Mapping gender variation in the spatial pattern of alcohol-related mortality: a Bayesian analysis using data from South Yorkshire, United Kingdom.
Gender variation in the spatial pattern of alcohol-related deaths in South Yorkshire, UK for the period 1999 and 2003 was explored using two Bayesian modelling approaches. Firstly, separate models were fitted to male and female deaths, each with a fixed effect deprivation covariate and a random effect with unstructured and spatially structured terms. In a modification to the initial models, covariates were assumed estimated with error rather than known with certainty. In the second modelling approach male and female deaths were modelled jointly with a shared component for random effects. A range of different unstructured and spatially structured specifications for the shared and gender-specific random effects were fitted. In the best fitting shared component model a spatially structured prior was assumed for the shared component, while gender-specific components were assumed unstructured. Deprivation coefficients and random effect standard deviations were very similar between the gender-specific and shared component models. In each case the effect of deprivation was observed to be greater in males than in females, and slightly larger in the measurement error models than in the fixed covariate models. Greater variation was observed in the spatially smoothed estimates of risk for males versus females in both gender-specific and shared component models. The shared component explained a greater proportion of the male risk than it did the female risk. The analysis approach reveals the residual (unexplained by deprivation) gender-specific and shared risk surfaces, information which may be useful for guiding public health action.
Public Health GIS Unit, School of Health and Related Research (ScHARR), University of Sheffield, Regent Court, 30 Regent Street, Sheffield S1 4DA, UK. m.strong@sheffield.ac.uk
Mark
M
Strong
Tim
T
Pearson
Ying C
YC
MacNab
Ravi
R
Maheswaran
D000437:Alcoholism / Q000401:mortality*; D001499:Bayes Theorem; D005260:Female; D062305:Geographic Mapping; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D011203:Poverty / Q000706:statistics & numerical data*; D012306:Risk; D017678:Sex Distribution; D006113:United Kingdom / Q000453:epidemiology