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Kandala, Ngianga-Bakwin; Mandungu, Tumwaka P; Mbela, Kisumbula; Nzita, Kikhela PD; Kalambayi, Banza B; Kayembe, Kalambayi P; Emina, Jacques B O (2014)
Publisher: BioMed Central
Journal: BMC Public Health
Languages: English
Types: Article
Subjects: Research Article, DRC, HB, Geographic patterns, Millennium development goals, U5M, Public Health, Environmental and Occupational Health, Conflict
Background\ud The child mortality rate is a good indicator of development. High levels of infectious diseases and high child mortality make the Democratic Republic of Congo (DRC) one of the most challenging environments for health development in Sub-Saharan Africa (SSA). Recent conflicts in the eastern part of the country and bad governance have compounded the problem. This study aimed to examine province-level geographic variation in under-five mortality (U5M), accounting for individual- and household-level risk factors including environmental factors such as conflict.\ud \ud Methods\ud Our analysis used the nationally representative cross-sectional household sample of 8,992 children under five in the 2007 DRC Demographic and Health Survey. In the survey year, 1,005 deaths among this group were observed. Information on U5M was aggregated to the 11 provinces, and a Bayesian geo-additive discrete-time survival mixed model was used to map the geographic distribution of under-five mortality rates (U5MRs) at the province level, accounting for observable and unobservable risk factors.\ud \ud Results\ud The overall U5MR was 159 per 1,000 live births. Significant associations with risk of U5M were found for < 24 month birth interval [posterior odds ratio and 95% credible region: 1.14 (1.04, 1.26)], home birth [1.13 (1.01, 1.27)] and living with a single mother [1.16 (1.03, 1.33)]. Striking variation was also noted in the risk of U5M by province of residence, with the highest risk in Kasaï-Oriental, a non-conflict area of the DRC, and the lowest in the conflict area of North Kivu.\ud \ud Conclusion\ud This study reveals clear geographic patterns in rates of U5M in the DRC and shows the potential role of individual child, household and environmental factors, which are unexplained by the ongoing conflict. The displacement of mothers to safer areas may explain the lower U5MR observed at the epicentre of the conflict in North Kivu, compared with rates in conflict-free areas. Overall, the U5M maps point to a lack of progress towards the Millennium Development Goal of reducing U5M by half by 2015.
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