Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China.
Biostatistics and Bioinformatics Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD, USA.
Am J Clin Nutr. 2020 Oct 1;112(4):920-925. doi: 10.1093/ajcn/nqaa176.
Dietary interventions often target foods that are underconsumed relative to dietary guidelines, such as vegetables, fruits, and whole grains. Because these foods are only consumed episodically for some participants, data from such a study often contains a disproportionally large number of zeros due to study participants who do not consume any of the target foods on the days that dietary intake is assessed, thus generating semicontinuous data. These zeros need to be properly accounted for when calculating sample sizes to ensure that the study is adequately powered to detect a meaningful intervention effect size. Nonetheless, this issue has not been well addressed in the literature. Instead, methods that are common for continuous outcomes are typically used to compute the sample sizes, resulting in a substantially under- or overpowered study. We propose proper approaches to calculating the sample size needed for dietary intervention studies that target episodically consumed foods. Sample size formulae are derived for detecting the mean difference in the amount of intake of an episodically consumed food between an intervention and a control group. Numerical studies are conducted to investigate the accuracy of the sample size formulae as compared with the ad hoc methods. The simulation results show that the proposed formulae are appropriate for estimating the sample sizes needed to achieve the desired power for the study. The proposed method for sample size is recommended for designing dietary intervention studies targeting episodically consumed foods.
饮食干预通常针对相对饮食指南摄入不足的食物,如蔬菜、水果和全谷物。由于这些食物对于一些参与者来说只是偶尔食用,因此此类研究中的数据通常由于研究参与者在评估饮食摄入量的日子里没有食用任何目标食物而包含大量的零值,从而产生半连续数据。在计算样本量时,需要正确考虑这些零值,以确保研究有足够的能力检测到有意义的干预效果大小。尽管如此,这个问题在文献中并没有得到很好的解决。相反,通常用于连续结果的方法用于计算样本量,导致研究的效力不足或过度。我们提出了针对间歇性食用食物的饮食干预研究计算所需样本量的适当方法。推导了用于检测干预组和对照组之间间歇性食用食物摄入量的平均值差异的样本量公式。进行了数值研究,以调查与特定方法相比,样本量公式的准确性。模拟结果表明,所提出的公式适用于估计达到研究所需效力所需的样本量。建议使用针对间歇性食用食物的饮食干预研究的推荐样本量方法。