4.6 Article

α-Priori and α-Posterior Dietary Pattern Analyses Have Similar Estimating and Discriminating Ability in Predicting 5-Y Incidence of Cardiovascular Disease: Methodological Issues in Nutrition Assessment

期刊

JOURNAL OF FOOD SCIENCE
卷 74, 期 7, 页码 H218-H224

出版社

WILEY
DOI: 10.1111/j.1750-3841.2009.01268.x

关键词

cardiovascular; diet; epidemiology; indices; multivariate analysis

资金

  1. Hellenic Cardiological Society

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The 5-y incidence of cardiovascular disease (CVD) in relation to dietary habits was evaluated, using 2 methodological approaches, an alpha-priori and an alpha-posterior diet pattern analyses. The aim of this study was to compare these methods in predicting CVD events. From May 2001 to December 2002, 3042 men and women (>18 y) without any clinical evidence of CVD were enrolled in the ATTICA study. In 2006, the 5-y follow-up was performed (941 of the 3042 [31%] participants were lost to follow-up). Development of CVD (coronary heart disease, acute coronary syndromes, stroke, or other CVD) during the follow-up period was defined according to WHO-ICD-10 criteria. An a-posterior statistical method, principal component analysis (PCA), was applied to extract dietary patterns from various foods or food groups. Moreover, a special diet score that incorporates inherent characteristics of the Mediterranean diet (the MedDietScore) was also used to assess level of adherence to this diet (alpha-priori approach). Using PCA 10 components were extracted that explained the 57% of the total variation in intake. The model that also included various potential confounders together with the extracted components showed adequate goodness of fit and very good discriminating ability (C-statistic = 0.85). The other model that included the same potential confounders together with the MedDietScore also showed adequate goodness of fit and very good discriminating ability, too (C-statistic = 0.83). alpha-priori and alpha-posterior dietary assessment showed similar estimating and discriminating ability in predicting CVD, in our sample.

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