Modeling data with excess zeros and measurement error: application to evaluating relationships between episodically consumed foods and health outcomes.
Modeling data with excess zeros and measurement error: application to evaluating relationships between episodically consumed foods and health outcomes.
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DOI：
10.1111/j.1541-0420.2009.01223.x
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发表时间：
2009-12
期刊：
影响因子：
1.9
通讯作者：
Freedman LS
中科院分区：
文献类型：
--
作者：
Kipnis V;Midthune D;Buckman DW;Dodd KW;Guenther PM;Krebs-Smith SM;Subar AF;Tooze JA;Carroll RJ;Freedman LS
对间歇性消费的食物进行膳食评估会产生非负数据，这些数据具有过多的零和测量误差。Journal of the American Dietetic Association 106，1575-1587）描述了一种通用统计方法（国家癌症研究所方法），用于对两次或更多次24小时回忆（24 HR）报告的这种食物摄入量进行建模，并证明了其用于估计一般人群中食物通常摄入量的分布。在这篇文章中，我们提出了一个扩展的这种方法来预测个人的日常摄入量，这些食物，并评估日常摄入量与健康结果的关系。根据测量误差校正的回归校准方法，个人通常的摄入量通常被预测为给定24小时报告的摄入量和健康模型中的其他协变量的条件平均摄入量。所提出的方法的一个特点是，额外的协变量可能与日常摄入量，可用于增加日常摄入量和饮食健康结果的关联估计的精度。将该方法应用于来自美国餐桌研究的数据，我们量化了从食物频率问卷（FFQ）中报告的摄入频率作为校准模型中的协变量获得的精度增加。然后，我们证明了该方法在评估的线性关系的日志血液中的汞含量和鱼类摄入量的妇女通过使用数据从全国健康和营养检查调查，并显示精度增加时，包括FFQ信息。最后，我们提出了模拟结果评估所提出的方法在这种情况下的性能。
Dietary assessment of episodically consumed foods gives rise to nonnegative data that have excess zeros and measurement error., Journal of the American Dietetic Association 106, 1575–1587) describe a general statistical approach (National Cancer Institute method) for modeling such food intakes reported on two or more 24-hour recalls (24HRs) and demonstrate its use to estimate the distribution of the food’s usual intake in the general population. In this article, we propose an extension of this method to predict individual usual intake of such foods and to evaluate the relationships of usual intakes with health outcomes. Following the regression calibration approach for measurement error correction, individual usual intake is generally predicted as the conditional mean intake given 24HR-reported intake and other covariates in the health model. One feature of the proposed method is that additional covariates potentially related to usual intake may be used to increase the precision of estimates of usual intake and of diet-health outcome associations. Applying the method to data from the Eating at America’s Table Study, we quantify the increased precision obtained from including reported frequency of intake on a food frequency questionnaire (FFQ) as a covariate in the calibration model. We then demonstrate the method in evaluating the linear relationship between log blood mercury levels and fish intake in women by using data from the National Health and Nutrition Examination Survey, and show increased precision when including the FFQ information. Finally, we present simulation results evaluating the performance of the proposed method in this context.
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影响因子：
3.7
作者：
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通讯作者：
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作者：
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10.1198/016214501753168389
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