ArticleJournal of research in health sciences2024
Diagnostic Accuracy of Mid-Upper Arm Circumference for the Detection of Acute Malnutrition Among Children Aged 6-60 Months: A Diagnostic Accuracy Study.
Article in Journal of research in health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Improving case-detection of wasting among under-five-year-old children in Ethiopia: A secondary analysis of community-based surveys in humanitarian settings.PLOS global public health · 2026Article
- Diagnostic accuracy of MUAC for assessment of acute malnutrition among children aged 6-59 months in Africa: systematic review and meta-analysis.Frontiers in nutrition · 2025Review
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTimely and accurate screening of malnutrition at the community level is essential to identifying malnourished children. The World Health Organization (WHO) guidelines classify non-oedematous acute malnutrition among children using mid-upper arm circumference (MUAC) or weight-for-height Z-score (WHZ).
methodsThis study was conducted among children aged 6‒60 months. After necessary exclusions, 433 participants were selected using a multi-stage simple random sampling method. Using WHO guidelines for global acute malnutrition (GAM) [WHZ<-2, MUAC<12.5 cm], the sensitivity (Se), specificity (Sp), predictive values, likelihood ratios, Youden index, and receiver operating characteristic (ROC) curve were calculated for MUAC using WHZ as the criterion.
resultsOut of 433 participants, 30% were diagnosed with GAM using WHZ, while 17.6% were found malnourished using MUAC measurements. As per WHO cut-offs, the Se, Sp, positive predictive value (PPV), negative predictive value (NPV), Youden index, positive likelihood ratio (LR+), and negative likelihood ratio (LR-) of MUAC were 48%, 96%, 83%, 81%, 0.44, 12, and 0.54, respectively. The ROC curve displayed an area under the curve of 0.86 (95% confidence interval=0.83, 0.90) for MUAC<12.5 cm. Bivariate Pearson correlation also demonstrated a positive linear relationship (R2=0.302) between the WHZ and MUAC variables.
conclusionBased on the findings, 48% of the children were correctly identified by the MUAC with an 83% probability of GAM (PPV=0.83). Moreover, there was 96% Sp in non-malnourished children, with only 4% false positives. Therefore, personnel at the grassroots level can use MUAC for timely and accurate screening of children in Anganwadi centers (AWCs) due to its ease of use and simplicity.
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