Ferrari Pietro, Kaaks Rudolf, Fahey Michael T, Slimani Nadia, Day Nicholas E, Pera Guillem, Boshuizen Hendriek C, Roddam Andrew, Boeing Heiner, Nagel Gabriele, Thiebaut Anne, Orfanos Philippos, Krogh Vittorio, Braaten Tonje, Riboli Elio
Unit of Nutrition and Cancer, International Agency for Research on Cancer, Lyon, France.
Am J Epidemiol. 2004 Oct 15;160(8):814-22. doi: 10.1093/aje/kwh280.
Multicenter epidemiologic studies provide a unique opportunity to evaluate the association between exposure and disease at the individual and the aggregate levels. The two components can eventually be pooled to corroborate each other, using weights proportional to the intraclass correlation coefficient (ICC), which expresses the amount of between-cohort variability in the exposure variable compared with the total. The greater the ICC, the more the overall estimate will reflect the between-cohort component. Dietary measurements are affected by measurement errors, particularly within a cohort. In 1992-2000, the variability of macronutrient intake distribution before and after calibration for measurement error in the European Prospective Investigation into Cancer and Nutrition was evaluated. A two-level, random-effects model was used. Evaluation of macronutrient densities revealed that energy has a considerable effect on the calibration model, leading to ICC values larger than those for the absolute intakes. Given the shrinkage of the within-center variability, a sizable increase in the ICC was observed for protein in men and women (0.48 and 0.54, respectively) and carbohydrates in men (0.41). Results suggest that the effect of calibration on macronutrient intake variability is greater for the within-cohort component, thus increasing the relative importance of the between-cohort component. After calibration, the two components had a similar weight. This observation has important implications for the analysis of multicenter studies because the between-cohort component provides a large part of the overall heterogeneity.
多中心流行病学研究提供了一个独特的机会，可在个体和总体水平上评估暴露与疾病之间的关联。最终，可以使用与组内相关系数（ICC）成比例的权重将这两个部分合并起来相互印证，ICC表示暴露变量在队列间的变异性与总体变异性相比的大小。ICC越大，总体估计就越能反映队列间的部分。膳食测量受到测量误差的影响，尤其是在一个队列内部。在1992年至2000年期间，对欧洲癌症与营养前瞻性调查中经测量误差校准前后的常量营养素摄入分布变异性进行了评估。使用了两级随机效应模型。对常量营养素密度的评估表明，能量对校准模型有相当大的影响，导致ICC值大于绝对摄入量的ICC值。鉴于中心内变异性的收缩，观察到男性和女性蛋白质（分别为0.48和0.54）以及男性碳水化合物（0.41）的ICC有相当大的增加。结果表明，校准对常量营养素摄入变异性的影响在队列内部分更大，从而增加了队列间部分的相对重要性。校准后，这两个部分的权重相似。这一观察结果对多中心研究的分析具有重要意义，因为队列间部分提供了总体异质性的很大一部分。
