Leslie TF, Frankenfeld CL, Menon N. 2022. Racial and economic residential segregation of diagnostic hospital: disparities in colorectal cancer time-to-treatment and survival in Georgia, United States. Cancer Epidemiol 81:102267, https://doi.org/10.1016/j.canep.2022.102267.
Abstract
Purpose
To evaluate patient-level colorectal cancer outcomes in relation to residential income and racial segregation and composition of the neighborhood surrounding the diagnosing hospitals, and characterize presence of cancer-relevant diagnosis and treatment modalities that might contribute to these associations.
Methods
We utilized Georgia state cancer registry data (2010–2015), matching diagnosis information to hospital technology provided by the American Hospital Association and spatial information to the US Census. We modeled time-to-treatment and survival time, using Cox proportional hazards models, stratified by segregation. Segregation was examined as residential economic and racial evenness (Atkinson index) and isolation (isolation index) and mean income at the Census tract level. To assess possible contributing factors, analysis of hospital diagnosis and treatment technologies in relation to segregation was conducted.
Results
Average income of the Census tract and racial residential segregation of the diagnosing hospital’s neighborhood was generally unassociated with time-to-treatment or survival time. Higher income evenness around the diagnosing hospital was associated with shorter time-to-treatment, with no association with time-to-death. Higher income isolation for the diagnosing hospital, conversely, was associated with longer times to treatment, but also longer survival times. Hospitals in regions with higher level of residential income segregation were less likely to have a particular diagnosing or treatment technologies, such as virtual colonoscopy and chemotherapy.
Conclusion
Hospital resources may be a function of their immediate economic environment, and this may have influence on cancer outcomes. Future work should evaluate patient outcomes in light of technologies or therapies utilized within particular economic environments.