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Invited Commentary: Improving Estimates of Severe Acute Malnutrition Requires More Data

机译:特邀评论:改善严重急性营养不良的估计值需要更多数据

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摘要

In this issue of the Journal, Isanaka et al. (Am J Epidemiol. 2016; 184(12): 861-869) set out to update an incidence correction factor used for estimating numbers of cases of severe acute malnutrition (SAM) in children aged 6-59 months. The total number of current SAM cases (prevalent cases) increases by the number of new (incident) cases and decreases as a result of recovery or death. Prevalence estimates are obtained from cross-sectional surveys. Calculation of incidence typically requires longitudinal data, which evidently are rarely collected for SAM, and so a correction factor is applied instead. Isanaka et al. pool and meta-analyze data from longitudinal and community programs in 3 West African countries (Mali, Niger, and Burkina Faso), covering the period 2009-2012. Heterogeneity and the ongoing lack of data undermine the use of a single incidence correction factor for SAM estimates. Routine data collection is recommended as a way forward and aligns with recommendations of the World Health Organization. This commentary helps to outline a context for the use of such data and provide some perspective on the inadequacy of data, relative to the importance of the issue.
机译:在本期杂志中,Isanaka等人。 (Am J Epidemiol。2016; 184(12):861-869)着手更新一种发病率校正因子,用于估计6至59个月大的儿童中的严重急性营养不良(SAM)的病例数。当前的SAM病例(流行病例)总数随着新(事件)病例数的增加而增加,由于恢复或死亡而减少。患病率估计数是从横断面调查中获得的。发生率的计算通常需要纵向数据,显然很少为SAM收集这些数据,因此改用校正因子。 Isanaka等。对三个西非国家(马里,尼日尔和布基纳法索)的纵向和社区计划的数据进行汇总和荟萃分析,涵盖2009-2012年期间。异质性和数据的持续缺乏破坏了使用单个事件校正因子进行SAM估计。建议定期收集数据,并将其与世界卫生组织的建议保持一致。这篇评论有助于概述使用此类数据的背景,并就与问题的重要性相关的数据不足提供一些观点。

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