Department of Nutrition, University of California, Davis, Davis, CA, USA.
Institute for Global Nutrition, University of California, Davis, CA, USA.
Adv Nutr. 2021 Mar 31;12(2):429-451. doi: 10.1093/advances/nmaa114.
Determining the proportion of a population at risk of inadequate or excessive nutrient intake is a crucial step in planning and managing nutrition intervention programs. Multiple days of 24-h dietary intake data per subject allow for adjustment of modeled usual nutrient intake distributions for the proportion of total variance in intake attributable to within-individual variation (WIV:total). When only single-day dietary data are available, an external adjustment factor can be used; however, WIV:total may vary by population, and use of incorrect WIV:total ratios may influence the accuracy of prevalence estimates and subsequent program impacts. WIV:total values were compiled from publications and from reanalyses of existing datasets to describe variation in WIV:total across populations and settings. The potential impact of variation in external WIV:total on estimates of prevalence of inadequacy was assessed through simulation analyses using the National Cancer Institute 1-d method. WIV:total values were extracted from 40 publications from 24 countries, and additional values were calculated from 15 datasets from 12 nations. Wide variation in WIV:total (from 0.02 to 1.00) was observed in publications and reanalyses. Few patterns by population characteristics were apparent, but WIV:total varied by age in children (< vs. >1 y) and between rural and urban settings. Simulation analyses indicated that estimates of the prevalence of inadequate intake are sensitive to the selected ratio in some cases. Selection of an external WIV:total estimate should consider comparability between the reference and primary studies with regard to population characteristics, study design, and statistical methods. Given wide variation in observed ratios with few discernible patterns, the collection of ≥2 days of intake data in at least a representative subsample in population dietary studies is strongly encouraged. In the case of single-day dietary studies, sensitivity analyses are recommended to determine the robustness of prevalence estimates to changes in the variance ratio.
确定人群中营养摄入不足或过量的比例,是规划和管理营养干预项目的关键步骤。每位研究对象采集多天 24 小时饮食摄入数据,可对模型化的通常营养素摄入分布进行调整,以反映摄入个体内变异(WIV:总)所导致的总变异比例。当仅获取单天饮食数据时,可以使用外部调整因子;然而,WIV:总可能因人群而异,使用不正确的 WIV:总比值可能会影响患病率估计的准确性以及后续项目的效果。WIV:总值是从文献中以及对现有数据集的重新分析中汇编而来,用于描述不同人群和环境下 WIV:总的变化情况。通过使用国家癌症研究所的 1 天法进行模拟分析,评估了外部 WIV:总变化对营养不足患病率估计的潜在影响。从 24 个国家的 40 篇文献中提取 WIV:总值,并从 12 个国家的 15 个数据集计算得到其他 WIV:总值。在文献和重新分析中观察到 WIV:总(0.02 至 1.00)的变化范围很广。根据人群特征,WIV:总没有明显的变化模式,但在儿童(<1 岁与>1 岁)和城乡环境之间,WIV:总随年龄而变化。模拟分析表明,在某些情况下,选择的比值会影响摄入不足的患病率估计。在选择外部 WIV:总估计值时,应考虑参考和主要研究在人群特征、研究设计和统计方法方面的可比性。鉴于观察到的比值变化范围很广,且模式很少,强烈建议在人群饮食研究中,至少在代表性子样本中收集≥2 天的摄入数据。在仅获取单天饮食数据的情况下,建议进行敏感性分析,以确定患病率估计值对方差比变化的稳健性。