) on day 6 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -8 = text illegible
Text
General cmnts actiheart mon on day7
Phase 2 data. General comments (actiheart monitor) on day 7 of wearing Actiheart and wrist accelerometer. -1 = left blank or crossed through; -8 = text illegible
Text
Time actiheart mon taken off day1
Phase 2 data. What time did you take off the actiheart monitor on day 1 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time actiheart mon taken off day2
Phase 2 data. What time did you take off the actiheart monitor on day 2 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time actiheart mon taken off day3
Phase 2 data. What time did you take off the actiheart monitor on day 3 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time actiheart mon taken off day4
Phase 2 data. What time did you take off the actiheart monitor on day 4 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time actiheart mon taken off day5
Phase 2 data. What time did you take off the actiheart monitor on day 5 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time actiheart mon taken off day6
Phase 2 data. What time did you take off the actiheart monitor on day 6 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time actiheart mon taken off day7
Phase 2 data. What time did you take off the actiheart monitor on day 7 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Final date AH monitor taken off
Phase 2 data. Date of Final time taken off Actiheart monitor dd/mm/yyyy. -1 = left blank or crossed through; -8 = text illegible
Date
Final time AH monitor taken off
Phase 2 data. Date of Final time taken off Actiheart monitor (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Date
Time actiheart mon put back on day1
Phase 2 data. What time did you put the actiheart monitor back on on day 1 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time actiheart mon put back on day2
Phase 2 data. What time did you put the actiheart monitor back on on day 2 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time actiheart mon put back on day3
Phase 2 data. What time did you put the actiheart monitor back on on day 3 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time actiheart mon put back on day4
Phase 2 data. What time did you put the actiheart monitor back on on day 4 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time actiheart mon put back on day5
Phase 2 data. What time did you put the actiheart monitor back on on day 5 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time actiheart mon put back on day6
Phase 2 data. What time did you put the actiheart monitor back on on day 6 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time actiheart mon put back on day7
Phase 2 data. What time did you put the actiheart monitor back on on day 7 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Reason take off actiheart mon day1
Phase 2 data. Reason for taking off (actiheart monitor) on day 1 of wearing Actiheart and wrist accelerometer; example provided on form is CHANGE ELECTRODES. -1 = left blank or crossed through; -8 = text illegible
Text
Reason take off actiheart mon day2
Phase 2 data. Reason for taking off (actiheart monitor) on day 2 of wearing Actiheart and wrist accelerometer; example provided on form is CHANGE ELECTRODES. -1 = left blank or crossed through; -8 = text illegible
Text
Reason take off actiheart mon day3
Phase 2 data. Reason for taking off (actiheart monitor) on day 3 of wearing Actiheart and wrist accelerometer; example provided on form is CHANGE ELECTRODES. -1 = left blank or crossed through; -8 = text illegible
Text
Reason take off actiheart mon day4
Phase 2 data. Reason for taking off (actiheart monitor) on day 4 of wearing Actiheart and wrist accelerometer; example provided on form is CHANGE ELECTRODES. -1 = left blank or crossed through; -8 = text illegible
Text
Reason take off actiheart mon day5
Phase 2 data. Reason for taking off (actiheart monitor) on day 5 of wearing Actiheart and wrist accelerometer; example provided on form is CHANGE ELECTRODES. -1 = left blank or crossed through; -8 = text illegible
Text
Reason take off actiheart mon day6
Phase 2 data. Reason for taking off (actiheart monitor) on day 6 of wearing Actiheart and wrist accelerometer; example provided on form is CHANGE ELECTRODES. -1 = left blank or crossed through; -8 = text illegible
Text
Reason take off actiheart mon day7
Phase 2 data. Reason for taking off (actiheart monitor) on day 7 of wearing Actiheart and wrist accelerometer; example provided on form is CHANGE ELECTRODES. -1 = left blank or crossed through; -8 = text illegible
Text
Barcode error comments
Phase 2 data. Actiheart and wrist accelerometer diary sheet barcode scanning error comment. -1 = no issues to report
Text
Time finish wrk day1 AhAcc Mon Worn
Phase 2 data. What time did you finish work on day 1 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time finish wrk day2 AhAcc Mon Worn
Phase 2 data. What time did you finish work on day 2 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time finish wrk day3 AhAcc Mon Worn
Phase 2 data. What time did you finish work on day 3 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time finish wrk day4 AhAcc Mon Worn
Phase 2 data. What time did you finish work on day 4 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time finish wrk day5 AhAcc Mon Worn
Phase 2 data. What time did you finish work on day 5 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time finish wrk day6 AhAcc Mon Worn
Phase 2 data. What time did you finish work on day 6 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time finish wrk day7 AhAcc Mon Worn
Phase 2 data. What time did you finish work on day 7 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Get up time day2 Ah Acc Mon Worn
Phase 2 data. What time did you get up on day 2 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Get up time day3 Ah Acc Mon Worn
Phase 2 data. What time did you get up on day 3 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Get up time day4 Ah Acc Mon Worn
Phase 2 data. What time did you get up on day 4 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Get up time day5 Ah Acc Mon Worn
Phase 2 data. What time did you get up on day 5 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Get up time day6 Ah Acc Mon Worn
Phase 2 data. What time did you get up on day 6 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Get up time day7 Ah Acc Mon Worn
Phase 2 data. What time did you get up on day 7 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time went sleep day1 AhAcc Mon Worn
Phase 2 data. What time did you go to sleep on day 1 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time went sleep day2 AhAcc Mon Worn
Phase 2 data. What time did you go to sleep on day 2 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time went sleep day3 AhAcc Mon Worn
Phase 2 data. What time did you go to sleep on day 3 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time went sleep day4 AhAcc Mon Worn
Phase 2 data. What time did you go to sleep on day 4 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time went sleep day5 AhAcc Mon Worn
Phase 2 data. What time did you go to sleep on day 5 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time went sleep day6 AhAcc Mon Worn
Phase 2 data. What time did you go to sleep on day 6 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Not wrk day1 Ah Acc Mon Worn
Phase 2 data. What time did you start work on day 1 of wearing Actiheart and wrist accelerometer (24 hr format)? 1 = did not work (box ticked); -1 = not ticked (worked)
Categorical
Not wrk day2 Ah Acc Mon Worn
Phase 2 data. What time did you start work on day 2 of wearing Actiheart and wrist accelerometer (24 hr format)? 1 = did not work (box ticked); -1 = not ticked (worked)
Categorical
Not wrk day3 Ah Acc Mon Worn
Phase 2 data. What time did you start work on day 3 of wearing Actiheart and wrist accelerometer (24 hr format)? 1 = did not work (box ticked); -1 = not ticked (worked)
Categorical
Not wrk day4 Ah Acc Mon Worn
Phase 2 data. What time did you start work on day 4 of wearing Actiheart and wrist accelerometer (24 hr format)? 1 = did not work (box ticked); -1 = not ticked (worked)
Categorical
Not wrk day5 Ah Acc Mon Worn
Phase 2 data. What time did you start work on day 5 of wearing Actiheart and wrist accelerometer (24 hr format)? 1 = did not work (box ticked); -1 = not ticked (worked)
Categorical
Not wrk day6 Ah Acc Mon Worn
Phase 2 data. What time did you start work on day 6 of wearing Actiheart and wrist accelerometer (24 hr format)? 1 = did not work (box ticked); -1 = not ticked (worked)
Categorical
Not wrk day7 Ah Acc Mon Worn
Phase 2 data. What time did you start work on day 7 of wearing Actiheart and wrist accelerometer (24 hr format)? 1 = did not work (box ticked); -1 = not ticked (worked)
Categorical
AH wrist acc qnr version date
Phase 2 data. Actiheart and wrist accelerometer diary sheet questionnaire version date.
Date
AH wrist acc qnr version no
Phase 2 data. Actiheart and wrist accelerometer diary sheet questionnaire version number.
Real
Time start wrk day1 Ah Acc Mon Worn
Phase 2 data. What time did you start work on day 1 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time start wrk day2 Ah Acc Mon Worn
Phase 2 data. What time did you start work on day 2 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time start wrk day3 Ah Acc Mon Worn
Phase 2 data. What time did you start work on day 3 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time start wrk day4 Ah Acc Mon Worn
Phase 2 data. What time did you start work on day 4 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time start wrk day5 Ah Acc Mon Worn
Phase 2 data. What time did you start work on day 5 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time start wrk day6 Ah Acc Mon Worn
Phase 2 data. What time did you start work on day 6 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
Time start wrk day7 Ah Acc Mon Worn
Phase 2 data. What time did you start work on day 7 of wearing Actiheart and wrist accelerometer (24 hr format). -1 = left blank or crossed through; -8 = text illegible
Time
OLINK assay AIFM1
Phase 1 OLINK assay data for target AIFM1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
None
New for R9. Phase 1 plasma fluoride sample data for aKlotho. the CV of calculated concentration between intraplate duplicates - this is calculated by the MSD software (where applicable)
Real
None
New for R9. Phase 1 plasma fluoride sample data for aKlotho. the individual calculated concertation for each intra plate duplicate in pg/mL - this is calculated by the MSD software
Real
None
New for R9. Phase 1 plasma fluoride sample data for PDGF-CC. Date of MSD aKlotho experiment
Date
None
New for R9. Phase 1 plasma fluoride sample data for aKlotho. number of times the sample was thawed
Real
None
New for R9. Phase 1 plasma fluoride sample data for aKlotho. Plate specific Lower limit of detection for aKlotho measurements.
Real
None
New for R9. Phase 1 plasma fluoride sample data for aKlotho. barcode label by MSD - each plate is unique
Text
None
New for R9. Phase 1 plasma fluoride sample data for aKlotho. number of the plate assigned by the lab team
Real
None
New for R9. Phase 1 plasma fluoride sample data for aKlotho. well position within a 96-well plate
Text
None
New for R9. Phase 1 plasma fluoride sample data for aKlotho. The comment of wether the calculated concentration of the sample is within or outside the detection range of the assay; as assigned by the MSD software
Text
None
New for R9. Phase 1 plasma fluoride sample data for aKlotho. Plate specific Upper limit of detection for aKlotho measurements.
Real
OLINK assay AKT1S1
Phase 1 OLINK assay data for target AKT1S1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Investigation Date
When was Subject Measured?
Date
Investigation Date
Phase 2 data. When was Subject Measured?
Date
RT longitudinal sweep made: Quality
What was the quality of the RT Longitudinal Sweep that was Made?
Categorical
RT longitudinal sweep made: Quality
Phase 2 data. What was the quality of the RT Longitudinal Sweep that was Made? -1 = Unable to be determined; -9 = Missing data; 1 = A(highest); 2 = B; 3 = C(lowest);
Categorical
R transverse sweep made: Quality
What was the quality of the RT transverse Sweep that was Made?
Categorical
RT transverse sweep made: Quality
Phase 2 data. What was the quality of the RT transverse Sweep that was Made? -1 = Unable to be determined; -9 = Missing data; 1 = A(highest); 2 = B; 3 = C(lowest);
Categorical
LT longitudinal sweep made: Quality
What was the quality of the LT longitudinal sweep that was Made?
Categorical
LT longitudinal sweep made: Quality
Phase 2 data. What was the quality of the LT longitudinal sweep that was Made? -1 = Unable to be determined; -9 = Missing data; 1 = A(highest); 2 = B; 3 = C(lowest);
Categorical
LT transverse sweep made: Quality
What was the quality of the LT transverse sweep that was Made?
Categorical
LT transverse sweep made: Quality
Phase 2 data. What was the quality of the LT transverse sweep that was Made? -1 = Unable to be determined; -9 = Missing data; 1 = A(highest); 2 = B; 3 = C(lowest);
Categorical
Repeat sweep representative segment : Quality
What was the quality of the Repeat sweep (representative segment) that was Made?
Categorical
Quality of Repeat sweep
Phase 2 data. What was the quality of the Repeat sweep (representative segment) that was Made? -1 = Unable to be determined; -9 = Missing data; 1 = A(highest); 2 = B; 3 = C(lowest);
Categorical
Increased echo reflectivity liver parenchyma in comparison with kidney
What was the (Increased) echo reflectivity liver parenchyma (in comparison with kidney) score? Scored from 1 (highest quality) to 4 (lowest quality).
Categorical
Scoring criteria 1
Phase 2 data. What was the (Increased) echo reflectivity liver parenchyma (in comparison with kidney) score? Scored from 1 (highest quality) to 4 (lowest quality).
Categorical
Decreased visualization of intra-hepatic vascula
What was the (Decreased) visualization of intra-hepatic vasculature score? Scored from 1 (highest quality) to 4 (lowest quality).
Categorical
Scoring criteria 2
Phase 2 data. What was the (Decreased) visualization of intra-hepatic vasculature score? Scored from 1 (highest quality) to 4 (lowest quality). -1 = Unable to be determined; -9 = Missing data; 1 = Normal; 2 = Mild; 3 = Moderate; 4 = Severe;
Categorical
Attenuation of ultrasound beam impaired penetrati
What was the Attenuation of ultrasound beam impaired penetration score? Scored from 1 (highest quality) to 4 (lowest quality).
Categorical
Scoring criteria 3
Phase 2 data. What was the Attenuation of ultrasound beam impaired penetration score? Scored from 1 (highest quality) to 4 (lowest quality). -1 = Unable to be determined; -9 = Missing data; 1 = Normal; 2 = Mild; 3 = Moderate; 4 = Severe;
Categorical
Total liver score
This is the score for AL09_scoring_criteria_1 AL10_scoring_criteria_2 and AL11_scoring_criteria_3 all added. Values from a minimum of 3 to a maximum of 12. 16 data items with a value of 41275 in some Fenland R6 or earlier data releases were corrected to 10 in later R6 data releases. Error was due to data incorrectly being labelled as a date.
Real
Total score Category
Provides the Assessed Category from total score. Normal = 4 or less; Mild = 5 to 7; Moderate = 8 to 10; Severe = 11 or more;
Categorical
Total score Category
Phase 2 data. Provides the Assessed Category from total score. Normal = 4 or less; Mild = 5 to 7; Moderate = 8 to 10; Severe = 11 or more;
Categorical
Liver ultrasound comments
The comment made on theTotal score Category was
Text
Liver ultrasound comments
Phase 2 data. The comment made on theTotal score Category
Text
Repeat sweep representative segment : Quality
What was the quality of the Repeat sweep (representative segment) that was Made?
Categorical
Inter frozen quality
Phase 2 data. What was the quality of the Repeat sweep (representative segment) that was Made? -1 = Unable to be determined; -9 = Missing data; 1 = A(highest); 2 = B; 3 = C(lowest);
Categorical
Image format used
Image format that was used by the liver reviewer to assess the liver
Categorical
Sonographer
Identification of sonographer who carried out the ultrasound.
Categorical
Liver reviewer
Identification of liver reviewer who determined the score
Categorical
Ala_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable Ala_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. 2nd and final QC step on this var created new and final var BIOA_001.
Real
Albumin 0 minutes
Serum Albumin measurement taken at 0 minutes in g/L
Integer
Albumin 0 minutes
Phase 2 data. Serum Albumin measurement taken at 0 minutes in g/L
Real
OLINK assay ALCAM
Phase 1 OLINK assay data for target ALCAM in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
number of units of alcohol consumed per week
Alcohol Units Per Week
Units of alcohol consumed per week
Phase 2 data. Alcohol Units Per Week in Phase 2 data. Phase 2 unit definition: 1 unit is equivalent to 1/2 pint of beer ; 1/2 glass of wine; 1 single measure of spirits; 1 glass of sherry; This is different from phase 1 unit definition. Used for participant feedback only. Not for analysis. Used set of alcohol consumption variables derived from general questionnaire instead.
Real
ALCOHOL_EPI
Current alcohol consumption History / Status as requested by Ruth Loos. Derived from GenQ Qs by DM team JAVA script. Pls request G_Alcohol variable as well. 0 = never;
Categorical
Alcohol_EPI_weekend
Phase 2 data. Current alcohol consumption on fri-sat-sun History / Status. Derived from GenQ Qs by DM team JAVA script. Pls request G_Alcohol variable as well. Codes of 1; 3 and 9 for G_ALCOHOL are recoded as 9 in this variable. 0 = never; 1 = ex; 2 = current; 9 = not known;
Categorical
Alcohol consumption weekday
Phase 2 data. Current alcohol consumption on mon-tue-wed-thu History / Status. Derived from GenQ Qs by DM team JAVA script. Pls request G_Alcohol variable as well. Codes of 1; 3 and 9 for G_ALCOHOL are recoded as 9 in this variable. 0 = never; 1 = ex; 2 = current; 9 = not known;
Categorical
OLINK assay ALDH1A1
Phase 1 OLINK assay data for target ALDH1A1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ALDH3A1
Phase 1 OLINK assay data for target ALDH3A1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
AlkPhos 0 minutes
Serum Alkaline Phosphatase measurement taken at 0 minutes in U/L
Integer
AlkPhos 0 minutes
Phase 2 data. Serum Alkaline Phosphatase measurement taken at 0 minutes in U/L
Integer
alphaAAA_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable alphaAAA_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. 2nd and final QC step on this var created new and final var BIOA_025.
Real
OLINK assay Alpha-2-MRAP
Phase 1 OLINK assay data for target Alpha-2-MRAP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Alt 0 minutes
Phase 2 data. Serum Alt measurement taken at 0 minutes in U/L
Integer
OLINK assay AMBP
Phase 1 OLINK assay data for target AMBP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay AMIGO2
Phase 1 OLINK assay data for target AMIGO2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay AMN
Phase 1 OLINK assay data for target AMN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
aneamia
Phase 2 data. Binary variable indicating whether a drug from the anemia medication class was prescribed. 0 = No; 1 = Yes;
Categorical
OLINK assay ANGPT2
Phase 1 OLINK assay data for target ANGPT2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ANGPTL1
Phase 1 OLINK assay data for target ANGPTL1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ANGPTL3
Phase 1 OLINK assay data for target ANGPTL3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ANGPTL4
Phase 1 OLINK assay data for target ANGPTL4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ANGPTL7
Phase 1 OLINK assay data for target ANGPTL7 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ANG-1
Phase 1 OLINK assay data for target ANG-1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ANG
Phase 1 OLINK assay data for target ANG in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
None
ANML signal normalization scale factor (0.005percent mix)
Real
None
Phase 2 data. ANML signal normalization scale factor (0.005% mix)
Real
None
ANML signal normalization scale factor (0.5percent mix)
Real
None
Phase 2 data. ANML signal normalization scale factor (0.5% mix)
Real
None
ANML signal normalization scale factor (20percent mix)
Real
None
Phase 2 data. ANML signal normalization scale factor (20% mix)
Real
Anno tool complete
Phase 2 data. Annotation tool completed? 1 = yes;
Categorical
Anno tool email sent date
Phase 2 data. Date Annotation tool email sent off.
Date
Anno tool invite sent date
Phase 2 data. Date Annotation tool invite sent off.
Date
Anthro data sourec
Phase 2 data. Tracker variable created by DMT. 1 = paper; 2 = electronic; 3 = private network study db; 9 = paper and electronic;
Real
antidepressants
Phase 2 data. Binary variable indicating whether a drug from the antidepressant class was prescribed. 0 = No; 1 = Yes;
Categorical
OLINK assay ANXA10
Phase 1 OLINK assay data for target ANXA10 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ANXA11
Phase 1 OLINK assay data for target ANXA11 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ANXA1
Phase 1 OLINK assay data for target ANXA1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ANXA4
Phase 1 OLINK assay data for target ANXA4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay AOC1
Phase 1 OLINK assay data for target AOC1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay AOC3
Phase 1 OLINK assay data for target AOC3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay APBB1IP
Phase 1 OLINK assay data for target APBB1IP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay APEX1
Phase 1 OLINK assay data for target APEX1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay APLP1
Phase 1 OLINK assay data for target APLP1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Serum Apo_A1 RAW
Serum biomarker Apo A1 measurement RAW in g/L. Raw data; cleaned data provided in variable G_ApoA1 with x_Threshold and x_Com variables provided for clarification. Only measured on 10000+ Fenland volunteers so far as it is not part of the routine set of measurements.
Real
Serum Apo_B RAW
Serum biomarker Apo B measurement RAW in g/L. Raw data; cleaned data provided in variable G_ApoB with x_Threshold and x_Com variables provided for clarification. Only measured on 10000+ Fenland volunteers so far as it is not part of the routine set of measurements.
Real
OLINK assay APOM
Phase 1 OLINK assay data for target APOM in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
AppDate_Attended
New for R8 and replaces AppDate. Date of the apppointment which the participant ACTUALLY attended so appointment status = 2. Where participant had 2 or more appointments with status 2 the most recent date has been entered here. This is different from the data in AppDate since this is the actual date and Appdate is the date is should have been had it not been cancelled. The AppDate variable should no longer be used in R8.
Date
None
Phase 2 data. Date of the apppointment which the participant ACTUALLY attended so appointment status = 2. Where participant had 2 or more appointments with status 2 the most recent date has been entered here.
Date
OLINK assay APP
Phase 1 OLINK assay data for target APP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay AP-N
Phase 1 OLINK assay data for target AP-N in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay AREG
Phase 1 OLINK assay data for target AREG in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay AREG
Phase 1 OLINK assay data for target AREG in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ARG1
Phase 1 OLINK assay data for target ARG1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Arg_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable Arg_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. 2nd and final QC step on this var created new and final var BIOA_002.
Real
OLINK assay ARHGAP1
Phase 1 OLINK assay data for target ARHGAP1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ARHGEF12
Phase 1 OLINK assay data for target ARHGEF12 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ARNT
Phase 1 OLINK assay data for target ARNT in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Arrival Time
Phase 2 data. Clinical visit arrival time
Time
OLINK assay ARSA
Phase 1 OLINK assay data for target ARSA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ARSB
Phase 1 OLINK assay data for target ARSB in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ARTN
Phase 1 OLINK assay data for target ARTN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ASGR1
Phase 1 OLINK assay data for target ASGR1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Asn_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable Asn_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. 2nd and final QC step on this var created new and final var BIOA_003.
Real
Asp_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable Asp_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. 2nd and final QC step on this var created new and final var BIOA_004.
Real
Assay team run observation
Phase 2 data. Assay team run observation
Text
asthma_BA
Phase 2 data. Binary variable indicating whether a drug from the asthma: beta agonist class was prescribed. 0 = No; 1 = Yes;
Categorical
asthma_other
Phase 2 data. Binary variable indicating whether a drug from the asthma: other class was prescribed. 0 = No; 1 = Yes;
Categorical
asthma_steroids
Phase 2 data. Binary variable indicating whether a drug from the asthma: steroid class was prescribed. 0 = No; 1 = Yes;
Categorical
OLINK assay ATG4A
Phase 1 OLINK assay data for target ATG4A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ATP6AP2
Phase 1 OLINK assay data for target ATP6AP2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ATP6V1F
Phase 1 OLINK assay data for target ATP6V1F in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
The average data lost during free living
The average data lost during free living (1st wear of ActiHeart only) Manual scoring for Q purposes.
Categorical
OLINK assay AXIN1
Phase 1 OLINK assay data for target AXIN1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay AXL
Phase 1 OLINK assay data for target AXL in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay AZU1
Phase 1 OLINK assay data for target AZU1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay B4GALT1
Phase 1 OLINK assay data for target B4GALT1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay B4GAT1
Phase 1 OLINK assay data for target B4GAT1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BACH1
Phase 1 OLINK assay data for target BACH1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Hours of Backpacking Or Mountain Climbing
Please indicate the average length of time (in hours) you spent doing the activity per episode. Backpacking Or Mountain Climbing.
Integer
Hours of Backpacking Or Mountain Climbing CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Backpacking Or Mountain Climbing. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Backpack Mountain hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Backpacking Or Mountain Climbing. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Backpacking Mountain Climbing hrs
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Backpacking Or Mountain Climbing. -1 = left blank. DO NOT USE THIS VARIABLE. Use BackPackMountainClimbHr_CLEAN_P2 instead.
Real
Minutes of Backpacking Or Mountain Climbing
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Backpacking Or Mountain Climbing.
Integer
Minutes of Backpacking Or Mountain Climbing CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Backpacking Or Mountain Climbing. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Backpack Mountain min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Backpacking Or Mountain Climbing. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Backpacking Mountain Climbing min
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Backpacking Or Mountain Climbing. -1 = left blank. DO NOT USE THIS VARIABLE. Use BackPackMountainClimbMin_CLEAN_P2 instead.
Real
Frequency of Backpacking Or Mountain Climbing CLEANED
Frequency of Backpacking Or Mountain Climbing CLEANED
Categorical
backPackMountainClimb_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for Backpacking Or Mountain Climbing
Real
Cln variable: Backpack Mountain
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Backpacking Or Mountain Climbing. CLEANED. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
BackPackMountainClimb_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Backpacking Or Mountain Climbing. Data normalised to DE template 1 data.
Categorical
Backpacking or Mountain Climbing
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Backpacking Or Mountain Climbing. DO NOT USE THIS VARIABLE. Use BackPackMountainClimb_CLEAN_P2 instead.
Real
Backpacking or Mountain Climbing
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Backpacking Or Mountain Climbing. Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Backpacking Or Mountain Climbing DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Backpacking Or Mountain Climbing. Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in BackPackMountainClimb_T2. Instead use BackPackMountainClimb_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Backpacking Or Mountain Climbing DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Backpacking Or Mountain Climbing. Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in BackPackMountainClimb_T1. Instead use BackPackMountainClimb_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
OLINK assay BAG6
Phase 1 OLINK assay data for target BAG6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BAMBI
Phase 1 OLINK assay data for target BAMBI in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BANK1
Phase 1 OLINK assay data for target BANK1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
2D Barcode of aliquot
Phase 2 data. 2D Barcode of aliquot
Text
Branch chain amino acid alanine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) alanine peak area compared against peak area of known internal standard
Real
Branch chain amino acid arginine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) arginine peak area compared against peak area of known internal standard
Real
Branch chain amino acid asparagine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) asparagine peak area compared against peak area of known internal standard
Real
Branch chain amino acid aspartic acid
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) aspartic acid peak area compared against peak area of known internal standard
Real
Branch chain amino acid betaine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) betaine peak area compared against peak area of known internal standard
Real
BCAA box number
New in R7. Number of BCAA box assigned by MRC Epi lab.
Integer
Branch chain amino acid citrulline
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) citrulline peak area compared against peak area of known internal standard
Real
Branch chain amino acid cystine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) cystine peak area compared against peak area of known internal standard
Real
Branch chain amino acid glutamic acid
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) glutamic acid peak area compared against peak area of known internal standard
Real
Branch chain amino acid glutamine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) glutamine peak area compared against peak area of known internal standard
Real
Branch chain amino acid glycine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) glycine peak area compared against peak area of known internal standard
Real
Branch chain amino acid histidine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) histidine peak area compared against peak area of known internal standard
Real
Branch chain amino acid isoleucine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) isoleucine peak area compared against peak area of known internal standard
Real
Branch chain amino acid leucine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) leucine peak area compared against peak area of known internal standard
Real
Branch chain amino acid lysine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) lysine peak area compared against peak area of known internal standard
Real
Branch chain amino acid methionine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) methionine peak area compared against peak area of known internal standard
Real
Branch chain amino acid methylhistidine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) methylhistidine peak area compared against peak area of known internal standard
Real
Branch chain amino acid ornithine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) ornithine peak area compared against peak area of known internal standard
Real
Branch chain amino acid phenylalanine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) phenylalanine peak area compared against peak area of known internal standard
Real
Branch chain amino acid proline
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) proline peak area compared against peak area of known internal standard
Real
BCAA sample ID
New in R7. ID number for BCAA sample assigned by MRC Epi lab.
Integer
Branch chain amino acid serine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) serine peak area compared against peak area of known internal standard
Real
Branch chain amino acid threonine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) threonine peak area compared against peak area of known internal standard
Real
Branch chain amino acid tryptophan
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) tryptophan peak area compared against peak area of known internal standard
Real
Branch chain amino acid tyrosine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) tyrosine peak area compared against peak area of known internal standard
Real
Branch chain amino acid valine
New in R7. Relative concentration of Plasma Heparin BCAA (branch Chain Amino Acid) valine peak area compared against peak area of known internal standard
Real
OLINK assay BCAM
Phase 1 OLINK assay data for target BCAM in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BCAN
Phase 1 OLINK assay data for target BCAN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BCL2L11
Phase 1 OLINK assay data for target BCL2L11 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BCR
Phase 1 OLINK assay data for target BCR in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OnBetablockers
New in R8. Is the volunteer on betablockers? As indicated by nurse at the time of doing treadmill test. Volunteer's affermative answer is recorded as yes. The data is then reviewed by the PA team and corrected where additional information (eg notes on form) indicates betablocker useage. This is a much more accurate indication of betablocker useage then BNF_Betablocker variable.
Categorical
beta_blocker
Phase 2 data. Binary variable indicating whether a drug from the beta blocker class was prescribed. 0 = No; 1 = Yes;
Categorical
OLINK assay Beta-NGF
Phase 1 OLINK assay data for target Beta-NGF in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay Beta-NGF
Phase 1 OLINK assay data for target Beta-NGF in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BGN
Phase 1 OLINK assay data for target BGN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BID
Phase 1 OLINK assay data for target BID in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Bilirubin 0 minutes
Serum Total Bili (Bilirubin) measurement taken at 0 minutes in umol/L
Integer
Bilirubin 0 minutes
Phase 2 data. Serum Total Bili (Bilirubin) measurement taken at 0 minutes in umol/L
Integer
None
Metabolomics Biocrates assay N of repeats (1 to 3). Most samples were assayed only once but some were assayed multiple times.
Integer
Ala_QCstep2 valid=1 LoD=1
New in R8. QCd metabolomics data (final) for alanine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=1 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable ala. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Ala_raw and QCstep1 var is Ala
Real
Arg_QCstep2 valid=1 LoD=05
New in R8. QCd metabolomics data (final) for arginine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.5 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable arg. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Arg_raw and QCstep1 var is Arg_i
Real
Asn_QCstep2 valid=1 LoD=15
New in R8. QCd metabolomics data (final) for asparagine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=1.5 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable asn. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Asn_raw and QCstep1 var is Asn_i
Real
Asp_QCstep2 valid=0 LoD=15
New in R8. QCd metabolomics data (final) for aspartate - Metabolomics measures in an absolute scale (uM) - validity=0 and LoD=1.5 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable asp. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Asp_raw and QCstep1 var is Asp_i
Real
Cit_QCstep2 valid=0 LoD=1
New in R8. QCd metabolomics data (final) for citrulline - Metabolomics measures in an absolute scale (uM) - validity=0 and LoD=1 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable cit. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Cit_raw and QCstep1 var is Cit_i
Real
Gln_QCstep2 valid=1 LoD=15
New in R8. QCd metabolomics data (final) for glutamine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=1.5 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable gln. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Gln_raw and QCstep1 var is Gln_i
Real
Glu_QCstep2 valid=1 LoD=2
New in R8. QCd metabolomics data (final) for glutamate - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=2 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable glu. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Glu_raw and QCstep1 var is Glu_i
Real
Gly_QCstep2 valid=1 LoD=05
New in R8. QCd metabolomics data (final) for glycine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.5 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable gly. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Gly_raw and QCstep1 var is Gly_i
Real
His_QCstep2 valid=1 LoD=05
New in R8. QCd metabolomics data (final) for histidine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.5 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable his. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is His_raw and QCstep1 var is His
Real
Ile_QCstep2 valid=1 LoD=15
New in R8. QCd metabolomics data (final) for isoleucine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=1.5 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable ile. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Ile_raw and QCstep1 var is Ile
Real
Leu_QCstep2 valid=1 LoD=15
New in R8. QCd metabolomics data (final) for leucine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=1.5 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable leu. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Leu_raw and QCstep1 var is Leu
Real
Lys_QCstep2 valid=1 LoD=05
New in R8. QCd metabolomics data (final) for lysine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.5 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable lys. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Lys_raw and QCstep1 var is Lys
Real
Met_QCstep2 valid=1 LoD=01
New in R8. QCd metabolomics data (final) for methionine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.1 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable met. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Met_raw and QCstep1 var is Met_i
Real
Orn_QCstep2 valid=1 LoD=05
New in R8. QCd metabolomics data (final) for ornithine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.5 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable orn. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Orn_raw and QCstep1 var is Orn_i
Real
PEA_QCstep2 valid=0 LoD=003
New in R8. QCd metabolomics data (final) for phenylethylamine - Metabolomics measures in an absolute scale (uM) - validity=0 and LoD=0.03 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pea. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PEA_raw and QCstep1 var is PEA_i
Real
Phe_QCstep2 valid=1 LoD=01
New in R8. QCd metabolomics data (final) for phenylalanine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.1 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable phe. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Phe_raw and QCstep1 var is Phe
Real
Pro_QCstep2 valid=1 LoD=1
New in R8. QCd metabolomics data (final) for proline - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=1 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pro. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Pro_raw and QCstep1 var is Pro_i
Real
Ser_QCstep2 valid=1 LoD=1
New in R8. QCd metabolomics data (final) for serine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=1 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable ser. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Ser_raw and QCstep1 var is Ser_i
Real
Thr_QCstep2 valid=1 LoD=05
New in R8. QCd metabolomics data (final) for threonine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.5 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable thr. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Thr_raw and QCstep1 var is Thr_i
Real
Trp_QCstep2 valid=1 LoD=05
New in R8. QCd metabolomics data (final) for tryptophan - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.5 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable trp. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Trp_raw and QCstep1 var is Trp_i
Real
Tyr_QCstep2 valid=1 LoD=05
New in R8. QCd metabolomics data (final) for tyrosine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.5 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable tyr. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Tyr_raw and QCstep1 var is Tyr
Real
Val_QCstep2 valid=1 LoD=05
New in R8. QCd metabolomics data (final) for valine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.5 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable val. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Val_raw and QCstep1 var is Val
Real
AcOrn_QCstep2 valid=0 LoD=015
New in R8. QCd metabolomics data (final) for acetylornithine - Metabolomics measures in an absolute scale (uM) - validity=0 and LoD=0.15 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable acorn. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is AcOrn_raw and QCstep1 var is AcOrn_i
Real
SDMA_QCstep2 valid=1 LoD=03
New in R8. QCd metabolomics data (final) for symmetric dimethylarginine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.3 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable sdma. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is SDMA_raw and QCstep1 var is SDMA_i
Real
alphaAAA_QCstep2 valid=0 LoD=03
New in R8. QCd metabolomics data (final) for alpha-aminoadipic acid - Metabolomics measures in an absolute scale (uM) - validity=0 and LoD=0.3 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable alphaaaa. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is alphaAAA_raw and QCstep1 var is alphaAAA_i
Real
Creatinine_QCstep2 valid=1 LoD=1
New in R8. QCd metabolomics data (final) for creatinine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=1 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable creatinine. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Creatinine_raw and QCstep1 var is Creatinine
Real
Kynurenine_QCstep2 valid=0 LoD=03
New in R8. QCd metabolomics data (final) for kynurenine - Metabolomics measures in an absolute scale (uM) - validity=0 and LoD=0.3 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable kynurenine. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Kynurenine_raw and QCstep1 var is Kynurenine_i
Real
MetSO_QCstep2 valid=0 LoD=03
New in R8. QCd metabolomics data (final) for methioninesulfoxide - Metabolomics measures in an absolute scale (uM) - validity=0 and LoD=0.3 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable metso. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is MetSO_raw and QCstep1 var is MetSO_i
Real
c4OHPro_QCstep2 valid=1 LoD=01
New in R8. QCd metabolomics data (final) for cis-hydroxyproline - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.1 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c4ohpro. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is c4OHPro_raw and QCstep1 var is c4OHPro_i
Real
t4OHPro_QCstep2 valid=1 LoD=01
New in R8. QCd metabolomics data (final) for trans-hydroxyproline - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.1 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable t4ohpro. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is t4OHPro_raw and QCstep1 var is t4OHPro
Real
Sarcosine_QCstep2 valid=1 LoD=03
New in R8. QCd metabolomics data (final) for sarcosine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.3 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable sarcosine. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Sarcosine_raw and QCstep1 var is Sarcosine_i
Real
Serotonin_QCstep2 valid=1 LoD=003
New in R8. QCd metabolomics data (final) for serotonin - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.03 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable serotonin. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Serotonin_raw and QCstep1 var is Serotonin_i
Real
Spermidine_QCstep2 valid=0 LoD=008
New in R8. QCd metabolomics data (final) for spermidine - Metabolomics measures in an absolute scale (uM) - validity=0 and LoD=0.08 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable spermidine. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Spermidine_raw and QCstep1 var is Spermidine_i
Real
Taurine_QCstep2 valid=1 LoD=05
New in R8. QCd metabolomics data (final) for taurine - Metabolomics measures in an absolute scale (uM) - validity=1 and LoD=0.5 uM based on the Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable taurine. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Taurine_raw and QCstep1 var is Taurine_i
Real
Biochem Comments
Comments from lab related to BioChem samples.
Text
BioChemFormRec
New in R7. Has the Biochemistry form been received
Categorical
None
Has Biochemistry data been imported into Study access database?
Categorical
Biochem Imported
Phase 2 data. Biochemistry Imported? Data from study database. 0 = No; 1 = Yes;
Categorical
None
Variable present in Fenland study database which indicates if there are any issues with biochemistry data collected.
Biochem Manual Edit Warning
Phase 2 data. Variable present in Fenland study database which indicates if there are any issues with biochemistry data collected. 0 = No; 1 = Yes;
Categorical
None
Biochemistry test results received date from test laboratory.
Date
Biochem Received Date
Phase 2 data. Date Phase 2 biochem sample was received in lab.
Date
None
Phase 2 data. BioChemistry Import variable (leptin results only?). Fields with Data
Integer
None
Phase 2 data. BioChemistry Import variable (leptin results only?). Fields with Data
Text
None
Phase 2 data. BioChemistry Import variable (leptin results only?). Fields with Data
Integer
None
Phase 2 data. BioChemistry Import variable (leptin results only?). Fields with Data
Text
None
Phase 2 data. BioChemistry Import variable (leptin results only?). Fields with Data
Date
None
Phase 2 data. BioChemistry Import variable (leptin results only?). Fields with Data
Integer
None
Phase 2 data. BioChemistry Import variable (leptin results only?). Fields with Data
Integer
None
Metabolomics Biocrates assay date (DD/MM/YYYY)
Date
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The CV of calculated concentation between intraplate (within plate) duplicates (where applicable) calculated by the MSD software for IFNg at T000 timepoint (fasting). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The mean of calculated concertation in pg/mL calculated by the MSD software for IFNg at T000 timepoint (fasting). Results for plates 1a to 41 were bridged with rest of the plates using a bridging factor of 1.645 to calculate Calc Conc Mean.
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate Barcode number of plate used for IFNg at T000 timepoint (fasting).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Random plate number (asigned by lab team) of plate used for IFNg at T000 timepoint (fasting).
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None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate well in 96-well plate used for IFNg at T000 timepoint (fasting).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Indication where measurement was in relation to detection range. Above Detection Range (above the calculated high). Or In Detection Range (between calculated high and calculated low. Or Below Detection Range and Below Fit Curve Range (below calculated low). For IFNg at T000 timepoint (fasting).
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None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The CV of calculated concentation between intraplate (within plate) duplicates (where applicable) calculated by the MSD software for IFNg at T120 timepoint (2hrs post glucose drink). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The mean of calculated concertation in pg/mL calculated by the MSD software for IFNg at T120 timepoint (fasting). Results for plates 1a to 41 were bridged with rest of the plates using a bridging factor of 1.645 to calculate Calc Conc Mean. EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate Barcode number of plate used forIFNg at T120 timepoint (2hrs post glucose drink).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Random plate number (asigned by lab team) of plate used for IFNg at T120 timepoint (2hrs post glucose drink).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate well in 96-well plate used for IFNg at T120 timepoint (2hrs post glucose drink).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Indication where measurement was in relation to detection range. Above Detection Range (above the calculated high). Or In Detection Range (between calculated high and calculated low. Or Below Detection Range and Below Fit Curve Range (below calculated low). For IFNg at T120 timepoint (2hrs post glucose drink).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The CV of calculated concentation between intraplate (within plate) duplicates (where applicable) calculated by the MSD software for IL1b at T000 timepoint (fasting). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The mean of calculated concertation in pg/mL calculated by the MSD software for IL1b at T000 timepoint (fasting). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate Barcode number of plate used forIL1b at T000 timepoint (fasting).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Random plate number (asigned by lab team) of plate used for IL1b at T000 timepoint (fasting).
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate well in 96-well plate used for IL1b at T000 timepoint (fasting).
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Indication where measurement was in relation to detection range. Above Detection Range (above the calculated high). Or In Detection Range (between calculated high and calculated low. Or Below Detection Range and Below Fit Curve Range (below calculated low). For IL1b at T000 timepoint (fasting).
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The CV of calculated concentation between intraplate (within plate) duplicates (where applicable) calculated by the MSD software for IL1b at T120 timepoint (2hrs post glucose drink). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The mean of calculated concertation in pg/mL calculated by the MSD software for IL1b at T120 timepoint (2hrs post glucose drink). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate Barcode number of plate used forIL1b at T120 timepoint (2hrs post glucose drink).
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Random plate number (asigned by lab team) of plate used for IL1b at T120 timepoint (2hrs post glucose drink).
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate well in 96-well plate used for IL1b at T120 timepoint (2hrs post glucose drink).
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Indication where measurement was in relation to detection range. Above Detection Range (above the calculated high). Or In Detection Range (between calculated high and calculated low. Or Below Detection Range and Below Fit Curve Range (below calculated low). For IL1b at T120 timepoint (2hrs post glucose drink).
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The CV of calculated concentation between intraplate (within plate) duplicates (where applicable) calculated by the MSD software for IL6 at T000 timepoint (fasting). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The mean of calculated concertation in pg/mL calculated by the MSD software for IL6 at T000 timepoint (fasting). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate Barcode number of plate used forIL6 at T000 timepoint (fasting).
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Random plate number (asigned by lab team) of plate used for IL6 at T000 timepoint (fasting).
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate well in 96-well plate used for IL6 at T000 timepoint (fasting).
Text
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Indication where measurement was in relation to detection range. Above Detection Range (above the calculated high). Or In Detection Range (between calculated high and calculated low. Or Below Detection Range and Below Fit Curve Range (below calculated low). For IL6 at T000 timepoint (fasting).
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The CV of calculated concentation between intraplate (within plate) duplicates (where applicable) calculated by the MSD software for IL6 at T120 timepoint (2hrs post glucose drink). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The mean of calculated concertation in pg/mL calculated by the MSD software for IL6 at T120 timepoint (2hrs post glucose drink). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate Barcode number of plate used forIL6 at T120 timepoint (2hrs post glucose drink).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Random plate number (asigned by lab team) of plate used for IL6 at T120 timepoint (2hrs post glucose drink).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate well in 96-well plate used for IL6 at T120 timepoint (2hrs post glucose drink).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Indication where measurement was in relation to detection range. Above Detection Range (above the calculated high). Or In Detection Range (between calculated high and calculated low. Or Below Detection Range and Below Fit Curve Range (below calculated low). For IL6 at T120 timepoint (2hrs post glucose drink).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The CV of calculated concentation between intraplate (within plate) duplicates (where applicable) calculated by the MSD software for IL8 at T000 timepoint (fasting). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The mean of calculated concertation in pg/mL calculated by the MSD software for IL8 at T000 timepoint (fasting). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
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New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate Barcode number of plate used forIL8 at T000 timepoint (fasting).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Random plate number (asigned by lab team) of plate used for IL8 at T000 timepoint (fasting).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate well in 96-well plate used for IL8 at T000 timepoint (fasting).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Indication where measurement was in relation to detection range. Above Detection Range (above the calculated high). Or In Detection Range (between calculated high and calculated low. Or Below Detection Range and Below Fit Curve Range (below calculated low). For IL8 at T000 timepoint (fasting).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The CV of calculated concentation between intraplate (within plate) duplicates (where applicable) calculated by the MSD software for IL8 at T120 timepoint (2hrs post glucose drink). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The mean of calculated concertation in pg/mL calculated by the MSD software for IL8 at T120 timepoint (2hrs post glucose drink). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate Barcode number of plate used forIL8 at T120 timepoint (2hrs post glucose drink).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Random plate number (asigned by lab team) of plate used for IL8 at T120 timepoint (2hrs post glucose drink).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate well in 96-well plate used for IL8 at T120 timepoint (2hrs post glucose drink).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Indication where measurement was in relation to detection range. Above Detection Range (above the calculated high). Or In Detection Range (between calculated high and calculated low. Or Below Detection Range and Below Fit Curve Range (below calculated low). For IL8 at T120 timepoint (2hrs post glucose drink).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The CV of calculated concentation between intraplate (within plate) duplicates (where applicable) calculated by the MSD software for TNFa at T000 timepoint (fasting). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The mean of calculated concertation in pg/mL calculated by the MSD software for TNFa at T000 timepoint (fasting). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate Barcode number of plate used forTNFa at T000 timepoint (fasting).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Random plate number (asigned by lab team) of plate used for TNFa at T000 timepoint (fasting).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate well in 96-well plate used for TNFa at T000 timepoint (fasting).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Indication where measurement was in relation to detection range. Above Detection Range (above the calculated high). Or In Detection Range (between calculated high and calculated low. Or Below Detection Range and Below Fit Curve Range (below calculated low). For TNFa at T000 timepoint (fasting).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The CV of calculated concentation between intraplate (within plate) duplicates (where applicable) calculated by the MSD software for TNFa at T120 timepoint (2hrs post glucose drink). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. The mean of calculated concertation in pg/mL calculated by the MSD software for TNFa at T120 timepoint (2hrs post glucose drink). EX = technical error; ALD = above upper limit of detectio; BLD = below lower limit of detection; PD = poor duplicate - CalcConcCV of within plate (intra-plate) duplicates higher than 20percent;
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate Barcode number of plate used forTNFa at T120 timepoint (2hrs post glucose drink).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Random plate number (asigned by lab team) of plate used for TNFa at T120 timepoint (2hrs post glucose drink).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Plate well in 96-well plate used for TNFa at T120 timepoint (2hrs post glucose drink).
Text
None
New for R8a. MSD Proinflammatory Cytokines Project 0139 measuring phase 1 serum samples for proinflammatory biomarkers using the MSD V-Plex Human proinflammatory panel I (4-plex) kits. Indication where measurement was in relation to detection range. Above Detection Range (above the calculated high). Or In Detection Range (between calculated high and calculated low. Or Below Detection Range and Below Fit Curve Range (below calculated low). For TNFa at T120 timepoint (2hrs post glucose drink).
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Metabolomics assay plate number as assigned by MRC Epi lab team
Integer
None
Metabolomics Random plate number as assigned by the data management team to be used to de-identify the results
Integer
C0_QCstep2 valid=1 LoD=4
New in R8. QCd metabolomics data (final) for carnitine - Metabolomics measures in a relative scale (uM) - validity=1 and LoD=4 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c0. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C0_raw and QCstep1 var is C0
Real
C2_QCstep2 valid=1 LoD=015
New in R8. QCd metabolomics data (final) for acetylcarnitine - Metabolomics measures in a relative scale (uM) - validity=1 and LoD=0.15 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c2. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C2_raw and QCstep1 var is C2
Real
C3_QCstep2 valid=1 LoD=008
New in R8. QCd metabolomics data (final) for propionylcarnitine - Metabolomics measures in a relative scale (uM) - validity=1 and LoD=0.08 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c3. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C3_raw and QCstep1 var is C3
Real
C31_QCstep2 valid=0 LoD=003
New in R8. QCd metabolomics data (final) for propenoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.03 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c31. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C31_raw and QCstep1 var is C31
Real
C3OH_QCstep2 valid=0 LoD=005
New in R8. QCd metabolomics data (final) for hydroxypropionylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.05 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c3oh. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C3OH_raw and QCstep1 var is C3OH
Real
C4_QCstep2 valid=1 LoD=003
New in R8. QCd metabolomics data (final) for butyrylcarnitine - Metabolomics measures in a relative scale (uM) - validity=1 and LoD=0.03 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c4. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C4_raw and QCstep1 var is C4
Real
C41_QCstep2 valid=0 LoD=003
New in R8. QCd metabolomics data (final) for butenylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.03 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c41. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C41_raw and QCstep1 var is C41
Real
C3DCMC5OH_QCstep2 valid=0 LoD=01
New in R8. QCd metabolomics data (final) for hydroxybutyrylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.1 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c3dcmc5oh. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C3DCMC5OH_raw and QCstep1 var is C3DCMC5OH
Real
C5_QCstep2 valid=1 LoD=004
New in R8. QCd metabolomics data (final) for valerylcarnitine - Metabolomics measures in a relative scale (uM) - validity=1 and LoD=0.04 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c5. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C5_raw and QCstep1 var is C5
Real
C51_QCstep2 valid=0 LoD=004
New in R8. QCd metabolomics data (final) for tiglylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.04 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c51. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C51_raw and QCstep1 var is C51
Real
C51DC_QCstep2 valid=0 LoD=0015
New in R8. QCd metabolomics data (final) for glutaconylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.015 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c51dc. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C51DC_raw and QCstep1 var is C51DC
Real
C5MDC_QCstep2 valid=0 LoD=006
New in R8. QCd metabolomics data (final) for methylglutarylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.06 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c5mdc. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C5MDC_raw and QCstep1 var is C5MDC
Real
C6C41DC_QCstep2 valid=1 LoD=008
New in R8. QCd metabolomics data (final) for hexanoylcarnitine (fumarylcarnitine) - Metabolomics measures in a relative scale (uM) - validity=1 and LoD=0.08 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c6c41dc. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C6C41DC_raw and QCstep1 var is C6C41DC
Real
C5DCC6OH_QCstep2 valid=0 LoD=0035
New in R8. QCd metabolomics data (final) for glutarylcarnitine (hydroxihexanoylcarnitine) - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.035 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c5dcc6oh. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C5DCC6OH_raw and QCstep1 var is C5DCC6OH
Real
C3DCC4OH_QCstep2 valid=0 LoD=009
New in R8. QCd metabolomics data (final) for hydroxyvalerylcarnitine (methylmalonlcarnitine) - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.09 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c3dcc4oh. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C3DCC4OH_raw and QCstep1 var is C3DCC4OH
Real
C61_QCstep2 valid=0 LoD=0035
New in R8. QCd metabolomics data (final) for hexenoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.035 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c61. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C61_raw and QCstep1 var is C61
Real
C7DC_QCstep2 valid=0 LoD=0035
New in R8. QCd metabolomics data (final) for pimelylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.035 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c7dc. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C7DC_raw and QCstep1 var is C7DC
Real
C8_QCstep2 valid=1 LoD=017
New in R8. QCd metabolomics data (final) for octanoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=1 and LoD=0.17 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c8. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C8_raw and QCstep1 var is C8
Real
C9_QCstep2 valid=0 LoD=004
New in R8. QCd metabolomics data (final) for nonaylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.04 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c9. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C9_raw and QCstep1 var is C9
Real
C10_QCstep2 valid=1 LoD=016
New in R8. QCd metabolomics data (final) for decanoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=1 and LoD=0.16 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c10. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C10_raw and QCstep1 var is C10
Real
C101_QCstep2 valid=0 LoD=012
New in R8. QCd metabolomics data (final) for decenoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.12 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c101. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C101_raw and QCstep1 var is C101
Real
C102_QCstep2 valid=0 LoD=004
New in R8. QCd metabolomics data (final) for decadienylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.04 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c102. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C102_raw and QCstep1 var is C102
Real
C12_QCstep2 valid=1 LoD=0057
New in R8. QCd metabolomics data (final) for dodecanoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=1 and LoD=0.057 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c12. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C12_raw and QCstep1 var is C12
Real
C12DC_QCstep2 valid=0 LoD=02
New in R8. QCd metabolomics data (final) for dodecaenoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.2 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c12dc. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C12DC_raw and QCstep1 var is C12DC
Real
C121_QCstep2 valid=0 LoD=02
New in R8. QCd metabolomics data (final) for dodecanedioylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.2 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c121. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C121_raw and QCstep1 var is C121
Real
C14_QCstep2 valid=1 LoD=003
New in R8. QCd metabolomics data (final) for tetradecanoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=1 and LoD=0.03 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c14. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C14_raw and QCstep1 var is C14
Real
C141_QCstep2 valid=0 LoD=0015
New in R8. QCd metabolomics data (final) for tetradecenoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.015 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c141. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C141_raw and QCstep1 var is C141
Real
C141OH_QCstep2 valid=0 LoD=0015
New in R8. QCd metabolomics data (final) for hydroxytetradecenoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.015 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c141oh. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C141OH_raw and QCstep1 var is C141OH
Real
C142_QCstep2 valid=0 LoD=0012
New in R8. QCd metabolomics data (final) for tetradecadienylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.012 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c142. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C142_raw and QCstep1 var is C142
Real
C142OH_QCstep2 valid=0 LoD=0015
New in R8. QCd metabolomics data (final) for hydroxytetradecadienylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.015 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c142oh. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C142OH_raw and QCstep1 var is C142OH
Real
C16_QCstep2 valid=1 LoD=0018
New in R8. QCd metabolomics data (final) for hexadecanoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=1 and LoD=0.018 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c16. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C16_raw and QCstep1 var is C16
Real
C161_QCstep2 valid=0 LoD=006
New in R8. QCd metabolomics data (final) for hexadecenoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.06 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c161. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C161_raw and QCstep1 var is C161
Real
C161OH_QCstep2 valid=0 LoD=002
New in R8. QCd metabolomics data (final) for hydroxyhexadecenoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.02 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c161oh. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C161OH_raw and QCstep1 var is C161OH
Real
C162_QCstep2 valid=0 LoD=0008
New in R8. QCd metabolomics data (final) for hexadecadienylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.008 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c162. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C162_raw and QCstep1 var is C162
Real
C162OH_QCstep2 valid=0 LoD=003
New in R8. QCd metabolomics data (final) for hydroxyhexadecadienylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.03 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c162oh. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C162OH_raw and QCstep1 var is C162OH
Real
C16OH_QCstep2 valid=0 LoD=0015
New in R8. QCd metabolomics data (final) for hydroxyhexadecanoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.015 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c16oh. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C16OH_raw and QCstep1 var is C16OH
Real
C18_QCstep2 valid=1 LoD=002
New in R8. QCd metabolomics data (final) for octadecanoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=1 and LoD=0.02 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c18. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C18_raw and QCstep1 var is C18_i
Real
C181_QCstep2 valid=0 LoD=004
New in R8. QCd metabolomics data (final) for octadecenoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.04 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c181. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C181_raw and QCstep1 var is C181_i
Real
C181OH_QCstep2 valid=0 LoD=0023
New in R8. QCd metabolomics data (final) for hydroxyoctadecenoylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.023 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c181oh. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C181OH_raw and QCstep1 var is C181OH_i
Real
C182_QCstep2 valid=0 LoD=0009
New in R8. QCd metabolomics data (final) for octadecadienylcarnitine - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.009 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable c182. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is C182_raw and QCstep1 var is C182_i
Real
PCaaC240_QCstep2 valid=0 LoD=01
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C240 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.1 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac240. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC240_raw and QCstep1 var is PCaaC240_i
Real
PCaaC260_QCstep2 valid=0 LoD=14
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C260 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=1.4 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac260. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC260_raw and QCstep1 var is PCaaC260_i
Real
PCaaC281_QCstep2 valid=0 LoD=004
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C281 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.04 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac281. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC281_raw and QCstep1 var is PCaaC281_i
Real
lysoPCaC140_QCstep2 valid=0 LoD=5
New in R8. QCd metabolomics data (final) for lysoPhosphatidylcholine acyl C140 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=5 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable lysopcac140. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is lysoPCaC140_raw and QCstep1 var is lysoPCaC140
Real
lysoPCaC161_QCstep2 valid=0 LoD=007
New in R8. QCd metabolomics data (final) for lysoPhosphatidylcholine acyl C161 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.07 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable lysopcac161. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is lysoPCaC161_raw and QCstep1 var is lysoPCaC161
Real
lysoPCaC170_QCstep2 valid=0 LoD=005
New in R8. QCd metabolomics data (final) for lysoPhosphatidylcholine acyl C170 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.05 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable lysopcac170. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is lysoPCaC170_raw and QCstep1 var is lysoPCaC170
Real
lysoPCaC180_QCstep2 valid=0 LoD=005
New in R8. QCd metabolomics data (final) for lysoPhosphatidylcholine acyl C180 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.05 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable lysopcac180. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is lysoPCaC180_raw and QCstep1 var is lysoPCaC180
Real
lysoPCaC182_QCstep2 valid=0 LoD=01
New in R8. QCd metabolomics data (final) for lysoPhosphatidylcholine acyl C182 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.1 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable lysopcac182. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is lysoPCaC182_raw and QCstep1 var is lysoPCaC182
Real
lysoPCaC204_QCstep2 valid=0 LoD=002
New in R8. QCd metabolomics data (final) for lysoPhosphatidylcholine acyl C204 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.02 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable lysopcac204. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is lysoPCaC204_raw and QCstep1 var is lysoPCaC204
Real
PCaaC300_QCstep2 valid=0 LoD=02
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C300 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.2 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac300. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC300_raw and QCstep1 var is PCaaC300_i
Real
PCaaC320_QCstep2 valid=0 LoD=004
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C320 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.04 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac320. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC320_raw and QCstep1 var is PCaaC320_i
Real
PCaaC321_QCstep2 valid=0 LoD=006
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C321 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.06 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac321. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC321_raw and QCstep1 var is PCaaC321_i
Real
lysoPCaC261_QCstep2 valid=0 LoD=4
New in R8. QCd metabolomics data (final) for lysoPhosphatidylcholine acyl C261 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=4 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable lysopcac261. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is lysoPCaC261_raw and QCstep1 var is lysoPCaC261
Real
lysoPCaC160_QCstep2 valid=0 LoD=012
New in R8. QCd metabolomics data (final) for lysoPhosphatidylcholine acyl C160 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.12 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable lysopcac160. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is lysoPCaC160_raw and QCstep1 var is lysoPCaC160_i
Real
lysoPCaC181_QCstep2 valid=0 LoD=01
New in R8. QCd metabolomics data (final) for lysoPhosphatidylcholine acyl C181 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.1 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable lysopcac181. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is lysoPCaC181_raw and QCstep1 var is lysoPCaC181_i
Real
lysoPCaC203_QCstep2 valid=0 LoD=02
New in R8. QCd metabolomics data (final) for lysoPhosphatidylcholine acyl C203 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.2 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable lysopcac203. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is lysoPCaC203_raw and QCstep1 var is lysoPCaC203_i
Real
lysoPCaC240_QCstep2 valid=0 LoD=13
New in R8. QCd metabolomics data (final) for lysoPhosphatidylcholine acyl C240 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=1.3 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable lysopcac240. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is lysoPCaC240_raw and QCstep1 var is lysoPCaC240_i
Real
lysoPCaC260_QCstep2 valid=0 LoD=05
New in R8. QCd metabolomics data (final) for lysoPhosphatidylcholine acyl C260 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.5 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable lysopcac260. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is lysoPCaC260_raw and QCstep1 var is lysoPCaC260_i
Real
PCaaC322_QCstep2 valid=0 LoD=003
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C322 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.03 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac322. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC322_raw and QCstep1 var is PCaaC322_i
Real
PCaaC323_QCstep2 valid=0 LoD=0008
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C323 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.008 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac323. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC323_raw and QCstep1 var is PCaaC323_i
Real
PCaaC341_QCstep2 valid=0 LoD=006
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C341 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.06 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac341. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC341_raw and QCstep1 var is PCaaC341_i
Real
lysoPCaC280_QCstep2 valid=0 LoD=033
New in R8. QCd metabolomics data (final) for lysoPhosphatidylcholine acyl C280 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.33 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable lysopcac280. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is lysoPCaC280_raw and QCstep1 var is lysoPCaC280_i
Real
lysoPCaC281_QCstep2 valid=0 LoD=015
New in R8. QCd metabolomics data (final) for lysoPhosphatidylcholine acyl C281 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.15 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable lysopcac281. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is lysoPCaC281_raw and QCstep1 var is lysoPCaC281_i
Real
PCaaC342_QCstep2 valid=0 LoD=01
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C342 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.1 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac342. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC342_raw and QCstep1 var is PCaaC342_i
Real
PCaaC343_QCstep2 valid=0 LoD=001
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C343 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.01 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac343. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC343_raw and QCstep1 var is PCaaC343_i
Real
PCaaC344_QCstep2 valid=0 LoD=0006
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C344 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.006 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac344. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC344_raw and QCstep1 var is PCaaC344_i
Real
PCaaC360_QCstep2 valid=0 LoD=02
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C360 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.2 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac360. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC360_raw and QCstep1 var is PCaaC360_i
Real
PCaaC361_QCstep2 valid=0 LoD=003
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C361 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.03 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac361. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC361_raw and QCstep1 var is PCaaC361_i
Real
PCaaC362_QCstep2 valid=0 LoD=015
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C362 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.15 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac362. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC362_raw and QCstep1 var is PCaaC362_i
Real
PCaaC363_QCstep2 valid=0 LoD=004
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C363 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.04 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac363. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC363_raw and QCstep1 var is PCaaC363_i
Real
PCaaC364_QCstep2 valid=0 LoD=004
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C364 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.04 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac364. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC364_raw and QCstep1 var is PCaaC364_i
Real
PCaaC365_QCstep2 valid=0 LoD=001
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C365 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.01 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac365. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC365_raw and QCstep1 var is PCaaC365_i
Real
PCaaC366_QCstep2 valid=0 LoD=0015
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C366 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.015 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac366. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC366_raw and QCstep1 var is PCaaC366_i
Real
PCaaC380_QCstep2 valid=0 LoD=02
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C380 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.2 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac380. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC380_raw and QCstep1 var is PCaaC380_i
Real
PCaaC381_QCstep2 valid=0 LoD=008
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C381 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.08 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac381. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC381_raw and QCstep1 var is PCaaC381_i
Real
PCaaC383_QCstep2 valid=0 LoD=004
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C383 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.04 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac383. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC383_raw and QCstep1 var is PCaaC383_i
Real
PCaaC384_QCstep2 valid=0 LoD=003
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C384 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.03 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac384. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC384_raw and QCstep1 var is PCaaC384_i
Real
PCaaC385_QCstep2 valid=0 LoD=0015
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C385 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.015 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac385. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC385_raw and QCstep1 var is PCaaC385_i
Real
PCaaC386_QCstep2 valid=0 LoD=002
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C386 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.02 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac386. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC386_raw and QCstep1 var is PCaaC386_i
Real
PCaaC401_QCstep2 valid=0 LoD=04
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C401 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.4 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac401. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC401_raw and QCstep1 var is PCaaC401_i
Real
PCaaC402_QCstep2 valid=0 LoD=002
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C402 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.02 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac402. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC402_raw and QCstep1 var is PCaaC402_i
Real
PCaaC403_QCstep2 valid=0 LoD=0006
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C403 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.006 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac403. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC403_raw and QCstep1 var is PCaaC403_i
Real
PCaaC404_QCstep2 valid=0 LoD=001
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C404 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.01 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac404. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC404_raw and QCstep1 var is PCaaC404_i
Real
PCaaC405_QCstep2 valid=0 LoD=004
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C405 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.04 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac405. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC405_raw and QCstep1 var is PCaaC405_i
Real
PCaaC406_QCstep2 valid=0 LoD=12
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C406 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=1.2 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac406. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC406_raw and QCstep1 var is PCaaC406_i
Real
PCaaC420_QCstep2 valid=0 LoD=005
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C420 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.05 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac420. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC420_raw and QCstep1 var is PCaaC420_i
Real
PCaaC421_QCstep2 valid=0 LoD=0008
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C421 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.008 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac421. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC421_raw and QCstep1 var is PCaaC421_i
Real
PCaaC422_QCstep2 valid=0 LoD=0006
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C422 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.006 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac422. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC422_raw and QCstep1 var is PCaaC422_i
Real
PCaaC424_QCstep2 valid=0 LoD=0006
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C424 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.006 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac424. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC424_raw and QCstep1 var is PCaaC424_i
Real
PCaaC425_QCstep2 valid=0 LoD=005
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C425 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.05 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac425. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC425_raw and QCstep1 var is PCaaC425_i
Real
PCaaC426_QCstep2 valid=0 LoD=03
New in R8. QCd metabolomics data (final) for phosphatidylcholine diacyl C426 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.3 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaac426. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaaC426_raw and QCstep1 var is PCaaC426_i
Real
PCaeC300_QCstep2 valid=0 LoD=015
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C300 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.15 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec300. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC300_raw and QCstep1 var is PCaeC300_i
Real
PCaeC301_QCstep2 valid=0 LoD=002
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C301 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.02 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec301. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC301_raw and QCstep1 var is PCaeC301_i
Real
PCaeC302_QCstep2 valid=0 LoD=057
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C302 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.57 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec302. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC302_raw and QCstep1 var is PCaeC302_i
Real
PCaeC321_QCstep2 valid=0 LoD=0009
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C321 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.009 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec321. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC321_raw and QCstep1 var is PCaeC321_i
Real
PCaeC322_QCstep2 valid=0 LoD=002
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C322 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.02 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec322. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC322_raw and QCstep1 var is PCaeC322_i
Real
PCaeC340_QCstep2 valid=0 LoD=0017
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C340 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.017 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec340. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC340_raw and QCstep1 var is PCaeC340_i
Real
PCaeC341_QCstep2 valid=0 LoD=0012
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C341 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.012 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec341. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC341_raw and QCstep1 var is PCaeC341_i
Real
PCaeC342_QCstep2 valid=0 LoD=001
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C342 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.01 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec342. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC342_raw and QCstep1 var is PCaeC342_i
Real
PCaeC343_QCstep2 valid=0 LoD=0015
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C343 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.015 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec343. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC343_raw and QCstep1 var is PCaeC343_i
Real
PCaeC360_QCstep2 valid=0 LoD=012
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C360 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.12 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec360. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC360_raw and QCstep1 var is PCaeC360_i
Real
PCaeC361_QCstep2 valid=0 LoD=003
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C361 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.03 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec361. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC361_raw and QCstep1 var is PCaeC361_i
Real
PCaeC362_QCstep2 valid=0 LoD=001
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C362 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.01 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec362. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC362_raw and QCstep1 var is PCaeC362_i
Real
PCaeC363_QCstep2 valid=0 LoD=0007
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C363 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.007 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec363. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC363_raw and QCstep1 var is PCaeC363_i
Real
PCaeC364_QCstep2 valid=0 LoD=0013
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C364 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.013 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec364. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC364_raw and QCstep1 var is PCaeC364_i
Real
PCaeC365_QCstep2 valid=0 LoD=0012
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C365 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.012 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec365. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC365_raw and QCstep1 var is PCaeC365_i
Real
PCaeC380_QCstep2 valid=0 LoD=0066
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C380 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.066 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec380. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC380_raw and QCstep1 var is PCaeC380_i
Real
PCaeC381_QCstep2 valid=0 LoD=0015
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C381 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.015 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec381. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC381_raw and QCstep1 var is PCaeC381_i
Real
PCaeC382_QCstep2 valid=0 LoD=0018
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C382 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.018 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec382. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC382_raw and QCstep1 var is PCaeC382_i
Real
PCaeC383_QCstep2 valid=0 LoD=001
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C383 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.01 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec383. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC383_raw and QCstep1 var is PCaeC383_i
Real
PCaeC384_QCstep2 valid=0 LoD=0015
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C384 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.015 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec384. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC384_raw and QCstep1 var is PCaeC384_i
Real
PCaeC385_QCstep2 valid=0 LoD=001
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C385 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.01 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec385. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC385_raw and QCstep1 var is PCaeC385_i
Real
PCaeC386_QCstep2 valid=0 LoD=003
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C386 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.03 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec386. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC386_raw and QCstep1 var is PCaeC386_i
Real
PCaeC401_QCstep2 valid=0 LoD=006
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C401 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.06 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec401. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC401_raw and QCstep1 var is PCaeC401_i
Real
PCaeC402_QCstep2 valid=0 LoD=001
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C402 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.01 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec402. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC402_raw and QCstep1 var is PCaeC402_i
Real
PCaeC403_QCstep2 valid=0 LoD=0015
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C403 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.015 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec403. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC403_raw and QCstep1 var is PCaeC403_i
Real
PCaeC404_QCstep2 valid=0 LoD=01
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C404 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.1 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec404. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC404_raw and QCstep1 var is PCaeC404_i
Real
PCaeC405_QCstep2 valid=0 LoD=0006
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C405 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.006 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec405. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC405_raw and QCstep1 var is PCaeC405_i
Real
PCaeC406_QCstep2 valid=0 LoD=0025
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C406 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.025 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec406. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC406_raw and QCstep1 var is PCaeC406_i
Real
PCaeC420_QCstep2 valid=0 LoD=04
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C420 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.4 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec420. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC420_raw and QCstep1 var is PCaeC420_i
Real
PCaeC421_QCstep2 valid=0 LoD=003
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C421 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.03 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec421. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC421_raw and QCstep1 var is PCaeC421_i
Real
PCaeC422_QCstep2 valid=0 LoD=0006
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C422 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.006 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec422. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC422_raw and QCstep1 var is PCaeC422_i
Real
PCaeC423_QCstep2 valid=0 LoD=0006
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C423 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.006 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec423. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC423_raw and QCstep1 var is PCaeC423_i
Real
PCaeC424_QCstep2 valid=0 LoD=03
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C424 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.3 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec424. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC424_raw and QCstep1 var is PCaeC424_i
Real
PCaeC425_QCstep2 valid=0 LoD=13
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C425 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=1.3 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec425. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC425_raw and QCstep1 var is PCaeC425_i
Real
PCaeC443_QCstep2 valid=0 LoD=0006
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C443 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.006 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec443. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC443_raw and QCstep1 var is PCaeC443_i
Real
PCaeC445_QCstep2 valid=0 LoD=002
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C445 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.02 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec445. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC445_raw and QCstep1 var is PCaeC445_i
Real
PCaeC446_QCstep2 valid=0 LoD=009
New in R8. QCd metabolomics data (final) for phosphatidylcholine acyl-alkyl C446 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.09 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable pcaec446. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is PCaeC446_raw and QCstep1 var is PCaeC446_i
Real
SMC160_QCstep2 valid=0 LoD=003
New in R8. QCd metabolomics data (final) for shpingomyeline C160 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.03 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable smc160. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is SMC160_raw and QCstep1 var is SMC160_i
Real
SMC161_QCstep2 valid=0 LoD=001
New in R8. QCd metabolomics data (final) for shpingomyeline C161 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.01 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable smc161. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is SMC161_raw and QCstep1 var is SMC161_i
Real
SMC180_QCstep2 valid=0 LoD=007
New in R8. QCd metabolomics data (final) for shpingomyeline C180 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.07 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable smc180. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is SMC180_raw and QCstep1 var is SMC180_i
Real
SMC181_QCstep2 valid=0 LoD=001
New in R8. QCd metabolomics data (final) for shpingomyeline C181 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.01 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable smc181. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is SMC181_raw and QCstep1 var is SMC181_i
Real
SMC202_QCstep2 valid=0 LoD=0005
New in R8. QCd metabolomics data (final) for shpingomyeline C202 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.005 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable smc202. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is SMC202_raw and QCstep1 var is SMC202_i
Real
SMC240_QCstep2 valid=0 LoD=013
New in R8. QCd metabolomics data (final) for shpingomyeline C240 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.13 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable smc240. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is SMC240_raw and QCstep1 var is SMC240_i
Real
SMC241_QCstep2 valid=0 LoD=0035
New in R8. QCd metabolomics data (final) for shpingomyeline C241 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.035 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable smc241. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is SMC241_raw and QCstep1 var is SMC241_i
Real
SMOHC141_QCstep2 valid=0 LoD=0025
New in R8. QCd metabolomics data (final) for hydroxysphingomyeline C141 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.025 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable smohc141. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is SMOHC141_raw and QCstep1 var is SMOHC141_i
Real
SMOHC161_QCstep2 valid=0 LoD=0012
New in R8. QCd metabolomics data (final) for hydroxysphingomyeline C161 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.012 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable smohc161. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is SMOHC161_raw and QCstep1 var is SMOHC161_i
Real
SMOHC221_QCstep2 valid=0 LoD=0015
New in R8. QCd metabolomics data (final) for hydroxysphingomyeline C221 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.015 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable smohc221. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is SMOHC221_raw and QCstep1 var is SMOHC221_i
Real
SMOHC222_QCstep2 valid=0 LoD=001
New in R8. QCd metabolomics data (final) for hydroxysphingomyeline C222 - Metabolomics measures in a relative scale (uM) - validity=0 and LoD=0.01 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable smohc222. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is SMOHC222_raw and QCstep1 var is SMOHC222_i
Real
Hexose_QCstep2 valid=1 LoD=20
New in R8. QCd metabolomics data (final) for hexose - Metabolomics measures in a relative scale (uM) - validity=1 and LoD=20 based on Biocrates report - processed for analysis use -derived by 2-step QC process from raw variable hexose. Assayed in MRC HNR lab on plasma using Liquid Chromatography Mass Spec with batch correction via location-scale method after 1) normalisation of a Box-Cox type and 2) winsorisation based on overall mean +/- 5 x batch-specific standard deviation - see the Fenland document on metabolomics for more details) Raw var is Hexose_raw and QCstep1 var is Hexose_i
Real
None
Metabolomics Biocrates assay well position(s)
Text
OLINK assay BIRC2
Phase 1 OLINK assay data for target BIRC2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BLM hydrolase
Phase 1 OLINK assay data for target BLM hydrolase in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BLVRB
Phase 1 OLINK assay data for target BLVRB in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BMP-4
Phase 1 OLINK assay data for target BMP-4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BMP-6
Phase 1 OLINK assay data for target BMP-6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
BNF_BetaBlocker
Has the volunteer reported usage of Beta blockers on the general questionnaire as defined by the following BNF code: 2.4 or 2.12 or 6.1.2 This does not imply that the volunteer is not on betablockers if the code here is 0 since there are more BNF codes for betablocker. Please use variable BNF_Betablocker_Pateam instead as an accurate indication of betablocker use.
Categorical
BNF_LipidLowering
Has the participant reported usage of Lipid lowering agents as defined by the following BNF code: 2.12
Categorical
OralAntidiabetic
Has the participant reported usage of Oral antidiabetic agents as defined by the following BNF code: 6.1.2
Categorical
OLINK assay BNP
Phase 1 OLINK assay data for target BNP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BOC
Phase 1 OLINK assay data for target BOC in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BOC
Phase 1 OLINK assay data for target BOC in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Body fat percent consolidated
Derived variable from Anthro data. This is AD47_DEXA_body_fat_percent data if it is available (since this is better data) if not it is E_TANITA_BodyFatPcnt data.
Real
Body fat percent device
Derived variable from Anthro data. To clarify whether BodyFatPercent_Cons data is DEXA data (AD47_DEXA_body_fat_percent) or Tanita data (E_TANITA_BodyFatPcnt). (Indicates the type of device that was used for reporting body fat percent for BodyFatPercent_Cons).
Text
Body Fat Percent Cons Device
Phase 2 data. Derived variable from Anthro data. To clarify whether BodyFatPercent_Cons data is DEXA data (AD47_DEXA_body_fat_percent_P2) or Tanita data (E_TANITA_BodyFatPcnt_P2). (Indicates the type of device that was used for reporting body fat percent for BodyFatPercent_Cons_P2).
Real
Body Fat Percent Cons
Phase 2 data. Derived variable from Anthro data. This is AD47_DEXA_body_fat_percent_P2 data if it is available (since this is better data) if not it is E_TANITA_BodyFatPcnt_P2 data.
Real
None
Fenland phase 1 serum sample Beta Hydroxy Butyrate measurement in umol/L. Only 24 samples were analysed for a small substudy.
Real
Hours of bowling
Please indicate the average length of time (in hours) you spent doing the activity per episode. Avg duration of bowling (indoor lawn or 10-pin).
Integer
Hours of bowling hrs CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Avg duration of bowling (indoor lawn or 10-pin). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Bowling hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Avg duration of bowling (indoor lawn or 10-pin). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Bowling hrs
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in hours) you spent doing the activity per episode. Avg duration of bowling (indoor lawn or 10-pin). -1 = left blank. DO NOT USE THIS VARIABLE. Use bowlingHr_CLEAN_P2 instead.
Real
Minutes of bowling
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Avg duration of bowling (indoor lawn or 10-pin).
Integer
Minutes of bowling mins CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Avg duration of bowling (indoor lawn or 10-pin). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Bowling min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Avg duration of bowling (indoor lawn or 10-pin). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Bowling min
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Avg duration of bowling (indoor lawn or 10-pin). -1 = left blank. DO NOT USE THIS VARIABLE. Use bowlingMin_CLEAN_P2 instead.
Real
Frequency of bowling CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Bowling (indoor lawn or 10-pin). Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
bowling_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for bowling (mins)
Real
Cln variable: Bowling
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Bowling (indoor lawn or 10-pin). Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
bowling_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Bowling (indoor lawn or 10-pin). Data normalised to DE template 1 data.
Categorical
Bowling
Phase 2 data. Questionnaire reads D14. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks.Bowling. DO NOT USE THIS VARIABLE. Use bowling_CLEAN_P2 instead.
Real
Bowling
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Bowling (indoor lawn or 10-pin). Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of bowling DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Bowling (indoor lawn or 10-pin). Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in bowling_T2. Instead use bowling_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of bowling DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Bowling (indoor lawn or 10-pin). Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in bowling_T1. Instead use bowling_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
First Diastolic Blood Pressure Measurement
First Diastolic Blood Pressure Measurement - BPDia1 in mmHg/min
Integer
First Diastolic Blood Pressure
Phase 2 data. First Diastolic Blood Pressure Measurement - BPDia1 in mmHg/min
Real
Second Diastolic Blood Pressure Measurement
Second Diastolic Blood Pressure Measurement - BPDia2 in mmHg/min
Integer
Second Diastolic Blood Pressure
Phase 2 data. Second Diastolic Blood Pressure Measurement - BPDia2 in mmHg/min
Real
Third Diastolic Blood Pressure Measurement
Third Diastolic Blood Pressure Measurement -BPDia3 in mmHg/min
Integer
Third Diastolic Blood Pressure
Phase 2 data. Third Diastolic Blood Pressure Measurement -BPDia3 in mmHg/min
Real
First Pulse Rate Measurement
First Pulse Rate Measurement - BPPR1 in beats/min bpm
Integer
First Pulse Rate Measurement
Phase 2 data. First Pulse Rate Measurement - BPPR1 in beats/min bpm
Real
Second Pulse Rate Measurement
Second Pulse Rate Measuremen - BPPR2 in beats/min bpm
Integer
Second Pulse Rate Measurement
Phase 2 data. Second Pulse Rate Measuremen - BPPR2 in beats/min bpm
Real
Third Pulse Rate Measurement
Third Pulse Rate Measurement - BPPR3 in beats/min bpm
Integer
Third Pulse Rate Measurement
Phase 2 data. Third Pulse Rate Measurement - BPPR3 in beats/min bpm
Real
First Systolic Blood Pressure Measurement
First Systolic Blood Pressure Measurement - BPSys1 in mmHg/min
Integer
First Systolic Blood Pressure
Phase 2 data. First Systolic Blood Pressure Measurement - BPSys1 in mmHg/min
Real
Second Systolic Blood Pressure Measurement
Second Systolic Blood Pressure Measurement - BPSys2 in mmHg/min
Integer
Second Systolic Blood Pressure
Phase 2 data. Second Systolic Blood Pressure Measurement - BPSys2 in mmHg/min
Real
Third Systolic Blood Pressure Measurement
Third Systolic Blood Pressure Measuremen - BPSys3 in mmHg/min
Integer
Third Systolic Blood Pressure
Phase 2 data. Third Systolic Blood Pressure Measuremen - BPSys3 in mmHg/min
Real
White bread and rolls ERROR CODES CLEANED
Average use last year of White bread and rolls After cleaning this variable is renamed as WHITE_BREAD which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Brown bread and rolls ERROR CODES CLEANED
Average use last year of Brown bread and rolls After cleaning this variable is renamed as BROWN_BREAD which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Wholemeal bread and rolls ERROR CODES CLEANED
Average use last year of Wholemeal bread and rolls After cleaning this variable is renamed as WHOLEMEAL_BREAD which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Cream crackers cheese biscuits ERROR CODES CLEANED
Average use last year of Cream crackers cheese biscuits After cleaning this variable is renamed as CRACKERS which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Crispbread eg Ryvita ERROR CODES CLEANED
Average use last year of Crispbread eg Ryvita After cleaning this variable is renamed as CRISPBREAD which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
White bread and rolls
Average use last year of White bread and rolls. After cleaning this variable is renamed as WHITE_BREAD which is then used by the FETA program for analysis.
Categorical
White bread and rolls
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Brown bread and rolls
Average use last year of Brown bread and rolls. After cleaning this variable is renamed as BROWN_BREAD which is then used by the FETA program for analysis.
Categorical
Brown bread and rolls
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Wholemeal bread and rolls
Average use last year of Wholemeal bread and rolls. After cleaning this variable is renamed as WHOLEMEAL_BREAD which is then used by the FETA program for analysis.
Categorical
Wholemeal bread and rolls
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Cream crackers; cheese biscuits
Average use last year of Cream crackers cheese biscuits. After cleaning this variable is renamed as CRACKERS which is then used by the FETA program for analysis.
Categorical
Cream crackers; cheese biscuits
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Crispbread eg Ryvita
Average use last year of Crispbread eg Ryvita. After cleaning this variable is renamed as CRISPBREAD which is then used by the FETA program for analysis.
Categorical
Crispbread eg Ryvita
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
OLINK assay BST1
Phase 1 OLINK assay data for target BST1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BST2
Phase 1 OLINK assay data for target BST2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BTC
Phase 1 OLINK assay data for target BTC in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay BTN3A2
Phase 1 OLINK assay data for target BTN3A2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
C0_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C0_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=1 LoD=4. 2nd and final QC step on this var created new and final var BIOR_001.
Real
C10_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C10_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=1 LoD=0.16. 2nd and final QC step on this var created new and final var BIOR_020.
Real
C101_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C101_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.12. 2nd and final QC step on this var created new and final var BIOR_021.
Real
C102_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C102_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.04. 2nd and final QC step on this var created new and final var BIOR_022.
Real
C12_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C12_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=1 LoD=0.057. 2nd and final QC step on this var created new and final var BIOR_023.
Real
C121_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C121_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.2. 2nd and final QC step on this var created new and final var BIOR_025.
Real
C12DC_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C12DC_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.2. 2nd and final QC step on this var created new and final var BIOR_024.
Real
C14_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C14_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=1 LoD=0.03. 2nd and final QC step on this var created new and final var BIOR_026.
Real
C141_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C141_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.015. 2nd and final QC step on this var created new and final var BIOR_027.
Real
C141OH_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C141OH_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.015. 2nd and final QC step on this var created new and final var BIOR_028.
Real
C142_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C142_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.012. 2nd and final QC step on this var created new and final var BIOR_029.
Real
C142OH_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C142OH_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.015. 2nd and final QC step on this var created new and final var BIOR_030.
Real
C16_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C16_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=1 LoD=0.018. 2nd and final QC step on this var created new and final var BIOR_031.
Real
C161_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C161_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.06. 2nd and final QC step on this var created new and final var BIOR_032.
Real
C161OH_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C161OH_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.02. 2nd and final QC step on this var created new and final var BIOR_033.
Real
C162_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C162_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.008. 2nd and final QC step on this var created new and final var BIOR_034.
Real
C162OH_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C162OH_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.03. 2nd and final QC step on this var created new and final var BIOR_035.
Real
C16OH_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C16OH_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.015. 2nd and final QC step on this var created new and final var BIOR_036.
Real
C181OH_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C181OH_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. valid=0 LoD=0.023. 2nd and final QC step on this var created new and final var BIOR_039.
Real
C181_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C181_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. valid=0 LoD=0.04. 2nd and final QC step on this var created new and final var BIOR_038.
Real
C182_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C182_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. valid=0 LoD=0.009. 2nd and final QC step on this var created new and final var BIOR_040.
Real
C18_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C18_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. valid=1 LoD=0.02. 2nd and final QC step on this var created new and final var BIOR_037.
Real
OLINK assay C1QTNF1
Phase 1 OLINK assay data for target C1QTNF1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
C2_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C2_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=1 LoD=0.15. 2nd and final QC step on this var created new and final var BIOR_002.
Real
OLINK assay C2
Phase 1 OLINK assay data for target C2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
C3_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C3_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=1 LoD=0.08. 2nd and final QC step on this var created new and final var BIOR_003.
Real
C31_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C31_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.03. 2nd and final QC step on this var created new and final var BIOR_004.
Real
C3DCC4OH_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C3DCC4OH_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.09. 2nd and final QC step on this var created new and final var BIOR_014.
Real
C3DCMC5OH_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C3DCMC5OH_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.1. 2nd and final QC step on this var created new and final var BIOR_008.
Real
C3OH_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C3OH_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.05. 2nd and final QC step on this var created new and final var BIOR_005.
Real
C4_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C4_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=1 LoD=0.03. 2nd and final QC step on this var created new and final var BIOR_006.
Real
C41_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C41_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.03. 2nd and final QC step on this var created new and final var BIOR_007.
Real
c4OHPro_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable c4OHPro_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. 2nd and final QC step on this var created new and final var BIOA_029.
Real
C5_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C5_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=1 LoD=0.04. 2nd and final QC step on this var created new and final var BIOR_009.
Real
C51_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C51_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.04. 2nd and final QC step on this var created new and final var BIOR_010.
Real
C51DC_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C51DC_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.015. 2nd and final QC step on this var created new and final var BIOR_011.
Real
C5DCC6OH_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C5DCC6OH_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.035. 2nd and final QC step on this var created new and final var BIOR_012.
Real
C5MDC_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C5MDC_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.06. 2nd and final QC step on this var created new and final var BIOR_013.
Real
C61_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C61_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.035. 2nd and final QC step on this var created new and final var BIOR_016.
Real
C6C41DC_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C6C41DC_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=1 LoD=0.08. 2nd and final QC step on this var created new and final var BIOR_015.
Real
C7DC_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C7DC_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.035. 2nd and final QC step on this var created new and final var BIOR_017.
Real
C8_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C8_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=1 LoD=0.17. 2nd and final QC step on this var created new and final var BIOR_018.
Real
C9_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable C9_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. valid=0 LoD=0.04. 2nd and final QC step on this var created new and final var BIOR_019.
Real
OLINK assay CA12
Phase 1 OLINK assay data for target CA12 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CA13
Phase 1 OLINK assay data for target CA13 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CA14
Phase 1 OLINK assay data for target CA14 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CA1
Phase 1 OLINK assay data for target CA1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CA2
Phase 1 OLINK assay data for target CA2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CA3
Phase 1 OLINK assay data for target CA3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CA4
Phase 1 OLINK assay data for target CA4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CA5A
Phase 1 OLINK assay data for target CA5A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CA6
Phase 1 OLINK assay data for target CA6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CADM3
Phase 1 OLINK assay data for target CADM3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CAIX
Phase 1 OLINK assay data for target CAIX in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CALCA
Phase 1 OLINK assay data for target CALCA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Calcium 0 minutes
Serum Calcium measurement taken at 0 minutes in mmol/l
Real
Calcium 0 minutes
Phase 2 data. Serum Calcium measurement taken at 0 minutes in mmol/l
Real
calcium_channel_blocker
Phase 2 data. Binary variable indicating whether a drug from the calcium channel blocker class was prescribed. 0 = No; 1 = Yes;
Categorical
Calibn Quality
The quality of the AH treadmill trace:
Categorical
Quality of the AH treadmill trace
Phase 2 data. The quality of the AH treadmill trace: 1 = pass; 0 = fail;
Categorical
OLINK assay CALR
Phase 1 OLINK assay data for target CALR in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CAMKK1
Phase 1 OLINK assay data for target CAMKK1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CANT1
Phase 1 OLINK assay data for target CANT1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CAPG
Phase 1 OLINK assay data for target CAPG in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
CARadj
CARadj. Derived Intermediate not for general release. Data can be provided if necessary.
Real
OLINK assay CARHSP1
Phase 1 OLINK assay data for target CARHSP1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
CARMILES
CARMILES. Derived Intermediate not for general release. Data can be provided if necessary.
Real
OLINK assay CASP-3
Phase 1 OLINK assay data for target CASP-3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CASP-8
Phase 1 OLINK assay data for target CASP-8 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CBL
Phase 1 OLINK assay data for target CBL in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCDC80
Phase 1 OLINK assay data for target CCDC80 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL11
Phase 1 OLINK assay data for target CCL11 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL11
Phase 1 OLINK assay data for target CCL11 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL14
Phase 1 OLINK assay data for target CCL14 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL15
Phase 1 OLINK assay data for target CCL15 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL16
Phase 1 OLINK assay data for target CCL16 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL17
Phase 1 OLINK assay data for target CCL17 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL18
Phase 1 OLINK assay data for target CCL18 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL19
Phase 1 OLINK assay data for target CCL19 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL20
Phase 1 OLINK assay data for target CCL20 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL21
Phase 1 OLINK assay data for target CCL21 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL23
Phase 1 OLINK assay data for target CCL23 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL24
Phase 1 OLINK assay data for target CCL24 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL25
Phase 1 OLINK assay data for target CCL25 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL27
Phase 1 OLINK assay data for target CCL27 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL28
Phase 1 OLINK assay data for target CCL28 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL3
Phase 1 OLINK assay data for target CCL3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL3
Phase 1 OLINK assay data for target CCL3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL4
Phase 1 OLINK assay data for target CCL4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CCL5
Phase 1 OLINK assay data for target CCL5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD109
Phase 1 OLINK assay data for target CD109 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD160
Phase 1 OLINK assay data for target CD160 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD163
Phase 1 OLINK assay data for target CD163 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD164
Phase 1 OLINK assay data for target CD164 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD177
Phase 1 OLINK assay data for target CD177 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD1C
Phase 1 OLINK assay data for target CD1C in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD200R1
Phase 1 OLINK assay data for target CD200R1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD200
Phase 1 OLINK assay data for target CD200 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD207
Phase 1 OLINK assay data for target CD207 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD209
Phase 1 OLINK assay data for target CD209 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD244
Phase 1 OLINK assay data for target CD244 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD27
Phase 1 OLINK assay data for target CD27 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD28
Phase 1 OLINK assay data for target CD28 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD2AP
Phase 1 OLINK assay data for target CD2AP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD300LG
Phase 1 OLINK assay data for target CD300LG in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD302
Phase 1 OLINK assay data for target CD302 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD33
Phase 1 OLINK assay data for target CD33 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD38
Phase 1 OLINK assay data for target CD38 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD40
Phase 1 OLINK assay data for target CD40 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD40-L
Phase 1 OLINK assay data for target CD40-L in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD46
Phase 1 OLINK assay data for target CD46 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD48
Phase 1 OLINK assay data for target CD48 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD4
Phase 1 OLINK assay data for target CD4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD58
Phase 1 OLINK assay data for target CD58 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD59
Phase 1 OLINK assay data for target CD59 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD5
Phase 1 OLINK assay data for target CD5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD63
Phase 1 OLINK assay data for target CD63 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD69
Phase 1 OLINK assay data for target CD69 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD6
Phase 1 OLINK assay data for target CD6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD70
Phase 1 OLINK assay data for target CD70 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD74
Phase 1 OLINK assay data for target CD74 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD79B
Phase 1 OLINK assay data for target CD79B in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD83
Phase 1 OLINK assay data for target CD83 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD84
Phase 1 OLINK assay data for target CD84 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD8A
Phase 1 OLINK assay data for target CD8A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD93
Phase 1 OLINK assay data for target CD93 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD97
Phase 1 OLINK assay data for target CD97 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CD99L2
Phase 1 OLINK assay data for target CD99L2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CDCP1
Phase 1 OLINK assay data for target CDCP1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CDH15
Phase 1 OLINK assay data for target CDH15 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CDH17
Phase 1 OLINK assay data for target CDH17 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CDH1
Phase 1 OLINK assay data for target CDH1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CDH2
Phase 1 OLINK assay data for target CDH2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CDH3
Phase 1 OLINK assay data for target CDH3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CDH5
Phase 1 OLINK assay data for target CDH5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CDH6
Phase 1 OLINK assay data for target CDH6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CDHR5
Phase 1 OLINK assay data for target CDHR5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CDKN1A
Phase 1 OLINK assay data for target CDKN1A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CDNF
Phase 1 OLINK assay data for target CDNF in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CDON
Phase 1 OLINK assay data for target CDON in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CDSN
Phase 1 OLINK assay data for target CDSN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CEACAM1
Phase 1 OLINK assay data for target CEACAM1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CEACAM3
Phase 1 OLINK assay data for target CEACAM3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CEACAM5
Phase 1 OLINK assay data for target CEACAM5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CEACAM8
Phase 1 OLINK assay data for target CEACAM8 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Porridge; Readybrek ERROR CODES CLEANED
How often did you eat Porridge/ readybrek (one bowl) on average last year After cleaning this variable is renamed as PORRIDGE which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Breakfast cereal ERROR CODES CLEANED
How often did you eatbreakfast cereal (one bowl) on average last year After cleaning this variable is renamed as CEREAL which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Porridge; Readybrek
How often did you eat Porridge/ readybrek (one bowl) on average last year. After cleaning this variable is renamed as PORRIDGE which is then used by the FETA program for analysis.
Categorical
Porridge; Readybrek
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Breakfast cereal
How often did you eatbreakfast cereal (one bowl) on average last year. After cleaning this variable is renamed as CEREAL which is then used by the FETA program for analysis.
Categorical
Breakfast cereal
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
The text given must be translated into food code s using the cereal lookup list You can list up t
Variable derived by study staff from raw FFQ data for A5bCereal1Brand A5bCereal1Type A5bCereal2Brand and A5bCereal2Type.
Categorical
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
OLINK assay CES1
Phase 1 OLINK assay data for target CES1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CES2
Phase 1 OLINK assay data for target CES2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CETN2
Phase 1 OLINK assay data for target CETN2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CFC1
Phase 1 OLINK assay data for target CFC1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CFHR5
Phase 1 OLINK assay data for target CFHR5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CGA
Phase 1 OLINK assay data for target CGA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CHI3L1
Phase 1 OLINK assay data for target CHI3L1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CHIT1
Phase 1 OLINK assay data for target CHIT1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CHL1
Phase 1 OLINK assay data for target CHL1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Cholesterol 0 minutes
Serum Cholesterol measurement taken at 0 minutes in mmol/l
Real
Cholestrol 0 minutes
Phase 2 data. Serum Cholesterol measurement taken at 0 minutes in mmol/l
Real
Total cholesterol to HDL cholesterol ratio 0 minutes
Total cholesterol to HDL cholesterol ratio measurement taken at 0 minutes
Real
Total Chol to HDLChol ratio 0 min
Phase 2 data. Total cholestrol to HDL cholestrol ratio measurement taken at 0 minutes
Real
OLINK assay CHRDL2
Phase 1 OLINK assay data for target CHRDL2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Cit_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable Cit_raw. All values below detection limit set to 0. -7 = Internal standard undetectable (Concentration unreliable). The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. 2nd and final QC step on this var created new and final var BIOA_005.
Real
OLINK assay CKAP4
Phase 1 OLINK assay data for target CKAP4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLEC10A
Phase 1 OLINK assay data for target CLEC10A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLEC11A
Phase 1 OLINK assay data for target CLEC11A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLEC14A
Phase 1 OLINK assay data for target CLEC14A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLEC1A
Phase 1 OLINK assay data for target CLEC1A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLEC1B
Phase 1 OLINK assay data for target CLEC1B in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLEC4A
Phase 1 OLINK assay data for target CLEC4A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLEC4C
Phase 1 OLINK assay data for target CLEC4C in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLEC4D
Phase 1 OLINK assay data for target CLEC4D in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLEC4G
Phase 1 OLINK assay data for target CLEC4G in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLEC5A
Phase 1 OLINK assay data for target CLEC5A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLEC6A
Phase 1 OLINK assay data for target CLEC6A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLEC7A
Phase 1 OLINK assay data for target CLEC7A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLMP
Phase 1 OLINK assay data for target CLMP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLM-1
Phase 1 OLINK assay data for target CLM-1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLM-6
Phase 1 OLINK assay data for target CLM-6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLSPN
Phase 1 OLINK assay data for target CLSPN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLSTN1
Phase 1 OLINK assay data for target CLSTN1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLSTN2
Phase 1 OLINK assay data for target CLSTN2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLSTN3
Phase 1 OLINK assay data for target CLSTN3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CLUL1
Phase 1 OLINK assay data for target CLUL1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
None
Cleaned BMI calculated as weight in kilograms divided by height in meters squared from CL_HeightCM_P1 and CL_WeightKG_P1
Real
Cln variable: BMI
Phase 2 data. Cleaned BMI calculated as weight in kilograms divided by height in meters squared from CL_HeightCM_P2 and CL_WeightKG_P2. Recommended BMI Varible
Real
None
Cleaned Height in centimetres (if E_HeightCM_P1 not = to ALT_Height_P1
Real
None
Cleaned Height code 1=No measures; 2=DEXA height measurement from DEXA image
Real
Cln variable: Height code
Phase 2 data. Cleaned Height code 1 = No measures; 2 = DEXA height measurement from DEXA image
Categorical
Cln variable: Height
Phase 2 data. Cleaned Height in centimetres (if E_HeightCM_P2 not = to ALT_Height_P2
Real
None
Cleaned Weight in centimetres (if E_WeightCM_P1 not = to ALT_Weight_P1
Real
None
Cleaned Weight code 1=No measures; 2=DEXA Weight measurement from DEXA
Real
Cln variable: Weight code
Phase 2 data. Cleaned Weight code 1 = No measures; 2 = DEXA Weight measurement from DEXA
Categorical
Cln variable: Weight
Phase 2 data. Cleaned Weight in centimetres (if E_WeightCM_P2 not = to ALT_Weight_P2
Real
OLINK assay CNDP1
Phase 1 OLINK assay data for target CNDP1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CNTN1
Phase 1 OLINK assay data for target CNTN1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CNTN2
Phase 1 OLINK assay data for target CNTN2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CNTN4
Phase 1 OLINK assay data for target CNTN4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CNTN5
Phase 1 OLINK assay data for target CNTN5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CNTNAP2
Phase 1 OLINK assay data for target CNTNAP2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay COCH
Phase 1 OLINK assay data for target COCH in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay COL18A1
Phase 1 OLINK assay data for target COL18A1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay COL1A1
Phase 1 OLINK assay data for target COL1A1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay COL4A1
Phase 1 OLINK assay data for target COL4A1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay COL4A3BP
Phase 1 OLINK assay data for target COL4A3BP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay COLEC12
Phase 1 OLINK assay data for target COLEC12 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Hours of Combat sports
Please indicate the average length of time (in hours) you spent doing the activity per episode. Combat sports (martial arts boxing or wrestling).
Integer
Hours of Combat sports CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Combat sports (martial arts boxing or wrestling). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Combat sports hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Combat sports (martial arts boxing or wrestling). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Combat sports hrs
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in hours) you spent doing the activity per episode. Combat sports (martial arts boxing or wrestling). -1 = left blank. DO NOT USE THIS VARIABLE. Use CombatsSportsHr_CLEAN_P2 instead.
Real
Minutes of Combat sports
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Combat sports (martial arts boxing or wrestling).
Integer
Minutes of Combat sports CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Combat sports (martial arts boxing or wrestling). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Combat sports min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Combat sports (martial arts boxing or wrestling). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Combat sports min
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Combat sports (martial arts boxing or wrestling). -1 = left blank. DO NOT USE THIS VARIABLE. Use CombatsSportsMin_CLEAN_P2 instead.
Real
Frequency of Combat sports CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Combat sports (martial arts boxing or wrestling). Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
combatsSports_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for Combat sports
Real
Cln variable: Combat sports
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Combat sports (martial arts boxing or wrestling). Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
CombatsSports_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Combat sports (martial arts boxing or wrestling). Data normalised to DE template 1 data.
Categorical
Combat sports
Phase 2 data. Questionnaire reads D14. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Martial arts boxing or wrestling. DO NOT USE THIS VARIABLE. Use CombatsSports_CLEAN_P2 instead.
Real
Combat sports
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Combat sports (martial arts boxing or wrestling). Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Combat sports DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Combat sports (martial arts boxing or wrestling). Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in CombatsSports_T2. Instead use CombatsSports_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Combat sports DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Combat sports (martial arts boxing or wrestling). Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in CombatsSports_T1. Instead use CombatsSports_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Insulin NEFA comments
Phase 2 data. Lab comments relating to heparin samples used for insulin and NEFA analysis for phase 2
Text
Cmnt geocodeing Cln work postcode
Phase 2 data. Comment related to geocodeing of phase 2 cleaned work postcode
Text
COMMUTEtime
COMMUTEtime. Derived Intermediate not for general release. Data can be provided if necessary.
Real
COMMUTE_ACTMETS
Commute domain activity energy expenditure [net METhrs/d]
Real
Commute domain AEE
Phase 2 data. Derived with method 2. Commute domain activity energy expenditure net METhrs/d
Real
COMMUTE_METS
Commute domain energy expenditure [METhrs/d]
Real
Commute domain energy expenditure
Phase 2 data. Derived with method 2. Commute domain energy expenditure METhrs/d
Real
COMMUTE_PAEE
Commute domain activity energy expenditure [kJ/kg/d]
Real
Commute domain PAEE
Phase 2 data. Derived with method 2. Commute domain activity energy expenditure kJ/kg/d
Real
COMPadj
COMPadj. Derived Intermediate not for general release. Data can be provided if necessary.
Real
COMPDUR1
COMPDUR1. Derived Intermediate not for general release. Data can be provided if necessary.
Real
COMPDUR2
COMPDUR2. Derived Intermediate not for general release. Data can be provided if necessary.
Real
COMPDUR3
COMPDUR3. Derived Intermediate not for general release. Data can be provided if necessary.
Real
COMPDUR4
COMPDUR4. Derived Intermediate not for general release. Data can be provided if necessary.
Real
Hours of Competitive Running
Please indicate the average length of time (in hours) you spent doing the activity per episode. Competitive Running.
Integer
Hours of Competitive Running CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Competitive Running. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Competitive running hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Competitive Running. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Competitive Running hrs
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in hours) you spent doing the activity per episode. Competitive Running. -1 = left blank. DO NOT USE THIS VARIABLE. Use compRunHr_CLEAN_P2 instead.
Real
Minutes of Competitive Running
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Competitive Running.
Integer
Minutes of Competitive Running CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Competitive Running. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Competitive running min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Competitive Running. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Competitive Running min
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Competitive Running. -1 = left blank. DO NOT USE THIS VARIABLE. Use compRunMin_CLEAN_P2 instead.
Real
Frequency of Competitive Running CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Competitive Running. Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
compRun_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for Competitive Running
Real
Cln variable: Competitive running
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Competitive Running. Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
compRun_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Competitive Running. Data normalised to DE template 1 data.
Categorical
Competitive Running
Phase 2 data. Questionnaire reads D14. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Competitive Running. DO NOT USE THIS VARIABLE. Use compRun_CLEAN_P2 instead.
Real
Competitive Running
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Competitive Running. Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Competitive Running DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Competitive Running. Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in compRun_T2. Instead use compRun_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Competitive Running DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Competitive Running. Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in compRun_T1. Instead use compRun_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Computer use at weekday after 6pm
Computer use at home but not at work (eg internet email playstation Xbox Gameboy etc). Hours of home computer use per day on a weekday after 6 pm. Average over the last 4 weeks
Categorical
Cln variable: Computer wkday post6pm
Phase 2 data. Computer use at home but not at work (eg internet email playstation Xbox Gameboy and Wii; non-active games only). Hours of home computer use per day on a weekday after 6 pm. Average over the last 4 weeks. Data not quite the same as phase 1 data for Computerweekdaypost6pm. Error codes cleaned by DM team with this rule: RELATIVE. And then -10 error codes cleaned by PA team. 1 = none; 2 = less than 1 hr a day; 3 = 1 to 2 hrs a day; 4 = 2 to 3 hrs a day; 5 = 3 to 4 hrs a day; 6 = more than 4 hrs a day; -1 = left blank;
Categorical
Hrs homecomputer use wkday post 6pm
Phase 2 data. Questionnaire reads D3. Computer use at home but not at work (eg internet email playstation Xbox Gameboy and Wii; non-active games only). Hours of home computer use per day on a weekday after 6 pm. Average over the last 4 weeks. Data not quite the same as phase 1 data for Computerweekdaypost6pm. DO NOT USE THIS VARIABLE. Use Computerweekdaypost6pmDiff_CLEAN_P2 instead. 1 = none; 2 = less than 1 hr a day; 3 = 1 to 2 hrs a day; 4 = 2 to 3 hrs a day; 5 = 3 to 4 hrs a day; 6 = more than 4 hrs a day;
Categorical
Computer use at weekday after 6pm CLEANED
Computer use at home but not at work (eg internet email playstation Xbox Gameboy etc). Hours of home computer use per day on a weekday after 6 pm. Average over the last 4 weeks. Error codes cleaned by DM team with this rule: RELATIVE. And then -10 error codes cleaned by PA team.
Categorical
Computer use at weekday before 6pm
Computer use at home but not at work (eg internet email playstation Xbox Gameboy etc). Hours of home computer use per day on a weekday before 6 pm. Average over the last 4 weeks.
Categorical
Cln variable: Computer wkday pre6pm
Phase 2 data. Computer use at home but not at work (eg internet email playstation Xbox Gameboy and Wii; non-active games only). Hours of home computer use per day on a weekday before 6 pm. Average over the last 4 weeks. Data not quite the same as phase 1 data for Computerweekdaypre6pm. Error codes cleaned by DM team with this rule: RELATIVE. And then -10 error codes cleaned by PA team. 1 = none; 2 = less than 1 hr a day; 3 = 1 to 2 hrs a day; 4 = 2 to 3 hrs a day; 5 = 3 to 4 hrs a day; 6 = more than 4 hrs a day; -1 = left blank;
Categorical
Hrs home computer use wkday pre 6pm
Phase 2 data. Questionnaire reads D3. Computer use at home but not at work (eg internet email playstation Xbox Gameboy and Wii; non-active games only). Hours of home computer use per day on a weekday before 6 pm. Average over the last 4 weeks. Data not quite the same as phase 1 data for Computerweekdaypre6pm. DO NOT USE THIS VARIABLE. Use Computerweekdaypre6pmDiff_CLEAN_P2 instead. 1 = none; 2 = less than 1 hr a day; 3 = 1 to 2 hrs a day; 4 = 2 to 3 hrs a day; 5 = 3 to 4 hrs a day; 6 = more than 4 hrs a day;
Categorical
Computer use at weekday before 6pm CLEANED
Computer use at home but not at work (eg internet email playstation Xbox Gameboy etc). Hours of home computer use per day on a weekday before 6 pm. Average over the last 4 weeks. Error codes cleaned by DM team with this rule: RELATIVE. And then -10 error codes cleaned by PA team.
Categorical
Computer use at weekend after 6pm
Computer use at home but not at work (eg internet email playstation Xbox Gameboy etc). Hours of home computer use on a weekend after 6 pm. Average over the last 4 weeks.
Categorical
Cln variable: Computer wknd post6pm
Phase 2 data. Computer use at home but not at work (eg internet email playstation Xbox Gameboy and Wii; non-active games only). Hours of home computer use on a weekend after 6 pm. Average over the last 4 weeks. Data not quite the same as phase 1 data for Computerweekendpost6pm. Error codes cleaned by DM team with this rule: RELATIVE. And then -10 error codes cleaned by PA team. 1 = none; 2 = less than 1 hr a day; 3 = 1 to 2 hrs a day; 4 = 2 to 3 hrs a day; 5 = 3 to 4 hrs a day; 6 = more than 4 hrs a day; -1 = left blank;
Categorical
Hrs homecomputer use wknday post6pm
Phase 2 data. Questionnaire reads D3. Computer use at home but not at work (eg internet email playstation Xbox Gameboy and Wii; non-active games only). Hours of home computer use on a weekend after 6 pm. Average over the last 4 weeks. Data not quite the same as phase 1 data for Computerweekendpost6pm. DO NOT USE THIS VARIABLE. Use Computerweekendpost6pmDiff_CLEAN_P2 instead. 1 = none; 2 = less than 1 hr a day; 3 = 1 to 2 hrs a day; 4 = 2 to 3 hrs a day; 5 = 3 to 4 hrs a day; 6 = more than 4 hrs a day;
Categorical
Computer use at weekend after 6pm CLEANED
Computer use at home but not at work (eg internet email playstation Xbox Gameboy etc). Hours of home computer use on a weekend after 6 pm. Average over the last 4 weeks. Error codes cleaned by DM team with this rule: RELATIVE. And then -10 error codes cleaned by PA team.
Categorical
Computer use at weekend before 6pm
Computer use at home but not at work (eg internet email playstation Xbox Gameboy etc). Hours of home computer use per day on a weekend before 6 pm. Average over the last 4 weeks.
Categorical
Cln variable: Computer wknd pre6pm
Phase 2 data. Computer use at home but not at work (eg internet email playstation Xbox Gameboy and Wii; non-active games only). Hours of home computer use per day on a weekend before 6 pm. Average over the last 4 weeks. Data not quite the same as phase 1 data for Computerweekendpre6pm. Error codes cleaned by DM team with this rule: RELATIVE. And then -10 error codes cleaned by PA team. 1 = none; 2 = less than 1 hr a day; 3 = 1 to 2 hrs a day; 4 = 2 to 3 hrs a day; 5 = 3 to 4 hrs a day; 6 = more than 4 hrs a day; -1 = left blank;
Categorical
Hrs homecomputer use wknday pre 6pm
Phase 2 data. Questionnaire reads D3. Computer use at home but not at work (eg internet email playstation Xbox Gameboy and Wii; non-active games only). Hours of home computer use per day on a weekend before 6 pm. Average over the last 4 weeks. Data not quite the same as phase 1 data for Computerweekendpre6pm. DO NOT USE THIS VARIABLE. Use Computerweekendpre6pmDiff_CLEAN_P2 instead. 1 = none; 2 = less than 1 hr a day; 3 = 1 to 2 hrs a day; 4 = 2 to 3 hrs a day; 5 = 3 to 4 hrs a day; 6 = more than 4 hrs a day;
Categorical
Computer use at weekend before 6pm CLEANED
Computer use at home but not at work (eg internet email playstation Xbox Gameboy etc). Hours of home computer use per day on a weekend before 6 pm. Average over the last 4 weeks. Error codes cleaned by DM team with this rule: RELATIVE. And then -10 error codes cleaned by PA team.
Categorical
OLINK assay COMP
Phase 1 OLINK assay data for target COMP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay COMT
Phase 1 OLINK assay data for target COMT in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Hours of Conditioning Exercises
Please indicate the average length of time (in hours) you spent doing the activity per episode. Conditioning Exercises (eg using a bike or rowing machine).
Integer
Hours of Conditioning Exercises CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Conditioning Exercises (eg using a bike or rowing machine). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Conditioning exercise hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Conditioning Exercises (eg using a bike or rowing machine). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Conditioning Exercises hrs
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Conditioning Exercises (eg using a bike or rowing machine). -1 = left blank. DO NOT USE THIS VARIABLE. Use conditionExerciseHr_CLEAN_P2 instead.
Real
Minutes of Conditioning Exercises
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Conditioning Exercises (eg using a bike or rowing machine).
Integer
Minutes of Conditioning Exercises CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Conditioning Exercises (eg using a bike or rowing machine). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Conditioning exercise min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Conditioning Exercises (eg using a bike or rowing machine). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Conditioning Exercises min
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Conditioning Exercises (eg using a bike or rowing machine). -1 = left blank. DO NOT USE THIS VARIABLE. Use conditionExerciseMin_CLEAN_P2 instead.
Real
Frequency of Conditioning Exercises CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Conditioning Exercises (eg using a bike or rowing machine). Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
conditionExercise_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for Conditioning Exercises
Real
Cln variable: Conditioning exercise
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Conditioning Exercises (eg using a bike or rowing machine). Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
conditionExercise_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Conditioning Exercises (eg using a bike or rowing machine). Data normalised to DE template 1 data.
Categorical
Conditioning Exercises
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Conditioning Exercises (eg using a bike or rowing machine). DO NOT USE THIS VARIABLE. Use conditionExercise_CLEAN_P2 instead.
Real
Conditioning Exercises
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Conditioning Exercises (eg using a bike or rowing machine). Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Conditioning Exercises DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Conditioning Exercises (eg using a bike or rowing machine). Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in conditionExercise_T2. Instead use conditionExercise_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Conditioning Exercises DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Conditioning Exercises (eg using a bike or rowing machine). Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in conditionExercise_T1. Instead use conditionExercise_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Consent Form version
Consent Form version of the main consent form (all versions) not the restrospective consent form.
Text
Consent Form version date
Consent Form version date (as written) of the main consent form (all versions) not the restrospective consent form.
Date
Statement 1 consented
Statement 1 consented V1.2 I confirm that I have read and understood the information sheet for the above study version dated (x/y/z) and have had the opprtunity to ask questions. Other form versions: I confirm that I have read and understood the information sheet for the above study version (nr) dated (x/y/z) and have had the opprtunity to ask questions.
Categorical
Statements 1 to 5 consented
Statements 1 to 5 consented derived variable where a 1 has been assigned if statements 1-5 have all been initialled a 0 if not.
Categorical
Statements 1 to 9 consented
Statements 1 to 9 consented derived variable where a 1 has been assigned if statements 1-9 have all been initialled a 0 if not.
Categorical
Statement 2 consented
Statement 2 consented all consent form versions: I agree to having a physical examination and giving a sample of blood and urine for research in the Fenland Study.
Categorical
Statement 3 consented
Statement 3 consented all consent form versions: I understand that future research will only be undertaken on anonymous samples and will include genetic studies aimed at investigating the cause of diabetes and related diseases but that the results of these investigations are unlikely to have any implications for me pesonally. I understand that I will not benefit financially if this research leads to the development of a new treatment or medical test.
Categorical
Statement 4 consented
Statement 4 consented all consent form versions: I understand that my participation is voluntary and that I am free to withdraw at any time without giving any reason and without my medical care or legal rights being affected.
Categorical
Statement 5 consented
Statement 5 consented: consent form V1.2 and 2: I agree that samples I have given and the information gathered about me can be looked after and stored at the MRC Epidemiology Unit for use in future projects aimed at identifying the cause of diabetes obesity and their complications. Consent form V: at replaced by (the MRC Epi Unit) consent form V4: at the MRC Epidemiology Unit replaced by the MRC Epidemiology Unit University of Cambridge
Categorical
Statement 6 consented
Statement 6 consented all consent form versions I agree to be reapproached to consider participating in possible future studies on the basis of information gained from the Fenland study. I note that I will be provided with full information about these additional studies when and if I am reapproached.
Categorical
Statement 7 consented
Statement 7 consented all consent form versions I agree that my test results can be forwarded to my general practitioner.
Categorical
Statement 8 consented
Statement 8 consented: not present on consent form V1.2 covered by retrospective consent form V3. Consent form version 2 onwards: I understand that information held by the NHS and records maintained by the General Register office may be used to kep in touch with me and follow up on my health status.
Categorical
Statement 9 consented
Statement 9 consented: not present on consent form V1.2 covered by retrospective consent form V3. Consent form version 2 and 3 I am willing to allow access to my medical records and information from them to be analysed in strict confidence by researchers from the MRC Epidemiology Unit. Consent form version 4: statement changed to researchers from the MRC Epidemiology Unit University of Cambridge
Categorical
None
Has Consent form been completed fully.
Categorical
Participant's signature present
Participant's signature (present) on the main consent form (all versions) not the restrospective consent form.
Categorical
Participant's signature date as written
Participant's signature date (as written) on the main consent form (all versions) not the restrospective consent form.
Date
Researcher's signature present
Researcher's signature (present) on the main consent form (all versions) not the restrospective consent form.
Categorical
Researcher's signature comments
Researcher's signature comments on the main consent form (all versions) not the restrospective consent form.
Text
Retrospective Participant's signature
Retrospective consent Participant's signature. A retrospective consent form was only sent out to any participant who'd signed Consent form version 1.2 since that only contained 7 statements not 9.
Categorical
Retrospective Participant's signature date
Retrospective consent Participant's signature date. A retrospective consent form was only sent out to any participant who'd signed Consent form version 1.2 since that only contained 7 statements not 9.
Date
Retrospective witness signature date
Retrospective consent witness signature date. A retrospective consent form was only sent out to any participant who'd signed Consent form version 1.2 since that only contained 7 statements not 9.
Date
Retrospective witness signature
Retrospective consent witness signature. A retrospective consent form was only sent out to any participant who'd signed Consent form version 1.2 since that only contained 7 statements not 9.
Categorical
None
Researcher's signature date (as written) on the main consent form (all versions) not the restrospective consent form.
Text
Participant's signature comments
Participant's signature comments on the main consent form (all versions) not the restrospective consent form.
Text
Consent form signed and dated
Consent form signed and dated? Related to the main consent form (all versions) not the restrospective consent form.
Categorical
None
Unique random ID number assigned to samples on InfiniumCoreExome-24v1 chip for genetic SNP analysis.
None
Comments left by data analyst performing core exome data QC.
None
Indication if Core Exome data can be included in the dataset or not due to potential relatedness of participants
Corrected calcium 0 minutes
Corrected calcium measurement taken at 0 minutes in mmol/l
Real
Corrected calcium 0 minutes
Phase 2 data. Corrected calcium measurement taken at 0 minutes in mmol/l
Real
Supermarket count around home 1km buffer p1
Number of supermarkets around participants home postcode unit within a 1 kilometer Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Supermarket count around home 1km buffer p2
Number of supermarkets around participants home postcode unit within a 1 kilometer Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
Takeaway count around home 1km buffer p1
Number of takeaway outlets around participants home postcode unit within a 1 kilometer Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Takeaway count around home 1km buffer p2
Number of takeaway outlets around participants home postcode unit within a 1 kilometer Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
Supermarket count around home 1mile buffer p1
Number of supermarkets around participants home postcode unit within a 1 mile Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Supermarket count around home 1mile buffer p2
Number of supermarkets around participants home postcode unit within a 1 mile Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
Takeaway count around home 1mile buffer p1
Number of takeaway outlets around participants home postcode unit within a 1 mile Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Takeaway count around home 1mile buffer p2
Number of takeaway outlets around participants home postcode unit within a 1 mile Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
Supermarket count around home 400m buffer p1
Number of supermarket outlets around participants home postcode unit within a 400 meter Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Supermarket count around home 400m buffer p2
Number of supermarket outlets around participants home postcode unit within a 400 meter Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
Takeaway count around home 400m buffer p1
Number of takeaway outlets around participants home postcode unit within a 400 meter Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Takeaway count around home 400m buffer p2
Number of takeaway outlets around participants home postcode unit within a 400 meter Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
Supermarket count around home 800m buffer p1
Number of supermarkets around participants home postcode unit within a 800 meter Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Supermarket count around home 800m buffer p2
Number of supermarkets around participants home postcode unit within a 800 meter Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
Takeaway count around home 800m buffer p1
Number of takeaway outlets around participants home postcode unit within a 800 meter Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Takeaway count around home 800m buffer p2
Number of takeaway outlets around participants home postcode unit within a 800 meter Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
Supermarket count around work 1km buffer p1
Number of supermarkets around participants work postcode unit within a 1 kilometer Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Supermarket count around work 1km buffer p2
Number of supermarkets around participants work postcode unit within a 1 kilometer Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
Takeaway count around work 1km buffer p1
Number of takeaway outlets around participants work postcode unit within a 1 kilometer Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Takeaway count around work 1km buffer p2
Number of takeaway outlets around participants work postcode unit within a 1 kilometer Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
Supermarket count around work 1mile buffer p1
Number of supermarkets around participants work postcode unit within a 1 mile Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Supermarket count around work 1mile buffer p2
Number of supermarkets around participants work postcode unit within a 1 mile Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
Takeaway count around work 1mile buffer p1
Number of takeaway outlets around participants work postcode unit within a 1 mile Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Takeaway count around work 1mile buffer p2
Number of takeaway outlets around participants work postcode unit within a 1 mile Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
Supermarket count around work 400m buffer p1
Number of supermarket outlets around participants work postcode unit within a 400 meter Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Supermarket count around work 400m buffer p2
Number of supermarket outlets around participants work postcode unit within a 400 meter Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
Takeaway count around work 400m buffer p1
Number of takeaway outlets around participants work postcode unit within a 400 meter Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Takeaway count around work 400m buffer p2
Number of takeaway outlets around participants work postcode unit within a 400 meter Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
Supermarket count around work 800m buffer p1
Number of supermarkets around participants work postcode unit within a 800 meter Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Supermarket count around work 800m buffer p2
Number of supermarkets around participants work postcode unit within a 800 meter Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
Takeaway count around work 800m buffer p1
Number of takeaway outlets around participants work postcode unit within a 800 meter Euclidean buffer in phase 1. Variable for analyses relating to the food environment.
Real
Takeaway count around work 800m buffer p2
Number of takeaway outlets around participants work postcode unit within a 800 meter Euclidean buffer in phase 2. Variable for analyses relating to the food environment.
Real
OLINK assay CPA1
Phase 1 OLINK assay data for target CPA1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CPA2
Phase 1 OLINK assay data for target CPA2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CPB1
Phase 1 OLINK assay data for target CPB1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CPE
Phase 1 OLINK assay data for target CPE in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CPM
Phase 1 OLINK assay data for target CPM in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CPXM1
Phase 1 OLINK assay data for target CPXM1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CR2
Phase 1 OLINK assay data for target CR2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CRADD
Phase 1 OLINK assay data for target CRADD in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Creatinine_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable Creatinine_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. 2nd and final QC step on this var created new and final var BIOA_026.
Real
Creatinine 0 minutes
Serum Creatinine measurement taken at 0 minutes in umol/l
Real
Creatinine 0 minutes
Phase 2 data. Serum Creatinine measurement taken at 0 minutes in umol/l
Real
OLINK assay CRELD2
Phase 1 OLINK assay data for target CRELD2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CRHBP
Phase 1 OLINK assay data for target CRHBP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CRH
Phase 1 OLINK assay data for target CRH in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Hours of Cricket
Please indicate the average length of time (in hours) you spent doing the activity per episode. Cricket.
Integer
Hours of Cricket CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Cricket. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Cricket hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Cricket. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Cricket hrs
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in hours) you spent doing the activity per episode. Cricket. -1 = left blank. DO NOT USE THIS VARIABLE. Use cricketHr_CLEAN_P2 instead.
Real
Minutes of Cricket
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Cricket.
Integer
Minutes of Cricket CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Cricket. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Cricket min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Cricket. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Cricket min
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Cricket. -1 = left blank. DO NOT USE THIS VARIABLE. Use cricketMin_CLEAN_P2 instead.
Real
Frequency of Cricket CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Cricket. Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
cricket_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for Cricket
Real
Cln variable: Cricket
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Cricket. Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
cricket_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Cricket. Data normalised to DE template 1 data.
Categorical
Cricket
Phase 2 data. Questionnaire reads D14. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Cricket. DO NOT USE THIS VARIABLE. Use cricket_CLEAN_P2 instead.
Real
Cricket
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Cricket. Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Cricket DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Cricket. Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in cricket_T2. Instead use cricket_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Cricket DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Cricket. Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in cricket_T1. Instead use cricket_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
OLINK assay CRIM1
Phase 1 OLINK assay data for target CRIM1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CRIP2
Phase 1 OLINK assay data for target CRIP2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CRISP2
Phase 1 OLINK assay data for target CRISP2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CRKL
Phase 1 OLINK assay data for target CRKL in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CRNN
Phase 1 OLINK assay data for target CRNN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CRTAC1
Phase 1 OLINK assay data for target CRTAC1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CRTAM
Phase 1 OLINK assay data for target CRTAM in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CRX
Phase 1 OLINK assay data for target CRX in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CSF-1
Phase 1 OLINK assay data for target CSF-1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CSNK1D
Phase 1 OLINK assay data for target CSNK1D in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CST3
Phase 1 OLINK assay data for target CST3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CST5
Phase 1 OLINK assay data for target CST5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CST6
Phase 1 OLINK assay data for target CST6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CSTB
Phase 1 OLINK assay data for target CSTB in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CTF1
Phase 1 OLINK assay data for target CTF1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CTRC
Phase 1 OLINK assay data for target CTRC in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CTSC
Phase 1 OLINK assay data for target CTSC in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CTSD
Phase 1 OLINK assay data for target CTSD in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CTSF
Phase 1 OLINK assay data for target CTSF in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CTSH
Phase 1 OLINK assay data for target CTSH in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CTSL1
Phase 1 OLINK assay data for target CTSL1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CTSO
Phase 1 OLINK assay data for target CTSO in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CTSS
Phase 1 OLINK assay data for target CTSS in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CTSV
Phase 1 OLINK assay data for target CTSV in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CTSZ
Phase 1 OLINK assay data for target CTSZ in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CX3CL1
Phase 1 OLINK assay data for target CX3CL1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CXADR
Phase 1 OLINK assay data for target CXADR in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CXCL10
Phase 1 OLINK assay data for target CXCL10 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CXCL11
Phase 1 OLINK assay data for target CXCL11 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CXCL12
Phase 1 OLINK assay data for target CXCL12 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CXCL13
Phase 1 OLINK assay data for target CXCL13 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CXCL16
Phase 1 OLINK assay data for target CXCL16 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CXCL1
Phase 1 OLINK assay data for target CXCL1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CXCL1
Phase 1 OLINK assay data for target CXCL1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CXCL5
Phase 1 OLINK assay data for target CXCL5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CXCL6
Phase 1 OLINK assay data for target CXCL6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CXCL9
Phase 1 OLINK assay data for target CXCL9 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay CXL17
Phase 1 OLINK assay data for target CXL17 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
CYCLEadj
CYCLEadj. Derived Intermediate not for general release. Data can be provided if necessary.
Real
CYCLEMILES
CYCLEMILES. Derived Intermediate not for general release. Data can be provided if necessary.
Real
Hours of Cycling For Pleasure
Please indicate the average length of time (in hours) you spent doing the activity per episode. Cycling For Pleasure (not as a means of transport).
Integer
Hours of Cycling For Pleasure CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Cycling For Pleasure (not as a means of transport). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Cycling pleasure hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Cycling For Pleasure (not as a means of transport). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Real
Cycling for Pleasure hrs
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Cycling For Pleasure (not as a means of transport). -1 = left blank. DO NOT USE THIS VARIABLE. Use cyclePleasureHr_CLEAN_P2 instead.
Real
Minutes of Cycling For Pleasure
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Cycling For Pleasure (not as a means of transport).
Integer
Minutes of Cycling For Pleasure CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Cycling For Pleasure (not as a means of transport). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Cycling pleasure min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Cycling For Pleasure (not as a means of transport). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Cycling for Pleasure min
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Cycling For Pleasure (not as a means of transport). -1 = left blank. DO NOT USE THIS VARIABLE. Use cyclePleasureMin_CLEAN_P2 instead.
Real
Frequency of Cycling For Pleasure CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Cycling For Pleasure (not as a means of transport). Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
cyclePleasure_CLEAN_FRQ
New in R8.Cleaned translated frequency (per week) for Cycling For Pleasure
Real
Cln variable: Cycling pleasure
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Cycling For Pleasure (not as a means of transport). Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
cyclePleasure_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Cycling For Pleasure (not as a means of transport). Data normalised to DE template 1 data.
Categorical
Cycling for Pleasure
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Cycling For Pleasure (not as a means of transport). DO NOT USE THIS VARIABLE. Use cyclePleasure_CLEAN_P2 instead.
Real
Cycling for Pleasure
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Cycling For Pleasure (not as a means of transport). Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Cycling For Pleasure DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Cycling For Pleasure (not as a means of transport). Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in cyclePleasure_T2. Instead use cyclePleasure_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Cycling For Pleasure DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Cycling For Pleasure (not as a means of transport). Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in cyclePleasure_T1. Instead use cyclePleasure_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Hours of Racing Or Rough Terrain Cycling
Please indicate the average length of time (in hours) you spent doing the activity per episode. Racing Or Rough Terrain Cycling.
Integer
Hours of Racing Or Rough Terrain Cycling CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Racing Or Rough Terrain Cycling. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Racing hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Racing Or Rough Terrain Cycling. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Racing or Rough Terrain Cycling hrs
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Racing Or Rough Terrain Cycling. -1 = left blank. DO NOT USE THIS VARIABLE. Use cyclingRacingRoughHr_CLEAN_P2 instead.
Real
Minutes of Racing Or Rough Terrain Cycling
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Racing Or Rough Terrain Cycling.
Integer
Minutes of Racing Or Rough Terrain Cycling CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Racing Or Rough Terrain Cycling. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Racing min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Racing Or Rough Terrain Cycling. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Racing or Rough Terrain Cycling min
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Racing Or Rough Terrain Cycling. -1 = left blank. DO NOT USE THIS VARIABLE. Use cyclingRacingRoughMin_CLEAN_P2 instead.
Real
Frequency of Racing Or Rough Terrain Cycling CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Racing Or Rough Terrain Cycling. Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
cyclingRacingRough_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for Racing Or Rough Terrain Cycling
Real
Cln variable: Racing
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Racing Or Rough Terrain Cycling. Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
cyclingRacingRough_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Racing Or Rough Terrain Cycling. Data normalised to DE template 1 data.
Categorical
Racing or Rough Terrain Cycling
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Racing Or Rough Terrain Cycling. DO NOT USE THIS VARIABLE. Use cyclingRacingRough_CLEAN_P2 instead.
Real
Racing or Rough Terrain Cycling
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Racing Or Rough Terrain Cycling. Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Racing Or Rough Terrain Cycling DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Racing Or Rough Terrain Cycling. Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in cyclingRacingRough_T2. Instead use cyclingRacingRough_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Racing Or Rough Terrain Cycling DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Racing Or Rough Terrain Cycling. Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in cyclingRacingRough_T1. Instead use cyclingRacingRough_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
OLINK assay CYR61
Phase 1 OLINK assay data for target CYR61 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
C_Peptide
C_Peptide measurement in pmol/L. Raw data; cleaned data provided in variable G_C_Peptide with x_Threshold and x_Com variables provided for clarification.
Real
OLINK assay DAB2
Phase 1 OLINK assay data for target DAB2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DAG1
Phase 1 OLINK assay data for target DAG1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Single or sour cream (tablespoon) ERROR CODES CLEANED
Average use last year of Single or sour cream (tablespoon) After cleaning this variable is renamed as SINGLE_CREAM which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Double or clotted cream (tablespoon) ERROR CODES CLEANED
Average use last year of Low calorie low fat salad cream (tablespoon) After cleaning this variable is renamed as LOWCAL_SALAD_CREAM which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Low fat yogurt fromage frais (125g carton) ERROR CODES CLEANED
Average use last year of Salad Cream Mayonnaise (tablespoon) After cleaning this variable is renamed as SALAD_CREAM which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Full fat or Greek yogurt (125g carton) ERROR CODES CLEANED
Average use last year of French Dressing (tablespoon) After cleaning this variable is renamed as FRENCH which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Dairy desserts (125g carton) ERROR CODES CLEANED
Average use last year of Other Salad Dressing (tablespoon) After cleaning this variable is renamed as OTHER_DRESSING which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Cheese eg Cheddar Brie Edam(medium serving) ERROR CODES CLEANED
Average use last year on bread or vegetables of Butter (teaspoon) After cleaning this variable is renamed as BUTTER which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Cottage cheese low fat soft cheese(medium serving) ERROR CODES CLEANED
Average use last year on bread or vegetables of Hard margarine eg Stork Krona (teaspoon) After cleaning this variable is renamed as HARD_MARGARINE which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Eggs as boiled fried scrambled etc (one) ERROR CODES CLEANED
Average use last year on bread or vegetables of Polyunsaturated margarine eg Flora sunflower (teaspoon) After cleaning this variable is renamed as POLYUNSATURATED_MARGARINE which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Quiche (medium serving) ERROR CODES CLEANED
Average use last year on bread or vegetables of Other soft margarine eg Blue Band Stork SB (teaspoon) After cleaning this variable is renamed as OTHER_MARGARINE which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Low calorie low fat salad cream tablespoon
Average use last year of Low calorie low fat salad cream (tablespoon). After cleaning this variable is renamed as LOWCAL_SALAD_CREAM which is then used by the FETA program for analysis.
Categorical
Low calorie low fat salad cream (tablespoon) ERROR CODES CLEANED
Average use last year on bread or vegetables of Low fat spread eg Outline Gold After cleaning this variable is renamed as LOWFAT_SPREAD which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Low calorie low fat salad cream tablespoon
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Salad Cream Mayonnaise tablespoon
Average use last year of Salad Cream Mayonnaise (tablespoon). After cleaning this variable is renamed as SALAD_CREAM which is then used by the FETA program for analysis.
Categorical
Salad Cream; Mayonnaise (tablespoon) ERROR CODES CLEANED
Average use last year on bread or vegetables of Very low fat spread (teaspoon) After cleaning this variable is renamed as VERY_LOWFAT_SPREAD which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Salad Cream Mayonnaise tablespoon
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
French Dressing tablespoon
Average use last year of French Dressing (tablespoon). After cleaning this variable is renamed as FRENCH which is then used by the FETA program for analysis.
Categorical
French Dressing (tablespoon) ERROR CODES CLEANED
Average use last year of Double or clotted cream (tablespoon) After cleaning this variable is renamed as DOUBLE_CREAM which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
French Dressing tablespoon
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Other Salad Dressing tablespoon
Average use last year of Other Salad Dressing (tablespoon). After cleaning this variable is renamed as OTHER_DRESSING which is then used by the FETA program for analysis.
Categorical
Other Salad Dressing (tablespoon) ERROR CODES CLEANED
Average use last year of Quiche (medium serving) After cleaning this variable is renamed as QUICHE which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Other Salad Dressing tablespoon
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Butter teaspoon
Average use last year on bread or vegetables of Butter (teaspoon). After cleaning this variable is renamed as BUTTER which is then used by the FETA program for analysis.
Categorical
Butter (teaspoon) ERROR CODES CLEANED
Average use last year of Low fat yogurt fromage frais (125g carton) After cleaning this variable is renamed as LOWFAT_YOGURT which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Butter teaspoon
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Hard margarine eg Stork Krona teaspoon
Average use last year on bread or vegetables of Hard margarine eg. Stork Krona (teaspoon). After cleaning this variable is renamed as HARD_MARGARINE which is then used by the FETA program for analysis.
Categorical
Hard margarine eg Stork Krona (teaspoon) ERROR CODES CLEANED
Average use last year of Full fat or Greek yogurt (125g carton) After cleaning this variable is renamed as FULLFAT_YOGURT which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Hard margarine eg Stork Krona teaspoon
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Polyunsaturated margarine eg Flora sunflower teaspoon
Average use last year on bread or vegetables of Polyunsaturated margarine eg. Flora sunflower (teaspoon). After cleaning this variable is renamed as POLYUNSATURATED_MARGARINE which is then used by the FETA program for analys.
Categorical
Polyunsaturated margarine eg Flora sunflower (teaspoon) ERROR CODES CLEANED
Average use last year of Dairy desserts (125g carton) After cleaning this variable is renamed as DAIRY_DESSERT which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Polyunsaturated margarine eg Flora sunflower teaspoon
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Other soft margarine eg Blue Band Stork SB. teaspoon
Average use last year on bread or vegetables of Other soft margarine eg. Blue Band Stork S.B. (teaspoon). After cleaning this variable is renamed as OTHER_MARGARINE which is then used by the FETA program for analysis.
Categorical
Other soft margarine eg Blue Band Stork S.B. (teaspoon) ERROR CODES CLEANED
Average use last year of Cheese eg Cheddar Brie Edam (medium serving) After cleaning this variable is renamed as CHEESE which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Other soft margarine eg Blue Band Stork teaspoon
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Low fat spread; eg Outline; Gold
Average use last year on bread or vegetables of Low fat spread eg. Outline Gold. After cleaning this variable is renamed as LOWFAT_SPREAD which is then used by the FETA program for analysis.
Categorical
Low fat spread eg Outline Gold ERROR CODES CLEANED
Average use last year of Cottage cheese; low fat soft cheese (medium serving) Average use last year of Cottage cheese low fat soft cheese (medium serving) After cleaning this variable is renamed as COTTAGE_CHEESE which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Low fat spread; eg Outline; Gold
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Very low fat spread teaspoon
Average use last year on bread or vegetables of Very low fat spread (teaspoon). After cleaning this variable is renamed as VERY_LOWFAT_SPREAD which is then used by the FETA program for analysis.
Categorical
Very low fat spread (teaspoon) ERROR CODES CLEANED
Average use last year of Eggs as boiled fried scrambled etc (one) After cleaning this variable is renamed as EGGS which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Very low fat spread teaspoon
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Single or sour cream tablespoon
Average use last year of Single or sour cream (tablespoon). After cleaning this variable is renamed as SINGLE_CREAM which is then used by the FETA program for analysis.
Categorical
Single or sour cream tablespoon
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Double or clotted cream tablespoon
Average use last year of Double or clotted cream (tablespoon). After cleaning this variable is renamed as DOUBLE_CREAM which is then used by the FETA program for analysis.
Categorical
Double or clotted cream tablespoon
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Low fat yogurt fromage frais 125g carton
Average use last year of Low fat yogurt fromage frais (125g carton). After cleaning this variable is renamed as LOWFAT_YOGURT which is then used by the FETA program for analysis.
Categorical
Low fat yogurt fromage frais 125g carton
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Full fat or Greek yogurt 125g carton
Average use last year of Full fat or Greek yogurt (125g carton). After cleaning this variable is renamed as FULLFAT_YOGURT which is then used by the FETA program for analysis.
Categorical
Full fat or Greek yogurt 125g carton
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Dairy desserts 125g carton
Average use last year of Dairy desserts (125g carton). After cleaning this variable is renamed as DAIRY_DESSERT which is then used by the FETA program for analysis.
Categorical
Dairy desserts 125g carton
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Cheese eg Cheddar Brie Edam medium serving
Average use last year of Cheese eg. Cheddar Brie Edam (medium serving). After cleaning this variable is renamed as CHEESE which is then used by the FETA program for analysis.
Categorical
Cheese eg Cheddar Brie Edam medium serving
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Cottage cheese
Average use last year of Cottage cheese; low fat soft cheese (medium serving). Average use last year of Cottage cheese low fat soft cheese (medium serving). After cleaning this variable is renamed as COTTAGE_CHEESE which is then used by the FETA program for analysis.
Categorical
Cottage cheese
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Eggs as boiled; fried; scrambled etc one
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Eggs as boiled; fried; scrambled etc one
Average use last year of Eggs as boiled fried scrambled etc (one). After cleaning this variable is renamed as EGGS which is then used by the FETA program for analysis.
Categorical
Quiche medium serving
Average use last year of Quiche (medium serving). After cleaning this variable is renamed as QUICHE which is then used by the FETA program for analysis.
Categorical
Quiche medium serving
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Hours of Dancing
Please indicate the average length of time (in hours) you spent doing the activity per episode. Dancing (eg ballroom or disco).
Integer
Hours of Dancing CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Dancing (eg ballroom or disco). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Dancing hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Dancing (eg ballroom or disco). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Dancing hrs
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in hours) you spent doing the activity per episode. Dancing (eg ballroom or disco). -1 = left blank. DO NOT USE THIS VARIABLE. Use dancingHr_CLEAN_P2 instead.
Real
Minutes of Dancing
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Dancing (eg ballroom or disco).
Integer
Minutes of Dancing CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Dancing (eg ballroom or disco). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Dancing min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Dancing (eg ballroom or disco). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Dancing min
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Dancing (eg ballroom or disco). -1 = left blank. DO NOT USE THIS VARIABLE. Use dancingMin_CLEAN_P2 instead.
Real
Frequency of Dancing CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Dancing (eg ballroom or disco). Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
dancing_CLEAN_FRQ
New in R8.Cleaned translated frequency (per week) for Dancing
Real
Cln variable: Dancing
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Dancing (eg ballroom or disco). Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
dancing_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Dancing (eg ballroom or disco). Data normalised to DE template 1 data.
Categorical
Dancing
Phase 2 data. Questionnaire reads D14. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Dancing (eg ballroom or disco). DO NOT USE THIS VARIABLE. Use dancing_CLEAN_P2 instead.
Real
Dancing
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Dancing (eg ballroom or disco). Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Dancing DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Dancing (eg ballroom or disco). Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in dancing_T2. Instead use dancing_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Dancing DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Dancing (eg ballroom or disco). Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in dancing_T1. Instead use dancing_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
OLINK assay DAPP1
Phase 1 OLINK assay data for target DAPP1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Date Report Sent
Phase 2 data. Date participant feedback Report was sent
Date
Days AH worn
Number of days ActiHeart monitor was worn during free living (first wear of Actiheart only)
Integer
Days AH monitor worn free living
Phase 2 data. Number of days ActiHeart monitor was worn during free living (first wear of Actiheart only). Used for Study cooridination purposes not for analysis. Use wear varibles in main AH dataset for analysis.
Integer
OLINK assay DCBLD2
Phase 1 OLINK assay data for target DCBLD2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DCBLD2
Phase 1 OLINK assay data for target DCBLD2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DCN
Phase 1 OLINK assay data for target DCN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DCTN1
Phase 1 OLINK assay data for target DCTN1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DCTN2
Phase 1 OLINK assay data for target DCTN2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DDAH1
Phase 1 OLINK assay data for target DDAH1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DDC
Phase 1 OLINK assay data for target DDC in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DDR1
Phase 1 OLINK assay data for target DDR1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DDX58
Phase 1 OLINK assay data for target DDX58 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DECR1
Phase 1 OLINK assay data for target DECR1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DEFA1
Phase 1 OLINK assay data for target DEFA1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DEFB4A
Phase 1 OLINK assay data for target DEFB4A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Departure Time
Phase 2 data. Clinical visit departure time
Time
DEXA Bone Density
Manually entered Bone Density as measured by the DEXA in grams per centimetre cubed [NOT RELEASED]
Real
M_DEXAEnt
Phase 2 data. M_DEXAEnt NOT RELEASED
Categorical
DEXA method
Phase 2 data. DEXA method used for positioning of volunteer. No DEXA; Normal; Symmetry; 1/2 body;
Text
DEXA TScore
Manually entered T Score as measured by the DEXA [NOT RELEASED]
M_DEXAUsed
Phase 2 data. M_DEXAUsed NOT RELEASED
Categorical
DEXA ZScore
Manually entered Z Score as measured by the DEXA [NOT RELEASED]
DEXA App lean mass
New in R7. Data derived by data management team by adding up data for AD15_DEXA_arms_lean_mass and AD39_DEXA_legs_lean_mass and rounding to 2 decimals.
Integer
DEXA App lean mass
Phase 2 data. Data derived by data management team by adding up data for AD15_DEXA_arms_lean_mass and AD39_DEXA_legs_lean_mass and rounding to 2 decimals.
Real
DEXA Sample Check
Phase 2 data. DEXA CRF Check done? 0 = no; 1 = yes;
Categorical
Ethnicity used fo DEXA
Phase 2 data. Ethnicity used fo DEXA. For Dexa dataset only. Should not be used to indicate participant ethnicity. Use variables derived from general questionniare instead
Text
DEXA ethnicity
Phase 2 data. DEXA ethnicity enterd by operator. White; Asian; Black; Hispanic; Other; -9 = Missing data; -1 = Unable to be determined;
Real
DEXA ethnicity
Phase 2 data. DEXA ethnicity enterd at phase 2 by operator. White; Asian; Black; Hispanic; Other; -9 = Missing data; -1 = Unable to be determined;
Real
DEXA method
DEXA method used for positioning of volunteer. No DEXA; Normal; Symmetry; 1/2 body;
DEXA Periph fat mass
New in R7. Data derived by data management team by adding up data for AD14_DEXA_arms_fat_mass and AD38_DEXA_legs_fat_mass and rounding to 2 decimals.
Integer
DEXA Periph fat mass
Phase 2 data. Data derived by data management team by adding up data for AD14_DEXA_arms_fat_mass and AD38_DEXA_legs_fat_mass and rounding to 2 decimals.
Real
M_DEXAQCFail
Phase 2 data. M_DEXAQCFail NOT RELEASED
Categorical
M_DEXARevReq
Phase 2 data. M_DEXARevReq NOT RELEASED
Categorical
M_DEXAReviewed
Phase 2 data. M_DEXAReviewed NOT RELEASED
Categorical
OLINK assay DFFA
Phase 1 OLINK assay data for target DFFA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DGKZ
Phase 1 OLINK assay data for target DGKZ in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Diabetes Diagnosed
Phase 2 data. Particpant reported. Phase 2 participants were asked over the phone; when booking their clinical visits; if they had been diagnosed with diabetes since their phase 1 visit. For recruitment at baseline it was not asked because one of the exclusion criteria for recruitment was a diabetes diagnosis. 1 = Has been diagnosed with diabetes since baseline; 0 = not diagnosed with diabetes since baseline
Integer
Diabetes Status
Record of participants diabetes status at time of site visit.
Categorical
Diabetes Status
Phase 2 data. Diabetes status of participant. This was used for study coordiniation purposes and participant feedback. It should NOT be used for analysis. The definition of raised and normal was based on WHO guidlines at the time of the visit and would have changed part way through the study. Use Glucose and HBA1c results to derive diabetes staus for analysis. 1 = HbA1C and OGTT normal; 2 = HbA1C and OGTT Raised; 3 = HbA1C raised and OGTT normal; 4 = HbA1C normal and OGTT raised;
Categorical
OLINK assay DIABLO
Phase 1 OLINK assay data for target DIABLO in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Avg dist to closest 5 supermarkets home p1
Average distance to the closest 5 supermarkets from participants home postcode unit in phase 1. Variable for analyses relating to the food environment.
Real
Avg dist to closest 5 supermarkets home p2
Average distance to the closest 5 supermarkets from participants home postcode unit in phase 2. Variable for analyses relating to the food environment.
Real
Avg dist to closest 5 takeaways home p1
Average distance to the closest 5 takeaway food outlets from participants home postcode unit in phase 1. Variable for analyses relating to the food environment.
Real
Avg dist to closest 5 takeaways home p2
Average distance to the closest 5 takeaway food outlets from participants home postcode unit in phase 2. Variable for analyses relating to the food environment.
Real
Dist to closest supermarket home p1
Distance to the nearest supermarket from participants home postcode unit in phase 1. Variable for analyses relating to the food environment.
Real
Dist to closest supermarket home p2
Distance to the nearest supermarket from participants home postcode unit in phase 2. Variable for analyses relating to the food environment.
Real
Dist to closest takeaway home p1
Distance to the nearest takeaway food outlet from participants home postcode unit in phase 1. Variable for analyses relating to the food environment.
Real
Dist to closest takeaway home p2
Distance to the nearest takeaway food outlet from participants home postcode unit in phase 2. Variable for analyses relating to the food environment.
Real
Dist to closest supermarket work p1
Distance to the nearest supermarket from participants work postcode unit in phase 1. Variable for analyses relating to the food environment.
Real
Dist to closest supermarket work p2
Distance to the nearest supermarket from participants work postcode unit in phase 2. Variable for analyses relating to the food environment.
Real
Dist to closest takeaway work p1
Distance to the nearest takeaway food outlet from participants work postcode unit in phase 1. Variable for analyses relating to the food environment.
Real
Dist to closest takeaway work p2
Distance to the nearest takeaway food outlet from participants work postcode unit in phase 2. Variable for analyses relating to the food environment.
Real
Avg dist to closest 5 supermarkets work p1
Average distance to the closest 5 supermarkets from participants work postcode unit in phase 1. Variable for analyses relating to the food environment.
Real
Avg dist to closest 5 supermarkets work p2
Average distance to the closest 5 supermarkets from participants work postcode unit in phase 2. Variable for analyses relating to the food environment.
Real
Avg dist to closest 5 takeaways work p1
Average distance to the closest 5 takeaway food outlets from participants work postcode unit in phase 1. Variable for analyses relating to the food environment.
Real
Avg dist to closest 5 takeaways work p2
Average distance to the closest 5 takeaway food outlets from participants work postcode unit in phase 2. Variable for analyses relating to the food environment.
Real
DISTFACTOR
DISTFACTOR. Derived Intermediate not for general release. Data can be provided if necessary.
Real
DISTWORKMILES
DISTWORKMILES. Derived Intermediate not for general release. Data can be provided if necessary.
Real
diuretic
Phase 2 data. Binary variable indicating whether a drug from the diuretic class was prescribed. 0: No 1: Yes
Categorical
Hours of DIY
Please indicate the average length of time (in hours) you spent doing the activity per episode. DIY (eg carpentry home or car maintenance).
Integer
Hours of DIY CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. DIY (eg carpentry home or car maintenance). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: DIY hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. DIY (eg carpentry home or car maintenance). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
DIY hrs
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. DIY (eg carpentry home or car maintenance). -1 = left blank. DO NOT USE THIS VARIABLE. Use dIYHr_CLEAN_P2 instead.
Real
Minutes of DIY
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. DIY (eg carpentry home or car maintenance).
Integer
Minutes of DIY CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. DIY (eg carpentry home or car maintenance). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: DIY min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. DIY (eg carpentry home or car maintenance). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
DIY min
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. DIY (eg carpentry home or car maintenance). -1 = left blank. DO NOT USE THIS VARIABLE. Use dIYMin_CLEAN_P2 instead.
Real
Frequency of DIY CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. DIY (eg carpentry home or car maintenance). Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
dIY_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for DIY
Real
Cln variable: DIY
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. DIY (eg carpentry home or car maintenance). Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
dIY_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. DIY (eg carpentry home or car maintenance). Data normalised to DE template 1 data.
Categorical
DIY
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. DIY (eg carpentry home or car maintenance). DO NOT USE THIS VARIABLE. Use dIY_CLEAN_P2 instead.
Real
DIY
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. DIY (eg carpentry home or car maintenance). Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of DIY DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. DIY (eg carpentry home or car maintenance). Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in dIY_T2. Instead use dIY_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of DIY DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. DIY (eg carpentry home or car maintenance). Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in dIY_T1. Instead use dIY_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
OLINK assay DKK3
Phase 1 OLINK assay data for target DKK3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DKKL1
Phase 1 OLINK assay data for target DKKL1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay Dkk-1
Phase 1 OLINK assay data for target Dkk-1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay Dkk-4
Phase 1 OLINK assay data for target Dkk-4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DLK-1
Phase 1 OLINK assay data for target DLK-1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DLL1
Phase 1 OLINK assay data for target DLL1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DNAJB1
Phase 1 OLINK assay data for target DNAJB1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DNER
Phase 1 OLINK assay data for target DNER in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Dominant hand grip strength 1st
Phase 2 data. Dominant hand grip strength 1st measurement
Real
Dominant hand grip strength 2nd
Phase 2 data. Dominant hand grip strength 2nd measurement
Real
Dominant hand
Phase 2 data. Dominant hand. Left or right.
Text
OLINK assay DPEP1
Phase 1 OLINK assay data for target DPEP1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DPEP2
Phase 1 OLINK assay data for target DPEP2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DPP10
Phase 1 OLINK assay data for target DPP10 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DPP4
Phase 1 OLINK assay data for target DPP4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DPP6
Phase 1 OLINK assay data for target DPP6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DPP7
Phase 1 OLINK assay data for target DPP7 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DRAXIN
Phase 1 OLINK assay data for target DRAXIN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Tea (cup) ERROR CODES CLEANED
Average use last year of Tea (cup) After cleaning this variable is renamed as TEA which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Coffee instant or ground (cup) ERROR CODES CLEANED
Average use last year of Coffee instant or ground (cup) After cleaning this variable is renamed as INSTANT_COFFEE which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Coffee decaffeinated (cup) ERROR CODES CLEANED
Average use last year of Coffee decaffeinated (cup) After cleaning this variable is renamed as DECAFF_COFFEE which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Coffee whitener eg Coffee-mate (teaspoon) ERROR CODES CLEANED
Average use last year of Coffee whitener eg Coffee-mate (teaspoon) After cleaning this variable is renamed as COFFEE_WHITENER which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Cocoa hot chocolate (cup) ERROR CODES CLEANED
Average use last year of Cocoa hot chocolate (cup) After cleaning this variable is renamed as COCOA which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Horlicks Ovaltine (cup) ERROR CODES CLEANED
Average use last year of Horlicks Ovaltine (cup) After cleaning this variable is renamed as HORLICKS which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Wine (glass) ERROR CODES CLEANED
Average use last year of Wine (glass) After cleaning this variable is renamed as WINE which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Beer lager or cider (half pint) ERROR CODES CLEANED
Average use last year of Beer lager or cider (half pint) After cleaning this variable is renamed as BEER which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Port sherry vermouth liqueurs (glass) ERROR CODES CLEANED
Average use last year of Port sherry vermouth liqueurs (glass) After cleaning this variable is renamed as PORT which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Spirits; eg gin; brandy; whisky; vodka single
Average use last year of Spirits eg. gin brandy whisky vodka (single). After cleaning this variable is renamed as SPIRITS which is then used by the FETA program for analysis.
Categorical
Spirits eg gin brandy whisky vodka (single) ERROR CODES CLEANED
Average use last year of Spirits eg gin brandy whisky vodka (single) After cleaning this variable is renamed as SPIRITS which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Spirits; eg gin brandy whisky vodka single
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Low calorie or diet fizzy soft drinks glass
Average use last year of Low calorie or diet fizzy soft drinks (glass). After cleaning this variable is renamed as LOWCAL_FIZZY_DRINKS which is then used by the FETA program for analysis.
Categorical
Low calorie or diet fizzy soft drinks (glass) ERROR CODES CLEANED
Average use last year of Low calorie or diet fizzy soft drinks (glass) After cleaning this variable is renamed as LOWCAL_FIZZY_DRINKS which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Low calorie or diet fizzy soft drinks glass
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Fizzy soft drinks
Average use last year of Fizzy soft drinks eg. Coca cola lemonade (glass). After cleaning this variable is renamed as FIZZY_DRINKS which is then used by the FETA program for analysis.
Categorical
Fizzy soft drinks eg Coca cola lemonade(glass) ERROR CODES CLEANED
Average use last year of Fizzy soft drinks eg Coca cola lemonade (glass) After cleaning this variable is renamed as FIZZY_DRINKS which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Fizzy soft drinks
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Pure fruit juice 100% eg orange applejuice glass
Average use last year of Pure fruit juice (100%) eg. orange applejuice (glass). After cleaning this variable is renamed as FRUIT_JUICE which is then used by the FETA program for analysis.
Categorical
Pure fruit juice (100%) eg orange applejuice (glass) ERROR CODES CLEANED
Average use last year of Pure fruit juice (100%) eg orange applejuice (glass) After cleaning this variable is renamed as FRUIT_JUICE which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Pure fruit juice 100% orange juice glass
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Fruit squash or cordial glass
Average use last year of Fruit squash or cordial (glass). After cleaning this variable is renamed as FRUIT_SQUASH which is then used by the FETA program for analysis.
Categorical
Fruit squash or cordial (glass) ERROR CODES CLEANED
Average use last year of Fruit squash or cordial (glass) After cleaning this variable is renamed as FRUIT_SQUASH which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Fruit squash or cordial glass
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Tea cup
Average use last year of Tea (cup). After cleaning this variable is renamed as TEA which is then used by the FETA program for analysis.
Categorical
Tea cup
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Coffee instant or ground cup
Average use last year of Coffee instant or ground (cup). After cleaning this variable is renamed as INSTANT_COFFEE which is then used by the FETA program for analysis.
Categorical
Coffee instant or ground cup
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Coffee decaffeinated cup
Average use last year of Coffee decaffeinated (cup). After cleaning this variable is renamed as DECAFF_COFFEE which is then used by the FETA program for analysis.
Categorical
Coffee decaffeinated cup
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Coffee whitener eg Coffee-mate teaspoon
Average use last year of Coffee whitener eg Coffee-mate (teaspoon). After cleaning this variable is renamed as COFFEE_WHITENER which is then used by the FETA program for analysis.
Categorical
Coffee whitener
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Cocoa hot chocolate cup
Average use last year of Cocoa hot chocolate (cup). After cleaning this variable is renamed as COCOA which is then used by the FETA program for analysis.
Categorical
Cocoa hot chocolate cup
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Horlicks Ovaltine cup
Average use last year of Horlicks Ovaltine (cup). After cleaning this variable is renamed as HORLICKS which is then used by the FETA program for analysis.
Categorical
Horlicks Ovaltine cup
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Wine glass
Average use last year of Wine (glass). After cleaning this variable is renamed as WINE which is then used by the FETA program for analysis.
Categorical
Wine glass
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Beer lager or cider half pint
Average use last year of Beer lager or cider (half pint). After cleaning this variable is renamed as BEER which is then used by the FETA program for analysis.
Categorical
Beer lager or cider half pint
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Port sherry vermouth liqueurs glass
Average use last year of Port sherry vermouth liqueurs (glass). After cleaning this variable is renamed as PORT which is then used by the FETA program for analysis.
Categorical
Port sherry vermouth liqueurs glass
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
OLINK assay DSC2
Phase 1 OLINK assay data for target DSC2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DSG3
Phase 1 OLINK assay data for target DSG3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay DSG4
Phase 1 OLINK assay data for target DSG4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
DURATIONINI
DURATIONINI. Derived Intermediate not for general release. Data can be provided if necessary.
Real
DURATIONJOB
DURATIONJOB. Derived Intermediate not for general release. Data can be provided if necessary.
Real
DURATIONJOB1
DURATIONJOB1. Derived Intermediate not for general release. Data can be provided if necessary.
Real
DURATIONJOB2
DURATIONJOB2. Derived Intermediate not for general release. Data can be provided if necessary.
Real
DURATIONJOB3
DURATIONJOB3. Derived Intermediate not for general release. Data can be provided if necessary.
Real
DURATIONJOB4
DURATIONJOB4. Derived Intermediate not for general release. Data can be provided if necessary.
Real
DURATIONLEIS
DURATIONLEIS. Derived Intermediate not for general release. Data can be provided if necessary.
Real
DURCAR
DURCAR. Derived Intermediate not for general release. Data can be provided if necessary.
Real
DURCOMP
DURCOMP. Derived Intermediate not for general release. Data can be provided if necessary.
Real
DURCYCLE
DURCYCLE. Derived Intermediate not for general release. Data can be provided if necessary.
Real
DURJOB
DURJOB. Derived Intermediate not for general release. Data can be provided if necessary.
Real
DURPUBLIC
DURPUBLIC. Derived Intermediate not for general release. Data can be provided if necessary.
Real
DURSTAIRFLIGHT
DURSTAIRFLIGHT. Derived Intermediate not for general release. Data can be provided if necessary.
Real
DURTV
DURTV. Derived Intermediate not for general release. Data can be provided if necessary.
Real
DURWALK
DURWALK. Derived Intermediate not for general release. Data can be provided if necessary.
Real
OLINK assay DUSP3
Phase 1 OLINK assay data for target DUSP3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ECE1
Phase 1 OLINK assay data for target ECE1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
None
Name of the original ECG a file. This will be the same for 90percent the files. Some will have had the scan date added to the pdf file at a later date (but not to the txt or tif files).
Text
None
Name of folder where ECG scans a were stored. This probably is (but might not always be) the same as the foldername where they were moved to. Files could be just a pdf file or a pdf; a tif and a text file.
Text
None
Name of the original ECG b file. This will be the same for 90percent the files. Some will have had the scan date added to the pdf file at a later date (but not to the txt or tif files).
Text
None
Name of folder where ECG scans b were stored. This probably is (but might not always be) the same as the foldername where they were moved to. Files could be just a pdf file or a pdf; a tif and a text file.
Text
None
Name of the original ECG c file. This will be the same for 90percent the files. Some will have had the scan date added to the pdf file at a later date (but not to the txt or tif files).
Text
None
Name of folder where ECG scans c were stored. This probably is (but might not always be) the same as the foldername where they were moved to. Files could be just a pdf file or a pdf; a tif and a text file.
Text
None
Any comments regarding the ECG scans provided by the DM team
Text
None
Indication whether ECG paper outputfor phase 1 analysis has been scanned into an electronic file. Data entered is the name of the file. Since this contains the study ID number this variable should not be released. If left blank it hasn't been scanned yet.
None
Indication which team scanned the ECG paper output for phase 1 analysis.
OLINK assay EDA2R
Phase 1 OLINK assay data for target EDA2R in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EDAR
Phase 1 OLINK assay data for target EDAR in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EDIL3
Phase 1 OLINK assay data for target EDIL3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EFEMP1
Phase 1 OLINK assay data for target EFEMP1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EFNA4
Phase 1 OLINK assay data for target EFNA4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
EFT In house Complete
Phase 2 data. In House Executive Function test completed? 1 = yes;
Categorical
EFT Online Complete
Phase 2 data. Online Executive Function test completed? 0 = no; 1 = yes;
Categorical
OLINK assay EGFL7
Phase 1 OLINK assay data for target EGFL7 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EGFR
Phase 1 OLINK assay data for target EGFR in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EGF
Phase 1 OLINK assay data for target EGF in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EGLN1
Phase 1 OLINK assay data for target EGLN1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EIF4B
Phase 1 OLINK assay data for target EIF4B in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EIF4G1
Phase 1 OLINK assay data for target EIF4G1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EIF5A
Phase 1 OLINK assay data for target EIF5A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Electrodes
Data as entered on Study database. Electrodes used Arbo or Red dot
Text
Electrodes used Arbo or Red dot
Phase 2 data. Data as entered on Study database. Electrodes used Arbo or Red dot For study coordination purposes and QC only.
Text
EMPLOYED
EMPLOYED. Derived Intermediate not for general release. Data can be provided if necessary.
Categorical
OLINK assay ENAH
Phase 1 OLINK assay data for target ENAH in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
None
Phase 2 data.
Real
None
Phase 2 data.
Real
OLINK assay ENG
Phase 1 OLINK assay data for target ENG in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ENO2
Phase 1 OLINK assay data for target ENO2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ENPP2
Phase 1 OLINK assay data for target ENPP2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ENPP7
Phase 1 OLINK assay data for target ENPP7 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ENTPD2
Phase 1 OLINK assay data for target ENTPD2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ENTPD5
Phase 1 OLINK assay data for target ENTPD5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ENTPD6
Phase 1 OLINK assay data for target ENTPD6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ENTPD6
Phase 1 OLINK assay data for target ENTPD6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EN-RAGE
Phase 1 OLINK assay data for target EN-RAGE in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EPHA10
Phase 1 OLINK assay data for target EPHA10 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EPHA2
Phase 1 OLINK assay data for target EPHA2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EPHB4
Phase 1 OLINK assay data for target EPHB4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EPHB6
Phase 1 OLINK assay data for target EPHB6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EPO
Phase 1 OLINK assay data for target EPO in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay Ep-CAM
Phase 1 OLINK assay data for target Ep-CAM in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ERBB2IP
Phase 1 OLINK assay data for target ERBB2IP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ERBB2
Phase 1 OLINK assay data for target ERBB2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ERBB3
Phase 1 OLINK assay data for target ERBB3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ERBB4
Phase 1 OLINK assay data for target ERBB4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay EREG
Phase 1 OLINK assay data for target EREG in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ESAM
Phase 1 OLINK assay data for target ESAM in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ESM-1
Phase 1 OLINK assay data for target ESM-1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Events Book Entry
Phase 2 data. Was there an entry in the Adverse Events books related to the Phase 2 Clinical visit? 0 = no; 1 = yes;
Categorical
Hours of Exercise With Weights
Please indicate the average length of time (in hours) you spent doing the activity per episode. Exercise With Weights.
Integer
Hours of Exercise With Weights CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Exercise With Weights. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Exercise Weights hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Exercise With Weights. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Exercise With Weights hrs
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Exercise With Weights. -1 = left blank. DO NOT USE THIS VARIABLE. Use exerciseWeightsHr_CLEAN_P2 instead.
Real
Minutes of Exercise With Weights
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Exercise With Weights.
Integer
Minutes of Exercise With Weights CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Exercise With Weights. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Exercise Weights min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Exercise With Weights. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Exercise With Weights min
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Exercise With Weights. -1 = left blank. DO NOT USE THIS VARIABLE. Use exerciseWeightsMin_CLEAN_P2 instead.
Real
Frequency of Exercise With Weights CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Exercise With Weights. Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
exerciseWeights_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for Exercise With Weights
Real
Cln variable: Exercise Weights
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Exercise With Weights. Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
exerciseWeights_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Exercise With Weights. Data normalised to DE template 1 data.
Categorical
Exercise With Weights
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Exercise With Weights. DO NOT USE THIS VARIABLE. Use exerciseWeights_CLEAN_P2 instead.
Real
Exercise With Weights
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Exercise With Weights. CLEANED. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Exercise With Weights DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Exercise With Weights. Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in exerciseWeights_T2. Instead use exerciseWeights_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Exercise With Weights DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Exercise With Weights. Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in exerciseWeights_T1. Instead use exerciseWeights_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
ExomeID
Exome ID number. All samples on the Illumina exome chip have a exomeid. Having an exomeid does not guarantee having exome data. Only those marked as HasExomeData - 1 have exome data.
OLINK assay EZR
Phase 1 OLINK assay data for target EZR in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Anthro code
Coding of anthropometry team data. Request with E_AnthroComment for further information.
Anthro code
Phase 2 data. Coding of anthropometry team data. Request with E_AnthroComment for further information. 8 = Correct extreme value; 9 = poor quality data;
Real
Anthro Team Comment
Data provided by Anthropometry team. Comments provided by Anthro team on the data they have derived. Not available in release 1-5. Request with E_AnthroCode.
Text
Anthro Team Comment
Phase 2 data. Data provided by Anthropometry team. Comments provided by Anthro team on the data they have derived. Not available in release 1-5. Request with E_AnthroCode.
Text
Average of all hip measurements
Data provided by Anthropometry team. Average of all hip measurements. If 2 measurements were taken: (hip1+hip2)/2 and (hip1+hip2+hip3)/3 if a third measurement was taken.
Real
Average of all hip measurements
Phase 2 data. Data provided by Anthropometry team. Average of all hip measurements. If 2 measurements were taken: (hip1+hip2)/2 and (hip1+hip2+hip3)/3 if a third measurement was taken. -1 = Unable to be determined; -9 = Missing data;
Real
Average of all waist measurements
Data provided by Anthropometry team. Average of all waist measurements. If 2 measurements were taken: (waist1+waist2)/2 and (waist1+waist2+waist3)/3 if a third measurement was taken.
Real
Average of all Waist measurements
Phase 2 data. Data provided by Anthropometry team. Average of all waist measurements. If 2 measurements were taken: (waist1+waist2)/2 and (waist1+waist2+waist3)/3 if a third measurement was taken. -1 = Unable to be determined; -9 = Missing data;
Real
Body Fat percentage
New in R7. Data provided by Anthropometry team. Body Fat % derived by in house prediction equations based on impedance and anthropometry values which were validated against DEXA values. We used the following equations in men: 16.34649+(Ht2Im*0.6493159)+( Weight*0.1334669)-(AgeAtTest *0.0801411) ; and in women: 13.09247+(Ht2Im*0.6587483)+( Weight*0.0914326)-(AgeAtTest *0.0660596) to firstly generate fat free mass then fat mass was derived as follows : weight - fat free mass and % derived: fat mass / (weight/100) ; further information on the validity can be found by requesting the BIARegeneratedBodyFatPcnt document.pdf. (Ht2Im = height2/Impedance)
Real
Body Fat percentage
Phase 2 data. Data provided by Anthropometry team. Body Fat percent derived by in house prediction equations based on impedance and anthropometry values which were validated against DEXA values. The following equations were used in men: 16.34649+(Ht2Im*0.6493159)+( Weight*0.1334669)-(AgeAtTest *0.0801411) and in women: 13.09247+(Ht2Im*0.6587483)+( Weight*0.0914326)-(AgeAtTest *0.0660596) to generate fat free mass (Ht2Im = height2/Impedance). Fat mass (weight - fat free mass) then percentage body fat (fat mass / (weight/100)) were derived. Further information on the validity can be provided by requesting the BIARegeneratedBodyFatPcnt document. -1 = unable to be determined; -7 = 0 values replaced; -9 = Missing data;
Real
Body Mass Index
Data provided by Anthropometry team. BMI (E_Weight / E_Height Squared).
Real
Body Mass Index
Phase 2 data. Data provided by Anthropometry team. BMI (E_Weight / E_Height Squared). -1 = Unable to be determined;
Real
Height in cm
Data provided by Anthropometry team. Height measurement in centimetres. This is data from the study database which has been QCd by the Anthropometry team. Any data issues have been corrected by the study team. Data checking is performed by comparing data from the DEXA machine and the study db. Any discrepancies are flagged and resolved.
Real
Comment for Cln E_Height Data
Phase 2 data. Comment for phase 2 cleaned E_Height Data (in E_Height_Cl_P2) Provided by Anthropometry team.
Text
Cln variable: height data
Phase 2 data. Replaces data for E_Height_P2. Cleaned phase 2 data provided by Anthropometry team. Height measurement in centimetres (data source: either from E_Height_P2 or where missing or incorrect a height estimate was taken from the phase 2 DEXA scan). -9 = Missing data;
Real
Height measurement in centimetres
Phase 2 data. Data provided by Anthropometry team. Height measurement in centimetres. This is data from the study database which has been QCd by the Anthropometry team. Any data issues have been corrected by the study team. Data checking is performed by comparing data from the DEXA machine and the study db. Any discrepancies are flagged and resolved. -9 = Missing data; Replaced by E_Height_Cl_P2
Real
Hip 1
Data provided by Anthropometry team. First Hip Measurement in centimetres.
Real
First Hip Measurement
Phase 2 data. Data provided by Anthropometry team. First Hip Measurement in centimetres. -1 = Unable to be determined; -9 = Missing data;
Real
Hip 2
Data provided by Anthropometry team. Second Hip Measurement in centimetres.
Real
Second Hip Measurement
Phase 2 data. Data provided by Anthropometry team. Second Hip Measurement in centimetres. -1 = Unable to be determined; -9 = Missing data;
Real
Hip 3
Data provided by Anthropometry team. Third Hip Measurement in centimetres.
Real
Third Hip Measurement
Phase 2 data. Data provided by Anthropometry team. Third Hip Measurement in centimetres. -1 = Unable to be determined; -9 = Missing data;
Real
Anthro comment
Anthropometry team comment on the data.
Text
None
Phase 2 data. Info on DEXA scanner used for volunteer. 1 = Prodigy; 2 = Prodigy Advanced; 3 = iDEXA; -9 = No DEXA scan performed;
Categorical
Sex
Participants gender checked and cleaned by Anthropometry team. Available for participants with Anthro data only.
Categorical
Sex
Phase 2 data. Participants gender checked and cleaned by Anthropometry team. Available for participants with Anthro data only. M = male; F = female; -9 = Missing data;
Categorical
Body fat percent Tanita
Data provided by Anthropometry team. Body Fat% by BIA (Bioelectrical Impedance Analysis) devise.
Real
Body fat percent Tanita
Phase 2 data. Data provided by Anthropometry team. Body Fat% by BIA (Bioelectrical Impedance Analysis) devise. -1 = Unable to be determined; -9 = Missing data;
Real
Tanita Impedance
Data provided by Anthropometry team. Bioelectrical Impedance for the whole body (right foot to right hand) in Ohm.
Integer
Tanita Impedance
Phase 2 data. Data provided by Anthropometry team. Bioelectrical Impedance for the whole body (right foot to right hand) in Ohm. -1 = Unable to be determined; -9 = Missing data;
Integer
Tanita left arm impedance
Data provided by Anthropometry team. Bioelectrical Impedance for the left arm in Ohm.
Integer
Tanita left arm Impedance
Phase 2 data. Data provided by Anthropometry team. Bioelectrical Impedance for the left arm in Ohm. -1 = Unable to be determined; -9 = Missing data;
Integer
Tanita left leg impedance
Data provided by Anthropometry team. Bioelectrical Impedance for the left leg in Ohm. -1 = Unable to be determined; -9 = Missing data;
Integer
Tanita left leg Impedance
Phase 2 data. Data provided by Anthropometry team. Bioelectrical Impedance for the left leg in Ohm. -1 = Unable to be determined; -9 = Missing data;
Integer
Tanita right arm impedance
Data provided by Anthropometry team. Bioelectrical Impedance for the right arm in Ohm.
Integer
Tanita right arm Impedance
Phase 2 data. Data provided by Anthropometry team. Bioelectrical Impedance for the right arm in Ohm. -1 = Unable to be determined; -9 = Missing data;
Integer
Tanita right leg impedance
Data provided by Anthropometry team. Bioelectrical Impedance for the right leg in Ohm.
Integer
Tanita right leg Impedance
Phase 2 data. Data provided by Anthropometry team. Bioelectrical Impedance for the right leg in Ohm. -1 = Unable to be determined; -9 = Missing data;
Integer
Test date
Data provided by Anthropometry team. Date of Test (DOT).
Date
Test date
Phase 2 data. Data provided by Anthropometry team. Date of Test (DOT). -9 = Missing data;
Date
None
E_TestDate rounded to 0.1 years. E_TestDate: Data provided by Anthropometry team. Date of Test (DOT). -9 = Missing data;
Date
US left lateral
Data provided by Anthropometry team. Left lateral ultrasound measurement in centimetres (no longer in the updated protocol).
Real
US Right lateral
Data provided by Anthropometry team. Right lateral ultrasound measurement in centimetres (no longer in the updated protocol).
Real
Ultrasound Medial
Data provided by Anthropometry team. Medial (depth of visceral abdominal tissue) ultrasound measurement in centimetres.
Real
Ultrasound Medial
Phase 2 data. Data provided by Anthropometry team. Medial (depth of visceral abdominal tissue) ultrasound measurement in centimetres.
Real
Ultrasound Sub Cut
Data provided by Anthropometry team. Subcutaneous (Depth of abdominal subcutaneous tissue) ultrasound measurement in centimetres.
Real
Ultrasound Subcutaneous
Phase 2 data. Data provided by Anthropometry team. Subcutaneous (Depth of abdominal subcutaneous tissue) ultrasound measurement in centimetres.
Real
Waist 1
Data provided by Anthropometry team. First Waist Measurement in centimetres.
Real
First Waist Measurement
Phase 2 data. Data provided by Anthropometry team. First Waist Measurement in centimetres. -1 = Unable to be determined; -9 = Missing data;
Real
Waist 2
Data provided by Anthropometry team. Second Waist Measurement in centimetres.
Real
Second Waist Measurement
Phase 2 data. Data provided by Anthropometry team. Second Waist Measurement in centimetres. -1 = Unable to be determined; -9 = Missing data;
Real
Waist 3
Data provided by Anthropometry team. Third Waist Measurement in centimetres (appended only if waist 1 and 2 differed by greater than 3 cm).
Real
Third Waist Measurement
Phase 2 data. Data provided by Anthropometry team. Third Waist Measurement in centimetres (appended only if waist 1 and 2 differed by greater than 3 cm). -1 = Unable to be determined; -9 = Missing data;
Real
Waist to hip ratio
Phase 2 data. Waist to hip ratio. Data provided by Anthropometry team.
Real
Weight
Data provided by Anthropometry team. Weight measurement in kilograms. This is data from the study database which has been QCd by the Anthropometry team. Any data issues have been corrected by the study team. Data checking is performed by comparing data from the DEXA machine and the study db. Any discrepancies are flagged and resolved.
Real
Weight Device
Data provided by Anthropometry team. Equipment used to measure weight. No data available for participants not included in R6 or earlier.
Categorical
Weight measurement in kilograms
Phase 2 data. Data provided by Anthropometry team. Weight measurement in kilograms. -9 = Missing data;
Real
OLINK assay F11
Phase 1 OLINK assay data for target F11 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay F7
Phase 1 OLINK assay data for target F7 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FABP2
Phase 1 OLINK assay data for target FABP2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FABP4
Phase 1 OLINK assay data for target FABP4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FABP9
Phase 1 OLINK assay data for target FABP9 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
FAB ID number
FAB ID number identical to study number so will not be released
Text
OLINK assay FADD
Phase 1 OLINK assay data for target FADD in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
OLINK assay FAM19A5
Phase 1 OLINK assay data for target FAM19A5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FAM3B
Phase 1 OLINK assay data for target FAM3B in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FAM3C
Phase 1 OLINK assay data for target FAM3C in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FAP
Phase 1 OLINK assay data for target FAP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FASLG
Phase 1 OLINK assay data for target FASLG in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Fasted status for rest and treadmill test
Fasting status for rest and treadmill test.
Categorical
Fasting Sample Arm
Phase 2 data. Arm from which fasting blood sample was taken.
Text
Fasting Sample by
Phase 2 data. Initials/ID of staff member fasting blood sample was taken by
Text
Fasting Sample Site
Phase 2 data. Site of fasting sample blood sample taken
Text
OLINK assay FAS
Phase 1 OLINK assay data for target FAS in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
This question asks about the type of fat used most often for baking cakes etc There is a fats look-
Variable derived by study staff from raw FFQ data for A7aBakingFat and A7bOtherfat.
Categorical
This question asks about the type of fat used most often for frying roasting grilling etc There i
Variable derived by study staff from raw FFQ data for A6aFryingFat and A6bOtherfat.
Categorical
C10:0 QCd
QCd Plasma phospholipid Saturated Fatty Acid: Capric (C10:0). This variable contains the data from FA_C10_0 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C11:0 QCd
QCd Plasma phospholipid Saturated Fatty Acid: Undecylic (C11:0). This variable contains the data from FA_C11_0 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C12:0 QCd
QCd Plasma phospholipid Saturated Fatty Acid: Lauric (C12:0). This variable contains the data from FA_C12_0 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C13:0 QCd
QCd Plasma phospholipid Saturated Fatty Acid: Tridecylic (C13:0). This variable contains the data from FA_C13_0 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C14:0 QCd
QCd Plasma phospholipid Saturated Fatty Acid: Myristic (C14:0). This variable contains the data from FA_C14_0 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C14:1 QCd
QCd Plasma phospholipid Monounsaturated Fatty Acid: Myristoleic (C14:1). This variable contains the data from FA_C14_1 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
C15:0 QCd
QCd Plasma phospholipid Saturated Fatty Acid: Pentadecanoic (C15:0). This variable contains the data from FA_C15_0 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C15:1 QCd
QCd Plasma phospholipid Monounsaturated Fatty Acid: No name (C15:1). This variable contains the data from FA_C15_1 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C16:0 QCd
QCd Plasma phospholipid Saturated Fatty Acid: Palmitic (C16:0). This variable contains the data from FA_C16_0 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C16:1c QCd
QCd Plasma phospholipid Monounsaturated Fatty Acid: Palmitoleic (C16:1c). This variable contains the data from FA_C16_1c which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C16:1t QCd
QCd Plasma phospholipid Trans Fatty Acid: Trans Palmitoleic Acid (C16:1t). This variable contains the data from FA_C16_1t which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
C17:0 QCd
QCd Plasma phospholipid Saturated Fatty Acid: Heptadecanoic (C17:0). This variable contains the data from FA_C17_0 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C17:1 QCd
QCd Plasma phospholipid Monounsaturated Fatty Acid: no name (C17:1). This variable contains the data from FA_C17_1 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
C18:0 QCd
QCd Plasma phospholipid Saturated Fatty Acid: Stearic (C18:0). This variable contains the data from FA_C18_0 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C18:1n9c QCd
QCd Plasma phospholipid Monounsaturated Fatty Acid: Oleic (C18:1n9c). This variable contains the data from FA_C18_1n9c which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C18:1n9t QCd
QCd Plasma phospholipid Trans Fatty Acid: ElaidicAcid (C18:1n9t). This variable contains the data from FA_C18_1n9t which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C18:2n6c QCd
QCd Plasma phospholipid Omega-6 Polyunsaturated Fatty Acid: Linoleic (C18:2n6c). This variable contains the data from FA_C18_2n6c which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C18:2n6t QCd
QCd Plasma phospholipid Trans Fatty Acid: ConjugatedLinoleic (C18:2n6t). This variable contains the data from FA_C18_2n6t which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C18:3n3 QCd
QCd Plasma phospholipid Omega-3 Polyunsaturated Fatty Acid: AlphaLinolenic (C18:3n3). This variable contains the data from FA_C18_3n3 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C18:3n6 QCd
QCd Plasma phospholipid Omega-6 Polyunsaturated Fatty Acid: GammaLinolenic (C18:3n6). This variable contains the data from FA_C18_3n6 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
C20:0 QCd
QCd Plasma phospholipid Saturated Fatty Acid: Arachidic (C20:0). This variable contains the data from FA_C20_0 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
None
New for R8a. Data from phase 1 samples. c20:1n-9 gondoic acid - percent total phospholipid fatty acids; The raw un-QCd data is stored in FA_C20_1. The result is the percent of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in molpercent. -9 if the assay was attempted but the sample was insufficient
Real
None
New for R8a. Data from phase 1 samples. c20:2n-6 eicosadienoic acid - percent total phospholipid fatty acids;The raw un-QCd data is stored in FA_C20_2. The result is the percent of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in molpercent. -9 if the assay was attempted but the sample was insufficient
Real
C20:3n6 QCd
QCd Plasma phospholipid Omega-6 Polyunsaturated Fatty Acid: DihomoGammaLinolenic (C20:3n6). This variable contains the data from FA_C20_3n6 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C20:4n6_plus_C20:3n3 QCd
QCd Plasma phospholipid Omega-6 Polyunsaturated Fatty Acid: Arachidonic acid(20_4n6). + Eicosatrienoic Acid(20_3n3). (C20:4n6_plus_C20:3n3). This variable contains the data from FA_C20_4n6_C20_3n3 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C20:5n3 QCd
QCd Plasma phospholipid Omega-3 Polyunsaturated Fatty Acid: Eicosapentaenoic (C20:5n3). This variable contains the data from FA_C20_5n3 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
C21:0 QCd
QCd Plasma phospholipid Saturated Fatty Acid: Heneicosanoic (C21:0). This variable contains the data from FA_C21_0 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C22:0 QCd
QCd Plasma phospholipid Saturated Fatty Acid: Behenic (C22:0). This variable contains the data from FA_C22_0 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C22:1n9 QCd
QCd Plasma phospholipid Monounsaturated Fatty Acid: Erucic (C22:1n9). This variable contains the data from FA_C22_1n9 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
None
New for R8a. Data from phase 1 samples. c22:2n-6 docosadienoic acid - percent total phospholipid fatty acids; The raw un-QCd data is stored in FA_C22_2. The result is the percent of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in molpercent. -9 if the assay was attempted but the sample was insufficient
Real
None
New for R8a. Data from phase 1 samples. c22:4n-6 adrenic acid - percent total phospholipid fatty acids; The raw un-QCd data is stored in FA_C21_0. The result is the percent of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in molpercent. -9 if the assay was attempted but the sample was insufficient
Real
C22:5n3 QCd
QCd Plasma phospholipid Omega-3 Polyunsaturated Fatty Acid: Docosapenteanoic (C22:5n3). This variable contains the data from FA_C22_5n3 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C22:5n6 QCd
QCd Plasma phospholipid Omega-6 Polyunsaturated Fatty Acid: Docosapentenoic (C22:5n6). This variable contains the data from FA_C22_5n6 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C22:6n3 QCd
QCd Plasma phospholipid Omega-3 Polyunsaturated Fatty Acid: Docosahexaenoic (C22:6n3). This variable contains the data from FA_C22_6n3 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
C23:0 QCd
QCd Plasma phospholipid Saturated Fatty Acid: Tricosanoic (C23:0). This variable contains the data from FA_C23_0 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C24:0 QCd
QCd Plasma phospholipid Saturated Fatty Acid: Lignoceric (C24:0). This variable contains the data from FA_C24_0 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
C24:1 QCd
QCd Plasma phospholipid Monounsaturated Fatty Acid: Nervonic (C24:1). This variable contains the data from FA_C24_1 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
C8:0 QCd
QCd Plasma phospholipid Saturated Fatty Acid: Caprylic (C8:0). This variable contains the data from FA_C8_0 which passed our QC steps. The result is the % of the peak area for this fatty acid of the total peak area for all 38 fatty acids measured in mol%
Real
OLINK assay FBP1
Phase 1 OLINK assay data for target FBP1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FCAR
Phase 1 OLINK assay data for target FCAR in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FCER2
Phase 1 OLINK assay data for target FCER2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FCGR2A
Phase 1 OLINK assay data for target FCGR2A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FCGR3B
Phase 1 OLINK assay data for target FCGR3B in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FCN2
Phase 1 OLINK assay data for target FCN2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FCRL1
Phase 1 OLINK assay data for target FCRL1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FcRL2
Phase 1 OLINK assay data for target FcRL2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FCRL3
Phase 1 OLINK assay data for target FCRL3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FCRL5
Phase 1 OLINK assay data for target FCRL5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FCRL6
Phase 1 OLINK assay data for target FCRL6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FCRLB
Phase 1 OLINK assay data for target FCRLB in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Ferritin_Comment
Comment provided by lab on ferritin lab measurement data
Ferritin_Date_Analysed
Date sample was analysed for ferritin
OLINK assay FES
Phase 1 OLINK assay data for target FES in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FETUB
Phase 1 OLINK assay data for target FETUB in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
General comments
Comments entered on FFQ form. Not mapped to FETA variable since not used by FETA.
Text
FFQ Q version number
Version number of the FFQ completed by the participant.
Text
None
Fenland phase 1 serum sample Fibroblast Growth Factor 21 measurement in pg/ml. Only 24 samples were analysed for a small substudy.
Real
OLINK assay FGF2
Phase 1 OLINK assay data for target FGF2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FGFR2
Phase 1 OLINK assay data for target FGFR2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FGF-19
Phase 1 OLINK assay data for target FGF-19 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FGF-21
Phase 1 OLINK assay data for target FGF-21 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FGF-21
Phase 1 OLINK assay data for target FGF-21 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FGF-21
Phase 1 OLINK assay data for target FGF-21 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FGF-23
Phase 1 OLINK assay data for target FGF-23 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FGF-23
Phase 1 OLINK assay data for target FGF-23 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FGF-5
Phase 1 OLINK assay data for target FGF-5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FGF-BP1
Phase 1 OLINK assay data for target FGF-BP1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FGR
Phase 1 OLINK assay data for target FGR in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
factor H
Complement Factor H. Data produced by UCL from blood samples.
Real
SiblingTotalText
How many brothers and sisters do or did you have (Please do not include any adopted family members or step-brothers/sisters/parents). For data entry: enter all text as is and where ? used = female ? = male
Text
No of brothers and sisters
Phase 2 data. How many brothers and sisters do or did you have (Please do not include any adopted family members or step-brothers/sisters/parents). For data entry: enter all text as is and where ? used = female ? = male
Text
SisterTotal
Total number of sisters. Please do not include step-sisters. For data entry: Enter number as is. NB this number should be interpreted based on the full text in the previous variable - SiblingTotaltext.
Integer
No of sisters
Phase 2 data. Total number of sisters. Please do not include step-sisters. For data entry: Enter number as is. NB this number should be interpreted based on the full text in the previous variable - SiblingTotaltext. -1 = no number of sister or brother given
Real
BrotherTotal
Total number of brothers. Please do not include step-brothers. For data entry: Enter number as is. NB this number should be interpreted based on the full text in the previous variable - SiblingTotaltext.
Integer
No of brothers
Phase 2 data. Total number of brothers. Please do not include step-brothers. For data entry: Enter number as is. NB this number should be interpreted based on the full text in the previous variable - SiblingTotaltext.-1 = no number of sister or brother given
Real
MotherDiabetic
Mother has/had diabetes. Please do not include step-mother. Please do not include gestational diabetes.
Categorical
Mother diabetes has/had
Phase 2 data. Mother has/had diabetes. Please do not include step-mother. Please do not include gestational diabetes. 2 = yes; 3 = No; 4 = Not known; -1 = left blank; -10 = answer plus additional text;
Categorical
MotherAge
Approximate age at diabetes diagnosis of mother.
Categorical
Age mother at diabetes diagnosis
Phase 2 data. Approximate age at diabetes diagnosis of mother. 1 = <10; 2 = 10-19; 3 = 20-29; 4 = 30-39; 5 = 40-49; 6 = 50-59; 7 = 60-69; 8 = 70+; 9 = Not known; -1 = left blank; -5 = more than one selected;
Categorical
FatherDiabetic
Father has/had diabetes. Please do not include step-father. Please do not include gestational diabetes.
Categorical
Father diabetes has/had
Phase 2 data. Father has/had diabetes. Please do not include step-father. Please do not include gestational diabetes. 2 = yes; 3 = No; 4 = Not known; -1 = left blank; -10 = answer plus additional text;
Categorical
FatherAge
Approximate age at diabetes diagnosis of father.
Categorical
Age father at diabetes diagnosis
Phase 2 data. Approximate age at diabetes diagnosis of father. 1 = <10; 2 = 10-19; 3 = 20-29; 4 = 30-39; 5 = 40-49; 6 = 50-59; 7 = 60-69; 8 = 70+; 9 = Not known; -1 = left blank; -5 = more than one selected;
Categorical
Type of sibling 01
Phase 2 data. Type of sibling 01. 1 = sister; 2 = brother; 3 = half sister; 4 = half brother; -1 = left blank; -7 = sibling type not on questionnaire; -10 = answer plus additional text;
Categorical
Sibling01Diabetic
Sibling 10 has/had diabetes. Please do not include gestational diabetes.
Categorical
Sibling 01 has/had diabetes
Phase 2 data. Sibling 01 has/had diabetes. Please do not include gestational diabetes. 2 = yes; 3 = No; 4 = Not known; -1 = left blank; -10 = answer plus additional text;
Categorical
Sibling01Age
Approximate age at diabetes diagnosis of sibling 01.
Categorical
Age Sibling 01 at diabetes diag
Phase 2 data. Approximate age at diabetes diagnosis of sibling 01. 1 = <10; 2 = 10-19; 3 = 20-29; 4 = 30-39; 5 = 40-49; 6 = 50-59; 7 = 60-69; 8 = 70+; 9 = Not known; -1 = left blank; -5 = more than one selected;
Categorical
Type of sibling 02
Phase 2 data. Type of sibling 02. 1 = sister; 2 = brother; 3 = half sister; 4 = half brother; -1 = left blank; -7 = sibling type not on questionnaire; -10 = answer plus additional text;
Categorical
Sibling02Diabetic
Sibling 02 has/had diabetes. Please do not include gestational diabetes.
Categorical
Sibling 02 has/had diabetes
Phase 2 data. Sibling 02 has/had diabetes. Please do not include gestational diabetes. 2 = yes; 3 = No; 4 = Not known; -1 = left blank; -10 = answer plus additional text;
Categorical
Sibling02 Age
Approximate age at diabetes diagnosis of sibling 02.
Categorical
Age Sibling 02 at diabetes diag
Phase 2 data. Approximate age at diabetes diagnosis of sibling 02. 1 = <10; 2 = 10-19; 3 = 20-29; 4 = 30-39; 5 = 40-49; 6 = 50-59; 7 = 60-69; 8 = 70+; 9 = Not known; -1 = left blank; -5 = more than one selected;
Categorical
Type of sibling 03
Phase 2 data. Type of sibling 03. 1 = sister; 2 = brother; 3 = half sister; 4 = half brother; -1 = left blank; -7 = sibling type not on questionnaire; -10 = answer plus additional text;
Categorical
Sibling03Diabetic
Sibling 03 has/had diabetes. Please do not include gestational diabetes.
Categorical
Sibling 03 has/had diabetes
Phase 2 data. Sibling 03 has/had diabetes. Please do not include gestational diabetes. 2 = yes; 3 = No; 4 = Not known; -1 = left blank; -10 = answer plus additional text;
Categorical
Sibling03Age
Approximate age at diabetes diagnosis of sibling 03.
Categorical
Age Sibling 03 at diabetes diag
Phase 2 data. Approximate age at diabetes diagnosis of sibling 03. 1 = <10; 2 = 10-19; 3 = 20-29; 4 = 30-39; 5 = 40-49; 6 = 50-59; 7 = 60-69; 8 = 70+; 9 = Not known; -1 = left blank; -5 = more than one selected;
Categorical
Type of sibling 04
Phase 2 data. Type of sibling 04. 1 = sister; 2 = brother; 3 = half sister; 4 = half brother; -1 = left blank; -7 = sibling type not on questionnaire; -10 = answer plus additional text;
Categorical
Sibling04Diabetic
Sibling 04 has/had diabetes. Please do not include gestational diabetes.
Categorical
Sibling 04 has/had diabetes
Phase 2 data. Sibling 04 has/had diabetes. Please do not include gestational diabetes. 2 = yes; 3 = No; 4 = Not known; -1 = left blank; -10 = answer plus additional text;
Categorical
Sibling04Age
Approximate age at diabetes diagnosis of sibling 04.
Categorical
Age Sibling 04 at diabetes diag
Phase 2 data. Approximate age at diabetes diagnosis of sibling 04. 1 = <10; 2 = 10-19; 3 = 20-29; 4 = 30-39; 5 = 40-49; 6 = 50-59; 7 = 60-69; 8 = 70+; 9 = Not known; -1 = left blank; -5 = more than one selected;
Categorical
Type of sibling 05
Phase 2 data. Type of sibling 05. 1 = sister; 2 = brother; 3 = half sister; 4 = half brother; -1 = left blank; -7 = sibling type not on questionnaire; -10 = answer plus additional text;
Categorical
Sibling05Diabetic
Sibling 05 has/had diabetes. Please do not include gestational diabetes.
Categorical
Sibling 05 has/had diabetes
Phase 2 data. Sibling 05 has/had diabetes. Please do not include gestational diabetes. 2 = yes; 3 = No; 4 = Not known; -1 = left blank; -10 = answer plus additional text;
Categorical
Sibling05Age
Approximate age at diabetes diagnosis of sibling 05.
Categorical
Age Sibling 05 at diabetes diag
Phase 2 data. Approximate age at diabetes diagnosis of sibling 05. 1 = <10; 2 = 10-19; 3 = 20-29; 4 = 30-39; 5 = 40-49; 6 = 50-59; 7 = 60-69; 8 = 70+; 9 = Not known; -1 = left blank; -5 = more than one selected;
Categorical
Type of sibling 06
Phase 2 data. Type of sibling 06. 1 = sister; 2 = brother; 3 = half sister; 4 = half brother; -1 = left blank; -7 = sibling type not on questionnaire; -10 = answer plus additional text;
Categorical
Sibling06Diabetic
Sibling 06 has/had diabetes. Please do not include gestational diabetes.
Categorical
Sibling 06 has/had diabetes
Phase 2 data. Sibling 06 has/had diabetes. Please do not include gestational diabetes. 2 = yes; 3 = No; 4 = Not known; -1 = left blank; -10 = answer plus additional text;
Categorical
Sibling06Age
Approximate age at diabetes diagnosis of sibling 06.
Categorical
Age Sibling 06 at diabetes diag
Phase 2 data. Approximate age at diabetes diagnosis of sibling 06. 1 = <10; 2 = 10-19; 3 = 20-29; 4 = 30-39; 5 = 40-49; 6 = 50-59; 7 = 60-69; 8 = 70+; 9 = Not known; -1 = left blank; -5 = more than one selected;
Categorical
Type of sibling 07
Phase 2 data. Type of sibling 07. 1 = sister; 2 = brother; 3 = half sister; 4 = half brother; -1 = left blank; -7 = sibling type not on questionnaire; -10 = answer plus additional text;
Categorical
Sibling07Diabetic
Sibling 07 has/had diabetes. Please do not include gestational diabetes.
Categorical
Sibling 07 has/had diabetes
Phase 2 data. Sibling 07 has/had diabetes. Please do not include gestational diabetes. 2 = yes; 3 = No; 4 = Not known; -1 = left blank; -10 = answer plus additional text;
Categorical
Sibling07Age
Approximate age at diabetes diagnosis of sibling 07.
Categorical
Age Sibling 07 at diabetes diag
Phase 2 data. Approximate age at diabetes diagnosis of sibling 07. 1 = <10; 2 = 10-19; 3 = 20-29; 4 = 30-39; 5 = 40-49; 6 = 50-59; 7 = 60-69; 8 = 70+; 9 = Not known; -1 = left blank; -5 = more than one selected;
Categorical
Type of sibling 08
Phase 2 data. Type of sibling 08. 1 = sister; 2 = brother; 3 = half sister; 4 = half brother; -1 = left blank; -7 = sibling type not on questionnaire; -10 = answer plus additional text;
Categorical
Sibling08Diabetic
Sibling 08 has/had diabetes. Please do not include gestational diabetes.
Categorical
Sibling 08 has/had diabetes
Phase 2 data. Sibling 08 has/had diabetes. Please do not include gestational diabetes. 2 = yes; 3 = No; 4 = Not known; -1 = left blank; -10 = answer plus additional text;
Categorical
Sibling08Age
Approximate age at diabetes diagnosis of sibling 08.
Categorical
Age Sibling 08 at diabetes diag
Phase 2 data. Approximate age at diabetes diagnosis of sibling 08. 1 = <10; 2 = 10-19; 3 = 20-29; 4 = 30-39; 5 = 40-49; 6 = 50-59; 7 = 60-69; 8 = 70+; 9 = Not known; -1 = left blank; -5 = more than one selected;
Categorical
Type of sibling 09
Phase 2 data. Type of sibling 09. 1 = sister; 2 = brother; 3 = half sister; 4 = half brother; -1 = left blank; -7 = sibling type not on questionnaire; -10 = answer plus additional text;
Categorical
Sibling09Diabetic
Sibling 09 has/had diabetes. Please do not include gestational diabetes.
Categorical
Sibling 09 has/had diabetes
Phase 2 data. Sibling 09 has/had diabetes. Please do not include gestational diabetes. 2 = yes; 3 = No; 4 = Not known; -1 = left blank; -10 = answer plus additional text;
Categorical
Sibling09Age
Approximate age at diabetes diagnosis of sibling 09.
Categorical
Age Sibling 09 at diabetes diag
Phase 2 data. Approximate age at diabetes diagnosis of sibling 09. 1 = <10; 2 = 10-19; 3 = 20-29; 4 = 30-39; 5 = 40-49; 6 = 50-59; 7 = 60-69; 8 = 70+; 9 = Not known; -1 = left blank; -5 = more than one selected;
Categorical
Type of sibling 10
Phase 2 data. Type of sibling 10. 1 = sister; 2 = brother; 3 = half sister; 4 = half brother; -1 = left blank; -7 = sibling type not on questionnaire; -10 = answer plus additional text;
Categorical
Sibling10Diabetic
Sibling 10 has/had diabetes. Please do not include gestational diabetes.
Categorical
Sibling 10 has/had diabetes
Phase 2 data. Sibling 10 has/had diabetes. Please do not include gestational diabetes. 2 = yes; 3 = No; 4 = Not known; -1 = left blank; -10 = answer plus additional text;
Categorical
Sibling10Age
Approximate age at diabetes diagnosis of sibling 10.
Categorical
Age Sibling 10 at diabetes diag
Phase 2 data. Approximate age at diabetes diagnosis of sibling 10. 1 = <10; 2 = 10-19; 3 = 20-29; 4 = 30-39; 5 = 40-49; 6 = 50-59; 7 = 60-69; 8 = 70+; 9 = Not known; -1 = left blank; -5 = more than one selected;
Categorical
FamilyHistoryEntryComments
Any additional text written on the questionnaire
Text
Family History entry comments
Phase 2 data. Any additional text written on the questionnaire
Text
OLINK assay FHIT
Phase 1 OLINK assay data for target FHIT in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Date finished eFamHist qnr
Phase 2 data. Date the participant finished filling in the Electronic Online FamHist questionnaire.
Date
Date started eFamHist qnr
Phase 2 data. Date the participant started to fill in the Electronic Online FamHist questionnaire.
Date
eFamHist qnr pt ID no
Phase 2 data. Electronic FamHist questionnaire-specicifc participant ID number.
Text
None
Phase 2 data. Please enter your 3-digit pin (on electronic form).
Text
eFamHist qnr ID no
Phase 2 data. Electronic FamHist questionnaire ID number for version control.
Text
eFamHist qnr ID name
Phase 2 data. Electronic FamHist questionnaire ID name for version control.
Text
Study phase eFamHist qnr
Phase 2 data. Study phase the Electronic FamHist questionnaire was used for.
Text
Time finished eFamHist qnr
Phase 2 data. Time the participant finished filling in the Electronic Online FamHist questionnaire.
Text
Time started eFamHist qnr
Phase 2 data. Time the participant started to fill in the Electronic Online FamHist questionnaire.
Text
eFamHist qnr version date
Phase 2 data. Electronic FamHist questionnaire version date for version control.
Text
eFamHist qnr version no
Phase 2 data. Electronic FamHist questionnaire version number for version control.
Text
eFamHist qnr web form version no
Phase 2 data. Electronic FamHist questionnaire web form version number for version control.
Text
None
To be used for clustering particpants in age groups of 5 year blocks. Useful when data of birth can not be released.
Five Year Age Group
Phase 2 data. Age group the volunteer belonged to at the time of their phase 2 clinical appointment where age groups have been split up into groups of 5 years. Derived by data management team based on AgeAtTest_DM_Attended_P2. Can be used where precise age cannot be released or in not required.
Text
OLINK assay FKBP1B
Phase 1 OLINK assay data for target FKBP1B in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FKBP4
Phase 1 OLINK assay data for target FKBP4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FKBP5
Phase 1 OLINK assay data for target FKBP5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FKBP7
Phase 1 OLINK assay data for target FKBP7 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Flag incomplete questionnaire
Phase 2 data. Derived with method 2. Flag those that did not complete questionnaire (1 = Not complete)
Categorical
Flag shift worker
Phase 2 data. 1=Noted as shift worker 2=Multiple sleep times reported (but not ticked shift)
Categorical
OLINK assay FLI1
Phase 1 OLINK assay data for target FLI1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Hours of Floor Exercises
Please indicate the average length of time (in hours) you spent doing the activity per episode. Floor Exercises(eg stretching bending keep fit or yoga).
Integer
Hours of Floor Exercises CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Floor Exercises(eg stretching bending keep fit or yoga). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Floor exercises hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Floor Exercises(eg stretching bending keep fit or yoga). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Floor Exercises hrs
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Floor Exercises(eg stretching bending keep fit or yoga). -1 = left blank. DO NOT USE THIS VARIABLE. Use floorExerciseHr_CLEAN_P2 instead.
Real
Minutes of Floor Exercises
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Floor Exercises(eg stretching bending keep fit or yoga).
Integer
Minutes of Floor Exercises CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Floor Exercises(eg stretching bending keep fit or yoga). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Floor exercises min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Floor Exercises(eg stretching bending keep fit or yoga). Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Floor Exercises min
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Floor Exercises(eg stretching bending keep fit or yoga). -1 = left blank. DO NOT USE THIS VARIABLE. Use floorExerciseMin_CLEAN_P2 instead.
Real
Frequency of Floor Exercises CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Floor Exercises (eg stretching bending keep fit or yoga). Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
floorExercise_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for Floor Exercises
Real
Cln variable: Floor exercises
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Floor Exercises (eg stretching bending keep fit or yoga). Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
floorExercise_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Floor Exercises (eg stretching bending keep fit or yoga). Data normalised to DE template 1 data.
Categorical
Floor Exercises
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Floor Exercises(eg stretching bending keep fit or yoga). DO NOT USE THIS VARIABLE. Use floorExercise_CLEAN_P2 instead.
Real
Floor Exercises
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Floor Exercises (eg stretching bending keep fit or yoga). Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Floor Exercises DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Floor Exercises (eg stretching bending keep fit or yoga). Data entered using data entry template with 1-2-3-4-5-6-7 codes . This data cannot be compared with data in floorExercise_T2. Instead use floorExercise_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Floor Exercises DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Floor Exercises (eg stretching bending keep fit or yoga). Data entered using data entry template with 1-3-4-5-6-7-8 codes . This data cannot be compared with data in floorExercise_T1. Instead use floorExercise_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
OLINK assay FLRT2
Phase 1 OLINK assay data for target FLRT2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay Flt3L
Phase 1 OLINK assay data for target Flt3L in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
FMR group
Indication wether the participant was allocated to FMR group A or B. People in group A were only told that the monitor they had to wear for 6 days and nights was a heart rate monitor. People in group B were also told it monitors movement and that by analysing the information stored in the monitor we will be able to tell exactly how active you have been during these six days.
Categorical
FMR Info date
Version date of the Information sheet provided to FMR participants.
Date
FMR Info version
Version number of the Information sheet provided to FMR participants.
Text
FMR participant
Is the participant part of the FMR study. Data generated by the data management team based on list provided by study coordination.
Categorical
FMR test date
Date FMR participant attended research unit to undergo FMR health checks and to hand over monitor.
Date
OLINK assay FOLR2
Phase 1 OLINK assay data for target FOLR2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
No. of correctly identified targets (target=food image)
This variable was derived from data collected as part of the Cognitive and Behavioural Measurement Sub Study. 482 participants from the Fenland Cohort took part on this sub study. Number of correctly identified targets in the trials where the target (a letter p or q) was on the food picture; in the Rapid Serial Visualisation Task.
Integer
No. of correctly identified targets (food distractor 1 image before target)
This variable was derived from data collected as part of the Cognitive and Behavioural Measurement Sub Study. 482 participants from the Fenland Cohort took part on this sub study. Number of correctly identified targets in the trials where the target (a letter p or q) was on a neutral image; with a distractor food picture shown 1 image before the target (i.e.; the distractor immediately preceded the target); in the Rapid Serial Visualisation Task.
Integer
No. of correctly identified targets (food distractor 2 images before target)
This variable was derived from data collected as part of the Cognitive and Behavioural Measurement Sub Study. 482 participants from the Fenland Cohort took part on this sub study. Number of correctly identified targets in the trials where the target (a letter p or q) was on a neutral image; with a distractor food picture shown 2 images before the target (i.e.; there was 1 neutral image between the distractor and the target); in the Rapid Serial Visualisation Task.
Integer
No. of correctly identified targets (food distractor 3 images before target)
This variable was derived from data collected as part of the Cognitive and Behavioural Measurement Sub Study. 482 participants from the Fenland Cohort took part on this sub study. Number of correctly identified targets in the trials where the target (a letter p or q) was on a neutral image; with a distractor food picture shown 3 images before the target (i.e.; there were 2 neutral image between the distractor and the target); in the Rapid Serial Visualisation Task.
Integer
No. of correctly identified targets (food distractor 4 images before target)
This variable was derived from data collected as part of the Cognitive and Behavioural Measurement Sub Study. 482 participants from the Fenland Cohort took part on this sub study. Number of correctly identified targets in the trials where the target (a letter p or q) was on a neutral image; with a distractor food picture shown 4 images before the target (i.e.; there were 3 neutral image between the distractor and the target); in the Rapid Serial Visualisation Task.
Integer
No. of errors in go trials (food)
This variable was derived from data collected as part of the Cognitive and Behavioural Measurement Sub Study. 482 participants from the Fenland Cohort took part on this sub study. Number of errors across all Go Trials for food stimuli in the Food Go/No-Go with Affective Shifting task.
Integer
No. of inhibition errors (food)
This variable was derived from data collected as part of the Cognitive and Behavioural Measurement Sub Study. 482 participants from the Fenland Cohort took part on this sub study. Number of inhibition errors across all food stimuli. Inhibition errors = responses that should have been inhibited as a distractor was presented. Number of times the participant is instructed not to respond to blue-outlined or green-outlined images; but responds when these are food images.
Integer
Hours of Football Rugby Or Hockey
Please indicate the average length of time (in hours) you spent doing the activity per episode. Football Rugby Or Hockey.
Integer
Hours of Football Rugby Or Hockey CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Football Rugby Or Hockey. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Football Hockey hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Football Rugby Or Hockey. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Football Rugby or Hockey hrs
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in hours) you spent doing the activity per episode. Football Rugby Or Hockey. -1 = left blank. DO NOT USE THIS VARIABLE. Use footballRugbyHockeyHr_CLEAN_P2 instead.
Real
Minutes of Football Rugby Or Hockey
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Football Rugby Or Hockey.
Integer
Minutes of Football Rugby Or Hockey CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Football Rugby Or Hockey. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Football Hockey min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Football Rugby Or Hockey. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Football Rugby or Hockey mins
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Football Rugby Or Hockey. -1 = left blank. DO NOT USE THIS VARIABLE. Use footballRugbyHockeyMin_CLEAN_P2 instead.
Real
Frequency of Football Rugby Or Hockey CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Football Rugby Or Hockey. Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
footballRugbyHockey_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for Football Rugby Or Hockey
Real
Cln variable: Football Hockey
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Football Rugby Or Hockey. Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
footballRugbyHockey_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Football Rugby Or Hockey. Data normalised to DE template 1 data.
Categorical
Football Rugby or Hockey
Phase 2 data. Questionnaire reads D14. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Football Rugby Or Hockey. DO NOT USE THIS VARIABLE. Use footballRugbyHockey_CLEAN_P2 instead.
Real
Football Rugby or Hockey
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Football Rugby Or Hockey. Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Football Rugby Or Hockey DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Football Rugby Or Hockey. Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in footballRugbyHockey_T2. Instead use footballRugbyHockey_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Football Rugby Or Hockey DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Football Rugby Or Hockey. Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in footballRugbyHockey_T1. Instead use footballRugbyHockey_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
OLINK assay FOSB
Phase 1 OLINK assay data for target FOSB in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FOXO1
Phase 1 OLINK assay data for target FOXO1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
FL_Data
Data as entered on Study database. Is free living data available? Yes-tick or no-left blank
FL_DataQuality
Data as entered on Study database. Has Free Living data quality been reviewed? yes-tick or no-left blank
Free Living data quality reviewed
Phase 2 data. Data as entered on Study database. For study coordination purposes and QC only. Has Free Living data quality been reviewed? 0 = no; 1 = yes;
Categorical
Free living data
Phase 2 data. Data as entered on Study database. For study coordination purposes and QC only. Is free living data available? 0 = no; 1 = yes;
Categorical
FL_DateMatch
Data as entered on Study database. Is the 1st date of the free living data the same as the test date? Yes or no
Test-Free living date match
Phase 2 data. Data as entered on Study database. For study coordination and QC purposes only. Is the 1st date of the free living data the same as the test date? Yes or blank
Text
FL_MismatchReason
Data as entered on Study database. If the 1st date of the free living data is not the same as the test date provide a reason why not.
Test-Free living date not match
Phase 2 data. Data as entered on Study database. For study coordination purposes and QC only. If the 1st date of the free living data is not the same as the test date provide a reason why not.
Text
FREQCARINI
FREQCARINI. Derived Intermediate not for general release. Data can be provided if necessary.
Real
FREQCYCLEINI
FREQCYCLEINI. Derived Intermediate not for general release. Data can be provided if necessary.
Real
FREQPUBLICINI
FREQPUBLICINI. Derived Intermediate not for general release. Data can be provided if necessary.
Real
FREQTOTAL
FREQTOTAL. Derived Intermediate not for general release. Data can be provided if necessary.
Real
FREQWALKINI
FREQWALKINI. Derived Intermediate not for general release. Data can be provided if necessary.
Real
Apples (1 fruit) ERROR CODES CLEANED
Average use last year of Apples (1 fruit) After cleaning this variable is renamed as APPLES which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Pears (1 fruit) ERROR CODES CLEANED
Average use last year of Pears (1 fruit) After cleaning this variable is renamed as PEARS which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Oranges satsumas mandarins 1 fruit
Average use last year of Oranges satsumas mandarins (1 fruit). After cleaning this variable is renamed as ORANGES which is then used by the FETA program for analysis.
Categorical
Oranges satsumas mandarins (1 fruit) ERROR CODES CLEANED
Average use last year of Oranges satsumas mandarins (1 fruit) After cleaning this variable is renamed as ORANGES which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Grapefruit (half) ERROR CODES CLEANED
Average use last year of Grapefruit (half) After cleaning this variable is renamed as GRAPEFRUIT which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Bananas (1 fruit) ERROR CODES CLEANED
Average use last year of Bananas (1 fruit) After cleaning this variable is renamed as BANANAS which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Grapes (medium serving) ERROR CODES CLEANED
Average use last year of Grapes (medium serving) After cleaning this variable is renamed as GRAPES which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Melon (1 slice) ERROR CODES CLEANED
Average use last year of Melon (1 slice) After cleaning this variable is renamed as MELONS which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Peaches Plums Apricots (1 fruit). Seasonal. ERROR CODES CLEANED
Average use last year of Peaches Plums Apricots (1 fruit) Seasonal For seasonal fruits please estimate your average use when the fruit is in season After cleaning this variable is renamed as PEACHES which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Strawberries Raspberries Kiwi Fruit medium serving Seasonal.
Average use last year of Strawberries Raspberries Kiwi Fruit (medium serving). Seasonal. For seasonal fruits please estimate your average use when the fruit is in season. After cleaning this variable is renamed as STRAWBERRIES which is then used by the FETA program for analysis.
Categorical
Strawberries; Raspberries; Kiwi Fruit (medium serving). Seasonal. ERROR CODES CLEANED
Average use last year of Strawberries Raspberries Kiwi Fruit (medium serving) Seasonal For seasonal fruits please estimate your average use when the fruit is in season After cleaning this variable is renamed as STRAWBERRIES which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Tinned Fruit
Average use last year of Tinned Fruit. After cleaning this variable is renamed as TINNED_FRUIT which is then used by the FETA program for analysis.
Categorical
Tinned Fruit ERROR CODES CLEANED
Average use last year of Tinned Fruit After cleaning this variable is renamed as TINNED_FRUIT which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Tinned Fruit
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Dried Fruit
Average use last year of Dried Fruit. After cleaning this variable is renamed as DRIED_FRUIT which is then used by the FETA program for analysis.
Categorical
Dried Fruit ERROR CODES CLEANED
Average use last year of Dried Fruit After cleaning this variable is renamed as DRIED_FRUIT which is then used by the FETA program for analysis. All raw data with error codes (> 1 answer) cleaned by averaging all answers ticked and rounding up to next whole number.
Categorical
Dried Fruit
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Apples 1 fruit
Average use last year of Apples (1 fruit). After cleaning this variable is renamed as APPLES which is then used by the FETA program for analysis.
Categorical
Apples 1 fruit
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Pears 1 fruit
Average use last year of Pears (1 fruit). After cleaning this variable is renamed as PEARS which is then used by the FETA program for analysis.
Categorical
Pears 1 fruit
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Oranges satsumas mandarins 1 fruit
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Grapefruit half
Average use last year of Grapefruit (half). After cleaning this variable is renamed as GRAPEFRUIT which is then used by the FETA program for analysis.
Categorical
Grapefruit half
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Bananas 1 fruit
Average use last year of Bananas (1 fruit). After cleaning this variable is renamed as BANANAS which is then used by the FETA program for analysis.
Categorical
Bananas 1 fruit
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Grapes medium serving
Average use last year of Grapes (medium serving). After cleaning this variable is renamed as GRAPES which is then used by the FETA program for analysis.
Categorical
Grapes medium serving
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Melon 1 slice
Average use last year of Melon (1 slice). After cleaning this variable is renamed as MELONS which is then used by the FETA program for analysis.
Categorical
Melon 1 slice
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Peaches Plums Apricots 1 fruit Seasonal.
Average use last year of Peaches Plums Apricots (1 fruit). Seasonal. For seasonal fruits please estimate your average use when the fruit is in season. After cleaning this variable is renamed as PEACHES which is then used by the FETA program for analysis.
Categorical
Peaches Plums Apricots 1 fruit
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
Strawberries Raspberries Kiwi Fruit medium serving
Phase 2 data. FFQ questionnaire ELY-PQ-3-204 reads Please estimate your average food use as best you can and please answer every question - do not leave ANY lines blank. Foods and Amounts; Average use last year. 1 = Never or less than once a month; 2 = 1-3 per month; 3 = Once a week; 4 = 2-4 per week; 5 = 5-6 per week; 6 = Once a day; 7 = 2-3 per day; 8 = 4-5 per day; 9 = 6+ per day; -1 = left blank; -5 = more than one selected;
Categorical
OLINK assay FR-alpha
Phase 1 OLINK assay data for target FR-alpha in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FR-gamma
Phase 1 OLINK assay data for target FR-gamma in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FSTL3
Phase 1 OLINK assay data for target FSTL3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FS
Phase 1 OLINK assay data for target FS in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
None
Thyroid Function Test (TFT) analaysis on T120 blood sample. Fenland phase 1. Triidothyronine (T3). Sample used is T120 plasma Heparin sample as that was being shipped off for Insulin_T120 measurement already.
Real
None
Thyroid Function Test (TFT) analaysis on T120 blood sample. Fenland phase 1. Thyroxine (T4). Sample used is T120 plasma Heparin sample as that was being shipped off for Insulin_T120 measurement already.
Real
OLINK assay FUCA1
Phase 1 OLINK assay data for target FUCA1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Full aliquot sample set collected
Aliquot & Biochemistry sample set fully collected according to form (TRUE/FALSE) (Default=FALSE) TRUE = completed fully;
Categorical
OLINK assay FURIN
Phase 1 OLINK assay data for target FURIN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FUT3/FUT5
Phase 1 OLINK assay data for target FUT3/FUT5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FUT8
Phase 1 OLINK assay data for target FUT8 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay FXYD5
Phase 1 OLINK assay data for target FXYD5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GALNT10
Phase 1 OLINK assay data for target GALNT10 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GALNT2
Phase 1 OLINK assay data for target GALNT2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GALNT3
Phase 1 OLINK assay data for target GALNT3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay Gal-1
Phase 1 OLINK assay data for target Gal-1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay Gal-3
Phase 1 OLINK assay data for target Gal-3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay Gal-4
Phase 1 OLINK assay data for target Gal-4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay gal-8
Phase 1 OLINK assay data for target gal-8 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay Gal-9
Phase 1 OLINK assay data for target Gal-9 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GAL
Phase 1 OLINK assay data for target GAL in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
GammaGT 0 minutes
Serum GGT (Gamma GT) measurement taken at 0 minutes in U/l
Integer
GammaGT 0 minutes
Phase 2 data. Serum GGT (Gamma GT) measurement taken at 0 minutes in U/l
Integer
OLINK assay GAS6
Phase 1 OLINK assay data for target GAS6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
calibration method applied
Phase 2 data. Calibration method applied to data file. Offset and scale with temperature (which uses both an offset and scaling factor for each axis) or offset only with temperature (which uses just the offsets).
Text
calibration type
Phase 2 data. Calibration type used. Single file; multi file or fail. Single file calibration uses the calibration factors from the file itself. Multi-file calibration uses calibration factors from all files in the processing database (all datasets) that have used the same device. Fail indicates that the file has failed calibration and therefore the results are unusable and have been set to missing.
Text
Device serial number
Phase 2 data. Device serial number of monitor used for data collection.
Integer
Proportion time spent >= 0 milli-g
Phase 2 data. Proportion of time spent above >=0 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 0 milli-g
Phase 2 data. Proportion of time spent above >=0 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 0 milli-g consolidated
Phase 2 data. Proportion of time spent above >=0 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 1000 milli-g
Phase 2 data. Proportion of time spent above >=1000 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 1000 milli-g
Phase 2 data. Proportion of time spent above >=1000 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Proportion timespent >= 1000 milli-g
Phase 2 data. Proportion of time spent above >=1000 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 100 milli-g
Phase 2 data. Proportion of time spent above >=100 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 100 milli-g
Phase 2 data. Proportion of time spent above >=100 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 100 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=100 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 105 milli-g
Phase 2 data. Proportion of time spent above >=105 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 105 milli-g
Phase 2 data. Proportion of time spent above >=105 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 105 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=105 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 10 milli-g
Phase 2 data. Proportion of time spent above >=10 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 10 milli-g
Phase 2 data. Proportion of time spent above >=10 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 10 milli-g consolidated
Phase 2 data. Proportion of time spent above >=10 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 110 milli-g
Phase 2 data. Proportion of time spent above >=110 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 110 milli-g
Phase 2 data. Proportion of time spent above >=110 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 110 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=110 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 115 milli-g
Phase 2 data. Proportion of time spent above >=115 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 115 milli-g
Phase 2 data. Proportion of time spent above >=115 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 115 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=115 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 120 milli-g
Phase 2 data. Proportion of time spent above >=120 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 120 milli-g
Phase 2 data. Proportion of time spent above >=120 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 120 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=120 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 125 milli-g
Phase 2 data. Proportion of time spent above >=125 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 125 milli-g
Phase 2 data. Proportion of time spent above >=125 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 125 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=125 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 130 milli-g
Phase 2 data. Proportion of time spent above >=130 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 130 milli-g
Phase 2 data. Proportion of time spent above >=130 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 130 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=130 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 135 milli-g
Phase 2 data. Proportion of time spent above >=135 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 135 milli-g
Phase 2 data. Proportion of time spent above >=135 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 135 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=135 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 140 milli-g
Phase 2 data. Proportion of time spent above >=140 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 140 milli-g
Phase 2 data. Proportion of time spent above >=140 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 140 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=140 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 145 milli-g
Phase 2 data. Proportion of time spent above >=145 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 145 milli-g
Phase 2 data. Proportion of time spent above >=145 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 145 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=145 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 150 milli-g
Phase 2 data. Proportion of time spent above >=150 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 150 milli-g
Phase 2 data. Proportion of time spent above >=150 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 150 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=150 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 15 milli-g
Phase 2 data. Proportion of time spent above >=15 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 15 milli-g
Phase 2 data. Proportion of time spent above >=15 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 15 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=15 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 160 milli-g
Phase 2 data. Proportion of time spent above >=160 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 160 milli-g
Phase 2 data. Proportion of time spent above >=160 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 160 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=160 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 170 milli-g
Phase 2 data. Proportion of time spent above >=170 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 170 milli-g
Phase 2 data. Proportion of time spent above >=170 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 170 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=170 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 180 milli-g
Phase 2 data. Proportion of time spent above >=180 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 180 milli-g
Phase 2 data. Proportion of time spent above >=180 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 180 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=180 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 190 milli-g
Phase 2 data. Proportion of time spent above >=190 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 190 milli-g
Phase 2 data. Proportion of time spent above >=190 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 190 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=190 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 1 milli-g
Phase 2 data. Proportion of time spent above >=1 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 1 milli-g
Phase 2 data. Proportion of time spent above >=1 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 1 milli-g consolidated
Phase 2 data. Proportion of time spent above >=1 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 2000 milli-g
Phase 2 data. Proportion of time spent above >=2000 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 2000 milli-g
Phase 2 data. Proportion of time spent above >=2000 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Proportion timespent >= 2000 milli-g
Phase 2 data. Proportion of time spent above >=2000 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 200 milli-g
Phase 2 data. Proportion of time spent above >=200 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 200 milli-g
Phase 2 data. Proportion of time spent above >=200 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 200 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=200 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 20 milli-g
Phase 2 data. Proportion of time spent above >=20 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 20 milli-g
Phase 2 data. Proportion of time spent above >=20 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 20 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=20 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 210 milli-g
Phase 2 data. Proportion of time spent above >=210 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 210 milli-g
Phase 2 data. Proportion of time spent above >=210 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 210 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=210 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 220 milli-g
Phase 2 data. Proportion of time spent above >=220 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 220 milli-g
Phase 2 data. Proportion of time spent above >=220 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 220 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=220 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 230 milli-g
Phase 2 data. Proportion of time spent above >=230 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 230 milli-g
Phase 2 data. Proportion of time spent above >=230 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 230 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=230 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 240 milli-g
Phase 2 data. Proportion of time spent above >=240 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 240 milli-g
Phase 2 data. Proportion of time spent above >=240 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 240 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=240 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 250 milli-g
Phase 2 data. Proportion of time spent above >=250 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 250 milli-g
Phase 2 data. Proportion of time spent above >=250 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 250 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=250 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 25 milli-g
Phase 2 data. Proportion of time spent above >=25 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 25 milli-g
Phase 2 data. Proportion of time spent above >=25 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 25 milli-g consolidated
Phase 2 data. Proportion of time spent above >=25 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 260 milli-g
Phase 2 data. Proportion of time spent above >=260 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 260 milli-g
Phase 2 data. Proportion of time spent above >=260 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 260 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=260 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 270 milli-g
Phase 2 data. Proportion of time spent above >=270 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 270 milli-g
Phase 2 data. Proportion of time spent above >=270 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 270 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=270 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 280 milli-g
Phase 2 data. Proportion of time spent above >=280 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 280 milli-g
Phase 2 data. Proportion of time spent above >=280 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 280 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=280 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 290 milli-g
Phase 2 data. Proportion of time spent above >=290 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 290 milli-g
Phase 2 data. Proportion of time spent above >=290 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 290 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=290 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 2 milli-g
Phase 2 data. Proportion of time spent above >=2 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 2 milli-g
Phase 2 data. Proportion of time spent above >=2 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 2 milli-g consolidated
Phase 2 data. Proportion of time spent above >=2 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 3000 milli-g
Phase 2 data. Proportion of time spent above >=3000 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 3000 milli-g
Phase 2 data. Proportion of time spent above >=3000 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Proportion timespent >= 3000 milli-g
Phase 2 data. Proportion of time spent above >=3000 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 300 milli-g
Phase 2 data. Proportion of time spent above >=300 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 300 milli-g
Phase 2 data. Proportion of time spent above >=300 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 300 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=300 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 30 milli-g
Phase 2 data. Proportion of time spent above >=30 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 30 milli-g
Phase 2 data. Proportion of time spent above >=30 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 30 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=30 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 35 milli-g
Phase 2 data. Proportion of time spent above >=35 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 35 milli-g
Phase 2 data. Proportion of time spent above >=35 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 35 milli-g consolidated
Phase 2 data. Proportion of time spent above >=35 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 3 milli-g
Phase 2 data. Proportion of time spent above >=3 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 3 milli-g
Phase 2 data. Proportion of time spent above >=3 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 3 milli-g consolidated
Phase 2 data. Proportion of time spent above >=3 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 4000 milli-g
Phase 2 data. Proportion of time spent above >=4000 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 4000 milli-g
Phase 2 data. Proportion of time spent above >=4000 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Proportion timespent >= 4000 milli-g
Phase 2 data. Proportion of time spent above >=4000 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 400 milli-g
Phase 2 data. Proportion of time spent above >=400 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 400 milli-g
Phase 2 data. Proportion of time spent above >=400 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 400 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=400 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 40 milli-g
Phase 2 data. Proportion of time spent above >=40 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 40 milli-g
Phase 2 data. Proportion of time spent above >=40 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 40 milli-g consolidated
Phase 2 data. Proportion of time spent above >=40 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 45 milli-g
Phase 2 data. Proportion of time spent above >=45 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 45 milli-g
Phase 2 data. Proportion of time spent above >=45 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 45 milli-g consolidated
Phase 2 data. Proportion of time spent above >=45 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 4 milli-g
Phase 2 data. Proportion of time spent above >=4 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 4 milli-g
Phase 2 data. Proportion of time spent above >=4 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 4 milli-g consolidated
Phase 2 data. Proportion of time spent above >=4 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 500 milli-g
Phase 2 data. Proportion of time spent above >=500 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 500 milli-g
Phase 2 data. Proportion of time spent above >=500 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 500 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=500 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 50 milli-g
Phase 2 data. Proportion of time spent above >=50 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 50 milli-g
Phase 2 data. Proportion of time spent above >=50 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 50 milli-g consolidated
Phase 2 data. Proportion of time spent above >=50 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 55 milli-g
Phase 2 data. Proportion of time spent above >=55 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 55 milli-g
Phase 2 data. Proportion of time spent above >=55 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 55 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=55 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 5 milli-g
Phase 2 data. Proportion of time spent above >=5 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 5 milli-g
Phase 2 data. Proportion of time spent above >=5 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 5 milli-g consolidated
Phase 2 data. Proportion of time spent above >=5 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 600 milli-g
Phase 2 data. Proportion of time spent above >=600 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 600 milli-g
Phase 2 data. Proportion of time spent above >=600 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 600 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=600 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 60 milli-g
Phase 2 data. Proportion of time spent above >=60 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 60 milli-g
Phase 2 data. Proportion of time spent above >=60 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 60 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=60 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 65 milli-g
Phase 2 data. Proportion of time spent above >=65 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 65 milli-g
Phase 2 data. Proportion of time spent above >=65 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 65 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=65 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 700 milli-g
Phase 2 data. Proportion of time spent above >=700 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 700 milli-g
Phase 2 data. Proportion of time spent above >=700 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 700 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=700 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 70 milli-g
Phase 2 data. Proportion of time spent above >=70 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 70 milli-g
Phase 2 data. Proportion of time spent above >=70 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 70 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=70 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 75 milli-g
Phase 2 data. Proportion of time spent above >=75 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 75 milli-g
Phase 2 data. Proportion of time spent above >=75 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 75 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=75 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 800 milli-g
Phase 2 data. Proportion of time spent above >=800 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 800 milli-g
Phase 2 data. Proportion of time spent above >=800 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Proportion time spent >= 800 milli-g
Phase 2 data. Proportion of time spent above >=800 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 80 milli-g
Phase 2 data. Proportion of time spent above >=80 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 80 milli-g
Phase 2 data. Proportion of time spent above >=80 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 80 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=80 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 85 milli-g
Phase 2 data. Proportion of time spent above >=85 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 85 milli-g
Phase 2 data. Proportion of time spent above >=85 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 85 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=85 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 900 milli-g
Phase 2 data. Proportion of time spent above >=900 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 900 milli-g
Phase 2 data. Proportion of time spent above >=900 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Proportion time spent >= 900 milli-g
Phase 2 data. Proportion of time spent above >=900 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 90 milli-g
Phase 2 data. Proportion of time spent above >=90 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 90 milli-g
Phase 2 data. Proportion of time spent above >=90 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 90 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=90 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Proportion time spent >= 95 milli-g
Phase 2 data. Proportion of time spent above >=95 milli-g (sleep imputed). The acceleration value is calculated as ENMO (euclidean norm minus one). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Proportion time spent >= 95 milli-g
Phase 2 data. Proportion of time spent above >=95 milli-g (no sleep imputed / standard output). The acceleration value is calculated as ENMO (euclidean norm minus one). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Time spent >= 95 milli-gconsolidated
Phase 2 data. Proportion of time spent above >=95 milli-g (consolidated). The acceleration value is calculated as ENMO (euclidean norm minus one). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Average acceleration ENMO Friday
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by day of week (Friday) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 10
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 10) (9:00-10:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 11
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 11) (10:00-11:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 12
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 12) (11:00-12:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 13
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 13) (12:00-13:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 14
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 14) (13:00-14:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 15
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 15) (14:00-15:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 16
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 16) (15:00-16:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 17
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 17) (16:00-17:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 18
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 18) (17:00-18:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 19
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 19) (18:00-19:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 1
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 1) (0:00-1:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 20
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 20) (19:00-20:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 21
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 21) (20:00-21:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 22
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 22) (21:00-22:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 23
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 23) (22:00-23:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 24
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 24) (23:00-00:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 2
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 2) (1:00-2:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 3
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 3) (2:00-3:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 4
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 4) (3:00-4:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 5
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 5) (4:00-5:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 6
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 6) (5:00-6:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 7
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 7) (6:00-7:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 8
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 8) (7:00-8:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg acceleration by hr of day hr 9
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by hour of day (hr 9) (8:00-9:00) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Average acceleration imputed
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) in milli-g; (sleep imputed). This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn.
Real
Average acceleration ENMO Monday
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by day of week (Monday) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Average acceleration non-imputed
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) in milli-g; (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Avg accel milli-g consolidated
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) in milli-g; (consolidated). Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1).
Real
Average acceleration ENMO Saturday
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by day of week (Saturday) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Average acceleration ENMO Sunday
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by day of week (Sunday) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Average acceleration ENMO Thursday
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by day of week (Thursday) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Average acceleration ENMO Tuesday
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by day of week (Tuesday) across the full data file (mg) (no sleep imputed / standard output) . This is the standard output (original) variable meaning no sleep imputation has been done.
Real
Average acceleration ENMO Wednesday
Phase 2 data. Average acceleration (euclidean norm minus one (ENMO)) by day of week (Wednesday) across the full data file (mg) (no sleep imputed / standard output). This is the standard output (original) variable meaning no sleep imputation has been done.
Real
File error after calibration single file
Phase 2 data. The absolute difference between 1g and the Euclidean Norm of the values of the three axes; averaged per file; after calibration (mg). Single file calibration.
Real
File error before calibration single file
Phase 2 data. The absolute difference between 1g and the Euclidean Norm of the values of the three axes; averaged per file; before calibration (mg). Single file calibration.
Real
First date timestamp
Phase 2 data. First date timestamp of hdf5 file (Stata formatted).
DateTime
Flag to indicate anomaly
Phase 2 data. Binary flag to indicate file had anomaly (1=anomaly present). Anomaly detected and fixed during processing.
Categorical
Flag to indicate axis issue
Phase 2 data. Binary flag to indicate there was an issue with one of the axis during the recording (1 = file had technical axis issue affecting integrity of data). Data set to missing.
Categorical
Flag to indicate = <1 hr valid data
Phase 2 data. Binary flag to indicate file had less than 1 hour of valid data (1= <1hour of data).
Categorical
Flag for data missing Pwear
Phase 2 data. Flag variable that can be used to condition the data on to protect against potential bias caused by data missing at certain times of day (i.e. missing in certain Pwear quadrants). It is advisable to ensure that data are distributed across the 24-hour period and use an inclusion criteria relating to compliance. This variable indicates: 0 = Insufficient wear time (Pwear <48 hours and three Pwear_quads <9 hours wear); 1 = Pwear >=48 hours and all four Pwear_quads >=9 hours; 2 = Pwear >=48 hours and three Pwear_quads >=9 hours (<9 hours in morning quad (midnight-6am)).
Categorical
Last date timestamp
Phase 2 data. Last date timestamp of hdf5 file (Stata formatted).
DateTime
File error after calibration multi-file
Phase 2 data. The absolute difference between 1g and the Euclidean Norm of the values of the three axes; averaged per file; after calibration (mg). Multi-file calibration.
Real
File error before calibration multi-file
Phase 2 data. The absolute difference between 1g and the Euclidean Norm of the values of the three axes; averaged per file; before calibration (mg). Multi-file calibration.
Real
Threshold set still bout detection
Phase 2 data. Threshold set for still bout detection (milli-g). Still bouts are flagged during processing as periods of time where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) fall below this threshold.
Integer
Flag to indicate imputed data used
Phase 2 data. Binary flag (imputed=1) indicates if the imputed data has been used in the consolidated variables for this dataset. In some instances where data is likely to be excluded non-randomly; imputation may be required. Most commonly this is observed with night recording with systematic non-adherence to wearing a monitor during sleep in a 24-hr protocol. The Pwear variable has been set to 1 during the night (midnight-6am); to impute sleep when the monitor was flagged as non-wear during those times. These data are imputed proportional to the amount of days the monitor was worn so as not to inflate wear-time over the recording period. During the creation of the consolidated variables; the standard output variables (means and intensity categories) have been updated with the imputed data if certain criteria are met (limited night data i.e. include=2). These variables are indicated in the label with consolidated.
Categorical
Processing epoch (seconds)
Phase 2 data. Frequency at which the data has been processed; in seconds. This may not reflect the raw frequency the monitor recorded in; instead is the level the data were collapsed to for the processing.
Integer
Pwear afternoon imputed
Phase 2 data. Number of valid hours worn during free-living in the afternoon quadrant (between 12:00-18:00); across the full data file (sleep imputed). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn. This variable indicates the total wear time between 12:00-18:00; across the whole data file; in hours.
Real
Pwear afternoon total time
Phase 2 data. Number of valid hours worn during free-living in the afternoon quadrant (between 12:00-18:00); across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 12:00-18:00; across the whole data file; in hours.
Real
No of hrs during free-living 12-18
Phase 2 data. Number of valid hours worn during free-living in the afternoon quadrant (between 12:00-18:00); across the full data file (consolidated). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1). This variable indicates the total wear time between 12:00-18:00; across the whole data file; in hours.
Real
Wkday afternoon pwear imputed
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 12:00-18:00) on weekdays (Monday-Friday); across the full data file (sleep imputed). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn. This variable indicates the total wear time between 12:00-18:00 on weekdays; across the whole data file; in hours.
Real
Pwear Friday hrs non-imputed
Phase 2 data. Number of valid hours worn during free-living on a Friday; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time on a Friday; across the whole data file; in hours.
Real
Pwear by hr of day hr10 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 09:00-10:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 09:00-10:00; across the whole data file; in hours.
Real
Pwear by hr of day hr11 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 10:00-11:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 10:00-11:00; across the whole data file; in hours.
Real
Wkday Pwear afternoon total time
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 12:00-18:00) on weekdays (Monday-Friday); across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 12:00-18:00 on weekdays; across the whole data file; in hours.
Real
Pwear wkday 12-18
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 12:00-18:00) on weekdays (Monday-Friday); across the full data file (consolidated). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1). This variable indicates the total wear time between 12:00-18:00 on weekdays; across the whole data file; in hours.
Real
Wkend afternoon pwear imputed
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 12:00-18:00) on weekend days (Saturday and Sunday); across the full data file (sleep imputed). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn. This variable indicates the total wear time between 12:00-18:00 on weekend days; across the whole data file; in hours.
Real
Wkend Pwear afternoon total time
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 12:00-18:00) on weekend days (Saturday and Sunday); across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 12:00-18:00 on weekend days; across the whole data file; in hours.
Real
Pwear wkend 12-18
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 12:00-18:00) on weekend days (Saturday and Sunday); across the full data file (consolidated). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1). This variable indicates the total wear time between 12:00-18:00 on weekend days; across the whole data file; in hours.
Real
Pwear by hr of day hr12 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 11:00-12:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 11:00-12:00; across the whole data file; in hours.
Real
Pwear by hr of day hr13 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 12:00-13:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 12:00-13:00; across the whole data file; in hours.
Real
Pwear by hr of day hr14 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 13:00-14:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 13:00-14:00; across the whole data file; in hours.
Real
Pwear by hr of day hr15 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 14:00-15:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 14:00-15:00; across the whole data file; in hours.
Real
Pwear by hr of day hr16 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 15:00-16:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 15:00-16:00; across the whole data file; in hours.
Real
Pwear by hr of day hr17 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 16:00-17:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 16:00-17:00; across the whole data file; in hours.
Real
Pwear by hr of day hr18 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 17:00-18:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 17:00-18:00; across the whole data file; in hours.
Real
Pwear by hr of day hr19 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 18:00-19:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 18:00-19:00; across the whole data file; in hours.
Real
Pwear by hr of day hr 1 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 00:00-01:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 00:00-01:00; across the whole data file; in hours.
Real
Pwear by hr of day hr20 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 19:00-20:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 19:00-20:00; across the whole data file; in hours.
Real
Pwear by hr of day hr21 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 20:00-21:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 20:00-21:00; across the whole data file; in hours.
Real
Pwear by hr of day hr22 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 21:00-22:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 21:00-22:00; across the whole data file; in hours.
Real
Pwear by hr of day hr23 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 22:00-23:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 22:00-23:00; across the whole data file; in hours.
Real
Pwear by hr of day hr24 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 23:00-00:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 23:00-00:00; across the whole data file; in hours.
Real
Pwear by hr of day hr 2 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 01:00-02:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 01:00-02:00; across the whole data file; in hours.
Real
Pwear by hr of day hr 3 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 02:00-03:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 02:00-03:00; across the whole data file; in hours.
Real
Pwear by hr of day hr 4 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 03:00-04:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 03:00-04:00; across the whole data file; in hours.
Real
Pwear by hr of day hr 5 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 04:00-05:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 04:00-05:00; across the whole data file; in hours.
Real
Pwear by hr of day hr 6 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 05:00-06:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 05:00-06:00; across the whole data file; in hours.
Real
Pwear by hr of day hr 7 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 06:00-07:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 06:00-07:00; across the whole data file; in hours.
Real
Pwear by hr of day hr 8 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 07:00-08:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 07:00-08:00; across the whole data file; in hours.
Real
Pwear by hr of day hr 9 non-imputed
Phase 2 data. Number of valid hours worn during free-living between 08:00-09:00; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 08:00-09:00; across the whole data file; in hours.
Real
Pwear Monday hrs non-imputed
Phase 2 data. Number of valid hours worn during free-living on a Monday; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time on a Monday; across the whole data file; in hours.
Real
Pwear morning total time
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 00:00-06:00); across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 00:00-06:00; across the whole data file; in hours.
Real
Pwear imputed
Phase 2 data. Time integral of wear probability based on accelerometry (number of hours considered worn during free-living) (sleep imputed). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn. This variable indicates the total wear time across the whole data file in hours.
Real
Pwear morning imputed
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 00:00-06:00); across the full data file (sleep imputed). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn. This variable indicates the total wear time between 00:00-06:00; across the whole data file; in hours.
Real
No of hrs during free-living 00-06
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 00:00-06:00); across the full data file (consolidated). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1). This variable indicates the total wear time between 00:00-06:00; across the whole data file; in hours.
Real
Wkday morning pwear imputed
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 00:00-06:00) on weekdays (Monday-Friday); across the full data file (sleep imputed). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn. This variable indicates the total wear time between 00:00-06:00 on weekdays; across the whole data file; in hours.
Real
Wkday Pwear morning total time
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 00:00-06:00) on weekdays (Monday-Friday); across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 00:00-06:00 on weekdays; across the whole data file; in hours.
Real
Pwear wkday 00-06
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 00:00-06:00) on weekdays (Monday-Friday); across the full data file (consolidated). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1). This variable indicates the total wear time between 00:00-06:00 on weekdays; across the whole data file; in hours.
Real
Pwear night total time
Phase 2 data. Number of valid hours worn during free-living in the night quadrant (between 18:00-00:00); across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 18:00-00:00; across the whole data file; in hours.
Real
Pwear noon total time
Phase 2 data. Number of valid hours worn during free-living in the noon quadrant (between 06:00-12:00); across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 06:00-12:00; across the whole data file; in hours.
Real
Pwear total time
Phase 2 data. Time integral of wear probability based on accelerometry (number of hours considered worn during free-living) (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time across the whole data file; in hours.
Real
Wkend morning pwear imputed
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 00:00-06:00) on weekend days (Saturday and Sunday); across the full data file (sleep imputed). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn. This variable indicates the total wear time between 00:00-06:00 on weekend days; across the whole data file; in hours.
Real
Wkend Pwear morning total time
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 00:00-06:00) on weekend days (Saturday and Sunday); across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 00:00-06:00 on weekend days; across the whole data file; in hours.
Real
Pwear wkend 00-06
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 00:00-06:00) on weekend days (Saturday and Sunday); across the full data file (consolidated). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1). This variable indicates the total wear time between 00:00-06:00 on weekend days; across the whole data file; in hours.
Real
Pwear night imputed
Phase 2 data. Number of valid hours worn during free-living in the night quadrant (between 18:00-00:00); across the full data file (sleep imputed). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn. This variable indicates the total wear time between 18:00-00:00; across the whole data file; in hours.
Real
No of hrs during free-living 18-00
Phase 2 data. Number of valid hours worn during free-living in the night quadrant (between 18:00-00:00); across the full data file (consolidated). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1). This variable indicates the total wear time between 18:00-00:00; across the whole data file; in hours.
Real
Wkday night pwear imputed
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 18:00-00:00) on weekdays (Monday-Friday); across the full data file (sleep imputed). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn. This variable indicates the total wear time between 18:00-00:00 on weekdays; across the whole data file; in hours.
Real
Pwear Saturday hrs non-imputed
Phase 2 data. Number of valid hours worn during free-living on a Saturday; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time on a Saturday; across the whole data file; in hours.
Real
Pwear Sunday hrs non-imputed
Phase 2 data. Number of valid hours worn during free-living on a Sunday; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time on a Sunday; across the whole data file; in hours.
Real
Pwear Thursday hrs non-imputed
Phase 2 data. Number of valid hours worn during free-living on a Thursday; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time on a Thursday; across the whole data file; in hours.
Real
Wkday Pwear night total time
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 18:00-00:00) on weekdays (Monday-Friday); across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 18:00-00:00 on weekdays; across the whole data file; in hours.
Real
Pwear wkday 18-00
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 18:00-00:00) on weekdays (Monday-Friday); across the full data file (consolidated). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1). This variable indicates the total wear time between 18:00-00:00 on weekdays; across the whole data file; in hours.
Real
Wkend night pwear imputed
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 18:00-00:00) on weekend days (Saturday and Sunday); across the full data file (sleep imputed). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn. This variable indicates the total wear time between 18:00-00:00 on weekend days; across the whole data file; in hours.
Real
Wkend Pwear night total time
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 18:00-00:00) on weekend days (Saturday and Sunday); across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 18:00-00:00 on weekend days; across the whole data file; in hours.
Real
Pwear wkend 18-00
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 18:00-00:00) on weekend days (Saturday and Sunday); across the full data file (consolidated). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1). This variable indicates the total wear time between 18:00-00:00 on weekend days; across the whole data file; in hours.
Real
Pwear noon imputed
Phase 2 data. Number of valid hours worn during free-living in the noon quadrant (between 06:00-12:00); across the full data file (sleep imputed). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn. This variable indicates the total wear time between 06:00-12:00; across the whole data file; in hours.
Real
Pwear Tuesday hrs non-imputed
Phase 2 data. Number of valid hours worn during free-living on a Tuesday; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time on a Tuesday; across the whole data file; in hours.
Real
Pwear Wednesday hrs non-imputed
Phase 2 data. Number of valid hours worn during free-living on a Wednesday; across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time on a Wednesday; across the whole data file; in hours.
Real
Wkday Pwear total time
Phase 2 data. Number of valid hours worn during free-living over weekdays (Monday-Friday); across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time on weekdays; across the whole data file; in hours.
Real
No of hrs during free-living 06-12
Phase 2 data. Number of valid hours worn during free-living in the noon quadrant (between 06:00-12:00); across the full data file (consolidated). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1). This variable indicates the total wear time between 06:00-12:00; across the whole data file; in hours.
Real
Wkday noon pwear imputed
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 06:00-12:00) on weekdays (Monday-Friday); across the full data file (sleep imputed). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn. This variable indicates the total wear time between 06:00-12:00 on weekdays; across the whole data file; in hours.
Real
Wkday Pwear noon total time
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 06:00-12:00) on weekdays (Monday-Friday); across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 06:00-12:00 on weekdays; across the whole data file; in hours.
Real
Pwear wkday 06-12
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 06:00-12:00) on weekdays (Monday-Friday); across the full data file (consolidated). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1). This variable indicates the total wear time between 06:00-12:00 on weekdays; across the whole data file; in hours.
Real
Wkend noon pwear imputed
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 06:00-12:00) on weekend days (Saturday and Sunday); across the full data file (sleep imputed). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn. This variable indicates the total wear time between 06:00-12:00 on weekend days; across the whole data file; in hours.
Real
Wkend Pwear noon total time
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 06:00-12:00) on weekend days (Saturday and Sunday); across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time between 06:00-12:00 on weekend days; across the whole data file; in hours.
Real
Wkend Pwear total time
Phase 2 data. Number of valid hours worn during free-living over weekend days (Saturday and Sunday); across the full data file (no sleep imputed / standard output). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This is the standard output (original) variable meaning no sleep imputation has been done. This variable indicates the total wear time on weekend days; across the whole data file; in hours.
Real
No of hours file was recording for
Phase 2 data. Number of hours file was recording for. The is the whole length of the file itself; regardless of whether it is being worn.
Real
Start date of free-living recording
Phase 2 data. Date of first day of free-living recording (Stata formatted). This date is regardless of whether the monitor was actually being worn; it is simply when the monitor started recording.
Date
Time resolution of processed data
Phase 2 data. The time resolution of the processed data outputted from accelerometry processing pipeline (pampro) and used by the post-processing scripts (minutes).
Integer
Pwear wkend 06-12
Phase 2 data. Number of valid hours worn during free-living in the morning quadrant (between 06:00-12:00) on weekend days (Saturday and Sunday); across the full data file (consolidated). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1). This variable indicates the total wear time between 06:00-12:00 on weekend days; across the whole data file; in hours.
Real
Total wear time
Phase 2 data. Time integral of wear probability based on accelerometry (number of hours considered worn during free-living) (consolidated). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1). This variable indicates the total wear time across the whole data file; in hours.
Real
Wkday pwear imputed
Phase 2 data. Number of valid hours worn during free-living over weekdays (Monday-Friday); across the full data file (sleep imputed). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn. This variable indicates the total wear time on weekdays; across the whole data file; in hours.
Real
Wkday valid hrs during free-living
Phase 2 data. Number of valid hours worn during free-living over weekdays (Monday-Friday); across the full data file (consolidated). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1). This variable indicates the total wear time on weekdays; across the whole data file; in hours.
Real
Wkend pwear imputed
Phase 2 data. Number of valid hours worn during free-living over weekend days (Saturday and Sunday); across the full data file (sleep imputed). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. This imputed variable is derived from imputing sleep data if certain criteria of limited night data are met (i.e. not worn between 00:00-06:00). Pwear is set to 1 during these hours to impute sleep if not worn. This variable indicates the total wear time on weekend days; across the whole data file; in hours.
Real
Wkend valid hrs during free-living
Phase 2 data. Number of valid hours worn during free-living over weekend days (Saturday and Sunday); across the full data file (consolidated). Non-wear periods are calculated as periods of time >=60 mins where the standard devigorous intensity activitytion of each of the three axes (x; y and z of the raw; triaxial accelerometry data) is <13mg. Both of these criteria are used to determine wear probability. Consolidated variable derived from either the original data (i.e. non-imputed) or imputed data where sleep has been imputed if certain criteria of limited night data are met (i.e. where inclusion criteria include= 2 (for details of inclusion criteria; see include variable)). In instances when the imputed data has been used in the consolidated variable; this will have a binary flag (imputed = 1). This variable indicates the total wear time on weekend days; across the whole data file; in hours.
Real
Location of GENEActiv wrist monitor
Phase 2 data. Location of the GENEActiv wrist monitor when worn for free-living (left/right). If wrist location was unknown; variable left as missing.
Text
OLINK assay GBP2
Phase 1 OLINK assay data for target GBP2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GCG
Phase 1 OLINK assay data for target GCG in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GCNT1
Phase 1 OLINK assay data for target GCNT1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GCP5
Phase 1 OLINK assay data for target GCP5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GDF-15
Phase 1 OLINK assay data for target GDF-15 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GDF-2
Phase 1 OLINK assay data for target GDF-2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GDF-8
Phase 1 OLINK assay data for target GDF-8 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GDNFR-alpha-3
Phase 1 OLINK assay data for target GDNFR-alpha-3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GDNF
Phase 1 OLINK assay data for target GDNF in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GDNF
Phase 1 OLINK assay data for target GDNF in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
GETABOUT
GETABOUT. Derived Intermediate not for general release. Data can be provided if necessary.
Categorical
Getting About
Which form of transport have you used MOST OFTEN in the last 4 weeks apart from your journey to and from work. Please tick one only.
Categorical
Getting About CLEANED
Getting About Error codes cleaned by DM team with this rule: CASE_TEXT. And then -10 errors cleaned by PA team.
Categorical
Cln variable: Mode of transport
Phase 2 data. Which form of transport have you used MOST OFTEN in the last 4 weeks apart from your journey to and from work. Please tick one only. 1 = car - motor vehicle; 2 = walking; 3 = public transport; 4 = cycling; -1 = left blank; Error codes cleaned by DM team with this rule: CASE_TEXT. And then -10 errors cleaned by PA team.
Categorical
Mode of transport
Phase 2 data. Questionnaire reads D1. Getting about. Which form of transport have you used MOST OFTEN in the last 4 weeks apart from your journey to and from work. Please tick one box only. DO NOT USE THIS VARIABLE. Use Gettingabout_CLEAN_P2 instead. 1 = car - motor vehicle; 2 = walking; 3 = public transport; 4 = cycling;
Categorical
OLINK assay GFRA2
Phase 1 OLINK assay data for target GFRA2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GFR-alpha-1
Phase 1 OLINK assay data for target GFR-alpha-1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GGT5
Phase 1 OLINK assay data for target GGT5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GH2
Phase 1 OLINK assay data for target GH2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GHRL
Phase 1 OLINK assay data for target GHRL in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GH
Phase 1 OLINK assay data for target GH in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GIF
Phase 1 OLINK assay data for target GIF in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GKN1
Phase 1 OLINK assay data for target GKN1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GLB1
Phase 1 OLINK assay data for target GLB1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Gln_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable Gln_raw. All values below detection limit set to 0. -7 = Internal standard undetectable (Concentration unreliable). The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. 2nd and final QC step on this var created new and final var BIOA_006.
Real
OLINK assay GLO1
Phase 1 OLINK assay data for target GLO1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GLRX
Phase 1 OLINK assay data for target GLRX in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Glucose 0 minutes
Fasting Serum Glucose measurement taken at 0 minutes in mmol/l
Real
Glucose 0 minutes
Phase 2 data. Fasting Serum Glucose measurement taken at 0 minutes in mmol/l
Real
Glucose 120 minutes
2 hour Glucose measurement taken at 120 minutes in mmol/l
Real
Glucose 120 minutes
Phase 2 data. 3 hour Glucose measurement taken at 120 minutes in mmol/l
Real
Time of glucose drink
Time glucose drink was drunk by participant.
Time
Glucose drink time
Phase 2 data. Time glucose drink was drunk by participant. For QC and filed team use. Not for analysis
Time
Glu_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable Glu_raw. All values below detection limit set to 0. -7 = Internal standard undetectable (Concentration unreliable). The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. 2nd and final QC step on this var created new and final var BIOA_007.
Real
Gly_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable Gly_raw. All values below detection limit set to 0. -7 = Internal standard undetectable (Concentration unreliable). The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. 2nd and final QC step on this var created new and final var BIOA_008.
Real
OLINK assay GM-CSF-R-alpha
Phase 1 OLINK assay data for target GM-CSF-R-alpha in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GNLY
Phase 1 OLINK assay data for target GNLY in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Hours of Golf
Please indicate the average length of time (in hours) you spent doing the activity per episode. Golf.
Integer
Hours of Golf CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Golf. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Golf hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Golf. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Golf hrs
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in hours) you spent doing the activity per episode. Golf. -1 = left blank. DO NOT USE THIS VARIABLE. Use golfHr_CLEAN_P2 instead.
Real
Minutes of Golf
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Golf.
Integer
Minutes of Golf CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Golf. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Golf min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Golf. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Golf min
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Golf. -1 = left blank. DO NOT USE THIS VARIABLE. Use golfMin_CLEAN_P2 instead.
Real
Frequency of Golf CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Golf. Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
golf_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for Golf
Real
Cln variable: Golf
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Golf. Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
golf_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Golf. Data normalised to DE template 1 data.
Categorical
Golf
Phase 2 data. Questionnaire reads D14. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Golf. DO NOT USE THIS VARIABLE. Use golf_CLEAN_P2 instead.
Real
Golf
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Golf. Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Golf DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Golf. Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in golf_T2. Instead use golf_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Golf DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Golf. Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in golf_T1. Instead use golf_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
OLINK assay GP1BA
Phase 1 OLINK assay data for target GP1BA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GP6
Phase 1 OLINK assay data for target GP6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GPC1
Phase 1 OLINK assay data for target GPC1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
GP ID
General Practitioner ID number. Replaces GP name variable from Release 5.
OLINK assay GPNMB
Phase 1 OLINK assay data for target GPNMB in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GPNMB
Phase 1 OLINK assay data for target GPNMB in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
GPS_Accepted
Has GPS data been accepted by field team yes or no. Data to be found on the GPS data log form in column with header Comments (Field Staff) lower half: Accepted?
Categorical
GPS_ExtraComment
Any additional comments provided on the GPS form on the form.
Text
DaysOfData
Total number of days over which the GPS data was collected. Data to be found on the GPS data log form in column with header Days of data.
Real
DeviceNr
Barcode number of GPS device used by volunteer. Data to be found on the GPS data log form in column with header GPS Device #.
Text
FieldStaffComments
Any comments the field staff have made about the GPS data. Data to be found on the GPS data log form in column with header Comments (Field Staff) top half.
Text
FileSize
Size of file containing the GPS data. Number entered as written omitting commas. Unit (KB) not entered if it was written. Data to be found on GPS data log form in column with header File Size.
Text
GPSissued
Data as entered on Study database. Has GPS been issued to participant? Yes-tick or no-left blank
GPS issued to participants
Phase 2 data. Data as entered on Study database. For study coordination purposes and QC only. Has GPS been issued to participant? 0 = no; 1 = yes;
Categorical
LogSheetNumber
Number of the GPS Data Log Sheet completed. Data located at the top of the GPS data log form in the section Sheet number.
Integer
LogSheetversion
Version number of GPS log sheet used. Data found on GPS data log form in the footer of the log sheet.
Real
StudySite
Study site where volunteer is registered. Data to be found on GPS data log form at the section Site at the top of the document next to the sheet number.
Text
DayofVisit
Date of 1st GPS visit - day. Data to be found on the GPS data log form in column with header Date.
Integer
MonthOfVisit
Date of 1st GPS visit - Month. Data to be found on the GPS data log form in column with header Date.
Integer
YearOfVisit
Date of 1st GPS visit - Year. Data to be found on the GPS data log form in column with header Date.
Integer
VolunteerComment
Any comments provided by the volunteer about wearing the GPS. Data to be found on the GPS data log form in column with header Comments from Volunteers.
Text
On medication
Are you taking any tablets or medicines at the moment? This data is also captured with GQV3_A1OnMedication and GQV4_A1OnMedication. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Meds and data derived into: gq_meds_DER. Please request those variables instead.
Categorical
Current Medication a BNF Code
BNF Code for medication a added by research team This data is also captured with GQV3_A2aCurrentMedicationBNFCode and GQV4_A2aCurrentMedicationBNFCode. You should request that data too.
Text
Dose Meds a
Dose of drug a. This data is also captured with GQV3_A2aCurrentMedicationDose and GQV4_A2aCurrentMedicationDose. You should request that data too.
Text
Name meds a
Name of drug a. This data is also captured with GQV3_A2aCurrentMedicationName and GQV4_A2aCurrentMedicationName. You should request that data too.
Text
Reason Meds a
Reason for taking the drug a. This data is also captured with GQV3_A2aCurrentMedicationReason and GQV4_A2aCurrentMedicationReason. You should request that data too.
Text
Current Medication b BNF Code
BNF Code for medication b added by research team. This data is also captured with GQV3_A2bCurrentMedicationBNFCode and GQV4_A2bCurrentMedicationBNFCode. You should request that data too.
Text
Dose Meds b
Dose of drug b. This data is also captured with GQV3_A2bCurrentMedicationDose and GQV4_A2bCurrentMedicationDose. You should request that data too.
Text
Name meds b
Name of drug b. This data is also captured with GQV3_A2bCurrentMedicationName and GQV4_A2bCurrentMedicationName. You should request that data too.
Text
Reason Meds b
Reason for taking the drug b. This data is also captured with GQV3_A2bCurrentMedicationReason and GQV4_A2bCurrentMedicationReason. You should request that data too.
Text
Current Medication c BNF Code
BNF Code for medication c added by research team. This data is also captured with GQV3_A2cCurrentMedicationBNFCode and GQV4_A2cCurrentMedicationBNFCode. You should request that data too.
Text
Dose Meds c
Dose of drug c. This data is also captured with GQV3_A2cCurrentMedicationDose and GQV4_A2cCurrentMedicationDose. You should request that data too.
Text
Name meds c
Name of drug c. This data is also captured with GQV3_A2cCurrentMedicationName and GQV4_A2cCurrentMedicationName. You should request that data too.
Text
reason Meds c
Reason for taking the drug c. This data is also captured with GQV3_A2cCurrentMedicationReason and GQV4_A2cCurrentMedicationReason. You should request that data too.
Text
Current Medication d BNF Code
BNF Code for medication d added by research team. This data is also captured with GQV3_A2dCurrentMedicationBNFCode and GQV4_A2dCurrentMedicationBNFCode. You should request that data too.
Text
Dose Meds d
Dose of drug d. This data is also captured with GQV3_A2dCurrentMedicationDose and GQV4_A2dCurrentMedicationDose. You should request that data too.
Text
Name meds d
Name of drug d. This data is also captured with GQV3_A2dCurrentMedicationName and GQV4_A2dCurrentMedicationName. You should request that data too.
Text
Reason Meds d
Reason for taking the drug d. This data is also captured with GQV3_A2dCurrentMedicationReason and GQV4_A2dCurrentMedicationReason. You should request that data too.
Text
Current Medication e BNF Code
BNF Code for medication e added by research team. This data is also captured with GQV3_A2eCurrentMedicationBNFCode and GQV4_A2eCurrentMedicationBNFCode. You should request that data too.
Text
Dose Meds e
Dose of drug e. This data is also captured with GQV3_A2eCurrentMedicationDose and GQV4_A2eCurrentMedicationDose. You should request that data too.
Text
Name meds e
Name of drug e. This data is also captured with GQV3_A2eCurrentMedicationName and GQV4_A2eCurrentMedicationName. You should request that data too.
Text
Reason Meds e
Reason for taking the drug e. This data is also captured with GQV3_A2eCurrentMedicationReason and GQV4_A2eCurrentMedicationReason. You should request that data too.
Text
Current Medication f BNF Code
BNF Code for medication f added by research team. This data is also captured with GQV3_A2fCurrentMedicationBNFCode and GQV4_A2fCurrentMedicationBNFCode. You should request that data too.
Text
Dose Meds f
Dose of drug f. This data is also captured with GQV3_A2fCurrentMedicationDose and GQV4_A2fCurrentMedicationDose. You should request that data too.
Text
Name meds f
Name of drug f. This data is also captured with GQV3_A2fCurrentMedicationName and GQV4_A2fCurrentMedicationName. You should request that data too.
Text
Reason Meds f
Reason for taking the drug f. This data is also captured with GQV3_A2fCurrentMedicationReason and GQV4_A2fCurrentMedicationReason. You should request that data too.
Text
Current Medication g BNF Code
BNF Code for medication g added by research team. This data is also captured with GQV3_A2gCurrentMedicationBNFCode and GQV4_A2gCurrentMedicationBNFCode. You should request that data too.
Text
Dose Meds g
Dose of drug g. This data is also captured with GQV3_A2gCurrentMedicationDose and GQV4_A2gCurrentMedicationDose. You should request that data too.
Text
Name meds g
Name of drug g. This data is also captured with GQV3_A2gCurrentMedicationName and GQV4_A2gCurrentMedicationName. You should request that data too.
Text
Reason Meds g
Reason for taking the drug g. This data is also captured with GQV3_A2gCurrentMedicationReason and GQV4_A2gCurrentMedicationReason. You should request that data too.
Text
Current Medication h BNF Code
BNF Code for medication h added by research team. This data is also captured with GQV3_A2hCurrentMedicationBNFCode and GQV4_A2hCurrentMedicationBNFCode. You should request that data too.
Text
Dose Meds h
Dose of drug h. This data is also captured with GQV3_A2hCurrentMedicationDose and GQV4_A2hCurrentMedicationDose. You should request that data too.
Text
Name meds h
Name of drug h. This data is also captured with GQV3_A2hCurrentMedicationName and GQV4_A2hCurrentMedicationName. You should request that data too.
Text
Reason Meds h
Reason for taking the drug h. This data is also captured with GQV3_A2hCurrentMedicationReason and GQV4_A2hCurrentMedicationReason. You should request that data too.
Text
On HRT
For women only. Are you on Hormone replacement therapy? This question was only asked in GenQ version 1 (25/11/2004 and 26/01/2005) so not all participants will have this data. From R8 phase 1 variable placed into variable: GQ_Med_hrt_v1 . Please request those variables instead.
Categorical
Birth weight value
What was your weight at birth value entered only. This data is also captured with GQV3_A3aBirthWeightImperial or GQV3_A3bBirthWeightMetric and GQV4_A3aBirthWeightImperial or GQV4_A3bBirthWeightMetric. You should request that data too.
Real
Birth weight unit
What was your weight at birth units only. This data is also captured with GQV3_A3aBirthWeightImperial or GQV3_A3bBirthWeightMetric and GQV4_A3aBirthWeightImperial or GQV4_A3bBirthWeightMetric. You should request that data too. From R8 phase 1 variable placed into variable: GQ_BWt_unit . Please request those variables instead.
Categorical
Birth weight unknown
Tick if you are not able to give your birth weight. This data is also captured with GQV3_A3cBirthWeightUnknown and GQV4_A3cBirthWeightUnknown. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_BWt_unknown . Please request those variables instead. -1 = left blank;
Categorical
Term of birth
When were you born (pre post or at term). This data is also captured with GQV3_A4aBorn and GQV4_A4aBorn. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Bterm and data derived into: gq_bterm_DER. Please request those variables instead.
Categorical
Dr report heart trouble
Has your doctor ever told you that you have heart trouble? This data is also captured with GQV3_A5aDrReportHeartTrouble and GQV4_A5aDrReportHeartTrouble. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Htn_dr and data derived into: gq_htn_dr_DER. Please request those variables. Instead.
Categorical
Chest pain ever
Have you ever had any pain or discomfort in your chest? If no proceed to question 7. If yes please answer the next question. This data is also captured with GQV3_A5bChestPain and GQV4_A5bChestPain. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_ChestPain_dr and data derived into: gq_chestpain_dr_DER. Please request those variables instead.
Categorical
Chest pain uphill
Do you experience pain or chest discomfort when you walk uphill or hurry? This data is also captured with GQV3_A5cChestPainUphill and GQV4_A5cChestPainUphill. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_ChestPain_uphill and data derived into: gq_chestpain_uphill_DER. Please request those variables instead.
Categorical
Chest pain normal pace
Do you experience pain or chest discomfort when you walk at an ordinary pace on the level? This data is also captured with GQV3_A5dChestPainNormalPace and GQV4_A5dChestPainNormalPace. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_ChestPain_normal and data derived into: gq_chestpain_normal_DER. Please request those variables instead.
Categorical
Action when chest discomfort
What do you do if you experience pain or chest discomfort while walking? This data is also captured with GQV3_A5eActionWhenChestDiscomfort and GQV4_A5eActionWhenChestDiscomfort. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_ChestPain_action and data derived into: gq_chestpain_action_DER. Please request those variables instead.
Categorical
Chest discomfort after stopping
If you stand still what happens to pain or chest discomfort? This data is also captured with GQV3_A5fChestDiscomfortAfterStopping and GQV4_A5fChestDiscomfortAfterStopping. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_ChestPain_stop and data derived into: gq_chestpain_stop_DER. Please request those variables instead.
Categorical
Feel faint or dizzy
Do you often feel faint or have spells of severe dizziness? This data is also captured with GQV3_A5gFeelFaint and GQV4_A5gFeelFaint. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_FeelFaint and data derived into: gq_feelfaint_DER. Please request those variables instead.
Categorical
Dr report high BP
Has a doctor ever told you that your blood pressure was too high? Yes or No. This data is also captured with GQV3_A5hDrReportBPHigh and GQV4_A5hDrReportBPHigh. You should request that data too.
Categorical
Treatment for high blood pressure
If you have been told that your blood pressure was too high are you now on treatment? This data is also captured with GQV3_A5iTreatmentHighBP and GQV4_A5iTreatmentHighBP. You should request that data too.
Categorical
Bone problems worse by exercise
Has your doctor ever told you that you have a bone or joint problem such as arthritis that has been aggravated by exercise or might be made worse by exercise? This data is also captured with GQV3_A5jBoneProblemsAggravatedByExercise and GQV4_A5jBoneProblem All phase 1 data from all 3 GenQs was merged into new variable: GQ_Bone_exercise and data derived into: gq_bone_exercise_DER. Please request those variables instead.
Categorical
Pregnancy status
Are you pregnant? This data is also captured with GQV3_A5kPregnant and GQV4_A5kPregnant. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Preg and data derived into: gq_preg_DER. Please request those variables instead.
Categorical
Any reason not to do PA
Is there any reason you know of that means you should not follow an activity programme even if you wanted to? This data is also captured with GQV3_A5lReasonNotToDoPA and GQV4_A5lReasonNotToDoPA. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_PA_reason and data derived into: gq_pa_reason_DER. Please request those variables instead.
Categorical
Smoke daily
Do you smoke daily? This question was only asked in GenQ version 1 (25/11/2004 and 26/01/2005) so not all participants will have this data. All phase 1 data from 1 GenQ was placed into variable: GQ_Sm_daily . Please request those variables instead.
Categorical
Smoke occasionally
Do you smoke occasionally? This question was only asked in GenQ version 1 (25/11/2004 and 26/01/2005) so not all participants will have this data. All phase 1 data from 1 GenQ was placed into variable: GQ_Sm_occasion . Please request those variables instead.
Categorical
Ever smoked
Have you ever smoked? This data is also captured with GQV3_B1aEverSmoked and GQV4_B1aEverSmoked. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Sm_ever and data derived into: gq_sm_ever_DER. Please request those variables instead.
Categorical
Ever smoked year quit
If you have ever smoked please add the year in which you quit. This data is also captured with GQV3_B1dYearQuit and GQV4_B1dYearQuit. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Sm_yearstop and data derived into: gq_sm_yearstop_DER. Please request those variables instead.
Text
Number of cigarettes per day
How many cigarettes did you or do you smoke a day on average? This data is also captured with GQV3_B1eNumberCigarettesPerDay and GQV4_B1eNumberCigarettesPerDay. You should request that data too. Note that if a decimal was provided by the participant data entry was asked to round it down if <0.5 and round up if >=0.5 All phase 1 data from all 3 GenQs was merged into new variable: GQ_Sm_Ncig and data derived into: gq_sm_ncig_DER. Please request those variables instead.
Integer
Number of cheroots smoked per day
How many cheroots did you or do you smoke a day on average? This data is also captured with GQV3_B1fNumberCherootsPerDay and GQV4_B1fNumberCherootsPerDay. You should request that data too. Note that if a decimal was provided by the participant data entry was asked to round it down if <0.5 and round up if >=0.5 All phase 1 data from all 3 GenQs was merged into new variable: GQ_Sm_Ncheroots and data derived into: gq_sm_ncheroots_DER. Please request those variables instead.
Integer
How many cigars smoked per day
How many cigars did you or do you smoke a day on average? This data is also captured with GQV3_B1gNumberCigarsPerDay and GQV4_B1gNumberCigarsPerDay. You should request that data too. Note that if a decimal was provided by the participant data entry was asked to round it down if <0.5 and round up if >=0.5 All phase 1 data from all 3 GenQs was merged into new variable: GQ_Sm_Ncigars and data derived into: gq_sm_ncigars_DER. Please request those variables instead.
Integer
Grams of tobacco per week
How much did you or do you smoke a day on average? Amount in grams of tobacco in a week. This data is also captured with GQV3_B1hTobaccoPerWeek and GQV4_B1hTobaccoPerWeek. You should request that data too. Note that if a decimal was provided by the participant data entry was asked to round it down if <0.5 and round up if >=0.5
Real
Units of beer lager or cider per week
How many units of Beer lager or cider do you consume in an average week? This data is also captured with GQV3_B3aUnitsBeerPerWk and GQV4_B3aUnitsBeerPerWk. You should request that data too.
Categorical
Units of wine per week
How many units of wine do you consume in an average week? This data is also captured with GQV3_B3bUnitsWinePerWk and GQV4_B3bUnitsWinePerWk. You should request that data too.
Categorical
Units of spirit per week
How many units of spirits do you consume in an average week? This data is also captured with GQV3_B3cUnitsSpiritsPerWk and GQV4_B3cUnitsSpiritsPerWk. You should request that data too.
Categorical
Units of fortified wine per week
How many units of Fortified wine (sherry Cinzano Campari) do you consume in an average week? This data is also captured with GQV3_B4dUnitsFortWinePerWk and GQV4_B4dUnitsFortWinePerWk. You should request that data too.
Categorical
Alcoholic drink frequency
How often do you usually have an alcoholic drink of any kind? This question was only asked in GenQ version 1 (25/11/2004) so not all participants will have this data. All phase 1 data from 2 GenQs was placed into variable: GQ_Alc_f ; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Eat breakfast
How often do you usually eat breakfast? Please tick the box which is most true. This data is also captured with GQV3_D1EatBreakfast and GQV4_D1EatBreakfast. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Breakfast and data derived into: gq_breakfast_DER. Please request those variables instead.
Categorical
Eat take-aways
When eating your main meal at home how often do you usually eat Home delivery or take-away meals. This data is also captured with GQV3_D2aEatTakeaways and GQV4_D2aEatTakeaways. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Takeaway and data derived into: gq_takeaway_DER. Please request those variables instead.
Categorical
Eat ready meals
When eating your main meal at home how often do you usually eat Ready-made meals/prepared foods. This data is also captured with GQV3_D2bEatReadyMeals and GQV4_D2bEatReadyMeals. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Readymeals and data derived into: gq_readymeals_DER. Please request those variables instead.
Categorical
Eat home cooked meals
When eating your main meal at home how often do you usually eat Home cooked meals. This data is also captured with GQV3_D2cEatHomeCookedMeals and GQV4_D2cEatHomeCookedMeals. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Homecooked and data derived into: gq_homecooked_DER. Please request those variables instead.
Categorical
Eat out
On average how often do you eat a meal outside of the home (restaurants pubs fast-food outlets etc)? This data is also captured with GQV3_D3EatOut and GQV4_D3EatOut. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eatout and data derived into: gq_eatout_DER. Please request those variables instead.
Categorical
Eat and watch TV
How often do you eat your meal while watching television or video? This data is also captured with GQV3_D4EatAndWatchTV and GQV4_D4EatAndWatchTV. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_eat and data derived into: gq_tv_eat_DER. Please request those variables instead.
Categorical
Snack and watch TV
Apart from meals how often do you eat snack foods while watching television? This data is also captured with GQV3_D5SnackAndWatchTV and GQV4_D5SnackAndWatchTV. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_snack and data derived into: gq_tv_snack_DER. Please request those variables instead.
Categorical
Main meal 6am - 7:59am
Had a main meal between 6am - 7:59am E.g. cooked dish e.g. meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV3_D601aMain and GQV4_D701aMain. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0204 and data derived into: gq_eat_main0204_DER. Please request those variables instead.
Categorical
Light meal 6-8am
Had a light meal between 6am - 7:59am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV3_D601bLight and GQV4_D701bLight. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0204 and data derived into: gq_eat_light0204_DER. Please request those variables instead.
Categorical
Snack 6-8am
Had a snack between 6am - 7:59am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV3_D601cSnack and GQV4_D701cSnack. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0204 and data derived into: gq_eat_snack0204_DER. Please request those variables instead.
Categorical
Drink only snack 6-8am
Had a drink only snack between 6am - 7:59am E.g. e.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV3_D601dDrink and GQV4_D701dDrink. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0204 and data derived into: gq_eat_drink0204_DER. Please request those variables instead.
Categorical
Main meal 8am - 9:59am
Had a main meal between 8am - 9:59am E.g. cooked dish e.g. meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV3_D602aMain and GQV4_D702aMain. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0406 and data derived into: gq_eat_main0406_DER. Please request those variables instead.
Categorical
Light meal 8-10am
Had a light meal between 8am - 9:59am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV3_D602bLight and GQV4_D702bLight. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0406 and data derived into: gq_eat_light0406_DER. Please request those variables instead.
Categorical
Snack 8-10am
Had a snack between 8am - 9:59am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV3_D602cSnack and GQV4_D702cSnack. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0406 and data derived into: gq_eat_snack0406_DER. Please request those variables instead.
Categorical
Drink only snack 8-10am
Had a drink only snack between 8am - 9:59am E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV3_D602dDrink and GQV4_D702dDrink. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0406 and data derived into: gq_eat_drink0406_DER. Please request those variables instead.
Categorical
Main meal 10am - 11:59am
Had a main meal between 10am - 11:59am E.g. cooked dish e.g. meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV3_D603aMain and GQV4_D703aMain. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0608 and data derived into: gq_eat_main0608_DER. Please request those variables instead.
Categorical
Light meal 10am-12pm
Had a light meal between 10am - 11:59pm E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV3_D603bLight and GQV4_D703bLight. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0608 and data derived into: gq_eat_light0608_DER. Please request those variables instead.
Categorical
Snack 10am-11:59 pm
Had a snack between 10am - 11:59pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV3_D603cSnack and GQV4_D703cSnack. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0608 and data derived into: gq_eat_snack0608_DER. Please request those variables instead.
Categorical
Drink only snack 10am-12pm
Had a drink only snack between 10am - 11:59pm E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV3_D603dDrink and GQV4_D703dDrink. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0608 and data derived into: gq_eat_drink0608_DER. Please request those variables instead.
Categorical
Main meal 12am - 1:59pm
Had a main meal between 12am - 1:59pm E.g. cooked dish e.g. meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV3_D604aMain and GQV4_D704aMain. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0810 and data derived into: gq_eat_main0810_DER. Please request those variables instead.
Categorical
Light meal 12-1:59 pm
Had a light meal between 12pm - 1:59pm E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV3_D604bLight and GQV4_D704bLight. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0810 and data derived into: gq_eat_light0810_DER. Please request those variables instead.
Categorical
Snack 12-2pm
Had a snack between 12pm - 1:59pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV3_D604cSnack and GQV4_D704cSnack. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0810 and data derived into: gq_eat_snack0810_DER. Please request those variables instead.
Categorical
Drink only snack 12-2pm
Had a drink only snack between 12pm - 1:59pm E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV3_D604dDrink and GQV4_D704dDrink. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0810 and data derived into: gq_eat_drink0810_DER. Please request those variables instead.
Categorical
Main meal 2-3:59pm
Had a main meal between 2pm - 3:59pm E.g. cooked dish e.g. meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV3_D605aMain and GQV4_D705aMain. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1012 and data derived into: gq_eat_main1012_DER. Please request those variables instead.
Categorical
Light meal 2-3:59 pm
Had a light meal between 2pm - 3:59pm E.g. porridge cereal toast sandwiches soup salad omelette. This data is also captured with GQV3_D605bLight and GQV4_D705bLight. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1012 and data derived into: gq_eat_light1012_DER. Please request those variables instead.
Categorical
Snack 2-3:59 pm
Had a snack between 2pm - 3:59pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. This data is also captured with GQV3_D605cSnack and GQV4_D705cSnack. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1012 and data derived into: gq_eat_snack1012_DER. Please request those variables instead.
Categorical
Drink only snack 2-3:59pm
Had a drink only snack between 2pm - 3:59pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV3_D605dDrink and GQV4_D705dDrink. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1012 and data derived into: gq_eat_drink1012_DER. Please request those variables instead.
Categorical
Main meal 4pm - 5:59pm
Had a main meal between 4pm - 5:59pm E.g. cooked dish e.g. meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV3_D606aMain and GQV4_D706aMain. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1214 and data derived into: gq_eat_main1214_DER. Please request those variables instead.
Categorical
Light meal 4-6pm
Had a light meal between 4pm - 5:59pm E.g. porridge cereal toast sandwiches soup salad omelette. This data is also captured with GQV3_D606bLight and GQV4_D706bLight. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1214 and data derived into: gq_eat_light1214_DER. Please request those variables instead.
Categorical
Snack 4-6pm
Had a snack between 4pm - 5:59pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. This data is also captured with GQV3_D606cSnack and GQV4_D706cSnack. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1214 and data derived into: gq_eat_snack1214_DER. Please request those variables instead.
Categorical
Drink only snack 4-6pm
Had a drink only snack between 4pm - 5:59pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV3_D606dDrink and GQV4_D706dDrink. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1214 and data derived into: gq_eat_drink1214_DER. Please request those variables instead.
Categorical
Main meal 6-8pm
Had a main meal between 6pm - 7:59pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV3_D607aMain and GQV4_D707aMain. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1416 and data derived into: gq_eat_main1416_DER. Please request those variables instead.
Categorical
Light meal 6-8pm
Had a light meal between 6pm - 7:59pm E.g. porridge cereal toast sandwiches soup salad omelette. This data is also captured with GQV3_D607bLight and GQV4_D707bLight. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1416 and data derived into: gq_eat_light1416_DER. Please request those variables instead.
Categorical
Snack 6-8pm
Had a snack between 6pm - 7:59pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. This data is also captured with GQV3_D607cSnack and GQV4_D707cSnack. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1416 and data derived into: gq_eat_snack1416_DER. Please request those variables instead.
Categorical
Drink only snack 6-8pm
Had a drink only snack between 6pm - 7:59pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV3_D607dDrink and GQV4_D707dDrink. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1416 and data derived into: gq_eat_drink1416_DER. Please request those variables instead.
Categorical
Main meal 8pm - 9:59 pm
Had a main meal between 8pm - 9:59pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV3_D608aMain and GQV4_D708aMain. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1618 and data derived into: gq_eat_main1618_DER. Please request those variables instead.
Categorical
Light meal 8-9:59 pm
Had a light meal between 8pm - 9:59pm E.g. porridge cereal toast sandwiches soup salad omelette. This data is also captured with GQV3_D608bLight and GQV4_D708bLight. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1618 and data derived into: gq_eat_light1618_DER. Please request those variables instead.
Categorical
Snack 8-9:59 pm
Had a snack between 8pm - 9:59pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV3_D608cSnack and GQV4_D708cSnack. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1618 and data derived into: gq_eat_snack1618_DER. Please request those variables instead.
Categorical
Drink only snack 8-9:59pm
Had a drink only snack between 8pm - 9:59pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV3_D608dDrink and GQV4_D708dDrink. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1618 and data derived into: gq_eat_drink1618_DER. Please request those variables instead.
Categorical
Main meal 10pm-12am
Had a main meal between 10pm - 11:59am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV3_D609aMain and GQV4_D709aMain. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1820 and data derived into: gq_eat_main1820_DER. Please request those variables instead.
Categorical
Light meal 10pm-12am
Had a light meal between 10pm - 11:59am E.g. porridge cereal toast sandwiches soup salad omelette. This data is also captured with GQV3_D609bLight and GQV4_D709bLight. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1820 and data derived into: gq_eat_light1820_DER. Please request those variables instead.
Categorical
Snack 10-11:59 pm
Had a snack between 10pm - 11:59am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. This data is also captured with GQV3_D609cSnack and GQV4_D709cSnack. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1820 and data derived into: gq_eat_snack1820_DER. Please request those variables instead.
Categorical
Drink only snack 10-11:59pm
Had a drink only snack between 10pm - 11:59am E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV3_D609dDrink and GQV4_D709dDrink. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1820 and data derived into: gq_eat_drink1820_DER. Please request those variables instead.
Categorical
Main meal 12 am - 1:59 am
Had a main meal between 12am - 1:59am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV3_D610aMain and GQV4_D710aMain. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main2022 and data derived into: gq_eat_main2022_DER. Please request those variables instead.
Categorical
Light meal 12 am - 1:59 am
Had a light meal between 12am - 1:59am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV3_D610bLight and GQV4_D710bLight. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light2022 and data derived into: gq_eat_light2022_DER. Please request those variables instead.
Categorical
Snack 12 am - 1:59 am
Had a snack between 12am - 1:59am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV3_D610cSnack and GQV4_D710cSnack. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack2022 and data derived into: gq_eat_snack2022_DER. Please request those variables instead.
Categorical
Drink only snack 12-1:59am
Had a drink only snack between 12am - 1:59am E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV3_D610dDrink and GQV4_D710dDrink. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink2022 and data derived into: gq_eat_drink2022_DER. Please request those variables instead.
Categorical
Main meal 2-3:59 am
Had a main meal between 2am - 3:59am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV3_D611aMain and GQV4_D711aMain. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main2224 and data derived into: gq_eat_main2224_DER. Please request those variables instead.
Categorical
Light meal 2-3:59 am
Had a light meal between 2am - 3:59am E.g. porridge cereal toast sandwiches soup salad omelette. This data is also captured with GQV3_D611bLight and GQV4_D711bLight. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light2224 and data derived into: gq_eat_light2224_DER. Please request those variables instead.
Categorical
Snack 2-4am
Had a snack between 2am - 3:59am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV3_D611cSnack and GQV4_D711cSnack. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack2224 and data derived into: gq_eat_snack2224_DER. Please request those variables instead.
Categorical
Drink only snack 2-3:59am
Had a drink only snack between 2am - 3:59am E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV3_D611dDrink and GQV4_D711dDrink. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink2224 and data derived into: gq_eat_drink2224_DER. Please request those variables instead.
Categorical
Main meal 4am - 6am
Had a main meal between 4am - 5:59am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV3_D612aMain and GQV4_D712aMain. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main2402 and data derived into: gq_eat_main2402_DER. Please request those variables instead.
Categorical
Light meal 4-6am
Had a light meal between 4am - 5:59am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV3_D612bLight and GQV4_D712bLight. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light2402 and data derived into: gq_eat_light2402_DER. Please request those variables instead.
Categorical
Snack 4-6am
Had a snack between 4am - 5:59am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV3_D612cSnack and GQV4_D712cSnack. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack2402 and data derived into: gq_eat_snack2402_DER. Please request those variables instead.
Categorical
Drink only snack 4-6am
Had a drink only snack between 4am - 5:59am E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV3_D612dDrink and GQV4_D712dDrink. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink2402 and data derived into: gq_eat_drink2402_DER. Please request those variables instead.
Categorical
Frequency of eating Vegetables
During the course of last year how many times a week did you eat Medium serving of Vegetables (not including potatoes). This data is also captured with GQV3_D7aVeg. You should request that data too. Not asked in GQV4. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_veg and data derived into: gq_eat_veg_DER. Please request those variables instead.
Categorical
Frequency of eating salads
During the course of last year how many times a week did you eat Medium serving of Salads. This data is also captured with GQV3_D7bSalad. You should request that data too. This data is not captured in GQV4. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_salads and data derived into: gq_eat_salads_DER. Please request those variables instead.
Categorical
Frequency of eating fruit
During the course of last year how many times a week did you eatMedium serving or 1 fruit of Fruit and fruit products (not including fruit juice). This data is also captured with GQV3_D7cFruit. You should request that data too. This data is not captured i All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_fruit and data derived into: gq_eat_fruit_DER. Please request those variables instead.
Categorical
Frequency of eating Fish
During the course of last year how many times a week did you eat medium serving of Fish and fish products. This data is also captured with GQV3_D7dFish. You should request that data too. Not asked in GQV4. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_fish and data derived into: gq_eat_fish_DER. Please request those variables instead.
Categorical
Frequency of eating Meat
During the course of last year how many times a week did you eat Medium serving of Meat meat products and meat dishes (including bacon ham or chicken). This data is also captured with GQV3_D7eMeat. You should request that data too. This data is not capt All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_meat and data derived into: gq_eat_meat_DER. Please request those variables instead.
Categorical
Weight Watchers' diet
Currently on a 'Weight Watchers' diet. This data is also captured with GQV3_D8aWW and GQV4_D8aWW. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_ww and data derived into: gq_diet_ww_DER. Please request those variables instead.
Categorical
Slimmers World' diet
Currently on a 'Slimmers World' diet. This data is also captured with GQV3_D8bSW and GQV4_D8bSW. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_slim and data derived into: gq_diet_slim_DER. Please request those variables instead. nstead.
Categorical
Low fat diet
Currently on a low fat diet. This data is also captured with GQV3_D8cLFD and GQV4_D8cLFD. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_lowf and data derived into: gq_diet_lowf_DER. Please request those variables instead. nstead.
Categorical
Low carbohydrate diet
Currently on a low carbohydrate diet eg Atkins Diet. This data is also captured with GQV3_D8dLCD and GQV4_D8dLCD. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_lowc and data derived into: gq_diet_lowc_DER. Please request those variables instead. nstead.
Categorical
Vegetarian diet
Currently on a vegetarian diet. This data is also captured with GQV3_D8eVegetarian and GQV4_D8eVegetarian. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_veg and data derived into: gq_diet_veg_DER. Please request those variables instead.
Categorical
Vegan diet
Currently on a vegan diet. This data is also captured with GQV3_D8fVegan and GQV4_D8fVegan. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_vegan and data derived into: gq_diet_vegan_DER. Please request those variables instead. nstead.
Categorical
Kosher diet
Currently on a Kosher diet. This data is also captured with GQV3_D8gKosher and GQV4_D8gKosher. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_kosh and data derived into: gq_diet_kosh_DER. Please request those variables instead. nstead.
Categorical
Halal diet
Currently on a Halal diet. This data is also captured with GQV3_D8hHalal and GQV4_D8hHalal. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_halal and data derived into: gq_diet_halal_DER. Please request those variables instead. nstead.
Categorical
Other diet
Currently on an other diet. Please describe. This data is also captured with GQV3_D8iOther and GQV4_D8iOther. You should request that data too.
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Full time work status
What is your current work status? In work - full time i.e. more than 30 hours per week. This data is also captured with GQV3_C1aFullTime and GQV4_C1aFullTime. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_full and data derived into: gq_job_full_DER. Please request those variables instead.
Categorical
Part time work status
What is your current work status? Part time work i.e. less than 30 hours per week. This data is also captured with GQV3_C1bPartTime and GQV4_C1bPartTime. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_part and data derived into: gq_job_part_DER. Please request those variables instead.
Categorical
Keeping house work status
What is your current work status? Keeping house. This data is also captured with GQV3_C1cKeepingHouse and GQV4_C1cKeepingHouse. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_house and data derived into: gq_job_house_DER. Please request those variables instead.
Categorical
Retired work status
What is your current work status? Wholly retired from work. This data is also captured with GQV3_C1dRetired and GQV4_C1dRetired. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_retired and data derived into: gq_job_retired_DER. Please request those variables instead.
Categorical
Obtained new job work status
What is your current work status? Waiting to start a new job already obtained. This data is also captured with GQV3_C1eObtainedNewJob and GQV4_C1eObtainedNewJob. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_newjob and data derived into: gq_job_newjob_DER. Please request those variables instead.
Categorical
Unemployed work status
What is your current work status? Unemployed and looking for work. This data is also captured with GQV3_C1fUnemployed and GQV4_C1fUnemployed. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_unempl and data derived into: gq_job_unempl_DER. Please request those variables instead.
Categorical
Temporarily sick work status
What is your current work status? Out of work as temporarily sick. This data is also captured with GQV3_C1gTempSick and GQV4_C1gTempSick. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_tempsick and data derived into: gq_job_tempsick_DER. Please request those variables instead.
Categorical
Permanently sick work status
What is your current work status? Permanently sick or disabled. This data is also captured with GQV3_C1hPermSick and GQV4_C1hPermSick. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_sick and data derived into: gq_job_sick_DER. Please request those variables instead.
Categorical
Work status other
What is your current work status? If other please specify. This data is also captured with GQV3_C1iOther and GQV4_C1iOther. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_oth and data derived into: gq_job_oth_DER. Please request those variables instead.
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Last job title
Please could you give us some details about your present or last job. What is (was) the title of your job ? This question was only asked in GenQ version 1 (25/11/2004 and 26/01/2005) so not all participants will have this data.
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Kind of work
What kind of work do (did) you do in your job ? This question was only asked in GenQ version 1 (25/11/2004 and 26/01/2005) so not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_type . Please request those variables instead.
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Training or qualifications for job
What training or qualifications are (were) needed for your job ? This question was only asked in GenQ version 1 (25/11/2004 and 26/01/2005) so not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_qual . Please request those variables instead.
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Employment type without employee data
Are (were) you working as an employee / as self-employed. This data is captured slightly differently with GQV3_C2EmployeeType and GQV4_C2EmployeeType. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Emp_type and data derived into: gq_emp_type_DER. Please request those variables instead.
Categorical
Supervisory status with numbers
Present or your last job: Do (did) you supervise or have management responsibility for the work of other people and if so for up to 24 or more than 24? This data is captured (without numbers) with GQV3_C4SupervisoryStatus and GQV4_C4SupervisoryStatus. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Emp_supervise and data derived into: gq_emp_supervise_DER. Please request those variables instead.
Categorical
Number of employees
Present or your last job: If you are (were) a supervisor or manager how many people are (were) employed in the firm company or establishment. This data is captured slightly differently with GQV3_C3NumberPeopleEmployed and GQV4_C3NumberPeopleEmployed. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Emp_n and data derived into: gq_emp_n_DER. Please request those variables instead.
Categorical
Household Income
Please can you indicate what your household income is. This data is also captured with GQV3_C8HouseholdIncome and GQV4_C8HouseholdIncome (with slightly different wording). You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Income and data derived into: gq_income_DER. Please request those variables instead.
Categorical
Age finished full time education
At what age did you finish full time education? (in years). This data is also captured with GQV3_C7AgeEndFTE and GQV4_C7AgeEndFTE. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_age and data derived into: gq_edu_age_DER. Please request those variables instead.
Real
School leaving certificate
Do you have any of the following qualifications? (tick all applicable). School Leaving certificate. This data is also captured with GQV3_C6aSLC and GQV4_C6aSLC. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_SLC and data derived into: gq_edu_slc_DER. Please request those variables instead.
Categorical
CSE qualification
Do you have any of the following qualifications? (tick all applicable). CSE. This data is also captured with GQV3_C6bCSE and GQV4_C6bCSE. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_CSE and data derived into: gq_edu_cse_DER. Please request those variables instead.
Categorical
O level or GCSE qualification
Do you have any of the following qualifications? (tick all applicable). GCE O level or GCSE. This data is also captured with GQV3_C6cGCSE and GQV4_C6cGCSE. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_GCSE and data derived into: gq_edu_gcse_DER. Please request those variables instead.
Categorical
Matriculation qualification
Do you have any of the following qualifications? (tick all applicable). Matriculation. This data is also captured with GQV3_C6dMatriculation and GQV4_C6dMatriculation. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_matricul and data derived into: gq_edu_matricul_DER. Please request those variables instead.
Categorical
A level qualification
Do you have any of the following qualifications? (tick all applicable). GCE A Level AS level Highers This data is also captured with GQV3_C6eALevels and GQV4_C6eALevels. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_Alev and data derived into: gq_edu_alev_DER. Please request those variables instead.
Categorical
Technical or C&G qualification
Do you have any of the following qualifications? (tick all applicable). Technical College exams City & Guilds. This data is also captured with GQV3_C6fC_G and GQV4_C6fC_G. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_TechCG and data derived into: gq_edu_techcg_DER. Please request those variables instead.
Categorical
HND or GNVQ qualification
Do you have any of the following qualifications? (tick all applicable). HND or GNVQ. This data is also captured with GQV3_C6gHND_GNVQ and GQV4_C6gHND_GNVQ. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_HND_NVQ and data derived into: gq_edu_hnd_nvq_DER. Please request those variables instead.
Categorical
Completed apprenticeship
Do you have any of the following qualifications? (tick all applicable). Completed Apprenticeship. This data is also captured with GQV3_C6hApprenticeship and GQV4_C6hApprenticeship. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_apprentice and data derived into: gq_edu_apprentice_DER. Please request those variables instead.
Categorical
Secretarial College qualification
Do you have any of the following qualifications? (tick all applicable). Secretarial College Exams. This data is also captured with GQV3_C6iSecretarial and GQV4_C6iSecretarial. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_secret and data derived into: gq_edu_secret_DER. Please request those variables instead.
Categorical
HNC or NVQ qualification
Do you have any of the following qualifications? (tick all applicable). Teaching Diploma HNC NVQ. This data is also captured with GQV3_C6jHNC and GQV4_C6jHNC. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_HNC and data derived into: gq_edu_hnc_DER. Please request those variables instead.
Categorical
University degree qualification
Do you have any of the following qualifications? (tick all applicable). University Degree. This data is also captured with GQV3_C6kDegree and GQV4_C6kDegree. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_degree and data derived into: gq_edu_degree_DER. Please request those variables instead.
Categorical
Trade certificate qualification
Do you have any of the following qualifications? (tick all applicable). Trade Certificates. This data is also captured with GQV3_C6lTradeCertificate and GQV4_C6lTradeCertificate. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_trade and data derived into: gq_edu_trade_DER. Please request those variables instead.
Categorical
Other qualifications
Do you have any of the following qualifications? (tick all applicable). Other please describe. This data is also captured with GQV3_C6mOther and GQV4_C6mOther. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_others and data derived into: gq_edu_others_DER. Please request those variables instead.
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No Qualifications
Do you have any of the following qualifications? (tick all applicable). None. This data is also captured with GQV3_C6nNone and GQV4_C6nNone. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_none and data derived into: gq_edu_none_DER. Please request those variables instead.
Categorical
Can use car or van
Does your household have any cars or vans normally available for its use? This data is also captured with GQV3_C10Cars and GQV4_C10Cars (with slightly different wording). You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Owncars and data derived into: gq_owncars_DER. Please request those variables instead.
Categorical
Own or buying house
Do you own your own (or are you buying) home? This data is also captured with GQV3_C11aOwnHouse and GQV4_C11aOwnHouse. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Ownhouse and data derived into: gq_ownhouse_DER. Please request those variables instead.
Categorical
Rent house
Do you rent your own home? This data is also captured with GQV3_C11bRentHouse and GQV4_C11bRentHouse. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Renthouse and data derived into: gq_renthouse_DER. Please request those variables instead.
Categorical
Partners job details
Only for women who currently live with their partner. Please could you give us some details about your husband/partner's present or last job. What kind of work does (did) he do in his job? What training or qualifications are (were) needed for his job? Only asked in version 1 of the questionnaire. The data was put into new variable: GQ_Job_partner . Please request that variable instead.
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Partners employment status
Is (was) he working as an employee or self-employed. This question was only asked in GenQ version 1 (25/11/2004 and 26/01/2005) so not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_others_txt . Please request those variables instead.
Categorical
Partners management status
Does (did) he supervise or have management responsibility for the work of other people? This question was only asked in GenQ version 1 (25/11/2004 and 26/01/2005) so not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_partnermanage. Please request those variables instead.
Categorical
Additional comments on gen questionnaire version 1
GQV1 additional comments made on any page with page number and text. This data is also captured with GQV3_FSGQComments and GQV4_FSGQComments. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: FSGQComments_Updated . Please request those variables instead.
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On medication
Are you taking any tablets or medicines at the moment? This data is also captured with GQV1_A1OnMedication or GQV4_A1OnMedication. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Meds and data derived into: gq_meds_DER. Please request those variables instead.
Categorical
Current Medication a BNF Code
BNF Code for medication a added by research team This data is also captured with GQV1_A2aCurrentMedicationBNFCode or GQV4_A2aCurrentMedicationBNFCode. You should be given that data too.
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Dose Meds a
Dose of drug a. This data is also captured with GQV1_A2aCurrentMedicationDose or GQV4_A2aCurrentMedicationDose. You should be given that data too.
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Name meds a
Name of drug a. This data is also captured with GQV1_A2aCurrentMedicationName or GQV4_A2aCurrentMedicationName. You should be given that data too.
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Reason Meds a
Reason for taking the drug a. This data is also captured with GQV1_A2aCurrentMedicationReason or GQV4_A2aCurrentMedicationReason. You should be given that data too.
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Current Medication b BNF Code
BNF Code for medication b added by research team. This data is also captured with GQV1_A2bCurrentMedicationBNFCode or GQV4_A2bCurrentMedicationBNFCode. You should be given that data too.
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Dose Meds b
Dose of drug b. This data is also captured with GQV1_A2bCurrentMedicationDose or GQV4_A2bCurrentMedicationDose. You should be given that data too.
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Name meds b
Name of drug b. This data is also captured with GQV1_A2bCurrentMedicationName or GQV4_A2bCurrentMedicationName. You should request that data too.
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Reason Meds b
Reason for taking the drug b. This data is also captured with GQV1_A2bCurrentMedicationReason or GQV4_A2bCurrentMedicationReason. You should be given that data too.
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Current Medication c BNF Code
BNF Code for medication c added by research team. This data is also captured with GQV1_A2cCurrentMedicationBNFCode or GQV4_A2cCurrentMedicationBNFCode. You should be given that data too.
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Dose Meds c
Dose of drug c. This data is also captured with GQV1_A2cCurrentMedicationDose or GQV4_A2cCurrentMedicationDose. You should be given that data too.
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Name meds c
Name of drug c. This data is also captured with GQV1_A2cCurrentMedicationName or GQV4_A2cCurrentMedicationName. You should be given that data too.
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Reason Meds c
Reason for taking the drug c. This data is also captured with GQV1_A2cCurrentMedicationReason or GQV4_A2cCurrentMedicationReason. You should be given that data too.
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Current Medication d BNF Code
BNF Code for medication d added by research team. This data is also captured with GQV1_A2dCurrentMedicationBNFCode or GQV4_A2dCurrentMedicationBNFCode. You should be given that data too.
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Dose Meds d
Dose of drug d. This data is also captured with GQV1_A2dCurrentMedicationDose or GQV4_A2dCurrentMedicationDose. You should be given that data too.
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Name meds d
Name of drug d. This data is also captured with GQV1_A2dCurrentMedicationName or GQV4_A2dCurrentMedicationName. You should be given that data too.
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Reason Meds d
Reason for taking the drug d. This data is also captured with GQV1_A2dCurrentMedicationReason or GQV4_A2dCurrentMedicationReason. You should be given that data too.
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Current Medication e BNF Code
BNF Code for medication e added by research team. This data is also captured with GQV1_A2eCurrentMedicationBNFCode or GQV4_A2eCurrentMedicationBNFCode. You should be given that data too.
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Dose Meds e
Dose of drug e. This data is also captured with GQV1_A2eCurrentMedicationDose or GQV4_A2eCurrentMedicationDose. You should be given that data too.
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Name meds e
Name of drug e. This data is also captured with GQV1_A2eCurrentMedicationName or GQV4_A2eCurrentMedicationName. You should be given that data too.
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Reason Meds e
Reason for taking the drug e. This data is also captured with GQV1_A2eCurrentMedicationReason or GQV4_A2eCurrentMedicationReason. You should be given that data too.
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Current Medication f BNF Code
BNF Code for medication f added by research team. This data is also captured with GQV1_A2fCurrentMedicationBNFCode or GQV4_A2fCurrentMedicationBNFCode. You should be given that data too.
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Dose Meds f
Dose of drug f. This data is also captured with GQV1_A2fCurrentMedicationDose or GQV4_A2fCurrentMedicationDose. You should be given that data too.
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Name meds f
Name of drug f. This data is also captured with GQV1_A2fCurrentMedicationName or GQV4_A2fCurrentMedicationName. You should be given that data too.
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Reason Meds f
Reason for taking the drug f. This data is also captured with GQV1_A2fCurrentMedicationReason or GQV4_A2fCurrentMedicationReason. You should be given that data too.
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Current Medication g BNF Code
BNF Code for medication g added by research team. This data is also captured with GQV1_A2gCurrentMedicationBNFCode or GQV4_A2gCurrentMedicationBNFCode. You should request that data too.
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Dose Meds g
Dose of drug g. This data is also captured with GQV1_A2gCurrentMedicationDose or GQV4_A2gCurrentMedicationDose. You should be given that data too.
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Name meds g
Name of drug b. This data is also captured with GQV1_A2gCurrentMedicationName or GQV4_A2gCurrentMedicationName. You should request that data too.
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Reason Meds g
Reason for taking the drug g. This data is also captured with GQV1_A2gCurrentMedicationReason or GQV4_A2gCurrentMedicationReason. You should be given that data too.
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Current Medication h BNF Code
BNF Code for medication h added by research team. This data is also captured with GQV1_A2hCurrentMedicationBNFCode or GQV4_A2hCurrentMedicationBNFCode. You should be given that data too.
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Dose Meds h
Dose of drug h. This data is also captured with GQV1_A2hCurrentMedicationDose or GQV4_A2hCurrentMedicationDose. You should be given that data too.
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Name meds h
Name of drug h. This data is also captured with GQV1_A2hCurrentMedicationName or GQV4_A2hCurrentMedicationName. You should be given that data too.
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Reason Meds h
Reason for taking the drug h. This data is also captured with GQV1_A2hCurrentMedicationReason or GQV4_A2hCurrentMedicationReason. You should be given that data too.
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Birth weight imperial
What was your weight at birth in pounds and ounces. This data is also captured with GQV1_A4aBirthWeight and GQV1_A4bBirthWeightUnits or GQV4_A3aBirthWeightImperial. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_BWt_imperial . Please request those variables instead.
Real
Birth weight metric
What was your weight at birth in kilograms. This data is also captured with GQV1_A4aBirthWeight and GQV1_A4bBirthWeightUnits or GQV4_A3bBirthWeightMetric. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_BWt_metric . Please request those variables instead.
Real
Birth weight unknown
Tick if you are not able to give your birth weight. This data is also captured with GQV1_A4cBirthWeightUnknown and GQV4_A3cBirthWeightUnknown. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_BWt_unknown . Please request those variables instead.
Categorical
Term of birth
When were you born (pre post or at term). This data is also captured with GQV1_A4dBorn or GQV4_A4aBorn. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Bterm and data derived into: gq_bterm_DER. Please request those variables instead.
Categorical
Dr report heart trouble
Has your doctor ever told you that you have heart trouble? This data is also captured with GQV1_A5aDrReportHeartTrouble or GQV4_A5aDrReportHeartTrouble. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Htn_dr and data derived into: gq_htn_dr_DER. Please request those variables instead.
Categorical
Chest pain ever
Have you ever had any pain or discomfort in your chest? If no proceed to question 7. If yes please answer the next question. This data is also captured with GQV1_A5bChestPain or GQV4_A5bChestPain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_ChestPain_dr and data derived into: gq_chestpain_dr_DER. Please request those variables instead.
Categorical
Chest pain uphill
Do you experience pain or chest discomfort when you walk uphill or hurry? This data is also captured with GQV1_A5cChestPainUphill or GQV4_A5cChestPainUphill. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_ChestPain_uphill and data derived into: gq_chestpain_uphill_DER. Please request those variables instead.
Categorical
Chest pain normal pace
Do you experience pain or chest discomfort when you walk at an ordinary pace on the level? This data is also captured with GQV1_A5dChestPainNormalPace or GQV4_A5dChestPainNormalPace. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_ChestPain_normal and data derived into: gq_chestpain_normal_DER. Please request those variables instead.
Categorical
Action taken when experience chest discomfort from walking
What do you do if you experience pain or chest discomfort while walking? This data is also captured with GQV1_A5eActionWhenChestDiscomfort or GQV4_A5eActionWhenChestDiscomfort. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_ChestPain_action and data derived into: gq_chestpain_action_DER. Please request those variables instead.
Categorical
Chest discomfort after stopping
If you stand still what happens to pain or chest discomfort? This data is also captured with GQV1_A5fChestDiscomfortAfterStopping or GQV4_A5fChestDiscomfortAfterStopping. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_ChestPain_stop and data derived into: gq_chestpain_stop_DER. Please request those variables instead.
Categorical
Feel faint or dizzy
Do you often feel faint or have spells of severe dizziness? This data is also captured with GQV1_A5gFeelFaint or GQV4_A5gFeelFaint. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_FeelFaint and data derived into: gq_feelfaint_DER. Please request those variables instead.
Categorical
Dr report high BP
Has a doctor ever told you that your blood pressure was too high? This data is also captured with GQV1_A5hDrReportBPHigh or GQV4_A5hDrReportBPHigh. You should be given that data too.
Categorical
Treatment for high blood pressure
If you have been told that your blood pressure was too high are you now on treatment? This data is also captured with GQV1_A5iTreatmentHighBP or GQV4_A5iTreatmentHighBP. You should be given that data too.
Categorical
Bone problems worse by exercise
Has your doctor ever told you that you have a bone or joint problem such as arthritis that has been aggravated by exercise or might be made worse by exercise? This data is also captured with GQV1_A5jBoneProblemsAggravatedByExercise or GQV4_A5jBoneProblems. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Bone_exercise and data derived into: gq_bone_exercise_DER. Please request those variables instead.
Categorical
Pregnancy status
Are you pregnant? This data is also captured with GQV1_A5kPregnant or GQV4_A5kPregnant. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Preg and data derived into: gq_preg_DER. Please request those variables instead.
Categorical
Any reason not to do PA
Is there any reason you know of that means you should not follow an activity programme even if you wanted to? Yes / No. This data is also captured with GQV1_A5lReasonNotToDoPA or GQV4_A5lReasonNotToDoPA. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_PA_reason and data derived into: gq_pa_reason_DER. Please request those variables instead.
Categorical
Age first menstruation
How old were you when you had your first menstrual period (in years)? This data is also captured with GQV4_A6AgeFirstMenstralPeriod. You should be given that data too. This data is not collected in GQV1. All phase 1 data from 2 GenQs was merged into new variable: GQ_Menstr_age and data derived into: gq_menstr_age_DER. Please request those variables instead.
Real
Still menstruating
Are you still having menstrual periods? This data is also captured with GQV4_A7aStillHaveMenstrualPeriods. You should be given that data too. This data is not collected in GQV1. All phase 1 data from 2 GenQs was merged into new variable: GQ_Menstr_still and data derived into: gq_menstr_still_DER. Please request those variables instead.
Categorical
Age menstruation stopped
If NO how old were you when you stopped having your periods (i.e. your age at menopause in years old)? This data is also captured with GQV4_A7bAgePeriodsStopped. You should be given that data too. This data is not collected in GQV1.
Real
Ever smoked
Have you ever smoked? If no please go to B2 on the next page. This data is also captured with GQV1_B1cEverSmoked or GQV4_B1aEverSmoked. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Sm_ever and data derived into: gq_sm_ever_DER. Please request those variables instead.
Categorical
Smoke now
Do you smoke now? This data is also captured with GQV4_B1bCurrentlySmoke. You should request that data too. Not asked in GQV1. All phase 1 data from 2 GenQs was merged into new variable: GQ_Sm_cur and data derived into: gq_sm_cur_DER. Please request those variables instead.
Categorical
Age start smoking
At what age did you start smoking? Please enter age in years. This data is also captured with GQV4_B1cAgeStartSmoking. You should request that data too. Data not requested in GQV1. All phase 1 data from 2 GenQs was merged into new variable: GQ_Sm_agestart and data derived into: gq_sm_agestart_DER. Please request those variables instead.
Real
Year stopped smoking
If you have stopped smoking in which year did you quit. This data is also captured with GQV1_B1dEverSmokedYearQuit and GQV4_B1dYearQuit. You shouldrequest that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Sm_yearstop and data derived into: gq_sm_yearstop_DER. Please request those variables instead.
Text
Number of cigarettes per day
How many cigarettes do you or did you smoke a day on average? This data is also captured with GQV1_B1eNumberCigarettesPerDay or GQV4_B1eNumberCigarettesPerDay. You should request that data too. Note that if a decimal was provided by the participant data entry was asked to round it down if <0.5 and round up if >=0.5
Integer
Number of cheroots smoked per day
How many cheroots do you or did you smoke a day on average? This data is also captured with GQV1_B1fNumberCherootsPerDay or GQV4_B1fNumberCherootsPerDay. You should request that data too. Note that if a decimal was provided by the participant data entry was asked to round it down if <0.5 and round up if >=0.5
Integer
How many cigars smoked per day
How many cigars do you or did you smoke a day on average? This data is also captured with GQV1_B1gNumberCigarsPerDay or GQV4_B1gNumberCigarsPerDay. You should request that data too. Note that if a decimal was provided by the participant data entry was asked to round it down if <0.5 and round up if >=0.5
Integer
Grams of tobacco per week
How much do you or did you smoke a day on average? Amount in grams of tobacco in a week. This data is also captured with GQV1_B1hTobaccoPerWeek or GQV4_B1hTobaccoPerWeek. You should request that data too. Note that if a decimal was provided by the participant data entry was asked to round it down if <0.5 and round up if >=0.5
Real
Never drink
Do you never drink alcohol? If you are a non drinker please go to section C on the next page. This question was only asked in GenQ version 3. GQV4 asks the question the other way around (Do you ever drink). All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_ever and data derived into: gq_alc_ever_DER; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Drink every day
Do you usually drink every day? This data is also captured with GQV4_B2bDrinkDaily and is covered in a different format in GQV1_B3aDrinkFrequency. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_everyday ; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Drink almost every day
Do you usually drink almost every day? This data is also captured with GQV4_B2cDrinkMostDays and is covered in a different format in GQV1_B3aDrinkFrequency. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_almostday ; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Drink 3-4 times per week
Do you usually drink 3-4 times per week This data is also captured with GQV4_B2dDrink3-4TimesPerWeek and is covered in a different format in GQV1_B3aDrinkFrequency. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_3to4perwk ; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Drink 1-2 times per week
Do you usually drink 1-2 times per week? This data is also captured with GQV4_B2eDrink1-2TimesPerWeek and is covered in a different format in GQV1_B3aDrinkFrequency. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_1to2perwk ; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Drink once per fortnight
Do you usually drink once per fortnight? This data is also captured with GQV4_B2fDrinkPerFortnight. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_1per14days ; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Drink 1 times per month
Do you usually drink once per month? This data is also captured with GQV4_B2gDrinkPerMonth and is covered in a different format in GQV1_B3aDrinkFrequency. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_1permth ; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Drink less then 1 times per month
Do you usually drink less often than once a month. This data is also captured with GQV4_B2hDrinkLessOncePerMonth and is covered in a different format in GQV1_B3aDrinkFrequency. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_less1permth ; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Units of beer lager or cider per week
How many units of beer lager or cider do you consume in an average week? This data is also captured with GQV1_B2aUnitsBeerPerWk or GQV4_B3aUnitsBeerPerWk. You should request that data too.
Categorical
Units of wine per week
How many units of wine do you consume in an average week? This data is also captured with GQV1_B2bUnitsWinePerWk or GQV4_B3bUnitsWinePerWk. You should request that data too.
Categorical
Units of spirit per week
How many units of spirits do you consume in an average week? This data is also captured with GQV1_B2cUnitsSpiritsPerWk or GQV4_B3cUnitsSpiritsPerWk. You should request that data too.
Categorical
Units of fortified wine per week
How many units of Fortified wine (sherry Cinzano Campari) do you consume in an average week? This data is also captured with GQV1_B2dUnitsFortWinePerWk or GQV4_B4dUnitsFortWinePerWk. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Alc_units_fortwine and data derived into: gq_alc_units_fortwine_DER; gq_alc_units_DER and gq_alc_g_DER. Please request those variables instead.
Categorical
Own a car or van
Do you own a car or van ? This data is also captured with GQV1_DMC5aCars or GQV4_C10Cars (with slightly different wording). You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Owncars and data derived into: gq_owncars_DER. Please request those variables instead.
Categorical
Own or buying house
Do you own or are you buying your own home? This data is also captured with GQV1_DMC5bOwnHouse or GQV4_C11aOwnHouse. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Ownhouse and data derived into: gq_ownhouse_DER. Please request those variables instead.
Categorical
Rent house
Do you rent your home? This data is also captured with GQV1_DMC5cRenHouse or GQV4_C11bRentHouse. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Renthouse and data derived into: gq_renthouse_DER. Please request those variables instead.
Categorical
Marital status
What is your marital status? This data is also captured with GQV4_C12MaritalStatus. You should request that data too. Not asked in GQV1. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Marit and data derived into: gq_marit_DER. Please request those variables instead.
Categorical
Full time work status
What is your current work status? In work full time i.e. more than 30 hours per week. This data is also captured with GQV1_DMC1aFullTime or GQV4_C1aFullTime. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_full and data derived into: gq_job_full_DER. Please request those variables instead.
Categorical
Part time work status
What is your current work status? Part time work i.e. less than 30 hours per week. This data is also captured with GQV1_DMC1bPartTime or GQV4_C1bPartTime. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_part and data derived into: gq_job_part_DER. Please request those variables instead.
Categorical
Keeping house work status
What is your current work status? Keeping house. This data is also captured with GQV1_DMC1cKeepingHouse or GQV4_C1cKeepingHouse. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_house and data derived into: gq_job_house_DER. Please request those variables instead.
Categorical
Retired work status
What is your current work status? Wholly retired from work. This data is also captured with GQV1_DMC1dRetired or GQV4_C1dRetired. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_retired and data derived into: gq_job_retired_DER. Please request those variables instead.
Categorical
Obtained new job work status
What is your current work status? Waiting to start a new job already obtained. This data is also captured with GQV1_DMC1eObtainedNewJob or GQV4_C1eObtainedNewJob. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_newjob and data derived into: gq_job_newjob_DER. Please request those variables instead.
Categorical
Unemployed work status
What is your current work status? Unemployed and looking for work. This data is also captured with GQV1_DMC1fUnemployed or GQV4_C1fUnemployed. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_unempl and data derived into: gq_job_unempl_DER. Please request those variables instead.
Categorical
Temporarily sick work status
What is your current work status? Out of work as temporarily sick. This data is also captured with GQV1_DMC1gTempSick or GQV4_C1gTempSick. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_tempsick and data derived into: gq_job_tempsick_DER. Please request those variables instead.
Categorical
Permanently sick work status
What is your current work status? Permanently sick or disabled. This data is also captured with GQV1_DMC1hPermSick or GQV4_C1hPermSick. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_sick and data derived into: gq_job_sick_DER. Please request those variables instead.
Categorical
Work status other
What is your current work status? If other please specify. This data is also captured with GQV1_DMC1iOther or GQV4_C1iOther. You should request that data too.
Text
Employment type with employee data
Present or your last job: Do (did) you work as an employee or are (were) you self-employed? This data is also captured with GQV1_DMC2dEmployeeType (though answers mean different things) or GQV4_C2EmployeeType. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Emp_type and data derived into: gq_emp_type_DER. Please request those variables instead.
Categorical
Number of people employed
Present or your last job: Number of employees. For employees: indicate below how many people work (worked) for your employer at the place where you work (worked). For self-employed: indicate below how many people you employ(ed). This data is also captured with GQV4_C3NumberPeopleEmployed. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Emp_n and data derived into: gq_emp_n_DER. Please request those variables instead.
Categorical
Supervisory status without numbers
Present or your last job: Supervisory status: Do (did) you supervise any other employees (A supervisor or foreman is responsible for overseeing the work of other employees on a day to day basis).This data is captured slightly differently with GQV1_DMC2eSupervisoryStatus (that captures numbers too) and identically with GQV4_C4SupervisoryStatus. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Emp_supervise and data derived into: gq_emp_supervise_DER. Please request those variables instead.
Categorical
Occupation type
Occupation type: Current work or last job.This data is also captured with GQV4_C5Occupation (but not in GQV1). You should request that data too.
Categorical
School leaving certificate
Do you have any of the following qualifications? (tick all applicable). School Leaving certificate. This data is also captured with GQV1_DMC4aSLC or GQV4_C6aSLC. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_SLC and data derived into: gq_edu_slc_DER. Please request those variables instead.
Categorical
CSE qualification
Do you have any of the following qualifications? (tick all applicable). CSE. This data is also captured with GQV1_DMC4bCSE or GQV4_C6bCSE. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_CSE and data derived into: gq_edu_cse_DER. Please request those variables instead.
Categorical
O level or GCSE qualification
Do you have any of the following qualifications? (tick all applicable). GCE O level or GCSE. This data is also captured with GQV1_DMC4cGCSE or GQV4_C6cGCSE. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_GCSE and data derived into: gq_edu_gcse_DER. Please request those variables instead.
Categorical
Matriculation qualification
Do you have any of the following qualifications? (tick all applicable). Matriculation. This data is also captured with GQV1_DMC4dMatriculation or GQV4_C6dMatriculation. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_matricul and data derived into: gq_edu_matricul_DER. Please request those variables instead.
Categorical
A level qualification
Do you have any of the following qualifications? (tick all applicable). GCE A Level AS level Highers This data is also captured with GQV1_DMc4eALevels or GQV4_C6eALevels. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_Alev and data derived into: gq_edu_alev_DER. Please request those variables instead.
Categorical
Technical or C&G qualification
Do you have any of the following qualifications? (tick all applicable). Technical College exams City & Guilds. This data is also captured with GQV1_DMC4fC_G or GQV4_C6fC_G. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_TechCG and data derived into: gq_edu_techcg_DER. Please request those variables instead.
Categorical
HND or GNVQ qualification
Do you have any of the following qualifications? (tick all applicable). HND or GNVQ. This data is also captured with GQV1_DMC4gHND or GQV4_C6gHND_NVQ. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_HND_NVQ and data derived into: gq_edu_hnd_nvq_DER. Please request those variables instead.
Categorical
Completed apprenticeship
Do you have any of the following qualifications? (tick all applicable). Completed Apprenticeship. This data is also captured with GQV1_DMC4hApprenticeship or GQV4_C6hApprenticeship. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_apprentice and data derived into: gq_edu_apprentice_DER. Please request those variables instead.
Categorical
Secretarial College qualification
Do you have any of the following qualifications? (tick all applicable). Secretarial College Exams. This data is also captured with GQV1_DMC4iSecretarial or GQV4_C6iSecretarial. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_secret and data derived into: gq_edu_secret_DER. Please request those variables instead.
Categorical
HNC or NVQ qualification
Do you have any of the following qualifications? (tick all applicable). Teaching Diploma HNC NVQ. This data is also captured with GQV1_DMC4jHMC or GQV4_C6jHNC. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_HNC and data derived into: gq_edu_hnc_DER. Please request those variables instead.
Categorical
University degree qualification
Do you have any of the following qualifications? (tick all applicable). University Degree. This data is also captured with GQV1_DMC4kDegree or GQV4_C6kDegree. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_degree and data derived into: gq_edu_degree_DER. Please request those variables instead.
Categorical
Trade certificate qualification
Do you have any of the following qualifications? (tick all applicable). Trade Certificates. This data is also captured with GQV1_DMC4lTradeCertificate or GQV4_C6lTradeCertificate. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_trade and data derived into: gq_edu_trade_DER. Please request those variables instead.
Categorical
Other qualifications
Do you have any of the following qualifications? (tick all applicable). Other please describe. This data is also captured with GQV1_DMC4mOther or GQV4_C6mOther. You should be given that data too.
Text
No Qualifications
Do you have any of the following qualifications? (tick all applicable). None. This data is also captured with GQV1_DMC4nNone or GQV4_C6nNone. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_none and data derived into: gq_edu_none_DER. Please request those variables instead.
Categorical
Age finished full time education
At what age did you finish full time education (in years)? This data is also captured with GQV1_DMC42aAgeEndFTE or GQV4_C7AgeEndFTE. You should be given that data too.
Real
Household income
What is your total combined household income? This data is also captured with GQV1_DMC3HouseholdIncome or GQV4_C8HouseholdIncome (with slightly different wording). You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Income and data derived into: gq_income_DER. Please request those variables instead
Categorical
Number of people in household
How many people are there in your household? (including children). This data is also captured with GQV4_C9NumberInHouse. You should be given that data too. Data not collected in GQV1.
Real
How often do you eat breakfast?
How often do you usually eat breakfast? Please tick the box which is most true. This data is also captured with GQV1_D1EatBreakfast or GQV4_D1EatBreakfast. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Breakfast and data derived into: gq_breakfast_DER. Please request those variables instead.
Categorical
How often do you takeaway meals
When eating your main meal at home how often do you usually eat Home delivery or take-away meals. This data is also captured with GQV1_D2aEatTakeaways or GQV4_D2aEatTakeaways. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Takeaway and data derived into: gq_takeaway_DER. Please request those variables instead.
Categorical
How often do you eat ready meals
When eating your main meal at home how often do you usually eat Ready-made meals/prepared foods. This data is also captured with GQV1_D2bEatReadyMeals or GQV4_D2bEatReadyMeals. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Readymeals and data derived into: gq_readymeals_DER. Please request those variables instead.
Categorical
How often do you eat home-cooked meals
When eating your main meal at home how often do you usually eat Home cooked meals. This data is also captured with GQV1_D2cEatHomeCookedMeals or GQV4_D2cEatHomeCookedMeals. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Homecooked and data derived into: gq_homecooked_DER. Please request those variables instead.
Categorical
How often do you a have a meal out?
On average how often do you eat a meal outside of the home (restaurants pubs fast-food outlets etc)? This data is also captured with GQV1_D3EatOut or GQV4_D3EatOut. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eatout and data derived into: gq_eatout_DER. Please request those variables instead.
Categorical
Meal while watching TV
How often do you eat your meal while watching television or video? This data is also captured with GQV1_D4EatAndWatchTV or GQV4_D4EatAndWatchTV. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_eat and data derived into: gq_tv_eat_DER. Please request those variables instead.
Categorical
Snack foods while watching TV
Apart from meals how often do you snack foods while watching television? This data is also captured with GQV1_D5SnackAndWatchTV or GQV4_D5SnackAndWatchTV. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_snack and data derived into: gq_tv_snack_DER. Please request those variables instead.
Categorical
Eating patterns: 6-8am 01
Had a main meal between 6am - 8am E.g. cooked dish e.g. meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV1_D601aMain or GQV4_D701aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0204 and data derived into: gq_eat_main0204_DER. Please request those variables instead.
Categorical
Eating patterns: 6-8am 01
Had a light meal between 6am - 8am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D601bLight or GQV4_D701bLight. You should be given that data too.All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0204 and data derived into: gq_eat_light0204_DER. Please request those variables instead.
Categorical
Snack 6-8am 01
Had a snack between 6am - 8am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D601cSnack or GQV4_D701cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0204 and data derived into: gq_eat_snack0204_DER. Please request those variables instead.
Categorical
Drink only snack 6-8am
Had a drink only snack between 6am - 8am E.g. e.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D601dDrink or GQV4_D701dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0204 and data derived into: gq_eat_drink0204_DER. Please request those variables instead.
Categorical
Eating patterns: 8-10am 02
Had a main meal between 8am - 10am E.g. cooked dish e.g. meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV1_D602aMain or GQV4_D702aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0406 and data derived into: gq_eat_main0406_DER. Please request those variables instead.
Categorical
Eating patterns: 8-10am 02
Had a light meal between 8am - 10am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D602bLight or GQV4_D702bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0406 and data derived into: gq_eat_light0406_DER. Please request those variables instead.
Categorical
Snack 8-10am 02
Had a snack between 8am - 10am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D602cSnack or GQV4_D702cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0406 and data derived into: gq_eat_snack0406_DER. Please request those variables instead.
Categorical
Drink only snack 8-10am
Had a drink only snack between 8am - 10am E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D602dDrink or GQV4_D702dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0406 and data derived into: gq_eat_drink0406_DER. Please request those variables instead.
Categorical
Eating patterns: 10-12am 03
Had a main meal between 10am - 12am E.g. cooked dish e.g. meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV1_D603aMain or GQV4_D703aMain. You should be given that data too.All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0608 and data derived into: gq_eat_main0608_DER. Please request those variables instead.
Categorical
Eating patterns: 10-12am 03
Had a light meal between 10am - 12pm E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D603bLight or GQV4_D703bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0608 and data derived into: gq_eat_light0608_DER. Please request those variables instead.
Categorical
Snack 10-12am 03
Had a snack between 10am - 12pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D603cSnack or GQV4_D703cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0608 and data derived into: gq_eat_snack0608_DER. Please request those variables instead.
Categorical
Drink only snack 10-12am
Had a drink only snack between 10am - 12pm E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D603dDrink or GQV4_D703dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0608 and data derived into: gq_eat_drink0608_DER. Please request those variables instead.
Categorical
Eating patterns: 12-2pm 04
Had a main meal between 12am - 2pm E.g. cooked dish e.g. meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV1_D604aMain or GQV4_D704aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0810 and data derived into: gq_eat_main0810_DER. Please request those variables instead. -1 = left blank;
Categorical
Eating patterns: 12-2pm 04
Had a light meal between 12pm -2pm E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D604bLight or GQV4_D704bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0810 and data derived into: gq_eat_light0810_DER. Please request those variables instead.
Categorical
Snack 12-2pm 04
Had a snack between 12pm - 2pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D604cSnack or GQV4_D704cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0810 and data derived into: gq_eat_snack0810_DER. Please request those variables instead.
Categorical
Drink only snack 12-2pm
Had a drink only snack between 12pm - 2pm E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D604dDrink or GQV4_D704dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0810 and data derived into: gq_eat_drink0810_DER. Please request those variables instead.
Categorical
Eating patterns: 2-4pm 05
Had a main meal between 2pm - 4pm E.g. cooked dish e.g. meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV1_D605aMain or GQV4_D705aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1012 and data derived into: gq_eat_main1012_DER. Please request those variables instead.
Categorical
Eating patterns: 2-4pm 05
Had a light meal between 2pm - 4pm E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D605bLight or GQV4_D705bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1012 and data derived into: gq_eat_light1012_DER. Please request those variables instead.
Categorical
Snack 2-4pm 05
Had a snack between 2pm - 4pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D605cSnack or GQV4_D705cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1012 and data derived into: gq_eat_snack1012_DER. Please request those variables instead.
Categorical
Drink only snack 2-4pm
Had a drink only snack between 2pm - 4pm E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D605dDrink or GQV4_D705dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1012 and data derived into: gq_eat_drink1012_DER. Please request those variables instead.
Categorical
Eating patterns: 4-6pm 06
Had a main meal between 4pm - 6pm E.g. cooked dish e.g. meat with potatoes pizza lasagne fish and chips burgers fried breakfast. This data is also captured with GQV1_D606aMain or GQV4_D706aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1214 and data derived into: gq_eat_main1214_DER. Please request those variables instead.
Categorical
Eating patterns: 4-6pm 06
Had a light meal between 4pm - 6pm E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D606bLight or GQV4_D706bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1214 and data derived into: gq_eat_light1214_DER. Please request those variables instead.
Categorical
Snack 4-6pm 06
Had a snack between 4pm - 6pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D606cSnack or GQV4_D706cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1214 and data derived into: gq_eat_snack1214_DER. Please request those variables instead.
Categorical
Drink only snack 4-6pm
Had a drink only snack between 4pm - 6pm E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D606dDrink or GQV4_D706dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1214 and data derived into: gq_eat_drink1214_DER. Please request those variables instead.
Categorical
Eating patterns: 6-8pm 07
Had a main meal between 6pm - 8pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D607aMain or GQV4_D707aMain. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1416 and data derived into: gq_eat_main1416_DER. Please request those variables instead.
Categorical
Eating patterns: 6-8pm 07
Had a light meal between 6pm - 8pm E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D607bLight or GQV4_D707bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1416 and data derived into: gq_eat_light1416_DER. Please request those variables instead.
Categorical
Snack 6-8pm 07
Had a snack between 6pm - 8pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D607cSnack or GQV4_D707cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1416 and data derived into: gq_eat_snack1416_DER. Please request those variables instead.
Categorical
Drink only snack 6-8pm
Had a drink only snack between 6pm - 8pm E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D607dDrink or GQV4_D707dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1416 and data derived into: gq_eat_drink1416_DER. Please request those variables instead.
Categorical
Eating patterns: 8-10pm 08
Had a main meal between 8pm - 10pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D608aMain or GQV4_D708aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1618 and data derived into: gq_eat_main1618_DER. Please request those variables instead.
Categorical
Eating patterns: 8-10pm 08
Had a light meal between 8pm - 10pm E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D608bLight or GQV4_D708bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1618 and data derived into: gq_eat_light1618_DER. Please request those variables instead.
Categorical
Snack 8-10pm 08
Had a snack between 8pm - 10pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D608cSnack or GQV4_D708cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1618 and data derived into: gq_eat_snack1618_DER. Please request those variables instead.
Categorical
Drink only snack 8-10pm
Had a drink only snack between 8pm - 10pm E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D608dDrink or GQV4_D708dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1618 and data derived into: gq_eat_drink1618_DER. Please request those variables instead.
Categorical
Eating patterns: 10-12pm 09
Had a main meal between 10pm - 12am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D609aMain or GQV4_D709aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1820 and data derived into: gq_eat_main1820_DER. Please request those variables instead.
Categorical
Eating patterns: 10-12pm 09
Had a light meal between 10pm - 12am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D609bLight or GQV4_D709bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1820 and data derived into: gq_eat_light1820_DER. Please request those variables instead.
Categorical
Snack 10-12pm 09
Had a snack between 10pm - 12am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D609cSnack or GQV4_D709cSnack. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1820 and data derived into: gq_eat_snack1820_DER. Please request those variables instead.
Categorical
Drink only snack 10-12pm
Had a drink only snack between 10pm - 12am E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D609dDrink or GQV4_D709dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1820 and data derived into: gq_eat_drink1820_DER. Please request those variables instead.
Categorical
Eating patterns: 0-2am 10
Had a main meal between 12am - 2am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D610aMain or GQV4_D710aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main2022 and data derived into: gq_eat_main2022_DER. Please request those variables instead.
Categorical
Eating patterns: 0-2am 10
Had a light meal between 12am - 2am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D610bLight or GQV4_D710bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light2022 and data derived into: gq_eat_light2022_DER. Please request those variables instead.
Categorical
Snack 0-2am 10
Had a snack between 12am - 2am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D610cSnack or GQV4_D710cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack2022 and data derived into: gq_eat_snack2022_DER. Please request those variables instead.
Categorical
Drink only snack 0-2am
Had a drink only snack between 12am - 2am E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D610dDrink or GQV4_D710dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink2022 and data derived into: gq_eat_drink2022_DER. Please request those variables instead.
Categorical
Eating patterns: 2-4am 11
Had a main meal between 2am - 4am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D611aMain or GQV4_D711aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main2224 and data derived into: gq_eat_main2224_DER. Please request those variables instead.
Categorical
Eating patterns: 2-4am 11
Had a light meal between 2am - 4am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D611bLight or GQV4_D711bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light2224 and data derived into: gq_eat_light2224_DER. Please request those variables instead.
Categorical
Snack 2-4am 11
Had a snack between 2am - 4am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D611cSnack or GQV4_D711cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack2224 and data derived into: gq_eat_snack2224_DER. Please request those variables instead.
Categorical
Drink only snack 2-4am
Had a drink only snack between 2am - 4am E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D611dDrink or GQV4_D711dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink2224 and data derived into: gq_eat_drink2224_DER. Please request those variables instead.
Categorical
Eating patterns: 4-6am 12
Had a main meal between 4am - 6am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D612aMain or GQV4_D712aMain. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main2402 and data derived into: gq_eat_main2402_DER. Please request those variables instead.
Categorical
Eating patterns: 4-6am 12
Had a light meal between 4am - 6am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D612bLight or GQV4_D712bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light2402 and data derived into: gq_eat_light2402_DER. Please request those variables instead.
Categorical
Snack 4-6am 12
Had a snack between 4am - 6am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D612cSnack or GQV4_D712cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack2402 and data derived into: gq_eat_snack2402_DER. Please request those variables instead.
Categorical
Drink only snack 4-6am
Had a drink only snack between 4am - 6am E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D612dDrink or GQV4_D712dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink2402 and data derived into: gq_eat_drink2402_DER. Please request those variables instead.
Categorical
Frequency of eating Vegetables
During the course of last year how many times a week did you eat Medium serving of Vegetables (not including potatoes). This data is also captured with GQV1_D7aVeg. You should be given that data too. This data is not captured with GQV4.
Categorical
Frequency of eating Salad
During the course of last year how many times a week did you eat Medium serving of Salads. This data is also captured with GQV1_D7bSalad. You should request that data too. This data is not captured in GQV4.
Categorical
Frequency of eating Fruit
During the course of last year how many times a week did you eat Medium serving or 1 fruit of Fruit and fruit products (not including fruit juice). This data is also captured with GQV1_D7cFruit. You should request that data too. This data is not captured with GQV4.
Categorical
Frequency of eating Fish
During the course of last year how many times a week did you eat Medium serving of Fish and fish products. This data is also captured with GQV1_D7dFish. You should request that data too. This data is not captured in GQV4.
Categorical
Frequency of eating Meat
During the course of last year how many times a week did you eat Medium serving of Meat meat products and meat dishes (including bacon ham or chicken). This data is also captured with GQV1_D7eMeat. You should request that data too. This data is not captured with GQV4.
Categorical
Currently participating in special diets: Weight Watchers
Please tick to show if you are currently on a 'Weight Watchers' diet. This data is also captured with GQV1_D8aWW or GQV4_D8aWW. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_ww and data derived into: gq_diet_ww_DER. Please request those variables instead.
Categorical
Currently participating in special diets: Slimmers world
Please tick to show if you are currently on a 'Slimmers World' diet. This data is also captured with GQV1_d8bSW or GQV4_D8bSW. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_slim and data derived into: gq_diet_slim_DER. Please request those variables instead.
Categorical
Currently participating in special diets: Low fat
Please tick to show if you are currently on a low fat diet. This data is also captured with GQV1_D8cLFD or GQV4_D8cLFD. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_lowf and data derived into: gq_diet_lowf_DER. Please request those variables instead.
Categorical
Currently participating in special diets: Low carb
Please tick to show if you are currently on a low carbohydrate diet eg Atkins Diet. This data is also captured with GQV1_D8dLCD or GQV4_D8dLCD. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_lowc and data derived into: gq_diet_lowc_DER. Please request those variables instead.
Categorical
Currently participating in special diets: Vegetarian
Please tick to show if you are currently on a vegetarian diet. This data is also captured with GQV1_D8eVegetarian or GQV4_D8eVegetarian. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_veg and data derived into: gq_diet_veg_DER. Please request those variables instead.
Categorical
Currently participating in special diets: Vegan
Please tick to show if you are currently on a a vegan diet. This data is also captured with GQV1_D8fVegan or GQV4_D8fVegan. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_vegan and data derived into: gq_diet_vegan_DER. Please request those variables instead.
Categorical
Currently participating in special diets: Kosher
Please tick to show if you are currently on a Kosher diet. This data is also captured with GQV1_D8gKosher or GQV4_D8gKosher. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_kosh and data derived into: gq_diet_kosh_DER. Please request those variables instead.
Categorical
Currently participating in special diets: Halal
Please tick to show if you are currently on a Halal diet. This data is also captured with GQV1_D8hHalal or GQV4_D8hHalal. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_halal and data derived into: gq_diet_halal_DER. Please request those variables instead.
Categorical
Other diet
Currently on an other diet. Please describe. This data is also captured with GQV1_D8iOther or GQV4_D8iOther. You should request that data too.
Text
Health in last 4 weeks
Self perceived health status. Overall how would you rate your health during the past 4 weeks? This data is also captured with GQV4_E1SRHealth. You should be given that data too. This data is not captured in Gen Q V1. All phase 1 data from all 3 GenQs was merged into new variable: GQ_SelfR_health and data derived into: gq_selfr_health_DER. Please request those variables instead.
Categorical
Physical problems
Self perceived health status. During the past 4 weeks how much did physical health problems limit your usual physycal activities (walking climbing stairs)? This data is also captured with GQV4_E2SRPhysicalProblems. You should be given that data too. This data is not captured in GQV1. All phase 1 data from all 3 GenQs was merged into new variable: GQ_SelfR_pa and data derived into: gq_selfr_pa_DER. Please request those variables instead.
Categorical
Physical daily work
Self perceived health status. During the past 4 weeks how much difficulty did you have doing your daily work both inside and outside the home because of your physical health? This data is also captured with GQV4_E3SRPhysicalDailyWork. You should request that data too. This data is not captured in GQV1. All phase 1 data from all 3 GenQs was merged into new variable: GQ_SelfR_work and data derived into: gq_selfr_work_DER. Please request those variables instead.
Categorical
Bodily pain
Self perceived health status. How much bodily pain have you had during the past 4 weeks? This data is also captured with GQV4_E4SRBodilyPain. You should request that data too. This data is not captured in Gen Q V1. All phase 1 data from all 3 GenQs was merged into new variable: GQ_SelfR_pain and data derived into: gq_selfr_pain_DER. Please request those variables instead.
Categorical
Energy levels
Self perceived health status. During the past 4 weeks how much energy did you have? This data is also captured with GQV4_E5SREnergy. You should request that data too. This data is not captured in Gen Q V1. All phase 1 data from all 3 GenQs was merged into new variable: GQ_SelfR_energy and data derived into: gq_selfr_energy_DER. Please request those variables instead.
Categorical
Emotional social
Self perceived health status. During the past 4 weeks how much did your physical health or emotional problems limit your social activities with family or friends? This data is also captured with GQV4_E6SREmotionalSocial. You should request that data too All phase 1 data from all 3 GenQs was merged into new variable: GQ_SelfR_social and data derived into: gq_selfr_social_DER. Please request those variables instead.
Categorical
Emotional problems
Self perceived health status. During the past 4 weeks how much have you been bothered by emotional problems (such as feeling anxious depressed or irritable)? This data is also captured with GQV4_E7SREmotional. You should request that data too. This data is not captured on GQV1. All phase 1 data from all 3 GenQs was merged into new variable: GQ_SelfR_emot and data derived into: gq_selfr_emot_DER. Please request those variables instead.
Categorical
Emotional daily work
Self perceived health status. During the past 4 weeks how much did personal or emotional problems keep you from doing your usual work studies or other daily activities? This data is also captured with GQV4_E8SREmotionalDailyWork. You should request that data too. This data is not captured with GQV1. All phase 1 data from all 2 GenQs was merged into new variable: GQ_SelfR_emotwork and data derived into: gq_selfr_emotwork_DER. Please request those variables instead.
Categorical
Ethnic origin
Ethnic origin (from the UK Government 2001 census ethnicity classification). This data is also captured with GQV4_F1Ethnicity. You should request that data too. This data is not collected in GQV1 so not all people with have this data. All phase 1 data from all 2 GenQs was merged into new variable: GQ_eth and data derived into: gq_eth_DER. Please request those variables instead.
Categorical
Additional comments on gen questionnaire version2/3
GQV3 additional comments made on any page with page number and text. This data is also captured with GQV1_FSGQComments or GQV4_FSGQComments. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: FSGQComments_Updated . Please request those variables instead.
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Questionnaire version number
Version number of the questionnaire completed by participant. This data is also captured with GQV4_QVersion. You should be given that data too. This data is not captured in Gen Q V1. All phase 1 data from all GenQs was merged into new variable: GQ_v . Please request that variable instead.
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On medication
Are you taking any tablets or medicines at the moment? This data is also captured with GQV1_A1OnMedication or GQV3_A1OnMedication. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Meds and data derived into: gq_meds_DER. Please request those variables instead.
Categorical
Current Medication a BNF Code
BNF Code for medication a added by research team. This data is also captured with GQV1_A2aCurrentMedicationBNFCode or GQV3_A2aCurrentMedicationBNFCode. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Med_bnf_a . Please request those variables instead.
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Current Medication Dose
Dose of drug a. This data is also captured with GQV1_A2aCurrentMedicationDose or GQV3_A2aCurrentMedicationDose. You should be given that data too.
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Current Medication Name
Name of drug a. This data is also captured with GQV1_A2aCurrentMedicationName or GQV3_A2aCurrentMedicationName. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Med_a and data derived into: gq_v_DER and into gq_med_?_DER where ? is asp; statin; lipid; acei; arb; betab; diuret; nitr; cardio; dm; depr; slp; can; gastro; bowel; nsaid; pain; painany; autoimm; inflamany; hrt; oc; infect; nutr; herb or any. Please request those variables instead.
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Current Medication Reason
Reason for taking the drug a. This data is also captured with GQV1_A2aCurrentMedicationReason or GQV3_A2aCurrentMedicationReason. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Med_why_a . Please request those variables instead.
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Current Medication b BNF Code
BNF Code for medication b added by research team. This data is also captured with GQV1_A2bCurrentMedicationBNFCode or GQV3_A2bCurrentMedicationBNFCode. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Med_bnf_b . Please request those variables instead.
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Current Medication Dose
Dose of drug b. This data is also captured with GQV1_A2bCurrentMedicationDose or GQV3_A2bCurrentMedicationDose. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Med_dose_b . Please request those variables instead.
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Current Medication Name
Name of drug b. This data is also captured with GQV1_A2bCurrentMedicationName or GQV3_A2bCurrentMedicationName. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Med_b . Please request those variables instead.
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Current Medication Reason
Reason for taking the drug b. This data is also captured with GQV1_A2bCurrentMedicationReason or GQV3_A2bCurrentMedicationReason. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Med_why_b . Please request those variables instead.
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Current Medication c BNF Code
BNF Code for medication c added by research team. This data is also captured with GQV1_A2cCurrentMedicationBNFCode or GQV3_A2cCurrentMedicationBNFCode. You should be given that data too.
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Current Medication Dose
Dose of drug c. This data is also captured with GQV1_A2cCurrentMedicationDose or GQV3_A2cCurrentMedicationDose. You should be given that data too.
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Current Medication Name
Name of drug c. This data is also captured with GQV1_A2cCurrentMedicationName or GQV3_A2cCurrentMedicationName. You should be given that data too.
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Current Medication Reason
Reason for taking the drug c. This data is also captured with GQV1_A2cCurrentMedicationReason or GQV3_A2cCurrentMedicationReason. You should be given that data too.
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Current Medication d BNF Code
BNF Code for medication d added by research team. This data is also captured with GQV1_A2dCurrentMedicationBNFCode or GQV3_A2dCurrentMedicationBNFCode. You should be given that data too.
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Current Medication Dose
Dose of drug d. This data is also captured with GQV1_A2dCurrentMedicationDose or GQV3_A2dCurrentMedicationDose. You should be given that data too.
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Current Medication Name
Name of drug d. This data is also captured with GQV1_A2dCurrentMedicationName or GQV3_A2dCurrentMedicationName. You should be given that data too.
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Current Medication Reason
Reason for taking the drug d. This data is also captured with GQV1_A2dCurrentMedicationReason or GQV3_A2dCurrentMedicationReason. You should be given that data too.
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Current Medication e BNF Code
BNF Code for medication e added by research team. This data is also captured with GQV1_A2eCurrentMedicationBNFCode or GQV3_A2eCurrentMedicationBNFCode. You should be given that data too.
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Current Medication Dose
Dose of drug e. This data is also captured with GQV1_A2eCurrentMedicationDose or GQV3_A2eCurrentMedicationDose. You should be given that data too.
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Current Medication Name
Name of drug e. This data is also captured with GQV1_A2eCurrentMedicationName or GQV3_A2eCurrentMedicationName. You should be given that data too.
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Current Medication Reason
Reason for taking the drug e. This data is also captured with GQV1_A2eCurrentMedicationReason or GQV3_A2eCurrentMedicationReason. You should be given that data too.
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Current Medication f BNF Code
BNF Code for medication f added by research team. This data is also captured with GQV1_A2fCurrentMedicationBNFCode or GQV3_A2fCurrentMedicationBNFCode. You should be given that data too.
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Current Medication Dose
Dose of drug f. This data is also captured with GQV1_A2fCurrentMedicationDose or GQV3_A2fCurrentMedicationDose. You should be given that data too.
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Current Medication Name
Name of drug f. This data is also captured with GQV1_A2fCurrentMedicationName or GQV3_A2fCurrentMedicationName. You should be given that data too.
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Current Medication Reason
Reason for taking the drug f. This data is also captured with GQV1_A2fCurrentMedicationReason or GQV3_A2fCurrentMedicationReason. You should be given that data too.
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Current Medication g BNF Code
BNF Code for medication g added by research team. This data is also captured with GQV1_A2gCurrentMedicationBNFCode or GQV3_A2gCurrentMedicationBNFCode. You should be given that data too.
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Current Medication Dose
Dose of drug g. This data is also captured with GQV1_A2gCurrentMedicationDose or GQV3_A2gCurrentMedicationDose. You should be given that data too.
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Current Medication Name
Name of drug g. This data is also captured with GQV1_A2gCurrentMedicationName or GQV3_A2gCurrentMedicationName. You should be given that data too.
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Current Medication Reason
Reason for taking the drug g. This data is also captured with GQV1_A2gCurrentMedicationReason or GQV3_A2gCurrentMedicationReason. You should be given that data too.
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Current Medication h BNF Code
BNF Code for medication h added by research team. This data is also captured with GQV1_A2hCurrentMedicationBNFCode or GQV3_A2hCurrentMedicationBNFCode. You should be given that data too.
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Current Medication Dose
Dose of drug h. This data is also captured with GQV1_A2hCurrentMedicationDose or GQV3_A2hCurrentMedicationDose. You should be given that data too.
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Current Medication Name
Name of drug h. This data is also captured with GQV1_A2hCurrentMedicationName or GQV3_A2hCurrentMedicationName. You should be given that data too.
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Current Medication Reason
Reason for taking the drug h. This data is also captured with GQV1_A2hCurrentMedicationReason or GQV3_A2hCurrentMedicationReason. You should be given that data too.
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Birth weight imperial
What was your weight at birth in pounds and ounces. This data is also captured with GQV1_A4aBirthWeight and GQV1_A4bBirthWeightUnits and GQV3_A3aBirthWeightImperial. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_BWt_imperial . Please request those variables instead.
Real
Birth weight metric
What was your weight at birth? Birth weight in kilograms. This data is also captured with GQV1_A4aBirthWeight and GQV1_A4bBirthWeightUnits and GQV3_A3bBirthWeightMetric. You should request that data too.All phase 1 data from 2 GenQs was merged into new variable: GQ_BWt_metric . Please request those variables instead.
Real
Unknown birth weight
Tick if you are not able to give your birth weight. This data is also captured with GQV1_A4cBirthWeightUnknown or GQV3_A3cBirthWeightUnknown. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_BWt_unknown. Please request those variables instead.
Categorical
Term of birth
When were you born (pre post or at term). This data is also captured with GQV1_A4dBorn or GQV3_A4aBorn. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Bterm and data derived into: gq_bterm_DER. Please request those variables instead.
Categorical
Dr reported heart trouble
Has your doctor ever told you that you have heart trouble? This data is also captured with GQV1_A5aDrReportHeartTrouble or GQV3_A5aDrReportHeartTrouble. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Htn_dr and data derived into: gq_htn_dr_DER. Please request those variables instead.
Categorical
Chest pain ever
Have you ever had any pain or discomfort in your chest? If no proceed to question 7. If yes please answer the next question. This data is also captured with GQV1_A5bChestPain or GQV3_A5bChestPain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_ChestPain_dr and data derived into: gq_chestpain_dr_DER. Please request those variables instead.
Categorical
Chest discomfort from walking uphill
Do you experience pain or chest discomfort when you walk uphill or hurry? This data is also captured with GQV1_A5cChestPainUphill or GQV3_A5cChestPainUphill. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_ChestPain_uphill and data derived into: gq_chestpain_uphill_DER. Please request those variables instead.
Categorical
Chest discomfort from walking
Do you experience pain or chest discomfort when you walk at an ordinary pace on the level? This data is also captured with GQV1_A5dChestPainNormalPace or GQV3_A5dChestPainNormalPace. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_ChestPain_normal and data derived into: gq_chestpain_normal_DER. Please request those variables instead.
Categorical
Action taken when experience chest discomfort from walking
What do you do if you experience pain or chest discomfort while walking? This data is also captured with GQV1_A5eActionWhenChestDiscomfort or GQV3_A5eActionWhenChestDiscomfort. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_ChestPain_action and data derived into: gq_chestpain_action_DER. Please request those variables instead.
Categorical
Chest discomfort after stopping
If you stand still what happens to pain or chest discomfort? This data is also captured with GQV1_A5fChestDiscomfortAfterStopping or GQV3_A5fChestDiscomfortAfterStopping. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_ChestPain_stop and data derived into: gq_chestpain_stop_DER. Please request those variables instead.
Categorical
Feel faint or dizzy
Do you often feel faint or have spells of severe dizziness? This data is also captured with GQV1_A5gFeelFaint or GQV3_A5gFeelFaint. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_FeelFaint and data derived into: gq_feelfaint_DER. Please request those variables instead.
Categorical
Dr reported high blood pressure
Has a doctor ever told you that your blood pressure was too high? This data is also captured with GQV1_A5hDrReportBPHigh or GQV3_A5hDrReportBPHigh. You should be given that data too.
Categorical
Treatment for high blood pressure
If you have been told that your blood pressure was too high are you now on treatment? This data is also captured with GQV1_A5iTreatmentHighBP or GQV3_A5iTreatmentHighBP. You should be given that data too.
Categorical
Bone problems worse by exercise
Has your doctor ever told you that you have a bone or joint problem such as arthritis that has been aggravated by exercise or might be made worse by exercise? This data is also captured with GQV1_A5jBoneProblemsAggravatedByExercise or GQV3_A5jBoneProblems All phase 1 data from all 3 GenQs was merged into new variable: GQ_Bone_exercise and data derived into: gq_bone_exercise_DER. Please request those variables instead.
Categorical
Pregnancy status
Are you pregnant? This data is also captured with GQV1_A5kPregnant or GQV3_A5kPregnant. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Preg and data derived into: gq_preg_DER. Please request those variables instead.
Categorical
Any reason not to do PA
Is there any reason you know of that means you should not follow an activity programme even if you wanted to? Yes / No. This data is also captured with GQV1_A5lReasonNotToDoPA or GQV3_A5lReasonNotToDoPA. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_PA_reason and data derived into: gq_pa_reason_DER. Please request those variables instead.
Categorical
Age first menstruation
How old were you when you had your first menstrual period (in years)? This data is also captured with GQV3_A6AgeFirstMenstralPeriod. You should be given that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Menstr_age and data derived into: gq_menstr_age_DER. Please request those variables instead.
Real
Still menstruating
Are you still having menstrual periods? This data is also captured with GQV3_A7aStillHaveMenstrualPeriods. You should be given that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Menstr_still and data derived into: gq_menstr_still_DER. Please request those variables instead.
Categorical
Age menstruation stopped
If NO how old were you when you stopped having your periods (i.e. your age at menopause in years old)? This data is also captured with GQV3_A7bAgePeriodsStopped. You should be given that data too. All phase 1 data from2 GenQs was merged into new variable: GQ_Meno_age and data derived into: gq_meno_age_DER. Please request those variables instead.
Real
Ever smoked
Have you ever smoked? If no please go to B2 on the next page. This data is also captured with GQV1_B1cEverSmoked or GQV3_B1aEverSmoked. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Sm_ever and data derived into: gq_sm_ever_DER. Please request those variables instead.
Categorical
Smoke now
Do you smoke now? This data is also captured with GQV3_B1bCurrentlySmoke. You should be given that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Sm_cur and data derived into: gq_sm_cur_DER. Please request those variables instead.
Categorical
Age started smoking
At what age did you start smoking? Please enter age in years. This data is also captured with GQV3_B1cAgeStartSmoking. You should be given that data too. Data not collected in GQV1. All phase 1 data from 2 GenQs was merged into new variable: GQ_Sm_agestart and data derived into: gq_sm_agestart_DER. Please request those variables instead.
Real
Year stopped smoking
If you have stopped smoking in which year did you quit. This data is also captured with GQV1_B1dEverSmokedYearQuit or GQV3_B1dYearQuit. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Sm_yearstop and data derived into: gq_sm_yearstop_DER. Please request those variables instead.
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Number of cigarettes per day
How many cigarettes do you or did you smoke a day on average? This data is also captured with GQV1_B1eNumberCigarettesPerDay or GQV3_B1eNumberCigarettesPerDay. You should request that data too. Note that if a decimal was provided by the participant data entry was asked to round it down if <0.5 and round up if >=0.5
Integer
Number of cheroots smoked per day
How many cheroots do you or did you smoke a day on average? This data is also captured with GQV1_B1fNumberCherootsPerDay or GQV3_B1fNumberCherootsPerDay. You should be given that data too. Note that if a decimal was provided by the participant data entry was asked to round it down if <0.5 and round up if >=0.5 All phase 1 data from all 3 GenQs was merged into new variable: GQ_Sm_Ncheroots and data derived into: gq_sm_ncheroots_DER. Please request those variables instead.
Categorical
How many cigars smoked per day
How many cigars do you or did you smoke a day on average? This data is also captured with GQV1_B1gNumberCigarsPerDay or GQV3_B1gNumberCigarsPerDay. You should be given that data too. Note that if a decimal was provided by the participant data entry was asked to round it down if <0.5 and round up if >=0.5
Integer
Grams of tobacco per week
How much do you or did you smoke a day on average? Amount of tobacco in grams in a week. This data is also captured with GQV1_B1hTobaccoPerWeek or GQV3_B1hTobaccoPerWeek. You should request that data too. Note that if a decimal was provided by the participant data entry was asked to round it down if <0.5 and round up if >=0.5
Real
Ever drink alcohol
Do you EVER drink alcohol? If you answered no please go to section C on the next page. This question was only asked in GenQ version 4. Therefore not all participants will have this data. All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_ever and data derived into: gq_alc_ever_DER; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Drink every day
Do you usually drink every day? This data is also captured with GQV3_B2bDrinkDaily. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_everyday ; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Drink almost every day
Do you usually drink almost every day? This data is also captured with GQV3_B2cDrinkMostDays. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_almostday ; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Drink 3-4 times per week
Do you usually drink 3-4 times per week This data is also captured with GQV3_B2dDrink3-4TimesPerWeek. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_3to4perwk ; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Drink 1-2 times per week
Do you usually drink 1-2 times per week This data is also captured with GQV3_B2eDrink1-2TimesPerWeek. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_1to2perwk ; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Drink once per fortnight
Do you usually drink once per fortnight? This data is also captured with GQV3_B2fDrinkPerFortnight. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_1per14days ; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Drink 1 times per month
Do you usually drink once per month? This data is also captured with GQV3_B2gDrinkPerMonth. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_1permth ; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Drink less then 1 times per month
Do you usually drink less often This data is also captured with GQV3_B2hDrinkLessOncePerMonth. You should request that data too. All phase 1 data from 2 GenQs was merged into new variable: GQ_Alc_less1permth ; gq_alc_freq_DER and gq_alc_freqc_DER. Please request those variables instead.
Categorical
Units of beer per week
How many units of beer lager or cider do you consume in an average week? This data is also captured with GQV1_B2aUnitsBeerPerWk or GQV3_B3aUnitsBeerPerWk. You should request that data too.
Categorical
Units of wine per week
How many units of wine do you consume in an average week? This data is also captured with GQV1_B2bUnitsWinePerWk or GQV3_B3bUnitsWinePerWk. You should request that data too.
Categorical
Units of spirits per week
How many units of spirits do you consume in an average week? This data is also captured with GQV1_B2cUnitsSpiritsPerWk or GQV3_B3cUnitsSpiritsPerWk. You should request that data too.
Categorical
Units of fortified wine per week
How many units of Fortified wine (sherry Cinzano Campari) do you consume in an average week? This data is also captured with GQV1_B2dUnitsFortWinePerWk or GQV3_B4dUnitsFortWinePerWk. You should request that data too.
Categorical
Own a car or van
Do you own a car or van ? This data is also captured with GQV1_DMC5aCars or GQV3_C10Cars (with slightly different wording). You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Owncars and data derived into: gq_owncars_DER. Please request those variables instead.
Categorical
Own house
Do you own or are you buying your own home? This data is also captured with GQV1_DMC5bOwnHouse or GQV3_C11aOwnHouse. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Ownhouse and data derived into: gq_ownhouse_DER. Please request those variables instead.
Categorical
Rent house
Do you rent your home? This data is also captured with GQV1_DMC5cRenHouse or GQV3_C11bRentHouse. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Renthouse and data derived into: gq_renthouse_DER. Please request those variables instead.
Categorical
Marital status
What is your marital status? This data is also captured with GQV3_C12MaritalStatus. You should request that data too. Not asked in GQV1. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Marit and data derived into: gq_marit_DER. Please request those variables instead.
Categorical
Full time work status
What is your current work status? In work full time i.e. more than 30 hours per week. This data is also captured with GQV1_DMC1aFullTime or GQV3_C1aFullTime. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_full and data derived into: gq_job_full_DER. Please request those variables instead.2 = yes
Categorical
Part time work status
What is your current work status? Part time work i.e. less than 30 hours per week. This data is also captured with GQV1_DMC1bPartTime or GQV3_C1bPartTime. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_part and data derived into: gq_job_part_DER. Please request those variables instead.2 = yes
Categorical
Keeping house work status
What is your current work status? Keeping house. This data is also captured with GQV1_DMC1cKeepingHouse or GQV3_C1cKeepingHouse. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_house and data derived into: gq_job_house_DER. Please request those variables instead.2 = yes
Categorical
Retired work status
What is your current work status? Wholly retired from work. This data is also captured with GQV1_DMC1dRetired or GQV3_C1dRetired. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_retired and data derived into: gq_job_retired_DER. Please request those variables instead.2 = yes
Categorical
Obtained new job work status
What is your current work status? Waiting to start a new job already obtained. This data is also captured with GQV1_DMC1eObtainedNewJob or GQV3_C1eObtainedNewJob. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_newjob and data derived into: gq_job_newjob_DER. Please request those variables instead.2 = yes
Categorical
Unemployed work status
What is your current work status? Unemployed and looking for work. This data is also captured with GQV1_DMC1fUnemployed or GQV3_C1fUnemployed. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_unempl and data derived into: gq_job_unempl_DER. Please request those variables instead.2 = yes
Categorical
Temporarily sick work status
What is your current work status? Out of work as temporarily sick. This data is also captured with GQV1_DMC1gTempSick or GQV3_C1gTempSick. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_tempsick and data derived into: gq_job_tempsick_DER. Please request those variables instead.2 = yes
Categorical
Permanently sick work status
What is your current work status? Permanently sick or disabled. This data is also captured with GQV1_DMC1hPermSick or GQV3_C1hPermSick. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_sick and data derived into: gq_job_sick_DER. Please request those variables instead.2 = yes
Categorical
Work status other
What is your current work status? If other please specify. This data is also captured with GQV1_DMC1iOther or GQV3_C1iOther. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Job_oth and data derived into: gq_job_oth_DER. Please request those variables instead.
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Employment type with employee data
Present or your last job: Employee or self-employed - Do (did) you work as an employee or are (were) you self-employed? This data is also captured with GQV1_DMC2dEmployeeType (though answers mean different things) or GQV3_C2EmployeeType. You should reques All phase 1 data from all 3 GenQs was merged into new variable: GQ_Emp_type and data derived into: gq_emp_type_DER. Please request those variables instead.
Categorical
Number of people employed
Present or your last job: Number of employees. For employees: indicate below how many people work (worked) for your employer at the place where you work (worked). For self-employed: indicate below how many people you employ(ed). This data is also captured with GQV3_C3NumberPeopleEmployed. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Emp_n and data derived into: gq_emp_n_DER. Please request those variables instead.
Categorical
Supervisory status without numbers
Present or your last job: Supervisory status: Do (did) you supervise any other employees. This data is is also captured with GQV1_DMC2eSupervisoryStatus (though that captures numbers too) and GQV3_C4SupervisoryStatus. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Emp_supervise and data derived into: gq_emp_supervise_DER. Please request those variables instead.
Categorical
Occupation type
Occupation type: Current work or last job.This data is also captured with GQV3_C5Occupation (but not in GQV1). You should request that data too.
Categorical
School Leaving Certificate
Do you have any of the following qualifications? (tick all applicable). School Leaving certificate. This data is also captured with GQV1_DMC4aSLC or GQV3_C6aSLC. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_SLC and data derived into: gq_edu_slc_DER. Please request those variables instead.
Categorical
CSE qualification
Do you have any of the following qualifications? (tick all applicable). CSE. This data is also captured with GQV1_DMC4bCSE or GQV3_C6bCSE. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_CSE and data derived into: gq_edu_cse_DER. Please request those variables instead.
Categorical
O level or GCSE qualification
Do you have any of the following qualifications? (tick all applicable). GCE O level or GCSE. This data is also captured with GQV1_DMC4cGCSE or GQV3_C6cGCSE. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_GCSE and data derived into: gq_edu_gcse_DER. Please request those variables instead.
Categorical
Matriculation qualification
Do you have any of the following qualifications? (tick all applicable). Matriculation. This data is also captured with GQV1_DMC4dMatriculation or GQV3_C6dMatriculation. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_matricul and data derived into: gq_edu_matricul_DER. Please request those variables instead.
Categorical
A level qualification
Do you have any of the following qualifications? (tick all applicable). GCE A Level AS level Highers This data is also captured with GQV1_DMc4eALevels or GQV3_C6eALevels. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_Alev and data derived into: gq_edu_alev_DER. Please request those variables instead.
Categorical
Technical or C&G qualification
Do you have any of the following qualifications? (tick all applicable). Technical College exams City & Guilds. This data is also captured with GQV1_DMC4fC_G or GQV3_C6fC_G. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_TechCG and data derived into: gq_edu_techcg_DER. Please request those variables instead.
Categorical
HND or GNVQ qualification
Do you have any of the following qualifications? (tick all applicable). HND or GNVQ. This data is also captured with GQV1_DMC4gHND or GQV3_C6gHND_NVQ. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_HND_NVQ and data derived into: gq_edu_hnd_nvq_DER. Please request those variables instead.
Categorical
Completed apprenticeship
Do you have any of the following qualifications? (tick all applicable). Completed Apprenticeship. This data is also captured with GQV1_DMC4hApprenticeship or GQV3_C6hApprenticeship. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_apprentice and data derived into: gq_edu_apprentice_DER. Please request those variables instead.
Categorical
Secretarial College qualification
Do you have any of the following qualifications? (tick all applicable). Secretarial College Exams. This data is also captured with GQV1_DMC4iSecretarial or GQV3_C6iSecretarial. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_secret and data derived into: gq_edu_secret_DER. Please request those variables instead.
Categorical
HNC or NVQ qualification
Do you have any of the following qualifications? (tick all applicable). Teaching Diploma HNC NVQ. This data is also captured with GQV1_DMC4jHMC or GQV3_C6jHNC. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_HNC and data derived into: gq_edu_hnc_DER. Please request those variables instead.
Categorical
University degree qualification
Do you have any of the following qualifications? (tick all applicable). University Degree. This data is also captured with GQV1_DMC4kDegree or GQV3_C6kDegree. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_degree and data derived into: gq_edu_degree_DER. Please request those variables instead.
Categorical
Trade certificate qualification
Do you have any of the following qualifications? (tick all applicable). Trade Certificates. This data is also captured with GQV1_DMC4lTradeCertificate or GQV3_C6lTradeCertificate. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_trade and data derived into: gq_edu_trade_DER. Please request those variables instead.
Categorical
Other qualifications
Do you have any of the following qualifications? (tick all applicable). Other please describe. This data is also captured with GQV1_DMC4mOther or GQV3_C6mOther. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_others and data derived into: gq_edu_others_DER. Please request those variables instead.
Text
No Qualifications
Do you have any of the following qualifications? (tick all applicable). None. This data is also captured with GQV1_DMC4nNone or GQV3_C6nNone. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_none and data derived into: gq_edu_none_DER. Please request those variables instead.
Categorical
Age finished full time education
At what age did you finish full time education (in years)? This data is also captured with GQV1_DMC42aAgeEndFTE or GQV3_C7AgeEndFTE. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_age and data derived into: gq_edu_age_DER. Please request those variables instead.
Real
Household income
What is your total combined household income? This data is also captured with GQV1_DMC3HouseholdIncome (slightly different wording) or GQV3_C8HouseholdIncome. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Income and data derived into: gq_income_DER. Please request those variables instead.
Categorical
Number of people in household
How many people are there in your household? (including children). This data is also captured with GQV3_C9NumberInHouse. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Nhouse and data derived into: gq_nhouse_DER. Please request those variables instead.
Integer
How often eat breakfast
How often do you usually eat breakfast? Please tick the box which is most true. This data is also captured with GQV1_D1EatBreakfast or GQV3_D1EatBreakfast. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Breakfast and data derived into: gq_breakfast_DER. Please request those variables instead.
Categorical
How often eat take-away
When eating your main meal at home how often do you usually eat Home delivery or take-away meals. This data is also captured with GQV1_D2aEatTakeaways or GQV3_D2aEatTakeaways. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Takeaway and data derived into: gq_takeaway_DER. Please request those variables instead.
Categorical
How often eat ready meals
When eating your main meal at home how often do you usually eat Ready-made meals/prepared foods. This data is also captured with GQV1_D2bEatReadyMeals or GQV3_D2bEatReadyMeals. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Readymeals and data derived into: gq_readymeals_DER. Please request those variables instead.
Categorical
How often eat home cooked meals
When eating your main meal at home how often do you usually eat Home cooked meals. This data is also captured with GQV1_D2cEatHomeCookedMeals or GQV3_D2cEatHomeCookedMeals. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Homecooked and data derived into: gq_homecooked_DER. Please request those variables instead.
Categorical
How often eat out
On average how often do you eat a meal outside of the home (restaurants pubs fast-food outlets etc)? This data is also captured with GQV1_D3EatOut or GQV3_D3EatOut. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eatout and data derived into: gq_eatout_DER. Please request those variables instead.
Categorical
Meal while watching TV
How often do you eat your meal while watching television or video? This data is also captured with GQV1_D4EatAndWatchTV or GQV3_D4EatAndWatchTV. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_eat and data derived into: gq_tv_eat_DER. Please request those variables instead.
Categorical
Snack foods while watching TV
Apart from meals how often do you snack foods while watching television? This data is also captured with GQV1_D5SnackAndWatchTV or GQV3_D5SnackAndWatchTV. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_snack and data derived into: gq_tv_snack_DER. Please request those variables instead.
Categorical
Savoury snacks while watching TV
How often did you have savoury snacks (crisps salted nuts -) while watching TV in addition to breakfast lunch or dinner (last 4 weeks) . This question was only asked in GQV4 so not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_savory and data derived into: gq_tv_savory_DER. Please request those variables instead.
Categorical
Sweets while watching TV
How often did you have Sweets chocolate(s) (bars) cakes biscuits while watching TV in addition to breakfast lunch or dinner (last 4 weeks) . This question was only asked in GQV4 so not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_swts and data derived into: gq_tv_swts_DER. Please request those variables instead.
Categorical
Ice cream while watching TV
How often did you have Ice cream chocolate mousse while watching TV in addition to breakfast lunch or dinner (last 4 weeks) . This question was only asked in GQV4 so not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_icecream and data derived into: gq_tv_icecream_DER. Please request those variables instead.
Categorical
Yoghurt while watching TV
How often did you have Yoghurt rice pudding while watching TV in addition to breakfast lunch or dinner (last 4 weeks) . This question was only asked in GQV4 so not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_yoghurt and data derived into: gq_tv_yoghurt_DER. Please request those variables instead.
Categorical
Soda or coke while watching TV
How often did you have Soda (coke -) while watching TV in addition to breakfast lunch or dinner (last 4 weeks) . This question was only asked in GQV4 so not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_soda and data derived into: gq_tv_soda_DER. Please request those variables instead.
Categorical
How often drink alcohol while watching TV
How often drink alcohol while watching TV (last 4 weeks) All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_alc and data derived into: gq_tv_alc_DER. Please request those variables instead.
Categorical
Fruit juice while watching TV
How often did you have Fruit juice while watching TV in addition to breakfast lunch or dinner (last 4 weeks) . This question was only asked in GQV4 so not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_frjuice and data derived into: gq_tv_frjuice_DER. Please request those variables instead.
Categorical
Squash while watching TV
How often did you have squash while watching TV in addition to breakfast lunch or dinner (last 4 weeks) . This question was only asked in GQV4 so not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_squash and data derived into: gq_tv_squash_DER. Please request those variables instead.
Categorical
Milk while watching TV
How often did you have Milk milkshake hot chocolate while watching TV in addition to breakfast lunch or dinner (last 4 weeks) . This question was only asked in GQV4 so not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_milk and data derived into: gq_tv_milk_DER. Please request those variables instead.
Categorical
Tea or coffee while watching TV
How often did you have tea or coffeewhile watching TV in addition to breakfast lunch or dinner (last 4 weeks) . This question was only asked in GQV4 so not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_teacoffee and data derived into: gq_tv_teacoffee_DER. Please request those variables instead.
Categorical
Other snacks while watching TV
How often did you have other (please list) snacks while watching TV in addition to breakfast lunch or dinner (last 4 weeks) . This question was only asked in GQV4 so not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_TV_others and data derived into: gq_tv_others_DER. Please request those variables instead.
Categorical
Other snacks while watching TV text
Which other (please list) snacks did you have while watching TV in addition to breakfast lunch or dinner (last 4 weeks) . This question was only asked in GQV4 so not all participants will have this data. New variable GQ_TV_others_txt now available which should be requested instead.
Text
Main meal 6-8am
Had a main meal between 6am - 8am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D601aMain or GQV3_D601aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0204 and data derived into: gq_eat_main0204_DER. Please request those variables instead.
Categorical
Light meal 6-8am
Had a light meal between 6am - 8am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D601bLight or GQV3_D601bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0204 and data derived into: gq_eat_light0204_DER. Please request those variables instead.
Categorical
Snack 6-8am
Had a snack between 6am - 8am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D601cSnack or GQV3_D601cSnack. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0204 and data derived into: gq_eat_snack0204_DER. Please request those variables instead.
Categorical
Drink only snack 6-8am
Had a drink only snack between 6am - 8am E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D601dDrink or GQV3_D601dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0204 and data derived into: gq_eat_drink0204_DER. Please request those variables instead.
Categorical
Main meal 8-10am
Had a main meal between 8am - 10am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D602aMain or GQV3_D602aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0406 and data derived into: gq_eat_main0406_DER. Please request those variables instead.
Categorical
Light meal 8-10am
Had a light meal between 8am - 10am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D602bLight or GQV3_D602bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0406 and data derived into: gq_eat_light0406_DER. Please request those variables instead.
Categorical
Snack 8-10am
Had a snack between 8am - 10am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D602cSnack or GQV3_D602cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0406 and data derived into: gq_eat_snack0406_DER. Please request those variables instead.
Categorical
Drink only snack 8-10am
Had a drink only snack between 8am - 10am E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D602dDrink or GQV3_D602dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0406 and data derived into: gq_eat_drink0406_DER. Please request those variables instead.
Categorical
Main meal 10am-12pm
Had a main meal between 10am - 12pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D603aMain or GQV3_D603aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0608 and data derived into: gq_eat_main0608_DER. Please request those variables instead.
Categorical
Light meal 10am-12pm
Had a light meal between 10am - 12pm E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D603bLight or GQV3_D603bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0608 and data derived into: gq_eat_light0608_DER. Please request those variables instead.
Categorical
Snack 10am-12pm
Had a snack between 10am - 12pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D603cSnack or GQV3_D603cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0608 and data derived into: gq_eat_snack0608_DER. Please request those variables instead.
Categorical
Drink only snack 10am-12pm
Had a drink only snack between 10am - 12pm E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D603dDrink or GQV3_D603dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0608 and data derived into: gq_eat_drink0608_DER. Please request those variables instead.
Categorical
Main meal 12-2pm
Had a main meal between 12pm - 2pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D604aMain or GQV3_D604aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0810 and data derived into: gq_eat_main0810_DER. Please request those variables instead.
Categorical
Light meal 12-2pm
Had a light meal between 12pm -2pm E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D604bLight or GQV3_D604bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0810 and data derived into: gq_eat_light0810_DER. Please request those variables instead.
Categorical
Snack 12-2pm
Had a snack between 12pm - 2pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D604cSnack or GQV3_D604cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0810 and data derived into: gq_eat_snack0810_DER. Please request those variables instead.
Categorical
Drink only snack 12-2pm
Had a drink only snack between 12pm - 2pm E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D604dDrink or GQV3_D604dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0810 and data derived into: gq_eat_drink0810_DER. Please request those variables instead.
Categorical
Main meal 2-4pm
Had a main meal between 2pm - 4pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D605aMain or GQV3_D605aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1012 and data derived into: gq_eat_main1012_DER. Please request those variables instead.
Categorical
Light meal 2-4pm
Had a light meal between 2pm - 4pm E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D605bLight or GQV3_D605bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1012 and data derived into: gq_eat_light1012_DER. Please request those variables instead.
Categorical
Snack 2-4pm
Had a snack between 2pm - 4pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D605cSnack or GQV3_D605cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1012 and data derived into: gq_eat_snack1012_DER. Please request those variables instead.
Categorical
Drink only snack 2-4pm
Had a drink only snack between 2pm - 4pm E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D605dDrink or GQV3_D605dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1012 and data derived into: gq_eat_drink1012_DER. Please request those variables instead.
Categorical
Main meal 4-6pm
Had a main meal between 4pm - 6pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D606aMain or GQV3_D606aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1214 and data derived into: gq_eat_main1214_DER. Please request those variables instead.
Categorical
Light meal 4-6pm
Had a light meal between 4pm - 6pm E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D606bLight or GQV3_D606bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1214 and data derived into: gq_eat_light1214_DER. Please request those variables instead.
Categorical
Snack 4-6pm
Had a snack between 4pm - 6pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D606cSnack or GQV3_D606cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1214 and data derived into: gq_eat_snack1214_DER. Please request those variables instead.
Categorical
Drink only snack 4-6pm
Had a drink only snack between 4pm - 6pm E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D606dDrink or GQV3_D606dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1214 and data derived into: gq_eat_drink1214_DER. Please request those variables instead.
Categorical
Main meal 6-8pm
Had a main meal between 6pm - 8pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D607aMain or GQV3_D607aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1416 and data derived into: gq_eat_main1416_DER. Please request those variables instead.
Categorical
Light meal 6-8pm
Had a light meal between 6pm - 8pm E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D607bLight or GQV3_D607bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1416 and data derived into: gq_eat_light1416_DER. Please request those variables instead.
Categorical
Snack 6-8pm
Had a snack between 6pm - 8pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D607cSnack or GQV3_D607cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1416 and data derived into: gq_eat_snack1416_DER. Please request those variables instead.
Categorical
Drink only snack 6-8pm
Had a drink only snack between 6pm - 8pm E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D607dDrink or GQV3_D607dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1416 and data derived into: gq_eat_drink1416_DER. Please request those variables instead.
Categorical
Main meal 8-10pm
Had a main meal between 8pm - 10pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D608aMain or GQV3_D608aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1618 and data derived into: gq_eat_main1618_DER. Please request those variables instead.
Categorical
Light meal 8-10pm
Had a light meal between 8pm - 10pm E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D608bLight or GQV3_D608bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1618 and data derived into: gq_eat_light1618_DER. Please request those variables instead.
Categorical
Snack 8-10pm
Had a snack between 8pm - 10pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D608cSnack or GQV3_D608cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1618 and data derived into: gq_eat_snack1618_DER. Please request those variables instead.
Categorical
Drink only snack 8-10pm
Had a drink only snack between 8pm - 10pm E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D608dDrink or GQV3_D608dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1618 and data derived into: gq_eat_drink1618_DER. Please request those variables instead.
Categorical
Main meal 10pm-12am
Had a main meal between 10pm - 12am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D609aMain or GQV3_D609aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1820 and data derived into: gq_eat_main1820_DER. Please request those variables instead.
Categorical
Light meal 10pm-12am
Had a light meal between 10pm - 12am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D609bLight or GQV3_D609bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1820 and data derived into: gq_eat_light1820_DER. Please request those variables instead.
Categorical
Snack 10pm-12am
Had a snack between 10pm - 12am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D609cSnack or GQV3_D609cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1820 and data derived into: gq_eat_snack1820_DER. Please request those variables instead.
Categorical
Drink only snack 10pm-12am
Had a drink only snack between 10pm - 12am E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D609dDrink or GQV3_D609dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1820 and data derived into: gq_eat_drink1820_DER. Please request those variables instead.
Categorical
Main meal 0-2am
Had a main meal between 12am - 2am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D610aMain or GQV3_D610aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main2022 and data derived into: gq_eat_main2022_DER. Please request those variables instead.
Categorical
Light meal 0-2am
Had a light meal between 12am - 2am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D610bLight or GQV3_D610bLight. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light2022 and data derived into: gq_eat_light2022_DER. Please request those variables instead.
Categorical
Snack 0-2am
Had a snack between 12am - 2am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D610cSnack or GQV3_D610cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack2022 and data derived into: gq_eat_snack2022_DER. Please request those variables instead.
Categorical
Drink only snack 0-2am
Had a drink only snack between 12am - 2am E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D610dDrink or GQV3_D610dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink2022 and data derived into: gq_eat_drink2022_DER. Please request those variables instead.
Categorical
Main meal 2-4am
Had a main meal between 2am - 4am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D611aMain or GQV3_D611aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main2224 and data derived into: gq_eat_main2224_DER. Please request those variables instead.
Categorical
Light meal 2-4am
Had a light meal between 2am - 4am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D611bLight or GQV3_D611bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light2224 and data derived into: gq_eat_light2224_DER. Please request those variables instead.
Categorical
Snack 2-4am
Had a snack between 2am - 4am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D611cSnack or GQV3_D611cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack2224 and data derived into: gq_eat_snack2224_DER. Please request those variables instead.
Categorical
Drink only snack 2-4am
Had a drink only snack between 2am - 4am E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D611dDrink or GQV3_D611dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink2224 and data derived into: gq_eat_drink2224_DER. Please request those variables instead.
Categorical
Main meal 4-6am
Had a main meal between 4am - 6am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast This data is also captured with GQV1_D612aMain or GQV3_D612aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main2402 and data derived into: gq_eat_main2402_DER. Please request those variables instead.
Categorical
Light meal 4-6am
Had a light meal between 4am - 6am E.g. porridge cereal toast sandwiches soup salad omelette This data is also captured with GQV1_D612bLight or GQV3_D612bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light2402 and data derived into: gq_eat_light2402_DER. Please request those variables instead.
Categorical
Snack 4-6am
Had a snack between 4am - 6am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream This data is also captured with GQV1_D612cSnack or GQV3_D612cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack2402 and data derived into: gq_eat_snack2402_DER. Please request those variables instead.
Categorical
Drink only snack 4-6am
Had a drink only snack between 4am - 6am E.g. drinks with some milk or sugar in; not low calorie drinks or water This data is also captured with GQV1_D612dDrink or GQV3_D612dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink2402 and data derived into: gq_eat_drink2402_DER. Please request those variables instead.
Categorical
Weight Watchers' diet
Currently on a 'Weight Watchers' diet. This data is also captured with GQV1_D8aWW or GQV3_D8aWW. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_ww and data derived into: gq_diet_ww_DER. Please request those variables instead.
Categorical
Slimmers World' diet
Currently on a 'Slimmers World' diet. This data is also captured with GQV1_d8bSW or GQV3_D8bSW. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_slim and data derived into: gq_diet_slim_DER. Please request those variables instead.
Categorical
Low fat diet
Currently on a low fat diet. This data is also captured with GQV1_D8cLFD or GQV3_D8cLFD. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_lowf and data derived into: gq_diet_lowf_DER. Please request those variables instead.
Categorical
Low carbohydrate diet
Currently on a low carbohydrate diet eg Atkins Diet. This data is also captured with GQV1_D8dLCD or GQV3_D8dLCD. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_lowc and data derived into: gq_diet_lowc_DER. Please request those variables instead.
Categorical
Vegetarian diet
Currently on a vegetarian diet. This data is also captured with GQV1_D8eVegetarian or GQV3_D8eVegetarian. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_veg and data derived into: gq_diet_veg_DER. Please request those variables instead.
Categorical
Vegan diet
Currently on a vegan diet. This data is also captured with GQV1_D8fVegan or GQV3_D8fVegan. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_vegan and data derived into: gq_diet_vegan_DER. Please request those variables instead.
Categorical
Kosher diet
Currently on a Kosher diet. This data is also captured with GQV1_D8gKosher or GQV3_D8gKosher. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_kosh and data derived into: gq_diet_kosh_DER. Please request those variables instead.
Categorical
Halal diet
Currently on a Halal diet. This data is also captured with GQV1_D8hHalal or GQV3_D8hHalal. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Diet_halal and data derived into: gq_diet_halal_DER. Please request those variables instead.
Categorical
Other diet
Currently on an other diet. Please describe. This data is also captured with GQV1_D8iOther or GQV3_D8iOther. You should request that data too.
Text
articipant body outline at age 10
Nine diagrams depicting participant body outline at age 10. Tick best matching one. This question was only asked in GenQ version 4. Therefore not all participants will have this data. Data was merged into new variable: GQ_BodImg_y10 and data derived into: gq_bodimg_y10_DER. Please request those variables instead.
Categorical
Participant body outline at age 20
Nine diagrams depicting participant body outline at age 20. Tick best matching one. This question was only asked in GenQ version 4. Therefore not all participants will have this data. Data was merged into new variable: GQ_BodImg_y20 and data derived into: gq_bodimg_y20_DER. Please request those variables instead.
Categorical
Participant body outline at age 30
Nine diagrams depicting participant body outline at age 30. Tick best matching one. This question was only asked in GenQ version 4. Therefore not all participants will have this data. Data was merged into new variable: GQ_BodImg_y30 and data derived into: gq_bodimg_y30_DER. Please request those variables instead.
Categorical
Participant body outline at age 40
Nine diagrams depicting participant body outline at age 40. Tick best matching one. This question was only asked in GenQ version 4. Therefore not all participants will have this data. Data was merged into new variable: GQ_BodImg_y40 and data derived into: gq_bodimg_y40_DER. Please request those variables instead.
Categorical
Participant body outline currently
Nine diagrams depicting participant body outline you currently. Tick best matching one. This question was only asked in GenQ version 4. Therefore not all participants will have this data. Data was merged into new variable: GQ_BodImg_cur and data derived into: gq_bodimg_cur_DER. Please request those variables instead.
Categorical
Fathers body outline in middle age
Nine diagrams depicting father's body outline in middle age. Tick best matching one. This question was only asked in GenQ version 4. Therefore not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_BodImg_fath and data derived into: gq_bodimg_fath_DER. Please request those variables instead.
Categorical
Weight at age 20
Approximately how much did you weigh when you were about 20 years old? This question was only asked in GenQ version 4. Therefore not all participants will have this data. All phase 1 data from all 3 GenQs was merged into new variable: GQ_BodWt_y20 and data derived into: gq_bodwt_y20_DER. Please request those variables instead.
Text
Mother's body outline in middle age
Nine diagrams depicting mother's body outline in middle age. Tick one best matching. This question was only asked in GenQ version 4. Therefore not all participants will have this data. Data wasmerged into new variable: GQ_BodImg_moth and data derived into: gq_bodimg_moth_DER. Please request those variables instead.
Categorical
Self recorded health
Self perceived health status. Overall how would you rate your health during the past 4 weeks? This data is also captured with GQV3_E1SRHealth. You should request that data too. This data is not captured in Gen Q V1. All phase 1 data from all 3 GenQs was merged into new variable: GQ_SelfR_health and data derived into: gq_selfr_health_DER. Please request those variables instead.
Categorical
Physical Activity limited by health problems
Self perceived health status. During the past 4 weeks how much did physical health problems limit your usual physycal activities (walking climbing stairs)? This data is also captured with GQV3_E2SRPhysicalProblems. You should request that data too. This All phase 1 data from all 3 GenQs was merged into new variable: GQ_SelfR_pa and data derived into: gq_selfr_pa_DER. Please request those variables instead.
Categorical
Difficulty doing daily work due to health problems
Self perceived health status. During the past 4 weeks how much difficulty did you have doing your daily work both inside and outside the home because of your physical health? This data is also captured with GQV3_E3SRPhysicalDailyWork. You should reques All phase 1 data from all 3 GenQs was merged into new variable: GQ_SelfR_work and data derived into: gq_selfr_work_DER. Please request those variables instead.
Categorical
Bodily pain
Self perceived health status. How much bodily pain have you had during the past 4 weeks? This data is also captured with GQV3_E4SRBodilyPain. You should request that data too. This data is not captured in Gen Q V1. All phase 1 data from all 3 GenQs was merged into new variable: GQ_SelfR_pain and data derived into: gq_selfr_pain_DER. Please request those variables instead.
Categorical
Energy level
Self perceived health status. During the past 4 weeks how much energy did you have? This data is also captured with GQV3_E5SREnergy. You should request that data too. This data is not captured in Gen Q V1. All phase 1 data from all 3 GenQs was merged into new variable: GQ_SelfR_energy and data derived into: gq_selfr_energy_DER. Please request those variables instead.
Categorical
Health and emotional problems affecting social activity
Self perceived health status. During the past 4 weeks how much did your physical health or emotional problems limit your social activities with family or friends? This data is also captured with GQV3_E6SREmotionalSocial. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_SelfR_social and data derived into: gq_selfr_social_DER. Please request those variables instead.
Categorical
Emotional problems
Self perceived health status. During the past 4 weeks how much have you been bothered by emotional problems (such as feeling anxious depressed or irritable)? This data is also captured with GQV3_E7SREmotional. You should request that data too. This dat All phase 1 data from all 3 GenQs was merged into new variable: GQ_SelfR_emot and data derived into: gq_selfr_emot_DER. Please request those variables instead.
Categorical
Emotional problems limiting daily work and activities
Self perceived health status. During the past 4 weeks how much did personal or emotional problems keep you from doing your usual work studies or other daily activities? This data is also captured with GQV3_E8SREmotionalDailyWork. You should request thi All phase 1 data from all 3 GenQs was merged into new variable: GQ_SelfR_emotwork and data derived into: gq_selfr_emotwork_DER. Please request those variables instead.
Categorical
Time went to sleep on a week day
In the last 4 weeks. If you had variable sleeping patterns please record the average time you went to bed and got up on weekdays and on weekend days. At what time did you go to sleep on a weekday? This question was only asked in GQV4. Therefore not all participants will have this data. Cleaned data available in GQV4_SleepingPatternsWeekDaySleep_CL.
Text
Went to sleep am or pm on a week day
In the last 4 weeks. If you had variable sleeping patterns please record the average time you went to sleep; am or pm on a week day? This question was only asked in GQV4. Therefore not all participants will have this data.
Categorical
Time got up on a week day
In the last 4 weeks. If you had variable sleeping patterns please record the average time you get up on a week day. This question was only asked in GQV4. Therefore not all participants will have this data. Cleaned data available in GQV4_SleepingPatternsWeekDayUP_CL.
Text
Got up am or pm on a week day
Got up am or pm on a week day? This question was only asked in GQV4. Therefore not all participants will have this data.
Categorical
Time went to sleep on a weekend day
In the last 4 weeks. If you had variable sleeping patterns please record the average time you went to sleep on a weekend day. This question was only asked in GQV4. Therefore not all participants will have this data. Cleaned data available in GQV4_SleepingPatternsWeekendDaySleep_CL.
Text
Went to sleep am or pm on a weekend day
In the last 4 weeks. If you had variable sleeping patterns please record the average time you went to sleep am or pm on a weekend day. This question was only asked in GQV4. Therefore not all participants will have this data.
Categorical
Time got up on a weekend day
In the last 4 weeks. If you had variable sleeping patterns please record the average time you get up on a weekend day. This question was only asked in GQV4. Therefore not all participants will have this data. Cleaned data available in GQV4_SleepingPatternsWeekendDayUP_CL.
Text
Got up am or pm on a weekend day
In the last 4 weeks. If you had variable sleeping patterns please record the average time you got up: am or pm on a weekend day. This question was only asked in GQV4. Therefore not all participants will have this data.
Categorical
Ethnic origin
Ethnic origin. This data is also captured with GQV3_F1Ethnicity but not in GQV1. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_eth and data derived into: gq_eth_DER. Please request those variables instead.
Categorical
Additional comments on gen questionnaire version 4
GQV4 additional comments made on any page with page number and text. This data is also captured with GQV1_FSGQComments or GQV3_FSGQComments. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: FSGQComments_Updated . Please request those variables instead.
Text
Questionnaire version
Questionnaire version. This data is also captured with GQV3_Qversion but not in GQV1. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_v . Please request those variables instead.
Categorical
Time went to sleep on a week day_CLEANED
New in R7. In the last 4 weeks. If you had variable sleeping patterns please record the average time you went to bed and got up on weekdays and on weekend days. At what time did you go to sleep on a weekday? CLEANED data using data in GQV4_E9SRSleepingPatternsWeekDaySleepAMPM. This question was only asked in GQV4. Therefore not all participants will have this data.
Time
Time got up on a week day_CLEANED
New in R7. In the last 4 weeks. If you had variable sleeping patterns please record the average time you get up on a week day. CLEANED data using data in GQV4_E9SRSleepingPatternsWeekDayUPAMPM. This question was only asked in GQV4. Therefore not all participants will have this data.
Time
Time went to sleep on a weekend day_CLEANED
New in R7. In the last 4 weeks. If you had variable sleeping patterns please record the average time you went to sleep on a weekend day. CLEANED data using data in GQV4_E9SRSleepingPatternsWeekendDaySleepAMPM. This question was only asked in GQV4. Therefore not all participants will have this data.
Time
Time got up on a weekend day_CLEANED
New in R7. In the last 4 weeks. If you had variable sleeping patterns please record the average time you get up on a weekend day. CLEANED data using data in GQV4_E9SRSleepingPatternsWeekendDayUPAMPM. This question was only asked in GQV4. Therefore not all participants will have this data.
Time
Body outline yourself age 30
Phase 2 data. Questionnaire reads E9. Which of the diagrams shown below best depicts your body outline at a given age and that of your parents when they were middle aged? Yourself at Age 30. Image 1 slimmest = 1 to Image 9 fattest = 9
Real
Pt taking any tablets or medicines
Phase 2 data. Questionnaire reads: Are you taking any tablets or medicines at the moment? 2 = yes; 3 = No;
Categorical
BNF code
Phase 2 data. Questionnaire reads: Which drugs and reasons? BNF Code
Text
Dosage of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Name of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Reason for taking the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
BNF code
Phase 2 data. Questionnaire reads: Which drugs and reasons? BNF Code
Real
Dosage of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Real
Name of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Reason for taking the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
BNF code
Phase 2 data. Questionnaire reads: Which drugs and reasons? BNF Code
Real
Dosage of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Name of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Reason for taking the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
BNF code
Phase 2 data. Questionnaire reads: Which drugs and reasons? BNF Code
Text
Dosage of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Name of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Reason for taking the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
BNF code
Phase 2 data. Questionnaire reads: Which drugs and reasons? BNF Code
Real
Dosage of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Name of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Reason for taking the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
BNF code
Phase 2 data. Questionnaire reads: Which drugs and reasons? BNF Code
Text
Dosage of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Name of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Reason for taking the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
BNF code
Phase 2 data. Questionnaire reads: Which drugs and reasons? BNF Code
Text
Dosage of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Name of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Reason for taking the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
BNF code
Phase 2 data. Questionnaire reads: Which drugs and reasons? BNF Code
Text
Dosage of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Name of the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Reason for taking the drugs
Phase 2 data. Questionnaire reads: Which drugs and reasons?
Text
Heart problems
Phase 2 data. Questionnaire reads A3. 1. Has your doctor ever told you that you have heart trouble? 2 = yes; 3 = no;
Categorical
Chest pain or discomfort
Phase 2 data. Questionnaire reads A3. 2. Have you ever had any pain or discomfort in your chest? If no proceed to question 7. If yes please answer also the next 4 questions. 2 = yes; 3 = no;
Categorical
Dicomfort when walking uphill
Phase 2 data. Questionnaire reads A3. 3. Do you experience this discomfort when you walk uphill or hurry? (from GQV1_A5cChestPainUphill GQV3_A5cChestPainUphill GQV4_A5cChestPainUphill) (raw info of gq_chestpain_uphill). 2 = yes; 3 = no;
Categorical
Discomfort in wlking ordinary pace
Phase 2 data. Questionnaire reads A3. 4. Do you experience this discomfort when you walk at an ordinary pace on the level? (from GQV1_A5dChestPainNormalPace GQV3_A5dChestPainNormalPace GQV4_A5dChestPainNormalPace) (raw info of gq_chestpain_normal). 2 = yes; 3 = no;
Categorical
Disomfort while walking
Phase 2 data. Questionnaire reads A3. 5. What do you do if you experience this discomfort while walking? 1 = Stop or slow down; 2 = Carry on
Categorical
Disomfort when standing still
Phase 2 data. Questionnaire reads A3. 6. If you stand still; what happens to this discomfort? 1 = It goes away; 2 = It remains the same or gets worse
Categorical
Feel faint or spells of dizziness
Phase 2 data. Questionnaire reads A3. 7. Do you often feel faint or have spells of severe dizziness? 2 - yes; 3 = no;
Categorical
Blood pressure too high
Phase 2 data. Questionnaire reads A3. 8. Has a doctor ever told you that your blood pressure was too high? 2 - yes; 3 = no;
Categorical
Taking treatment for high BP
Phase 2 data. Questionnaire reads A3. 9. If you have been told that your blood pressure was too high; are you now on treatment? 2 - yes; 3 = no;
Categorical
Bone or joint problem
Phase 2 data. Questionnaire reads A3. 10. Has your doctor ever told you that you have a bone or joint problem such as arthritis that has been aggravated by exercise or might be made worse by exercise? 2 - yes; 3 = no;
Categorical
Pregnant
Phase 2 data. Questionnaire reads A3. 11. Are you pregant? 2 = yes; 3 = no;
Categorical
Reason not following acitivity prog
Phase 2 data. Questionnaire reads A3. 12. Is there any reason you know of that means you should not follow an activity programme even if you wanted to? 2 - yes; 3 = no;
Categorical
Walk unaided 10 minutes
Phase 2 data. Questionnaire reads A3. 13. Can you walk unaided for 10 minutes at a moderate pace? 2 - yes; 3 = no;
Categorical
Ever smoked
Phase 2 data. Questionnaire reads A4. Smoking. Have you ever smoked? 2 = yes; 3 = no;
Categorical
Smoke now
Phase 2 data. Questionnaire reads A4. Smoking. Do you smoke now? 2 = yes; 3 = No;
Categorical
Age smoking started
Phase 2 data. Questionnaire reads A4. Smoking. At what age did you start smoking? Please enter age in years.
Real
Year smoking quitted
Phase 2 data. Questionnaire reads A4. Smoking. If you have stopped smoking in which year did you quit.
Real
Number of cigarettes a day
Phase 2 data. Questionnaire reads A4. Smoking. How much do you or did you smoke a day on average? Number of cigarettes a day
Real
Number of cheroots a day
Phase 2 data. Questionnaire reads A4. Smoking. How much do you or did you smoke a day on average? Number of cheroots a day
Real
Number of cigars a day
Phase 2 data. Questionnaire reads A4. Smoking. How much do you or did you smoke a day on average? Number of cigars a day
Real
Tobacco in a week
Phase 2 data. Questionnaire reads A4. Smoking. How much do you or did you smoke a day on average? Amount in grams of tobacco in a week
Real
Age of first menstrual period
Phase 2 data. Questionnaire reads A5.1. How old were you when you had your first menstrual period? 2 = I Dont Know; 3 = I have never had a period;
Categorical
Still having menstrual period
Phase 2 data. Questionnaire reads A5.2. Are you still having menstrual periods? 2 = yes; 3 = No;
Categorical
Date 1st day of last menstrual period
Phase 2 data. Questionnaire reads A6.1. On what date was the first day of your last menstrual period?
Real
Days between menstrual periods
Phase 2 data. Questionnaire reads A6.2. About how many days are there usually from the first day of one menstrual period to the first day of the next?
Real
Irregular cycles
Phase 2 data. Questionnaire reads A6.3. Do you have irregular cycles? (i.e. you cannot predict within 5 days in either direction when your next period will start) 2 = yes; 3 = No;
Categorical
Reached menopause
Phase 2 data. Questionnaire reads A7.1. Have you reached the menopause? (i.e. your periods have now stopped completely and you believe permanently; and your last period was at least six months ago) 2 = Yes; 3 = No; 4 = Dont Know because I am taking HRT and therefore am unsure whether I have reached natural menopause;
Categorical
Age when periods stopped
Phase 2 data. Questionnaire reads A7.2. How old were you when your periods stopped completely and permanently? YEARS of age
Real
Age unkown when periods stopped
Phase 2 data. Questionnaire reads A7.2. How old were you when your periods stopped completely and permanently? Dont Know
Categorical
Reason for periods stopping
Phase 2 data. Questionnaire reads A7.3. What was the reason for your periods stopping? 1 = Natural menopause; 3 = Natural menopause while on HRT or contraception; 2 = Surgery (e.g.hysterectomy/removal of ovaries); 4 = Dont know
Categorical
Other reasons for periods stopping
Phase 2 data. Questionnaire reads IF NO A7c. What was the reason for your periods stopping? Other; specify
Text
Mother's age of Menopause
Phase 2 data. Questionnaire reads IF NO A7d. What was your mother’s age of natural menopause? (see exclusions above) YEARS of age
Real
Mother's age of natural menopause
Phase 2 data. Questionnaire reads IF NO A7d. What was your mother’s age of natural menopause? (see exclusions above) Dont know
Real
When voice break
Phase 2 data. Questionnaire reads A8a. When did your voice break? 1 = Younger than average; 2 = About average age; 3 = Older than average; 4 = Dont know;
Categorical
Age of voice break
Phase 2 data. Questionnaire reads A8b. If known; at what age did your voice break? YEARS of age
Real
Age of voice break not known
Phase 2 data. Questionnaire reads A8b. If known; at what age did your voice break? Dont know
Real
When facial hair started to grow
Phase 2 data. Questionnaire reads A9a. When did you start to grow facial hair? 1 = Younger than average; 2 = About average age; 3 = Older than average; 4 = Dont know;
Categorical
Age of facial hair
Phase 2 data. Questionnaire reads A9b. If known; at what age did you grow facial hair? YEARS of age
Real
Age of facial hair not known
Phase 2 data. Questionnaire reads A9b. If known; at what age did you grow facial hair? Dont know
Real
GQ_Alc_1per14days
New in R8. B2. Do you usually drink once per fortnight? (a single variable Alc_f in GQv1) (from GQV3_B2fDrinkPerFortnight GQV4_B2fDrinkPerFortnight) (raw info of gq_alc_1per14days).
Categorical
GQ_Alc_1permth
New in R8. B2. Do you usually drink once per month? (a single variable Alc_f in GQv1) (from GQV3_B2gDrinkPerMonth GQV4_B2gDrinkPerMonth) (raw info of gq_alc_1permth).
Categorical
GQ_Alc_1to2perwk
New in R8. B2. Do you usually drink 1-(not asked in GQv1) 2 times per week? (a single variable Alc_f in GQv1) (from GQV3_B2eDrink1-2TimesPerWeek GQV4_B2eDrink12TimesPerWeek) (raw info of gq_alc_1to2perwk).
Categorical
GQ_Alc_3to4perwk
New in R8. B2. Do you usually drink 3-4 times per week? (a single variable Alc_f in GQv1) (from GQV3_B2dDrink3-4TimesPerWeek GQV4_B2dDrink34TimesPerWeek) (raw info of gq_alc_3to4perwk).
Categorical
GQ_Alc_almostday
New in R8. B2. Do you usually drink almost every day? (a single variable Alc_f in GQv1) (from GQV3_B2cDrinkMostDays GQV4_B2cDrinkMostDays) (raw info of gq_alc_almostday).
Categorical
C2. Change in alcohol consumption
C2. Has your current alcohol consumption changed significantly compared with that of some years ago? Please only tick one box. derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank;1=My consumption has increased a lot;2=My consumption has slightly increased;3=I currently consume a similar amount as before;4=My consumption has slightly decreased;5=My consumption has decreased a lot;6=In the past and at present I have been consuming little or no alcohol
Categorical
GQ_Alc_ever
New in R8. B2. Do you EVER drink alcohol? If never drinkers please go to section C on the next page. (a single variable Alc_f in GQv1) Asked differently in GQv3 (never drinkers?) and GQv4 (ever drinkers?). (from GQV3_B2aNeverDrink GQV4_B2aEverDrink) (raw info of gq_alc_ever).
Categorical
GQ_Alc_everyday
New in R8. B2. Do you usually drink every day? (a single variable Alc_f in GQv1) (from GQV3_B2bDrinkDaily GQV4_B2bDrinkDaily) (raw info of gq_alc_everyday).
Categorical
B2. Alc drink ever or never (check GQ version)
B2. Alc drink ever or never (check GQ version): 2=Yes; 3=No; -7=not applicable/answered but undetermined; -1=left blank
Categorical
GQ_Alc_f
New in R8. B3. How often do you usually have an alcoholic drink of any kind? (compiled in 8 different variables in GQv3 and GQv4) (from GQV1_B3aDrinkFrequency ) (raw info of gq_alc_f).
Categorical
B2. Alc frequency categories
B2. Alc frequency categories: 1=never/rare; 2= <1/wk; 3=1-2/wk; 4=3-4/wk; 5=almost daily; -7=not applicable/answered but undetermined
Categorical
C1. Alc frequency categories
C1. Alcohol consumption in categories of frequency consumption (5 categories) based on gq_alc_freq derived from GQ_V3.0_24/04: 1=never/rare;2= <1/wk;3=1-2/wk;4=3-4/wk;5=almost daily
Categorical
B2. Alc frequency/week
B2. Alc frequency/week: -7=not applicable/answered but undetermined; -1=left blank
Real
C1. Alc frequency/week
C1. Alcohol consumption in frequency (servings/week) based on frequency variables asked differently across the versions of the general questionnaire derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank;1=Never or rarely;2=About once a month;3=1-2 times per week;4=3-4 times per week;5=Almost every day;6=Every day
Categorical
B2. Alc exposure (grams of ethanol/week)
B2. Alc exposure (grams of ethanol/week): -7=not applicable/answered but undetermined
Real
C3. Alc exposure (grams of ethanol/week)
C3. Alcohol consumption in amounts (grams of ethanol/week) derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined
Real
GQ_Alc_less1permth
New in R8. B2. Do you usually drink less than once a month? (a single variable Alc_f in GQv1) (from GQV3_B2hDrinkLessOncePerMonth GQV4_B2hDrinkLessOncePerMonth) (raw info of gq_alc_less1permth).
Categorical
GQ_Alc_units_beer
New in R8. B3. How many units of beer lager or cider do you consume in an average week? (units/week)(from GQV1_B2aUnitsBeerPerWk GQV3_B3aUnitsBeerPerWk GQV4_B3aUnitsBeerPerWk) (raw info of gq_alc_units_beer).
Categorical
B3. Alc units of beer per week
B3. Alc units of beer per week: -7=not applicable/answered but undetermined; -1=left blank
Real
C3. Beer in weekdays (UK unites).
C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? Beer in weekdays. UK Units. derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Real
C3. Beer in weekends (UK unites).
C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? Beer in weekends. UK Units. derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Real
B2. Alc exposure (UK units/week)
B2. Alc exposure (UK units/week): -7=not applicable/answered but undetermined
Real
C3. Alc exposure (UK units/week)
C3. Alcohol consumption in amounts (UK units/week) derived from GQ_V3.0_24/04: beer x1.4 wine x2.1 spirits x1.0 fortified wine x0.9x3.5) after cleaning/harmonisation (see variables with the prefix of GQ_Alc_units_): -7=not applicable/answered but undetermined
Real
GQ_Alc_units_fortwine
New in R8. B4. How many units of Fortified wine (sherry Cinzano Campari) do you consume in an average week? (units/week) (from GQV1_B2dUnitsFortWinePerWk GQV3_B4dUnitsFortWinePerWk GQV4_B4dUnitsFortWinePerWk) (raw info of gq_alc_units_fortwine).
Categorical
B4. Alc units of fortified wine per week
B4. Alc units of fortified wine per week: -7=not applicable/answered but undetermined; -1=left blank
Real
C3. Fortified wine in weekdays (UK unites).
C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? Fortified wine in weekdays. UK Units. derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Real
C3. Fortified wine in weekends (UK unites).
C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? Fortified wine in weekdays. UK Units. derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Real
GQ_Alc_units_spirits
New in R8. B3. How many units of spirits do you consume in an average week? (units/week) (from GQV1_B2cUnitsSpiritsPerWk GQV3_B3cUnitsSpiritsPerWk GQV4_B3cUnitsSpiritsPerWk) (raw info of gq_alc_units_spirits).
Categorical
B3. Alc units of spirits per week
B3. Alc units of spirits per week: -7=not applicable/answered but undetermined; -1=left blank
Real
C3. Spirits in weekdays (UK unites).
C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? Spirits in weekdays. UK Units. derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Real
C3. Spirits in weekends (UK unites).
C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? Spirits in weekends. UK Units. derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Real
GQ_Alc_units_wine
New in R8. B3. How many units of wine do you consume in an average week? (units/week) (from GQV1_B2bUnitsWinePerWk GQV3_B3bUnitsWinePerWk GQV4_B3bUnitsWinePerWk) (raw info of gq_alc_units_wine).
Categorical
B3. Alc units of wine per week
B3. Alc units of wine per week: -7=not applicable/answered but undetermined; -1=left blank
Real
C3. Wine in weekdays (UK unites).
C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? Wine in weekdays. UK Units. derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Real
C3. Wine in weekends (UK unites).
C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? Wine in weekends. UK Units. derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Real
C3. Alc exposure weekday (grams of ethanol/week)
C3. Alc exposure weekday (grams of ethanol/week) derived from GQ_V3.0_24/04
Real
C3. Alc exposure weekday (UK units/week)
C3. Alc exposure weekday (UK units/week) derived from GQ_V3.0_24/04
Real
C3. Alc exposure weekend (grams of ethanol/week)
C3. Alc exposure weekend (grams of ethanol/week)
Real
C3. Alc exposure weekend (UK units/week)
C3. Alc exposure weekend (UK units/week) derived from GQ_V3.0_24/04
Real
Own a car or van
Phase 2 data. Questionnaire reads B10. Do you own a car or van? 2 = yes; 3 = no;
Categorical
Tv or computer in bedroom
Phase 2 data. Questionnaire reads B11. Do you have a TV or computer in your bedroom?
Categorical
Own house
Phase 2 data. Questionnaire reads B12. Do you own or rent the home where you live? Own it/buying it 2 = yes; 3 = no; -1 = left blank; -5 = more than one selected;
Categorical
Rent house
Phase 2 data. Questionnaire reads B12. Do you own or rent the home where you live? Rent it. 2 = yes; 3 = no; -1 = left blank; -5 = more than one selected;
Categorical
Marital status
Phase 2 data. Questionnaire reads B13. What is your marital status? This data is also captured with GQV3_C12MaritalStatus. You should request that data too. Not asked in GQV1. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Marit and data derived into: gq_marit_DER. Please request those variables instead. 1 = single; 2 = married or living as married; 3 = widowed; 4 = separated; 5 = divorced;
Categorical
Work full time
Phase 2 data. Questionnaire reads B1. What is your current work status? In work full time i.e. more than 30 hours per week. 2 = yes; 3 = no;
Categorical
Work part time
Phase 2 data. Questionnaire reads B1. What is your current work status? Part time work i.e. less than 30 hours per week. 2 = yes; 3 = no;
Categorical
Work keeping house
Phase 2 data. Questionnaire reads B1. What is your current work status? Keeping house. 2 = yes; 3 = no;
Categorical
Retired
Phase 2 data. Questionnaire reads B1. What is your current work status? Wholly retired from work. 2 = yes; 3 = no;
Categorical
Starting a new job
Phase 2 data. Questionnaire reads B1. What is your current work status? Waiting to start a new job already obtained. 2 = yes; 3 = no;
Categorical
Unemployed
Phase 2 data. Questionnaire reads B1. What is your current work status? Unemployed and looking for work. 2 = yes; 3 = no;
Categorical
Temporary out of work
Phase 2 data. Questionnaire reads B1. What is your current work status? Out of work as temporarily sick. 2 = yes; 3 = no;
Categorical
Sick or disabled
Phase 2 data. Questionnaire reads B1. What is your current work status? Permanently sick or disabled. 2 = yes; 3 = no;
Categorical
Work other
Phase 2 data. Questionnaire reads B1. What is your current work status? If other please specify.
Real
Self employed
Phase 2 data. Questionnaire reads B2. Employee or self employed; Do (did) you work as an employee or are (were) you self-employed? 1 = Employee; 2 = Self employed with employees; 3 = Self employed without employees;
Categorical
No of employees at work
Phase 2 data. Questionnaire reads B3. Number of employees; For employees: indicate below how many people work (worked) for your employer at the place where you work (worked). For self-employed: indicate below how many people you employ (employed). 1 = 1 to 24 people; 2 = 25 or more people;
Categorical
Supervise other employees
Phase 2 data. Questionnaire reads B4. Supervisory status; Do (did) you supervise any other employees? A supervisor or foreman is responsible for overseeing the work of other employees on a day to day basis. 2 = yes; 3 = no;
Categorical
Occupation type
Phase 2 data. Questionnaire reads B5. Occupation type; Please tick one box which best describes the sort of work you do. If you are not working now; please tick a box to show what you did in your last job. This data is also captured with GQV3_C5Occupation (but not in GQV1). You should request that data too. 1 = Modern professional ; 2 = Clerical; 3 = Senior manager; 4 = Technical; 5 = Semi-routine; 6 = Routine; 7 = Middle management; 8 = Traditional professional;
Categorical
School leaving certificate
Phase 2 data. Questionnaire reads B6. Do you have any of the following qualifications? (tick all applicable). School Leaving certificate. This data is also captured with GQV1_DMC4aSLC or GQV3_C6aSLC. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_SLC and data derived into: gq_edu_slc_DER. Please request those variables instead. 2 = yes
Categorical
CSE qualification
Phase 2 data. Questionnaire reads B6. Do you have any of the following qualifications? (tick all applicable). CSE. This data is also captured with GQV1_DMC4bCSE or GQV3_C6bCSE. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_CSE and data derived into: gq_edu_cse_DER. Please request those variables instead. 2 = yes
Categorical
GCE qualification
Phase 2 data. Questionnaire reads B6. Do you have any of the following qualifications? (tick all applicable). GCE O level or GCSE. This data is also captured with GQV1_DMC4cGCSE or GQV3_C6cGCSE. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_GCSE and data derived into: gq_edu_gcse_DER. Please request those variables instead. 2 = yes
Categorical
Matriculation
Phase 2 data. Questionnaire reads B6. Do you have any of the following qualifications? (tick all applicable). Matriculation. This data is also captured with GQV1_DMC4dMatriculation or GQV3_C6dMatriculation. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_matricul and data derived into: gq_edu_matricul_DER. Please request those variables instead. 2 = yes
Categorical
A levels
Phase 2 data. Questionnaire reads B6. Do you have any of the following qualifications? (tick all applicable). GCE A Level AS level Highers This data is also captured with GQV1_DMc4eALevels or GQV3_C6eALevels. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_Alev and data derived into: gq_edu_alev_DER. Please request those variables instead. 2 = yes
Categorical
Technical qualifications
Phase 2 data. Questionnaire reads B6. Do you have any of the following qualifications? (tick all applicable). Technical College exams City and Guilds. This data is also captured with GQV1_DMC4fC_G or GQV3_C6fC_G. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_TechCG and data derived into: gq_edu_techcg_DER. Please request those variables instead. 2 = yes
Categorical
HND or GNVQ
Phase 2 data. Questionnaire reads B6. Do you have any of the following qualifications? (tick all applicable). HND or GNVQ. This data is also captured with GQV1_DMC4gHND or GQV3_C6gHND_NVQ. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_HND_NVQ and data derived into: gq_edu_hnd_nvq_DER. Please request those variables instead. 2 = yes
Categorical
Apprenticeship
Phase 2 data. Questionnaire reads B6. Do you have any of the following qualifications? (tick all applicable). Completed Apprenticeship. This data is also captured with GQV1_DMC4hApprenticeship or GQV3_C6hApprenticeship. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_apprentice and data derived into: gq_edu_apprentice_DER. Please request those variables instead. 2 = yes
Categorical
Secretarial
Phase 2 data. Questionnaire reads B6. Do you have any of the following qualifications? (tick all applicable). Secretarial College Exams. This data is also captured with GQV1_DMC4iSecretarial or GQV3_C6iSecretarial. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_secret and data derived into: gq_edu_secret_DER. Please request those variables instead. 2 = yes
Categorical
Teaching Diploma
Phase 2 data. Questionnaire reads B6. Do you have any of the following qualifications? (tick all applicable). Teaching Diploma HNC NVQ. This data is also captured with GQV1_DMC4jHMC or GQV3_C6jHNC. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_HNC and data derived into: gq_edu_hnc_DER. Please request those variables instead. 2 = yes
Categorical
University degree
Phase 2 data. Questionnaire reads B6. Do you have any of the following qualifications? (tick all applicable). University Degree. This data is also captured with GQV1_DMC4kDegree or GQV3_C6kDegree. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_degree and data derived into: gq_edu_degree_DER. Please request those variables instead. 2 = yes
Categorical
Trade certificates
Phase 2 data. Questionnaire reads B6. Do you have any of the following qualifications? (tick all applicable). Trade Certificates. This data is also captured with GQV1_DMC4lTradeCertificate or GQV3_C6lTradeCertificate. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_trade and data derived into: gq_edu_trade_DER. Please request those variables instead. 2 = yes
Categorical
Other qualifications
Phase 2 data. Questionnaire reads B6. Do you have any of the following qualifications? (tick all applicable). Other please describe. This data is also captured with GQV1_DMC4mOther or GQV3_C6mOther. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_others and data derived into: gq_edu_others_DER. Please request those variables instead.
Text
No qualifications
Phase 2 data. Questionnaire reads B6. Do you have any of the following qualifications? (tick all applicable). None. This data is also captured with GQV1_DMC4nNone or GQV3_C6nNone. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_none and data derived into: gq_edu_none_DER. Please request those variables instead. 2 = yes
Categorical
Age full time education finished
Phase 2 data. Questionnaire reads B7. At what age did you finish full time education (in years)? This data is also captured with GQV1_DMC42aAgeEndFTE or GQV3_C7AgeEndFTE. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Edu_age and data derived into: gq_edu_age_DER. Please request those variables instead.
Real
Household Income
Phase 2 data. Questionnaire reads B8. Please can you indicate what your household income is. 1 = < £2000; 2 = £20000 - <£40000; 3 = > £40000 - <£60000; 4 = £60000 - <£80000; 5 = £80000 and above;
Categorical
No of people in household
Phase 2 data. Questionnaire reads B9. How many people are there in your household? (including children)
Real
GQ_BodImg_cur
New in R8. E10. Nine diagrams depicting participant body outline currently. Tick best matching one. (asked only in GQv4) (integers 1 to 9) (from GQV4_E10fYC) (raw info of gq_bodimg_cur).
Categorical
E10. Participant current body outline
E10. Participant current body outline : -8=not asked (GQ version difference); -1=left blank
Categorical
E9. Participant current body outline
E9. Nine diagrams depicting participant body outline currently. Tick best matching one. (integers 1 to 9) derived from GQ_V3.0_24/04: -1=left blank
Categorical
GQ_BodImg_fath
New in R8. E10. Nine diagrams depicting fathers body outline in middle age. Tick best matching one. (asked only in GQv4) (integers 1 to 9) (from GQV4_E10gFIMA) (raw info of gq_bodimg_fath).
Categorical
E10. Father's body outline in middle age
E10. Father's body outline in middle age: -8=not asked (GQ version difference); -7=not applicable/answered but undetermined; -1=left blank
Categorical
E9. Father's body outline in middle age
E9. Nine diagrams depicting fathers body outline in middle age. Tick best matching one. (integers 1 to 9) derived from GQ_V3.0_24/04: -1=left blank
Categorical
GQ_BodImg_moth
New in R8. E10. Nine diagrams depicting mothers body outline in middle age. Tick one best matching. (asked only in GQv4) (integers 1 to 9) (from GQV4_E10MIMA) (raw info of gq_bodimg_moth).
Categorical
E10. Mother's body outline in middle age
E10. Mother's body outline in middle age: -8=not asked (GQ version difference); -7=not applicable/answered but undetermined; -1=left blank
Categorical
E9. Mother's body outline in middle age
E9. Nine diagrams depicting mothers body outline in middle age. Tick one best matching. (integers 1 to 9) derived from GQ_V3.0_24/04: -1=left blank
Categorical
GQ_BodImg_y10
New in R8. E10. Nine diagrams depicting participant body outline at age 10. Tick best matching one. (asked only in GQv4) (integers 1 to 9) (from GQV4_E10bYA10) (raw info of gq_bodimg_y10).
Categorical
E10. Participant body outline at age 10
E10. Participant body outline at age 10: -8=not asked (GQ version difference); -1=left blank
Categorical
E9. Participant body outline at age 10
E9. Nine diagrams depicting participant body outline at age 10. Tick best matching one. (integers 1 to 9) derived from GQ_V3.0_24/04: -1=left blank
Categorical
GQ_BodImg_y20
New in R8. E10. Nine diagrams depicting participant body outline at age 20. Tick best matching one. (asked only in GQv4) (integers 1 to 9) (from GQV4_E10cYA20) (raw info of gq_bodimg_y20).
Categorical
E10. Participant body outline at age 20
E10. Participant body outline at age 20: -8=not asked (GQ version difference); -1=left blank
Categorical
E9. Participant body outline at age 20
E9. Nine diagrams depicting participant body outline at age 20. Tick best matching one. (integers 1 to 9) derived from GQ_V3.0_24/04: -1=left blank
Categorical
GQ_BodImg_y30
New in R8. E10. Nine diagrams depicting participant body outline at age 30. Tick best matching one. (asked only in GQv4) (integers 1 to 9) (from GQV4_E10dYA30) (raw info of gq_bodimg_y30).
Categorical
E10. Participant body outline at age 30
E10. Participant body outline at age 30: -8=not asked (GQ version difference); -1=left blank
Categorical
E9. Participant body outline at age 30
E9. Nine diagrams depicting participant body outline at age 30. Tick best matching one. (integers 1 to 9) derived from GQ_V3.0_24/04: -1=left blank
Categorical
GQ_BodImg_y40
New in R8. E10. Nine diagrams depicting participant body outline at age 40. Tick best matching one. (asked only in GQv4) (integers 1 to 9) (from GQV4_E10eYA40) (raw info of gq_bodimg_y40).
Categorical
E10. Participant body outline at age 40
E10. Participant body outline at age 40: -8=not asked (GQ version difference); -7=not applicable/answered but undetermined; -1=left blank
Categorical
E9. Participant body outline at age 40
E9. Nine diagrams depicting participant body outline at age 40. Tick best matching one. (integers 1 to 9) derived from GQ_V3.0_24/04: -1=left blank
Categorical
GQ_BodWt_y20
New in R8. E10. Approximately how much did you weigh (kg) when you were about 20 years old? Imperial or metric unit (asked only in GQv4)
Real
E10. Participant body weight at age 20
E10. Participant body weight at age 20: -8=not asked (GQ version difference); -7=not applicable/answered but undetermined; -1=left blank
Real
E10. Participant body weight at age 20
E10. Approximately how much did you weigh (kg) when you were about 20 years old? Imperial or metric unit derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Real
gq_bodwt_y20_kg_DER_p2
Data derived from Fenland Phase 2 General Questionnaire data. Data Dictionary entry not available - please contact Data management for more details.
Real
GQ_Bone_exercise
New in R8. A5. Has your doctor ever told you that you have a bone or joint problem such as arthritis that has been aggravated by exercise or might be made worse by exercise? (from GQV1_A5jBoneProblemsAggravatedByExercise GQV3_A5jBoneProblemsAggravatedByExercise GQV4_A5jBoneProblemsAggravatedByExercise) (raw info of gq_bone_exercise).
Categorical
A5. Bone problems worse by exercise
A5. Bone problems worse by exercise: 2=Yes; 3=No; -1=left blank
Categorical
A3. Bone problems worse by exercise
A3. Has your doctor ever told you that you have a bone or joint problem such as arthritis that has been aggravated by exercise or might be made worse by exercise? derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
GQ_Breakfast
New in R8. D1. How often do you usually eat breakfast? Please tick the box which is most true. (from GQV1_D1EatBreakfast GQV3_D1EatBreakfast GQV4_D1EatBreakfast) (raw info of gq_breakfast).
Categorical
D1. How often eat breakfast
D1. How often eat breakfast: 1=never or rarely; 2=1-2 times/wk; 3=3-5 times/wk; 4=>5 times/wk; -1=left blank
Categorical
C4. How often eat breakfast
C4. How often do you usually eat breakfast? Please tick the box which is most true. derived from GQ_V3.0_24/04: 1=never or rarely;2=1-2 times/wk;3=3-5 times/wk;4=>5 times/wk;-1=left blank
Categorical
GQ_Bterm
New in R8. A4. When were you born (pre post or at term). (from GQV1_A4dBorn GQV3_A4aBorn GQV4_A4aBorn) (raw info of gq_bterm).
Categorical
A4. Term of birth
A4. Term of birth: 1=very pre-term; 2=pre-term; 3=at term; 4=post term; 5=not known; -7=not applicable/answered but undetermined; -1=left blank
Categorical
A3. Birth weight in grams
A3. Birth weight in grams: -7=not applicable/answered but undetermined; -1=left blank
Real
Derived Birth weight imperial weight
New for R8. A3. What was your weight at birth in pounds and ounces. Asked differently in GQv1. (from GQV3_A3aBirthWeightImperial GQV4_A3aBirthWeightImperial) (raw info of gq_bwt_imperial).
Real
GQ_BWt_metric
New in R8. A3. What was your weight at birth? Birth weight in kilograms. Asked differently in GQv1. (from GQV3_A3bBirthWeightMetric GQV4_A3bBirthWeightMetric) (raw info of gq_bwt_metric).
Categorical
GQ_BWt_unit
New in R8. A4. What was your weight at birth units only. Asked differently in GQv3 and GQv4. (from GQV1_A4bBirthWeightUnits ) (raw info of gq_bwt_unit).
Categorical
GQ_BWt_unknown
New in R8. A3. Tick if you are not able to give your birth weight. (from GQV1_A4cBirthWeightUnknown GQV3_A3cBirthWeightUnknown GQV4_A3cBirthWeightUnknown) (raw info of gq_bwt_unknown).
Categorical
GQ_BWt_value
New in R8. A4. What was your weight at birth value entered only. Asked differently in GQv3 and GQv4.
Real
Eat snack foods using PC
Phase 2 data. Questionnaire reads C10. Apart from meals how often do you eat snack foods while using PC; tablet; smartphone or similar electronic device? 1 = Never or rarely; 2 = Occasionally; 3 = Usually; 4 = Always;
Categorical
Main meal between 6am - 8am
Phase 2 data. Questionnaire reads Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a main meal: between 6am - 8am cooked dish e.g. meat with potatoes; pizza; lasagne; fish and chips; burgers; fried breakfast. This data is also captured with GQV1_D601aMain or GQV3_D601aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0204 and data derived into: gq_eat_main0204_DER. Please request those variables instead. 2 = yes
Categorical
Light meal between 6am - 8am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a light meal between: 6am - 8am E.g. porridge; cereal; toast; sandwiches; soup; salad; omelette. This data is also captured with GQV1_D601bLight or GQV3_D601bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0204 and data derived into: gq_eat_light0204_DER. Please request those variables instead. 2 = yes
Categorical
Snack between 6am - 8am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a snack between: 6am - 8am E.g. biscuit; cake; fruit; sweets; chocolate; crisps; nuts; ice cream. This data is also captured with GQV1_D601cSnack or GQV3_D601cSnack. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0204 and data derived into: gq_eat_snack0204_DER. Please request those variables instead. 2 = yes
Categorical
Drink only snack between 6am - 8am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a drink only snack between: 6am - 8am E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV1_D601dDrink or GQV3_D601dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0204 and data derived into: gq_eat_drink0204_DER. Please request those variables instead. 2 = yes
Categorical
Main meal between 8am - 10am
Phase 2 data. Questionnaire reads Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a main meal between: 8am - 10am cooked dish e.g. meat with potatoes; pizza; lasagne; fish and chips; burgers; fried breakfast. This data is also captured with GQV1_D602aMain or GQV3_D602aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0406 and data derived into: gq_eat_main0406_DER. Please request those variables instead. 2 = yes
Categorical
Light meal between 8am - 10am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a light meal between: 8am - 10am E.g. porridge; cereal; toast; sandwiches; soup; salad; omelette. This data is also captured with GQV1_D602bLight or GQV3_D602bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0406 and data derived into: gq_eat_light0406_DER. Please request those variables instead. 2 = yes
Categorical
Snack between 8am - 10am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a snack between: 8am - 10am E.g. biscuit; cake; fruit; sweets; chocolate; crisps; nuts; ice cream. This data is also captured with GQV1_D602cSnack or GQV3_D602cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0406 and data derived into: gq_eat_snack0406_DER. Please request those variables instead. 2 = yes
Categorical
Drink only snack between 8am - 10am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a drink only snack between: 8am - 10am E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV1_D602dDrink or GQV3_D602dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0406 and data derived into: gq_eat_drink0406_DER. Please request those variables instead. 2 = yes
Categorical
Main meal between 10am - 12am
Phase 2 data. Questionnaire reads Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a main meal between: 10am - 12am cooked dish e.g. meat with potatoes; pizza; lasagne; fish and chips; burgers; fried breakfast. This data is also captured with GQV1_D603aMain or GQV3_D603aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0608 and data derived into: gq_eat_main0608_DER. Please request those variables instead. 2 = yes
Categorical
Light meal between 10am - 12pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a light meal between: 10am - 12pm E.g. porridge; cereal; toast; sandwiches; soup; salad; omelette. This data is also captured with GQV1_D603bLight or GQV3_D603bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0608 and data derived into: gq_eat_light0608_DER. Please request those variables instead. 2 = yes
Categorical
Snack between 10am - 12pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a snack between: 10am - 12pm E.g. biscuit; cake; fruit; sweets; chocolate; crisps; nuts; ice cream. This data is also captured with GQV1_D603cSnack or GQV3_D603cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0608 and data derived into: gq_eat_snack0608_DER. Please request those variables instead. 2 = yes
Categorical
Drink only snack btwn 10am - 12pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a drink only snack between: 10am - 12pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV1_D603dDrink or GQV3_D603dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0608 and data derived into: gq_eat_drink0608_DER. Please request those variables instead. 2 = yes
Categorical
Main meal between 12pm - 2pm
Phase 2 data. Questionnaire reads Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a main meal between: 12pm - 2pm cooked dish e.g. meat with potatoes; pizza; lasagne; fish and chips; burgers; fried breakfast. This data is also captured with GQV1_D604aMain or GQV3_D604aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main0810 and data derived into: gq_eat_main0810_DER. Please request those variables instead. 2 = yes
Categorical
Light meal between 12pm - 2pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a light meal between: 12pm -2pm E.g. porridge; cereal; toast; sandwiches; soup; salad; omelette. This data is also captured with GQV1_D604bLight or GQV3_D604bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light0810 and data derived into: gq_eat_light0810_DER. Please request those variables instead. 2 = yes
Categorical
Snack between 12pm - 2pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a snack between: 12pm - 2pm E.g. biscuit; cake; fruit; sweets; chocolate; crisps; nuts; ice cream. This data is also captured with GQV1_D604cSnack or GQV3_D604cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack0810 and data derived into: gq_eat_snack0810_DER. Please request those variables instead. 2 = yes
Categorical
Drink only snack between 12pm - 2pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a drink only snack between: 12pm - 2pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV1_D604dDrink or GQV3_D604dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink0810 and data derived into: gq_eat_drink0810_DER. Please request those variables instead. 2 = yes
Categorical
Main meal between 2pm - 4pm
Phase 2 data. Questionnaire reads Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a main meal between: 2pm - 4pm cooked dish e.g. meat with potatoes; pizza; lasagne; fish and chips; burgers; fried breakfast. This data is also captured with GQV1_D605aMain or GQV3_D605aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1012 and data derived into: gq_eat_main1012_DER. Please request those variables instead. 2 = yes
Categorical
Light meal between 2pm - 4pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a light meal between: 2pm - 4pm E.g. porridge; cereal; toast; sandwiches; soup; salad; omelette. This data is also captured with GQV1_D605bLight or GQV3_D605bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1012 and data derived into: gq_eat_light1012_DER. Please request those variables instead. 2 = yes
Categorical
Snack between 2pm - 4pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a snack between: 2pm - 4pm E.g. biscuit; cake; fruit; sweets; chocolate; crisps; nuts; ice cream. This data is also captured with GQV1_D605cSnack or GQV3_D605cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1012 and data derived into: gq_eat_snack1012_DER. Please request those variables instead. 2 = yes
Categorical
Drink only snack between 2pm - 4pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a drink only snack between: 2pm - 4pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV1_D605dDrink or GQV3_D605dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1012 and data derived into: gq_eat_drink1012_DER. Please request those variables instead. 2 = yes
Categorical
Main meal between 4pm - 6pm
Phase 2 data. Questionnaire reads Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a main meal between: 4pm - 6pm cooked dish e.g. meat with potatoes; pizza; lasagne; fish and chips; burgers; fried breakfast. This data is also captured with GQV1_D606aMain or GQV3_D606aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1214 and data derived into: gq_eat_main1214_DER. Please request those variables instead. 2 = yes
Categorical
Light meal between 4pm - 6pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a light meal between: 4pm - 6pm E.g. porridge; cereal; toast; sandwiches; soup; salad; omelette. This data is also captured with GQV1_D606bLight or GQV3_D606bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1214 and data derived into: gq_eat_light1214_DER. Please request those variables instead. 2 = yes
Categorical
Snack between 4pm -6pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a snack between: 4pm - 6pm E.g. biscuit; cake; fruit; sweets; chocolate; crisps; nuts; ice cream. This data is also captured with GQV1_D606cSnack or GQV3_D606cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1214 and data derived into: gq_eat_snack1214_DER. Please request those variables instead. 2 = yes
Categorical
Drink only snack between 4pm - 6pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a drink only snack between: 4pm - 6pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV1_D606dDrink or GQV3_D606dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1214 and data derived into: gq_eat_drink1214_DER. Please request those variables instead. 2 = yes
Categorical
Main meal between 6pm - 8pm
Phase 2 data. Questionnaire reads Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a main meal between: 6pm - 8pm cooked dish e.g. meat with potatoes; pizza; lasagne; fish and chips; burgers; fried breakfast. This data is also captured with GQV1_D607aMain or GQV3_D607aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1416 and data derived into: gq_eat_main1416_DER. Please request those variables instead. 2 = yes
Categorical
Light meal between 6pm - 8pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a light meal between: 6pm - 8pm E.g. porridge; cereal; toast; sandwiches; soup; salad; omelette. This data is also captured with GQV1_D607bLight or GQV3_D607bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1416 and data derived into: gq_eat_light1416_DER. Please request those variables instead. 2 = yes
Categorical
Snack between 6pm -8pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a snack between: 6pm - 8pm E.g. biscuit; cake; fruit; sweets; chocolate; crisps; nuts; ice cream. This data is also captured with GQV1_D607cSnack or GQV3_D607cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1416 and data derived into: gq_eat_snack1416_DER. Please request those variables instead. 2 = yes
Categorical
Drink only snack between 6pm - 8pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a drink only snack between: 6pm - 8pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV1_D607dDrink or GQV3_D607dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1416 and data derived into: gq_eat_drink1416_DER. Please request those variables instead. 2 = yes
Categorical
Main meal between 8pm - 10pm
Phase 2 data. Questionnaire reads Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a main meal between: 8pm - 10pm cooked dish e.g. meat with potatoes; pizza; lasagne; fish and chips; burgers; fried breakfast. This data is also captured with GQV1_D608aMain or GQV3_D608aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1618 and data derived into: gq_eat_main1618_DER. Please request those variables instead. 2 = yes
Categorical
Light meal between 8pm - 10pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a light meal between: 8pm - 10pm E.g. porridge; cereal; toast; sandwiches; soup; salad; omelette. This data is also captured with GQV1_D608bLight or GQV3_D608bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1618 and data derived into: gq_eat_light1618_DER. Please request those variables instead. 2 = yes
Categorical
Snack between 8pm -10pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a snack between: 8pm - 10pm E.g. biscuit; cake; fruit; sweets; chocolate; crisps; nuts; ice cream. This data is also captured with GQV1_D608cSnack or GQV3_D608cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1618 and data derived into: gq_eat_snack1618_DER. Please request those variables instead. 2 = yes
Categorical
Drink only snack between 8pm - 10pm
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a drink only snack between: 8pm - 10pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV1_D608dDrink or GQV3_D608dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1618 and data derived into: gq_eat_drink1618_DER. Please request those variables instead. 2 = yes
Categorical
Main meal between 10pm - 12am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a main meal between: 10pm - 12am cooked dish e.g. meat with potatoes; pizza; lasagne; fish and chips; burgers; fried breakfast. This data is also captured with GQV1_D609aMain or GQV3_D609aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main1820 and data derived into: gq_eat_main1820_DER. Please request those variables instead. 2 = yes
Categorical
Light meal between 10pm - 12am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a light meal between: 10pm - 12am E.g.porridge; cereal; toast; sandwiches; soup; salad; omelette. This data is also captured with GQV1_D609bLight or GQV3_D609bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light1820 and data derived into: gq_eat_light1820_DER. Please request those variables instead. 2 = yes
Categorical
Snack between 10pm -12am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a snack between: 10pm - 12am E.g. biscuit; cake; fruit; sweets; chocolate; crisps; nuts; ice cream. This data is also captured with GQV1_D609cSnack or GQV3_D609cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack1820 and data derived into: gq_eat_snack1820_DER. Please request those variables instead. 2 = yes
Categorical
Drink only snack btwn 10pm - 12am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a drink only snack between: 10pm - 12am E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV1_D609dDrink or GQV3_D609dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink1820 and data derived into: gq_eat_drink1820_DER. Please request those variables instead. 2 = yes
Categorical
Main meal between 12am - 2am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a main meal between: 12am - 2am cooked dish e.g. meat with potatoes; pizza; lasagne; fish and chips; burgers; fried breakfast. This data is also captured with GQV1_D610aMain or GQV3_D610aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main2022 and data derived into: gq_eat_main2022_DER. Please request those variables instead. 2 = yes
Categorical
Light meal between 12am - 2am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a light meal between: 12am - 2am E.g. porridge; cereal; toast; sandwiches; soup; salad; omelette. This data is also captured with GQV1_D610bLight or GQV3_D610bLight. You should request that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light2022 and data derived into: gq_eat_light2022_DER. Please request those variables instead. 2 = yes
Categorical
Snack between 12am - 2am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a snack between: 12am - 2am E.g. biscuit; cake; fruit; sweets; chocolate; crisps; nuts; ice cream. This data is also captured with GQV1_D610cSnack or GQV3_D610cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack2022 and data derived into: gq_eat_snack2022_DER. Please request those variables instead. 2 = yes
Categorical
Drink only snack between 12am - 2am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a drink only snack between: 12am - 2am E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV1_D610dDrink or GQV3_D610dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink2022 and data derived into: gq_eat_drink2022_DER. Please request those variables instead. 2 = yes
Categorical
Main meal between 2am - 4am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a main meal between: 2am - 4am cooked dish e.g. meat with potatoes; pizza; lasagne; fish and chips; burgers; fried breakfast. This data is also captured with GQV1_D611aMain or GQV3_D611aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main2224 and data derived into: gq_eat_main2224_DER. Please request those variables instead. 2 = yes
Categorical
Light meal between 2am - 4am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a light meal between: 2am - 4am E.g. porridge; cereal; toast; sandwiches; soup; salad; omelette. This data is also captured with GQV1_D611bLight or GQV3_D611bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light2224 and data derived into: gq_eat_light2224_DER. Please request those variables instead. 2 = yes
Categorical
Snack between 2am - 4am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a snack between: 2am - 4am E.g. biscuit; cake; fruit; sweets; chocolate; crisps; nuts; ice cream. This data is also captured with GQV1_D611cSnack or GQV3_D611cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack2224 and data derived into: gq_eat_snack2224_DER. Please request those variables instead. 2 = yes
Categorical
Drink only snack between 2am - 4am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a drink only snack between: 2am - 4am E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV1_D611dDrink or GQV3_D611dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink2224 and data derived into: gq_eat_drink2224_DER. Please request those variables instead. 2 = yes
Categorical
Main meal between 4am - 6am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a main meal between: 4am - 6am cooked dish e.g. meat with potatoes; pizza; lasagne; fish and chips; burgers; fried breakfast. This data is also captured with GQV1_D612aMain or GQV3_D612aMain. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Main2402 and data derived into: gq_eat_main2402_DER. Please request those variables instead. 2 = yes
Categorical
Light meal between 4am - 6am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a light meal between: 4am - 6am E.g. porridge; cereal; toast; sandwiches; soup; salad; omelette. This data is also captured with GQV1_D612bLight or GQV3_D612bLight. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Light2402 and data derived into: gq_eat_light2402_DER. Please request those variables instead. 2 = yes
Categorical
Snack between 4am - 6am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a snack between: 4am - 6am E.g. biscuit; cake; fruit; sweets; chocolate; crisps; nuts; ice cream. This data is also captured with GQV1_D612cSnack or GQV3_D612cSnack. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Snack2402 and data derived into: gq_eat_snack2402_DER. Please request those variables instead. 2 = yes
Categorical
Drink only snack between 4am - 6am
Phase 2 data. Questionnaire reads C11. Eating patterns: In the table below; describe the meals or snacks you usually eat during a 24hour period. Tick the boxes that best describe what you eat and when. You may tick more than one box per line. Had a drink only snack between: 4am - 6am E.g. drinks with some milk or sugar in; not low calorie drinks or water. This data is also captured with GQV1_D612dDrink or GQV3_D612dDrink. You should be given that data too. All phase 1 data from all 3 GenQs was merged into new variable: GQ_Eat_Drink2402 and data derived into: gq_eat_drink2402_DER. Please request those variables instead. 2 = yes
Categorical
Savoury snacks plus usual meals
Phase 2 data. Questionnaire reads C12. We are interested in how often you had snacks or drinks while watching TV in the last 4 weeks in addition to your usual meals. Only think of snacks in addition to your breakfast; lunch or dinner. Please tick one box only per line. In the last 4 weeks on average how often did you have the following snacks or drinks while watching TV in addition to your breakfast; lunch or dinner? Savoury snacks(crisps;salted nuts) 1 = None; 2 = 1-2 times a week; 3 = 3-4 times a week; 4 = 5-6 times a week; 5 = Once a day; 6 = 2 times a day; 7 = 3 times a day; 8 = 4 times a day; 9 = 5 times a day; 10 = More than 5 a day;
Categorical
Sweets cakes bisct plus usual meals
Phase 2 data. Questionnaire reads C12. We are interested in how often you had snacks or drinks while watching TV in the last 4 weeks in addition to your usual meals. Only think of snacks in addition to your breakfast; lunch or dinner. Please tick one box only per line. In the last 4 weeks on average how often did you have the following snacks or drinks while watching TV in addition to your breakfast; lunch or dinner? Sweets; chocolate bars; cakes; biscuits. 1 = None; 2 = 1-2 times a week; 3 = 3-4 times a week; 4 = 5-6 times a week; 5 = Once a day; 6 = 2 times a day; 7 = 3 times a day; 8 = 4 times a day; 9 = 5 times a day; 10 = More than 5 a day;
Categorical
Icecream chocolate plus usual meals
Phase 2 data. Questionnaire reads C12. We are interested in how often you had snacks or drinks while watching TV in the last 4 weeks in addition to your usual meals. Only think of snacks in addition to your breakfast; lunch or dinner. Please tick one box only per line. In the last 4 weeks on average how often did you have the following snacks or drinks while watching TV in addition to your breakfast; lunch or dinner? Ice cream; chocolate mousse. 1 = None; 2 = 1-2 times a week; 3 = 3-4 times a week; 4 = 5-6 times a week; 5 = Once a day; 6 = 2 times a day; 7 = 3 times a day; 8 = 4 times a day; 9 = 5 times a day; 10 = More than 5 a day;
Categorical
Yoghurt rice pudd plus usual meals
Phase 2 data. Questionnaire reads C12. We are interested in how often you had snacks or drinks while watching TV in the last 4 weeks in addition to your usual meals. Only think of snacks in addition to your breakfast; lunch or dinner. Please tick one box only per line. In the last 4 weeks on average how often did you have the following snacks or drinks while watching TV in addition to your breakfast; lunch or dinner? Yoghurt; rice pudding. 1 = None; 2 = 1-2 times a week; 3 = 3-4 times a week; 4 = 5-6 times a week; 5 = Once a day; 6 = 2 times a day; 7 = 3 times a day; 8 = 4 times a day; 9 = 5 times a day; 10 = More than 5 a day;
Categorical
Soda in addition to usual meals
Phase 2 data. Questionnaire reads C12. We are interested in how often you had snacks or drinks while watching TV in the last 4 weeks in addition to your usual meals. Only think of snacks in addition to your breakfast; lunch or dinner. Please tick one box only per line. In the last 4 weeks on average how often did you have the following snacks or drinks while watching TV in addition to your breakfast; lunch or dinner? Soda. 1 = None; 2 = 1-2 times a week; 3 = 3-4 times a week; 4 = 5-6 times a week; 5 = Once a day; 6 = 2 times a day; 7 = 3 times a day; 8 = 4 times a day; 9 = 5 times a day; 10 = More than 5 a day;
Categorical
Alcoholic drinks plus usual meals
Phase 2 data. Questionnaire reads C12. We are interested in how often you had snacks or drinks while watching TV in the last 4 weeks in addition to your usual meals. Only think of snacks in addition to your breakfast; lunch or dinner. Please tick one box only per line. In the last 4 weeks on average how often did you have the following snacks or drinks while watching TV in addition to your breakfast; lunch or dinner? Alcoholic drinks. 1 = None; 2 = 1-2 times a week; 3 = 3-4 times a week; 4 = 5-6 times a week; 5 = Once a day; 6 = 2 times a day; 7 = 3 times a day; 8 = 4 times a day; 9 = 5 times a day; 10 = More than 5 a day;
Categorical
Fruit juice plus usual meals
Phase 2 data. Questionnaire reads C12. We are interested in how often you had snacks or drinks while watching TV in the last 4 weeks in addition to your usual meals. Only think of snacks in addition to your breakfast; lunch or dinner. Please tick one box only per line. In the last 4 weeks on average how often did you have the following snacks or drinks while watching TV in addition to your breakfast; lunch or dinner? Fruit juice. 1 = None; 2 = 1-2 times a week; 3 = 3-4 times a week; 4 = 5-6 times a week; 5 = Once a day; 6 = 2 times a day; 7 = 3 times a day; 8 = 4 times a day; 9 = 5 times a day; 10 = More than 5 a day;
Categorical
Squash plus usual meals
Phase 2 data. Questionnaire reads C12. We are interested in how often you had snacks or drinks while watching TV in the last 4 weeks in addition to your usual meals. Only think of snacks in addition to your breakfast; lunch or dinner. Please tick one box only per line. In the last 4 weeks on average how often did you have the following snacks or drinks while watching TV in addition to your breakfast; lunch or dinner? Squash. 1 = None; 2 = 1-2 times a week; 3 = 3-4 times a week; 4 = 5-6 times a week; 5 = Once a day; 6 = 2 times a day; 7 = 3 times a day; 8 = 4 times a day; 9 = 5 times a day; 10 = More than 5 a day;
Categorical
Milk shake plus usual meals
Phase 2 data. Questionnaire reads C12. We are interested in how often you had snacks or drinks while watching TV in the last 4 weeks in addition to your usual meals. Only think of snacks in addition to your breakfast; lunch or dinner. Please tick one box only per line. In the last 4 weeks on average how often did you have the following snacks or drinks while watching TV in addition to your breakfast; lunch or dinner? Milk; milkshake; hot chocolate. 1 = None; 2 = 1-2 times a week; 3 = 3-4 times a week; 4 = 5-6 times a week; 5 = Once a day; 6 = 2 times a day; 7 = 3 times a day; 8 = 4 times a day; 9 = 5 times a day; 10 = More than 5 a day;
Categorical
Tea or coffee plus usual meals
Phase 2 data. Questionnaire reads C12. We are interested in how often you had snacks or drinks while watching TV in the last 4 weeks in addition to your usual meals. Only think of snacks in addition to your breakfast; lunch or dinner. Please tick one box only per line. In the last 4 weeks on average how often did you have the following snacks or drinks while watching TV in addition to your breakfast; lunch or dinner? Tea or coffee. 1 = None; 2 = 1-2 times a week; 3 = 3-4 times a week; 4 = 5-6 times a week; 5 = Once a day; 6 = 2 times a day; 7 = 3 times a day; 8 = 4 times a day; 9 = 5 times a day; 10 = More than 5 a day;
Categorical
Other snack splus usual meals
Phase 2 data. Questionnaire reads C12. We are interested in how often you had snacks or drinks while watching TV in the last 4 weeks in addition to your usual meals. Only think of snacks in addition to your breakfast; lunch or dinner. Please tick one box only per line. In the last 4 weeks on average how often did you have the following snacks or drinks while watching TV in addition to your breakfast; lunch or dinner? Other. 1 = None; 2 = 1-2 times a week; 3 = 3-4 times a week; 4 = 5-6 times a week; 5 = Once a day; 6 = 2 times a day; 7 = 3 times a day; 8 = 4 times a day; 9 = 5 times a day; 10 = More than 5 a day;
Categorical
Name of the other text
Phase 2 data. Questionnaire reads C12. We are interested in how often you had snacks or drinks while watching TV in the last 4 weeks in addition to your usual meals. Only think of snacks in addition to your breakfast; lunch or dinner. Please tick one box only per line. In the last 4 weeks on average how often did you have the following snacks or drinks while watching TV in addition to your breakfast; lunch or dinner? Other (text)
Text
Special diets: Weight watchers
Phase 2 data. Questionnaire reads C13. Special diets. Please tick to show if you are currently on any of the following special diets. Weight watchers. 1 = Less than 6 months; 2 = More than 6 months;
Categorical
Special diets: Slimming world
Phase 2 data. Questionnaire reads C13. Special diets. Please tick to show if you are currently on any of the following special diets. Slimming world. 1 = Less than 6 months; 2 = More than 6 months;
Categorical
Low fat diet
Phase 2 data. Questionnaire reads C13. Special diets. Please tick to show if you are currently on any of the following special diets. Low fat diet. 1 = Less than 6 months; 2 = More than 6 months;
Categorical
Low carbohydrate diet
Phase 2 data. Questionnaire reads C13. Special diets. Please tick to show if you are currently on any of the following special diets. Low carbohydrate diet eg Atkins diet.
Categorical
Vegetarian diet
Phase 2 data. Questionnaire reads C13. Special diets. Please tick to show if you are currently on any of the following special diets. Vegetarian. 1 = Less than 6 months; 2 = More than 6 months;
Categorical
Vegan diet
Phase 2 data. Questionnaire reads C13. Special diets. Please tick to show if you are currently on any of the following special diets. Vegan. 1 = Less than 6 months; 2 = More than 6 months;
Categorical
Kosher diet
Phase 2 data. Questionnaire reads C13. Special diets. Please tick to show if you are currently on any of the following special diets. Kosher. 1 = Less than 6 months; 2 = More than 6 months;
Categorical
Halal
Phase 2 data. Questionnaire reads C13. Special diets. Please tick to show if you are currently on any of the following special diets. Halal. 1 = Less than 6 months; 2 = More than 6 months;
Categorical
Other diet
Phase 2 data. Questionnaire reads C13. Special diets. Please tick to show if you are currently on any of the following special diets. Other. 1 = Less than 6 months; 2 = More than 6 months;
Categorical
Special diets: Jenny Craig
Phase 2 data. Questionnaire reads C13. Special diets. Please tick to show if you are currently on any of the following special diets. Jenny Craig. 1 = Less than 6 months; 2 = More than 6 months;
Categorical
Drank alcohol in the past 1 year
Phase 2 data. Questionnaire reads C1. During the past 1 year; how often did you drink alcoholic drinks of any kind? Please only tick one box. 1 = Never or rarely; 2 = About once a month; 3 = 1-2 times per week; 4 = 3-4 times per week; 5 = Almost every day; 6 = Every day;
Categorical
Alcohol consumption changed
Phase 2 data. Questionnaire reads C2. Has your current alcohol consumption changed significantly compared with that of some years ago? Please only tick one box. 1 = My consumption has increased a lot; 2 = My consumption has slightly increased; 3 = I currently consume a similar amount as before; 4 = My consumption has slightly decreased; 5 = My consumption has decreased a lot; 6 = In the past and at present I have been consuming little or no alcohol;
Categorical
Units alcohol consumed wkday beer
Phase 2 data. Questionnaire reads C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? With 1 unit equivalent to 1/2 pint of Beer; Lager; or cider. Number of units.
Real
Units alcohol consumed wkday wine
Phase 2 data. Questionnaire reads C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? With 1 unit equivalent to 1/2 glass of Wine. Number of units.
Real
Units alcohol consumedwkday spirits
Phase 2 data. Questionnaire reads C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? With 1 unit equivalent to 1 single measure of Spirits. Number of units.
Real
Units beer consumed wknd day
Phase 2 data. Questionnaire reads C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? With 1 unit equivalent to 1/2 pint of Beer; Lager; or cider. Number of units.
Real
Units wine consumed wknd day
Phase 2 data. Questionnaire reads C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? With 1 unit equivalent to 1/2 glass of Wine. Number of units.
Real
Units spirits consumed wknd day
Phase 2 data. Questionnaire reads C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? With 1 unit equivalent to 1 single measure of Spirits. Number of units.
Real
Units fortifiedwine consumed wkday
Phase 2 data. Questionnaire reads C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? Fortified wine (such as sherry Cinzano Campari) With 1 unit equivalent to 1 glass of sherry. Number of units.
Real
Breakfast frequency
Phase 2 data. Questionnaire reads C4. How often do you usually eat breakfast? 1 = Never or rarely; 2 = 1-2 times per week; 3 = 3-5 times per week; 4 = More than 5 times per week
Categorical
Units fortwine consumed wkndday
Phase 2 data. Questionnaire reads C3. In a typical week; how many units of alcohol do you consume during weekdays (Monday through Thursday) and weekends (Friday through Sunday)? Fortified wine (such as sherry Cinzano Campari) With 1 unit equivalent to 1 glass of sherry. Number of units.
Real
Home delivery or take-away meals
Phase 2 data. Questionnaire reads C5. When eating your main meal at home; how often do you usually eat the following: Home delivery or take-away meals; 1 = Never or rarely; 2 = 1-2 times per week; 3 = 3-5 times per week; 4 = More than 5 times per week
Categorical
Ready-made meals or prepared foods
Phase 2 data. Questionnaire reads C5. When eating your main meal at home; how often do you usually eat the following: Ready-made meals/prepared foods; 1 = Never or rarely; 2 = 1-2 times per week; 3 = 3-5 times per week; 4 = More than 5 times per week
Categorical
Home cooked meals
Phase 2 data. Questionnaire reads C5. When eating your main meal at home; how often do you usually eat the following: Home cooked meals; 1 = Never or rarely; 2 = 1-2 times per week; 3 = 3-5 times per week; 4 = More than 5 times per week
Categorical
Meal ate outside of home
Phase 2 data. Questionnaire reads C6. On average how often do you eat a meal outside of the home (restaurants; pubs; fast-food outlets; etc)? 1 = Less than once a week; 2 = Once a week; 3 = 2-4 times a week; 4 = 5-6 times a week; 5 = Once a day; 6 = More than once a day;
Categorical
Ate meal watching tv or video
Phase 2 data. Questionnaire reads C7. How often do you eat your meal while watching television or video? 1 = Less than once a week; 2 = Once a week; 3 = 2-4 times a week; 4 = 5-6 times a week; 5 = Once a day; 6 = More than once a day;
Categorical
Ate meal using PC or similar device
Phase 2 data. Questionnaire reads C8. How often do you eat your meal while using PC; tablet; smartphone or similar electronic device? 1 = Less than once a week; 2 = Once a week; 3 = 2-4 times a week; 4 = 5-6 times a week; 5 = Once a day; 6 = More than once a day;
Categorical
Eat snack foods watching TV
Phase 2 data. Questionnaire reads C9. Apart from meals how often do you eat snack foods while watching television? 1 = Never or rarely; 2 = Occasionally; 3 = Usually; 4 = Always;
Categorical
GQ_ChestPain_action
New in R8. A5. What do you do if you experience pain or chest discomfort while walking? (from GQV1_A5eActionWhenChestDiscomfort GQV3_A5eActionWhenChestDiscomfort GQV4_A5eActionWhenChestDiscomfort) (raw info of gq_chestpain_action).
Categorical
A5. Action taken after chest discomfort from walking
A5. Action taken after chest discomfort from walking: 1=stop or slow down; 2=carry on; -7=not applicable/answered but undetermined; -1=left blank
Categorical
A3. Action taken after chest discomfort from walking
A3. What do you do if you experience pain or chest discomfort while walking? derived from GQ_V3.0_24/04: 1=stop or slow down;2=carry on;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_ChestPain_dr
New in R8. A5. Has your doctor ever told you that you have heart trouble? (from GQV1_A5aDrReportHeartTrouble GQV3_A5aDrReportHeartTrouble GQV4_A5aDrReportHeartTrouble) (raw info of gq_chestpain_dr).
Categorical
Derived Dr reported heart trouble
New for R8. A5. Has your doctor ever told you that you have heart trouble? derived from GQV1_A5aDrReportHeartTrouble GQV3_A5aDrReportHeartTrouble GQV4_A5aDrReportHeartTrouble after cleaning/harmonisation (see GQ_ChestPain_dr). 2 = Yes; 3 = No; -7 = not applicable/answered but undetermined; -1 = left blank;
Categorical
GQ_ChestPain_ever
New in R8. A5. Have you ever had any pain or discomfort in your chest? If no proceed to question 7. If yes please answer the next question. (from GQV1_A5bChestPain GQV3_A5bChestPain GQV4_A5bChestPain) (raw info of gq_chestpain_ever).
Categorical
A5. Chest pain ever
A5. Chest pain ever: 2=Yes; 3=No; -1=left blank
Categorical
A3. Chest pain ever
A3. Have you ever had any pain or discomfort in your chest? If no proceed to question 7. If yes please answer the next question. derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_ChestPain_normal
New in R8. A5. Do you experience pain or chest discomfort when you walk at an ordinary pace on the level? (from GQV1_A5dChestPainNormalPace GQV3_A5dChestPainNormalPace GQV4_A5dChestPainNormalPace) (raw info of gq_chestpain_normal).
Categorical
A5. Chest discomfort from walking
A5. Chest discomfort from walking: 2=Yes; 3=No; -7=not applicable/answered but undetermined; -1=left blank
Categorical
A3. Chest discomfort from walking
A3. Do you experience pain or chest discomfort when you walk at an ordinary pace on the level? derived from GQ_V3.0_24/04: 2=Yes;3=No;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_ChestPain_stop
New in R8. A5. If you stand still what happens to pain or chest discomfort? (from GQV1_A5fChestDiscomfortAfterStopping GQV3_A5fChestDiscomfortAfterStopping GQV4_A5fChestDiscomfortAfterStopping) (raw info of gq_chestpain_stop).
Categorical
A5. Chest discomfort after stopping
A5. Chest discomfort after stopping: 1=it gose away; 2=it remains the same or gets worse; -7=not applicable/answered but undetermined; -1=left blank
Categorical
A3. Chest discomfort after stopping
A3. If you stand still what happens to pain or chest discomfort? derived from GQ_V3.0_24/04: 1=it goes away;2=it remains the same or gets worse;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_ChestPain_uphill
New in R8. A5. Do you experience pain or chest discomfort when you walk uphill or hurry? (from GQV1_A5cChestPainUphill GQV3_A5cChestPainUphill GQV4_A5cChestPainUphill) (raw info of gq_chestpain_uphill).
Categorical
A5. Chest discomfort from walking uphill
A5. Chest discomfort from walking uphill: 2=Yes; 3=No; -7=not applicable/answered but undetermined; -1=left blank
Categorical
A3. Chest discomfort from walking uphill
A3. Do you experience pain or chest discomfort when you walk uphill or hurry? derived from GQ_V3.0_24/04: 2=Yes;3=No;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_comments
New in R8. GQ. Additional comments made on any page with page number and text. TEXT. (from GQV1_FSGQComments GQV3_FSGQComments GQV4_FSGQComments)
Text
Weekday go to bed time
Phase 2 data. Questionnaire reads C15. Sleeping patterns. Think about what time you went to sleep and you got up on a typical day in the last 4 weeks. If you had variable sleeping patterns (eg you did shift work) please record the typical time you went to bed and got up on weekdays and on weekend days. Please use 24 hr clock format. At what time did you go to bed on a weekday? -1 = left blank;
Time
Weekday wake time
Phase 2 data. Questionnaire reads C15. Sleeping patterns. Think about what time you went to sleep and you got up on a typical day in the last 4 weeks. If you had variable sleeping patterns (eg you did shift work) please record the typical time you went to bed and got up on weekdays and on weekend days. Please use 24 hr clock format. At what time did you wake up on a weekday? -1 = left blank;
Time
Weekend day go to bed time
Phase 2 data. Questionnaire reads C15. Sleeping patterns. Think about what time you went to sleep and you got up on a typical day in the last 4 weeks. If you had variable sleeping patterns (eg you did shift work) please record the typical time you went to bed and got up on weekdays and on weekend days. Please use 24 hr clock format. At what time did you go to bed on a weekend day? -1 = left blank;
Time
Weekend day wake time
Phase 2 data. Questionnaire reads C15. Sleeping patterns. Think about what time you went to sleep and you got up on a typical day in the last 4 weeks. If you had variable sleeping patterns (eg you did shift work) please record the typical time you went to bed and got up on weekdays and on weekend days. Please use 24 hr clock format. At what time did you wake up on a weekend day? -1 = left blank;
Time
Journey to Work1 from
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
Mode of trsprt for journey to Wrk1
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. 1 = Walk; 2 = Cycle; 3 = Bus/train; 4 = Car/motorcycle
Categorical
Journey to Work1 to
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
Journey to Work2 from
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
Mode of trsprt for journey to Wrk2
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. 1 = Walk; 2 = Cycle; 3 = Bus/train; 4 = Car/motorcycle
Categorical
Journey to Work2 to
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
Journey to Work3 from
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
Mode of trsprt for journey to Wrk3
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. 1 = Walk; 2 = Cycle; 3 = Bus/train; 4 = Car/motorcycle
Categorical
Journey to Work3 to
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
Journey to Work4 from
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
Mode of trsprt for journey to Wrk4
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. 1 = Walk; 2 = Cycle; 3 = Bus/train; 4 = Car/motorcycle
Categorical
Journey to Work4 to
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
Time at work from
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
Time at work to
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
None
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
Return from Wrk1 mode of transport
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. 1 = Walk; 2 = Cycle; 3 = Bus/train; 4 = Car/motorcycle
Categorical
Time return from wrk1
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
None
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
Return from Wrk2 mode of transport
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. 1 = Walk; 2 = Cycle; 3 = Bus/train; 4 = Car/motorcycle
Categorical
Time return from wrk2
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
None
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
Return from Wrk3 mode of transport
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. 1 = Walk; 2 = Cycle; 3 = Bus/train; 4 = Car/motorcycle
Categorical
Time return from wrk3
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
None
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
Return from Wrk4 mode of transport
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. 1 = Walk; 2 = Cycle; 3 = Bus/train; 4 = Car/motorcycle
Categorical
Time return from wrk4
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. Time
Time
Do not travel direct to work
Phase 2 data. Questionnaire reads D16. Transportation/commuting patterns for work. Think about how you got to work on a typical day in the last 4 weeks. Which main mode(s) of transport did you use and what time did you start (different parts of) your journey to work? Similarly; think of your journey home which may or may not be the same sequence; just in reverse. Please use 24hr clock format; e.g. 08:30 and 16:30. If your usual journey home involves going vigorous intensity activity another location; include that in the table. 1 = I dont usually travel direct from work to home.
Categorical
C8. Meal while using an electric device
C8. How often do you eat your meal while watching television or video? derived from GQ_V3.0_24/04: 1=<1/wk;2=1/wk;3=2-4 times/wk;4=5-6 times/wk;5=once/d;6=>1/d;-1=left blank;-7=not applicable/answered but undetermined
Categorical
C10. Snack while using an electric device
C10. How often do you eat your meal while watching television or video? derived from GQ_V3.0_24/04: 1=<1/wk;2=1/wk;3=2-4 times/wk;4=5-6 times/wk;5=once/d;6=>1/d;-1=left blank;-7=not applicable/answered but undetermined
Categorical
D8. food tolerance to some foods
D8. food tolerance to some foods: 2=Yes; -7=not applicable/answered but undetermined
Categorical
C13. food tolerance or avoidance against some foods
C13. Special diet concerning intolerance to some foods (eg dairy fibre fish) derived from GQ_V3.0_24/04: 2=Yes;-7=not applicable/answered but undetermined
Categorical
C13. Intermittent Fasting; 5:2 etc.
C13. Intermittent Fasting; 5:2 etc. derived from GQ_V3.0_24/04: 2=Yes;-7=not applicable/answered but undetermined
Categorical
D8. gluten-free diet
D8. gluten-free diet: 2=Yes; -7=not applicable/answered but undetermined
Categorical
C13. gluten-free diet
C13. Special diet avoiding gluten (gluten-free diet) derived from GQ_V3.0_24/04: 2=Yes;-7=not applicable/answered but undetermined
Categorical
GQ_Diet_halal
New in R8. D8. Currently on a Halal diet. (from GQV1_D8hHalal GQV3_D8hHalal GQV4_D8hHalal) (raw info of gq_diet_halal).
Categorical
D8. Special diet - Halal diet
D8. Special diet - Halal diet: 1=Yes for <6 m; 2=Yes for 6 m or longer; -7=not applicable/answered but undetermined; -1=left blank
Categorical
C13. Special diet - Halal diet
C13. Currently on a Halal diet. derived from GQ_V3.0_24/04: 1=Yes for <6 m;2=Yes for 6 m or longer;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_Diet_kosh
New in R8. D8. Currently on a Kosher diet. (from GQV1_D8gKosher GQV3_D8gKosher GQV4_D8gKosher) (raw info of gq_diet_kosh).
Categorical
D8. Special diet - Kosher diet
D8. Special diet - Kosher diet: 1=Yes for <6 m; 2=Yes for 6 m or longer; -7=not applicable/answered but undetermined; -1=left blank
Categorical
C13. Special diet - Kosher diet
C13. Currently on a Kosher diet. derived from GQ_V3.0_24/04: 1=Yes for <6 m;2=Yes for 6 m or longer;-7=not applicable/answered but undetermined;-1=left blank
Categorical
D8. lacto-free diet
D8. lacto-free diet: 2=Yes; -7=not applicable/answered but undetermined
Categorical
C13. lacto-free diet
C13. Special diet avoiding dairy products (lacto-free diet) derived from GQ_V3.0_24/04: 2=Yes;-7=not applicable/answered but undetermined
Categorical
GQ_Diet_lowc
New in R8. D8. Currently on a low carbohydrate diet eg Atkins Diet. (from GQV1_D8dLCD GQV3_D8dLCD GQV4_D8dLCD) (raw info of gq_diet_lowc).
Categorical
D8. Special diet - Low carbohydrate diet
D8. Special diet - Low carbohydrate diet: 1=Yes for <6 m; 2=Yes for 6 m or longer; -7=not applicable/answered but undetermined; -1=left blank
Categorical
C13. Special diet - Low carbohydrate diet
C13. Currently on a low carbohydrate diet eg Atkins Diet. derived from GQ_V3.0_24/04: 1=Yes for <6 m;2=Yes for 6 m or longer;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_Diet_lowf
New in R8. D8. Currently on a low fat diet. (from GQV1_D8cLFD GQV3_D8cLFD GQV4_D8cLFD) (raw info of gq_diet_lowf).
Categorical
D8. Special diet - Low fat diet
D8. Special diet - Low fat diet: 1=Yes for <6 m; 2=Yes for 6 m or longer; -7=not applicable/answered but undetermined; -1=left blank
Categorical
C13. Special diet - Low fat diet
C13. Currently on a low fat diet. derived from GQ_V3.0_24/04: 1=Yes for <6 m;2=Yes for 6 m or longer;-7=not applicable/answered but undetermined;-1=left blank
Categorical
D8. Other special diets
D8. Other special diets: 2=Yes; -7=not applicable/answered but undetermined
Categorical
C13. Other special diets
C13. Special diet not classified to a specific type derived from GQ_V3.0_24/04: 2=Yes;-7=not applicable/answered but undetermined
Categorical
D8. Diet w/o meat
D8. Diet w/o meat: 1=vegan/vegetarian; 2=Pescetarian/ovo-vegetarian/low meat; -7=not applicable/answered but undetermined
Categorical
C13. Diet w/o meat
C13. Special diet not eating meat as vegans/vegetarians or as semi vegetarians eating fish (eg Pescetarian diet) or chicken or eggs derived from GQ_V3.0_24/04: 1=vegan/vegetarian;2=Pescetarian/ovo-vegetarian/low meat;-7=not applicable/answered but undetermined
Categorical
GQ_Diet_oth
New in R8. D8. Currently on an other diet. Please describe. TEXT
Text
GQ_Diet_slim
New in R8. D8. Currently on a 'Slimmers World' diet. (from GQV1_d8bSW GQV3_D8bSW GQV4_D8bSW) (raw info of gq_diet_slim).
Categorical
D8. Special diet - Slimmers World' diet
D8. Special diet - Slimmers World' diet: 1=Yes for <6 m; 2=Yes for 6 m or longer; -7=not applicable/answered but undetermined; -1=left blank
Categorical
C13. Special diet - Slimmers World' diet
C13. Currently on a 'Slimmers World' diet. derived from GQ_V3.0_24/04: 1=Yes for <6 m;2=Yes for 6 m or longer;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_Diet_veg
New in R8. D8. Currently on a vegetarian diet. (from GQV1_D8eVegetarian GQV3_D8eVegetarian GQV4_D8eVegetarian) (raw info of gq_diet_veg).
Categorical
GQ_Diet_vegan
New in R8. D8. Currently on a vegan diet. (from GQV1_D8fVegan GQV3_D8fVegan GQV4_D8fVegan) (raw info of gq_diet_vegan).
Categorical
D8. Special diet - Vegan diet
D8. Special diet - Vegan diet: 1=Yes for <6 m; 2=Yes for 6 m or longer; -7=not applicable/answered but undetermined; -1=left blank
Categorical
C13. Special diet - Vegan diet
C13. Currently on a vegan diet. derived from GQ_V3.0_24/04: 1=Yes for <6 m;2=Yes for 6 m or longer;-7=not applicable/answered but undetermined;-1=left blank
Categorical
D8. Special diet - Vegetarian diet
D8. Special diet - Vegetarian diet: 1=Yes for <6 m; 2=Yes for 6 m or longer; -7=not applicable/answered but undetermined; -1=left blank
Categorical
C13. Special diet - Vegetarian diet
C13. Currently on a vegetarian diet. derived from GQ_V3.0_24/04: 1=Yes for <6 m;2=Yes for 6 m or longer;-7=not applicable/answered but undetermined;-1=left blank
Categorical
D8. Diet for wt manage/loss
D8. Diet for wt manage/loss: 2=Yes; -7=not applicable/answered but undetermined
Categorical
C13. Diet for wt manage/loss
C13. Special diet for weight loss derived from GQ_V3.0_24/04: 2=Yes;-7=not applicable/answered but undetermined
Categorical
GQ_Diet_ww
New in R8. D8. Currently on a 'Weight Watchers' diet. (from GQV1_D8aWW GQV3_D8aWW GQV4_D8aWW) (raw info of gq_diet_ww).
Categorical
D8. Special diet - Weight Watchers' diet
D8. Special diet - Weight Watchers' diet: 1=Yes for <6 m; 2=Yes for 6 m or longer; -7=not applicable/answered but undetermined; -1=left blank
Categorical
C13. Special diet - Weight Watchers' diet
C13. Currently on a 'Weight Watchers' diet. derived from GQ_V3.0_24/04: 1=Yes for <6 m;2=Yes for 6 m or longer;-7=not applicable/answered but undetermined;-1=left blank
Categorical
Overall health rating
Phase 2 data. Questionnaire reads Self-Perceived Health Status. Mark the box that best describes your answer. E1. Overall; how would you rate your health during the past 4 weeks? 1 = Excellent; 2 = Very good; 3 = Good; 4 = Fair; 5 = Poor; 6 = Very poor
Categorical
PA limited by health problems
Phase 2 data. Questionnaire reads Self-Perceived Health Status. Mark the box that best describes your answer. E2. During the past 4 weeks; how much did physical health problems limit your usual physical activities (walking; climbing stairs)? 1 = Not at all; 2 = Very little; 3 = Somewhat; 4 = Quite a lot; 5 = Could not do physical activities;
Categorical
Daily activities limited by health
Phase 2 data. Questionnaire reads Self-Perceived Health Status. Mark the box that best describes your answer. E3. During the past 4 weeks; how much difficulty did you have doing your daily work; both inside and outside the home; because of your physical health? 1 = Not at all; 2 = Very little; 3 = Somewhat; 4 = Quite a lot; 5 = Could not do daily work;
Categorical
Body pain
Phase 2 data. Questionnaire reads Self-Perceived Health Status. Mark the box that best describes your answer. E4. How much bodily pain have you had during the past 4 weeks? 1 = None; 2 = Very mild; 3 = Mild; 4 = Moderate; 5 = Severe; 6 = Very severe;
Categorical
Energy
Phase 2 data. Questionnaire reads Self-Perceived Health Status. Mark the box that best describes your answer. E5. During the past 4 weeks; how much energy did you have? 1 = Very much; 2 = Quite a bit; 3 = Some; 4 = A little; 5 = None;
Categorical
Social activities limited by health
Phase 2 data. Questionnaire reads Self-Perceived Health Status. Mark the box that best describes your answer. E6. During the past 4 weeks; how much did your physical health or emotional problems limit your usual social activities with family or friends? 1 = Not at all; 2 = Very little; 3 = Somewhat; 4 = Quite a lot; 5 = Could not do social activities;
Categorical
Emotional problems
Phase 2 data. Questionnaire reads Self-Perceived Health Status. Mark the box that best describes your answer. E7. During the past 4 weeks; how much have you been bothered by emotional problems (such as feeling anxious; depressed or irritable)? 1 = Not at all; 2 = Slightly; 3 = Moderately; 4 = Quite a lot; 5 = Extremely;
Categorical
Other activities limited by emotional problems
Phase 2 data. Questionnaire reads Self-Perceived Health Status. Mark the box that best describes your answer. E8. During the past 4 weeks; how much did personal or emotional problems keep you from doing your usual work; studies; or other daily activities? 1 = Not at all; 2 = Very little; 3 = Somewhat; 4 = Quite a lot; 5 = Could not do daily activities;
Categorical
Body outline yourself age 10
Phase 2 data. Questionnaire reads E9. Which of the diagrams shown below best depicts your body outline at a given age and that of your parents when they were middle aged? Yourself at Age 10. Image 1 slimmest = 1 to Image 9 fattest = 9
Real
Body outline yourself age 20
Phase 2 data. Questionnaire reads E9. Which of the diagrams shown below best depicts your body outline at a given age and that of your parents when they were middle aged? Yourself at Age 20. Image 1 slimmest = 1 to Image 9 fattest = 9
Real
Body outline yourself age 40
Phase 2 data. Questionnaire reads E9. Which of the diagrams shown below best depicts your body outline at a given age and that of your parents when they were middle aged? Yourself at Age 40. Image 1 slimmest = 1 to Image 9 fattest = 9
Real
Body outline yourself age current
Phase 2 data. Questionnaire reads E9. Which of the diagrams shown below best depicts your body outline at a given age and that of your parents when they were middle aged? Yourself Currently. Image 1 slimmest = 1 to Image 9 fattest = 9
Real
Body outline Fthr middle age
Phase 2 data. Questionnaire reads E9. Which of the diagrams shown below best depicts your body outline at a given age and that of your parents when they were middle aged? Father in middle age. Image 1 slimmest = 1 to Image 9 fattest = 9
Real
Weight at age 20 in Kg
Phase 2 data. Questionnaire reads E9. Approximately how much did you weigh when you were about 20 years old? In Kg
Real
Weight at age 20 in lbs
Phase 2 data. Questionnaire reads E9. Approximately how much did you weigh when you were about 20 years old? In lbs
Real
Weight at age 20 in Stone
Phase 2 data. Questionnaire reads E9. Approximately how much did you weigh when you were about 20 years old? In Stone
Real
Body outline Mthr middle age
Phase 2 data. Questionnaire reads E9. Which of the diagrams shown below best depicts your body outline at a given age and that of your parents when they were middle aged? Mother in middle age. Image 1 slimmest = 1 to Image 9 fattest = 9
Real
GQ_Eatout
New in R8. D3. On average how often do you eat a meal outside of the home (restaurants pubs fast-food outlets etc)? (from GQV1_D3EatOut GQV3_D3EatOut GQV4_D3EatOut) (raw info of gq_eatout).
Categorical
D3. How often eat out
D3. How often eat out: 1=<1/wk; 2=1/wk; 3=2-4 times/wk; 4=5-6 times/wk; 5=once/d; 6=>1/d; -1=left blank
Categorical
C6. How often eat out
C6. How often eat out: 1=<1/wk;2=1/wk;3=2-4 times/wk;4=5-6 times/wk;5=once/d;6=>1/d;-1=left blank
Categorical
GQ_Eat_Drink0204
New in R8. D7. Had a drink only snack between 2am - 4am E.g. drinks with some milk or sugar in; not low calorie drinks or water. (from GQV1_D611dDrink GQV3_D611dDrink GQV4_D711dDrink) (raw info of gq_eat_drink0204).
Categorical
D7. Eating pattern - Drink only snack 2-4am
D7. Eating pattern - Drink only snack 2-4am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Drink only snack 2-4am
C11. Had a drink only snack between 2am - 4am E.g. drinks with some milk or sugar in; not low calorie drinks or water. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Drink0406
New for R8. D7. Had a drink only snack between 4am - 6am E.g. drinks with some milk or sugar in; not low calorie drinks or water. (from GQV1_D612dDrink GQV3_D612dDrink GQV4_D712dDrink) (raw info of gq_eat_drink0406)
Categorical
D7. Eating pattern - Drink only snack 4-6am
D7. Eating pattern - Drink only snack 4-6am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Drink only snack 4-6am
C11. Had a drink only snack between 4am - 6am E.g. drinks with some milk or sugar in; not low calorie drinks or water. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Drink0608
New in R8. D7. Had a drink only snack between 6am - 8am E.g. drinks with some milk or sugar in; not low calorie drinks or water. (from GQV1_D601dDrink GQV3_D601dDrink GQV4_D701dDrink) (raw info of gq_eat_drink0608).
Categorical
D7. Eating pattern - Drink only snack 6-8am
D7. Eating pattern - Drink only snack 6-8am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Drink only snack 6-8am
C11. Had a drink only snack between 6am - 8am E.g. drinks with some milk or sugar in; not low calorie drinks or water. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Drink0810
New in R8. D7. Had a drink only snack between 8am - 10am E.g. drinks with some milk or sugar in; not low calorie drinks or water. (from GQV1_D602dDrink GQV3_D602dDrink GQV4_D702dDrink) (raw info of gq_eat_drink0810).
Categorical
D7. Eating pattern - Drink only snack 8-10am
D7. Eating pattern - Drink only snack 8-10am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Drink only snack 8-10am
C11. Had a drink only snack between 8am - 10am E.g. drinks with some milk or sugar in; not low calorie drinks or water. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Drink1012
New in R8. D7. Had a drink only snack between 10am - 12pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. (from GQV1_D603dDrink GQV3_D603dDrink GQV4_D703dDrink) (raw info of gq_eat_drink1012).
Categorical
D7. Eating pattern - Drink only snack 10am-12pm
D7. Eating pattern - Drink only snack 10am-12pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Drink only snack 10am-12pm
C11. Had a drink only snack between 10am - 12pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Drink1214
New in R8. D7. Had a drink only snack between 12pm - 2pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. (from GQV1_D604dDrink GQV3_D604dDrink GQV4_D704dDrink) (raw info of gq_eat_drink1214).
Categorical
D7. Eating pattern - Drink only snack 12-2pm
D7. Eating pattern - Drink only snack 12-2pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Drink only snack 12-2pm
C11. Had a drink only snack between 12pm - 2pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Drink1416
New in R8. D7. Had a drink only snack between 2pm - 4pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. (from GQV1_D605dDrink GQV3_D605dDrink GQV4_D705dDrink) (raw info of gq_eat_drink1416).
Categorical
D7. Eating pattern - Drink only snack 2-4pm
D7. Eating pattern - Drink only snack 2-4pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Drink only snack 2-4pm
C11. Had a drink only snack between 2pm - 4pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Drink1618
New in R8. D7. Had a drink only snack between 4pm - 6pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. (from GQV1_D606dDrink GQV3_D606dDrink GQV4_D706dDrink) (raw info of gq_eat_drink1618).
Categorical
D7. Eating pattern - Drink only snack 4-6pm
D7. Eating pattern - Drink only snack 4-6pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Drink only snack 4-6pm
C11. Had a drink only snack between 4pm - 6pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Drink1820
New in R8. D7. Had a drink only snack between 6pm - 8pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. (from GQV1_D607dDrink GQV3_D607dDrink GQV4_D707dDrink) (raw info of gq_eat_drink1820).
Categorical
D7. Eating pattern - Drink only snack 6-8pm
D7. Eating pattern - Drink only snack 6-8pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Drink only snack 6-8pm
C11. Had a drink only snack between 6pm - 8pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Drink2022
New in R8. D7. Had a drink only snack between 8pm - 10pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. (from GQV1_D608dDrink GQV3_D608dDrink GQV4_D708dDrink) (raw info of gq_eat_drink2022).
Categorical
D7. Eating pattern - Drink only snack 8-10pm
D7. Eating pattern - Drink only snack 8-10pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Drink only snack 8-10pm
C11. Had a drink only snack between 8pm - 10pm E.g. drinks with some milk or sugar in; not low calorie drinks or water. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Drink2224
New in R8. D7. Had a drink only snack between 10pm - 12am E.g. drinks with some milk or sugar in; not low calorie drinks or water. (from GQV1_D609dDrink GQV3_D609dDrink GQV4_D709dDrink) (raw info of gq_eat_drink2224).
Categorical
D7. Eating pattern - Drink only snack 10pm-12am
D7. Eating pattern - Drink only snack 10pm-12am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Drink only snack 10pm-12am
C11. Had a drink only snack between 10pm - 12am E.g. drinks with some milk or sugar in; not low calorie drinks or water. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Drink2402
New in R8. D7. Had a drink only snack between 12am - 2am E.g. drinks with some milk or sugar in; not low calorie drinks or water. (from GQV1_D610dDrink GQV3_D610dDrink GQV4_D710dDrink) (raw info of gq_eat_drink2402).
Categorical
D7. Eating pattern - Drink only snack 0-2am
D7. Eating pattern - Drink only snack 0-2am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Drink only snack 0-2am
C11. Had a drink only snack between 12am - 2am E.g. drinks with some milk or sugar in; not low calorie drinks or water. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_fish
New in R8. D7. During the course of last year how many times a week did you eat Medium serving of Fish and fish products. (not asked in GQv4) (from GQV1_D7dFish GQV3_D7dFish ) (raw info of gq_eat_fish).
Categorical
D7. Frequency (servings/week) of eating Fish (v1 and v3)
D7. Frequency (servings/week) of eating Fish (v1 and v3): -8=not asked (GQ version difference); -1=left blank
Real
GQ_Eat_fruit
New in R8. D7. During the course of last year how many times a week did you eat Medium serving or 1 fruit of Fruit and fruit products (not including fruit juice). (not asked in GQv4) (from GQV1_D7cFruit GQV3_D7cFruit ) (raw info of gq_eat_fruit).
Categorical
D7. Frequency (servings/week) of eating fruit (v1 and v3)
D7. Frequency (servings/week) of eating fruit (v1 and v3): -8=not asked (GQ version difference); -1=left blank
Real
GQ_Eat_Light0204
New in R8. D7. Had a light meal between 2am - 4am E.g. porridge cereal toast sandwiches soup salad omelette. (from GQV1_D611bLight GQV3_D611bLight GQV4_D711bLight) (raw info of gq_eat_light0204).
Categorical
D7. Eating pattern - Light meal 2-4am
D7. Eating pattern - Light meal 2-4am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Light meal 2-4am
C11. Had a light meal between 2am - 4am E.g. porridge cereal toast sandwiches soup salad omelette. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Light0406
New in R8. D7. Had a light meal between 4am - 6am E.g. porridge cereal toast sandwiches soup salad omelette. (from GQV1_D612bLight GQV3_D612bLight GQV4_D712bLight) (raw info of gq_eat_light0406).
Categorical
D7. Eating pattern - Light meal 4-6am
D7. Eating pattern - Light meal 4-6am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Light meal 4-6am
C11. Had a light meal between 4am - 6am E.g. porridge cereal toast sandwiches soup salad omelette. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Light0608
New in R8. D7. Had a light meal between 6am - 8am E.g. porridge cereal toast sandwiches soup salad omelette. (from GQV1_D601bLight GQV3_D601bLight GQV4_D701bLight) (raw info of gq_eat_light0608).
Categorical
D7. Eating pattern - Light meal 6-8am
D7. Eating pattern - Light meal 6-8am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Light meal 6-8am
C11. Had a light meal between 6am - 8am E.g. porridge cereal toast sandwiches soup salad omelette. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Light0810
New in R8. D7. Had a light meal between 8am - 10am E.g. porridge cereal toast sandwiches soup salad omelette. (from GQV1_D602bLight GQV3_D602bLight GQV4_D702bLight) (raw info of gq_eat_light0810).
Categorical
D7. Eating pattern - Light meal 8-10am
D7. Eating pattern - Light meal 8-10am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Light meal 8-10am
C11. Had a light meal between 8am - 10am E.g. porridge cereal toast sandwiches soup salad omelette. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Light1012
New in R8. D7. Had a light meal between 10am - 12pm E.g. porridge cereal toast sandwiches soup salad omelette. (from GQV1_D603bLight GQV3_D603bLight GQV4_D703bLight) (raw info of gq_eat_light1012).
Categorical
D7. Eating pattern - Light meal 10am-12pm
D7. Eating pattern - Light meal 10am-12pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Light meal 10am-12pm
C11. Had a light meal between 10am - 12pm E.g. porridge cereal toast sandwiches soup salad omelette. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Light1214
New in R8. D7. Had a light meal between 12pm -2pm E.g. porridge cereal toast sandwiches soup salad omelette. (from GQV1_D604bLight GQV3_D604bLight GQV4_D704bLight) (raw info of gq_eat_light1214).
Categorical
D7. Eating pattern - Light meal 12-2pm
D7. Eating pattern - Light meal 12-2pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Light meal 12-2pm
C11. Had a light meal between 12pm -2pm E.g. porridge cereal toast sandwiches soup salad omelette. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Light1416
New in R8. D7. Had a light meal between 2pm - 4pm E.g. porridge cereal toast sandwiches soup salad omelette. (from GQV1_D605bLight GQV3_D605bLight GQV4_D705bLight) (raw info of gq_eat_light1416).
Categorical
D7. Eating pattern - Light meal 2-4pm
D7. Eating pattern - Light meal 2-4pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Light meal 2-4pm
C11. Had a light meal between 2pm - 4pm E.g. porridge cereal toast sandwiches soup salad omelette. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Light1618
New in R8. D7. Had a light meal between 4pm - 6pm E.g. porridge cereal toast sandwiches soup salad omelette. (from GQV1_D606bLight GQV3_D606bLight GQV4_D706bLight) (raw info of gq_eat_light1618).
Categorical
D7. Eating pattern - Light meal 4-6pm
D7. Eating pattern - Light meal 4-6pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Light meal 4-6pm
C11. Had a light meal between 4pm - 6pm E.g. porridge cereal toast sandwiches soup salad omelette. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Light1820
New in R8. D7. Had a light meal between 6pm - 8pm E.g. porridge cereal toast sandwiches soup salad omelette. (from GQV1_D607bLight GQV3_D607bLight GQV4_D707bLight) (raw info of gq_eat_light1820).
Categorical
D7. Eating pattern - Light meal 6-8pm
D7. Eating pattern - Light meal 6-8pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Light meal 6-8pm
C11. Had a light meal between 6pm - 8pm E.g. porridge cereal toast sandwiches soup salad omelette. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Light2022
New in R8. D7. Had a light meal between 8pm - 10pm E.g. porridge cereal toast sandwiches soup salad omelette. (from GQV1_D608bLight GQV3_D608bLight GQV4_D708bLight) (raw info of gq_eat_light2022).
Categorical
D7. Eating pattern - Light meal 8-10pm
D7. Eating pattern - Light meal 8-10pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Light meal 8-10pm
C11. Had a light meal between 8pm - 10pm E.g. porridge cereal toast sandwiches soup salad omelette. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Light2224
New in R8. D7. Had a light meal between 10pm - 12am E.g. porridge cereal toast sandwiches soup salad omelette. (from GQV1_D609bLight GQV3_D609bLight GQV4_D709bLight) (raw info of gq_eat_light2224).
Categorical
D7. Eating pattern - Light meal 10pm-12am
D7. Eating pattern - Light meal 10pm-12am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Light meal 10pm-12am
C11. Had a light meal between 10pm - 12am E.g. porridge cereal toast sandwiches soup salad omelette. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Light2402
New in R8. D7. Had a light meal between 12am - 2am E.g. porridge cereal toast sandwiches soup salad omelette. (from GQV1_D610bLight GQV3_D610bLight GQV4_D710bLight) (raw info of gq_eat_light2402).
Categorical
D7. Eating pattern - Light meal 0-2am
D7. Eating pattern - Light meal 0-2am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Light meal 0-2am
C11. Had a light meal between 12am - 2am E.g. porridge cereal toast sandwiches soup salad omelette. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Main0204
New in R8. D7. Had a main meal between 2am - 4am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. (from GQV1_D611aMain GQV3_D611aMain GQV4_D711aMain) (raw info of gq_eat_main0204).
Categorical
D7. Eating pattern - Main meal 2-4am
D7. Eating pattern - Main meal 2-4am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Main meal 2-4am
C11. Had a main meal between 2am - 4am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Main0406
New in R8. D7. Had a main meal between 4am - 6am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. (from GQV1_D612aMain GQV3_D612aMain GQV4_D712aMain) (raw info of gq_eat_main0406).
Categorical
D7. Eating pattern - Main meal 4-6am
D7. Eating pattern - Main meal 4-6am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Main meal 4-6am
C11. Had a main meal between 4am - 6am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Main0608
New in R8. D7. Had a main meal between 6am - 8am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. (from GQV1_D601aMain GQV3_D601aMain GQV4_D701aMain) (raw info of gq_eat_main0608).
Categorical
D7. Eating pattern - Main meal 6-8am
D7. Eating pattern - Main meal 6-8am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Main meal 6-8am
C11. Had a main meal between 6am - 8am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Main0810
New in R8. D7. Had a main meal between 8am - 10am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. (from GQV1_D602aMain GQV3_D602aMain GQV4_D702aMain) (raw info of gq_eat_main0810).
Categorical
D7. Eating pattern - Main meal 8-10am
D7. Eating pattern - Main meal 8-10am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Main meal 8-10am
C11. Had a main meal between 8am - 10am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Main1012
New in R8. D7. Had a main meal between 10am - 12pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. (from GQV1_D603aMain GQV3_D603aMain GQV4_D703aMain) (raw info of gq_eat_main1012).
Categorical
D7. Eating pattern - Main meal 10am-12pm
D7. Eating pattern - Main meal 10am-12pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Main meal 10am-12pm
C11. Had a main meal between 10am - 12pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Main1214
New in R8. D7. Had a main meal between 12pm - 2pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. (from GQV1_D604aMain GQV3_D604aMain GQV4_D704aMain) (raw info of gq_eat_main1214).
Categorical
D7. Eating pattern - Main meal 12-2pm
D7. Eating pattern - Main meal 12-2pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Main meal 12-2pm
C11. Had a main meal between 12pm - 2pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Main1416
New in R8. D7. Had a main meal between 2pm - 4pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. (from GQV1_D605aMain GQV3_D605aMain GQV4_D705aMain) (raw info of gq_eat_main1416).
Categorical
D7. Eating pattern - Main meal 2-4pm
D7. Eating pattern - Main meal 2-4pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Main meal 2-4pm
C11. Had a main meal between 2pm - 4pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Main1618
New in R8. D7. Had a main meal between 4pm - 6pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. (from GQV1_D606aMain GQV3_D606aMain GQV4_D706aMain) (raw info of gq_eat_main1618).
Categorical
D7. Eating pattern - Main meal 4-6pm
D7. Eating pattern - Main meal 4-6pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Main meal 4-6pm
C11. Had a main meal between 4pm - 6pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Main1820
New in R8. D7. Had a main meal between 6pm - 8pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. (from GQV1_D607aMain GQV3_D607aMain GQV4_D707aMain) (raw info of gq_eat_main1820).
Categorical
D7. Eating pattern - Main meal 6-8pm
D7. Eating pattern - Main meal 6-8pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Main meal 6-8pm
C11. Had a main meal between 6pm - 8pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Main2022
New in R8. D7. Had a main meal between 8pm - 10pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. (from GQV1_D608aMain GQV3_D608aMain GQV4_D708aMain) (raw info of gq_eat_main2022).
Categorical
D7. Eating pattern - Main meal 8-10pm
D7. Eating pattern - Main meal 8-10pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Main meal 8-10pm
C11. Had a main meal between 8pm - 10pm E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Main2224
New in R8. D7. Had a main meal between 10pm - 12am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. (from GQV1_D609aMain GQV3_D609aMain GQV4_D709aMain) (raw info of gq_eat_main2224).
Categorical
D7. Eating pattern - Main meal 10pm-12am
D7. Eating pattern - Main meal 10pm-12am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Main meal 10pm-12am
C11. Had a main meal between 10pm - 12am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Main2402
New in R8. D7. Had a main meal between 12am - 2am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. (from GQV1_D610aMain GQV3_D610aMain GQV4_D710aMain) (raw info of gq_eat_main2402).
Categorical
D7. Eating pattern - Main meal 0-2am
D7. Eating pattern - Main meal 0-2am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Main meal 0-2am
C11. Had a main meal between 12am - 2am E.g. cooked dish meat with potatoes pizza lasagne fish and chips burgers fried breakfast. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_meat
New in R8. D7. During the course of last year how many times a week did you eat Medium serving of Meat meat products and meat dishes (including bacon ham or chicken).(not asked in GQv4) (from GQV1_D7eMeat GQV3_D7eMeat ) (raw info of gq_eat_meat).
Categorical
D7. Frequency (servings/week) of eating Meat (v1 and v3)
D7. Frequency (servings/week) of eating Meat (v1 and v3): -8=not asked (GQ version difference); -1=left blank
Real
GQ_Eat_salads
New in R8. D7. During the course of last year how many times a week did you eat Medium serving of Salads. (not asked in GQv4) (from GQV1_D7bSalad GQV3_D7bSalad ) (raw info of gq_eat_salads).
Categorical
D7. Frequency (servings/week) of eating salads (v1 and v3)
D7. Frequency (servings/week) of eating salads (v1 and v3): -8=not asked (GQ version difference); -7=not applicable/answered but undetermined; -1=left blank
Real
GQ_Eat_Snack0204
New in R8. D7. Had a snack between 2am - 4am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. (from GQV1_D611cSnack GQV3_D611cSnack GQV4_D711cSnack) (raw info of gq_eat_snack0204).
Categorical
D7. Eating pattern - Snack 2-4am
D7. Eating pattern - Snack 2-4am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Snack 2-4am
C11. Had a snack between 2am - 4am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Snack0406
New in R8. D7. Had a snack between 4am - 6am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. (from GQV1_D612cSnack GQV3_D612cSnack GQV4_D712cSnack) (raw info of gq_eat_snack0406).
Categorical
D7. Eating pattern - Snack 4-6am
D7. Eating pattern - Snack 4-6am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Snack 4-6am
C11. Had a snack between 4am - 6am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Snack0608
New in R8. D7. Had a snack between 6am - 8am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. (from GQV1_D601cSnack GQV3_D601cSnack GQV4_D701cSnack) (raw info of gq_eat_snack0608).
Categorical
D7. Eating pattern - Snack 6-8am
D7. Eating pattern - Snack 6-8am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Snack 6-8am
C11. Had a snack between 6am - 8am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Snack0810
New in R8. D7. Had a snack between 8am - 10am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. (from GQV1_D602cSnack GQV3_D602cSnack GQV4_D702cSnack) (raw info of gq_eat_snack0810).
Categorical
D7. Eating pattern - Snack 8-10am
D7. Eating pattern - Snack 8-10am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Snack 8-10am
C11. Had a snack between 8am - 10am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Snack1012
New in R8. D7. Had a snack between 10am - 12pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. (from GQV1_D603cSnack GQV3_D603cSnack GQV4_D703cSnack) (raw info of gq_eat_snack1012).
Categorical
D7. Eating pattern - Snack 10am-12pm
D7. Eating pattern - Snack 10am-12pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Snack 10am-12pm
C11. Had a snack between 10am - 12pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Snack1214
New in R8. D7. Had a snack between 12pm - 2pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. (from GQV1_D604cSnack GQV3_D604cSnack GQV4_D704cSnack) (raw info of gq_eat_snack1214).
Categorical
D7. Eating pattern - Snack 12-2pm
D7. Eating pattern - Snack 12-2pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Snack 12-2pm
C11. Had a snack between 12pm - 2pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Snack1416
New in R8. D7. Had a snack between 2pm - 4pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. (from GQV1_D605cSnack GQV3_D605cSnack GQV4_D705cSnack) (raw info of gq_eat_snack1416).
Categorical
D7. Eating pattern - Snack 2-4pm
D7. Eating pattern - Snack 2-4pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Snack 2-4pm
C11. Had a snack between 2pm - 4pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Snack1618
New in R8. D7. Had a snack between 4pm - 6pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. (from GQV1_D606cSnack GQV3_D606cSnack GQV4_D706cSnack) (raw info of gq_eat_snack1618).
Categorical
D7. Eating pattern - Snack 4-6pm
D7. Eating pattern - Snack 4-6pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Snack 4-6pm
C11. Had a snack between 4pm - 6pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Snack1820
New in R8. D7. Had a snack between 6pm - 8pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. (from GQV1_D607cSnack GQV3_D607cSnack GQV4_D707cSnack) (raw info of gq_eat_snack1820).
Categorical
D7. Eating pattern - Snack 6-8pm
D7. Eating pattern - Snack 6-8pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Snack 6-8pm
C11. Had a snack between 6pm - 8pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Snack2022
New in R8. D7. Had a snack between 8pm - 10pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. (from GQV1_D608cSnack GQV3_D608cSnack GQV4_D708cSnack) (raw info of gq_eat_snack2022).
Categorical
D7. Eating pattern - Snack 8-10pm
D7. Eating pattern - Snack 8-10pm: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Snack 8-10pm
C11. Had a snack between 8pm - 10pm E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Snack2224
New in R8. D7. Had a snack between 10pm - 12am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. (from GQV1_D609cSnack GQV3_D609cSnack GQV4_D709cSnack) (raw info of gq_eat_snack2224).
Categorical
D7. Eating pattern - Snack 10pm-12am
D7. Eating pattern - Snack 10pm-12am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Snack 10pm-12am
C11. Had a snack between 10pm - 12am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_Snack2402
New in R8. D7. Had a snack between 12am - 2am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. (from GQV1_D610cSnack GQV3_D610cSnack GQV4_D710cSnack) (raw info of gq_eat_snack2402).
Categorical
D7. Eating pattern - Snack 0-2am
D7. Eating pattern - Snack 0-2am: 2=ticked; -1=left blank
Categorical
C11. Eating pattern - Snack 0-2am
C11. Had a snack between 12am - 2am E.g. biscuit cake fruit sweets chocolate crisps nuts ice cream. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Eat_veg
New in R8. D7. During the course of last year how many times a week did you eat Medium serving of Vegetables (not including potatoes). (not asked in GQv4) (from GQV1_D7aVeg GQV3_D7aVeg ) (raw info of gq_eat_veg).
Categorical
D7. Frequency (servings/week) of eating Vegetables (v1 and v3)
D7. Frequency (servings/week) of eating Vegetables (v1 and v3): -8=not asked (GQ version difference); -7=not applicable/answered but undetermined; -1=left blank
Real
GQ_Edu_age
New in R8. C7. At what age did you finish full time education (in years)? (Years of age) (from GQV1_DMC42aAgeEndFTE GQV3_C7AgeEndFTE GQV4_C7AgeEndFTE) (raw info of gq_edu_age) -10=text info;
Real
C7. Age finished full time education
C7. Age finished full time education: -7=not applicable/answered but undetermined; -5=Current or not finished; -1=left blank
Time
B7. Age finished full time education
B7. At what age did you finish full time education (in years)? (Years of age) - derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-5=Current or not finished;-1=left blank
Real
GQ_Edu_Alev
New in R8. C6. Do you have any of the following qualifications? (tick all applicable). GCE A Level AS level Highers (from GQV1_DMc4eALevels GQV3_C6eALevels GQV4_C6eALevels) (raw info of gq_edu_alev).
Categorical
C6. A level qualification
C6. A level qualification: 2=ticked; -1=left blank
Categorical
B6. A level qualification
B6. Do you have any of the following qualifications? (tick all applicable). GCE A Level AS level Highers derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Edu_apprentice
New in R8. C6. Do you have any of the following qualifications? (tick all applicable). Completed Apprenticeship. (from GQV1_DMC4hApprenticeship GQV3_C6hApprenticeship GQV4_C6hApprenticeship) (raw info of gq_edu_apprentice).
Categorical
C6. Completed apprenticeship
C6. Completed apprenticeship: 2=ticked; -1=left blank
Categorical
B6. Completed apprenticeship
B6. Do you have any of the following qualifications? (tick all applicable). Completed Apprenticeship. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Edu_CSE
New in R8. C6. Do you have any of the following qualifications? (tick all applicable). CSE. (from GQV1_DMC4bCSE GQV3_C6bCSE GQV4_C6bCSE) (raw info of gq_edu_cse).
Categorical
C6. CSE qualification
C6. CSE qualification: 2=ticked; -1=left blank
Categorical
B6. CSE qualification
B6. Do you have any of the following qualifications? (tick all applicable). CSE. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Edu_degree
New in R8. C6. Do you have any of the following qualifications? (tick all applicable). University Degree. (from GQV1_DMC4kDegree GQV3_C6kDegree GQV4_C6kDegree) (raw info of gq_edu_degree).
Categorical
C6. University degree qualification
C6. University degree qualification: 2=ticked; -1=left blank
Categorical
B6. University degree qualification
B6. Do you have any of the following qualifications? (tick all applicable). University Degree. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Edu_GCSE
New in R8. C6. Do you have any of the following qualifications? (tick all applicable). GCE O level or GCSE. (from GQV1_DMC4cGCSE GQV3_C6cGCSE GQV4_C6cGCSE) (raw info of gq_edu_gcse).
Categorical
C6. O level or GCSE qualification
C6. O level or GCSE qualification: 2=ticked; -1=left blank
Categorical
B6. O level or GCSE qualification
B6. Do you have any of the following qualifications? (tick all applicable). GCE O level or GCSE. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Edu_HNC
New in R8. C6. Do you have any of the following qualifications? (tick all applicable). Teaching Diploma HNC NVQ. (from GQV1_DMC4jHMC GQV3_C6jHNC GQV4_C6jHNC) (raw info of gq_edu_hnc).
Categorical
C6. HNC or NVQ qualification
C6. HNC or NVQ qualification: 2=ticked; -1=left blank
Categorical
B6. HNC or NVQ qualification
B6. Do you have any of the following qualifications? (tick all applicable). Teaching Diploma HNC NVQ. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Edu_HND_NVQ
New in R8. C6. Do you have any of the following qualifications? (tick all applicable). HND or GNVQ. (from GQV1_DMC4gHND_GNVQ GQV3_C6gHND_NVQ GQV4_C6gHND_NVQ) (raw info of gq_edu_hnd_nvq).
Categorical
C6. HND or GNVQ qualification
C6. HND or GNVQ qualification: 2=ticked; -1=left blank
Categorical
B6. HND or GNVQ qualification
B6. Do you have any of the following qualifications? (tick all applicable). HND or GNVQ. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Edu_matricul
New in R8. C6. Do you have any of the following qualifications? (tick all applicable). Matriculation. (from GQV1_DMC4dMatriculation GQV3_C6dMatriculation GQV4_C6dMatriculation) (raw info of gq_edu_matricul).
Categorical
C6. Matriculation qualification
C6. Matriculation qualification: 2=ticked; -1=left blank
Categorical
B6. Matriculation qualification
B6. Do you have any of the following qualifications? (tick all applicable). Matriculation. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Edu_none
New in R8. C6. Do you have any of the following qualifications? (tick all applicable). None. (from GQV1_DMC4nNone GQV3_C6nNone GQV4_C6nNone) (raw info of gq_edu_none).
Categorical
C6. No Qualifications
C6. No Qualifications: 2=ticked; -1=left blank
Categorical
GQ_Edu_others
New in R8. C6. Do you have any of the following qualifications? (tick all applicable). Other please describe. TEXT
Text
C6. Other qualifications
C6. Other qualifications: 2=GCE A level AS level or highers; 3=Secretarial coll exams; 4=CSE; 5=Technical coll exams city and guilds; 6=Teaching diploma HNC NVQ; 7=GCE O level or GCSE; 8=HND GNVQ; 9=University Degree; 12=Trade certificates; -7=not applicable/answered but undetermined; -5=unclear qualification (eg qual outside the UK); -3=>1 qualification written in text description; -1=left blank
Categorical
B6. Other qualifications
B6. Do you have any of the following qualifications? (tick all applicable). Other please describe. TEXT derived from GQ_V3.0_24/04: 2=GCE A level AS level or highers;3=Secretarial coll exams;4=CSE;5=Technical coll exams city and guilds;6=Teaching diploma HNC NVQ;7=GCE O level or GCSE;8=HND GNVQ;9=University Degree;12=Trade certificates;-7=not applicable/answered but undetermined;-5=unclear qualification (eg qual outside the UK);-3=>1 qualification written in text description;-1=left blank
Categorical
GQ_Edu_qual
New in R8. C2. What training or qualifications are (were) needed for your job ? (only asked in GQv1 25/11/2004 and 26/01/2005) TEXT
Text
GQ_Edu_secret
New in R8. C6. Do you have any of the following qualifications? (tick all applicable). Secretarial College Exams. (from GQV1_DMC4iSecretarial GQV3_C6iSecretarial GQV4_C6iSecretarial) (raw info of gq_edu_secret).
Categorical
C6. Secretarial College qualification
C6. Secretarial College qualification: 2=ticked; -1=left blank
Categorical
B6. Secretarial College qualification
B6. Do you have any of the following qualifications? (tick all applicable). Secretarial College Exams. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Edu_SLC
New in R8. C6. Do you have any of the following qualifications? (tick all applicable). School Leaving certificate. (from GQV1_DMC4aSLC GQV3_C6aSLC GQV4_C6aSLC) (raw info of gq_edu_slc).
Categorical
C6. School Leaving Certificate
C6. School Leaving Certificate: 2=ticked; -1=left blank
Categorical
B6. School Leaving Certificate
B6. Do you have any of the following qualifications? (tick all applicable). School Leaving certificate. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Edu_TechCG
New in R8. C6. Do you have any of the following qualifications? (tick all applicable). Technical College exams City & Guilds. (from GQV1_DMC4fC_G GQV3_C6fC_G GQV4_C6fC_G) (raw info of gq_edu_techcg).
Categorical
C6. Technical or C&G qualification
C6. Technical or C&G qualification: 2=ticked; -1=left blank
Categorical
B6. Technical or C&G qualification
B6. Do you have any of the following qualifications? (tick all applicable). Technical College exams City & Guilds. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Edu_trade
New in R8. C6. Do you have any of the following qualifications? (tick all applicable). Trade Certificates.(from GQV1_DMC4lTradeCertificate GQV3_C6lTradeCertificate GQV4_C6lTradeCertificate) (raw info of gq_edu_trade).
Categorical
C6. Trade certificate qualification
C6. Trade certificate qualification: 2=ticked; -1=left blank
Categorical
B6. Trade certificate qualification
B6. Do you have any of the following qualifications? (tick all applicable). Trade Certificates. derived from GQ_V3.0_24/04: 2=ticked;-1=left blank
Categorical
GQ_Emp_n
New in R8. C3. Number of employees. How many people work (worked) for your employer? For self-employed: how many people you employ(ed)? (see GQ_emp_n_supervise for GQv1). (from GQV3_C3NumberPeopleEmployed GQV4_C3NumberPeopleEmployed) (raw info of gq_emp_n).
Categorical
C3. Number of people employed
C3. Number of people employed: 1=1 to 24 people; 2=>25; -7=not applicable/answered but undetermined; -1=left blank
Categorical
B3. Number of people employed
B3. Number of employees. How many people work (worked) for your employer? For self-employed: how many people you employ(ed)? derived from GQ_V3.0_24/04: 1=1 to 24 people;2=>25;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_Emp_n_supervise
New in R8. C2. Number of employees. How many people work (worked) at the place where you work (worked)? For self-employed how many people you employ(ed)? (asked in GQv3 and GQv4 differently). Derived from GQV1_DMC2fNumerEmployees with cleaning/harmonisation (see GQ_Emp_n_supervise);
Categorical
C2. Number of people employed (if employers-v1 only)
C2. Number of people employed (if employers- v1 only): 1=1 to 24 people; 2=>25; -8=not asked (GQ version difference); -1=left blank
Categorical
GQ_Emp_occup
New in R8. C5. Occupation type: Current/last job. (not asked in GQv1) 8 categ. (from GQV3_C5Occupation GQV4_C5Occupation) (raw info of gq_emp_occup).
Categorical
C5. Occupation type
C5. Occupation type: 1=Mod prof job; 2=Clerical; 3=Senior manage; 4=Tech; 5=Semi-routine; 6=Routine; 7=Mid manage; 8=Traditional prof; -8=not asked (GQ version difference); -7=not applicable/answered but undetermined; -1=left blank
Categorical
B5. Occupation type
B5. Occupation type: Current/last job. 8 categ. 1 Mod prof job 2 Clerical 3 Senior manage 4 tech 5 Semi-routine 6 Routine 7 Mid manage 8 Traditional prof derived from GQ_V3.0_24/04: 1=Mod prof job;2=Clerical;3=Senior manage;4=Tech;5=Semi-routine;6=Routine;7=Mid manage;8=Traditional prof;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_Emp_partner
New in R8. C6. Is (was) he working as an employee or self-employed. (only asked in GQv1 25/11/2004 and 26/01/2005). (from GQV1_DMC6bPartnersEmployeeStatus ) (raw info of gq_emp_partner).
Categorical
C6. Partners employment status (v1 only)
C6. Partners employment status (v1 only): 1=as an employee; 2=as self-employed; -8=not asked (GQ version difference); -1=left blank
Categorical
GQ_Emp_supervise
New in R8. C4. Present or your last job: Supervisory status: Do (did) you supervise any other employees. (from GQV1_DMC2eSupervisoryStatus GQV3_C4SupervisoryStatus GQV4_C4SupervisoryStatus) (raw info of gq_emp_supervise).
Categorical
C4. Supervisory status without numbers
C4. Supervisory status without numbers: 2=Yes; 3=No; -1=left blank
Categorical
B4. Supervisory status without numbers
B4. Present or your last job: Supervisory status: Do (did) you supervise any other employees. derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
GQ_Emp_type
New in R8. C2. Do (did) you work as an employee or are (were) you self-employed? (GQv1 answer means slightly different things) (from GQV1_DMC2dEmployeeType GQV3_C2EmployeeType GQV4_C2EmployeeType) (raw info of gq_emp_type).
Categorical
C2. Employment type with employee data
C2. Employment type with employee data: 1=Employee; 2=Self employed w employees; 3=Self employed w/o employees; -7=not applicable/answered but undetermined; -1=left blank
Categorical
B2. Employment type with employee data
B2. Do (did) you work as an employee or are (were) you self-employed? derived from GQ_V3.0_24/04: 1=Employee;2=Self employed w employees;3=Self employed w/o employees;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_eth
New in R8. F1. Ethnicity. (not asked in GQv1) (2001 Census class.) (from GQV3_F1Ethnicity GQV4_F1Ethnicity) (raw info of gq_eth).
Categorical
F1. Ethnicity - 5 categories
F1. Ethnicity - 5 categories: 1=White; 2=South Asia; 3=Blacks; 4=East Asia; 5=Others; -8=not asked (GQ version difference); -1=left blank
Categorical
F1. Ethnicity - 17 categories
F1. Ethnicity - 17 categories: 1=British; 2=Irish; 3=other white; 4=Wh&Blk Carib; 5=Wh&Blk African; 6=Wh&Asian; 7=mixed; 8=India; 9=Pakistani; 10=Bangladeshi; 11=Any Asian; 12=Carib; 13=Afican; 14=any black; 15=Chinese; 16=any others; 17=not stated; -8=not asked (GQ version difference); -1=left blank
Categorical
A9b. Age of facial hair
A9b. If known at what age did you grow facial hair? derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined
Real
A9b. Age of facial hair unknown
A9b. If known; at what age did you grow facial hair? Don't know. derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined 1=don’t know
Categorical
A9a. When facial hair.
A9a. When did you start to grow facial hair? derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_FeelFaint
New in R8. A5. Do you often feel faint or have spells of severe dizziness? (from GQV1_A5gFeelFaint GQV3_A5gFeelFaint GQV4_A5gFeelFaint) (raw info of gq_feelfaint).
Categorical
A5. Feel faint or dizzy
A5. Feel faint or dizzy: 2=Yes; 3=No; -1=left blank
Categorical
A3. Feel faint or dizzy
A3. Do you often feel faint or have spells of severe dizziness? derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
A5. Dr reported heart trouble
A5. Dr reported heart trouble: -7=not applicable/answered but undetermined; -1=left blank
Categorical
A3. Dr reported heart trouble
A3. Has your doctor ever told you that you have heart trouble? derived from GQ_V3.0_24/04: 2=Yes;3=No;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_Homecooked
New in R8. D2. When eating your main meal at home how often do you usually eat Home cooked meals. (from GQV1_D2cEatHomeCookedMeals GQV3_D2cEatHomeCookedMeals GQV4_D2cEatHomeCookedMeals) (raw info of gq_homecooked).
Categorical
D2. How often eat home cooked meals
D2. How often eat home cooked meals: 1=never or rarely; 2=1-2 times/wk; 3=3-5 times/wk; 4=>5 times/wk; -1=left blank
Categorical
C5. How often eat home cooked meals
C5. When eating your main meal at home how often do you usually eat Home cooked meals. derived from GQ_V3.0_24/04: 1=never or rarely;2=1-2 times/wk;3=3-5 times/wk;4=>5 times/wk;-1=left blank
Categorical
GQ_Htn_dr
New in R8. A5. Has a doctor ever told you that your blood pressure was too high? (from GQV1_A5hDrReportBPHigh GQV3_A5hDrReportBPHigh GQV4_A5hDrReportBPHigh) (raw info of gq_htn_dr).
Categorical
A5. Dr reported high blood pressure
A5. Dr reported high blood pressure: 2=Yes; 3=No; -1=left blank
Categorical
A3. Dr reported high blood pressure
A3. Has a doctor ever told you that your blood pressure was too high? derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
GQ_Htn_trt
New in R8. A5. If you have been told that your blood pressure was too high are you now on treatment? (from GQV1_A5iTreatmentHighBP GQV3_A5iTreatmentHighBP GQV4_A5iTreatmentHighBP) (raw info of gq_htn_trt).
Categorical
A5. Treatment for high blood pressure
A5. Treatment for high blood pressure: 2=Yes; 3=No; -7=not applicable/answered but undetermined; -1=left blank
Categorical
A3. Treatment for high blood pressure
A3. If you have been told that your blood pressure was too high are you now on treatment? derived from GQ_V3.0_24/04: 2=Yes;3=No;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_Income
New in R8. C8. What is your total combined household income? In pounds sterling (from GQV1_DMC3HouseholdIncome GQV3_C8HouseholdIncome GQV4_C8HouseholdIncome) (raw info of gq_income).
Categorical
C8. Household income
C8. Household income: 1=<20000; 2=20000-40000; 3=>=40000; -7=not applicable/answered but undetermined; -1=left blank
Categorical
B8. Household income
B8. What is your total combined household income? derived from GQ_V3.0_24/04: 1=<20000;2=20000-40000;3=>=40000;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_Job_full
New in R8. C1. What is your current work status? In work full time i.e. more than 30 hours per week. (from GQV1_DMC1aFullTime GQV3_C1aFullTime GQV4_C1aFullTime) (raw info of gq_job_full).
Categorical
C1. Job status - full time >30 h/wk
C1. Job status - full time >30 h/wk: 2=Yes; 3=No; -1=left blank
Categorical
B1. Job status - full time >30 h/wk
B1. What is your current work status? In work full time i.e. more than 30 hours per week. derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_Job_house
New in R8. C1. What is your current work status? Keeping house. (from GQV1_DMC1cKeepingHouse GQV3_C1cKeepingHouse GQV4_C1cKeepingHouse) (raw info of gq_job_house).
Categorical
C1. Job status - house-keeping
C1. Job status - house-keeping : 2=Yes; 3=No; -1=left blank
Categorical
B1. Job status - house-keeping
B1. What is your current work status? Keeping house. derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
GQ_Job_newjob
New in R8. C1. What is your current work status? Waiting to start a new job already obtained. (from GQV1_DMC1eObtainedNewJob GQV3_C1eObtainedNewJob GQV4_C1eObtainedNewJob) (raw info of gq_job_newjob).
Categorical
C1. Job status - obtained new job
C1. Job status - obtained new job: 2=Yes; 3=No; -1=left blank
Categorical
B1. Job status - obtained new job
B1. What is your current work status? Waiting to start a new job already obtained. derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_Job_oth
New in R8. C1. What is your current work status? If other please specify. TEXT
Text
C1. Job status others assigned integers 1 to 8 for classification
C1. Job status others assigned integers 1 to 8 for classification: 1=full time >30 h/wk; 2=part time <30 h/wk; 3=house-keeping; 4=retired; 6=unemployed; 7=temporarily sick; 8=permanently sick; -7=not applicable/answered but undetermined; -5=volunteer / unclassified; -3=student (unemployed) or studying while working
Categorical
B1. Job status others assigned integers 1 to 8 for classification
B1. What is your current work status? If other please specify. TEXT derived from GQ_V3.0_24/04: 1=full time >30 h/wk;2=part time <30 h/wk;3=house-keeping;4=retired;6=unemployed;7=temporarily sick;8=permanently sick;-7=not applicable/answered but undetermined;-5=volunteer / unclassified;-3=student (unemployed) or studying while working
Categorical
GQ_Job_part
New in R8. C1. What is your current work status? Part time work i.e. less than 30 hours per week. (from GQV1_DMC1bPartTime GQV3_C1bPartTime GQV4_C1bPartTime) (raw info of gq_job_part).
Categorical
GQ_Job_partner
New in R8. C6. Only for women who currently live with their partner. Please could you give us some details about your husband/partner's present or last job. (asked only in GQv1) TEXT -8=not assessed (version difference) (from GQV1_DMC6aPartnersJobDetails )
Text
GQ_Job_partnermanage
New in R8. C6. Does (did) he supervise or have management responsibility for the work of other people? (only in GQv1 25/11/2004 and 26/01/2005). (from GQV1_DMC6cPartnersManagementStatus ) (raw info of gq_job_partnermanage).
Categorical
C6. Partners management status (v1 only)
C6. Partners management status (v1 only): 1=No; 2=Yes 1 to 24 people; 3=Yes 25 or more people; -8=not asked (GQ version difference); -7=not applicable/answered but undetermined; -1=left blank
Categorical
C1. Job status - part time <30 h/wk
C1. Job status - part time <30 h/wk: 2=Yes; 3=No; -1=left blank
Categorical
B1. Job status - part time <30 h/wk
B1. What is your current work status? Part time work i.e. less than 30 hours per week. derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_Job_retired
New in R8. C1. What is your current work status? Wholly retired from work (from GQV1_DMC1dRetired GQV3_C1dRetired GQV4_C1dRetired) (raw info of gq_job_retired).
Categorical
C1. Job status - retired
C1. Job status - retired : 2=Yes; 3=No; -1=left blank
Categorical
B1. Job status - retired
B1. What is your current work status? Wholly retired from work. derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_Job_sick
New in R8. C1. What is your current work status? Permanently sick or disabled. (from GQV1_DMC1hPermSick GQV3_C1hPermSick GQV4_C1hPermSick) (raw info of gq_job_sick).
Categorical
C1. Job status - permanently sick
C1. Job status - permanently sick: 2=Yes; 3=No; -1=left blank
Categorical
B1. Job status - permanently sick
B1. What is your current work status? Permanently sick or disabled. derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
GQ_Job_tempsick
New in R8. C1. What is your current work status? Out of work as temporarily sick. (from GQV1_DMC1gTempSick GQV3_C1gTempSick GQV4_C1gTempSick) (raw info of gq_job_tempsick).
Categorical
C1. Job status - temporarily sick
C1. Job status - temporarily sick: 2=Yes; 3=No; -1=left blank
Categorical
B1. Job status - temporarily sick
B1. What is your current work status? Out of work as temporarily sick. derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_Job_title
New in R8. C2. Please could you give us some details about your present or last job. What is (was) the title of your job ? (only asked in GQv1 25/11/2004 and 26/01/2005) TEXT
Text
GQ_Job_type
New in R8. C2. What kind of work do (did) you do in your job ? (only asked in GQv1 25/11/2004 and 26/01/2005) TEXT
Text
GQ_Job_unempl
New in R8. C1. What is your current work status? Unemployed and looking for work. (from GQV1_DMC1fUnemployed GQV3_C1fUnemployed GQV4_C1fUnemployed) (raw info of gq_job_unempl).
Categorical
C1. Job status - unemployed
C1. Job status - unemployed : 2=Yes; 3=No; -1=left blank
Categorical
B1. Job status - unemployed
B1. What is your current work status? Unemployed and looking for work. derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_Marit
New in R8. C12. What is your marital status? (Not asked in GQv1 and some GQv3 Mar2006 and May2006 versions) (from GQV3_C12MaritalStatus GQV4_C12MaritalStatus) (raw info of gq_marit).
Categorical
C12. Marital status (not in v1 and some in v3)
C12. Marital status (not in v1 and some in v3): 1=Single; 2=Married or living as married; 3=widowed; 4=Separated; 5=Divorced; -8=not asked (GQ version difference); -1=left blank
Categorical
B13. Marital status (not in v1 and some in v3)
B12. What is your marital status? (Not asked in GQv1 and some GQv3 Mar2006 and May2006 versions) derived from GQ_V3.0_24/04: 1=Single;2=Married or living as married;3=widowed;4=Separated;5=Divorced;-1=left blank;7=not applicable/answered but undetermined
Categorical
GQ_Meds
New in R8. A1. Are you taking any tablets or medicines at the moment? (from GQV1_A1OnMedication GQV3_A1OnMedication GQV4_A1OnMedication) (raw info of gq_meds).
Categorical
A1. On medication
A1. On medication: 2=Yes; 3=No; -1=left blank
Categorical
A1. On medication
A1. Are you taking any tablets or medicines at the moment? derived from GQ_V3.0_24/04: 2=Yes; 3=No;-1=left blank
Categorical
GQ_Med_a
New in R8. A2a. Current Medication Name of drug a.
Text
A2. ACE inhibitor
A2. ACE inhibitor: 2=yes self-reported; -1=left blank
Categorical
A2. ACE inhibitor
A2. Current self-reported meds - ACE inhibitor (eg perindopril enalapril lisinipril ramipril) derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
A2. Any self-reported medications
A2. Any self-reported medications: 2=yes self-reported; -1=left blank
Categorical
A2. Any self-reported medications
A2. Current self-reported meds - Any self-reported meds including unclassified meds: 1) weight loss drugs (orlistat/xenital) 2) drugs for smoking cessation / alcoholism / nasal discomfort / non-specific migraine 3) device for contraception 4) tamoxifen zoledex anastrozole exemestane or other anti-cancer drugs 5) related to specific organs (eg thyroid prostate bladder lung eye bone skin joint) unless noted on pain killers or autoimmune diseases. derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
A2. Angiotensin receptor blocker
A2. Angiotensin receptor blocker: 2=yes self-reported; -1=left blank
Categorical
A2. Angiotensin receptor blocker
A2. Current self-reported meds - Angio II receptor blocker (eg losartan olmesartan telmisartan valsartan) derived from GQ_V3.0_24/04: 2=yes self-reported;1=left blank
Categorical
A2. Aspirin
A2. Aspirin: 2=yes self-reported; -3=yes for pain/non-cardiac purpose; -1=left blank
Categorical
A2. Aspirin
A2. Current self-reported meds - Aspirin derived from GQ_V3.0_24/04: 2=yes self-reported;-3=yes for pain/non-cardiac purpose;-1=left blank
Categorical
A2. Drugs for autoimmune diseases
A2. Drugs for autoimmune diseases: 2=yes self-reported; -1=left blank
Categorical
A2. Drugs for autoimmune diseases
A2. Current self-reported meds - Drugs for an autoimmune disease (eg carbimazole azathioprine dovobet fludrocortisone hydroxychloroquine methotrexate sulfasalazine) including: 1) gastro-intestinal conditions with a reason for Colitis or Coeliac disease 2) rheumatoid arthritis / psoriasis / systemic lupus erythematosus 3) multiple sclerosis 4) Addisons or Graves or Hashimotos diseases -- not including non-specific arthritis osteoarthritis asthma gout irritable-bowel syndrome and other immunological diseases without autoimmunity derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
GQ_Med_b
New in R8. A2b. Current Medication Name of drug b.
Text
A2. Beta blocker
A2. Beta blocker: 2=yes self-reported; -5=yes for psychiatric symptoms rather than migraine; -3=yes for migraine; -1=left blank
Categorical
A2. Beta blocker
A2. Current self-reported meds - Beta blocker (eg atenolol bisoprolol carvediol levobunolol emtoprolol sotalol propranolol) not including beta-blokers used as an eye drop derived from GQ_V3.0_24/04: 2=yes self-reported;5=yes for psychiatric symptoms rather than migraine;-3=yes for migraine;-1=left blank
Categorical
GQ_Med_bnf_a
New in R8. A2a. Current Medication BNF Code for drug a added by research team.
Text
GQ_Med_bnf_b
New in R8. A2b. Current Medication BNF Code for drug b added by research team. (from GQV1_A2bCurrentMedicationBNFCode GQV3_A2bCurrentMedicationBNFCode GQV4_A2bCurrentMedicationBNFCode).
Text
GQ_Med_bnf_c
New in R8. A2c. Current Medication BNF Code for drug c added by research team.
Text
GQ_Med_bnf_d
New in R8. A2d. Current Medication BNF Code for drug d added by research team.
Text
GQ_Med_bnf_e
New in R8. A2e. Current Medication BNF Code for drug e added by research team.
Text
GQ_Med_bnf_f
New in R8. A2f. Current Medication BNF Code for drug f added by research team.
Text
GQ_Med_bnf_g
New in R8. A2g. Current Medication BNF Code for drug g added by research team.
Text
GQ_Med_bnf_h
New in R8. A2h. Current Medication BNF Code for drug h added by research team.
Text
A2. Drugs for irritable bowel syndrome or constipation or others
A2. Drugs for irritable bowel syndrome or constipation or others: 2=yes self-reported; -1=left blank
Categorical
A2. Drugs for irritable bowel syndrome or constipation or others
A2. Current self-reported meds - Drugs related to bowel conditions (alverine azathioprine buscopan lactulose lansoprazole mebeverine senna) including laxatives or IBS or others: marked if use of drugs for gastro-intestinal conditions indicated IBS Colitis Coeliac disease or Crohns disease derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
GQ_Med_c
New in R8. A2c. Current Medication Name of drug c. (from GQV1_A2cCurrentMedicationName GQV3_A2cCurrentMedicationName GQV4_A2cCurrentMedicationName).
Text
A2. Any cardiovascular drugs except blood-clotting drug such as tranexamte
A2. Any cardiovascular drugs except blood-clotting drug such as tranexamte: 2=yes self-reported; -5=yes indicated for non-cardiac use (eg beta-blockers for migraine); -1=left blank
Categorical
A2. Any cardiovascular drugs except blood-clotting drug such as tranexamte
A2. Current self-reported meds - Any cardiovascular drugs except blood-clotting drug (eg tranexamic acid) for menstrual blood loss. Broad categories are lipid-lowering drugs / ace inhibitors / ARB / beta blockers / diuretics / nitrates / Ca channele blockers / anticoagulants derived from GQ_V3.0_24/04: 2=yes self-reported;-5=yes indicated for non-cardiac use (eg beta-blockers for migraine);-1=left blank
Categorical
A2. Drugs acting on the central nervous system
A2. Drugs acting on the central nervous system: 2=yes self-reported; -1=left blank
Categorical
A2. Drugs acting on the central nervous system
A2. Current self-reported meds - Any drugs acting on a central nervous system including 1) pain killers 2) psychiatric disorders 3) acid reflax derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
GQ_Med_d
New in R8. A2d. Current Medication Name of drug d.
Text
A2. Anti-depressant for depression mood anxiety or stress
A2. Anti-depressant for depression mood anxiety or stress: 2=yes self-reported; -1=left blank
Categorical
A2. Anti-depressant for depression mood anxiety or stress
A2. Current self-reported meds - Anti-depressant coded for depression anxiety stress panic attack (eg citalopram dosulepin duloxetine escitalopram fluoxetine mirtazapine paroxetine prozac seroxat quetiapine sertraline venlafaxine zopiclone) derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
A2. Diuretics
A2. Diuretics: 2=yes self-reported; -1=left blank
Categorical
A2. Diuretics
A2. Current self-reported meds - Diuretics (eg frusemide hydrochlorothiazide indapamide spironolactone zestoretic) including diuretic drugs used for water retention - not including ones used as eye drop derived from GQ_V3.0_24/04: 2=yes self-reported -1=left blank
Categorical
A2. Anti-diabetic medications (metformin) for polycystic ovary syndrome
A2. Anti-diabetic medications (metformin) for polycystic ovary syndrome: 2=yes self-reported; -1=left blank
Categorical
A2. Anti-diabetic medications (metformin) for polycystic ovary syndrome
A2. Current self-reported meds - Anti-diabetic meds (metformin) - all for polycystic ovary syndrome - participants should be free from diabetes at baseline. derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
GQ_Med_dose_a
New in R8. A2a. Current Medication Dose of drug a.
Text
GQ_Med_dose_b
New in R8. A2b. Current Medication Dose of drug b.
Text
GQ_Med_dose_c
New in R8. A2c. Current Medication Dose of drug c.
Text
GQ_Med_dose_d
New in R8. A2d. Current Medication Dose of drug d.
Text
GQ_Med_dose_e
New in R8. A2e. Current Medication Dose of drug e.
Text
GQ_Med_dose_f
New in R8. A2f. Current Medication Dose of drug f.
Text
GQ_Med_dose_g
New in R8. A2g. Current Medication Dose of drug g.
Text
GQ_Med_dose_h
New in R8. A2h. Current Medication Dose of drug h.
Text
GQ_Med_e
New in R8. A2e. Current Medication Name of drug e.
Text
GQ_Med_f
New in R8. A2f. Current Medication Name of drug f.
Text
GQ_Med_g
New in R8. A2g. Current Medication Name of drug g.
Text
A2. Drugs for gastric conditions
A2. Drugs for gastric conditions: 2=yes self-reported; -1=left blank
Categorical
A2. Drugs for gastric conditions
A2. Current self-reported meds - Drugs for gastric conditions (eg gaviscon lansoprazole omeprazole ranitidine) including acid reflux a heartburn symptom or others caused by a gastrointestinal side-effect of other drugs derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
GQ_Med_h
New in R8. A2h. Current Medication Name of drug h.
Text
A2. Herbal supplements including non-herbal ones (eg ginko)
A2. Herbal supplements including non-herbal ones (eg ginko): 2=yes self-reported; -1=left blank
Categorical
A2. Herbal supplements including non-herbal ones (eg ginko)
A2. Current self-reported meds - Herbal supplements including plant oils for menopausal symptoms or other specific conditions (eg black cohosh primrose oil St Johns wort) - also including non-herbal plant-origin supplements (ginko garlic and others). derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
A2. Exogenous hormone including testosterone - not for endometriosis
A2. Exogenous hormone including testosterone - not for endometriosis: 2=yes self-reported; 3=no self-reported; -1=left blank
Categorical
A2. Exogenous hormone including testosterone - not for endometriosis
A2. Current self-reported meds - Exogenous hormone use (GQV1_A3HRT accounted for) (eg estradiol elleste climesse climagest sandrena premarine premique progynova tibolone vagefem provera testosterone) 1) including testosteron use among men 2) not including non-hormonal agents for menopausal conditions (drugs for osteoporosis / psychiatric drugs / St Johns Wort / primrose oil / black cohosh) 3) not including exogenous hormone use for endometriosis or for excess menstual blood loss 4) including HRT requiring transdermal dosage derived from GQ_V3.0_24/04: 2=yes self-reported;3=no self-reported;-1=left blank
Categorical
GQ_Med_hrt_v1
New in R8. A3. For women only. Are you on Hormone replacement therapy? Only asked in GQv1 (25/11/2004 and 26/01/2005). (from GQV1_A3HRT ) (raw info of gq_med_hrt_v1).
Categorical
A2. Drugs against infection
A2. Drugs against infection: 2=yes self-reported; -1=left blank
Categorical
A2. Drugs against infection
A2. Current self-reported meds - Drugs (eg flucoxacillin lymecycline aciclovir metronidazole amoxicillin ) against 1) fungal infection including terbinafine 2) topical abnormality with use of lymecycline / minocycline / ocytetracycline 3) urinary tract infection 4) HIV derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
A2. Drugs for inflammation including NSAIDS antihistamine and others
A2. Drugs for inflammation including NSAIDS antihistamine and others: 2=yes self-reported; -1=left blank
Categorical
A2. Drugs for inflammation including NSAIDS antihistamine and others
A2. Current self-reported meds - Drugs for inflammatory conditions (not including eczema) 1) irritable bowel syndrome crohn coeliac disease and colitus 2) asthma 3) inflammatory arthritis including gout non-autoimmune diseases and autoimmune diseases 4) topical medicine if specifically lupus or psoriasis was noted 5) hay fever / allergy / epipen for anaphylaxis 7) use of NSAIDS 8) antihistamine drugs (eg promethazine hydroxyzine acrivastine desloratadine fexofenadine levocetirizine loratadine mizolastine) derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
A2. Any lipid lowering drug (including omega-3 PUFA as BNF defines)
A2. Any lipid lowering drug (including omega-3 PUFA as BNF defines): 2=yes self-reported; -1=left blank
Categorical
A2. Any lipid lowering drug (including omega-3 PUFA as BNF defines)
A2. Current self-reported meds - Any lipid lowering drug (including omega-3 PUFA as BNF lists). Bile acid sequestrants are not included if use for a intestinal disorder was specified derived from GQ_V3.0_24/04: 2=yes self-reported;1=left blank
Categorical
A2. Nitrates including meds for transdermal dosage
A2. Nitrates including meds for transdermal dosage: 2=yes self-reported; -1=left blank
Categorical
A2. Nitrates including meds for transdermal dosage
A2. Current self-reported meds - Nitrates (eg trinitrate GTNspray nicorandil) including meds for transdermal dosage - considered as a cardiac drug unless notified derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
A2. NSAIDs for any purpose not including aspirin (gq_med_asp)/topical NSAIDs
A2. NSAIDs for any purpose not including aspirin (gq_med_asp)/topical NSAIDs: 2=yes self-reported; -1=left blank
Categorical
A2. NSAIDs for any purpose not including aspirin (gq_med_asp)/topical NSAIDs
A2. Current self-reported meds - NSAIDs for any purpose (eg celecoxib diclofenac etodolac ibuprofen meloxicam naprosyn omeprazole) 1) not including aspirin (see gq_med_asp) 2) not including topical ones (eg eumovate cream) 3) coded in use of a gastrointestinal med against NSAID use derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
A2. Dieatry supplements (oils vitamins minerals) for any reasons
A2. Dieatry supplements (oils vitamins minerals) for any reasons: 2=yes self-reported; -1=left blank
Categorical
A2. Dieatry supplements (oils vitamins minerals) for any reasons
A2. Current self-reported meds - Dieatry supplements (oils vitamins minerals) (eg iron calcium zinc vitamin D) derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
A2. Oral contraceptive not including non-oral ones
A2. Oral contraceptive not including non-oral ones: 2=yes self-reported; -7=not applicable/answered but undetermined; -1=left blank
Categorical
A2. Oral contraceptive not including non-oral ones
A2. Current self-reported meds - Oral contraceptives (eg cerazetta cilest depo gedarel loestrin marvelon micronor ovranette yasmin) 1) not including non-oral contraception eg (implanon mirena coil) 2) including cerazette for any reasons 3) birth control interpreted as oral contraceptive use 4) not including contraceptive drugs used for endometriosis or abnormal menstruation derived from GQ_V3.0_24/04: 2=yes self-reported;-7=not applicable/answered but undetermined;-1=left blank
Categorical
A2. NSAIDs or others used for pain as gq_med_pain
A2. NSAIDs or others used for pain as gq_med_pain: 2=yes self-reported; -1=left blank
Categorical
A2. NSAIDs or others used for pain as gq_med_pain
A2. Current self-reported meds - NSAIDs or others used for pain as gq_med_pain - including aspirin and beta-blocker used against migrane or for migraine profilaxis derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
A2. Any pain killers not classified as NSAIDs/aspirin/b-blockers
A2. Any pain killers not classified as NSAIDs/aspirin/b-blockers: 2=yes self-reported; -1=left blank
Categorical
A2. Any pain killers not classified as NSAIDs/aspirin/b-blockers
A2. Current self-reported meds - Any pain killers not classified as NSAIDs or aspirin (eg paracetamol almotriptan eletriptan frovatriptan naratriptan rizatriptan sumatriptan zolmitriptan pizotifen) or beta-blockers (propranol used for migraine) derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
A2. Drugs to aid sleeping - not necessarily sleeping disorder
A2. Drugs to aid sleeping - not necessarily sleeping disorder: 2=yes self-reported; -1=left blank
Categorical
A2. Drugs to aid sleeping - not necessarily sleeping disorder
A2. Current self-reported meds - Drugs to aid sleeping (etmazapam mirtazapine zopiclone) - mixed with a drug acting on central nervous system to suppress pain or other discomfort derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
A2. Statin
A2. Statin: 2=yes self-reported; -1=left blank
Categorical
A2. Statin
A2. Current self-reported meds - Statin (eg atorvastatin pravastatin rosuvastatin and simvastatin) derived from GQ_V3.0_24/04: 2=yes self-reported;-1=left blank
Categorical
GQ_Med_why_a
New in R8. A2a. Current Medication Reason for taking the drug a.
Text
GQ_Med_why_b
New in R8. A2b. Current Medication Reason for taking the drug b.
Text
GQ_Med_why_c
New in R8. A2c. Current Medication Reason for taking the drug c.
Text
GQ_Med_why_d
New in R8. A2d. Current Medication Reason for taking the drug d.
Text
GQ_Med_why_e
New in R8. A2e. Current Medication Reason for taking the drug e.
Text
GQ_Med_why_f
New in R8. A2f. Current Medication Reason for taking the drug f.
Text
GQ_Med_why_g
New in R8. A2g. Current Medication Reason for taking the drug g.
Text
GQ_Med_why_h
New in R8. A2h. Current Medication Reason for taking the drug h.
Text
GQ_Meno_age
New in R8. A7. If NO how old were you when you stopped having your periods (i.e. your age at menopause in years old)? YEARS of age (from GQV3_A7bAgePeriodsStopped GQV4_A7bAgePeriodsStopped) (raw info of gq_meno_age). number = age in years at menopause;
Categorical
A7. Age menstruation stopped
A7. Age menstruation stopped: -8=not asked (GQ version difference); -7=not applicable/answered but undetermined; -5=hysterectomy or other answers (see text of GQ_Meno_age); -1=left blank
Time
A7. Age menstruation stopped
A7b. How old were you when your periods stopped completely and permanently? derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined
Real
A7. Age menstruation stopped. Don't know.
A7b. How old were you when your periods stopped completely and permanently? Don't know. derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined 1=don’t know
Categorical
A7a. Menopause
A7a. Have you reached the menopause? (i.e. your periods have now stopped completely and you believe permanently and your last period was at least six months ago) derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined;2=yes;3=no 4=don’t know
Categorical
A7d. Mother’s age of natural menopause
A7d. What was your mother’s age of natural menopause? (years) derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined
Real
A7d. Mother’s age of natural menopause. Don't know.
A7d. What was your mother’s age of natural menopause? Don't know. derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined 1=don’t know
Categorical
A7c. Reason for periods stopping
A7c. What was the reason for your periods stopping? derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined 1=natural menopause 2=natural menopause with HRT treatment 3=surgery 4=don’t know 5=others
Categorical
A7c. Reason for periods stopping. others.
A7c. What was the reason for your periods stopping? derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined 1=checked for others.
Categorical
GQ_Menstr_age
New in R8. A6. How old were you when you had your first menstrual period (in years)? YEARS of age (from GQV3_A6AgeFirstMenstralPeriod GQV4_A6AgeFirstMenstralPeriod) (raw info of gq_menstr_age).
Real
A6. Age first menstruation
A6. Age first menstruation: -8=not asked (GQ version difference); -7=not applicable/answered but undetermined; -1=left blank
Time
A5. Age first menstruation
A5a. How old were you when you had your first menstrual period? (years) derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined
Real
A6b. Days between menstruations
A6b. About how many days are there usually from the first day of one menstrual period to the first day of the next? derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined
Real
A6c. Irregular cycles.
A6c. Do you have irregular cycles? (i.e. you cannot predict within 5 days in either direction when your next period will start): -1=left blank;-7=not applicable/answered but undetermined;2=yes;3=no
Categorical
A6a. The first day of the last menstrual period.
A6a. On what date was the first day of your last menstrual period? derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined
Real
GQ_Menstr_still
New in R8. A7. Are you still having menstrual periods? (from GQV3_A7aStillHaveMenstrualPeriods GQV4_A7aStillHaveMenstrualPeriods) (raw info of gq_menstr_still)
Categorical
A7. Still menstruating
A7. Still menstruating: 2=Yes; 3=No; -8=not asked (GQ version difference); -7=not applicable/answered but undetermined; -1=left blank
Categorical
A5b. Still menstruation
A5b. Are you still having menstrual periods? derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined;2=yes;3=no
Categorical
GQ_Nhouse
New in R8. C9. How many people are there in your household? (including children) Count. (from GQV3_C9NumberInHouse GQV4_C9NumberInHouse) (raw info of gq_nhouse).
Real
C9. Number of people in household
C9. Number of people in household: -8=not asked (GQ version difference); -7=not applicable/answered but undetermined; -1=left blank
Integer
B9. Number of people in household
B9. How many people are there in your household? (including children) Count derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Integer
C5. Occup Clerical and intermediate
C5. Occup Clerical and intermediate: 2=Yes; 3=No; -8=not asked (GQ version difference); -1=left blank
Categorical
B5. Occup Clerical and intermediate
B5. Occupation type - Clerical and intermediate derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
C5. Occup Middle or junir managers
C5. Occup Middle or junir managers: 2=Yes; 3=No; -8=not asked (GQ version difference); -1=left blank
Categorical
B5. Occup Middle or junir managers
B5. Occupation type - Middle or junir managers derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
C5. Occup Modern professional
C5. Occup Modern professional: 2=Yes; 3=No; -8=not asked (GQ version difference); -1=left blank
Categorical
B5. Occup Modern professional
B5. Occupation type - Modern professional derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
C5. Occup Routine manual and service occupations
C5. Occup Routine manual and service occupations: 2=Yes; 3=No; -8=not asked (GQ version difference); -1=left blank
Categorical
B5. Occup Routine manual and service occupations
B5. Occupation type - Routine manual and service occupations derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
C5. Occup Semi-routine manual and service occupations
C5. Occup Semi-routine manual and service occupations: 2=Yes; 3=No; -8=not asked (GQ version difference); -1=left blank
Categorical
B5. Occup Semi-routine manual and service occupations
B5. Occupation type - Semi-routine manual and service occupations derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
C5. Occup Senior manager or administrators
C5. Occup Senior manager or administrators: 2=Yes; 3=No; -8=not asked (GQ version difference); -1=left blank
Categorical
B5. Occup Senior manager or administrators
B5. Occupation type - Senior manager or administrators derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
C5. Occup Technical and craft
C5. Occup Technical and craft: 2=Yes; 3=No; -8=not asked (GQ version difference); -1=left blank
Categorical
B5. Occup Technical and craft
B5. Occupation type - Technical and craft derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
C5. Occup Traditional professional occupations
C5. Occup Traditional professional occupations: 2=Yes; 3=No; -8=not asked (GQ version difference); -1=left blank
Categorical
B5. Occup Traditional professional occupations
B5. Occupation type - Traditional professional occupations derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
GQ_Owncars
New in R8. C10. Do you own a car or van ? (from GQV1_DMC5aCars GQV3_C10Cars GQV4_C10Cars) (raw info of gq_owncars).
Categorical
C10. Own a car or van
C10. Own a car or van: 2=Yes; 3=No; -7=not applicable/answered but undetermined; -1=left blank
Categorical
B10. Own a car or van
B10. Do you own a car or van ? derived from GQ_V3.0_24/04: 2=Yes;3=No;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_Ownhouse
New in R8. C11. Do you own or are you buying your own home? (from GQV1_DMC5bOwnHouse GQV3_C11aOwnHouse GQV4_C11aOwnHouse) (raw info of gq_ownhouse).
Categorical
C11. Own house
C11. Own house: 2=Yes; 3=No; -1=left blank
Categorical
B12. Own house
B12. Do you own or are you buying your own home? derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
GQ_PA_reason
New in R8. A5. Is there any reason you know of that means you should not follow an activity programme even if you wanted to? (from GQV1_A5lReasonNotToDoPA GQV3_A5lReasonNotToDoPA GQV4_A5lReasonNotToDoPA) (raw info of gq_pa_reason).
Categorical
A5. Any reason not to do PA
A5. Any reason not to do PA: 2=Yes; 3=No; -1=left blank
Categorical
A3. Any reason not to do PA
A3. Is there any reason you know of that means you should not follow an activity programme even if you wanted to? derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
GQ_Preg
New in R8. A5. Are you pregnant? (from GQV1_A5kPregnant GQV3_A5kPregnant GQV4_A5kPregnant) (raw info of gq_preg).
Categorical
A5. Pregnancy status
A5. Pregnancy status: 2=Yes; 3=No; -7=not applicable/answered but undetermined; -1=left blank
Categorical
A3. Pregnancy status
A3. Are you pregnant? derived from GQ_V3.0_24/04: 2=Yes;3=No;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_Readymeals
New in R8. D2. When eating your main meal at home how often do you usually eat Ready-made meals/prepared foods. (from GQV1_D2bEatReadyMeals GQV3_D2bEatReadyMeals GQV4_D2bEatReadyMeals) (raw info of gq_readymeals).
Categorical
D2. How often eat ready meals
D2. How often eat ready meals: 1=never or rarely; 2=1-2 times/wk; 3=3-5 times/wk; 4=>5 times/wk; -1=left blank
Categorical
C5. How often eat ready meals
C5. When eating your main meal at home how often do you usually eat Ready-made meals/prepared foods. derived from GQ_V3.0_24/04: 1=never or rarely;2=1-2 times/wk;3=3-5 times/wk;4=>5 times/wk;-1=left blank
Categorical
GQ_Renthouse
New in R8. C11. Do you rent your home?(from GQV1_DMC5cRenHouse GQV3_C11bRentHouse GQV4_C11bRentHouse) (raw info of gq_renthouse).
Categorical
C11. Rent house
C11. Rent house: 2=Yes; 3=No; -1=left blank
Categorical
B12. Rent house
B12. Do you rent your home? derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
GQ_SelfR_emot
New in R8. E7. Self perceived health. During the past 4 weeks how much have you been bothered by emotional problems (such as feeling anxious depressed or irritable)? (not asked in GQv1) (from GQV3_E7SREmotional GQV4_E7SREmotional) (raw info of gq_selfr_emot).
Categorical
GQ_SelfR_emotwork
New in R8. E8. Self perceived health. During the past 4 weeks how much did personal or emotional problems keep you from doing your usual work studies or other daily activities? (not asked in GQv1) (from GQV3_E8SREmotionalDailyWork GQV4_E8SREmotionalDailyWork) (raw info of gq_selfr_emotwork).
Categorical
E8. Self perceived health - Emotional problems limiting daily work/activities
E8. Self perceived health - Emotional problems limiting daily work/activities: 1=not at all; 2=very little; 3=somewhat; 4=quite a lot; 5=could not do daily activities; -8=not asked (GQ version difference); -1=left blank
Categorical
E8. Self perceived health - Emotional problems limiting daily work/activities
E8. Self perceived health. During the past 4 weeks how much did personal or emotional problems keep you from doing your usual work studies or other daily activities? derived from GQ_V3.0_24/04: 1=not at all;2=very little;3=somewhat;4=quite a lot;5=could not do daily activities;-1=left blank;-7=not applicable/answered but undetermined
Categorical
E7. Self perceived health - Emotional problems
E7. Self perceived health - Emotional problems: 1=not at all; 2=slightly; 3=moderately; 4=quite a lot; 5=extremely; -8=not asked (GQ version difference); -1=left blank
Categorical
E7. Self perceived health - Emotional problems
E7. Self perceived health. During the past 4 weeks how much have you been bothered by emotional problems (such as feeling anxious depressed or irritable)? derived from GQ_V3.0_24/04: 1=not at all;2=slightly;3=moderately;4=quite a lot;5=extremely;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_SelfR_energy
New in R8. E5. Self perceived health. During the past 4 weeks how much energy did you have? (not asked in GQv1) (from GQV3_E5SREnergy GQV4_E5SREnergy) (raw info of gq_selfr_energy).
Categorical
E5. Self perceived health - Energy level
E5. Self perceived health - Energy level: 1=very much; 2=quite a bit; 3=some; 4=a little; 5=none; -8=not asked (GQ version difference); -1=left blank
Categorical
E5. Self perceived health - Energy level
E5. Self perceived health. During the past 4 weeks how much energy did you have? derived from GQ_V3.0_24/04: 1=very much;2=quite a bit;3=some;4=a little;5=none;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_SelfR_health
New in R8. E1. Self perceived health. Overall how would you rate your health during the past 4 weeks? (not asked in GQv1) (from GQV3_E1SRHealth GQV4_E1SRHealth) (raw info of gq_selfr_health).
Categorical
E1. Self perceived health - Self recorded health
E1. Self perceived health - Self recorded health: 1=excellent; 2=very good; 3=good; 4=fair; 5=poor; 6=very poor; -8=not asked (GQ version difference); -1=left blank
Categorical
E1. Self perceived health - Self recorded health
E1. Self perceived health. Overall how would you rate your health during the past 4 weeks? derived from GQ_V3.0_24/04: 1=excellent;2=very good;3=good;4=fair;5=poor;6=very poor;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_SelfR_pa
New in R8. E2. Self perceived health. During the past 4 weeks how much did physical health problems limit your usual physical activities (walking climbing stairs)? (not asked in GQv1) (from GQV3_E2SRPhysicalProblems GQV4_E2SRPhysicalProblems) (raw info of gq_selfr_pa).
Categorical
GQ_SelfR_pain
New in R8. E4. Self perceived health. How much bodily pain have you had during the past 4 weeks? (not asked in GQv1) (from GQV3_E4SRBodilyPain GQV4_E4SRBodilyPain) (raw info of gq_selfr_pain).
Categorical
E4. Self perceived health - Bodily pain
E4. Self perceived health - Bodily pain: 1=none; 2=very mild; 3=mild; 4=moderate; 5=severe; 6=very severe; -8=not asked (GQ version difference); -1=left blank
Categorical
E4. Self perceived health - Bodily pain
E4. Self perceived health. How much bodily pain have you had during the past 4 weeks? ) derived from GQ_V3.0_24/04: 1=none;2=very mild;3=mild;4=moderate;5=severe;6=very severe;-1=left blank;-7=not applicable/answered but undetermined
Categorical
E2. Self perceived health - Physical Activity limited by health problems
E2. Self perceived health - Physical Activity limited by health problems: 1=not at all; 2=very little; 3=somewhat; 4=quite a lot; 5=could not do physical activities; -8=not asked (GQ version difference); -1=left blank
Categorical
E2. Self perceived health - Physical Activity limited by health problems
E2. Self perceived health. During the past 4 weeks how much did physical health problems limit your usual physycal activities (walking climbing stairs)? derived from GQ_V3.0_24/04: 1=not at all;2=very little;3=somewhat;4=quite a lot;5=could not do physical activities;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_SelfR_social
New in R8. E6. Self perceived health. During the past 4 weeks how much did your physical health or emotional problems limit your social activities with family or friends? (not asked in GQv1) (from GQV3_E6SREmotionalSocial GQV4_E6SREmotionalSocial) (raw info of gq_selfr_social).
Categorical
E6. Self perceived health - Health/emotional problems affecting social activity
E6. Self perceived health - Health/emotional problems affecting social activity: 1=not at all; 2=very little; 3=somewhat; 4=quite a lot; 5=could not do social activities; -8=not asked (GQ version difference); -1=left blank
Categorical
E6. Self perceived health - Health/emotional problems affecting social activity
E6. Self perceived health. During the past 4 weeks how much did your physical health or emotional problems limit your social activities with family or friends? derived from GQ_V3.0_24/04: 1=not at all;2=very little;3=somewhat;4=quite a lot;5=could not do social activities;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_SelfR_work
New in R8. E3. Self perceived health. During the past 4 weeks how much difficulty did you have doing your daily work both inside and outside the home because of your physical health? (not asked in GQv1) (from GQV3_E3SRPhysicalDailyWork GQV4_E3SRPhysicalDailyWork) (raw info of gq_selfr_work).
Categorical
E3. Self perceived health - Difficulty doing daily work due to health problems
E3. Self perceived health - Difficulty doing daily work due to health problems: 1=not at all; 2=very little; 3=somewhat; 4=quite a lot; 5=could not do daily work; -8=not asked (GQ version difference); -1=left blank
Categorical
E3. Self perceived health - Difficulty doing daily work due to health problems
E3. Self perceived health. During the past 4 weeks how much difficulty did you have doing your daily work both inside and outside the home because of your physical health? derived from GQ_V3.0_24/04: 1=not at all;2=very little;3=somewhat;4=quite a lot;5=could not do daily work;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_Sm_agestart
New in R8. B1. At what age did you start smoking? Please enter age in years. (not asked in GQv1) YEARS of age or (from GQV3_B1cAgeStartSmoking GQV4_B1cAgeStartSmoking) (raw info of gq_sm_agestart). number = age in years;
B1. Age started smoking
B1. Age started smoking: -8=not asked (GQ version difference); -7=not applicable/answered but undetermined; -1=left blank
Time
A4. Age started smoking
A4. At what age did you start smoking? Please enter age in years derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Real
GQ_Sm_cur
New in R8. B1. Do you smoke now? (from GQV3_B1bCurrentlySmoke GQV4_B1bCurrentlySmoke) (raw info of gq_sm_cur).
Categorical
B1. Smoke currently (daily or occasionally)
B1. Smoke currently (daily or occasionally): 2=Yes; 3=No; -8=not asked (GQ version difference); -1=left blank
Categorical
A4. Smoke currently (daily or occasionally)
A4. Do you smoke now? derived from GQ_V3.0_24/04: 2=Yes;3=No;-7=not applicable/answered but undetermined;-1=left blank
Categorical
GQ_Sm_daily
New in R8. B1. Do you smoke daily? (only asked in GQv 1 25/11/2004 and 26/01/2005). (from GQV1_B1aSmokeDaily ) (raw info of gq_sm_daily).
Categorical
B1. Smoking habits
B1. Smoking habits: 1=Never smokers; 2=Former smokers; 3=Current smokers; 4=Ever smokers (unknown for current habit); -7=not applicable/answered but undetermined
Categorical
A4. Smoking habits
A4. Smoking habits based on multiple variables the Fenland Phase 2 general questionnaire GQ_V3.0_24/04: 1=Never smokers;2=Former smokers;3=Current smokers;4=Ever smokers (unknown for current habit);-7=not applicable/answered but undetermined
Categorical
B1. Smoking duration (years)
B1. Smoking duration (years): -8=not asked (GQ version difference); -7=not applicable/answered but undetermined
Time
A4. Smoking duration (years)
A4. Duration of smoking (years) projected from a time of starting smoking and a time of quitting smoking or current smoking habit (if smoking cessation during a certain calendar-time period was noted the period was accounted for as a non-smoking period.) derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-5=former smokers who reported a time of smoking cessation which appeared to be earlier than a starting date.
Real
GQ_Sm_ever
New in R8. B1. Have you ever smoked? If no please go to B2 on the next page. (from GQV1_B1cEverSmoked GQV3_B1aEverSmoked GQV4_B1aEverSmoked) (raw info of gq_sm_ever).
Categorical
B1. Ever smoked
B1. Ever smoked: 2=Yes; 3=No; -1=left blank
Categorical
A4. Ever smoked
A4. Have you ever smoked? If no please go to B2 on the next page. derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
B1. Smoke exposure(grams/day)
B1. Smoke exposure(grams/day): -7=not applicable/answered but undetermined
Real
A4. Smoke exposure(grams/day)
A4. Smoking exposure in volume (grams/day) based on N or gram of smoking with the formula (CIGARETTESx1.25 + CHEROOTSx2x1.25 + CIGARSx3x1.25 + TOBACCO/7) derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined
Real
GQ_Sm_Ncheroots
New in R8. B1. How many cheroots do you or did you smoke a day on average? Rounded to integers. (from GQV1_B1fNumberCherootsPerDay GQV3_B1fNumberCherootsPerDay GQV4_B1fNumberCherootsPerDay) (raw info of gq_sm_ncheroots).
Categorical
B1. N cheroots smoked per day
B1. N cheroots smoked per day: -7=not applicable/answered but undetermined; -1=left blank
Integer
A4. N cheroots smoked per day
A4. How many cheroots do you or did you smoke a day on average? Rounded to integers. derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Integer
GQ_Sm_Ncig
New in R8. B1. How many cigarettes do you or did you smoke a day on average? (rounded to an integer) (from GQV1_B1eNumberCigarettesPerDay GQV3_B1eNumberCigarettesPerDay GQV4_B1eNumberCigarettesPerDay) (raw info of gq_sm_ncig).
Categorical
GQ_Sm_Ncigars
New in R8. B1. How many cigars do you or did you smoke a day on average? Rounded to integers (from GQV1_B1gNumberCigarsPerDay GQV3_B1gNumberCigarsPerDay GQV4_B1gNumberCigarsPerDay) (raw info of gq_sm_ncigars).
Categorical
B1. N cigars per day
B1. N cigars per day: -7=not applicable/answered but undetermined; -1=left blank
Integer
A4. N cigars per day
A4. How many cigars do you or did you smoke a day on average? Rounded to integers derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Integer
B1. N cigarettes per day
B1. N cigarettes per day: -7=not applicable/answered but undetermined; -1=left blank
Integer
A4. N cigarettes per day
A4. How many cigarettes do you or did you smoke a day on average? (rounded to an integer) derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Integer
GQ_Sm_occasion
New in R8. B1. Do you smoke occasionally? (Only asked in GQv1 25/11/2004 and 26/01/2005). (from GQV1_B1bSmokeOccasionally ) (raw info of gq_sm_occasion).
Categorical
B1. Smoking pack-years (N x years)
B1. Smoking pack-years (N x years): -8=not asked (GQ version difference); -7=not applicable/answered but undetermined
Real
A4. Smoking pack-years (N x years)
A4. Smoking cumulative exposure (pack x years) with gq_sm_dur (years) x gq_sm_g / (1.25x20) (assuming 1.25 g per 1 cigarette and 20 cigarretes per 1 pack) derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined
Real
GQ_Sm_tobacco_grm
New in R8. B1. How much do you or did you smoke a day on average? Grams/week. Rounded to integers (from GQV1_B1hTobaccoPerWeek GQV3_B1hTobaccoPerWeek GQV4_B1hTobaccoPerWeek) (raw info of gq_sm_tobacco_grm).
Categorical
B1. Grams of tobacco per week
B1. Grams of tobacco per week: -7=not applicable/answered but undetermined; -1=left blank
Real
A4. Grams of tobacco per week
A4. How much do you or did you smoke a day on average? Grams/week. Rounded to integers derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Real
GQ_Sm_yearstop
New in R8. B1. If you have stopped smoking in which year did you quit? Calendar YEARS
Real
B1. Year stopped smoking
B1. Year stopped smoking: -7=not applicable/answered but undetermined; -1=left blank
Time
A4. Year stopped smoking
A4. If you have stopped smoking in which year did you quit? Calendar YEARS derived from GQ_V3.0_24/04: -7=not applicable/answered but undetermined;-1=left blank
Real
GQ_Takeaway
New in R8. D2. When eating your main meal at home how often do you usually eat Home delivery or take-away meals. (from GQV1_D2aEatTakeaways GQV3_D2aEatTakeaways GQV4_D2aEatTakeaways) (raw info of gq_takeaway).
Categorical
D2. How often eat take-away
D2. How often eat take-away: 1=never or rarely; 2=1-2 times/wk; 3=3-5 times/wk; 4=>5 times/wk; -1=left blank
Categorical
C5. How often eat take-away
C5. When eating your main meal at home how often do you usually eat Home delivery or take-away meals. derived from GQ_V3.0_24/04: 1=never or rarely;2=1-2 times/wk;3=3-5 times/wk;4=>5 times/wk;-1=left blank
Categorical
B11. TV or computer in a bedroom
B11. Do you have a TV or computer in your bedroom? derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
GQ_TV_alc
New in R8. D6. How often drink alcohol while watching TV (last 4 weeks)? (Only asked in GQv4) (from GQV4_D6fAlcohol) (raw info of gq_tv_alc).
Categorical
D6. How often drink alcohol while watching TV
D6. How often drink alcohol while watching TV: 1=none; 2=1-2/wk; 3=3-4/wk; 4=5-6/wk; 5=once/d; 6=2/d; 7=3/d; 10=>5/d; -8=not asked (GQ version difference); -1=left blank
Categorical
C12. How often drink alcohol while watching TV
C12. How often drink alcohol while watching TV (last 4 weeks)? derived from GQ_V3.0_24/04: 1=none;2=1-2/wk;3=3-4/wk;4=5-6/wk;5=once/d;6=2/d;7=3/d;10=>5/d;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_TV_eat
New in R8. D4. How often do you eat your meal while watching television or video? (from GQV1_D4EatAndWatchTV GQV3_D4EatAndWatchTV GQV4_D4EatAndWatchTV) (raw info of gq_tv_eat).
Categorical
D4. Meal while watching TV
D4. Meal while watching TV: 1=<1/wk; 2=1/wk; 3=2-4 times/wk; 4=5-6 times/wk; 5=once/d; 6=>1/d; -8=not asked (GQ version difference); -1=left blank
Categorical
C7. Meal while watching TV
C7. How often do you eat your meal while watching television or video? derived from GQ_V3.0_24/04: 1=<1/wk;2=1/wk;3=2-4 times/wk;4=5-6 times/wk;5=once/d;6=>1/d;-1=left blank
Categorical
GQ_TV_frjuice
New in R8. D6. How often did you have Fruit juice while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? (Only asked in GQv4) (from GQV4_D6gFruitJuice) (raw info of gq_tv_frjuice).
Categorical
D6. Fruit juice while watching TV
D6. Fruit juice while watching TV: 1=none; 2=1-2/wk; 3=3-4/wk; 4=5-6/wk; 5=once/d; 6=2/d; 7=3/d; 9=5/d; 10=>5/d; -8=not asked (GQ version difference); -1=left blank
Categorical
C12. Fruit juice while watching TV
C12. How often did you have Fruit juice while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? derived from GQ_V3.0_24/04: 1=none;2=1-2/wk;3=3-4/wk;4=5-6/wk;5=once/d;6=2/d;7=3/d;9=5/d;10=>5/d;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_TV_icecream
New in R8. D6. How often did you have Ice cream chocolate mousse while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? (Only asked in GQv4) (from GQV4_D6cIceCream) (raw info of gq_tv_icecream).
Categorical
D6. Ice cream while watching TV
D6. Ice cream while watching TV: 1=none; 2=1-2/wk; 3=3-4/wk; 4=5-6/wk; 5=once/d; 6=2/d; 10=>5/d; -8=not asked (GQ version difference); -1=left blank
Categorical
C12. Ice cream while watching TV
C12. How often did you have Ice cream chocolate mousse while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? derived from GQ_V3.0_24/04: 1=none;2=1-2/wk;3=3-4/wk;4=5-6/wk;5=once/d;6=2/d;10=>5/d;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_TV_milk
New in R8. D6. How often did you have Milk milkshake hot chocolate while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? (Only asked in GQv4) (from GQV4_D6iMilk) (raw info of gq_tv_milk).
Categorical
D6. Milk while watching TV
D6. Milk while watching TV: 1=none; 2=1-2/wk; 3=3-4/wk; 4=5-6/wk; 5=once/d; 6=2/d; 7=3/d; 8=4/d; 9=5/d; 10=>5/d; -8=not asked (GQ version difference); -1=left blank
Categorical
C12. Milk while watching TV
C12. How often did you have Milk milkshake hot chocolate while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? derived from GQ_V3.0_24/04: 1=none;2=1-2/wk;3=3-4/wk;4=5-6/wk;5=once/d;6=2/d;7=3/d;8=4/d;9=5/d;10=>5/d;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_TV_others
New in R8. D6. Which other (please list) snacks did you have while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? (Only asked in GQv4) (from GQV4_D6kOther) (raw info of gq_tv_others).
Categorical
D6. Other snacks while watching TV
D6. Other snacks while watching TV: 1=none; 2=1-2/wk; 3=3-4/wk; 4=5-6/wk; 5=once/d; 6=2/d; 7=3/d; 8=4/d; 9=5/d; 10=>5/d; -8=not asked (GQ version difference); -1=left blank
Categorical
C12. Other snacks while watching TV
C12. Which other (please list) snacks did you have while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? derived from GQ_V3.0_24/04: 1=none;2=1-2/wk;3=3-4/wk;4=5-6/wk;5=once/d;6=2/d;7=3/d;8=4/d;9=5/d;10=>5/d;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_TV_others_txt
New in R8. D6. Which other (please list) snacks did you have while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? (Only asked in GQv4) TEXT. -8=not assessed (version difference) (from GQV4_D6lOtherText)
Text
GQ_TV_savory
New in R8. D6. How often did you have savoury snacks (crisps salted nuts..) while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? (Only asked in GQv4) (from GQV4_D6aSavoury) (raw info of gq_tv_savory).
Categorical
D6. Savoury snacks while watching TV
D6. Savoury snacks while watching TV: 1=none; 2=1-2/wk; 3=3-4/wk; 4=5-6/wk; 5=once/d; 6=2/d; 7=3/d; 9=5/d; 10=>5/d; -8=not asked (GQ version difference); -1=left blank
Categorical
C12. Savoury snacks while watching TV
C12. How often did you have savoury snacks (crisps salted nuts...) while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? derived from GQ_V3.0_24/04: 1=none;2=1-2/wk;3=3-4/wk;4=5-6/wk;5=once/d;6=2/d;7=3/d;9=5/d;10=>5/d;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_TV_snack
New in R8. D5. Apart from meals how often do you snack foods while watching television? (from GQV1_D5SnackAndWatchTV GQV3_D5SnackAndWatchTV GQV4_D5SnackAndWatchTV) (raw info of gq_tv_snack).
Categorical
D5. Snack foods while watching TV
D5. Snack foods while watching TV: 1=never; 2=occasionally; 3=usually; 4=alwyas; -8=not asked (GQ version difference); -1=left blank
Categorical
C9. Snack while watching TV
C9. How often do you eat your meal while watching television or video? derived from GQ_V3.0_24/04: 1=<1/wk;2=1/wk;3=2-4 times/wk;4=5-6 times/wk;5=once/d;6=>1/d;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_TV_soda
New in R8. D6. How often did you have Soda (coke) while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? (Only asked in GQv4) (from GQV4_D6eSoda) (raw info of gq_tv_soda).
Categorical
D6. Soda or coke while watching TV
D6. Soda or coke while watching TV: 1=none; 2=1-2/wk; 3=3-4/wk; 4=5-6/wk; 5=once/d; 6=2/d; 7=3/d; 8=4/d; 9=5/d; 10=>5/d; -8=not asked (GQ version difference); -1=left blank
Categorical
C12. Soda or coke while watching TV
C12. How often did you have Soda (coke Ë) while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? derived from GQ_V3.0_24/04: 1=none;2=1-2/wk;3=3-4/wk;4=5-6/wk;5=once/d;6=2/d;7=3/d;8=4/d;9=5/d;10=>5/d;-1=left blank
Categorical
GQ_TV_squash
New in R8. D6. How often did you have squash while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? (Only asked in GQv4) (from GQV4_D6hSquash) (raw info of gq_tv_squash).
Categorical
D6. Squash while watching TV
D6. Squash while watching TV: 1=none; 2=1-2/wk; 3=3-4/wk; 4=5-6/wk; 5=once/d; 6=2/d; 7=3/d; 8=4/d; 9=5/d; 10=>5/d; -8=not asked (GQ version difference); -1=left blank
Categorical
C12. Squash while watching TV
C12. How often did you have squash while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? derived from GQ_V3.0_24/04: 1=none;2=1-2/wk;3=3-4/wk;4=5-6/wk;5=once/d;6=2/d;7=3/d;8=4/d;9=5/d;10=>5/d;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_TV_swts
New in R8. D6. How often did you have Sweets chocolate(s) (bars) cakes biscuits while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? (Only asked in GQv4) (from GQV4_D6bSweets) (raw info of gq_tv_swts).
Categorical
D6. Sweets while watching TV
D6. Sweets while watching TV: 1=none; 2=1-2/wk; 3=3-4/wk; 4=5-6/wk; 5=once/d; 6=2/d; 7=3/d; 8=4/d; 9=5/d; 10=>5/d; -8=not asked (GQ version difference); -1=left blank
Categorical
C12. Sweets while watching TV
C12. How often did you have Sweets chocolate(s) (bars) cakes biscuits while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? derived from GQ_V3.0_24/04: 1=none;2=1-2/wk;3=3-4/wk;4=5-6/wk;5=once/d;6=2/d;10=>5/d;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_TV_teacoffee
New in R8. D6. How often did you have tea or coffeewhile watching TV in addition to breakfast lunch or dinner (last 4 weeks)? (Only asked in GQv4) (from GQV4_D6jTea_coffee) (raw info of gq_tv_teacoffee).
Categorical
D6. Tea or coffee while watching TV
D6. Tea or coffee while watching TV: 1=none; 2=1-2/wk; 3=3-4/wk; 4=5-6/wk; 5=once/d; 6=2/d; 7=3/d; 8=4/d; 9=5/d; 10=>5/d; -8=not asked (GQ version difference); -1=left blank
Categorical
C12. Tea or coffee while watching TV
C12. How often did you have tea or coffeewhile watching TV in addition to breakfast lunch or dinner (last 4 weeks)? derived from GQ_V3.0_24/04: 1=none;2=1-2/wk;3=3-4/wk;4=5-6/wk;5=once/d;6=2/d;7=3/d;8=4/d;9=5/d;10=>5/d;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_TV_yoghurt
New in R8. D6. How often did you have Yoghurt rice pudding while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? (Only asked in GQv4) (from GQV4_D6dYoghurt) (raw info of gq_tv_yoghurt).
Categorical
D6. Yoghurt while watching TV
D6. Yoghurt while watching TV: 1=none; 2=1-2/wk; 3=3-4/wk; 4=5-6/wk; 5=once/d; 6=2/d; 7=3/d; 8=4/d; 9=5/d; 10=>5/d; -8=not asked (GQ version difference); -1=left blank
Categorical
C12. Yoghurt while watching TV
C12. How often did you have Yoghurt rice pudding while watching TV in addition to breakfast lunch or dinner (last 4 weeks)? derived from GQ_V3.0_24/04: 1=none;2=1-2/wk;3=3-4/wk;4=5-6/wk;5=once/d;6=2/d;7=3/d;8=4/d;9=5/d;10=>5/d;-1=left blank;-7=not applicable/answered but undetermined
Categorical
GQ_v
New in R8. GQ. Version of the Fenland General Questionnaire (GQ). From GQV3_QVersion and GQV4_QVersion; (raw info of gq_v).
Categorical
A8b. Age of voice break
A8b. If known; at what age did your voice break? derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined
Real
A8a. When voice break
A8a. When did your voice break? derived from GQ_V3.0_24/04: -1=left blank;-7=not applicable/answered but undetermined 1=younger than average 2=about average age 3=older than average 4=don’t know
Categorical
GQ. Version info
GQ. Version info: 1=GQ v1; 3=GQ v3; 4=GQ v4
Categorical
A3. Walk unaided for 10 minutes
A3. Can you walk unaided for 10 minutes at a moderate pace? derived from GQ_V3.0_24/04: 2=Yes;3=No;-1=left blank
Categorical
OLINK assay GRAP2
Phase 1 OLINK assay data for target GRAP2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GRN
Phase 1 OLINK assay data for target GRN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GSAP
Phase 1 OLINK assay data for target GSAP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GSTP1
Phase 1 OLINK assay data for target GSTP1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GT
Phase 1 OLINK assay data for target GT in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GUSB
Phase 1 OLINK assay data for target GUSB in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GZMA
Phase 1 OLINK assay data for target GZMA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GZMB
Phase 1 OLINK assay data for target GZMB in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay GZMH
Phase 1 OLINK assay data for target GZMH in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Serum Adiponectin CLEANED
Serum Adiponectin CLEANED in ug/ml. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: 0.3.
Categorical
Serum Adiponectin CLEANED Comment
Serum Adiponectin measurement CLEANED comment (on threshold)
Text
Serum Adiponectin Threshold
Serum Adiponectin CLEANED threshold.
Categorical
G_AgeAtTest_Attended
New in R8. Calculated age of participant at first visit; rounded down to whole year. This variable replaces G_AgeAtTest
Calculated age of pt first visit
Phase 2 data. Calculated age of participant at first visit; rounded down to whole year.
Real
Alcohol Amount Consumption
Alcohol consumption amount. Derived from GenQ Qs by DM team JAVA script. 1 unit = 8g ethanol. Calculation: (Beer + Wine + Spirits+ Fort Wine)/7
Real
Alcohol Amount Consumption weekend
Phase 2 data. Alcohol consumption amount averaged per weekend day across fri-sat-sun. Please note: in phase 1 1 unit was defined as 1/2 pint of beer or 1 glass of wine or 1 single measure of spirits or 1 glass of sherry. For phase 2 the units were defined as 1/2 pint of beer or 1/2 glass of wine or 1 single measure of spirits or 1 glass of sherry. Derived from GenQ Qs by DM team JAVA script. Calculation: (Beer + Wine + Spirits+ Fort Wine)/3
Real
Alcohol amount consumption weekday
Phase 2 data. Alcohol consumption amount averaged per weekday across mon-tue-wed-thu. Derived from GenQ Qs by DM team JAVA script. Please note: in phase 1; 1 unit was defined as 1/2 pint of beer or 1 glass of wine or 1 single measure of spirits or 1 glass of sherry. For phase 2 the units were defined as 1/2 pint of beer or 1/2 glass of wine or 1 single measure of spirits or 1 glass of sherry. Calculation: (Beer + Wine + Spirits+ Fort Wine)/4
Real
Alcohol Consumption Frequency
Alcohol consumption frequency. Derived from GenQ Qs by DM team JAVA script. WARNING: CODE DEFINITION (NOT CODES) WRONG IN EARLIER RELEASES.
Categorical
Alcohol consumption frequency
Phase 2 data. Alcohol consumption frequency. Derived from GenQ Qs by DM team JAVA script. 1 = Occasional; 2 = 1-2/week; 3 = 3-4/week; 4 = Daily; 9 = not known; 0 = never;
Categorical
Alcohol History / Status
Current Alcohol Consumption History / Status. Derived from GenQ Qs by DM team JAVA script. If units of beer/wine/spirits and/or fortified wine = >0 then this is automatically adjusted to
Categorical
Alcohol Consumption weekend
Phase 2 data. Current Alcohol Consumption on fri-sat-sun History / Status. Derived from GenQ Qs by DM team JAVA script. If units of beer/wine/spirits and/or fortified wine = >0 then this is automatically adjusted to 4 = current; 0 = never; 1 = not current; 2 = ex; 3 = ever; 4 = current; 9 = not known;
Categorical
Alcohol History
Phase 2 data. Current Alcohol Consumption on mon-tue-wed-thu History / Status. Derived from GenQ Qs by DM team JAVA script. If units of beer/wine/spirits and/or fortified wine = >0 then this is automatically adjusted to 4 = current; 0 = never; 1 = not current; 2 = ex; 3 = ever; 4 = current; 9 = not known;
Categorical
Serum Apo_A1 CLEANED
Serum Apo A1 measurement in g/L CLEANED. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: 0.2
Categorical
Apo_A1 CLEANED Comment
Serum Apo A1 measurement CLEANED comment (on threshold).
Text
Apo_A1 CLEANED Threshold
Serum Apo A1 measurement CLEANED Threshold.
Categorical
Serum Apo_B CLEANED
Serum Apo B measurement in g/L CLEANED. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: no verified threshold available.
Categorical
Serum Apo_B CLEANED Comment
Serum Apo B measurement CLEANED comment (on threshold).
Text
Serum Apo_B CLEANED Threshold
Serum Apo B CLEANED Threshold.
Categorical
Status Drinks beer
Current Beer Drinking Status. Derived from GenQ Qs by DM team JAVA script.
Categorical
Beer Drinking Status weekend
Phase 2 data. Current Beer Drinking Status on fri-sat-sun. Derived from GenQ Qs by DM team JAVA script. 1 = yes does drink beer; 9 = not known; 0 = no does not drink beer;
Categorical
Beer drinking status weekday
Phase 2 data. Current Beer Drinking Status on mon-tue-wed-thu. Derived from GenQ Qs by DM team JAVA script. 1 = yes does drink beer; 9 = not known; 0 = no does not drink beer;
Categorical
OLINK assay G-CSF
Phase 1 OLINK assay data for target G-CSF in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
C_Peptide CLEANED
C_Peptide measurement in pmol/L CLEANED. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: no verified threshold available.
Categorical
C_Peptide CLEANED Comment
C_Peptide measurement CLEANED comment (on threshold).
Text
C_Peptide CLEANED Threshold
C_Peptide measurement CLEANED Threshold.
Categorical
General questionnaire Data management comment
Data management comment for general questionnaire data.
Text
Status Drinks fortified wines
Current Fortified Wine Drinking Status e.g.sherry. Derived from GenQ Qs by DM team JAVA script.
Categorical
Fort Wine Drinking Status wknd
Phase 2 data. Current Fortified Wine Drinking Status on fri-sat-sun e.g.sherry. Derived from GenQ Qs by DM team JAVA script. 1 = yes does drink Fortified Wine; 9 = not known; 0 = no does not drink Fortified Wine;
Categorical
Fortified Wine drink status weekday
Phase 2 data. Current Fortified Wine Drinking Status on mon-tue-wed-thu e.g.sherry. Derived from GenQ Qs by DM team JAVA script. 1 = yes does drink Fortified Wine; 9 = not known; 0 = no does not drink Fortified Wine;
Categorical
hs_CRP CLEANED
hs_CRP measurement CLEANED. Serum levels of C-reactive protein measured with high-sensitivity system. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: 0.1
Categorical
hs_CRP CLEANED Comment
hs_CRP measurement CLEANED comment (on threshold).
Text
hs_CRP CLEANED Threshold
hs_CRP measurement CLEANED Theshold.
Categorical
Insulin CLEANED
Heparin Insulin measurement CLEANED in pmol/l. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: no verified threshold available.
Categorical
Insulin CLEANED Comment
Heparin Insulin measurement CLEANED comment (on threshold).
Text
Insulin CLEANED Comment
Heparin Insulin measurement CLEANED comment (on threshold).
Text
Insulin CLEANED
Heparin Insulin measurement CLEANED in pmol/l. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: no verified threshold available.
Real
Insulin CLEANED Threshold
Heparin Insulin measurement CLEANED Threshold.
Categorical
Insulin CLEANED Threshold
Heparin Insulin measurement CLEANED Threshold.
Categorical
Serum Iron CLEANED
Serum Iron measurement in umol/L CLEANED. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: no verified threshold available.
Categorical
Serum Iron CLEANED Comment
Serum Iron measurement CLEANED comment (on threshold).
Text
Serum Iron Threshold
Serum Iron measurement CLEANED threshold
Categorical
Serum Leptin CLEANED
Serum Leptin measurement in ng/ml CLEANED. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: 0.1
Categorical
Serum Leptin CLEANED Comment
Serum Leptin measurement CLEANED comment (on threshold).
Text
Cln variable: Leptin comment
Phase 2 data. Serum Leptin measurement CLEANED comment (on threshold).
Text
Cln variable: Leptin measurement
Phase 2 data. Phase 2 Serum Leptin measurement in ng/ml CLEANED. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: 0.1 -88.8 = measured but results below threshold value;
Real
Serum Leptin Threshold
Serum Leptin measurement CLEANED threshold.
Categorical
Cln variable: Leptin threshold
Phase 2 data. Phase 2 Serum Leptin measurement CLEANED threshold. 1 = Average value; 2 = value less than threshold; 3 = Single value; -1 = Blank (not measured); -2 = sample problem; -3 = Interference; -4 = Unsuitable; -5 = Insufficient; -9 = Everything else; 0 = No sample;
Categorical
NEFA CLEANED
Heparin NEFA measurement CLEANED in umol/l. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: 50.
Categorical
NEFA CLEANED Comment
Heparin NEFA measurement CLEANED comment (on threshold).
Text
NEFA CLEANED Comment
Heparin NEFA measurement CLEANED comment (on threshold).
Text
NEFA CLEANED
Heparin NEFA measurement CLEANED in umol/l. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: 50.
Real
NEFA CLEANED Threshold
Heparin NEFA measurement CLEANED Threshold.
Categorical
NEFA CLEANED Threshold
Heparin NEFA measurement CLEANED Threshold.
Categorical
NT_proBNP RAW-changed CLEANED by DM
Serum NT_proBNP measurement in pg/ml RAW-changed CLEANED by DM. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: 10
Categorical
NT_proBNP RAW-changed CLEANED Comment
Serum NT_proBNP measurement RAW-changed CLEANED comment (on threshold).
Text
NT_proBNP RAW-changed CLEANED Threshold
Serum NT_proBNP measurement RAW-changed CLEANED Threshold.
Categorical
Proinsulin CLEANED
Heparin Intact Pro-insulin measurement CLEANED in pmol/l. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: 1.25
Categorical
Proinsulin CLEANED Comment
Heparin Intact Pro-insulin measurement CLEANED comment (on threshold).
Text
Proinsulin CLEANED Threshold
Heparin Intact Pro-insulin measurement CLEANED Threshold.
Categorical
Smoking Amount in cigarettes
Current Smoking Amount in cigarette equivalents. Derived from GenQ Qs by DM team JAVA script. Rules: 1 cigarette = 1.25 g. 1 cheroot = 2 cigarettes 1 cigar = 3 cigarettes. Calculation: CIGARETTES + CHEROOTS*2 + CIGARS*3
Integer
Smoking Amount in grams
Retired in R8. Current Smoking Amount in grams equivalents either cigarettes pipes or cigars. Derived from GenQ Qs by DM team JAVA script. Rules: 1 cigarette = 1.25 g. 1 cheroot = 2 cigarettes 1 cigar = 3 cigarettes. Calculation: CIGARETTES*1.25 + CHEROOTS*2*1.25 + CIGARS*3*1.25 + TOBACCO/7. This variable has now been replaced with gq_sm_DER and has not been updated post R7.
Real
Smoking Amount in grams
Phase 2 data. Current Smoking Amount in grams equivalents either cigarettes pipes or cigars. Derived from GenQ Qs by DM team JAVA script. Rules: 1 cigarette = 1.25 g. 1 cheroot = 2 cigarettes 1 cigar = 3 cigarettes. Calculation: CIGARETTES*1.25 + CHEROOTS*2*1.25 + CIGARS*3*1.25 + TOBACCO/7
Real
Smoking Amount in cigarettes
Phase 2 data. Current Smoking Amount in cigarette equivalents. Derived from GenQ Qs by DM team JAVA script. Rules: 1 cigarette = 1.25 g. 1 cheroot = 2 cigarettes 1 cigar = 3 cigarettes. Calculation: CIGARETTES + CHEROOTS*2 + CIGARS*3
Integer
Smoking Duration
Retired in R8. Derived from GenQ Qs by DM team JAVA script. Current number of Years of Smoking. Blank if not calculated. Has been replaced by gq_sm_dur_DER.
Integer
Smoking Duration
Phase 2 data. Derived from GenQ Qs by DM team JAVA script. Current number of Years of Smoking. Blank if not calculated. Has been replaced by gq_sm_dur_DER.
Integer
Smoking History
Phase 2 data. Current Smoking Consumption History / Status. Data derived by DM team from GenQ Qs on smoking If number of cigarettes/ cheroots/ cigars and/ or tobacco >0 then this category gets adjusted automatically. 1 = not current (never or ex); 2 =Ex (former); 3 =Ever (former or current); 4 = Current; 9 = Not known; 0 = never;
Categorical
Smoking Type
Predominant smoking type(s). Derived from GenQ Qs by DM team JAVA script.
Categorical
Smoking type
Phase 2 data. Predominant smoking type(s). Derived from GenQ Qs by DM team JAVA script. 1 = cigarettes (chosen even if any of the other options has been ticked); 2 = cheroots-cigars (chosen if cigarettes = 0 and either cheroots or cigars >0); 9 = not known; -1 = non smoker (chosen if all of them are left blank or 0 AND smoking category = Never);
Categorical
Smoking Years Stopped
Derived from GenQ Qs by DM team JAVA script. Current number of Years Stopped Smoking. Blank if not calculated.
Integer
Smoking Years Stopped
Phase 2 data. Derived from GenQ Qs by DM team JAVA script. Current number of Years Stopped Smoking. Blank if not calculated.
Integer
Status Drinks spirits
Current Spirits Drinking Status. Derived from GenQ Qs by DM team JAVA script.
Categorical
Smoking History / Status
Current Smoking Consumption History / Status. Data derived by DM team from GenQ Qs on smoking as follows: for GQVersion1 code 1 applies to (ever smoke (ES) - other and smokes daily(D) - no and occasionally(O) - no); code 2 to (ES - yes and D - no and O - no); code 3 to (ES - yes and D -other and O - other); code 4 to either (ES - yes and (D - yes or O - yes) or (ES - no and (D - yes or O - yes); code 9 to (ES - no and (D - yes or O - yes). For GQversion 2 3 and 4 code 1 applies to (ES - other and current (C) - no); code 2 to (ES - yes and C- no); code 3 to (ES - yes and C - other); code 4 to either (ES - yes and C - yes) or (ES - other and C - yes); code 9 to either (ES - no and C - other) or (ES - other and C - other). If number of cigarettes/ cheroots/ cigars and/ or tobacco >0 then this category gets adjusted automatically. The data in this variable is slightly different from data in gq_sm_DER since different definitions for the answers have been applied.
Categorical
Spirits Drinking Status weekend
Phase 2 data. Current Spirits Drinking Status on fri-sat-sun. Derived from GenQ Qs by DM team JAVA script. 1 = yes does drink spirits; 9 = not known; 0 = no does not drink spirits;
Categorical
Spirits drinking status weekday
Phase 2 data. Current Spirits Drinking Status on mon-tue-wed-thu. Derived from GenQ Qs by DM team JAVA script. 1 = yes does drink spirits; 9 = not known; 0 = no does not drink spirits;
Categorical
SplitPI3233 CLEANED
Heparin 32-33 Split proinsulin measurement CLEANED in pmol/l. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: 1.25.
Categorical
SplitPI3233 CLEANED Comment
Heparin 32-33 Split proinsulin measurement CLEANED comment (on threshold).
Text
SplitPI3233 CLEANED Threshold
Heparin 32-33 Split proinsulin measurement CLEANED Threshold.
Categorical
Serum TIBC CLEANED
Serum TIBC (Total Iron Binding Capacity) measured in umol/L CLEANED. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: no verified threshold available.
Categorical
G_TIBC_Com
TIBC measurement CLEANED comment (on threshold).
Text
G_TIBC_Threshold
TIBC measurement CLEANED Threshold.
Categorical
Serum Transferrin CLEANED
Serum transferrin measured in g/L CLEANED. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: no verified threshold available.
Categorical
Serum Transferrin CLEANED Comment
Serum transferrin measurement CLEANED comment (on threshold).
Text
Serum Transferrin Threshold
Serum transferrin measurement CLEANED Threshold.
Categorical
Urine Albumin CLEANED
Urine Albumin measurement CLEANED. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: 2.5.
Categorical
Urine Albumin CLEANED Comment
Urine Albumin measurement CLEANED comment (on threshold).
Text
Cln variable: Urine Albumin cmnt
Phase 2 data. Urine Albumin measurement CLEANED comment (on threshold).
Text
Cln variable: UrAlbumin measurement
Phase 2 data. Urine Albumin measurement CLEANED. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: 2.5. -88.8 = measured but results below threshold value;
Real
Urine Albumin CLEANED Threshold
Urine Albumin measurement CLEANED Threshold.
Categorical
Cln variable: Ur Albumin threshold
Phase 2 data. Urine Albumin measurement CLEANED Threshold. 1 = Average value; 2 = value less than threshold; 3 = Single value; -1 = Blank (not measured); -2 = sample problem; -3 = Interference; -4 = Unsuitable; -5 = Insufficient; -9 = Everything else; 0 = No sample;
Categorical
Urine Creatinine CLEANED
Urine Creatinine measurement CLEANED in mmol/l. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: none.
Categorical
Urine Creatinine CLEANED Comment
Urine Creatinine measurement CLEANED comment (on threshold).
Text
Cln variable: UrCreatinine cmnt
Phase 2 data. Urine Creatinine measurement CLEANED comment (on threshold).
Text
Cln variable: Urine Creatinine
Phase 2 data. Urine Creatinine measurement CLEANED in mmol/l. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: none. -88.8 = measured but results below threshold value;
Real
Urine Creatinine CLEANED Threshold
Urine Creatinine measurement CLEANED Threshold.
Categorical
Cln variable:UrCreatinine threshold
Phase 2 data. Urine Creatinine measurement CLEANED Threshold. 1 = Average value; 2 = value less than threshold; 3 = Single value; -1 = Blank (not measured); -2 = sample problem; -3 = Interference; -4 = Unsuitable; -5 = Insufficient; -9 = Everything else; 0 = No sample;
Categorical
G_VitaminCResult
Vitamin C Result CLEANED in umol/l. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: 10.
Categorical
G_VitaminCResult_Com
Vitamin C Result CLEANED comment (on threshold).
Text
G_VitaminCResult_Com
Vitamin C Result CLEANED comment (on threshold).
Text
G_VitaminCResult
Vitamin C Result CLEANED in umol/l. Left blank if not measured (reason provided in Threshold variable). (note on threshold value provided in Comment variable). Lower threshold: 10.
Real
G_VitaminCResult_Threshold
Vitamin C Result CLEANED Threshold.
Categorical
G_VitaminCResult_Threshold
Vitamin C Result CLEANED Threshold.
Categorical
Status Drinks wine
Current Wine Drinking Status. Derived from GenQ Qs by DM team JAVA script.
Categorical
Wine Drinking Status weekend
Phase 2 data. Current Wine Drinking Status on fri-sat-sun. Derived from GenQ Qs by DM team JAVA script. 1 = yes does drink wine; 9 = not known; 0 = no does not drink wine;
Categorical
Wine drinking status weekday
Phase 2 data. Current Wine Drinking Status on mon-tue-wed-thu. Derived from GenQ Qs by DM team JAVA script. 1 = yes does drink wine; 9 = not known; 0 = no does not drink wine;
Categorical
OLINK assay HAGH
Phase 1 OLINK assay data for target HAGH in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Hand Grip Exclusion Check
Phase 2 data. Hand grip safety check done before hand grip test?. 0 = no; 1 = yes;
Categorical
OLINK assay HAOX1
Phase 1 OLINK assay data for target HAOX1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
None
Indication if any data is available from the Core exome (InfiniumCoreExome-24v1 chip) chip. This includes any for whom the data actually failed data QC.
Categorical
Has Exome Data
Has participant got Exome data. Use this to check which magicid actually has GWAS data (having an exomeid does not guarantee having Illumina exome chip data).
Categorical
Has GWAS Data
Has participant got GWAS data. Use this to check which magicid actually has GWAS data (having a magicid does not guarantee having Affymetrix 500K GWAS data).
Categorical
Has Metabochip data
Has participant got Metabo chip data. Use this to check which metabo actually has metabo data (having a metabo does not guarantee having Illumina cardio metabochip data).
Categorical
OLINK assay HAVCR2
Phase 1 OLINK assay data for target HAVCR2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Hba1C O_MM
Hba1C measurement taken at 0 minutes in mmol (IFCC output). Participants will either have Hba1C0_MM or Hba1C0_PC depending on when they are tested earlier on in the study the lab measured Hba1C0 in percentage. Later on in the study it was measured in mmol) You should therefore request Hba1C_PC too (more volunteers have Hba1C measured in % then in mmol n=7860+ and n=4460+ resp). To get a full set of data you will need to convert the data in the Hba1C0_PC to mmol.
Real
Hba1C0 MM
Phase 2 data. Hba1C measurement taken at 0 minutes in mmol (IFCC output). Participants will either have Hba1C0_MM or Hba1C0_PC depending on when they are tested earlier on in the study the lab measured Hba1C0 in percentage
Real
Hba1C O_%
Hba1C measurement taken at 0 minutes as a percentage (DCCT output) . Participants will either have Hba1C0_MM or Hba1C0_PC depending on when they are tested (earlier on in the study the lab measured Hba1C0 in percentage. Later on in the study it was measured in mmol) so you should request Hba1C_MM too (more volunteers have Hba1C measured in % then in mmol n=7860+ and n=4460+ resp). To get a full set of data you will need to convert the data in the Hba1C0_MM to percentage.
Real
Hba1C0 in percentage
Phase 2 data. Hba1C measurement taken at 0 minutes as a percentage (DCCT output) . Participants will either have Hba1C0_MM or Hba1C0_PC depending on when they are tested (earlier on in the study the lab measured Hba1C0 in percentage
Real
OLINK assay HB-EGF
Phase 1 OLINK assay data for target HB-EGF in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay HCLS1
Phase 1 OLINK assay data for target HCLS1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay HDGF
Phase 1 OLINK assay data for target HDGF in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
HDL 0 minutes
Serum HDL cholesterol measurement taken at 0 minutes in mmol/l
Real
HDL 0 minutes
Phase 2 data. Serum HDL cholestrol measurement taken at 0 minutes in mmol/l
Real
Hours of Digging shovelling or chopping wood
Please indicate the average length of time (in hours) you spent doing the activity per episode. Digging shovelling or chopping wood.
Integer
Hours of Digging shovelling or chopping wood CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Digging shovelling or chopping wood. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Heavy gardening hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Digging shovelling or chopping wood. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Heavy gardening hrs
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Digging shovelling or chopping wood. -1 = left blank. DO NOT USE THIS VARIABLE. Use HeavyGardeningHr_CLEAN_P2 instead.
Real
Minutes of Digging shovelling or chopping wood
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Digging shovelling or chopping wood.
Integer
Minutes of Digging shovelling or chopping wood CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Digging shovelling or chopping wood. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Heavy gardening min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Digging shovelling or chopping wood. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Heavy gardening min
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Digging shovelling or chopping wood. -1 = left blank. DO NOT USE THIS VARIABLE. Use HeavyGardeningMin_CLEAN_P2 instead.
Real
Frequency of Digging shovelling or chopping wood CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Heavy Gardening - Digging shovelling or chopping wood. Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
heavyGardening_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for Digging shovelling or chopping wood
Real
Cln variable: Heavy Gardening
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Heavy Gardening - Digging shovelling or chopping wood. Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
HeavyGardening_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Heavy Gardening - Digging shovelling or chopping wood. Data normalised to DE template 1 data.
Categorical
Heavy gardening
Phase 2 data. Questionnaire reads D13. Please indicate the average length of time (in hours) you spent doing the activity per episode. Digging shovelling or chopping wood. DO NOT USE THIS VARIABLE. Use HeavyGardening_CLEAN_P2 instead.
Real
Heavy Gardening
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Heavy Gardening - Digging shovelling or chopping wood. Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Digging shovelling or chopping wood DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Heavy Gardening - Digging shovelling or chopping wood. Data entered using data entry template with 1-2-3-4-5-6-7 codes . This data cannot be compared with data in HeavyGardening_T2. Instead use HeavyGardening_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Digging shovelling or chopping wood DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Heavy Gardening - Digging shovelling or chopping wood. Data entered using data entry template with 1-3-4-5-6-7-8 codes . This data cannot be compared with data in HeavyGardening_T1. Instead use HeavyGardening_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Hemocue 1
First Hemocue glucose measurement taken at 0 minutes.
Real
Hemocue 120
Hemocue glucose measurement taken at 120 minutes.
Real
Hemocue 120
Phase 2 data. Hemocue glucose measurement taken at 120 minutes. mmol/l
Real
Hemocue 1
Phase 2 data. First Hemocue glucose measurement taken at 0 minutes.
Real
Hemocue 2
Second Hemocue glucose measurement taken at 0 minutes.
Real
Hemocue 2
Phase 2 data. Second Hemocue glucose measurement taken at 0 minutes.
Real
Hemocue 3
Third Hemocue glucose measurement taken at 0 minutes.
Real
Hemocue 3
Phase 2 data. Third Hemocue glucose measurement taken at 0 minutes. mmol/l
Real
Hemocue Used
Indication whether or not a hemocue test was used 0 = no; -1 = yes;
Categorical
Hemocue Used
Phase 2 data. Indication whether or not a hemocue test was used 0 = no; -1 = yes;
Categorical
OLINK assay HEXIM1
Phase 1 OLINK assay data for target HEXIM1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Hexose_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable Hexose_raw. All values below detection limit set to 0. -7 = Internal standard undetectable (Concentration unreliable). The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. valid=1 LoD=20. 2nd and final QC step on this var created new and final var BIOR_140.
Real
OLINK assay HGF
Phase 1 OLINK assay data for target HGF in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay HGF
Phase 1 OLINK assay data for target HGF in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Land use mix
Herfindahl-Hirschman Index: A measure of how mixed the land uses in a neighbourhood are. There were 5 possible land uses contained in a neighbourhood; including residential; commercial; institutional/governmental; recreational and mixed landuses. (Range: 0 to 10000; 10000=least mixed; 0=most mixed) HHI = Sk(pk*100)^2 p is the proportion of land area devoted to the specific land use (k) in each buffer. As for the LUM entropy score; the proportions (pk) were calculated as the land area devoted to a specific land use divided by the total area of walkable land uses in each buffer. Note: LUM=10;000 (i.e. no mix) if none or only one of the relevant land uses fell into the buffer. Data Source: OS MasterMap Topography Layer Data (December 2016) AddressBase Premium Data (OS Managed GB Set)
Real
His_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable His_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. 2nd and final QC step on this var created new and final var BIOA_009.
Real
Histamine_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable Histamine_raw. All values below detection limit set to 0. -7 = Internal standard undetectable (Concentration unreliable). The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. 2nd and final QC step on this var created new and final var .
Real
OLINK assay hK11
Phase 1 OLINK assay data for target hK11 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay hK14
Phase 1 OLINK assay data for target hK14 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay hK8
Phase 1 OLINK assay data for target hK8 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Land use mix P2
Phase 2 data: Herfindahl-Hirschman Index: A measure of how mixed the land uses in a neighbourhood are. There were 5 possible land uses contained in a neighbourhood; including residential; commercial; institutional/governmental; recreational and mixed landuses. (Range: 0 to 10000; 10000=least mixed; 0=most mixed) HHI = Sk(pk*100)^2 p is the proportion of land area devoted to the specific land use (k) in each buffer. As for the LUM entropy score; the proportions (pk) were calculated as the land area devoted to a specific land use divided by the total area of walkable land uses in each buffer. Note: LUM=10;000 (i.e. no mix) if none or only one of the relevant land uses fell into the buffer. Data Source: OS MasterMap Topography Layer Data (December 2016) AddressBase Premium Data (OS Managed GB Set)
Real
OLINK assay HMOX2
Phase 1 OLINK assay data for target HMOX2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay HNMT
Phase 1 OLINK assay data for target HNMT in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Home
Participant postcode phase 1 is valid and lives within the study area of Cambridgeshire (1=yes; 2=no)
Categorical
Home postcode
What is the postcode for your home address? Data as entered by the participant.
Text
Home postcode CLEANED
Home postcode as entered by participant CLEANED
Text
Home postcode DERIVED
Home postcode as derived by PA team from home address data provided by participant using google.
Text
Home postcode
Phase 2 data. Questionnaire reads D12. What is the postcode for your home address? Data as entered by the participant. -1 = left blank
Text
HOMEtime
HOMEtime. Derived Intermediate not for general release. Data can be provided if necessary.
Real
HomeWorker
Created by PA team to facilitate data cleaning. Data can be provided if needed. Indication of wether the participant works from home or not.
Categorical
HOME_ACTMETS
Home domain activity energy expenditure [net METhrs/d]
Real
Home domain AEE
Phase 2 data. Derived with method 2. Home domain activity energy expenditure net METhrs/d
Real
Home_district
Random unique value for home postcode district in phase 1. Duplicate values indicate that home postcode is in the same postcode district (i.e. that participants are clustered within districts). -1 is missing home postcode
Integer
Uniuqe value for home postcode district
Phase 2 data. Random unique value for home postcode district in Phase 2 data. Duplicate values indicate that home postcode is in the same postcode district (i.e. that participants are clustered within districts). -1 is missing home postcode
Integer
HOME_METS
Home domain energy expenditure [METhrs/d]
Real
Home domain energy expenditure
Phase 2 data. Derived with method 2. Home domain energy expenditure METhrs/d
Real
Participant postcode
Phase 2 data. Participant postcode phase 2 is valid and lives within the study area of Cambridgeshire (1=yes; 2=no; -9=missing as participant declined to participate)
Categorical
HOME_PAEE
Home domain activity energy expenditure [kJ/kg/d]
Real
Home domain PAEE
Phase 2 data. Derived with method 2. Home domain activity energy expenditure kJ/kg/d
Real
Home_sector
Random unique value for home postcode sector in phase 1. Duplicate values indicate that home postcode is in the same postcode sector (i.e. that participants are clustered within sectors). -1 is missing home postcode
Integer
Unique value for home postcode sector
Phase 2 data. Random unique value for home postcode sector in Phase 2 data. Duplicate values indicate that home postcode is in the same postcode sector (i.e. that participants are clustered within sectors). -1 is missing home postcode
Integer
Home_Supermarket
Count of supermarkets within a 1 mile Eucladian distance of participants home Fenland phase 1 (-9 = missing)
Integer
Cnt of supermarkets 1 mile Pts home
Phase 2 data. Count of supermarkets within a 1 mile Eucladian distance of participants' home Fenland phase 2 (-9 = missing)
Integer
Home_Takeaway
Count of takeaways within a 1 mile Eucladian distance of participants home Fenland phase 1 (-9 = missing)
Integer
Cnt of takeaways 1 mile Pts home
Phase 2 data. Count of takeaways within a 1 mile Eucladian distance of participants' home Fenland phase 2 (-9 = missing)
Integer
Hours of Horse riding
Please indicate the average length of time (in hours) you spent doing the activity per episode. Horse riding.
Integer
Hours of Horse riding CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Horse riding. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Horse riding hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Horse riding. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Horse riding hrs
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in hours) you spent doing the activity per episode. Horse riding. -1 = left blank. DO NOT USE THIS VARIABLE. Use HorseBasedHr_CLEAN_P2 instead.
Real
Minutes of Horse riding
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Horse riding.
Integer
Minutes of Horse riding CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Horse riding. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Horse riding min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Horse riding. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Horse riding min
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Horse riding. -1 = left blank. DO NOT USE THIS VARIABLE. Use HorseBasedMin_CLEAN_P2 instead.
Real
Frequency of Horse riding CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Horse riding. Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
horseBased_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for Horse riding
Real
Cln variable: Horse riding
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Horse riding. Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
HorseBased_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Horse riding. Data normalised to DE template 1 data.
Categorical
Horse riding
Phase 2 data. Questionnaire reads D14. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Horse riding. DO NOT USE THIS VARIABLE. Use HorseBased_CLEAN_P2 instead.
Real
Horse riding
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Horse riding. Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Horse riding DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Horse riding. Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in HorseBased_T2. Instead use HorseBased_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Horse riding DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Horse riding. Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in HorseBased_T1. Instead use HorseBased_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
OLINK assay hOSCAR
Phase 1 OLINK assay data for target hOSCAR in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Pt relocated home postcode
Phase 2 data. Participant relocated as home postcode differed between phases 1 and 2 (-9 = missing; 1 = not relocated 2 = relocated)
Categorical
OLINK assay HO-1
Phase 1 OLINK assay data for target HO-1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay HPGDS
Phase 1 OLINK assay data for target HPGDS in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
None
Has the heart rate (actiheart) monitor been entered?
HR Actiheart Entered
Phase 2 data. Heart Rate and Achtiheart data entered? 0 = no; 1 = yes;
Categorical
OLINK assay HS3ST3B1
Phase 1 OLINK assay data for target HS3ST3B1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay HS6ST1
Phase 1 OLINK assay data for target HS6ST1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay HSD11B1
Phase 1 OLINK assay data for target HSD11B1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay HSP90B1
Phase 1 OLINK assay data for target HSP90B1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay HSP 27
Phase 1 OLINK assay data for target HSP 27 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
hs_CRP
Serum biomarker hs_CRP measurement (Serum levels of C-reactive protein measured with high-sensitivity system). Raw data; lower detection limit is 10 mg/l. Cleaned data provided in variable G_hs_CRP with x_Threshold and x_Com variables provided for clarification. Only measured on 10000+ Fenland volunteers so far as it is not part of the routine set of measurements.
Real
OLINK assay HTRA2
Phase 1 OLINK assay data for target HTRA2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Hours of fishing CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Fishing. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Hours of fishing
Please indicate the average length of time (in hours) you spent doing the activity per episode. Fishing.
Integer
Cln variable: Hunting hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Hunting shooting fishing. Error codes cleand by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Hunting Shooting Fishing hrs
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in hours) you spent doing the activity per episode. Fishing. -1 = left blank. DO NOT USE THIS VARIABLE. Use HuntingShootingFishingHr_CLEAN_P2 instead.
Real
Minutes of fishing
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Fishing.
Integer
Cln variable: Hunting min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Hunting shooting fishing. Error codes cleand by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Hunting Shooting Fishing min
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Fishing. -1 = left blank. DO NOT USE THIS VARIABLE. Use HuntingShootingFishingMin_CLEAN_P2 instead.
Real
Cln variable: Hunting
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Hunting shooting fishing. Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
HuntingShootingFishing_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Fishing. Data normalised to DE template 1 data.
Categorical
Hunting Shooting Fishing
Phase 2 data. Questionnaire reads D14. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Fishing. DO NOT USE THIS VARIABLE. Use HuntingShootingFishing_CLEAN_P2 instead.
Real
Fishing
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Fishing. Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of fishing DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Fishing. Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in HuntingShootingFishing_T2. Instead use HuntingShootingFishing_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of fishing DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Fishing. Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in HuntingShootingFishing_T1. Instead use HuntingShootingFishing_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Minutes of fishing CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Fishing. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Frequency of fishing CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Fishing. Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
huntingShootingFish_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for fishing
Real
None
Hybridization control scale factor
Real
Hybridization control scale factor
Phase 2 data. Hybridization control scale factor
Real
OLINK assay ICA1
Phase 1 OLINK assay data for target ICA1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ICAM1
Phase 1 OLINK assay data for target ICAM1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ICAM3
Phase 1 OLINK assay data for target ICAM3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ICAM-2
Phase 1 OLINK assay data for target ICAM-2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Hours of Ice-Skating
Please indicate the average length of time (in hours) you spent doing the activity per episode. Ice-Skating.
Integer
Hours of Ice-Skating CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Ice-Skating. Error codes cleand by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Ice-Skating hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Ice-Skating. Error codes cleand by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Ice or roller skating hrs
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in hours) you spent doing the activity per episode. Ice-Skating. -1 = left blank.DO NOT USE THIS VARIABLE. Use iceSkatingHr_CLEAN_P2 instead.
Real
Minutes of Ice-Skating
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Ice-Skating.
Integer
Minutes of Ice-Skating CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Ice-Skating. Error codes cleand by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Ice-Skating min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Ice-Skating. Error codes cleand by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Ice or roller skating min
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Ice-Skating. -1 = left blank.DO NOT USE THIS VARIABLE. Use iceSkatingMin_CLEAN_P2 instead.
Real
Frequency of Ice-Skating CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Ice-Skating. Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
iceSkating_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for Ice-Skating
Real
Cln variable: Ice-Skating
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Ice-Skating. Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
iceSkating_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Ice-Skating. Data normalised to DE template 1 data.
Categorical
Ice or roller skating
Phase 2 data. Questionnaire reads D14. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Ice or roller skating. DO NOT USE THIS VARIABLE. Use iceSkating_CLEAN_P2 instead.
Real
Ice-Skating
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Ice-Skating. Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Ice-Skating DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Ice-Skating. Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in iceSkating_T2. Instead use iceSkating_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Ice-Skating DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Ice-Skating. Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in iceSkating_T1. Instead use iceSkating_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
OLINK assay ICOSLG
Phase 1 OLINK assay data for target ICOSLG in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
iDEXA Height measurement in centimetres
New in R7. Height measurement in centimetres. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Direct comparison with study support data.
Real
iDEXA Height measurement
Phase 2 data. Height measurement in centimetres. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Direct comparison with study support data.
Real
iDEXA Weight measurement in kilograms
New in R7. Weight measurement in kilograms. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Direct comparison with study support data.
Real
iDEXA Weight measurement
Phase 2 data. Weight measurement in kilograms. Raw data from DEXA Lunar Prodigy reprocessed with iDEXA software. Calculation and or check: Direct comparison with study support data.
Real
iDEXA App lean mass
New in R7. Data derived by data management team by adding up data for AD15i_iDEXA_arms_lean_mass and AD39i_iDEXA_legs_lean_mass and rounding to 2 decimals.
Integer
iDEXA App lean mass
Phase 2 data. Data derived by data management team by adding up data for AD15i_iDEXA_arms_lean_mass and AD39i_iDEXA_legs_lean_mass and rounding to 2 decimals.
Integer
iDEXA Periph fat mass
New in R7. Data derived by data management team by adding up data for AD14i_iDEXA_arms_fat_mass and AD38i_iDEXA_legs_fat_mass and rounding to 2 decimals.
Integer
iDEXA Periph fat mass
Phase 2 data. Data derived by data management team by adding up data for AD14i_iDEXA_arms_fat_mass and AD38i_iDEXA_legs_fat_mass and rounding to 2 decimals.
Integer
OLINK assay IDUA
Phase 1 OLINK assay data for target IDUA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IFI30
Phase 1 OLINK assay data for target IFI30 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IFNL1
Phase 1 OLINK assay data for target IFNL1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IFNLR1
Phase 1 OLINK assay data for target IFNLR1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IFN-gamma
Phase 1 OLINK assay data for target IFN-gamma in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IFN-gamma-R1
Phase 1 OLINK assay data for target IFN-gamma-R1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IGF1R
Phase 1 OLINK assay data for target IGF1R in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IGF2R
Phase 1 OLINK assay data for target IGF2R in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IGFBP3
Phase 1 OLINK assay data for target IGFBP3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IGFBP6
Phase 1 OLINK assay data for target IGFBP6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IGFBPL1
Phase 1 OLINK assay data for target IGFBPL1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IGFBP-1
Phase 1 OLINK assay data for target IGFBP-1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IGFBP-2
Phase 1 OLINK assay data for target IGFBP-2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IGFBP-7
Phase 1 OLINK assay data for target IGFBP-7 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IgG Fc receptor II-b
Phase 1 OLINK assay data for target IgG Fc receptor II-b in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IGLC2
Phase 1 OLINK assay data for target IGLC2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IGSF3
Phase 1 OLINK assay data for target IGSF3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IKZF2
Phase 1 OLINK assay data for target IKZF2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL10
Phase 1 OLINK assay data for target IL10 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL10
Phase 1 OLINK assay data for target IL10 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL12RB1
Phase 1 OLINK assay data for target IL12RB1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL12
Phase 1 OLINK assay data for target IL12 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL13RA1
Phase 1 OLINK assay data for target IL13RA1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL13
Phase 1 OLINK assay data for target IL13 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL15
Phase 1 OLINK assay data for target IL15 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL16
Phase 1 OLINK assay data for target IL16 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL17RB
Phase 1 OLINK assay data for target IL17RB in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL18
Phase 1 OLINK assay data for target IL18 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL18
Phase 1 OLINK assay data for target IL18 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL1RL2
Phase 1 OLINK assay data for target IL1RL2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL2
Phase 1 OLINK assay data for target IL2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL2-RA
Phase 1 OLINK assay data for target IL2-RA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL32
Phase 1 OLINK assay data for target IL32 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL33
Phase 1 OLINK assay data for target IL33 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL3RA
Phase 1 OLINK assay data for target IL3RA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL4
Phase 1 OLINK assay data for target IL4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL5
Phase 1 OLINK assay data for target IL5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL5
Phase 1 OLINK assay data for target IL5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL6
Phase 1 OLINK assay data for target IL6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL6
Phase 1 OLINK assay data for target IL6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL6
Phase 1 OLINK assay data for target IL6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL6
Phase 1 OLINK assay data for target IL6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL7R
Phase 1 OLINK assay data for target IL7R in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL7
Phase 1 OLINK assay data for target IL7 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL8
Phase 1 OLINK assay data for target IL8 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Ile_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable Ile_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. 2nd and final QC step on this var created new and final var BIOA_010.
Real
OLINK assay ILKAP
Phase 1 OLINK assay data for target ILKAP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-10RA
Phase 1 OLINK assay data for target IL-10RA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-10RB
Phase 1 OLINK assay data for target IL-10RB in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-12B
Phase 1 OLINK assay data for target IL-12B in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-15RA
Phase 1 OLINK assay data for target IL-15RA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-17A
Phase 1 OLINK assay data for target IL-17A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-17C
Phase 1 OLINK assay data for target IL-17C in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-17D
Phase 1 OLINK assay data for target IL-17D in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-17RA
Phase 1 OLINK assay data for target IL-17RA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-18BP
Phase 1 OLINK assay data for target IL-18BP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-18R1
Phase 1 OLINK assay data for target IL-18R1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-1ra
Phase 1 OLINK assay data for target IL-1ra in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-1RT1
Phase 1 OLINK assay data for target IL-1RT1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-1RT2
Phase 1 OLINK assay data for target IL-1RT2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-1 alpha
Phase 1 OLINK assay data for target IL-1 alpha in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-20RA
Phase 1 OLINK assay data for target IL-20RA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-20
Phase 1 OLINK assay data for target IL-20 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-22 RA1
Phase 1 OLINK assay data for target IL-22 RA1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-24
Phase 1 OLINK assay data for target IL-24 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-27
Phase 1 OLINK assay data for target IL-27 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-2RB
Phase 1 OLINK assay data for target IL-2RB in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-4RA
Phase 1 OLINK assay data for target IL-4RA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-5R-alpha
Phase 1 OLINK assay data for target IL-5R-alpha in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IL-6RA
Phase 1 OLINK assay data for target IL-6RA in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
IMD 2009 subdomain barriers to housing rank
2009 IMD subdomain barriers to housing and services rank where lower ranks are more deprived. 1 is most deprived.
Integer
IMD 2009 subdomain barriers to housing score
2009 IMD subdomain barriers to housing and services score where lower scores are more deprived
Integer
IMD 2009 subdomain children rank
2009 IMD subdomain children and young people rank where lower ranks are more deprived. 1 is most deprived.
Integer
IMD 2009 subdomain children score
2009 IMD subdomain children and young people score where lower scores are more deprived
Integer
IMD 2009 subdomain crime rank
2009 IMD subdomain crime and disorder rank where lower ranks are more deprived. 1 is most deprived.
Integer
IMD 2009 subdomain crime score
2009 IMD subdomain crime and disorder score where lower scores are more deprived
Integer
None
IMD decile is England wide deprivation deciles attributed to their postcode. Decile 1 is most deprived.
Real
IMD,
IMD_decile
Phase 2 data. IMD decile is England wide deprivation deciles attributed to their postcode. Decile 1 is most deprived.
Categorical
IMD 2009 subdomain education rank
2009 IMD subdomain education skills and training rank where lower ranks are more deprived. 1 is most deprived.
Integer
IMD 2009 subdomain education score
2009 IMD subdomain education skills and training score where lower scores are more deprived
Integer
IMD 2009 subdomain employment score
2009 IMD subdomain employment score where lower scores are more deprived
Integer
IMD 2009 subdomain employment rank
2009 IMD subdomain employment rank where lower ranks are more deprived. 1 is most deprived.
Integer
IMD 2009 subdomain living env rank
2009 IMD subdomain living environment rank where lower ranks are more deprived. 1 is most deprived.
Integer
IMD 2009 subdomain living env score
2009 IMD subdomain living environment score where lower scores are more deprived
Integer
2009 IMD score directly from LSOA list
2009 IMD score retrieved from the list reporting which postcode can be found in which Lower Super Output Area (LSOA). Only use for Fenland phase 1 participants.
Integer
IMD 2009 subdomain geographical barriers rank
2009 IMD subdomain geographical barriers rank where lower ranks are more deprived. 1 is most deprived.
Integer
IMD 2009 subdomain geograpical barriers score
2009 IMD subdomain geographical barriers score where lower scores are more deprived
Integer
IMD 2009 subdomain health deprivation rank
2009 IMD subdomain health deprivation and disability rank where lower ranks are more deprived. 1 is most deprived.
Integer
IMD 2009 subdomain health deprivation score
2009 IMD subdomain health deprivation and disability score where lower scores are more deprived
Integer
IMD 2009 subdomain IDACI rank
2009 IMD subdomain Income Deprivation Affecting Children Index (IDACI) rank where lower ranks are more deprived. 1 is most deprived.
Integer
IMD 2009 subdomain IDACI score
2009 IMD subdomain Income Deprivation Affecting Children Index (IDACI) score where lower scores are more deprived
Integer
IMD 2009 subdomain IDAOPI rank
2009 IMD subdomain Income Deprivation Affecting Older People Index (IDAOPI) rank where lower ranks are more deprived. 1 is most deprived.
Integer
IMD 2009 subdomain IDAOPI score
2009 IMD subdomain Income Deprivation Affecting Older People Index (IDAOPI) score where lower scores are more deprived
Integer
IMD 2009 subdomain income rank
2009 IMD subdomain income rank where lower ranks are more deprived. 1 is most deprived.
Integer
IMD 2009 subdomain income score
2009 IMD subdomain income score where lower scores are more deprived
Integer
IMD 2009 subdomain indoors rank
2009 IMD subdomain indoors rank where lower ranks are more deprived. 1 is most deprived.
Integer
IMD 2009 subdomain indoors score
2009 IMD subdomain indoors score where lower scores are more deprived
Integer
IMD 2009 subdomain outdoors rank
2009 IMD subdomain outdoors rank where lower ranks are more deprived. 1 is most deprived.
Integer
IMD 2009 subdomain outdoors score
2009 IMD subdomain outdoors score where lower scores are more deprived
Integer
None
IMD rank is the England-wide ranking of the LSOA in which each postcode is located where a lower rank is more deprived (i.e. 1 is most deprived). This variable would allow anyone accessing the data to create their own relative measure of deprivation (e.g. quintiles) within the Fenland cohort.
Real
IMD,
2009 IMD score
2009 IMD rank based on IMD score linking phase 1 participants home postcode unit to LSOA area. Lower ranks are more deprived. IMD information was retrieved from https://www.gov.uk/government/statistics/english-indices-of-deprivation-2019. Only use for Fenland phase 1 participants.
Integer
IMD_rank
Phase 2 data. IMD rank is the England-wide ranking of the LSOA in which each postcode is located; where a lower rank is more deprived (i.e. 1 is most deprived). This variable would allow anyone accessing the data to create their own relative measure of deprivation (e.g. quintiles) within the Fenland cohort.
Real
IMD 2009 subdomain skills rank
2009 IMD subdomain skills rank where lower ranks are more deprived. 1 is most deprived.
Integer
IMD 2009 subdomain skills score
2009 IMD subdomain skills score where lower scores are more deprived
Integer
IMD 2009 subdomain wider barriers rank
2009 IMD subdomain wider barriers rank where lower ranks are more deprived. 1 is most deprived.
Integer
IMD 2009 subdomain wider barriers score
2009 IMD subdomain wider barriers score where lower scores are more deprived
Integer
IMD work Easting
Phase 2 data. Easting for phase 2 work postcode based on Work_postcode_cleaned_P2
Real
IMD work Northing
Phase 2 data. Northing for phase 2 work postcode based on Work_postcode_cleaned_P2
Real
OLINK assay IMPA1
Phase 1 OLINK assay data for target IMPA1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Incretin protein measured
Incretin protein measured. GIP_Total - Glucose-dependent insulinotropic polypeptide (total). GLP-1_Total - Glucagon-like peptide-1 (total). Glucagon - Glucagon peptide.
Text
Intra plate variation
The Coefficient of Variation of calculated concentration between intra plate duplicates - this is calculated by the MSD software (where applicable)
Real
Mean incretin value
The mean of calculated concertation in (pg/mL) for GIP (total); and (pM) for GLP-1 (t) and Glucagon - this is calculated by the MSD software. pM = (pg/ml)/(Molecular Weight in kilodalton)
Real
ULOD per plate
Upper limit of detection (ULOD) per plate expressed in (pg/mL) for GIP (total); and (pM) for GLP-1 (t) and Glucagon; calculated by the MSD software and adjusted by the lab team with the sample dilution factor (2). pM = (pg/ml)/(Molecular Weight in kilod
Real
LLOD per plate
Lower limit of detection (LLOD) per plate expressed in (pg/mL) for GIP (total); and (pM) for GLP-1 (t) and Glucagon; calculated by the MSD software and adjusted by the lab team with the sample dilution factor (2). pM = (pg/ml)/(Molecular Weight in kilod
Real
Sample FreezeThaw Cycles
Number of times the sample was thawed
Integer
Within detection limits
The calculated concentration is within detection limits (between Lower Limit Of Detection and Upper Limit Of Detection). NOTE: Samples outside of In Detection Range have not been excluded and may be used if needed to; but technically do not pass lab QC.
Real
Increntin Plate Number
Increntin data number of the plate assigned by the lab team
Integer
Sample Timepoint
T000 minute plasma heparin aliquot - this sample was collected before OGTT test. T120 minute plasma heparin aliquot - this sample was collected after OGTT test
Text
Incretin well position
Well position within a 96-well plate
Integer
Information Sheet version date as written
Information Sheet version date (as written)
Date
Information Sheet version number
Information Sheet version number
Text
Info sheet version and date
InfoVersion. Version number and date of information sheet handed over to participant alongside consent form. This has been replaced by InfoVersion_Corrected in R8 as this data is now stored in a new variable which has version number data which has been improved. Do not use this variable anymore but use InfoVersion_Corrected instead.
InfoVersion_Corrected
New in R8. This is the same data as InfoVersion but the data in the variable has been consolidated across the study to ensure data uniformity. Use this var instead of InfoVersion
OLINK assay ING1
Phase 1 OLINK assay data for target ING1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay INHBC
Phase 1 OLINK assay data for target INHBC in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay INPPL1
Phase 1 OLINK assay data for target INPPL1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Insulin
Heparin biomarker Insulin measurement in pmol/l. Raw data; Cleaned data provide in variable G_Insulin with x_Threshold and x_Com variables provided for clarification. Lower threshold: none. Only measured on 10000+ Fenland volunteers so far as it is not part of the routine set of measurements.
Real
Insulin Raw
Phase 2 data. Heparin biomarker Insulin measurement in pmol/l. Raw data; Cleaned data provide in variable G_Insulin with x_Threshold and x_Com variables provided for clarification. Lower threshold: none. Test date is the date of visit for Fenland Phase 2 data.
Real
None
Heparin biomarker Insulin measurement at T120 in pmol/l. Raw Fenland phase 1 data; Cleaned data not yet available.
Real
None
Heparin biomarker Insulin measurement at T120 in pmol/l. Raw Fenland phase 1 data; Lab commetns on test results and sample quality.
Text
None
Heparin biomarker Insulin measurement at T120 in pmol/l. Raw Fenland phase 1 data; Date of test
Date
Int24 food survey Alcohol(g)
Phase 2 data. Intake 24 Food Intake survey - Alcohol (g)
Real
Int24 food survey food brand
Phase 2 data. Intake 24 Food Intake survey brand. Asda; Tesco; Other; N/A
Text
Int24 food survey Calcium(mg)
Phase 2 data. Intake 24 Food Intake survey - Calcium (mg)
Real
Int24 food survey Carbohydrate(g)
Phase 2 data. Intake 24 Food Intake survey - Carbohydrate (g)
Real
Int24 food survey Cholesterol(mg)
Phase 2 data. Intake 24 Food Intake survey - Cholesterol (mg)
Real
Int24 food survey Energy(kcal)
Phase 2 data. Intake 24 Food Intake survey - Energy (kcal)
Real
Int24 food survey Energy(kj)
Phase 2 data. Intake 24 Food Intake survey - Energy (kj)
Real
Int24 food survey Fat(g)
Phase 2 data. Intake 24 Food Intake survey - Fat (g)
Real
Int24 food survey Folate(µg)
Phase 2 data. Intake 24 Food Intake survey - Folate (µg)
Real
Int24 food survey food desc En
Phase 2 data. Intake 24 Food Intake survey food description in English
Text
Int24 food surv food desc local
Phase 2 data. Intake 24 Food Intake survey food description in the local language
Text
Int24 food survey food group code
Phase 2 data. Intake 24 Food Intake survey food group code. 2 = ; 4 = ; etc
Text
Int24 food surv food group desc En
Phase 2 data. Intake 24 Food Intake survey food group description in English
Text
Int24 food surv foodgrp desc local
Phase 2 data. Intake 24 Food Intake survey food group description in the local language
Text
Int24 food survey food ID
Phase 2 data. Intake 24 Food Intake survey food ID. 1 = ; 2 = ; 3 = ; 4 = ; 5 = ; 6 = ; 7 = ; 8 = ; 9 = ; 10 = ;
Real
Int24 food survey food code
Phase 2 data. Intake 24 Food Intake survey food code. Lookup table
Text
Int24 food survey Iron(mg)
Phase 2 data. Intake 24 Food Intake survey - Iron (mg)
Real
Int24 food survey food leftovers
Phase 2 data. Intake 24 Food Intake survey leftovers after meal?
Text
Int24 food surv food leftoversimage
Phase 2 data. Intake 24 Food Intake survey meal leftovers image name
Text
Int24 food survey Meal ID
Phase 2 data. Intake 24 Food Intake survey meal ID. 1 = ; 2 = ; 3 = ; 4 = ; 5 = ; 6 = ;
Real
Int24 food survey Meal name
Phase 2 data. Intake 24 Food Intake survey meal name.Choices are Afternoon snack or drink; biscuit; Biscuit; Breakfast; drink; Early snack or drink; Evening meal; evening snack or drink; Late snack or drink;
Text
Int24 food survey food desc missing
Phase 2 data. Intake 24 Food Intake survey - description of foods reported as missing. This is an optional free text field completed by participant if they report a missing food
Text
Int24 food survey amt eaten missing
Phase 2 data. Intake 24 Food Intake survey - amount eaten of foods reported as missing. This is an optional free text field completed by participant if they report a missing food. Note: we are aware that the description does not match the Field Name for this variable but the Description is correct
Text
Int24 food survey missing methods
Phase 2 data. Intake 24 Food Intake survey - cooking method of foods reported as missing. This is an optional free text field completed by participant if they report a missing food. Note: we are aware that the description does not match the Field Name for this variable but the Description is correct
Text
Int24 food survey Non-milk
Phase 2 data. Intake 24 Food Intake survey - Non-milk extrinsic sugars (g)
Real
Int24 food surv nutrient table code
Phase 2 data. Intake 24 Food Intake survey nutrient table code from nutrient lookup table recorded in INT24_nutrient_table_code
Text
Int24 food surv nutrient table name
Phase 2 data. Intake 24 Food Intake survey nutrient table name used to lookup Nutrients. NDNS only option available
Text
Int24 food survey food portion size
Phase 2 data. Intake 24 Food Intake survey meal portion size in g/ml
Real
Int24 food survey Protein(g)
Phase 2 data. Intake 24 Food Intake survey - Protein (g)
Real
Int24 food survey food ready meal
Phase 2 data. Intake 24 Food Intake survey ready meal? Yes or no
Text
Int24 food survey reasonable amount
Phase 2 data. Intake 24 Food Intake survey. Reasonable amount? Yes or no
Text
Int24 food survey Saturated fatty
Phase 2 data. Intake 24 Food Intake survey - Saturated fatty acids (g)
Real
Int24 food survey search term
Phase 2 data. Intake 24 Food Intake survey search term. Search term as entered by participant
Text
Int24 food survey Selenium(µg)
Phase 2 data. Intake 24 Food Intake survey - Selenium (µg)
Real
Int24 food surv food serving image
Phase 2 data. Intake 24 Food Intake survey food serving image
Text
Int24 food survey food serving size
Phase 2 data. Intake 24 Food Intake survey food servig size in g/ml
Real
Int24 food survey Sodium(mg)
Phase 2 data. Intake 24 Food Intake survey - Sodium (mg)
Real
Int24 food survey start time
Phase 2 data. Intake 24 Food Intake survey start time
Time
Int24 food surv submission time
Phase 2 data. Intake 24 Food Intake survey submssion time
Time
Survey ID for the Intake24 recall
Phase 2 data. A unique identifier for the Intake24 recall
Text
Int24 food surv completion time
Phase 2 data. Intake 24 Food Intake survey time taken to complete survey
Text
Int24 food survey Total sugars(g)
Phase 2 data. Intake 24 Food Intake survey - Total sugars (g)
Real
Int24 food survey Vitamin A(µg)
Phase 2 data. Intake 24 Food Intake survey - Vitamin A (µg)
Real
Int24 food survey Vitamin C(mg)
Phase 2 data. Intake 24 Food Intake survey - Vitamin C (mg)
Real
Int24 food survey Vitamin D(µg)
Phase 2 data. Intake 24 Food Intake survey - Vitamin D (µg)
Real
Int24 food survey Vitamin E(mg)
Phase 2 data. Intake 24 Food Intake survey - Vitamin E (mg)
Real
Int24 food survey Zinc(mg)
Phase 2 data. Intake 24 Food Intake survey - Zinc (mg)
Real
OLINK assay IQGAP2
Phase 1 OLINK assay data for target IQGAP2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IRAK1
Phase 1 OLINK assay data for target IRAK1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IRAK4
Phase 1 OLINK assay data for target IRAK4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay IRF9
Phase 1 OLINK assay data for target IRF9 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Serum Iron measured Raw
Serum biomarker Iron measurement in umol/L. Raw data; cleaned data provided in variable G_Iron with x_Threshold and x_Com variables provided for clarification. Only measured on 10000+ Fenland volunteers so far as it is not part of the routine set of measurements.
Real
OLINK assay ISLR2
Phase 1 OLINK assay data for target ISLR2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ITGA11
Phase 1 OLINK assay data for target ITGA11 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ITGA5
Phase 1 OLINK assay data for target ITGA5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ITGA6
Phase 1 OLINK assay data for target ITGA6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ITGAM
Phase 1 OLINK assay data for target ITGAM in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ITGAV
Phase 1 OLINK assay data for target ITGAV in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ITGB1BP1
Phase 1 OLINK assay data for target ITGB1BP1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ITGB1BP2
Phase 1 OLINK assay data for target ITGB1BP2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ITGB1
Phase 1 OLINK assay data for target ITGB1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ITGB2
Phase 1 OLINK assay data for target ITGB2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ITGB5
Phase 1 OLINK assay data for target ITGB5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ITGB6
Phase 1 OLINK assay data for target ITGB6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ITGB7
Phase 1 OLINK assay data for target ITGB7 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay ITM2A
Phase 1 OLINK assay data for target ITM2A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay JAM-A
Phase 1 OLINK assay data for target JAM-A in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay JAM-B
Phase 1 OLINK assay data for target JAM-B in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
JOBadj
JOBadj. Derived Intermediate not for general release. Data can be provided if necessary.
Hours of Jogging
Please indicate the average length of time (in hours) you spent doing the activity per episode. Jogging.
Integer
Hours of Jogging CLEANED
Please indicate the average length of time (in hours) you spent doing the activity per episode. Jogging. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Jogging hrs
Phase 2 data. Please indicate the average length of time (in hours) you spent doing the activity per episode. Jogging. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Jogging hrs
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in hours) you spent doing the activity per episode. Jogging. -1 = left blank. DO NOT USE THIS VARIABLE. Use jogHr_CLEAN_P2 instead.
Real
Minutes of Jogging
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Jogging.
Integer
Minutes of Jogging CLEANED
Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Jogging. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team.
Integer
Cln variable: Jogging min
Phase 2 data. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Jogging. Error codes cleaned by DM team with this rule: AVG_TEXT (average returned as text with no rounding). And then -10 errors cleaned by PA team. -1 = left blank.
Real
Jogging min
Phase 2 data. Questionnaire reads D14. Please indicate the average length of time (in additional minutes) you spent doing the activity per episode. Jogging. -1 = left blank. DO NOT USE THIS VARIABLE. Use jogMin_CLEAN_P2 instead.
Real
Frequency of Jogging CLEANED
Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Jogging. Error codes cleaned by DM team. And then -10 errors cleaned by PA team.
Categorical
jog_CLEAN_FRQ
New in R8. Cleaned translated frequency (per week) for Jogging
Real
Cln variable: Jogging
Phase 2 data. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Jogging. Error codes cleaned by DM team. And then -10 errors cleaned by PA team. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -9 = not completed; -10 = any text as written;
Categorical
jog_NORM
New in R7. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Jogging. Data normalised to DE template 1 data.
Categorical
Jogging
Phase 2 data. Questionnaire reads D14. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Jogging. DO NOT USE THIS VARIABLE. Use jog_CLEAN_P2 instead.
Real
Jogging
Phase 2 data. Data sources are varname_T1 and varname_T2 where the raw uncleaned data was normalised to the same data entry codes and then pooled into this new variable. Do not use. Use _CLEAN variable instead. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Jogging. Data normalised to DE template 1 data. 1 = None; 2 = once in last 4 wks; 3 = 2-3 times in last 4 wks; 4 = once a week; 5 = 2-3 times a week; 6 = 4-5 times a week; 7 = every day; -1 = left blank; -5 = more than one selected; -10 = any text as written;
Categorical
Freq of Jogging DE temp1
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Jogging. Data entered using data entry template with 1-2-3-4-5-6-7 codes. This data cannot be compared with data in jog_T2. Instead use jog_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Freq of Jogging DE temp2
New in R7. Please indicate how often (total number of times) you did the activity on average over the last 4 weeks. Jogging. Data entered using data entry template with 1-3-4-5-6-7-8 codes. This data cannot be compared with data in jog_T1. Instead use jog_Norm which contains combined raw uncleaned data from varname_T1 and varname_T2 normalised to the same data entry codes.
Categorical
Junction density
The number of three-or-more way intersections falling inside of the 800-metre street network buffers divided by the area of the buffer (km2): Data Source 2016 OS MasterMap Integrated Transport Network Layer
Real
Junction density P2
Phase 2 data: The number of three-or-more way intersections falling inside of the 800-metre street network buffers divided by the area of the buffer (km2): Data Source 2016 OS MasterMap Integrated Transport Network Layer
Real
OLINK assay JUN
Phase 1 OLINK assay data for target JUN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay JUN
Phase 1 OLINK assay data for target JUN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KAZALD1
Phase 1 OLINK assay data for target KAZALD1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KIF1BP
Phase 1 OLINK assay data for target KIF1BP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KIM1
Phase 1 OLINK assay data for target KIM1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KIM1
Phase 1 OLINK assay data for target KIM1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KIR2DL3
Phase 1 OLINK assay data for target KIR2DL3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KIRREL2
Phase 1 OLINK assay data for target KIRREL2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KIT
Phase 1 OLINK assay data for target KIT in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KLB
Phase 1 OLINK assay data for target KLB in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KLK10
Phase 1 OLINK assay data for target KLK10 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KLK12
Phase 1 OLINK assay data for target KLK12 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KLK13
Phase 1 OLINK assay data for target KLK13 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KLK6
Phase 1 OLINK assay data for target KLK6 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KLRD1
Phase 1 OLINK assay data for target KLRD1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KPNA1
Phase 1 OLINK assay data for target KPNA1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KRT19
Phase 1 OLINK assay data for target KRT19 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay KYAT1
Phase 1 OLINK assay data for target KYAT1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Kynurenine_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable Kynurenine_raw. All values below detection limit set to 0. -7 = Internal standard undetectable (Concentration unreliable). The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD. 2nd and final QC step on this var created new and final var BIOA_027.
Real
OLINK assay KYNU
Phase 1 OLINK assay data for target KYNU in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LAG3
Phase 1 OLINK assay data for target LAG3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LAIR1
Phase 1 OLINK assay data for target LAIR1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LAIR-2
Phase 1 OLINK assay data for target LAIR-2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LAMA4
Phase 1 OLINK assay data for target LAMA4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LAMP3
Phase 1 OLINK assay data for target LAMP3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LAP TGF-beta-1
Phase 1 OLINK assay data for target LAP TGF-beta-1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LAT2
Phase 1 OLINK assay data for target LAT2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LAT
Phase 1 OLINK assay data for target LAT in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LAYN
Phase 1 OLINK assay data for target LAYN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LCN2
Phase 1 OLINK assay data for target LCN2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
LDL 0 minutes
Serum LDL cholesterol (calculated) at 0 minutes in mmol/l
Real
LDL 0 minutes
Phase 2 data. Serum LDL cholestrol (calculated) at 0 minutes in mmol/l
Real
OLINK assay LDL receptor
Phase 1 OLINK assay data for target LDL receptor in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
LEISadj
LEISadj. Derived Intermediate not for general release. Data can be provided if necessary.
Real
LEIStime
LEIStime. Derived Intermediate not for general release. Data can be provided if necessary.
Real
LEIS_ACTMETS
Leisure domain activity energy expenditure [net METhrs/d]
Real
Leisure domain AEE
Phase 2 data. Derived with method 2. Leisure domain activity energy expenditure net METhrs/d
Real
LEIS_METS
Leisure domain energy expenditure [METhrs/d]
Real
Leisure domain energy expenditure
Phase 2 data. Derived with method 2. Leisure domain energy expenditure METhrs/d
Real
LEIS_PAEE
Leisure domain activity energy expenditure [kJ/kg/d]
Real
Leisure domain PAEE
Phase 2 data. Derived with method 2. Leisure domain activity energy expenditure kJ/kg/d
Real
OLINK assay LEPR
Phase 1 OLINK assay data for target LEPR in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Serum Leptin RAW
Serum biomarkjer Leptin measurement RAW in ng/ml. Raw data; cleaned data provided in variable G_Leptin with x_Threshold and x_Com variables provided for clarification. Only measured on 10000+ Fenland volunteers so far as it is not part of the routine set of measurements.
Real
None
Lab comments relating to samples used for Leptin/Adiponectin analysis for phase 1
Text
Serum Leptin RAW
Phase 2 data. Leptin measurement for phase 2 sample. Only has data for 10 samples which were part of the PPARA set. Serum biomarker Leptin measurement RAW in ng/ml. Raw data; cleaned data provided in variable G_Leptin with x_Threshold and x_Com variables provided for clarification.
Real
None
Repeat leptin analysis (in ng/ml) of stored sample for those phase 1 volunteers whose leptin measurements were 3 SD below the mean of their body fat percent catagory. -1 = repeat sample not requested; -7 = required sample is missing
Categorical
None
Comments made by the lab on the quality of the sample being analysed.
Text
OLINK assay LEP
Phase 1 OLINK assay data for target LEP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Leu_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable Leu_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. 2nd and final QC step on this var created new and final var BIOA_011.
Real
OLINK assay LGALS7
Phase 1 OLINK assay data for target LGALS7 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LGMN
Phase 1 OLINK assay data for target LGMN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LHB
Phase 1 OLINK assay data for target LHB in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LIF
Phase 1 OLINK assay data for target LIF in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LIF-R
Phase 1 OLINK assay data for target LIF-R in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
LIGHTtime
Time spent at light intensity activity [hrs/d]
Real
LIGHT_INTENSITY
Light intensity energy expenditure [METhrs/d]
Real
OLINK assay LILRA5
Phase 1 OLINK assay data for target LILRA5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LILRB1
Phase 1 OLINK assay data for target LILRB1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LILRB2
Phase 1 OLINK assay data for target LILRB2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LILRB4
Phase 1 OLINK assay data for target LILRB4 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LILRB5
Phase 1 OLINK assay data for target LILRB5 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
lipid_lowering
Phase 2 data. Binary variable indicating whether a drug from the lipid lowering agent class was prescribed. 0: No 1: Yes
Categorical
None
Liver scan done? Data from study database. Please note this variable is not complete as it was not available at the start of the study and data should not be used for analysis.
Categorical
Liver Scan Done
Phase 2 data. Liver scan done? Data from study database. Please note this variable is not complete as it was not available at the start of the study and data should not be used for analysis. 1 = yes; 0 = no;
Categorical
Liver Score Taken
Phase 2 data. Liver Score Taken? From Study Database. Do not release. Use liver score variables from Anthro team 0 = no; 1 = yes;
Categorical
Lost epochs
Total number of lost epochs during free living (first wear of Actiheart only) [For quality of trace information]
Integer
OLINK assay LOX-1
Phase 1 OLINK assay data for target LOX-1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
None
Lipid profile obtained by negative mode ionisation high resolution mass spectrometry.
Real
OLINK assay LPL
Phase 1 OLINK assay data for target LPL in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LRIG1
Phase 1 OLINK assay data for target LRIG1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LRMP
Phase 1 OLINK assay data for target LRMP in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LRP11
Phase 1 OLINK assay data for target LRP11 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LRP1
Phase 1 OLINK assay data for target LRP1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LRRN1
Phase 1 OLINK assay data for target LRRN1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LTA4H
Phase 1 OLINK assay data for target LTA4H in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LTBP2
Phase 1 OLINK assay data for target LTBP2 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LTBR
Phase 1 OLINK assay data for target LTBR in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LXN
Phase 1 OLINK assay data for target LXN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LY75
Phase 1 OLINK assay data for target LY75 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Land use mix
The Shannon Entropy Index: A measure of how mixed land uses most relevant for PA are in a neighbourhood (Range: 0 to 1; 1= most mixed; 0=least mixed) LUM=(-1) Sk(pklnpk)/ln N p is the proportion of land area devoted to the specific land use (k) in each buffer divided by ln N N is the number of land uses under consideration. In this case N=5 (i.e. residential; commercial; institutional/governmental; recreational and mixed areas) The proportions (pk) were calculated as the land area devoted to a specific land use divided by the total area of walkable land uses in each buffer. Note: LUM=0 (i.e.; no mix) if none or only one of the relevant land uses fell into the buffer. Data Source: OS MasterMap Topography Layer Data (December 2016) AddressBase Premium Data (OS Managed GB Set)
Real
Land use mix P2
Phase 2 data: The Shannon Entropy Index: A measure of how mixed land uses most relevant for PA are in a neighbourhood (Range: 0 to 1; 1= most mixed; 0=least mixed) LUM=(-1) Sk(pklnpk)/ln N p is the proportion of land area devoted to the specific land use (k) in each buffer divided by lnN N is the number of land uses under consideration. In this case N=5 (i.e. residential; commercial; institutional/governmental; recreational and mixed areas) The proportions (pk) were calculated as the land area devoted to a specific land use divided by the total area of walkable land uses in each buffer. Note: LUM=0 (i.e.; no mix) if none or only one of the relevant land uses fell into the buffer. Data Source: OS MasterMap Topography Layer Data (December 2016) AddressBase Premium Data (OS Managed GB Set)
Real
OLINK assay LY9
Phase 1 OLINK assay data for target LY9 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LYAR
Phase 1 OLINK assay data for target LYAR in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LYN
Phase 1 OLINK assay data for target LYN in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LYPD1
Phase 1 OLINK assay data for target LYPD1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
OLINK assay LYPD3
Phase 1 OLINK assay data for target LYPD3 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
Lys_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable Lys_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit. Unit = uM. 2nd and final QC step on this var created new and final var BIOA_012.
Real
lysoPCaC140_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable lysoPCaC140_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit). Unit = uM; valid=0 LoD=5. 2nd and final QC step on this var created new and final var BIOR_041.
Real
lysoPCaC160_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable lysoPCaC160_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit). Unit = uM The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD.; valid=0 LoD=0.12. 2nd and final QC step on this var created new and final var BIOR_048.
Real
lysoPCaC161_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable lysoPCaC161_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit). Unit = uM; valid=0 LoD=0.07. 2nd and final QC step on this var created new and final var BIOR_042.
Real
lysoPCaC170_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable lysoPCaC170_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit). Unit = uM; valid=0 LoD=0.05. 2nd and final QC step on this var created new and final var BIOR_043.
Real
lysoPCaC180_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable lysoPCaC180_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit). Unit = uM; valid=0 LoD=0.05. 2nd and final QC step on this var created new and final var BIOR_044.
Real
lysoPCaC181_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable lysoPCaC181_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit). Unit = uM The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD.; valid=0 LoD=0.1. 2nd and final QC step on this var created new and final var BIOR_049.
Real
lysoPCaC182_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable lysoPCaC182_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit). Unit = uM; valid=0 LoD=0.1. 2nd and final QC step on this var created new and final var BIOR_045.
Real
lysoPCaC203_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable lysoPCaC203_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit). Unit = uM The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD.; valid=0 LoD=0.2. 2nd and final QC step on this var created new and final var BIOR_050.
Real
lysoPCaC204_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable lysoPCaC204_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit). Unit = uM; valid=0 LoD=0.02. 2nd and final QC step on this var created new and final var BIOR_046.
Real
lysoPCaC240_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable lysoPCaC240_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit). Unit = uM The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD.; valid=0 LoD=1.3. 2nd and final QC step on this var created new and final var BIOR_051.
Real
lysoPCaC260_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable lysoPCaC260_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit). Unit = uM The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD.; valid=0 LoD=0.5. 2nd and final QC step on this var created new and final var BIOR_052.
Real
lysoPCaC261_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable lysoPCaC261_raw. 0% missingness was found so data is identical to the raw variable data. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit). Unit = uM; valid=0 LoD=4. 2nd and final QC step on this var created new and final var BIOR_047.
Real
lysoPCaC280_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable lysoPCaC280_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit). Unit = uM The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD.; valid=0 LoD=0.33. 2nd and final QC step on this var created new and final var BIOR_053.
Real
lysoPCaC281_QCstep1
New in R8. 1st step QCd metabolomics data variable for raw variable lysoPCaC281_raw. All values below detection limit set to 0. Invalid flag: missing peak; internal standard too low; signal exceeds quantification limit). Unit = uM The _i in the name indicates that missingness was between 0 and 5% and the missing values have been replaced by a random imputed value between 0 and the plate-specific LOD.; valid=0 LoD=0.15. 2nd and final QC step on this var created new and final var BIOR_054.
Real
OLINK assay LYVE1
Phase 1 OLINK assay data for target LYVE1 in NPX format. See https://olink.com/faq/what-is-npx/ for explanation of units and how to use.
Real
M237_2212T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (237.2212) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M239_2368T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (239.2368) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M254_2477T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (254.2477) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M261_2212T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (261.2212) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M263_2369T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (263.2369) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M265_2525T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (265.2525) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M279_2317T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (279.2317) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M280_2634T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (280.2634) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M285_2424T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (285.2424) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M287_2361T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (287.2361) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M289_2525T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (289.2525) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M294_2398T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (294.2398) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M311_2576T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (311.2576) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M313_2736T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (313.2736) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M327_2267T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (327.2267) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M335_2580T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (335.2580) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M337_2733T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (337.2733) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M337_3099T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (337.3099) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M339_2893T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (339.2893) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M341_3049T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (341.3049) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M361_2739T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (361.2739) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M367_3365T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (367.3365) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M369_4330T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (369.4330) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M381_3509T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (381.3509) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M383_3669T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (383.3669) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M480_3451T_1_LysoPC_P 16db0
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (480.3451) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. LysoPC_PC = lyso-phosphatidylcholine alkenyl ethers.
Real
M484_2825T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (484.2825) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M580_5376T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (580.5376) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M583_5089T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (583.5089) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M482_3601T_1_LysoPC_O 16db0
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (482.3601) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC_O = phosphatidylcholine alkyl ethers
Real
M495_4409T_1_DG_H20 28db0
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (495.4409) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M496_3398T_1_LysoPC 16db0
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (496.3398) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC = phosphatidylcholines.
Real
M502_3288T_1_LysoPC_P 18db3
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (502.3288) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. LysoPC_PC = lyso-phosphatidylcholine alkenyl ethers.
Real
M504_3451T_1_LysoPC_P 18db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (504.3451) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. LysoPC_PC = lyso-phosphatidylcholine alkenyl ethers.
Real
M519_4411T_1_DG_H20 30db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (519.4411) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M605_5482T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (605.5482) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M611_5402T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (611.5402) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M617_5131T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (617.5131) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M619_5428T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (619.5428) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M520_3399T_1_LysoPC 18db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (520.3399) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC = phosphatidylcholines.
Real
M521_4565T_1_DG_H20 30db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (521.4565) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M522_3556T_1_LysoPC 18db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (522.3556) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC = phosphatidylcholines.
Real
M523_4722T_1_DG_H20 30db0
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (523.4722) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M524_3712T_1_LysoPC 18db0
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (524.3712) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC = phosphatidylcholines.
Real
M544_3392T_1_LysoPC 20db4
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (544.3392) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC = phosphatidylcholines.
Real
M630_6185T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (630.6185) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M632_6340T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (632.6340) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid.
Real
M650_5943T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (650.5943) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M650_6246T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (650.6246) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M545_4564T_1_DG_H20 32db3
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (545.4564) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M547_4724T_1_DG_H20 32db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (547.4724) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M549_4879T_1_DG_H20 32db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (549.4879) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M551_5033T_1_DG_H20 32db0
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (551.5033) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M561_4878T_1_DG_H20 33db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (561.4878) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M563_5034T_1_DG_H20 33db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (563.5034) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M651_6068T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (651.6068) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M653_5476T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (653.5476) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M655_6001T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (655.6001) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M666_4846T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (666.4846) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M571_4723T_1_DG_H20 34db4
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (571.4723) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M573_4879T_1_DG_H20 34db3
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (573.4879) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M575_5035T_1_DG_H20 34db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (575.5035) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M577_5190T_1_DG_H20 34db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (577.5190) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M587_5037T_1_DG_H20 35db3
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (587.5037) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M589_5191T_1_DG_H20 35db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (589.5191) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M679_4494T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (679.4494) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M716_5629T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (716.5629) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M720_5949T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (720.5949) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M724_5262T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (724.5262) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M591_5347T_1_DG_H20 35db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (591.5347) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M597_4878T_1_DG_H20 36db5
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (597.4878) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M599_5034T_1_DG_H20 36db4
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (599.5034) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M601_5190T_1_DG_H20 36db3
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (601.5190) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M603_5346T_1_DG_H20 36db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (603.5346) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M623_5035T_1_DG_H20 38db6
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (623.5035) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M726_5377T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (726.5377) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M726_5466T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (726.5466) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M741_5736T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (741.5736) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M745_4752T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (745.4752) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M625_5189T_1_DG_H20 38db5
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (625.5189) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M627_5347T_1_DG_H20 38db4
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (627.5347) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M629_5494T_1_DG_H20 38db3
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (629.5494) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M631_5655T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (631.5655) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. LysoPC_PC = lyso-phosphatidylcholine alkenyl ethers.
Real
M633_5811T_1_DG_H20 38db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (633.5811) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M640_6029T_1_CE 16db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (640.6029) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. CE = cholesteryl esters.
Real
M749_5080T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (749.5080) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M752_5754T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (752.5754) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M753_5670T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (753.5670) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M754_5933T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (754.5933) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M642_6184T_1_CE 16db0
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (642.6184) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. CE = cholesteryl esters.
Real
M643_5281T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (643.5281) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. LysoPC_PC = lyso-phosphatidylcholine alkenyl ethers.
Real
M649_5190T_1_DG_H20 40db7
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (649.5190) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M651_5347T_1_DG_H20 40db6
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (651.5347) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M656_5825T_1_TG 36db0
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (656.5825) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds.TG = triglycerides.
Real
M664_6028T_1_CE 18db3
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (664.6028) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. CE = cholesteryl esters.
Real
M757_6228T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (757.6228) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M758_0089T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (758.0089) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M758_5434T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (758.5434) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M758_7969T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (758.7969) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M666_6184T_1_CE 18db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (666.6184) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. CE = cholesteryl esters.
Real
M668_6322T_1_CE 18db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (668.6322) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. CE = cholesteryl esters.
Real
M673_5277T_1_SM 32db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (673.5277) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. SM = sphingomyelins.
Real
M675_5436T_1_SM 32db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (675.5436) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. SM = sphingomyelins.
Real
M688_6031T_1_CE 20db5
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (688.6031) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. CE = cholesteryl esters.
Real
M689_5598T_1_SM 33db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (689.5598) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. SM = sphingomyelins.
Real
M762_6735T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (762.6735) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M764_5614T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (764.5614) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M768_7037T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (768.7037) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M769_5505T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (769.5505) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M690_6185T_1_CE 20db4
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (690.6185) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. CE = cholesteryl esters.
Real
M692_6321T_1_CE 20db3
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (692.6321) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. CE = cholesteryl esters.
Real
M701_5592T_1_SM 34db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (701.5592) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. SM = sphingomyelins.
Real
M703_5749T_1_SM 34db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (703.5749) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. SM = sphingomyelins.
Real
M704_5236T_1_DG 42db11
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (704.5236) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M706_5375T_1_PC 30db0
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (706.5375) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC = phosphatidylcholines.
Real
M772_5254T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (772.5254) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M772_6093T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (772.6093) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M774_6352T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (774.6352) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M776_6891T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (776.6891) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M714_6172T_1_CE 22db6
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (714.6172) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. CE = cholesteryl esters.
Real
M718_5377T_1_PE 34db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (718.5377) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PE = phosphoethanolamines.
Real
M718_5750T_1_PC_P 32db0
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (718.5750) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC_P = phosphatidylcholine alkenyl ethers.
Real
M729_5905T_1_SM 36db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (729.5905) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. SM = sphingomyelins.
Real
M730_5376T_1_PC 32db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (730.5376) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC = phosphatidylcholines.
Real
M730_5743T_1_PC_O 33db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (730.5743) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC_O = phosphatidylcholine alkyl ethers.
Real
M780_5885T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (780.5885) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M780_5989T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (780.5989) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M782_6018T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (782.6018) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M782_6264T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (782.6264) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M731_6064T_1_SM 36db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (731.6064) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. SM = sphingomyelins.
Real
M732_5542T_1_DG 44db11
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (732.5542) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. DG = diglycerides
Real
M734_5699T_1_PC 32db0
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (734.5699) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC = phosphatidylcholines.
Real
M742_5380T_1_PE 36db3
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (742.5380) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PE = phosphoethanolamines.
Real
M744_5545T_1_PE 36db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (744.5545) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PE = phosphoethanolamines.
Real
M744_5902T_1_PC_O 34db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (744.5902) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC_O = phosphatidylcholine alkyl ethers.
Real
M800_6209T_1_0
Improved name in R8. Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (800.6209) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. LysoPC_PC = lyso-phosphatidylcholine alkenyl ethers.
Real
M808_6243T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (808.6243) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M823_6389T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (823.6389) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M825_6628T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (825.6628) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M745_6234T_1_SM 37db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (745.6234) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. SM = sphingomyelins.
Real
M746_5701T_1_PE 36db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (746.5701) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PE = phosphoethanolamines.
Real
M746_6065T_1_PC_P 34db0
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (746.6065) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC_P = phosphatidylcholine alkenyl ethers.
Real
M754_5388T_1_PC 34db4
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (754.5388) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC = phosphatidylcholines.
Real
M756_5540T_1_PC 34db3
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (756.5540) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC = phosphatidylcholines.
Real
M758_5696T_1_PC 34db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (758.5696) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC = phosphatidylcholines.
Real
M827_6987T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (827.6987) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M828_5513T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (828.5513) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M829_6786T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (829.6786) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M830_5676T_1_0
Explanation of var name M(1)_(2)T_(3)_(4) where 1.2 (830.5676) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified.
Real
M758_6056T_1_PC_O 35db2
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (758.6056) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. PC_O = phosphatidylcholine alkyl ethers.
Real
M759_6377T_1_SM 38db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (759.6377) is the mass to charge ratio's of the ions measured (unit = m/z) (3) is the charge of the ions (1 in all cases which means that the numbers correspond to the Molecular weight of the ion including the source of the ionisation agent). Based on accurate mass to charge ratio libraries can be searched to identify the molecular formula and corresponding lipid. Where (4) is 0 these were not identified. For the identified lipids the identity was also confirmed by LCMSMS. Where identified (5) is the number of carbons in the fatty acids and (6) is the number of double bonds. SM = sphingomyelins.
Real
M760_5858T_1_PC 34db1
Explanation of var name M(1)_(2)T_(3)_(4_((5)db(6))) where 1.2 (760.5858) is the mass to cha