Effect of screening out implausible energy intake reports on relationships between diet and BMI
Effect of screening out implausible energy intake reports on relationships between diet and BMI
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DOI：
10.1038/oby.2005.143
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发表时间：
2005-07-01
期刊：
影响因子：
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通讯作者：
McCrory, MA
中科院分区：
文献类型：
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作者：
Huang, TTK;Roberts, SB;McCrory, MA
目的：我们提出了一个更新的方法，通过比较报告的能量摄入量（rEI）与预测的能量需求（pER），确定生理上不合理的饮食报告，我们研究的影响，排除这些reports.Research方法和程序：成人数据的持续调查的食物摄入量的个人1994年至1996年。根据膳食参考摄入量方程计算pER。2天（d）内rEI [变异系数（CV）约为23%]、pER（CV约为11%）和测量的总能量消耗（mTEE;双标记水，CV约为8.2%）的受试者内变异和误差得到传播，其中+/- 1 SD =根C-V-rEI（2）/d+ CV 2（pER）+CV 2 mTEE = +/-22%。因此，如果rEI不在pER的78%-122%范围内，则报告被确定为不可信。结果：总样本（n = 6499）中的%rEI/pER = 81%，+/- 1 SD样本（n = 2685）中的%rEI/pER逐渐增加至95%。+/- 1至1.4 SD样本产生的rEI-体重相关性最接近理论关系（mTEE与体重）。弱或虚假的饮食BMI协会存在于总样本中; +/-1至1.4 SD样本显示出最强的关联集，并提供了最大的n，同时保持biologicalaccessibility.Discussion：我们的方法可以应用于不同的数据集，以评估不可信的rEI对健康结果的影响。不可信的rEI会降低样本的整体有效性，不排除它们可能会导致关于健康结果（如肥胖）的潜在饮食原因的不适当结论。
Objective: We present an updated method for identifying physiologically implausible dietary reports by comparing reported energy intake (rEI) with predicted energy requirements (pER), and we examine the impact of excluding these reports.Research Methods and Procedures: Adult data from the Continuing Survey of Food Intakes by Individuals 1994 to 1996 were used. pER was calculated from the dietary reference intake equations. Within-subject variations and errors in rEI [coefficient of variation (CV) approximate to 23%] over 2 days (d), pER (CV approximate to 11%), and measured total energy expenditure (mTEE; doubly labeled water, CV approximate to 8.2%) were propagated, where +/- 1 SD = root C-V-rEI(2)/d+ CV2 (pER) + CV2 mTEE = +/- 22%. Thus, a report was identified as implausible if rEI was not within 78% to 122% of pER. Multiple cut-offs between +/- 1 and 2 SD were tested.Results: %rEI/pER = 81% in the total sample (n = 6499) and progressively increased to 95% in the +/- 1 SD sample (n = 2685). The +/- 1 to 1.4 SD samples yielded rEI-weight associations closest to the theoretical relationship (mTEE to weight). Weak or spurious diet-BMI associations were present in the total sample; +/- 1 to 1.4 SD samples showed the strongest set of associations and provided the maximum n while maintaining biological plausibility.Discussion: Our methodology can be applied to different data sets to evaluate the impact of implausible rEIs on health outcomes. Implausible rEIs reduce the overall validity of a sample, and not excluding them may lead to inappropriate conclusions about potential dietary causes of health outcomes such as obesity.