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B1196
Title: Integrate dietary assessments with biomarker measurements in aetiological models Authors:  Marta Pittavino - Geneva School of Economics and Management (GSEM), Research Center for Statistics (RCS) (Switzerland) [presenting]
Pietro Ferrari - International Agency for Research on Cancer (France)
Martyn Plummer - University of Warwick (United Kingdom)
Abstract: In nutritional epidemiology, self-reported assessments of dietary exposure are prone to measurement errors, which is responsible for bias in the association between dietary factors and risk of disease. In this study, self-reported dietary assessments were complemented by biomarkers of dietary intake. Dietary and serum measurements of folate and vitamin-B6 from two nested case-control studies within the European Prospective Investigation into Cancer and Nutrition (EPIC) study were integrated into a Bayesian model to explore the measurement error structure of the data, and relate dietary exposures to risk of site-specific cancer. A Bayesian hierarchical model was developed, which included: 1) an exposure model, to define the distribution of unknown true exposure ($X$); 2) a measurement model, to relate observed assessments, in turn, dietary questionnaires ($Q$), 24-hour recalls ($R$) and biomarkers ($M$) to $X$ measurements; 3) a disease model, to estimate exposures/cancer relationships. The marginal posterior distribution of model parameters was obtained from the joint posterior distribution, using Markov Chain Monte Carlo (MCMC) sampling techniques in JAGS. This challenging developmental work will be described, together with preliminary findings.