|Bayesian count regression analysis for determinants of antenatal care service visits among pregnant women in Amhara regional state, Ethiopia|
||Mekuanint Simeneh Workie, and Ayenew Molla Lakew
||Journal of Big Data, 5:7; DOI: https://doi.org/10.1186/s40537-018-0117-8
Health care utilization
Complications of pregnancy and childbirth are a leading cause of maternal morbidities and mortalities in developing countries. World Health Organization (WHO) estimates that over 500,000 women and girls die each year from the complications. Despite proven interventions that could prevent death or disability during pregnancy and childbirth, maternal mortality remains a major burden in many developing countries, including Ethiopia. This study aimed to assess the status of antenatal care utilization and modeling Bayesian Count Regression model for the determinants of utilization of antenatal care services visits among pregnant women in Amhara regional state.
It was a community based analytical cross-sectional study, conducted in Amhara region among women in the reproductive age group (age 15–49). The analysis was based on data from women who had at least one birth during the 5 years preceding the survey. The source of data was the 2014 Ethiopia Demographic and Health Survey which was accessed from Central Statistical Agency. Bayesian analytic approach was applied to model the mixture data structure inherent in zero-inflated count data by using the zero-inflated Poisson model.
About 37% (95% CI 0.32, 0.42) of the pregnant mothers were not received antenatal care services during their pregnancy and about 23% of them were visited at least four times. From Bayesian zero inflated Poisson regression it was found that rural pregnant women (OR = 1.13; HPD CI 1.12, 1.44), women who can read and write (OR = 0.54; HPD CI 0.40, 0.72), middle Wealth index (OR = 0.60; HPD CI 0.46, 0.78) and media exposures (OR = 0.72; HPD: 0.56, 0.92) were statistically associated with no ANC visits.
About three-fourth pregnant mothers were not receive adequate number of visits recommended by the World Health Organization. Mother’s education, media exposure, residence and wealth index were significant predictors of ANC service utilization. This research suggests that to reduce the inadequate number of ANC visits in Amhara region, attention should be given to women with low educational status and rural women.
Bayesian approach Classical approach ANC Amhara region MCMC Posterior distribution Prior density