Improving Estimates of Numbers of Children With Severe Acute Malnutrition Using Cohort and Survey Data.

Abstract

Severe acute malnutrition (SAM) is reported to affect 19 million children worldwide. However, this estimate is based on prevalence data from cross-sectional surveys and can be expected to miss some children affected by an acute condition such as SAM. The burden of acute conditions is more appropriately represented by cumulative incidence data. In the absence of incidence data, a method for burden estimation has been proposed that corrects available prevalence estimates to account for incident cases using an "incidence correction factor." We used data from 3 West African countries (Mali, Niger, and Burkina Faso, 2009-2012) to test the hypothesis that a single incidence correction factor may be used for estimation of SAM burden. We estimated the incidence correction factor and performed meta-analysis to calculate summary estimates for each country and for all 3 countries. Heterogeneity between countries and years was assessed using the I2 statistic. We estimated a pooled incidence correction factor of 4.82 (95% confidence interval: 3.15, 7.38), although there was substantial between-country heterogeneity (I2=69%). Knowing how many children in a particular area will be malnourished is fundamental to planning an effective operational response. Our results show that the incidence correction factor varies widely and suggest that estimating the burden of SAM with a common incidence correction factor is unlikely to be adequate.