A new statistical method for estimating the usual intake of episodically consumed foods with application to their distribution
A new statistical method for estimating the usual intake of episodically consumed foods with application to their distribution
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DOI：
10.1016/j.jada.2006.07.003
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发表时间：
2006-10-01
影响因子：
--
通讯作者：
Kipnis, Victor
中科院分区：
文献类型：
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作者：
Tooze, Janet A.;Midthune, Douglas;Kipnis, Victor
目的我们提出了一种新的统计方法，使用信息从两个24小时召回，以估计通常摄入的偶发性消费foods.Statistical analysisperformed的方法开发的美国国家癌症研究所（NCI）适应大量的非消费日发生的食物通过分离的消费概率从消费日金额，使用两部分模型。协变量，如性别，年龄，种族，或来自食物频率问卷的信息，可以使用相关混合模型回归补充来自两个或更多个24小时回忆的信息。该模型允许在一天内消费食物的概率和消费量之间的相关性。通常的摄入量的分布的百分位数计算从估计的模型parameters.Results在美国的餐桌上吃的研究数据被用来说明的方法来估计分布的全谷物和深绿色蔬菜的男性和女性和男性的教育水平的全谷物的通常摄入量的分布。模拟研究表明，NCI方法导致现有的方法估计的分布，通常摄入的foods.Conclusions的NCI方法提供了显着的优势，比以前提出的方法占消费概率和消费量之间的相关性，并将协变量信息。有兴趣估计一个人口或亚人口的食物通常摄入量分布的研究人员建议与统计学家合作，并将NCI方法纳入分析。
Objective We propose a new statistical method that uses information from two 24-hour recalls to estimate usual intake of episodically consumed foods.Statistical analyses performed The method developed at the National Cancer Institute (NCI) accommodates the large number of nonconsumption days that occur with foods by separating the probability of consumption from the consumption-day amount, using a two-part model. Covariates, such as sex, age, race, or information from a food frequency questionnaire, may supplement the information from two or more 24-hour recalls using correlated mixed model regression. The model allows for correlation between the probability of consuming a food on a single day and the consumption-day amount. Percentiles of the distribution of usual intake are computed from the estimated model parameters.Results The Eating at America's Table Study data are used to illustrate the method to estimate the distribution of usual intake for whole grains and dark-green vegetables for men and women and the distribution of usual intakes of whole grains by educational level among men. A simulation study indicates that the NCI method leads to substantial improvement over existing methods for estimating the distribution of usual intake of foods.Conclusions The NCI method provides distinct advantages over previously proposed methods by accounting for the correlation between probability of consumption and amount consumed and by incorporating covariate information. Researchers interested in estimating the distribution of usual intakes of foods for a population or subpopulation are advised to work with a statistician and incorporate the NCI method in analyses.