Literature DB >> 27856449

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

Alexis Hure, Christopher Oldmeadow, John Attia.   

Abstract

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.
© The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  child; correction factor; incidence; malnutrition; public health; severe acute malnutrition

Mesh:

Year:  2016        PMID: 27856449     DOI: 10.1093/aje/kww131

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  11 in total

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9.  Response to Malnutrition Treatment in Low Weight-for-Age Children: Secondary Analyses of Children 6-59 Months in the ComPAS Cluster Randomized Controlled Trial.

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10.  Improving estimates of the burden of severe acute malnutrition and predictions of caseload for programs treating severe acute malnutrition: experiences from Nigeria.

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