A Dietary Pattern Derived from Reduced Rank Regression and Fatty Acid Biomarkers Is Associated with Lower Risk of Type 2 Diabetes and Coronary Artery Disease in Chinese Adults
Abstract
Combinations of circulating fatty acids may affect the risk of type 2 diabetes (T2D) and coronary artery disease (CAD). No previous studies have identified a dietary pattern predicting fatty acid profiles using reduced rank regression (RRR) and evaluated its associations with the risk of T2D and CAD. The aim of this study was to derive a dietary pattern to explain variation in plasma fatty acid concentrations using RRR and evaluate these in relation to risk of T2D and CAD. We derived a dietary pattern using fatty acid concentrations from 711 controls of a nested case-control study in the Singapore Chinese Health Study using RRR with 36 food and beverages as predictors and 19 fatty acid biomarkers as responses. Dietary pattern scores were then calculated for the full cohort of men and women (mean age: 56 y). We followed up 45,411 and 58,065 participants for incident T2D and CAD mortality, respectively. Multivariable Cox regression models were used to estimate HRs and 95% CIs. We identified a dietary pattern high in soy, vegetables, fruits, tea, tomato products, bread, fish, margarine and dairy, and low in rice, red meat, coffee, alcohol, sugar-sweetened beverages, and eggs. This pattern predicted higher circulating n-3 (ω-3) PUF...Continue Reading
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References
Visceral fat thickness in overweight men correlates with alterations in serum fatty acid composition
Dietary patterns, cardiovascular risk factors and C-reactive protein in a healthy Italian population
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