What type of study is this?

This is a Cross-Sectional Study study (also classified as: Pre-Registered Trial, Validation Study).

What question did this study set out to answer?

This research assesses the prevalence of undernutrition and MUACZ's diagnostic performance in children with cerebral palsy.

March 8, 2026Open Access

Diagnostic accuracy of mid-upper arm circumference-for-age Z-score (MUACZ) for detecting malnutrition in children with cerebral palsy: a cross-sectional study

Key Points

This research assesses the prevalence of undernutrition and MUACZ's diagnostic performance in children with cerebral palsy.
Cross-sectional design including 81 children with CP aged 2–18 years
Nutritional status assessed using BMI-for-age, height-for-age, and MUACZ
Functional severity classified using GMFCS and EDACS
Diagnostic accuracy of MUACZ evaluated with ROC analysis
Multivariate logistic regression to identify predictors of undernutrition.
63% of the cohort faced undernutrition, increasing with functional severity
MUACZ showed fair accuracy for detecting wasting (AUC = 0.757)
Strongest MUACZ performance in children aged 5–10 years (AUC = 0.866)
Older age and higher GMFCS levels predicted undernutrition.

Abstract

Malnutrition is common in children with cerebral palsy (CP) due to feeding difficulties, altered body composition, and functional limitations, making an accurate nutritional assessment essential. The mid-upper arm circumference-for-age Z-score (MUACZ) is a practical screening tool, yet its diagnostic performance across childhood and adolescence remains insufficiently defined. The objective of this study was to assess the prevalence of undernutrition in children suffering from CP as well as the diagnostic performance of MUACZ in comparison with other anthropometric indicators across different age groups. This cross-sectional study included 81 children with CP aged 2–18 years. Nutritional status was assessed using BMI-for-age (BAZ), height-for-age (HAZ), and MUACZ. Functional severity was classified using validated systems (GMFCS and EDACS). The diagnostic accuracy of MUACZ was evaluated with ROC analysis, and predictors of undernutrition were identified using multivariate logistic regression. Undernutrition (BAZ or HAZ ≤ − 2) affected 63% of the cohort, and its prevalence increased markedly with functional severity, reaching 88.6% in GMFCS level V compared with 10% in level I (p < 0.001). MUACZ showed fair accuracy for detecting wasting (AUC = 0.757), with its strongest performance observed in children aged 5–10 years (AUC = 0.866). Older age and higher GMFCS levels were independent predictors of undernutrition. Malnutrition in CP is closely linked to functional severity. MUACZ is simple, feasible, and may serve as a supportive screening tool to help identify undernutrition in children with CP. ClinicalTrials.gov NCT07351695 (Retrospectively registered).

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