Deb Linton

Role 

My role in this group project involved project design and write up, as well as health data collection, interpretation, and data preparation. I also influenced what methods of data analysis should be used and what the project’s findings did (and did not) represent.

• Researcher

• Writer

• 4 Person Team

Description

The project used Pandas to linked public emissions data from the EPA and health indicator data from the California Department of Public Health in an attempt to find a correlation between incidences of asthma treatments and air pollutants.

GIT CODE & DATA

findings

There is a moderate correlation between environmental factors and hospitalizations due to asthma. Hospitalizations due to asthma can represent a variety of health events but the indicator sits on the spectrum of severity between mortality and emergency room visits. We identified hospitalization due to asthma as relevant because this health event might be less prone to the many external factors that contribute to emergency room visits due to asthma and asthma related death. If we expanded the scope of our project to include a multi-dimensional analysis of factors such as socioeconomic class, rates of genetic predisposition, age, hospital ranking, etc., we would expect to see a similar correlation between emergency room visits and environmental factors. Further investigation about the progression of asthma related emergency room visits to asthma related hospitalization is needed to verify this reasoning. We chose to use the data visualization technique of small multiples to allow readers to draw connections between the geographic areas on their own as the direct combination of county health and emissions data would not be statistically accurate. For example we see the central valley has both high asthma hospitalizations and emissions in comparison with other counties over the course of multiple years. This is perhaps due to the topography of the region creating an area for pollutants to concentrate.

Ideas for Future Work

This project exposed many opportunities for future work. In no particular order, we encourage others to build on our findings with projects that:

• Include other emissions health triggers like Sulfur Dioxide to find correlations with asthma and other chronic diseases attributed to air quality.
•  A comparison of how open state data may or may not align with more exogenous evaluations of the Clean Air Act.
• Develop an interactive county level time series map to show how emissions and health indicators have changed after certain regulation were enacted, such as the Clean Air Act or The Protect California Air Act.
• Tackle the interoperability issues of state gathered asthma data by writing 50 state based data frames.
• Incorporate the costs for treating asthma hospitalizations and compare it to the costs of air quality regulation.
• Displaying PPD county data about the progression of asthma related emergency room visits to asthma related hospitalization.