Determining an optimal case definition using mid-upper arm circumference with or without weight for age to identify childhood wasting in the Philippines

In resource-limited areas, where accurate weight-for-height Z-scores are hard to obtain, Mid-Upper Arm Circumference (MUAC) is a simple tool to identify wasted children. MUAC alone, however, may miss identification of many wasted children, leading to untimely intervention and potentially death. Our study aimed to identify the best-performing case definition to detect wasting by Weight-for-Height z-scores (WHZ) in Filipino children aged 6-59 months. We analyzed the 2018-2019 Expanded National Nutrition Survey to assess the diagnostic performance of MUAC cutoffs and a case definition combining MUAC and weight-for-age z-score (WAZ) in identifying moderate and severe wasting compared to the WHZ criterion. The optimal cutoff and case definition was identified as having the highest area under the receiver operating characteristic curve (AUROC). Our findings showed that the current MUAC cutoffs poorly identify severe (sensitivity: 13%; specificity: 99%; AUROC: 0.558) and moderate (sensitivity: 22%; specificity: 96%; AUROC: 0.586) wasting (N = 30,522) in Filipino children. Instead, the optimal MUAC cutoff for severe and moderate wasting were <13.6cm (sensitivity: 62%; specificity: 76%; AUROC: 0.690) and 14.0cm (sensitivity: 80%; specificity: 67%; AUROC: 0.737). There was no effect of sex on MUAC cutoffs, but cutoffs increased with age. We found that the combination of WAZ < -2 or MUAC ≤ 11.7cm (Sensitivity: 80%; Specificity: 80%; AUROC: 0.800) for severe wasting and WAZ < -2 or MUAC ≤ 12.7cm (Sensitivity: 84%; Specificity: 78%; AUROC: 0.810) for moderate wasting significantly improved sensitivity for acceptable decreases in specificity. In summary, implementing alternative case definitions solely based on expanding MUAC insufficiently improves diagnostic accuracy for identifying wasted children by WHZ criteria. Combining WAZ with MUAC could increase the number of eligible children identified and treated by the Philippine Integrated Management of Acute Malnutrition. Further studies are advised to understand the practicality and cost-effectiveness of using the proposed alternative case definitions in the Philippines.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2024-12-27
DOI
https://doi.org/10.1371/journal.pone.0315253
Citations
1
Primary Topic
Child Nutrition and Water Access
Type
article
Field-Weighted Citation Impact
0.31

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Determining an optimal case definition using mid-upper arm circumference with or without weight for age to identify childhood wasting in the Philippines

Valerie Gilbert Ulep, Behzad Noubary, Mueni Mutunga, Charmaine Duante et al.
1 citations
PLoS ONE
Child Nutrition and Water Access
0.31
article

Determining an optimal case definition using mid-upper arm circumference with or without weight for age to identify childhood wasting in the Philippines

Valerie Gilbert Ulep, Behzad Noubary, Mueni Mutunga, Charmaine Duante, Sanele Nkomani, Paluku Bahwere, Eldridge Ferrer, Roland Kupka, Lyle Daryll Casas, Jhanna Uy, Alice Nkoroi, Rene Gerard Jr. Galera
article en
1 citations

Abstract

In resource-limited areas, where accurate weight-for-height Z-scores are hard to obtain, Mid-Upper Arm Circumference (MUAC) is a simple tool to identify wasted children. MUAC alone, however, may miss identification of many wasted children, leading to untimely intervention and potentially death. Our study aimed to identify the best-performing case definition to detect wasting by Weight-for-Height z-scores (WHZ) in Filipino children aged 6-59 months. We analyzed the 2018-2019 Expanded National Nutrition Survey to assess the diagnostic performance of MUAC cutoffs and a case definition combining MUAC and weight-for-age z-score (WAZ) in identifying moderate and severe wasting compared to the WHZ criterion. The optimal cutoff and case definition was identified as having the highest area under the receiver operating characteristic curve (AUROC). Our findings showed that the current MUAC cutoffs poorly identify severe (sensitivity: 13%; specificity: 99%; AUROC: 0.558) and moderate (sensitivity: 22%; specificity: 96%; AUROC: 0.586) wasting (N = 30,522) in Filipino children. Instead, the optimal MUAC cutoff for severe and moderate wasting were <13.6cm (sensitivity: 62%; specificity: 76%; AUROC: 0.690) and 14.0cm (sensitivity: 80%; specificity: 67%; AUROC: 0.737). There was no effect of sex on MUAC cutoffs, but cutoffs increased with age. We found that the combination of WAZ < -2 or MUAC ≤ 11.7cm (Sensitivity: 80%; Specificity: 80%; AUROC: 0.800) for severe wasting and WAZ < -2 or MUAC ≤ 12.7cm (Sensitivity: 84%; Specificity: 78%; AUROC: 0.810) for moderate wasting significantly improved sensitivity for acceptable decreases in specificity. In summary, implementing alternative case definitions solely based on expanding MUAC insufficiently improves diagnostic accuracy for identifying wasted children by WHZ criteria. Combining WAZ with MUAC could increase the number of eligible children identified and treated by the Philippine Integrated Management of Acute Malnutrition. Further studies are advised to understand the practicality and cost-effectiveness of using the proposed alternative case definitions in the Philippines.

PLoS ONEVol. 19(12)
Ateneo de Manila University (PH), Nutrition Center of the Philippines (PH), UNICEF East Asia and Pacific Regional Office (TH), University of the Philippines Manila (PH)
UNICEF
Zero hunger
Openalex Percentile: Top 39%
Child Nutrition and Water Access
0.31
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.