A Multilevel Decomposition of Time Variation in the Risks of Infant Mortality in Rural Uganda: UDHS 1995–2016

Abstract

The study assessed the contribution of maternal, child, paternal, household, proximate, and community-level factors to infant mortality risk time variation in rural Uganda between 1995 and 2016. Five rounds of Uganda Demographic and Health Survey data sets were used, and a multilevel mixed-effect logistic regression model was applied to decompose the contribution of different factors to time variation in the risks of infant mortality. All live births that were made five years before the surveys of 1995, 2001, 2006, 2011, and 2016 were considered, with infants who did not survive beyond one year treated as the outcome variable analysis, excluding those who were born less than 12 months before the survey. The fixed part of the model helped us detect the significant variables in determining infant mortality, and yet the random part of the model helped us quantify the amount of time variation in the risks of infant mortality explained by the selected variables. The child-level determinants of infant mortality were sex, birth order, and weight. Among the maternal factors, the study revealed that marital status, access to ANC, use of contraceptives, maternal education level, and preceding birth interval were consistent deterrents of infant mortality, while household size, sanitation, and wealth index remained critical. While controlling for other factors in the rural areas, time variation in the risks of infant mortality was dependent on community factors (such as region, community hygiene, and prenatal care utilization rate), proximate factors (such as access to prenatal care, contraceptives use, place of delivery, and the number of ANC visits), maternal factors (such as marital status, educational level, age, parity, preceding birth interval, desire for pregnancy, and breastfeeding), and endowment. It was observed that the changes in the risks of infant mortality over the period were explained by community (30.7%), proximate (22.7%), maternal (41.0%), and endowment (37.9%). Child-level factors explained 28.2%, and paternal-level education level explained only 30.1%. Remarkably, household-level factors captured 32.3% of the changes in infant mortality. A higher proportion of the explained variation in the risk of infant mortality across communities (PCV) was captured by child, paternal, maternal endowment, and household factors. Interventions to accelerate the reduction in infant mortality should target birth spacing to at least two years, girl child education to at least o level, joint household decision-making in having children, avoiding teenage pregnancies, postnatal care utilization, enforcing at least four ANC visits during pregnancy, improving household sanitation, and increasing access to safe water at household-levels