Strategies For Improving the Nutritional Status of Children Under Five (U5) Based on Knowledge and Socioeconomic Factors

toddlers nutritional status, knowledge socio-economic Structural Equation Modeling (SEM)

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October 31, 2026

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Nutritional problems among children under five remain a public health concern, reflecting the interplay between parental knowledge, household resources, and feeding practices. This study examined the associations between maternal knowledge, socioeconomic status, and the nutritional status of children under five and identified implications for strategies to improve nutritional outcomes in Kediri City, Indonesia. The study involved 200 mothers of children under five from the Mojoroto, Kota, and Pesantren subdistricts. Data were collected through interviews, observations, surveys, and document reviews using a Participatory Rapid Appraisal (PRA) approach. Descriptive statistics and structural equation modeling (SEM) were employed to characterize the respondents and examine the relationships among variables. The results showed that 42.0% of children were underweight, 39.0% had normal nutritional status, 18.5% were overweight, and 0.5% were severely malnourished. Maternal knowledge was significantly associated with children's nutritional status, with an estimated coefficient of 0.17 and a t-value of 3.05. Socioeconomic status showed no statistically significant direct association, with an estimated coefficient of 0.02 and a t-value of 0.40. These findings suggest that maternal knowledge plays a role in children's nutritional status, although the modest magnitude of the association indicates that additional contributing factors should be considered. Strengthening nutrition education, routine growth monitoring, and guidance on affordable, nutritious foods through integrated community health posts (posyandu) may support efforts to improve children's nutritional status. However, these strategies require further evaluation, as the study examined associations rather than intervention effectiveness or causal relationships