Category
Three-Minute Thesis
Description
Health equity depends on accurate representation, yet vulnerable populations are often undercounted in community health assessments. In Lynchburg, Virginia, reliance on voluntary survey data in the Community Health Needs Assessment (CHNA) obscures the true scale of transportation barriers to care. This study examines how transportation access intersects with socioeconomic disadvantage to shape health outcomes.
Using census-based data from the American Community Survey and Centers for Disease Control and Prevention PLACES dataset, we analyzed the overlap of low income, lack of insurance, and limited vehicle access. Data were processed in SAS and standardized using Z-scores to create a Vulnerability Index identifying high-risk census tracts.
Results show a strong correlation (r = 0.83) between transportation barriers and poor health outcomes. High-vulnerability tracts (6, 7, 11, 19, and 4) experience transportation burdens underestimated by two to three times in CHNA data. These findings reveal that current assessment methods overlook the most vulnerable populations, leading to misaligned resource allocation. Integrating census-based data into planning is essential to ensure equitable, data-driven health interventions.
Statistical Ghosts: The People Our Health System Can’t See
Three-Minute Thesis
Health equity depends on accurate representation, yet vulnerable populations are often undercounted in community health assessments. In Lynchburg, Virginia, reliance on voluntary survey data in the Community Health Needs Assessment (CHNA) obscures the true scale of transportation barriers to care. This study examines how transportation access intersects with socioeconomic disadvantage to shape health outcomes.
Using census-based data from the American Community Survey and Centers for Disease Control and Prevention PLACES dataset, we analyzed the overlap of low income, lack of insurance, and limited vehicle access. Data were processed in SAS and standardized using Z-scores to create a Vulnerability Index identifying high-risk census tracts.
Results show a strong correlation (r = 0.83) between transportation barriers and poor health outcomes. High-vulnerability tracts (6, 7, 11, 19, and 4) experience transportation burdens underestimated by two to three times in CHNA data. These findings reveal that current assessment methods overlook the most vulnerable populations, leading to misaligned resource allocation. Integrating census-based data into planning is essential to ensure equitable, data-driven health interventions.
