Imamura Fumiaki, Lichtenstein Alice H, Dallal Gerard E, Meigs James B, Jacques Paul F
Jean Mayer US Department of Agriculture, Human Nutrition Research Center on Aging at Tufts University, Boston, MA 02111, USA.
Am J Clin Nutr. 2009 Oct;90(4):1075-83. doi: 10.3945/ajcn.2009.28009. Epub 2009 Aug 26.
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.
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).
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.
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).
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.
降秩回归（RRR）已被用于推导饮食模式得分，以预测疾病生物标志物的线性组合。这些模式在独立人群中的可推广性仍然未知。
本研究旨在检验以下先前研究中使用RRR预测2型糖尿病（T2DM）的饮食模式在弗雷明汉后代研究中的可推广性：护士健康研究（NHS）、欧洲癌症与营养前瞻性调查德国队列（EPIC）以及白厅II研究（WS）。
利用弗雷明汉后代研究（n = 2879）中每种饮食模式食物组的相对权重来生成每种饮食模式得分。对每个外部得分（验证性得分）进行检验，以确定其是否能够预测随访7年期间的新发T2DM，以及使用针对T2DM风险因素进行调整的Cox比例风险模型在弗雷明汉后代研究中内部得出的得分。
发现肉类产品、精制谷物和软饮料（含热量和不含热量）的摄入量是所有验证性得分的常见预测成分，但油炸食品、鸡蛋和酒精饮料在部分而非所有验证性得分中具有预测性。基于得分每连续增加1个标准差，基于NHS的验证性得分可预测T2DM风险（风险比：1.44；95%置信区间：1.25，1.66）。然而，基于EPIC的得分（风险比：1.14；95%置信区间：0.99，1.32）和基于WS的得分（风险比：1.16；95%置信区间：1.00，1.35）对T2DM风险的预测作用较弱。
该研究表明，在不同人群中预测T2DM风险的饮食模式可能无法推广至其他不同人群。应开展更多关于可推广性的饮食模式研究。
