Abstract Background: Breast cancer (BC) disparities across race, socioeconomic status, and location, stress the need for equitable access to screening. In Virginia (VA), BC is a major concern, with Petersburg City having the highest mortality rate nationwide. Understanding social and structural factors’ impact on mammography accessibility may provide insights on effectively serving screening-eligible women in VA, particularly those facing greater BC burden. Also, analyzing data at the census tract level is vital for accurate accessibility assessment, mitigating county-level data skewing and disparity concealment. Objective: Examine how social and structural factors (e.g., demographics, transportation, area deprivation) influence mammography facility and unit distribution in VA. Methods: We utilized a comprehensive approach to compile and analyze data at the census tract level. We employed Poisson regression models to predict the number of mammography facilities and units within each tract. The predictor variables included the number of bus stops (VA Transit Routes & Stops GTFS), percentage of Black residents (American Community Survey), area deprivation index (ADI) scores (Neighborhood Atlas®), and vehicle ownership rates (American Community Survey), with the logarithm of the population of females aged 40-74 used as an offset to account for population size. Separate models were built for VA, our catchment area, urban areas within our catchment, and rural areas within our catchment. We exponentiated the model coefficients to obtain relative risks, indicating the multiplicative effect of each predictor on the outcome variable. Results: Study findings highlighted statistically significant disparities in the distribution of mammography facilities and units within VA. Higher ADI scores, indicating greater socioeconomic deprivation, were linked to fewer mammography units. This association was notable in our rural catchment areas (RR = 0.5492), indicating a 45.08% reduction in mammography units, in our catchment area overall (RR = 0.8653), a 13.47% decrease, and in urban catchment areas (RR = 0.8800), a 12.00% decline. Similarly, an increase in the percentage of Black residents was consistently associated with a decrease in the number of mammography units, with a relative risk of 0.8828 within our catchment area, indicating a 11.72% decrease, 0.8793 in urban areas within our catchment, signifying a 12.07% decrease, and 0.9391 statewide, showing a 6.09% decrease. Conclusions: These findings stress the need for targeted resource allocation to enhance mammography access. For instance, findings suggest a specific need for increased mammography units in rural areas and areas with higher percentages of Black women, like Petersburg (67.5% to 94.9% Black population depending on the tract), specifically within our catchment. Implications from these findings provide a unique opportunity to leverage the expertise of residents, community leaders and local representatives to identify where additional resources can be allocated. Citation Format: Bianca D. Owens, Jinlei Zhao, Katherine Y. Tossas. Toward breast health equity: Insights into mammography access across Virginia’s social and structural landscape [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C181.
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