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

Int J Environ Res Public Health. 2021 Jun 15;18(12):6447. doi: 10.3390/ijerph18126447.

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; bayesian; children under five; spatial.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Africa
  • Anemia* / epidemiology
  • Bayes Theorem
  • Child
  • Child, Preschool
  • Female
  • Guinea / epidemiology
  • Humans
  • Infant
  • Prevalence
  • Risk Factors