Maternal and Child Health Journal

, Volume 18, Issue 9, pp 2148–2157 | Cite as

Exclusive Breastfeeding Practice in Nigeria: A Bayesian Stepwise Regression Analysis

  • Ezra Gayawan
  • Samson B. Adebayo
  • Stanley Chitekwe
Article

Abstract

Despite the importance of breast milk, the prevalence of exclusive breastfeeding (EBF) in Nigeria is far lower than what has been recommended for developing countries. Worse still, the practise has been on downward trend in the country recently. This study was aimed at investigating the determinants and geographical variations of EBF in Nigeria. Any intervention programme would require a good knowledge of factors that enhance the practise. A pooled data set from Nigeria Demographic and Health Survey conducted in 1999, 2003, and 2008 were analyzed using a Bayesian stepwise approach that involves simultaneous selection of variables and smoothing parameters. Further, the approach allows for geographical variations at a highly disaggregated level of states to be investigated. Within a Bayesian context, appropriate priors are assigned on all the parameters and functions. Findings reveal that education of women and their partners, place of delivery, mother’s age at birth, and current age of child are associated with increasing prevalence of EBF. However, visits for antenatal care during pregnancy are not associated with EBF in Nigeria. Further, results reveal considerable geographical variations in the practise of EBF. The likelihood of exclusively breastfeeding children are significantly higher in Kwara, Kogi, Osun, and Oyo states but lower in Jigawa, Katsina, and Yobe. Intensive interventions that can lead to improved practise are required in all states in Nigeria. The importance of breastfeeding needs to be emphasized to women during antenatal visits as this can encourage and enhance the practise after delivery.

Keywords

Nigeria Exclusive breastfeeding Spatial analysis Child nutrition Stepwise regression 

Notes

Acknowledgments

The first author appreciates support from the National Council for Scientific and Technological Development (CNPq) and The Third World Academy of Science (TWAS) towards a post doctoral fellowship during which this study was carried out. We acknowledge Macro ORS/ICF International and the Nigeria National Population Commission for granting us access to the data analysed.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Ezra Gayawan
    • 1
    • 4
  • Samson B. Adebayo
    • 2
  • Stanley Chitekwe
    • 3
  1. 1.Department of Mathematical SciencesRedeemer’s UniversityRedemption CityNigeria
  2. 2.Planning, Research and Statistics DirectorateNational Agency for Food and Drug Administration and ControlAbujaNigeria
  3. 3.UNICEFAbujaNigeria
  4. 4.Centro de Desenvolviment e Planejamento Regional (CEDEPLAR)Universidade Federal de Minas GeraisBelo HorizonteBrazil

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