SOCIOECONOMIC DISPARITIES AS PREDICTORS OF NUTRITION INEQUALITIES AMONG CHILDREN UNDER FIVE IN HUNGARY AND INDONESIA
Arie Dwi Alristina
Health Sciences
Dr. Nagy Zoltán Zsolt
SE ETK Szél Éva terem
2026-08-25 14:00:00
Interdisciplinary applied health sciences
Dr. Vingender István
Dr. Feith Helga
Dr. Boros Julianna
Dr. Molnár Edina
Dr. Réthy Lajos Attila
Dr. Kormosné Bugyi Zsuzsanna
Dr. Vékony Blanka
This dissertation explores how SES, household food insecurity, maternal nutrition knowledge, child feeding practices, child eating behaviour, household environment, wealth, and child factors could be related to child malnutrition in urban areas in Hungary and Indonesia. A cross-sectional analysis, focusing on 36 to 59 months, was conducted. SEM PLS was employed in separate analyses for each country to predict direct and indirect pathways linking SES to malnutrition and to investigate the mediating role of other predictors. First, our results highlighted that SES is a key predictor of child nutrition. Families with higher incomes, more educated, and stable employment will be in a better financial situation overall and able to meet basic needs such as food, health care, and expenses for their children. Second, limited access to health coverage in Indonesia reveals socioeconomic disparities, policy, and health system inequalities between Hungary and Indonesia. Third, limited financial resources and lower formal parental education have a strong direct effect on maternal nutritional knowledge. Fourth, child feeding practices do not have a statistically significant direct or indirect effect on malnutrition. Nonetheless, feeding practices in Hungary are strongly influenced by maternal nutritional knowledge, suggesting it shapes what and how children are fed. In Indonesia, child feeding practices are more clearly shaped by the household environment (income and educational attainment). Fifth, the child factor (low birth weight) was a key predictor of malnutrition, suggesting that health interventions do not protect children at the early stage of life. Sixth, Path analysis reveals the dominance of structural factors (SES, food insecurity, wealth status, household environment) in both countries. Likewise, a child's biological factors were found to directly affect malnutrition. Seventh, the Indonesian Path Model was more predictive of malnutrition than the Hungarian. The implication of this study is that each of these major causal factors is potentially modifiable, and there are considerable factors overall that changes in national-level variables lead to improvements in child health. Moreover, the best interventions and programmes will be implemented in different subnations according to current conditions, not only SES but also other factors, which are significantly suggested for change in child nutrition and health status (217). Specific research is required to help governments prioritise the most effective factors for change.
