Mid upper arm circumference as a predictor of risk of mortality in children in a low resource setting in India

PLoS One. 2018 Jun 1;13(6):e0197832. doi: 10.1371/journal.pone.0197832. eCollection 2018.

Abstract

Objective: In this secondary analysis of data from an intervention trial, we assessed the performance of Mid Upper Arm Circumference (MUAC) as a predictor of mortality in children aged 6-59 months from Delhi, India, one year after their initial MUAC measurements were taken. Additionally, we assessed MUAC as an absolute value and MUAC z-scores as predictors of risk of mortality.

Methods: In the trial, children were screened using MUAC prior to referral to the study clinic. These children were revisited a year later to ascertain their vital status. Baseline MUAC and MUAC z-scores were used to categorize children as severely (MUAC <115 mm, MUAC z-score <-3SD) or moderately (MUAC 115 to <125 mm, MUAC z-score <-2SD) malnourished. The proportion of malnutrition, risk of mortality, relative risk estimates, positive predictive value and area under the curve (AUC) by MUAC and MUAC z-scores were calculated.

Results: In the resurvey, the first 36159 children of the 48635 in the initial survey were contacted. Of these, vital status of 34060 (94.2%) was available. The proportion of severe malnutrition by MUAC (<115 mm) was 0.5% with an associated mortality of 4.7% over a one year period and an attributable mortality of 13% while the proportion of the severe malnutrition by MUAC z-score (<-3SDwas 0.9% with an associated mortality of 2.2%.

Conclusions: MUAC is a significant predictor of subsequent mortality in under-five children. In settings where height measurement is not feasible, MUAC can be used as a screening tool for identifying severely malnourished children for management.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Arm / anatomy & histology*
  • Child Mortality*
  • Child, Preschool
  • Female
  • Health Resources / supply & distribution*
  • Humans
  • India / epidemiology
  • Infant
  • Male
  • Risk Assessment