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Comparison of methods to account for implausible reporting of energy intake in epidemiologic studies

  • Jinnie J. Rhee
  • , Laura Sampson
  • , Eunyoung Cho
  • , Michael D. Hughes
  • , Frank B. Hu
  • , Walter C. Willett
  • Harvard University
  • Stanford University
  • Brown University

Research output: Contribution to journalArticlepeer-review

195 Scopus citations

Abstract

In a recent article in the American Journal of Epidemiology by Mendez et al. (Am J Epidemiol. 2011;173(4):448- 458), the use of alternative approaches to the exclusion of implausible energy intakes led to significantly different cross-sectional associations between diet and body mass index (BMI), whereas the use of a simpler recommended criteria (<500 and >3,500 kcal/day) yielded no meaningful change. However, these findings might have been due to exclusions made based on weight, a primary determinant of BMI. Using data from 52,110 women in the Nurses' Health Study (1990), we reproduced the cross-sectional findings of Mendez et al. and compared the results from the recommended method with those from 2 weight-dependent alternative methods (the Goldberg method and predicted total energy expenditure method). The same 3 exclusion criteriawere then used to examine dietary variables prospectively in relation to change in BMI, which is not a direct function of attained weight. We found similar associations using the 3 methods. In a separate cross-sectional analysis using biomarkers of dietary factors, we found similar correlations for intakes of fatty acids (n = 439) and carotenoids and retinol (n = 1,293) using the 3 methods for exclusions. These results do not support the general conclusion that use of exclusion criteria based on the alternative methods might confer an advantage over the recommended exclusion method.

Original languageEnglish
Pages (from-to)225-233
Number of pages9
JournalAmerican Journal of Epidemiology
Volume181
Issue number4
DOIs
StatePublished - Feb 15 2015

Keywords

  • Biomarkers
  • Body mass index
  • Diet
  • Energy intake
  • Implausible reporting
  • Selection bias

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