An Application of Mixed-Effect Models to Analyze Contraceptive use in Malawian Women

In Malawi, the current approach to family planning using contraceptive methods is individualized, yet studies have shown that variability in contraceptive use still remains after accounting for it at individual and household levels. Therefore, this study assessed variability at higher levels such as enumeration areas, districts, and regions. Biasness of the estimates was addressed by the use of the Bayesian approach. The study used the 2015–16 Malawi Demographic Health Survey women data. After ascertaining the significance of the association of all explanatory variables with contraceptive use, the top-down (backward) stepwise model selection method was followed in the Bayesian framework using Markov Chain Monte Carlo and defuse priors. Models were compared on the basis of Deviance Information Criteria and the significance of parameter estimates was checked via credible intervals while that of cross-cluster variances was checked by examining their diagnostic plots. All the selected socio-demographic factors were strongly associated with contraceptive use (p-value< 0.001). These factors include; region, place of residence, age, parity, education, occupation, marital status, and religion. It was also found that about 15 and 2.3% of the variation in contraceptive use was attributed to enumeration area and district clustering, respectively. The single-level model underestimated the parameter estimates by at least 4% for both models. And parity-enumeration area, age-enumeration area, and age-district random effects were significant in their respective models. It was also noted that most young women aged between 15 and 24 years were not using any contraceptive methods. The study indicated that there exist significant enumeration area and district heterogeneity on contraceptive use in Malawian women and random-effect models are the most appropriate models other than single-level models. Thus family planning programs focusing on contraceptive use should switch to an inclusive approach and statistical analyses should consider including enumeration area and district heterogeneity while controlling for the above significant factors. Stakeholders may also consider encouraging young women to use contraceptive methods if Malawi is to minimize problems due to overpopulation.