Posters
How Healthcare Access and Socioeconomic Factors Influence Life Expectancy Across Texas Counties
Presenting Author Academic/Professional Position
Medical Student
Academic Level (Author 1)
Medical Student
Academic Level (Author 2)
Medical Student
Presentation Type
Poster
Discipline Track
Community/Public Health
Abstract Type
Research/Clinical
Abstract
Objective: Life expectancy is often used as a public health measure for health outcomes. Certain health outcomes, including life expectancy, are influenced by various factors such as healthcare access and socioeconomic status. This study explores the relationship between these factors across Texas counties, using data on life expectancy, median household income, and the ratio of primary care physicians. This analysis may help to identify regions that may require increased economic resources and improved healthcare access, while highlighting the Rio Grande Valley (RGV) counties.
Methods: Life expectancy data was obtained from County Health Rankings & Roadmaps (2024), primary care physician ratios were sourced from the same dataset, and median household income data was collected from TexasCounties.net (2020). Statistical analyses, including correlation analysis and a two-tailed paired t-test (alpha = 0.05), were performed to assess the relationships between the variables. Outliers were removed from the data before analysis. The investigation was limited by some missing values and unknown source data collection.
Results: Results indicate that the average life expectancy in Texas is 77.2 years (SD = 2.52), with life expectancy in Cameron, Hidalgo, and Starr counties showing minimal deviation from the state average (z-scores of 0.040, 0.278, and -1.15, respectively). The average physician ratio across Texas is 1657:1 (SD = 2331.89), and a negative correlation of -0.1603 (p = 2 x 10⁻⁴⁹) was found between the physician ratio and life expectancy. For the three RGV counties, the z-scores for physician ratios in Cameron, Hidalgo, and Starr counties were 0.1615, 0.1690, and 0.954, respectively, indicating no statistical significance. Median household income in Texas averaged $67,110 (SD = 12,982.99), with a significant positive correlation of 0.5552 (p = 2.35 x 10⁻¹⁵⁸) between income and life expectancy. The z-scores for Cameron and Hidalgo counties' median household incomes were not statistically significant, while Starr County had a z-score of -2.418, indicating that its income is significantly below the state average.
Conclusion: The findings suggest that life expectancy is strongly influenced by both primary care physician ratios and median household income. Specifically, a high physician-to-population ratio correlates with improved life expectancy, while higher income levels are linked to better health outcomes. The study highlights that Starr County, with its lower income and higher physician ratio, is more disadvantaged than other counties, which could explain its lower life expectancy. These results emphasize the need for increased healthcare access and economic resources in underserved regions, particularly in rural areas such as the RGV.
Recommended Citation
Tah, Giani C. and Mora, Johanna, "How Healthcare Access and Socioeconomic Factors Influence Life Expectancy Across Texas Counties" (2025). Research Symposium. 67.
https://scholarworks.utrgv.edu/somrs/2025/posters/67
How Healthcare Access and Socioeconomic Factors Influence Life Expectancy Across Texas Counties
Objective: Life expectancy is often used as a public health measure for health outcomes. Certain health outcomes, including life expectancy, are influenced by various factors such as healthcare access and socioeconomic status. This study explores the relationship between these factors across Texas counties, using data on life expectancy, median household income, and the ratio of primary care physicians. This analysis may help to identify regions that may require increased economic resources and improved healthcare access, while highlighting the Rio Grande Valley (RGV) counties.
Methods: Life expectancy data was obtained from County Health Rankings & Roadmaps (2024), primary care physician ratios were sourced from the same dataset, and median household income data was collected from TexasCounties.net (2020). Statistical analyses, including correlation analysis and a two-tailed paired t-test (alpha = 0.05), were performed to assess the relationships between the variables. Outliers were removed from the data before analysis. The investigation was limited by some missing values and unknown source data collection.
Results: Results indicate that the average life expectancy in Texas is 77.2 years (SD = 2.52), with life expectancy in Cameron, Hidalgo, and Starr counties showing minimal deviation from the state average (z-scores of 0.040, 0.278, and -1.15, respectively). The average physician ratio across Texas is 1657:1 (SD = 2331.89), and a negative correlation of -0.1603 (p = 2 x 10⁻⁴⁹) was found between the physician ratio and life expectancy. For the three RGV counties, the z-scores for physician ratios in Cameron, Hidalgo, and Starr counties were 0.1615, 0.1690, and 0.954, respectively, indicating no statistical significance. Median household income in Texas averaged $67,110 (SD = 12,982.99), with a significant positive correlation of 0.5552 (p = 2.35 x 10⁻¹⁵⁸) between income and life expectancy. The z-scores for Cameron and Hidalgo counties' median household incomes were not statistically significant, while Starr County had a z-score of -2.418, indicating that its income is significantly below the state average.
Conclusion: The findings suggest that life expectancy is strongly influenced by both primary care physician ratios and median household income. Specifically, a high physician-to-population ratio correlates with improved life expectancy, while higher income levels are linked to better health outcomes. The study highlights that Starr County, with its lower income and higher physician ratio, is more disadvantaged than other counties, which could explain its lower life expectancy. These results emphasize the need for increased healthcare access and economic resources in underserved regions, particularly in rural areas such as the RGV.
