Child mortality inequalities across Rwanda districts: a geoadditive continuous-time survival analysis

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François Niragire *
Thomas N.O. Achia
Alexandre Lyambabaje
Joseph Ntaganira
(*) Corresponding Author:
François Niragire | fniragire@ur.ac.rw

Abstract

Child survival programmes are efficient when they target the most significant and area-specific factors. This study aimed to assess the key determinants and spatial variation of child mortality at the district level in Rwanda. Data from the 2010 Rwanda Demographic and Health Survey were analysed for 8817 live births that occurred during five years preceding the survey. Out of the children born, 433 had died before survey interviews were carried out. A full Bayesian geo-additive continuous-time hazard model enabled us to maximise data utilisation and hence improve the accuracy of our estimates. The results showed substantial district- level spatial variation in childhood mortality in Rwanda. District-specific spatial characteristics were particularly associated with higher death hazards in two districts: Musanze and Nyabihu. The model estimates showed that there were lower death rates among children from households of medium and high economic status compared to those from low-economic status households. Factors, such as four antenatal care visits, delivery at a health facility, prolonged breastfeeding and mothers younger than 31 years were associated with lower child death rates. Long preceding birth intervals were also associated with fewer hazards. For these reasons, programmes aimed at reducing child mortality gaps between districts in Rwanda should target maternal factors and take into consideration district-specific spatial characteristics. Further, child survival gains require strengthening or scaling-up of existing programmes pertaining to access to, and utilisation of maternal and child health care services as well as reduction of the household gap in the economic status.

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Author Biography

François Niragire, Department of Applied Statistics, College of Business and Economics, University of Rwanda, Kigali

Niragire François is Lecturer of Applied Statistics, Department of Applied Statistics of the University of Rwanda. He has recently published in Plos One, Global Health Action, and Rwanda Journal.