MULTILEVEL AND CLUSTERING ANALYSIS OF HEALTH OUTCOMES IN SMALL AREAS

This paper considers models of the variable incidence of health outcom es in geographical areas and of variable regression effects of socio-e conomic variables on such outcomes. It adopts a Bayesian approach to v ariation in relative risk and regression effects, and assesses differe nt prior specifications of risk (e.g. a latent class structure versus a spatially correlated structure). Implications are considered for smo othing and mapping rare health outcomes. The analysis is for electoral wards in London, with the health-deprivation link forming the focus f or regression effects. Implications for inferences about risk factors and for health-need ratings (before and after smoothing) are also cons idered.