Statistical models to understand factors associated with under-five child mortality in Tanzania.

Abstract

The risk or probability of dying between birth and five years of age expressed per 1000 live births is known as Under-five mortality. The well-being of a child reflects household, community and national involvement on family health. This will have an immense future contribution towards the development of a country. Globally, a substantial progress in improving child survival since 1990 has been made. The decline globally in under-five mortality from approximately 12.7 million in 1990 to approximately 6.3 million in 2013 had been observed. Notably, all regions except Sub-Saharan Africa, Central Asia, Southern Asia and Oceania had reduced the rate by 52% or more in 2013. This study aims to identify factors that are associated with the under-five mortality in Tanzania. In order to robustly identify these factors, the study utilized different statistical models that accommodate a response which is dichotomous. Models studied include Logistic Regression (LR), Survey Logistic Regression (SLR), Generalized Linear Mixed Model (GLMM) and Generalized Additive Model (GAM). The result revealed that HIV status of the mother is associated with the under-five mortality. Furthermore, the results revealed that childbirth order number, breastfeeding and a total number of children alive affects the survival status of the child. The study shows that there is a need to intensify child health interventions to reduce the under-five mortality rate even more and to be in line with the millennium development goal 4(MDG4).