Performances of bayesian structured additive regression and logistic models in assessing factors associated with modern contraceptive use among ever-in-union women in Nigeria.

BACKGROUND: Modern contraceptive use plays a key role in reducing unintended pregnancies, improving maternal health, and curbing rapid population growth. In Nigeria, despite growing awareness and government-led interventions, usage remains low and unevenly distributed across regions. While most studies focus on individual-level determinants, limited attention has been paid to how geographic and spatial differences influence contraceptive behavior. This study compared the performance of Bayesian structured additive regression with frequentist logistic regression in identifying factors associated with modern contraceptive use among ever-in-union women in Nigeria. METHODS: This cross-sectional study used data from the 2018 Nigeria Demographic and Health Survey (NDHS) of ever-in-union women aged 15-49 years. Bayesian structured additive regression and frequentist logistic regression models were applied. The deviance information criterion (DIC) was used for model evaluation. RESULTS: Modern contraceptive prevalence was 11.5% among 31,152 ever-in-union women. Strong north-south disparities were identified, with higher uptake in urban and southern regions. A nonlinear relationship was observed between age at first marriage and contraceptive use, with 20.9% of women marrying before age 15years. Women with more than three children alive had 48% higher odds of contraceptive use (aOR = 1.48; 95% CrI: 1.24-1.66). Working women (aOR = 1.91; 95% CrI: 1.89-2.23) and those knowledgeable about modern methods (aOR = 1.78; 95% CrI: 1.66-2.25) also had higher odds.