AUTHOR=Menber Yonatan , Belachew Tefera , Fentahun Netsanet 

TITLE=Diagnostic accuracy of MUAC for assessment of acute malnutrition among children aged 6–59 months in Africa: systematic review and meta-analysis

JOURNAL=Frontiers in Nutrition

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2025.1536386

DOI=10.3389/fnut.2025.1536386

ISSN=2296-861X

ABSTRACT=BackgroundMid-Upper Arm Circumference (MUAC) or Weight-for-Length Z-Score (WHZ) are used to screen for acute malnutrition in children. The relative merits of MUAC and WHZ, as well as whether they ought to be used separately, are still up for debate. Considering the significant impact of acute malnutrition on a large number of children in Africa, along with the constraints on resources, it is crucial to critically assess the validity of simple and widely used tools utilized in both African communities and clinical settings. Therefore, this study aimed to assess the diagnostic test accuracy of MUAC in screening acute malnutrition among children aged 6–59 months in Africa.MethodsA systematic review and meta-analysis study was conducted to pool evidence on the diagnostic performance of MUAC compared to WHZ among children aged 6 to 59 months across various studies in Africa. The StataMP 17.0 software was utilized for analysis, employing a Bivariate Random-effects Meta-Analysis model. Sensitivity, specificity, the Diagnostic Odds Ratio, and the Area Under the Curve were calculated. Heterogeneity was assessed using Cochrane’s Q statistic and the I2 test. Additionally, meta-regression, subgroup analysis, sensitivity analysis, and assessments for publication bias were employed. The overall level of diagnostic test accuracy was estimated using a random-effects meta-analysis model.ResultsSeventeen studies were included in the meta-analysis. The pooled sensitivity and specificity were 38.1% (95% CI: 30.7, 46.1%) and 94.9% (95% CI: 93.2, 96.2%), respectively. The summary receiver operating characteristic curve plot showed that MUAC had good accuracy in detecting acute malnutrition (AUC = 0.85, 95% CI: 0.82, 0.88). The pooled level of diagnostic odds ratio was 13.22 (95% CI: 9.68, 16.77). The rate of misclassification in screening for acute malnutrition using MUAC was observed to be 11.7%.ConclusionThe MUAC demonstrated low sensitivity but high specificity in diagnosing acute malnutrition in children aged 6 to 59 months across various regions of Africa. Furthermore, it was found that MUAC provides good diagnostic test accuracy when compared to WHZ. To enhance its accuracy, it is suggested to increase the MUAC cutoff thresholds.