Child malnutrition remains a major global public health concern, with a disproportionately higher burden in developing countries such as Bangladesh. It is a leading contributor to childhood morbidity and mortality and has long-term consequences for physical growth, cognitive development, educational attainment, and adult productivity. Multiple socioeconomic and demographic factors are responsible for this condition. Therefore, this study aims to identify the factors associated with child malnutrition in Bangladesh using multivariate analytical approaches. In this study, malnutrition-related data from the Bangladesh Demographic and Health Survey (BDHS) 2022 were used. Multivariate analysis of variance (MANOVA) and multivariate linear regression models were performed to identify significant factors of child malnutrition in Bangladesh (p\: <0. 05). Multivariate linear regression analysis showed that the Z-scores for height-for-age (HAZ), weight-for-age (WAZ), and weight-for-height (WAH) among children aged 12–23 months were significantly lower compared to those aged < 12 months, with reductions of 32. 63, 24. 01, and 16. 40 units, respectively (p < 0. 001). Maternal underweight was negatively associated with all three anthropometric outcomes, whereas higher maternal education and better household wealth status were positively associated with improved nutritional outcomes. The findings of this study suggest that both governmental and non-governmental organizations should prioritize improving maternal education and nutritional status, enhancing household income-generating activities among disadvantaged populations, and promoting adequate birth spacing.
Rahman et al. (Sat,) studied this question.