Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany.
NutriAct-Competence Cluster Nutrition Research Berlin-Potsdam, Germany.
Am J Clin Nutr. 2018 Feb 1;107(2):227-235. doi: 10.1093/ajcn/nqx027.
Principal component analysis (PCA) is a widely used exploratory method in epidemiology to derive dietary patterns from habitual diet. Such dietary patterns seem to originate from intakes on multiple days and eating occasions. Therefore, analyzing food intake of study populations with different levels of food consumption can provide additional insights as to how habitual dietary patterns are formed.
We analyzed the food intake data of German adults in terms of the relations among food groups from three 24-h dietary recalls (24hDRs) on the habitual, single-day, and main-meal levels, and investigated the contribution of each level to the formation of PCA-derived habitual dietary patterns.
Three 24hDRs were collected in 2010-2012 from 816 adults for an European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam subcohort study. We identified PCA-derived habitual dietary patterns and compared cross-sectional food consumption data in terms of correlation (Spearman), consistency (intraclass correlation coefficient), and frequency of consumption across all days and main meals. Contribution to the formation of the dietary patterns was obtained through Spearman correlation of the dietary pattern scores.
Among the meals, breakfast appeared to be the most consistent eating occasion within individuals. Dinner showed the strongest correlations with "Prudent" (Spearman correlation = 0.60), "Western" (Spearman correlation = 0.59), and "Traditional" (Spearman correlation = 0.60) dietary patterns identified on the habitual level, and lunch showed the strongest correlations with the "Cereals and legumes" (Spearman correlation = 0.60) habitual dietary pattern.
Higher meal consistency was related to lower contributions to the formation of PCA-derived habitual dietary patterns. Absolute amounts of food consumption did not strongly conform to the habitual dietary patterns by meals, suggesting that these patterns are formed by complex combinations of variable food consumption across meals. Dinner showed the highest contribution to the formation of habitual dietary patterns. This study provided information about how PCA-derived dietary patterns are formed and how they could be influenced.
主成分分析（PCA）是一种广泛应用于流行病学的探索性方法，可从习惯性饮食中得出饮食模式。这些饮食模式似乎源于多天和多个进食场合的摄入量。因此，分析具有不同食物摄入量的研究人群的食物摄入情况，可以更深入地了解习惯性饮食模式是如何形成的。
我们分析了德国成年人的食物摄入数据，这些数据涉及到从三次 24 小时膳食回顾（24hDR）中获得的食物组之间的关系，分别是习惯性、单日和主餐水平，同时还研究了每个水平对 PCA 得出的习惯性饮食模式形成的贡献。
2010-2012 年，欧洲癌症与营养前瞻性调查（EPIC）-波茨坦子队列研究收集了 816 名成年人的三次 24hDR。我们确定了 PCA 得出的习惯性饮食模式，并根据相关性（Spearman）、一致性（组内相关系数）和所有天数和主餐的消费频率，比较了横断面食物消费数据。通过饮食模式得分的 Spearman 相关性，获得对饮食模式形成的贡献。
在餐次方面，早餐似乎是个体内最一致的进食场合。晚餐与“谨慎”（Spearman 相关性=0.60）、“西方”（Spearman 相关性=0.59）和“传统”（Spearman 相关性=0.60）饮食模式在习惯性水平上的相关性最强，午餐与“谷物和豆类”（Spearman 相关性=0.60）习惯性饮食模式的相关性最强。
更高的餐次一致性与 PCA 得出的习惯性饮食模式形成的贡献较低有关。食物的绝对摄入量与各餐的饮食模式并不完全一致，这表明这些模式是由各餐之间的可变食物摄入量的复杂组合形成的。晚餐对习惯性饮食模式的形成贡献最大。本研究提供了关于 PCA 得出的饮食模式是如何形成的以及它们如何受到影响的信息。
Zotero 插件