Obesity Epidemiology

DIETARY ASSESSMENT METHODS 107173 women. 1 In that total energy intake is quite well regulated by physiologic mechanisms,there is relatively low day-to-day variation for total calories. In contrast, theconcentration of vitamin A and other micronutrients in certain foods can cause intaketo vary considerably from day to day, depending on food choices and seasonable availabilityof foodstuffs.Because of day-to-day variations in diet, a single 24-hour recall provides a poor estimateof a person’s usual diet. However, repeated measures can be used to improve the estimate.In validation studies, repeated measures of the reference method are commonly used tocorrect for within-person variations in dietary intakes. For example, deattenuated correlationcoefficients for the nutrient of interest between a FFQ and weighed diet records werecorrected for week-to-week variation in diet records by using the following formula. 99r 5 11 gtr0/ k (6.1)where r tis the corrected correlation between the dietary pattern scores derived fromthe FFQ and diet records, r ois the observed correlation, γ is the ratio of estimatedwithin-person and between-person variation in nutrient intakes derived from the two1-week diet records, and k is the number of repeated observations of diet records.Conceptually, these corrected correlations provide an estimate of the correlationsbetween the FFQ and true intake whereby each person’s intake was measured by avery large number of diet records. Rosner and Willett 100 provided an estimate of thestandard error for the corrected or deattenuated correlation coefficient and an associated100% × (1 − α) confidence interval.In epidemiologic studies of diet and disease risk, the regression calibration approachcan be used to correct for both random and systematic errors, but this approach requiresa validation study in a subsample of the cohort. Rosner et al. 101 developed a method tocorrect odds ratio estimates from logistic regression models for measurement errors incontinuous exposures within cohort studies; these errors could be systematic or due torandom within-person variation. Let X denote true dietary intake by a reference methodand Z denote surrogate exposure by a FFQ. Ignoring measurement error, the logisticregression model for regressing a dichotomous disease variable D on Z,log[D∕(1 − D)] =α+βz (6.2)True intake (X) is estimated as a function of observed surrogate intake (Z) from a regressionderived from validation study data (X = α′ + λZ+ ε). The corrected β* is obtained byβ* = β∕λ (6.3)where β is the uncorrected logistic regression coefficient of D on Z from the main study(from equation 6.2), and λ is the estimated regression slope of X on Z from the validationstudy.Koh-Banerjee et al. 102 extended the regression calibration method to estimate regressioncoefficients adjusted for measurement error in an analysis of the relationship betweenchanges in diet and 9-year gain in waist circumference. Such an analysis requires validationstudies conducted at two separate time points.Let: X 1represent true dietary intake (diet record) in time 1; X 2represent truedietary intake (diet record) in time 2.Z 1represent dietary intake measured by a surrogate (FFQ) in time 1.Z 2represent dietary intake measured by a surrogate (FFQ) in time 2.