Household and community variations and nested risk factors for diarrhoea prevalence in southern Malawi: a binary logistic multi-level analysis.
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 (sigma(2)(u) = 4.476; 95% CI: 2.081, 6.871). A joint Wald test of significance shows that an individual's age [chi(2)(4) = 55.921, p = 0.000] and school [chi(2)(2) = 18.203, p = 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 [beta = 0.606, p = 0.000]. Household factors that influence diarrhoea include employment status of head of household [beta = -0.619, p < 0.021], maternal age [beta = -0.013, p < 0.003], and size of household [beta = -0.669, p = 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.
Masangwi
Salule Joseph
SJ
Department of Civil Engineering, University of Strathclyde, Glasgow, UK. salule.masangwi@strath.ac.uk
Ferguson
N S
NS
Grimason
A M
AM
Morse
T D
TD
Zawdie
G
G
Kazembe
L N
LN
D000293:Adolescent; D000328:Adult; D001499:Bayes Theorem; D002648:Child; D002675:Child, Preschool; D003967:Diarrhea / Q000453:epidemiology*; D005191:Family Characteristics; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D016015:Logistic Models; D008295:Malawi / Q000453:epidemiology; D008875:Middle Aged; D012044:Regression Analysis; D012111:Residence Characteristics / Q000706:statistics & numerical data*; D012307:Risk Factors; D055815:Young Adult