Routinely MUAC screening for severe acute malnutrition should consider the gender and age group bias in the Ethiopian non-emergency context

PLoS One. 2020 Apr 9;15(4):e0230502. doi: 10.1371/journal.pone.0230502. eCollection 2020.

Abstract

Early identification of children <5 years with severe acute malnutrition (SAM) is a high priority to reduce child mortality and improved health outcomes. Current WHO guidelines for community screening for SAM recommend a Mid-Upper-Arm Circumference (MUAC) of less than 115 mm to identify children with SAM, but this cut-off does not identify a significant number of children with a weight-for-height Z-score <-3. To establish new specific MUAC cut-offs, pooled data was obtained for 25,755 children from 49 SMART recent surveys in Ethiopia (2016-2019). Sensitivity, proportion of false positive, and areas under receiver-operator characteristic curves (AUC) were calculated. MUAC below 115mm alone identified 55% of children with SAM identified with both methodologies. MUAC was worse in identifying older children (21%), those from a pastoral region (42%) and boys (41%). Using current WHO cut-offs, the sensitivity (Se) of MUAC below 115mm to identify the children severly malnourished screened through Weight-for-height below-3 was 16%. Analysing the ROC curve and Youden Index, Se and Specificity (Sp) were maximal at a MUAC < 133 mm cut-off to identify SAM (respectively Se 61.1%, Sp 81.4%). However, given the high proportion of false-positive children, according to gender, region and age groups, a cut-off around 125 mm to screen SAM could be the optimal one. In Ethiopia, implementation of a MUAC-only screening program for the identification of severe acute malnutrition with the actual cut-off of 115 mm would be unethical as it will lead to many children remaining undiagnosed and untreated. In addition, future study on implementation challenge on screening children with a higher cut-off or gender/age sensitive ones should be assessed with the collection of mortality and morbidity data to ensure that the most in need are being taking care of.

Publication types

  • Evaluation Study

MeSH terms

  • Age Factors
  • Arm / anatomy & histology*
  • Bias
  • Body Height / physiology
  • Body Weight / physiology
  • Body Weights and Measures / methods*
  • Child Development / physiology*
  • Child, Preschool
  • Diagnostic Tests, Routine / methods
  • Ethiopia / epidemiology
  • Female
  • Growth Charts
  • Health Status Indicators
  • Humans
  • Infant
  • Male
  • Mass Screening / methods
  • ROC Curve
  • Sensitivity and Specificity
  • Severe Acute Malnutrition / diagnosis*
  • Severe Acute Malnutrition / epidemiology
  • Sex Factors

Grants and funding

The author(s) received no specific funding for this work.