Gilbert, A., & Chakraborty, J. (2011). Using geographically weighted regression for environmental justice analysis: Cumulative cancer risks from air toxics in Florida. Social Science Research, 40(1), 273-286.
This paper draws on previous literature about inequality in health geography to investigate the risk of cancer risk from ambient exposure to air pollutants between different socioeconomic groups across Florida, focusing on the following 2 research questions:
- Are cumulative lifetime cancer risks from ambient exposure to multiple sources of hazardous air pollutants distributed inequitably with respect to race/ethnicity and socioeconomic status across Florida?
- How does the direction and significance of statistical relationships between cumulative lifetime cancer risk and race/ethnicity or socioeconomic status vary across the state of Florida?
Methodology:
Using modelled cumulative air cancer risk and socio-economic factors such as racial structure of communities, the authors conducted two forms of regression analysis. Ordinary Least Squares was used to acquire a global fit and Geographically Weighted Regression was used to determine whether the difference in the fit between the explanatory variables and the overall cancer risk changed differed across the state.
Results:
- There is a positive and significant relationship between the proportion of Black, Hispanic and Asian residents and overall cancer risk and a negative and significant relationship between population density and number of people below the poverty line and overall cancer risk.
2. In comparison to the OLS model, the GWR model fit the data disproportionately across the map, with hotspots in urban centres like Miami.
This paper makes a convincing case for GWR and the authors use GIS software to produce clear and legible maps, but more care could have gone into the selection of model data. The authors elaborate on the theoretical element of GWR but this soon becomes repetitive. As such, this paper has been given a rating of 7/10.