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Article

Bayesian Spatial Modeling of Anemia among Children under 5 Years in Guinea

by
Thierno Souleymane Barry
1,*,
Oscar Ngesa
2,
Nelson Owuor Onyango
3 and
Henry Mwambi
4
1
Mathematics (Statistics Option) Program, Pan African University Institute for Basic Sciences, Technology and Innovation (PAUISTI), Nairobi 62000-00200, Kenya
2
Department of Mathematics and Physical Sciences, Taita Taveta University, Voi 635-80300, Kenya
3
School of Mathematics, College of Biology and Physical Sciences, University of Nairobi, Nairobi 30197, Kenya
4
School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Durban 4041, South Africa
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2021, 18(12), 6447; https://doi.org/10.3390/ijerph18126447
Submission received: 17 March 2021 / Revised: 18 April 2021 / Accepted: 19 April 2021 / Published: 15 June 2021

Abstract

Anemia is a major public health problem in Africa, affecting an increasing number of children under five years. Guinea is one of the most affected countries. In 2018, the prevalence rate in Guinea was 75% for children under five years. This study sought to identify the factors associated with anemia and to map spatial variation of anemia across the eight (8) regions in Guinea for children under five years, which can provide guidance for control programs for the reduction of the disease. Data from the Guinea Multiple Indicator Cluster Survey (MICS5) 2016 was used for this study. A total of 2609 children under five years who had full covariate information were used in the analysis. Spatial binomial logistic regression methodology was undertaken via Bayesian estimation based on Markov chain Monte Carlo (MCMC) using WinBUGS software version 1.4. The findings in this study revealed that 77% of children under five years in Guinea had anemia, and the prevalences in the regions ranged from 70.32% (Conakry) to 83.60% (NZerekore) across the country. After adjusting for non-spatial and spatial random effects in the model, older children (48–59 months) (OR: 0.47, CI [0.29 0.70]) were less likely to be anemic compared to those who are younger (0–11 months). Children whose mothers had completed secondary school or above had a 33% reduced risk of anemia (OR: 0.67, CI [0.49 0.90]), and children from household heads from the Kissi ethnic group are less likely to have anemia than their counterparts whose leaders are from Soussou (OR: 0.48, CI [0.23 0.92]).
Keywords: anemia; children under five; bayesian; spatial anemia; children under five; bayesian; spatial

Share and Cite

MDPI and ACS Style

Barry, T.S.; Ngesa, O.; Onyango, N.O.; Mwambi, H. Bayesian Spatial Modeling of Anemia among Children under 5 Years in Guinea. Int. J. Environ. Res. Public Health 2021, 18, 6447. https://doi.org/10.3390/ijerph18126447

AMA Style

Barry TS, Ngesa O, Onyango NO, Mwambi H. Bayesian Spatial Modeling of Anemia among Children under 5 Years in Guinea. International Journal of Environmental Research and Public Health. 2021; 18(12):6447. https://doi.org/10.3390/ijerph18126447

Chicago/Turabian Style

Barry, Thierno Souleymane, Oscar Ngesa, Nelson Owuor Onyango, and Henry Mwambi. 2021. "Bayesian Spatial Modeling of Anemia among Children under 5 Years in Guinea" International Journal of Environmental Research and Public Health 18, no. 12: 6447. https://doi.org/10.3390/ijerph18126447

APA Style

Barry, T. S., Ngesa, O., Onyango, N. O., & Mwambi, H. (2021). Bayesian Spatial Modeling of Anemia among Children under 5 Years in Guinea. International Journal of Environmental Research and Public Health, 18(12), 6447. https://doi.org/10.3390/ijerph18126447

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