Unincorporation in counties as a political determinant of health: An exploration of five states

Local government policies and practices shape the context of the places that can alter a population's life chances through socioeconomic factors, built environments, and healthcare access. County governments, one of the most ubiquitous U.S. political structures, impact health outcomes within their jurisdiction through multiple policy levers and pathways. By identifying which political determinants within counties are associated with variation in life expectancy and premature death, we can better intervene on modifiable factors. One overlooked political determinant from public health studies is the county's responsibility as the primary local government for approximately a third of the U.S. population and 93% of land in unincorporated areas. To conduct an ecological study and assess associations between county population health and county responsibility for unincorporated areas and populations, we created and tested two county indicators of unincorporation. Multilevel multivariable regression results showed that larger proportions of unincorporated land within a county are associated with lower average county life expectancy. More testing of the measurement is needed to understand the relationship between unincorporation, county government, and population health outcomes.

Authors

Institutions

Publication Details

Journal
SSM - Population Health
Published
2024-11-19
DOI
https://doi.org/10.1016/j.ssmph.2024.101728
Primary Topic
Global Health Care Issues
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Unincorporation in counties as a political determinant of health: An exploration of five states

G. Allen Ratliff, Ashley N. Palmer, Cristina Gomez-Vidal, Katherine Kitchens et al.
SSM - Population Health
Global Health Care Issues
article

Unincorporation in counties as a political determinant of health: An exploration of five states

G. Allen Ratliff, Ashley N. Palmer, Cristina Gomez-Vidal, Katherine Kitchens, Genevieve Graaf
article en

Abstract

Local government policies and practices shape the context of the places that can alter a population's life chances through socioeconomic factors, built environments, and healthcare access. County governments, one of the most ubiquitous U.S. political structures, impact health outcomes within their jurisdiction through multiple policy levers and pathways. By identifying which political determinants within counties are associated with variation in life expectancy and premature death, we can better intervene on modifiable factors. One overlooked political determinant from public health studies is the county's responsibility as the primary local government for approximately a third of the U.S. population and 93% of land in unincorporated areas. To conduct an ecological study and assess associations between county population health and county responsibility for unincorporated areas and populations, we created and tested two county indicators of unincorporation. Multilevel multivariable regression results showed that larger proportions of unincorporated land within a county are associated with lower average county life expectancy. More testing of the measurement is needed to understand the relationship between unincorporation, county government, and population health outcomes.

SSM - Population HealthVol. 28
Texas Christian University (US), University of Nevada, Reno (US), The University of Texas at Arlington (US), University of California, Berkeley (US)
Openalex Percentile: Top 63%
Global Health Care Issues
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.