Socio-Environmental Conditions Associated with Geospatial Clusters of Urothelial Carcinoma: A Multi-Institutional Analysis. Issue 6 (21st December 2021)

• Record Type: Journal Article
• Authors: Yankelevich, Gabrielle R.; Dreher, Paulette C.; Taylor, Zachariah; Kim, Daniel; Buckley, Meghan; Larson, Sharon; Belkoff, Laurence; Bernstein, Guy; Edwards, Daniel C.
• Is Part Of: Journal of urology. Volume 206:Issue 6(2021)
• Page Start: 1390
• Page End: 1402
• Publication Date: 2021-12-21
• Subjects: healthcare disparities -- urologic neoplasms -- carcinogens -- environmental; Genitourinary organs -- Periodicals; Urology -- Periodicals; Urology -- Periodicals; Urologie -- Périodiques; Urologie; 616.6
• DOI: 10.1097/JU.0000000000002119
• Languages: English
• ISSNs: 0022-5347

Abstract

Abstract : Purpose: The interaction between sources of industrial byproducts and environmental pollutants (IBP/EP) and the prevalence of urothelial carcinoma (UC) in surrounding communities has been infrequently explored. The purpose of this research is to identify microregional UC hotspots and associated industrial and environmental risk factors. Materials and Methods: We retrospectively queried a multi-institutional database for UC patients diagnosed between 2008 and 2018. Addresses were geocoded and used to perform hotspot analysis on the census block level. Demographic and clinicopathological characteristics, census data and proximity to sources of IBP/EP were compared between patients who did vs did not reside in a hotspot. Associations were tested using multilevel logistic regression models using 95% confidence intervals. Results: A total of 5, 080 patients met inclusion criteria and 148 (2.9%) were identified as living in 1 of 3 UC hotspots. In univariate analyses, race, tobacco and alcohol use, household income, IBP/EP exposure and proximity to traffic, industrial discharge and airports were significantly associated with UC hotspots. Multivariable analysis demonstrated that polycyclic aromatic hydrocarbon exposure (OR: 48.09, p ≤0.001) and proximity to high-density traffic (OR: >999, p ≤0.001) increased the odds of living in a hotspot. Patients living in a hotspot were significantly less likely to be white (OR: 0.06, p ≤0.001) or tobacco users (OR: 0.39, p=0.031) on multivariate analysis. Conclusions: Spatially related clusters of UC may be associated with locoregional environmental exposures rather than tobacco exposure and may also be correlated with socioeconomic disparities. Geospatial analysis can help to identify at-risk populations, offering the opportunity to better focus preventive and diagnostic interventions.