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Spatial Distribution of Malnutrition among Children Under Five in Nigeria: A Bayesian Quantile Regression Approach

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Abstract

Issues of malnutrition among young children in developing countries are gaining more attention of policy-makers because of the adverse effects on the well-being of people and economic of these nations. Anthropometric variables used for determining malnutrition are measured through z-scores where those whose measures fall into the extreme ends of the scores are considered malnourished. Conditional mean regression has been adopted to examine the determinants but often times, covariates would have effect on the mean, but have no substantial influence on more extreme quantiles. We adopt Bayesian quantile regression approach to measure the spatial distributions of childhood undernutrition at state and local government levels in Nigeria. Markov random fields and Bayesian P-splines were used as priors for the spatial and nonlinear components respectively and estimation was through MCMC technique. Results show the existence of north-south divide in undernutrition in Nigeria and that observed socioeconomic variables could have little influence on the distribution of undernutrition across space in the country.

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Notes

  1. Water sources classified as protected are: piped into dwelling/yard, public tap/standpipe, tube well/borehole, protected well, protected spring, rainwater, and bottled water while those classified as unprotected include unprotected well, unprotected spring, tanker truck/cart with drum, surface water, sachet water, and other sources.

  2. Toilet facilities considered as improved are: flush/pour into piped sewer system, flush into septic tank, flush into pit latrine, ventilated improved pit latrine, pit latrine with slab, and composite toilet. Those considered as non-improved include flush not to sewer/septic tank, pit latrine without slab/open pit, bucket toilet, hanging toilet and no facility/bush/field.

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Acknowledgements

This work was supported with a grant from UNICEF’s Nigeria Country office. We appreciate Measure DHS for granting access to the data and boundary file used for the analysis and useful comments from Elisabeth Waldmann on Bayesian quantile regression.

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Authors and Affiliations

  1. Department of Statistics, Federal University of Technology, Akure, Nigeria

    Ezra Gayawan & Abayomi A. Akomolafe

  2. Planning, Research and Statistics Directorate, National Agency for Food and Drug Administration and Control, Abuja, Nigeria

    Samson B. Adebayo

  3. Department of Remote Sensing and GIS, Federal University of Technology, Akure, Nigeria

    Akinola A. Komolafe

Authors
  1. Ezra Gayawan
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  2. Samson B. Adebayo
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  3. Akinola A. Komolafe
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  4. Abayomi A. Akomolafe
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Correspondence to Ezra Gayawan.

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Gayawan, E., Adebayo, S.B., Komolafe, A.A. et al. Spatial Distribution of Malnutrition among Children Under Five in Nigeria: A Bayesian Quantile Regression Approach. Appl. Spatial Analysis 12, 229–254 (2019). https://doi.org/10.1007/s12061-017-9240-8

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