Income and Access to Healthcare’s Impact on Longevity Throughout Illinois Counties
Session Number
Project ID: BHVSO 13
Advisor(s)
Patrick Kearney, Illinois Mathematics and Science Academy
Discipline
Behavioral and Social Sciences
Start Date
20-4-2022 9:10 AM
End Date
20-4-2022 9:25 AM
Abstract
Across the United States, there is a twenty-year life expectancy difference between the county with the highest longevity and the county with the lowest longevity (USC). Income is a major factor with wealthier regions having some of the highest longevity. However, there are many more external factors, especially those relating to healthcare, that shorten the longevity of those residing in a particular region. This project determines the extent to which higher income and better access to healthcare, measured as the percentage of uninsured residents and the percentage of licensed physicians and surgeons in each region, affects the average life expectancy for each county in Illinois. These hypotheses will be tested using OLS regression analysis. These conclusions will inform further research and actions to be implemented to address the factors that are correlated with shorter life expectancies in order to decrease the gap between longevity within Illinois.
Income and Access to Healthcare’s Impact on Longevity Throughout Illinois Counties
Across the United States, there is a twenty-year life expectancy difference between the county with the highest longevity and the county with the lowest longevity (USC). Income is a major factor with wealthier regions having some of the highest longevity. However, there are many more external factors, especially those relating to healthcare, that shorten the longevity of those residing in a particular region. This project determines the extent to which higher income and better access to healthcare, measured as the percentage of uninsured residents and the percentage of licensed physicians and surgeons in each region, affects the average life expectancy for each county in Illinois. These hypotheses will be tested using OLS regression analysis. These conclusions will inform further research and actions to be implemented to address the factors that are correlated with shorter life expectancies in order to decrease the gap between longevity within Illinois.