In order to visualize statistically significant hot or cold spots within our study area, we performed a series of hot spot analyses. Hot or cold spots are areas where there is significant spatial clustering of high or low values which, when visualized, help to distinguish larger patterns of a variable’s distribution over space. We performed the hot spot analysis using ArcMap’s Hot Spot (Getis-Ord Gi*) spatial analyst tool on the five-year lung cancer mortality rate (1999-2003) (the dependent variable), and six other explanatory variables. These explanatory variables were selected based on existing research, suggesting they are linked to lung cancer in a causal or associative manner. These variables of interest were:
- Median household income
- Proportion of non-white population
- Percent of homes occupied by renters
- Annual arithmetic mean PM 2.5 concentration
- Proportion of population with a university degree
- Smoking prevalence