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Open Access Research article

Risk factors and a predictive model for under-five mortality in Nigeria: evidence from Nigeria demographic and health survey

Gbenga A Kayode12*, Victor T Adekanmbi12 and Olalekan A Uthman12

Author Affiliations

1 Department of Public Health & Biostatistics, University of Birmingham, Birmingham, UK

2 Centre for Evidence-Based Global Health, Ilorin, Kwara State, Nigeria

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BMC Pregnancy and Childbirth 2012, 12:10  doi:10.1186/1471-2393-12-10

Published: 29 February 2012



Under-5 mortality is a major public health challenge in developing countries. It is essential to identify determinants of under-five mortality (U5M) childhood mortality because these will assist in formulating appropriate health programmes and policies in order to meet the United Nations MDG goal. The objective of this study was to develop a predictive model and identify maternal, child, family and other risk factors associated U5M in Nigeria.


Population-based cross-sectional study which explored 2008 demographic and health survey of Nigeria (NDHS) with multivariable logistic regression. Likelihood Ratio Test, Hosmer-Lemeshow Goodness-of-Fit and Variance Inflation Factor were used to check the fit of the model and the predictive power of the model was assessed with Receiver Operating Curve (ROC curve).


This study yielded an excellent predictive model which revealed that the likelihood of U5M among the children of mothers that had their first marriage at age 20-24 years and ≥ 25 years declined by 20% and 30% respectively compared to children of those that married before the age of 15 years. Also, the following factors reduced odds of U5M: health seeking behaviour, breastfeeding children for > 18 months, use of contraception, small family size, having one wife, low birth order, normal birth weight, child spacing, living in urban areas, and good sanitation.


This study has revealed that maternal, child, family and other factors were important risk factors of U5M in Nigeria. This study has identified important risk factors that will assist in formulating policies that will improve child survival.