Structural Equation Modelling of Socioeconomic Status on Malnutrition Among Urban Preschoolers: Multi-Group Analysis of Hungary and Indonesia

Background: Child malnutrition is a major public health problem worldwide, but the pathways through which socioeconomic status (SES) affects nutritional outcomes differ markedly between economic and welfare regimes. Differentiating whether these impacts are direct or through behavioural and structural factors is key to focused policy intervention. Objective: This study aimed to investigate the effects of socioeconomic inequalities, maternal knowledge and feeding practices, and food insecurity on preschool undernutrition in Hungary and Indonesia. Methods: The study employs a cross-national comparative design. Respondents were households with children 36 to 59 months old; the sample comprised 128 households in Budapest, Hungary and 535 households in Surabaya, Indonesia. The instruments were designed to fit within a survey for data collection. Data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) with Multi-Group Analysis (MGA). Results: In Hungary, SES and food insecurity are positively associated with malnutrition, whereas in Indonesia, SES and biological factors drive malnutrition. Intermediate factors such as maternal feeding practices (Hungary) and health coverage (Indonesia) did not directly affect malnutrition. Although the model identified significant socioeconomic pathways, its very low explanatory and predictive power for child malnutrition in both urban Hungary (R2 = 0.024) and Indonesia (R2 = 0.062), and the predictive relevance ((Q2 Hungary: −0.009); Q2 Indonesia: 0.016), which remained close to zero or negative, indicate that these variables only partially capture the complex, multifactorial mechanisms driving nutritional status. Conclusions: These findings indicate that a more targeted approach to food insecurity and behavioural screening within the Hungarian welfare system would be necessary to address malnutrition effectively. Findings in Indonesia underline the potential benefits of prioritising equity in health coverage and income support.