title: A Comparison of Different Methods for Evaluating Diet, Physical Activity, and Long-Term Weight Gain in 3 Prospective Cohort Studies.
abstract: BACKGROUND
  The insidious pace of long-term weight gain (∼ 1 lb/y or 0.45 kg/y) makes it difficult to study in trials; long-term prospective cohorts provide crucial evidence on its key contributors. Most previous studies have evaluated how prevalent lifestyle habits relate to future weight gain rather than to lifestyle changes, which may be more temporally and physiologically relevant.
  
  
  OBJECTIVE
  Our objective was to evaluate and compare different methodological approaches for investigating diet, physical activity (PA), and long-term weight gain.
  
  
  METHODS
  In 3 prospective cohorts (total n = 117,992), we assessed how lifestyle relates to long-term weight change (up to 24 y of follow-up) in 4-y periods by comparing 3 analytic approaches: 1) prevalent diet and PA and 4-y weight change (prevalent analysis); 2) 4-y changes in diet and PA with a 4-y weight change (change analysis); and 3) 4-y change in diet and PA with weight change in the subsequent 4 y (lagged-change analysis). We compared these approaches and evaluated the consistency across cohorts, magnitudes of associations, and biological plausibility of findings.
  
  
  RESULTS
  Across the 3 methods, consistent, robust, and biologically plausible associations were seen only for the change analysis. Results for prevalent or lagged-change analyses were less consistent across cohorts, smaller in magnitude, and biologically implausible. For example, for each serving of a sugar-sweetened beverage, the observed weight gain was 0.01 lb (95% CI: -0.08, 0.10) [0.005 kg (95% CI: -0.04, 0.05)] based on prevalent analysis; 0.99 lb (95% CI: 0.83, 1.16) [0.45 kg (95% CI: 0.38, 0.53)] based on change analysis; and 0.05 lb (95% CI: -0.10, 0.21) [0.02 kg (95% CI: -0.05, 0.10)] based on lagged-change analysis. Findings were similar for other foods and PA.
  
  
  CONCLUSIONS
  Robust, consistent, and biologically plausible relations between lifestyle and long-term weight gain are seen when evaluating lifestyle changes and weight changes in discrete periods rather than in prevalent lifestyle or lagged changes. These findings inform the optimal methods for evaluating lifestyle and long-term weight gain and the potential for bias when other methods are used.
authors.affiliation: Departments of Nutrition and Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA; and jess.smith@tufts.edu.
authors.forename: Jessica D
authors.initials: JD
authors.lastname: Smith
authors.affiliation: Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA;
authors.forename: Tao
authors.initials: T
authors.lastname: Hou
authors.affiliation: Departments of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA.
authors.forename: Frank B
authors.initials: FB
authors.lastname: Hu
authors.affiliation: Departments of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA.
authors.forename: Eric B
authors.initials: EB
authors.lastname: Rimm
authors.affiliation: Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA;
authors.forename: Donna
authors.initials: D
authors.lastname: Spiegelman
authors.affiliation: Departments of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA.
authors.forename: Walter C
authors.initials: WC
authors.lastname: Willett
authors.affiliation: Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA; and.
authors.forename: Dariush
authors.initials: D
authors.lastname: Mozaffarian
mesh_terms: D000328:Adult; D001628:Beverages / Q000032:analysis; D015992:Body Mass Index; D002241:Carbohydrates / Q000008:administration & dosage; D004032:Diet; D005260:Female; D005500:Follow-Up Studies; D062489:Health Impact Assessment / Q000379:methods*; D006801:Humans; D008019:Life Style; D008297:Male; D008875:Middle Aged; D009043:Motor Activity; D015596:Nutrition Assessment; D011446:Prospective Studies; D012680:Sensitivity and Specificity; D011795:Surveys and Questionnaires; D015430:Weight Gain
chemical_list: D002241:Carbohydrates
keywords: baseline dietary intake; baseline physical activity; dietary intake change; epidemiological methods; long-term weight gain; obesity prevention; physical activity change; prospective cohorts