Predictors of fertility-limiting preferences among currently married women in Bangladesh: an interpretable machine learning analysis of the 2022 Demographic and Health Survey
Using interpretable machine learning on 2022 Bangladesh Demographic and Health Survey data, this study demonstrates that XGBoost can accurately predict fertility-limiting preferences among married women, identifying age, number of living children, and contraceptive intention as key predictors while revealing that digital inclusion and mental health have minimal influence.