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)

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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