BINARY LOGISTIC REGRESSION ANALYSIS OF ENVIRONMENTAL AND SOCIODEMOGRAPHIC DETERMINANTS FOR CHILDHOOD STUNTING

Authors

  • Laelatul Khikmah Department of Statistics, Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang, Indonesia
  • Ayu Ashari Department of Medical Records and Health Information, Dian Nuswantoro University, Indonesia
  • Atika Nurani Ambarwati Department of Statistics, Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang, Indonesia
  • Vania Putri Priyandhini Department of Statistics, Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang, Indonesia
  • Muhammad Alif Natonegoro Department of Statistics, Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang, Indonesia

DOI:

https://doi.org/10.53806/jmscowa.v6i2.1400

Keywords:

Binary Logistic Regression; Central Java; Environmental Health; Sanitation; Stunting

Abstract

This study analyzed the influence of regional disparities, environmental factors, and sociodemographic characteristics on stunting risk among children under five in Central Java. A cross-sectional design utilized secondary data from 73,358 children, which were evaluated through binary logistic regression to identify multiple risk factors. The results revealed that children residing in urban areas exhibited 1.73 times higher odds of stunting (95% CI: 1.27–2.36, p < 0.001). Unsafe non-drinking water access emerged as the most significant predictor, increasing stunting odds by 2.30 times (95% CI:1.56–3.37, p < 0.001). Conversely, parental education, employment status, and toilet availability showed no statis
tically significant associations with the outcome in this cohort. The study concluded that structural environmental challenges in urbanized settings outweighed individual sociodemographic factors. These findings highlight the necessity for targeted urban-specific sanitation strategies and improved water quality for daily household hygiene to effectively mitigate stunting prevalence and support regional health development targets.

Downloads

Published

2025-12-30

Issue

Section

Articles