Obesity Epidemiology

ANALYTIC EPIDEMIOLOGIC DESIGNS IN OBESITY RESEARCH 31Design I. Single exposure measurement at baselineDesign II. Multiple exposure measurements during baselineperiodDesign III. Multiple exposure measurements during follow-upperiodFigure 3.1 Three possible designs of prospective cohort studies with respect to exposureassessment. Used with permission from Hu FB, Stampfer MJ, Rimm E, et al. Dietary fat andcoronary heart disease: a comparison of approaches for adjusting for total energy intake andmodeling repeated dietary measurements. Am J Epidemiol. 1999;149:531-540. 23weight, and other lifestyle data during follow-up (Design III, Fig. 3.1). Although periodiccollection of dietary and lifestyle data increases costs substantially, there is considerablereturn in improved validity and power of the study.The repeated measures of body weight are useful in several ways. First, updated bodyweight data provide an opportunity to test whether remote or current weight is a betterpredictor of disease risk. In several studies, current weight has been shown to be morepredictive of type 2 diabetes incidence, 25 whereas baseline weight is more predictive ofCVD risk. 26 This is probably related to the fact that the induction and latency periodsof CVD are much longer than those of diabetes. In prospective cohort studies, remotebody mass index (BMI) is typically more predictive of mortality risk than current BMIbecause current weight is likely to be affected by the development of chronic diseasesduring follow-up. 27 Second, repeated measures of weight enable researchers to examinewhether weight gain or loss, weight cycling, or weight fluctuations predict subsequentrisk of chronic disease and mortality independent of baseline BMI (see Chapter 5). Onestudy using updated measures of waist circumference found that increase in waist sizewas an important predictor of type 2 diabetes independent of weight gain. 28Repeated measures of diet and physical activity are useful in examining dietary andlifestyle predictors of incidence of obesity or chronic diseases. The use of updated lifestyledata in analyses not only allows for changes in dietary and exercise habits among participantsbut also reduces within-person random error. In a previous analysis of the NHScohort, we calculated the cumulative average of dietary intake from all available dietaryquestionnaires up to the start of each 2-year follow-up interval. 23 For example, disease incidence1980-1984 was related to the fat intake from the 1980 questionnaire, and disease incidence1984-1986 was related to the average intake from the 1980 and 1984 questionnaires.We found that the analyses using cumulative averages of diet yielded stronger associationsbetween dietary fats and CHD than did analyses that used only baseline or the most recent