RESUMO
BACKGROUND: About 75.5% of women in Nepal's urban areas receive at least four ANC visits, compared to 61.7% of women in the country's rural areas. Similarly, just 34% of women in the lowest wealth quintile give birth in a medical facility compared to 90% of women in the richest group. As a result of this inequality, the poor in emerging nations suffer since those who are better off can make greater use of the healthcare than those who are less fortunate. This study aims to examine and decompose the contributions of various socioeconomic factors towards MCH service inequality in Nepal in the years 2011 and 2016. METHODS: Inequality in MCH services was estimated using concentration curves and their corresponding indices using data from Nepal Demographic Health Survey (NDHS) 2011 and 2016. We examined the inequality across three MCH service outcomes: less than 4 ANC visits, no postnatal checkups within 2 months of delivery and no SBA delivery and decomposed them across observed characteristics of the mothers aged between 15 and 49. Furthermore, Oaxaca-blinder decomposition approach was used to measure and decompose the inequality differential between two time periods. RESULTS: Inequality in MCH services was prevalent for all 3 MCH outcomes in 2011 and 2016, respectively. However, the concentration indices for <4 ANC visits, no SBA delivery, and no postnatal checkups within 2 months of birth increased from -0.2184, -0.1643, and -0.1284 to -0.1871, -0.0504, and -0.0218 correspondingly, showing the decrease in MCH services inequality over two time periods. Wealth index, women's literacy, place of living, mother's employment status, and problem of distance to reach nearest health facility were the main contributors. CONCLUSION: We find that MCH services are clearly biased towards the women with higher living standards. National policies should focus on empowering women through education and employment, along with the creation of health facilities and improved educational institutions, in order to address inequalities in living standards, women's education levels, and the problem of distance. Leveraging these factors can reduce inequality in MCH services.
