Prediction Model of Low Birth Weight Based on the Factors that Influence at West Bandung Regional Hospital
DOI:
https://doi.org/10.35316/oksitosin.v12i2.6544Keywords:
Predictive model, birth weight, maternal weight, maternal age, parity, pregnancy spacing, MUACAbstract
Low Birth Weight (LBW) is a major contributor to neonatal mortality and developmental disorders in Indonesia. In West Bandung Regency, the prevalence of LBW remains high and plays a significant role in the overall infant mortality rate in West Java Province. Despite this, no locally adapted predictive model has been developed to assess LBW risk based on maternal characteristics. This study aimed to construct a predictive model for LBW using maternal factors among mothers delivering at three district public hospitals: RSUD Cililin, RSUD Lembang, and RSUD Cikalong Wetan. This quantitative study employed a retrospective approach involving 265 respondents selected through purposive sampling. Data were collected from medical records and brief interviews and analyzed using multiple linear regression. The research was conducted between January and March 2024. The results showed that among six independent variables tested, three had a statistically significant effect on infant birth weight: maternal age (p = 0.047), maternal weight gain during pregnancy (p = 0.004), and parity (p < 0.001). The predictive model generated was: Y = 2570.162 + 3.739X₁ – 11.501X₂ – 94.726X₃, with an R² value of 0.464, indicating that 46.4% of the variation in birth weight can be explained by the model. The model suggests that maternal age positively influences birth weight, whereas excessive maternal weight gain and higher parity show a negative relationship. This model can be used by healthcare providers as an early screening tool to detect LBW risk and to support targeted nutrition education and antenatal interventions at health service facilities.
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