Jasani KM, Gosalia VV, Misra SV. Diagnostic Accuracy of Mid-Upper Arm Circumference for the Detection of Acute Malnutrition Among Children Aged 6-60 Months: A Diagnostic Accuracy Study.
J Res Health Sci 2024;
24:e00612. [PMID:
39072548 PMCID:
PMC11264450 DOI:
10.34172/jrhs.2024.147]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 04/02/2024] [Accepted: 05/11/2024] [Indexed: 07/30/2024] Open
Abstract
BACKGROUND
Timely 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). Study Design: A cross-sectional study.
METHODS
This 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.
RESULTS
Out 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.
CONCLUSION
Based 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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