Politics influence people’s health in profound and often unexpected ways. A recent study reveals that conservative trifecta states—where Republicans control the governorship and have majorities in both branches of the state legislature—consistently experience poorer health outcomes, including higher premature mortality rates and lower vaccination coverage. Harvard Public Health spoke with Nancy Krieger, social epidemiology professor at the Harvard T.H. Chan School of Public Health and lead author of the study.
Why study this topic?
Public health is inherently political. Policies don’t just appear—they are enacted by legislators, implemented by state agencies, and influenced by political ideologies. Yet, political metrics like voting records and state trifectas are rarely used in public health research. I was motivated to investigate the political determinants of health through a fresh lens.
What did you find?
We analyzed over a decade of data and found consistent associations between political conservatism and poorer health outcomes. The strongest correlations came from metrics rarely used in public health—state trifectas and political ideologies of elected officials.
For example, premature mortality rates were significantly higher in Republican trifecta states, which had 55.4 more deaths per 100,000 person-years compared to Democratic trifectas in 2016. To capture the immediate effects of governance, we focused on outcomes for which the time period from exposure to the health event is very fast (such as getting vaccinated and getting, or losing, health insurance coverage) as opposed to health events that could take a long time to show up, such as getting and being diagnosed with cancer. Our findings underscore the tangible impact of political decisions on population health.
What would you like to see happen based on the study’s results?
This research highlights the need for evidence-based governance. Legislators, advocacy groups, and public health agencies must prioritize health equity when making policy decisions. These associations are not deterministic—they reflect practices that can change. Looking forward, we plan to investigate additional health outcomes and refine causal analysis methods. By making our data publicly available, we hope to encourage further research and informed policymaking.
—Paul Adepoju