The prevalence of undernutrition among children in Malaysia: the difference between conventional assessments and the composite index of anthropometric failure

Background: Child undernutrition remains a significant public health concern in Malaysia, with implications for long-term growth, development, and health outcomes. Conventional indicators of underweight (UW), stunting (ST), and wasting (WT), which are widely used, may underestimate the true burden. This study aims to assess the prevalence and risk factors of undernutrition among children under five in Malaysia using both traditional measures and the Composite Index of Anthropometric Failure (CIAF). Methods: A secondary analysis was conducted using data from the National Health and Morbidity Survey (NHMS) 2022: Maternal and Child Health. Approximately 17,176 children under five were included in the study. Nutritional status was assessed using the WHO growth standards. The CIAF was applied to capture all forms of anthropometric failure. The complex sampling module in IBM SPSS 26 was used to analyse the data. Multivariable logistic regression models were performed to identify associated factors based on conventional indicators and CIAF classifications. Results: The prevalence of UW, ST, and WT was 15.3%, 21.2%, and 11.0%, respectively. The CIAF revealed an overall prevalence of undernutrition at 32.4% (95% CI: 31.0, 33.8), comprising 12.4% (95% CI: 11.5, 13.3) ST only, 4.9% (95% CI: 4.2, 5.7) WT only, and 1.8% (95% CI: 1.5, 2.1) UW only. Approximately 13.3% of the children exhibited more than one anthropometric failure. The determinants of underweight (region, strata, age, household income, and birth weight and length), stunting (region, strata, ethnicity, and birth weight and length), and wasting (region, age, sex, household income, and birth weight) varied, whereas the determinants for undernutrition based on the CIAF were region, strata, and birth weight and length. Conclusion: The CIAF offers a comprehensive representation by uncovering overlapping nutritional deficiencies that are often underestimated by conventional indicators. Integrating the CIAF into national monitoring systems could improve the precision of nutrition policies and ensure targeted, cost-effective interventions.

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