Spring 2022

Document Type



School of Business

Faculty Advisor

Mitchell Priestley


In this paper, our dependent variable is average life expectancy by state in the United States. The purpose is to determine which factors have an impact on average life expectancy, as well as the magnitude of these impacts. While other studies have been conducted on life expectancy, our focus is different in a subtle but important way. Rather than centering on individual life expectancy, studying factors like “activity” or “genetics,” we focus on the broader population in a state and which factors affect life expectancy on a macro-scale. There is little known about this topic that isn’t in direct reference to life expectancy for a single person, and we found that some commonly held beliefs about life expectancy, which may be based on studies such as these, were contradicted by this study. For example, it is understood that women tend to live longer than men (Disabled World). Yet, in our analysis, although all but 4 states were majority-female, we found that states with higher proportions of men have higher average life expectancies. This appears to be contrary to the other findings, but we explore our hypothesis as to why this may be the case. The information contained in this study could be useful to state legislators for determining policies that affect the variables in question. For example, we found that obesity rates have a negative correlation with life expectancy. This understanding could be used to sponsor state health campaigns that attempt to reduce obesity rates, raising their state’s average life expectancy. We used OLS regression analysis and found that the percentage of smokers had the largest impact on life expectancy in a state, while the least impactful, though still significant, factor we found was the percentage of uninsured individuals. The information provided here on these factors could, perhaps, embolden anti-smoking and health care campaigns in states across the country.