| Titre : | Gains in Statistical Power From Using a Dietary Biomarker in Combination With Self-reported Intake to Strengthen the Analysis of a Diet-Disease Association : An Example From CAREDS. (2010) |
| Auteurs : | Laurence-S FREEDMAN ; Victor KIPNIS ; Julie MARES ; Nancy POTISCHMAN ; Arthur SCHATZKIN ; Natasa TASEVSKA ; Lesley TINKER |
| Type de document : | Article |
| Dans : | American journal of epidemiology (vol. 172, n° 7, 2010) |
| Pagination : | 836-842 |
| Langues: | Anglais |
| Mots-clés : | Cataracte ; Gain ; Statistique ; Régime alimentaire ; Alimentation ; Aliment ; Association thérapeutique ; Autoévaluation ; Pathologie ; Epidémiologie |
| Résumé : | [BDSP. Notice produite par INIST-CNRS pmprR0xk. Diffusion soumise à autorisation]. A major problem in detecting diet-disease associations in nutritional cohort studies is measurement error in self-reported intakes, which causes loss of statistical power. The authors propose using biomarkers correlated with dietary intake to strengthen analyses of diet-disease hypotheses and to increase statistical power. They consider combining self-reported intakes and biomarker levels using principal components or a sum of ranks and relating the combined measure to disease in conventional regression analyses. They illustrate their method in a study of the inverse association of dietary lutein plus zeaxanthin with nuclear cataracts, using serum lutein plus zeaxanthin as the biomarker, with data from the Carotenoids in Age-Related Eye Disease Study (United States, 2001-2004). This example demonstrates that the combined measure provides higher statistical significance than the dietary measure or the serum measure alone, and it potentially provides sample savings of 8% - 53% over analysis with dietary intake alone and of 6% - 48% over analysis with serum level alone, depending on the definition of the outcome variable and the choice of confounders entered into the regression model. The authors conclude that combining appropriate biomarkers with dietary data in a cohort can strengthen the investigation of diet-disease associations by increasing the statistical power to detect them. |
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