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Generalizability of dietary patterns associated with incidence of type 2 diabetes mellitus^1,2,3,4

¹ From the Jean Mayer US Department of Agriculture, Human Nutrition Research Center on Aging at Tufts University, Boston, MA (FI, AHL, GED, and PFJ), and the General Medicine Division and Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA (JBM).

² Any opinions, findings, conclusions or recommendations expressed in this publication are those of the authors, and do not necessarily reflect the view of the US Department of Agriculture.

³ Supported in part by the US Department of Agriculture, Agricultural Research Service, under agreement no. 58-1950-7-707 and the Framingham Heart Study of the National Heart Lung and Blood Institute of the National Institutes of Health (contract no. N01-HC-25195). JBM was supported by NIDDK K24 DK080140.

⁴ Address correspondence to PF Jacques, Jean Meyer USDA Human Nutrition Research Center on Aging, 711 Washington Street, Boston, MA, 02111. E-mail: paul.jacques{at}tufts.edu.

Background: Reduced rank regression (RRR) has been used to derive dietary pattern scores that predict linear combinations of disease biomarkers. The generalizability of these patterns to independent populations remains unknown.

Objective: The goal was to examine the generalizability of dietary patterns from the following prior studies using RRR to predict type 2 diabetes mellitus (T2DM): the Nurses' Health Study (NHS), European Prospective Investigation into Cancer and Nutrition Germany (EPIC), and Whitehall II Study (WS).

Design: The relative weights of food groups of each dietary pattern were used to generate each dietary pattern score in the Framingham Offspring Study (n = 2879). Each of the external scores (confirmatory scores) was examined to determine whether it could predict incident T2DM during 7 y of follow-up as well as scores developed internally in the Framingham Offspring Study using a Cox-proportional hazard model adjusted for T2DM risk factors.

Results: Intakes of meat products, refined grains, and soft drinks (caloric and noncaloric) were found to be common predictive components of all confirmatory scores, but fried foods, eggs, and alcoholic beverages were predictive in some, but not in all, confirmatory scores. On the basis of a continuous increase in the score by 1 SD, the NHS-based confirmatory score predicted T2DM risk (hazard ratio: 1.44; 95% CI: 1.25, 1.66). However, T2DM risk was only weakly predicted by the EPIC-based score (hazard ratio: 1.14; 95% CI: 0.99, 1.32) and the WS-based score (hazard ratio: 1.16; 95% CI: 1.00, 1.35).

Conclusions: The study suggested that dietary patterns that predict T2DM risk in different populations may not be generalizable to different populations. Additional dietary pattern studies should be conducted with regard to generalizability.