Bibliometric Visualization of Adolescent Reproductive Health Research and Decision Tree Analysis for Stunting Risk Prediction in Developing Regions

Abstract

Adolescent reproductive health plays a critical role in shaping long-term nutritional outcomes and population health in developing regions. Stunting remains a persistent public health challenge, often rooted in intergenerational factors linked to adolescent health, early pregnancy, and limited access to reproductive health services. This study aims to (1) map global research trends in adolescent reproductive health using bibliometric visualization techniques and (2) develop a decision tree model to predict stunting risk based on reproductive health and socio-demographic indicators in developing regions. A bibliometric analysis was conducted using Scopus-indexed publications from 2000 to 2024, visualized through thematic evolution and keyword co-occurrence mapping. Subsequently, a decision tree classification model was constructed using simulated multi-country health survey data to identify key predictors of stunting risk. The bibliometric results reveal a growing interdisciplinary focus linking adolescent reproductive health, nutrition, and social determinants, while predictive modeling highlights early marriage, maternal anemia, and inadequate antenatal care as dominant risk factors. This hybrid approach provides a comprehensive evidence base for policy-oriented interventions targeting adolescent health as a strategic entry point for stunting prevention in low- and middle-income countries.