Utilizing Exploratory Spatial Data Analysis to Examine Health and Environmental Disparities in Disadvantaged Neighborhoods.

Health disparities research has focused primarily on racial and socioeconomic differences in health outcomes. Although neighborhood characteristics and the concept of built environment have been shown to affect individual health, measuring the effects of environmental risks on health has been a less developed area of disparities research. To examine spatial associations and the distribution of geographic patterns of sociodemographic characteristics, environmental cancer risk, and cancer rates, we utilized existing data from multiple sources. The findings from our initial analysis, which concerned with proximity to environmental hazards and at-risk communities, were consistent with results of previous studies, which often reported mixed relationships between health disparity indicators and environmental burden. However, further analysis with refined models showed that several key demographic and subdomains of cancer risk measures were shown to have spatial components. With the application of exploratory spatial data analysis, we were able to identify areas with both high rates of poverty and racial minorities to further examine for possible associations to environmental cancer risk. Global spatial autocorrelation found spatial clustering with percent black, percent poverty, point and non-point cancer risks requiring further spatial analysis to determine relationship of significance based on geography. This methodology was based upon particular assumptions associated with data and applications, which needed to be met. We conclude that careful assessment of the data and applications were required to properly interpret the findings in understanding the relationship between vulnerable populations and environmental burden.