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    Rights statement: This is the author’s version of a work that was accepted for publication in Spatial and Spatio-temporal Epidemiology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Spatial and Spatio-temporal Epidemiology, 21, 2017 DOI: 10.1016/j.sste.2017.02.003

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Modelling and Forecasting Spatio-temporal Variations in the Risk of Chronic Malnutrition Among Under-Five Children in Ghana

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<mark>Journal publication date</mark>06/2017
<mark>Journal</mark>Spatial and Spatio-temporal Epidemiology
Volume21
Number of pages10
Pages (from-to)37-46
Publication StatusPublished
Early online date2/03/17
<mark>Original language</mark>English

Abstract

Background: Spatio-temporal variation in under-five-year-old children malnutrition remains unstudied in most developing countries like Ghana. This study explores and forecasts the spatio-temporal patterns in childhood chronic malnutrition among these children. We also investigate the effect of maternal education on childhood malnutrition.
Methods: We analysed data on 10,036 children residing in 1,516 geographic locations. A spatio-temporal model was fitted to the data and was used to produce predictive maps of spatio-temporal variation in the probability of stunting.
Results: The study found substantial spatio-temporal variation in the prevalence of stunting. Also, higher levels of mother's education were associated with decreased risk of being stunted.
Conclusion: Our spatio-temporal model captured variations in childhood stunting over place and time. Our method facilitates and enriches modelling and forecasting of future stunting prevalence to identify areas at high risk. Improving maternal education could be given greater consideration within an overall strategy for addressing childhood malnutrition.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Spatial and Spatio-temporal Epidemiology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Spatial and Spatio-temporal Epidemiology, 21, 2017 DOI: 10.1016/j.sste.2017.02.003