Detecting severe acute malnutrition in children under five at scale : the challenges of anthropometry to reach the missed millions
2016
Objective: Severe Acute Malnutrition (SAM) interventions aim to detect and
treat children at highest risk of death who benefit most from treatment. SAM
services reach less than 20% of affected children worldwide, and innovative
policy changes are needed to scale up services. This paper discusses
anthropometry to diagnose SAM as one pathway to improve the effectiveness
coverage of SAM services.
Results: WHO defines SAM by either MUAC <115 mm or WHZ <−3 or
the presence of nutritional oedema. Both MUAC and WHZ are proxy indicators
of a clinical condition, and neither is a gold standard. Because they measure
different characteristics of the same illness, MUAC and WHZ identify different
SAM populations that overlap differently in different contexts across and
within countries. MUAC is a better predictor of mortality and has the practical
advantages of simplicity, reliability and accuracy. Using both indicators
independently identifies more children and loses sensitivity to risk of death.
Discussion and Conclusion: Based on current evidence and operational
and policy considerations, using MUAC only for diagnosing SAM with a countryadapted cut-off could feasibly scale up SAM services and improve coverage to
reach the millions of missed children. Meanwhile, continued research on the
biomedical consequences and policy implications of this approach, as well as
innovations such as system dynamics modeling, may contribute to the evidence.
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