Modeling the risk factors associated with neonatal mortality in Rwanda, 2010-2015

Abstract

Internationally, neonatal mortality rates are considered as an indicator that best reflects the economic and social development of a region or a country. Reducing newborn death was expressed in the fourth objective of the MDGs, later on in the UN SDG 3.2 goal aimed at ending preventable newborn deaths and under-five mortality, with all counties striving to reduce neonatal mortality to at least 12 deaths and U5MR to at least 25 deaths per 1,000 live births. One of the growing concern of neonatal mortality in developing countries including Rwanda, is that the proportion of neonatal deaths in under-five and infant mortality is increasing as the overall under-five mortality is declining significantly. In trying to understand of the risk factors associated with neonatal mortality in Rwanda, the study used secondary data from the fifth Rwanda Demographic and Health Survey (RDHS-V) conducted in 2014-2015. The aim was to examine socio-economic and demographic factors that are associated with current levels of neonatal mortality in Rwanda. To attain to this objective, were used in the analysis a descriptive analysis, a chi-square test and logistic regression but also survival analysis. Findings have shown that maternal age, place of residence, mother education, ANC, wealth index, CEB, birth order, sex of the birth, place of delivery, size and weight of the baby at birth, breastfeeding practice, and birth interval, have an association with the neonatal deaths(p<0.05). It was found that births from too young mothers (<18) or too old (>34), mothers in rural areas, mothers with no education, mothers who did less than 4 ANC, mothers in very poor families, mothers with high parity (CEB), first and very highest birth order, male babies, very small and very large size and weight of the baby at birth, babies that didn’t breastfeed in the first hour after birth, babies with short birth interval have the highest risk of dying during the neonatal period. From risk factors of neonatal mortality in Rwanda, a logistic regression model was constructed using the maximum likelihood but also survival analysis was used. Recommendations were drawn from the study informing where to put more efforts toward reducing neonatal mortality in Rwanda and achieving SDGs’ target such as increasing women’s education, encouraging breastfeeding practices in the first hour after birth or during infancy, antenatal care visit during pregnancy, birth spacing and limitation, but also fighting against poverty.