从家庭消费和支出调查中计算营养素不足的程度:案例研究

Ana Moltedo, Cristina Álvarez-Sánchez, Nathalie Troubat, Carlo Cafiero
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引用次数: 0

摘要

本文介绍了一种利用家庭消费和支出调查(HCES)数据估算营养素摄入量受试者间变异性(通过变异系数[CV])的方法,以及一种估算营养素摄入不足流行率(PoNI)(针对八种微量营养素)的方法。流行率值与使用国家癌症研究所方法得出的个人水平估计值进行了比较。数据来自 2015 年孟加拉国综合住户调查(Bangladesh Integrated-Household-Survey ),该调查对同一农村住户进行了家庭层面的 7 天回忆(7DR)和两轮个人层面的 24 小时回忆(24HR),由一名受访者代表所有成员填写。根据 7DR 计算出的 PoNI 值低于根据 24HR 数据计算出的 PoNI 值,这是因为 7DR 数据中的平均摄入量估计值较大。在控制了平均摄入量估计值的差异并对家庭层面的数据进行了随机测量误差调整后,7DR 和 24HR 数据得出的 PoNI 值非常接近。这凸显了 HCES 数据(根据国际公认标准进行)在估算人群通常营养素摄入量的受试者间变异水平方面的潜在用途。HCES 的 CV 值可用于利用个人层面数据的平均摄入量估算值计算 PoNI;以及利用供应和利用账户数据计算全球营养素供应量的不足之处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computing levels of nutrient inadequacy from household consumption and expenditure surveys: A case study
This paper presents an approach to estimate the between-subject variability in nutrient intake (through the coefficient of variation [CV]) and a method to estimate the prevalence of nutrient inadequacy (PoNI) (for eight micronutrients) using household consumption and expenditure survey (HCES) data. Prevalence values are compared to individual-level estimates derived using the National-Cancer-Institute method. Data come from the 2015 Bangladesh Integrated-Household-Survey, which conducted a household-level 7-day recall (7DR) and two rounds of individual-level 24-hour recall (24HR), filled by one respondent on behalf of all members, for the same rural households. The PoNI values based on 7DR are lower than those calculated from 24HR data, due to the larger average intake estimates from 7DR data. After controlling for differences in average intake estimates and adjusting household-level data for random measurement errors, the PoNI values from 7DR and 24HR data are remarkably close. This highlights the potential use of HCES data (conducted according to international agreed standards) for estimating the level of between-subject variability in usual nutrient intake in a population. The CVs from HCES could be used to compute the PoNI using average intake estimates from individual-level data; and the inadequacy of global nutrient supply using Supply and Utilization Accounts data.
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