An urban study of crime and health using an exploratory spatial data analysis approach

Abstract

Research into the impacts of crime on health is relevant to adopting effective social policy and encouraging partnerships between local health and crime prevention agencies. Although it is not difficult to support the notion of crime as a threat to public health, the difficulty lies in quantifying the impact. Confounding effects of other influential variables (i.e. income, employment, housing) further complicate any analysis into the causal relationships between crime and health. An exploratory spatial data analysis approach was adopted in this study to examine the spatial relationships between crime, health, and quality of life indicators in Super Output Areas (SOAs) in Sheffield (UK). Quantitative methods of spatial data exploration and visualisation, and spatial autocorrelation analysis were used, based on aggregated secondary data drawn from census and crime databases. Statistical models of crime and health were specified, while taking into account the presence of spatial effects by applying spatial regression techniques. © 2009 Springer Berlin Heidelberg.