The Relationship between Air Quality and Health Outcomes
Advisor(s)
Dr. Marynia Kolak, Univeristy of Chicago
Location
Room A121
Start Date
26-4-2019 10:25 AM
End Date
26-4-2019 10:40 AM
Abstract
Compelling evidence suggests that a relationship between air quality and health outcomes has already been established but has not been studied on a census-tract level. The objective of this research is to identify the phenomenon in the observed trends in a more specific manner and to measure and explore relationships of multiple health outcomes with particulate matter in the Chicagoland area using spatial data integration and analysis techniques, thus allowing for a more formulaic understanding of the correlation. The air quality data used in this project is a 2018 yearly average of PM2.5. This data is interpolated from nearby Environmental Protection Agency (EPA) monitoring stations using geostatistical kriging methods. The census-tract level data is taken from the 500 Cities project by the Centers for Disease Control and Protection for 2018. The specific health outcomes we looked at were current asthma, coronary heart disease, diagnosed diabetes, mental health, and physical health among adults aged greater than 18 years, as identified from an extensive literature review. We explored data relationships using scatterplots, choropleth maps, and box plots using Rstudio and Geoda and identified bivariate hotspots of high air pollution and poor health outcomes to identify priority areas. Preliminary results show that correlations persist, though remain complex, between poor air quality and worse health outcomes, even at a small area resolution.
The Relationship between Air Quality and Health Outcomes
Room A121
Compelling evidence suggests that a relationship between air quality and health outcomes has already been established but has not been studied on a census-tract level. The objective of this research is to identify the phenomenon in the observed trends in a more specific manner and to measure and explore relationships of multiple health outcomes with particulate matter in the Chicagoland area using spatial data integration and analysis techniques, thus allowing for a more formulaic understanding of the correlation. The air quality data used in this project is a 2018 yearly average of PM2.5. This data is interpolated from nearby Environmental Protection Agency (EPA) monitoring stations using geostatistical kriging methods. The census-tract level data is taken from the 500 Cities project by the Centers for Disease Control and Protection for 2018. The specific health outcomes we looked at were current asthma, coronary heart disease, diagnosed diabetes, mental health, and physical health among adults aged greater than 18 years, as identified from an extensive literature review. We explored data relationships using scatterplots, choropleth maps, and box plots using Rstudio and Geoda and identified bivariate hotspots of high air pollution and poor health outcomes to identify priority areas. Preliminary results show that correlations persist, though remain complex, between poor air quality and worse health outcomes, even at a small area resolution.