Determinants of stunting in children under five years old in South Sulawesi and West Sulawesi Province: 2013 and 2018 Indonesian Basic Health Survey

**Background** Stunting affects approximately 151 million children (22.2%) globally, with more than half in Asia. Indonesia has a stunting prevalence of 30–39% and has underperformed in reducing stunting compared with regional peers. South Sulawesi had a 2018 prevalence of 35.74% (fourth highest nationally) and West Sulawesi 41.59% (second highest). The study examined household, maternal, and child-level determinants of stunting in these two provinces using two waves of the Indonesian Basic Health Survey (Riskesdas).

**Methods** This was a cross-sectional secondary data analysis of the 2013 and 2018 Riskesdas. Samples included 3,641 (2013) and 4,423 (2018) children under five in South Sulawesi, and 804 (2013) and 1,059 (2018) children in West Sulawesi. Mean child age was 31.1 months (South Sulawesi 2013), 30.8 months (West Sulawesi 2013), 29.6 months (South Sulawesi 2018), and 29.1 months (West Sulawesi 2018). Stunting was defined per WHO height-for-age z-score (< −2.0 SD). Fifteen predictors across household, maternal, and child domains were examined. Because prevalence exceeded 10%, prevalence ratios (PRs) from Poisson regression were used instead of odds ratios. Variables with p ≤ 0.2 in bivariate analysis entered multivariable models; p < 0.05 defined statistical significance. Sampling weights were applied.

**Key Results**

*South Sulawesi, 2013:* Significant determinants included two children under five in household (APR 1.24; 95% CI 1.1–1.3; p = 0.006), maternal BMI (APR 1.1; 95% CI 1.03–1.1; p < 0.001), maternal weight (APR 0.9; 95% CI 0.94–0.97; p < 0.001), child age 12–23 months (APR 2.2; 95% CI 1.7–2.7; p < 0.001), child age 24–59 months (APR 2.2; 95% CI 1.8–2.7; p < 0.001), and birthweight < 2500 g (APR 1.9; 95% CI 1.5–2.5; p < 0.001).

*South Sulawesi, 2018:* Maternal weight (APR 0.9; 95% CI 0.98–0.99; p = 0.005), primary/no maternal education (APR 1.5; 95% CI 1.3–1.9; p < 0.001), middle school education (APR 1.3; 95% CI 1.1–1.6; p = 0.014), maternal height ≤150 cm (APR 2.2; 95% CI 1.5–3.1; p < 0.001), maternal height 151–160 cm (APR 1.5; 95% CI 1.03–2.2; p = 0.032), child age 12–23 months (APR 2.2; 95% CI 1.7–2.8; p < 0.001), child age 24–59 months (APR 2.5; 95% CI 2.0–3.2; p < 0.001), and birthweight < 2500 g (APR 1.5; 95% CI 1.2–1.9; p < 0.001).

*West Sulawesi, 2013:* Children in poorest quantile 2 households (APR 1.9; 95% CI 1.1–3.3; p = 0.021), three or more children under five in household (APR 1.8; 95% CI 1.2–2.7; p = 0.002), child age 12–23 months (APR 1.8; 95% CI 1.2–2.6; p = 0.006), and child age 24–59 months (APR 1.9; 95% CI 1.3–2.7; p = 0.001).

*West Sulawesi, 2018:* Maternal BMI (APR 1.02; 95% CI 1.01–1.03; p = 0.004), maternal weight (APR 0.9; 95% CI 0.95–0.98; p < 0.001), primary/no maternal education (APR 1.9; 95% CI 1.3–2.7; p = 0.001), middle school (APR 1.9; 95% CI 1.3–2.7; p = 0.001), high school (APR 1.8; 95% CI 1.2–2.6; p = 0.004), child age 12–23 months (APR 2.1; 95% CI 1.4–3.0; p < 0.001), child age 24–59 months (APR 2.6; 95% CI 1.9–3.6; p < 0.001), male sex (APR 1.2; 95% CI 1.01–1.4; p = 0.035), and acute respiratory infection (ARI) (APR 1.6; 95% CI 1.04–2.5; p = 0.030).

A household wealth index could not be constructed for the 2018 survey because household facility and asset variables were unavailable.

**Clinical Implications** Stunting in these provinces is multifactorial, driven by maternal anthropometry (height, weight, BMI), maternal education, household composition, child age, birthweight, sex, and recent ARI. Consistent with prior regional literature, short maternal stature reflects intergenerational nutritional and environmental disadvantage, and low maternal education limits caregiving knowledge. The marked increase in stunting risk after 12 months suggests a critical window linked to complementary feeding transitions and increased infection exposure. Boys showed modestly higher risk in West Sulawesi 2018, consistent with greater male vulnerability to nutritional stress. Interventions should integrate maternal nutrition (food and micronutrient supplementation), female education, poverty reduction, birthweight prevention, and ARI control. Study strengths include large sample size and use of sampling weights; limitations include absence of household wealth data in 2018 and restriction to variables available in Riskesdas.