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Background: Health information systems provide a comprehensive platform to capture multidimensional determinants of stunting. This study aimed to identify and analyze key predictors of stunting among toddlers using data from the National Population and Family Planning Board (BKKBN). Materials and Methods: This study employed an analytic cross-sectional design and secondary data derived from the nationwide Family Data Collection conducted by BKKBN, which is implemented every five years as a national household survey. The dataset was officially released in 2022. The dataset included 9,401 mothers with toddlers. Bivariate analysis using the Chi-square test and multivariable logistic regression were performed to identify independent predictors of stunting. Results: Several factors were significantly associated with stunting. The strongest predictors included absence of fixed household income (adjusted odds ratio [AOR] = 7.14), low dietary pattern (AOR = 6.25), lack of access to safe drinking water (AOR = 5.56), absence of toilet facilities (AOR = 5.54), and uninhabitable housing conditions (AOR = 5.12). Maternal reproductive factors also showed strong associations, particularly late pregnancy (>35 years; AOR = 8.91) and teenage/early pregnancy (<20 years; AOR = 7.27), followed by short birth interval (<2 years; AOR = 3.28) and multiparity (>2 children; AOR = 2.97). Conclusions: A combination of economic instability, poor housing and sanitation, inadequate dietary pattern, and high-risk maternal reproductive factors emerged as the most influential predictors of stunting, underscoring the need for integrated, multi-sectoral interventions.
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Putri et al. (2026) studied this question.
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