Mammography Access, Urbanicity, and Late-Stage Breast Cancer Burden Across Texas: A Bayesian Spatial Analysis

Background Geographic disparities in access to preventive healthcare services remain an important contributor to breast cancer inequities in the United States. Mammography screening plays a critical role in early detection and improved survival; however, screening infrastructure and healthcare accessibility remain unevenly distributed across many regions, particularly within large and socioeconomically diverse states such as Texas. Understanding the spatial relationships among mammography access, urbanicity, socioeconomic vulnerability, and late-stage breast cancer burden is important for developing geographically targeted public health interventions. Methods This study integrated multiple county-level datasets, including mammography facility locations from the Texas Cancer Information database, late-stage breast cancer burden data from the National Cancer Institute, and socioeconomic indicators from census-derived datasets and the Centers for Disease Control and Prevention Social Vulnerability Index. Geographic information systems (GIS), spatial autocorrelation analyses, and Bayesian spatial epidemiologic methods were used to evaluate geographic patterns across Texas counties from 2018 to 2022. Global and local Moran's I statistics were calculated to assess spatial clustering patterns. Bayesian spatial Poisson conditional autoregressive (CAR) regression models were subsequently estimated to examine associations between mammography center density, population density, female socioeconomic characteristics, and late-stage breast cancer burden while accounting for residual spatial dependence. Results Significant positive spatial autocorrelation was observed for county-level late-stage breast cancer burden across Texas counties. Mammography facilities were heavily concentrated within major metropolitan regions, while many rural counties demonstrated comparatively limited screening infrastructure availability. Bayesian spatial regression analyses demonstrated that log-transformed population density was significantly inversely associated with the burden of late-stage breast cancer ({beta} = -0.136, 95% CrI [-0.175, -0.103]), indicating that less densely populated counties experienced greater burden than more urbanized counties. Mammography center density showed a borderline inverse association with late-stage burden ({beta} = -0.008, 95% CrI [-0.017, 0.002]), suggesting that greater availability of screening infrastructure may contribute to reduced burden. Persistent residual spatial dependence remained across counties ({rho} = 0.472, 95% CrI [0.038, 0.919]), indicating ongoing geographic clustering beyond measured explanatory variables. Conclusions Substantial geographic disparities in late-stage breast cancer burden, mammography access, and socioeconomic vulnerability exist across Texas counties. The findings suggest that urbanicity and screening infrastructure availability play important roles in shaping geographic inequities in breast cancer outcomes. Public health interventions should move beyond increasing facility availability alone and instead incorporate geographically targeted strategies that address rural healthcare access limitations, healthcare infrastructure disparities, and broader structural barriers to preventive screening services.