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Analysis of the spatial patterns of malnutrition among women in Nigeria with a Bayesian structured additive model

  • Rebecca A. Akeresola
  • Ezra Gayawan
Article
  • 11 Downloads

Abstract

Malnutrition among women has severe consequences on their health, households and national development. The different forms of malnutrition among adult individuals are severe thinness, underweight, overweight and obesity which are usually assessed using height and weight indices calculated as body mass index (BMI). In this study, the spatial distributions of the various forms of malnutrition measured at the upper and lower tails of the BMI were accessed among women of reproductive age in Nigeria after accounting for the influence of socio-economic factors. Bayesian quantile regression that permits for inference on conditional quantiles, yielding a complete description of the functional changes among covariates at different quantiles of the response variable was adopted. Markov random field and Bayesian P-splines were used as prior distributions for the spatial and nonlinear effects respectively, while computation was based on MCMC approach. Data were derived from the 2013 Nigeria Demographic and Health Survey. Findings indicate the existence of spatial structure in the various forms of malnutrition with neighbouring states sharing similar patterns and that the socio-economic variables exact dissimilar influence on the various forms of malnutrition. The study provides valuable insights for policy makers in the quest for halting all forms of malnutrition among Nigerian women.

Keywords

Malnutrition Spatial structure Nigeria Bayesian method Quantile regression 

Notes

Acknowledgements

This work was supported with a grant from UNICEF’s Nigeria Country office but the design, analysis and interpretation of results were carried out by the authors without any role by UNICEF. We appreciate Measure DHS for granting access to the data and useful comments from Elisabeth Waldmann on Bayesian quantile regression.

Compliance with Ethical Standards

Conflict of interest

The authors have no conflict of interest to declare.

Ethical Standard

The data used in this study was obtained from The DHS Program (https://dhsprogram.com), who was the main partner that conducted the survey, after approval was given to our request.

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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Biostatistics and Spatial Statistics Laboratory, Department of StatisticsFederal University of TechnologyAkureNigeria

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