title: The impact of stratification by implausible energy reporting status on estimates of diet-health relationships.
abstract: The food frequency questionnaire (FFQ) is known to be prone to measurement error. Researchers have suggested excluding implausible energy reporters (IERs) of FFQ total energy when examining the relationship between a health outcome and FFQ-reported intake to obtain less biased estimates of the effect of the error-prone measure of exposure; however, the statistical properties of stratifying by IER status have not been studied. Under certain assumptions, including nondifferential error, we show that when stratifying by IER status, the attenuation of the estimated relative risk in the stratified models will be either greater or less in both strata (implausible and plausible reporters) than for the nonstratified model, contrary to the common belief that the attenuation will be less among plausible reporters and greater among IERs. Whether there is more or less attenuation depends on the pairwise correlations between true exposure, observed exposure, and the stratification variable. Thus exclusion of IERs is inadvisable but stratification by IER status can sometimes help. We also address the case of differential error. Examples from the Observing Protein and Energy Nutrition Study and simulations illustrate these results.
authors.affiliation: Department of Biostatistical Sciences, Wake Forest School of Medicine, Medical Center Blvd, Winston-Salem, NC, 27157, USA. jtooze@wakehealth.edu.
authors.forename: Janet A
authors.initials: JA
authors.lastname: Tooze
authors.affiliation: Sheba Medical Center, Gertner Institute for Epidemiology and Health Policy Research, Tel Hashomer, 52161, Israel.
authors.forename: Laurence S
authors.initials: LS
authors.lastname: Freedman
authors.affiliation: Department of Statistics, Texas A&M University, College Station, TX, 77843, USA.
authors.forename: Raymond J
authors.initials: RJ
authors.lastname: Carroll
authors.affiliation: National Cancer Institute, Bethesda, MD, 20892, USA.
authors.forename: Douglas
authors.initials: D
authors.lastname: Midthune
authors.affiliation: National Cancer Institute, Bethesda, MD, 20892, USA.
authors.forename: Victor
authors.initials: V
authors.lastname: Kipnis
mesh_terms: D003198:Computer Simulation; D004032:Diet; D002149:Energy Intake; D006262:Health / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical
keywords: Attenuation; Bias (epidemiology); Food frequency questionnaire; Models; Statistical; Underreporting