Household and community variations and nested risk factors for diarrhoea prevalence in Southern Malawi: a binary logistic multilevel analysis

S.J. Masangwi, N.S. Ferguson, A.M. Grimason, T.D. Morse, G. Zawdie, L.N. Kazembe

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6 Citations (Scopus)

Abstract

This paper examines household and community-level influences on diarrhoeal prevalence in southern Malawi. A Bayesian multi-level modelling technique is used in the estimation of hierarchically built data from a survey of individuals nested within households nested within communities. Households have strong unobserved influence on diarrhoeal illness (s2u ¼ 4.476; 95%CI: 2.081, 6.871). A joint Wald test of significance shows that an individual's age [w24 ¼ 55:921; p ¼ 0:000] and school [w22 ¼ 18:203; p ¼ 0:000] have strong influence on an individual's diarrhoeal prevalence. An individual's history of malarial-like illness also has a strong positive relationship with diarrhoeal prevalence [b ¼ 0.606, p ¼ 0.000]. Household factors that influence diarrhoea include employment status of head of household [b ¼ 70.619, p 5 0.021], maternal age [b ¼ 70.013, p 5 0.003], and size of household [b ¼ 70.669, p ¼ 0.000]. The positive relationship between diarrhoea and malaria-like episodes highlights common risk factors hence the need for common approaches to combat the diseases. Significant household effects underline the importance of household considerations in policy issues.
LanguageEnglish
Pages141-158
Number of pages18
JournalInternational Journal of Environmental Health Research
Volume20
Issue number2
DOIs
Publication statusPublished - 2010

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Multilevel Analysis
Malawi
Logistics
Diarrhea
History
Maternal Age
Malaria
Joints

Keywords

  • Bayesian estimation
  • diarrhoeal prevalence
  • multi-level analysis
  • Malawi

Cite this

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title = "Household and community variations and nested risk factors for diarrhoea prevalence in Southern Malawi: a binary logistic multilevel analysis",
abstract = "This paper examines household and community-level influences on diarrhoeal prevalence in southern Malawi. A Bayesian multi-level modelling technique is used in the estimation of hierarchically built data from a survey of individuals nested within households nested within communities. Households have strong unobserved influence on diarrhoeal illness (s2u ¼ 4.476; 95{\%}CI: 2.081, 6.871). A joint Wald test of significance shows that an individual's age [w24 ¼ 55:921; p ¼ 0:000] and school [w22 ¼ 18:203; p ¼ 0:000] have strong influence on an individual's diarrhoeal prevalence. An individual's history of malarial-like illness also has a strong positive relationship with diarrhoeal prevalence [b ¼ 0.606, p ¼ 0.000]. Household factors that influence diarrhoea include employment status of head of household [b ¼ 70.619, p 5 0.021], maternal age [b ¼ 70.013, p 5 0.003], and size of household [b ¼ 70.669, p ¼ 0.000]. The positive relationship between diarrhoea and malaria-like episodes highlights common risk factors hence the need for common approaches to combat the diseases. Significant household effects underline the importance of household considerations in policy issues.",
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AU - Grimason, A.M.

AU - Morse, T.D.

AU - Zawdie, G.

AU - Kazembe, L.N.

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