Eating patterns associated Eating patterns associated with overweight and with overweight and
obesity in children and obesity in children and adolescents: adolescents:
methodological methodological considerationsconsiderationsMegan A. McCrory, PhDMegan A. McCrory, PhD
Dept of Foods and NutritionDept of Foods and NutritionDept of Psychological SciencesDept of Psychological SciencesIngestive Behavior Research Ingestive Behavior Research
CenterCenterPurdue UniversityPurdue University
Trends in Overweight in US Trends in Overweight in US Children and AdolescentsChildren and Adolescents
*Sex-and age-specific BMI *Sex-and age-specific BMI >> 95th percentile based on 95th percentile based on the CDC growth charts. the CDC growth charts.
Source: CDC
How to Study Causes and Treatment of How to Study Causes and Treatment of Overweight?Overweight?
DesignDesign AdvantagesAdvantages DisadvantagesDisadvantages
Clinical Clinical studies/controlled studies/controlled interventionsinterventions
Precisely control Precisely control conditions and conditions and monitor effectsmonitor effects
not like “home”not like “home” non-compliancenon-compliance may may occuroccur possible inconsistency possible inconsistency between short-term vs. between short-term vs. long term; wt gain vs. wt long term; wt gain vs. wt lossloss
Outpatient/Outpatient/
behavioral behavioral interventionsinterventions
Shows what is Shows what is possiblepossible
goals usually modestgoals usually modest non-compliance is non-compliance is major issuemajor issue effects may be effects may be protocol-specificprotocol-specific
Observational/Observational/
epidemiologyepidemiologyObserve “usual Observe “usual life” conditionslife” conditions
does not show cause does not show cause and effectand effect inaccurate inaccurate (implausible) dietary (implausible) dietary reportingreporting can lead to can lead to spurious conclusionsspurious conclusions
Modified from: Susan Roberts
How to Assess Compliance in How to Assess Compliance in Human Feeding StudiesHuman Feeding Studies
ChecklistChecklist Container ReturnContainer Return Innocuous Marker – eg PABAInnocuous Marker – eg PABA Why isn’t the latter done more Why isn’t the latter done more
often?often?
Assessment of Dietary Assessment of Dietary Compliance with Para-amino Compliance with Para-amino benzoic acid (PABA) – use in benzoic acid (PABA) – use in controlled feeding studiescontrolled feeding studies
Supplementation of Supplementation of provided foods with PABA provided foods with PABA and recovery of PABA in and recovery of PABA in complete urine complete urine collections can help collections can help determine determine whether whether provided foods are provided foods are actually consumedactually consumed in in clinical studies.clinical studies.
In a validation study in 10 In a validation study in 10 adults, PABA recovery adults, PABA recovery was 98.7±3.7% over 3 was 98.7±3.7% over 3 daysdays
Expected minimum PABA Expected minimum PABA excretion is 92.6% (5th excretion is 92.6% (5th percentile)percentile)
0
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D1 D2 D3 Mean
Roberts et al. Am J Clin Nutr 1990;51:485Roberts et al. Am J Clin Nutr 1990;51:485
Assessment of Dietary Compliance Assessment of Dietary Compliance by Measurement of Urinary Osmolar by Measurement of Urinary Osmolar
Excretion Rate (OER) - use in Excretion Rate (OER) - use in controlled feeding studiescontrolled feeding studies
Urinary OER can be used to Urinary OER can be used to predict predict whether subjects in whether subjects in clinical studies are eating clinical studies are eating food other than that provided food other than that provided by the research centerby the research center..
This is because the urinary This is because the urinary osmolar load is 95% due to osmolar load is 95% due to N, Na and K salts, which N, Na and K salts, which come from the dietcome from the diet
In 34 subjects in 3 closely-In 34 subjects in 3 closely-supervised metabolic studies, supervised metabolic studies, mean OER over 6 days was mean OER over 6 days was 100±7% of expected100±7% of expected
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012345678910111213141516171819202122232425262728293031323334Individual Subjects
Study 1 Study 2 Study 3
Roberts et al. Am J Clin Nutr 1991;54:774Roberts et al. Am J Clin Nutr 1991;54:774
Assess dietary intakeAssess dietary intake Intake-balance methodIntake-balance method
How to Assess Compliance in How to Assess Compliance in Controlled and Behavioral Controlled and Behavioral
InterventionsInterventionsand Observational Studiesand Observational Studies
Traditional Dietary Assessment Traditional Dietary Assessment Methods in Free-Living Methods in Free-Living
PersonsPersons Food intake record (3-7 days)Food intake record (3-7 days)
Weighed or measuredWeighed or measured Estimated with visual aidsEstimated with visual aids
24-h recall24-h recall Multiple-pass techniqueMultiple-pass technique Several (≥3)Several (≥3) UnscheduledUnscheduled
Food Frequency Questionnaire (not in Food Frequency Questionnaire (not in kids)kids)
Diet History Questionnaire (not in kids)Diet History Questionnaire (not in kids)
Problem: Underreporting of Problem: Underreporting of Energy IntakeEnergy Intake
Greater amount and prevalence of Greater amount and prevalence of underreporting with increasing underreporting with increasing weight statusweight status
In adults, selective underreporting In adults, selective underreporting occurs for foods high in energy occurs for foods high in energy density, and selective density, and selective underreporting occurs for underreporting occurs for vegetables (fruits?)vegetables (fruits?)
Related to social desirabilityRelated to social desirability
Total Energy Expenditure: Total Energy Expenditure: Biomarker for Energy IntakeBiomarker for Energy Intake
If total energy expenditure and If total energy expenditure and energy balance are measured energy balance are measured accurately, energy intake can be accurately, energy intake can be validated because:validated because:
Energy Intake = Total Energy Energy Intake = Total Energy Expenditure +∆ Energy BalanceExpenditure +∆ Energy Balance
Validation of Reported Energy Validation of Reported Energy Intake (rEI) Intake (rEI)
• rEI can be validated by comparing it with total energy expenditure (TEE), since during body weight stability
Total Energy Expenditure = Total Energy Intake(TEE = TEI)
• If rEI does not agree with TEE, it could be considered “implausible” for representing usual EI
Validating Reported Energy Intake (rEI) Validating Reported Energy Intake (rEI)
0
500
1000
1500
2000
2500
Total EnergyExpenditure
Reported EnergyIntake
0
500
1000
1500
2000
2500
Total EnergyExpenditure
Reported EnergyIntake
kcal/d
kcal/d
• rEI can be validated by rEI can be validated by comparing it with total energy comparing it with total energy expenditure (TEE), since during expenditure (TEE), since during body weight and composition body weight and composition stability over the long-term,stability over the long-term,
ENERGY INTAKE
ENERGY EXPENDITURE
=
Plausible rEI
Implausible rEI
kcal/d
kcal/d
1. Usual Energy Intake over the long term is represented by Energy Requirements, since when an individual is in energy balance
Energy Intake = Energy Expenditure (Requirement)
2. Energy Requirement determined
Measured precisely by using doubly-labeled water method
calculated using equations based on age, weight, height, sex and physical activity level (Dietary Reference Intakes, 2003)
Others?
Steps for Determining Plausibility of Reported Steps for Determining Plausibility of Reported Energy IntakeEnergy Intake
3. Reporting “plausibility” = reported energy intake (rEI) expressed as a percentage of predicted energy requirement (pER), i.e. (rEI/pER)*100%
4. Determine acceptable cutoffs for EI reporting plausibility based on day-to-day biological and methodological variation associated with EI and ER measurement (McCrory et al, 2002; Huang et al, 2005)
Steps for Determining Plausibility of Reported Steps for Determining Plausibility of Reported Energy IntakeEnergy Intake
Measurement of Total Energy Measurement of Total Energy Expenditure with Doubly Expenditure with Doubly
Labeled WaterLabeled Water Two stable isotopes of water are given by Two stable isotopes of water are given by
mouth (mouth (22HH22O and HO and H221818O)O)
They mix in body water and then They mix in body water and then disappear over time as they are diluted disappear over time as they are diluted out of the bodyout of the body
Rate of Rate of 22H reflects water turnover, rate of H reflects water turnover, rate of 1818O reflects water plus COO reflects water plus CO22 turnover turnover
Difference between two disappearance Difference between two disappearance rates equals COrates equals CO22 production, from which production, from which TEE can be calculatedTEE can be calculated
Dose Time
2H H2O output
18O H2O + CO2 outputIso
top
ic a
bu
nd
an
ce
s
Isotopic backgrounds
DLW is a Practical DLW is a Practical MethodMethod
Measures TEE over long periods of time Measures TEE over long periods of time (7-14 days)(7-14 days)
Shown to be accurate in wide range of Shown to be accurate in wide range of subjectssubjects
Easy on subjects - just a dose of isotope to Easy on subjects - just a dose of isotope to drink and collection of few urine drink and collection of few urine specimensspecimens
Hard on investigators - very expensive, Hard on investigators - very expensive, needs careful analysis (mass needs careful analysis (mass spectrometer), but nothing else is as goodspectrometer), but nothing else is as good
Predicting Energy RequirementsPredicting Energy Requirements(IOM, 2002)(IOM, 2002)
Predicted from:Predicted from: AgeAge WeightWeight HeightHeight PAL estimate (sedentary, PAL estimate (sedentary, low activelow active*, moderately *, moderately
active, highly active)active, highly active)
Separate equations for:Separate equations for: Normal weight (BMI 18.5-24.9 kg/mNormal weight (BMI 18.5-24.9 kg/m22) vs. ) vs.
Overweight/Obese (BMI Overweight/Obese (BMI ≥≥25 kg/m25 kg/m22) adults) adults Women vs. MenWomen vs. Men Children and adolescents (girls vs boys)Children and adolescents (girls vs boys) InfantsInfants Lactating womenLactating women
* PAL = 1.4-1.6, where PAL is TEE/REE
√(CV2mTEE + CV2
pTEE + (CV2wEI/d)) = “± 1 SD cut-off”
Calculating Cut-offs for the Agreement Between rEI and pTEE
[(rEI/pTEE)*100%] ± error
CVwEI is the within-person CV for rEI (20-28% among BMI-age-sex strata)
d is the number of days of intake (2)
CVmTEE is the within-person CV for TEE measured by doubly-labeled water and includes measurement error and biological variation (8.2%)
Error Propagation: The sum of the errors of the different components that constitute an estimate, measurement or calculation
CVpTEE is the within-person CV for predicted TEE, calculated by dividing the SD of prediction equation residuals by mean doubly labeled water-measured TEE (8-15% among BMI-age-sex strata)
± 1 SD cut-offs ranged from 20-24%; we therefore used the average, 22%
Characteristics of Sample
(CSFII ‘94-96, NPNL adults age 21-45, reported weight and height, and 2 d of intake)
Men (n=1969) Women (n=1786)
White, % 80 77
Income >130% of 78 74
poverty threshold, %
Current smokers, % 32 27
Education, years (mean) 13.4 13.4
Body Mass Index (mean) 26.4 25.5
Cut-off Ranges Tested for Agreement between Cut-off Ranges Tested for Agreement between rEI and pERrEI and pER
Cut-offCut-off ValueValue Range of (rEI/pER)*100%Range of (rEI/pER)*100%
± 1 SD± 1 SD ± 22%± 22% 78% - 122%78% - 122%
± 1.5 SD± 1.5 SD ± 33%± 33% 67% - 133%67% - 133%
± 2 SD *± 2 SD * ± 44%± 44% 56% - 144%56% - 144%
* 95% confidence interval
Huang et al 2005, Obes Res
How close do rEI and pER need to be in order for rEI to be considered plausible?
Adults aged 21-45 y, CSFII 1994-96 (not dieting, not pregnant or lactating)
(rEI/pER)*100% in Men and Women(rEI/pER)*100% in Men and Women
Huang et al 2005, Obes Res
Regression of rEI on pER (-----)
Line of identity
( )
Regression line differs from line of identity in total sample but not the ±2 and ±1.5 SD samples. Slope in ±1 SD sample does not differ from 1.0, but intercept differs from 0.
Residuals are smaller and R2 improves with progressively narrower cut-offs.
Regressions of rEI on weight in CSFII 1994-96 and mTEE on weight in DRI data
Note increasing approximation of the two slopes with progressively narrower cut-offs
Only in the ±1 SD sample are the two slopes not significantly different
Underrecording vs. Undereating
• Underrecording – not reporting everything actually consumed
• Undereating – reporting everything consumed, but eating less than required to maintain current body weight
Question: How would you tell the difference? Use a 7-day weighed food record as an example
Characteristics Associated with Under-reporting in Adults
Obesity
Dietary Restraint
Sex
Age
Ethnicity
Race and culture
Physical Activity
Smoking Status
Education level
Literacy
Social class
Living arrangements
Depression
Past Dieting Frequency
Reviewed in McCrory et al 2002
Major Factors Related to Major Factors Related to Dietary Misreporting in Dietary Misreporting in
ChildrenChildren AgeAge Weight StatusWeight Status Weight Concern (girls)Weight Concern (girls) Dietary Method (?)Dietary Method (?)
Ratio of rEI:TEE in Studies in Ratio of rEI:TEE in Studies in Children and Adolescents aged Children and Adolescents aged
1-18 yrs *1-18 yrs *
Data from Table 1 in Livingstone et al Br J Nutr 2004;92:S213-22
00.20.40.60.8
11.21.41.61.8
0 5 10 15 20
Age or Age Range Midpoint (y)
rEI:
TE
E
* Studies 1994-2002, where TEE was measured by the “gold standard” doubly-labeled water
Range ~ 0.6 to 1.6
• White, non-Hispanic
• Age 11.3±0.3 y (SD)
• 3 x 24-h multi-pass recalls over 2 wks
•Mothers present but only assisted when necessary
Pre-adolescent Girls (n=171)Pre-adolescent Girls (n=171)
Ventura et al 2006 Obes 14:1073-84
Pre-adolescent Girls (n=171)Pre-adolescent Girls (n=171)
Ventura et al 2006 Obes 14:1073-84
Under Under (n=57)(n=57)
Plausible Plausible (n=86)(n=86)
Over Over (n=28)(n=28)
BMI (kg/mBMI (kg/m22)) 21.6±4.2 21.6±4.2 aa 19.5±3.9 19.5±3.9 bb 18.5±3.0 18.5±3.0 bb
BMI z-scoreBMI z-score 0.9±0.9 0.9±0.9 aa 0.3±1.0 0.3±1.0 bb 0.1±0.9 0.1±0.9 bb
BMI BMI percentilepercentile
88.0±23.2 88.0±23.2 aa
72.0±28.0 72.0±28.0 bb
58.0±27.2 58.0±27.2 bb
Fat mass (kg)Fat mass (kg) 15.0±61.8 15.0±61.8 aa
11.6±62.0 11.6±62.0 bb
10.4±48.2 10.4±48.2 bb
Body Fat (%)Body Fat (%) 30.6±6.9 30.6±6.9 aa 26.5±6.9 26.5±6.9 bb 25.2±6.8 25.2±6.8 bb
Reported Pyramid Food Group Reported Pyramid Food Group IntakeIntake
Ventura et al
Reported Grain IntakeReported Grain Intake
Ventura et al
Reported Vegetable IntakeReported Vegetable Intake
Ventura et al
Reported Dairy IntakeReported Dairy Intake
Ventura et al
Reported Beverage IntakeReported Beverage Intake
Ventura et al
Reported Meal and Snack Frequency Reported Meal and Snack Frequency Over 3 DaysOver 3 Days
Ventura et al
Pre-adolescent Girls (n=171)Pre-adolescent Girls (n=171)
Fiorito et al JADA 2006;106:1985-1855
Dairy <3 svgs/dDairy <3 svgs/d Dairy ≥ 3 Dairy ≥ 3 svgs/dsvgs/d
Energy Intake Energy Intake (kcal/d)(kcal/d)
Total sampleTotal sample 1706±4241706±424 2040±419 ***2040±419 ***
PlausiblePlausible 1861±2061861±206 1884±1711884±171
UnderUnder 1418±2621418±262 1528±1941528±194
OverOver 2654±5372654±537 2540±3022540±302
BMI Percentile BMI Percentile ††
Total sampleTotal sample 66.9±26.366.9±26.3 58.7±28.0 *58.7±28.0 *
PlausiblePlausible 58.7±28.058.7±28.0 58.8±27.558.8±27.5
UnderUnder 76.0±21.976.0±21.9 76.1±21.976.1±21.9
OverOver 59.7±24.959.7±24.9 50.9±28.250.9±28.2
Mean±SD
***p<0.001; * p<0.05 †† Same results using BMI z-score and
% body fat
EI Reporting Plausibility in Boys: EI Reporting Plausibility in Boys: CSFII 1994-96CSFII 1994-96
Huang et al 2004 Obes Res 2004;12:1875-85
Huang et al 2004 Obes Res
EI Reporting Plausibility in Girls: EI Reporting Plausibility in Girls: CSFII 1994-6CSFII 1994-6
Eating Patterns Associations with Eating Patterns Associations with BMI in BoysBMI in Boys
Age (y)Age (y) NN Sig variableSig variable
TotalTotal 3-53-5 11951195 Meal portionMeal portion
6-116-11 569569 Snack portionSnack portion
12-1912-19 447447 Total eating freq. (-), Total eating freq. (-), %energy FAFH, % energy %energy FAFH, % energy CHO (-)CHO (-)
PlausiblPlausiblee
3-53-5 11991199 NothingNothing
6-116-11 557557 Energy intake; meal Energy intake; meal portion; meal energyportion; meal energy
12-1912-19 441441 Energy intake; meal Energy intake; meal portion; meal energy; portion; meal energy; %energy FAFH; %energy %energy FAFH; %energy from fat; %energy CHO from fat; %energy CHO (-)(-)
Future GoalsFuture Goals
Test validity of objective biomarkers for Test validity of objective biomarkers for specific macronutrients or other specific macronutrients or other components of dietcomponents of diet In conditions where dietary intake is knownIn conditions where dietary intake is known Reflection of actual intakeReflection of actual intake Eg urinary sugars (Sheila Bingham group)Eg urinary sugars (Sheila Bingham group)
Method to statistically adjust reported Method to statistically adjust reported dietary data for specificity of dietary data for specificity of misreportingmisreporting
Thank YouThank You
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