Fitting and validation of logistic regression models For long-acting reversible contraception and Unplanned pregnancy among adolescents and young Women in rural Kenya.

Abstract

In rural Kenya, adolescent girls and young women face significant challenges in accessing and utilizing Long-Acting Reversible Contraceptives (LARC) and continue to experience a high prevalence of unplanned pregnancies. Previous studies have primarily focused on women of all reproductive ages, with limited attention given to the unique circumstances of adolescents and young women living in rural regions. This study aimed to identify socio-demographic and predictive factors influencing LARC use and unplanned pregnancies among adolescent girls and young women in rural Kenya, utilizing logistic regression analysis. Additionally, it validated the logistic regression models employed in identifying these determinants. The study used nationally representative secondary data from the Performance Monitoring for Action (PMA) survey, which employed a multi-stage stratified cluster design. The study population included adolescent girls and young women from 10 selected counties in rural Kenya, who had used at least some form of contraceptive and had experienced at least one childbirth. The analysis employed bivariate analysis using the Chi-square test of independence to identify significant variables (p<0.15) for inclusion in the multivariate analysis. Multiple logistic regression at 95% confidence interval (p<0.05) was then fitted to determine the factors associated with LARC use and unplanned pregnancy. Our findings indicated that partner decision on the current method of contraception was the strongest predictor of LARC use (OR = 5.384, 95% CI = [3.223, 9.275]) among marital status and county of residence. Younger age (15-19 years) was a significant predictor of unplanned pregnancies (OR=3.216, 95% CI= [1.615, 6.281]). Additionally, women residing in West Pokot County were more likely to experience an unplanned pregnancy (OR=2.693, 95% CI=[1.003, 7.624]). The logistic regression models demonstrated good predictive accuracy, with an area under the ROC curve (AUC) of 0.736 for LARC use and 0.799 for unplanned pregnancies. Both models also demonstrated good overall fit as shown by the Hosmer-Lemeshow test (p-value >0.05), suggesting that the models adequately capture the relationships between the predictor variables and LARC use or unplanned pregnancy. All variables had AGVIF values close to one, signifying mild collinearity. Furthermore, cross-validation technique was employed to evaluate the models' predictive performance and generalizability, achieving acceptable average accuracy values (>0.6). These results indicate the importance of targeting educational interventions for LARC use to males. The government should also promote equitable access to family planning services, particularly LARC methods, by strengthening devolved health service delivery at the county level to increase LARC uptake in Nyamira and Kericho counties.