Inequities in the Uptake of Reproductive and Maternal Health Services in the Biggest Regional State of Ethiopia: Too Far from “Leaving No One Behind”

Background Despite improvement in the coverage of most maternal, newborn, and child health services, inequality in the uptake of services still remains the challenge of health systems in most developing countries. This study was conducted to examine the degree of inequities and potential predictors of inequity in reproductive and maternal health services utilization in the Oromia region, Ethiopia. Methods The 2016 Ethiopian demographic and health survey data set was used. Utilization rate of four maternal health service categories (family planning, antenatal care, facility based delivery and postnatal care) was considered in the analysis. Equity in each of these indicators was assessed by residence (urban/rural), wealth index, and educational status. Inequality in service utilization was estimated using rate ratios, concentration curve, and concentration indices. Results Overall data of 5701 women were used in this analysis. The concentration index to all of the maternal health service utilization indicators showed significance. The concentration index of family planning, antenatal care, facility based delivery, and postnatal care was 0.136 (95% CI=0.099-0.173), 0.106 (95% CI=0.035-0.177), 0.348 (95% CI=0.279-0.418), and 0.348 (95% CI=0.279-0.418), respectively. Maternal age and all of the three socio-demographic factors (residence, education, and wealth) showed inequitable distribution of maternal health service utilization in the Oromia region. The majority of women who were in the favored groups utilized the key reproductive and maternal health services. Conclusion The utilization of maternal health services in the study area is grossly skewed to those who are well off, educated, and live in urban areas. Any action intended to improve utilization of maternal and child health services should aim to reduce the unnecessary and avoidable disparity demonstrated in our analysis. This of course demands multisectoral intervention to impact on the determinants.