biostudies-literatureDavis ESNCI NIH HHS268-271https://www.ebi.ac.uk/biostudies/studies/S-EPMC10902199biostudies-literatureUnknown40(2)<h4>Objective</h4>To assess urban-rural differences in cancer mortality across definitions of rurality as (1) established binary cut-points, (2) data-driven binary cut-points, and (3) continuous.<h4>Methods</h4>We used Surveillance, Epidemiology, and End Results (SEER) data between 2000 and 2016 to identify incident adult screening-related cancers. Analyses were based on one testing and four validation cohorts (all n = 26,587). Urban-rural status was defined by Rural-Urban Continuum Codes, National Center for Health Statistics codes, and the Index of Relative Rurality. Each was modeled using established binary cut-points, data-driven cut-points, and as continuous. The primary outcome was 5-year cancer-specific mortality.<h4>Results</h4>Compared to established cut-points, data-driven cut-points classified more patients as rural, resulted in larger White populations in rural areas, and yielded 7%-14% lower estimates of urban-rural differences in cancer mortality. Further, hazard of cancer mortality increased 4%-67% with continuous rurality measures, revealing important between-unit differences.<h4>Conclusions</h4>Different cut-points introduce variation in urban-rural differences in mortality across definitions, whereas using urban-rural measures as continuous allows rurality to be conceptualized as a continuum, rather than a simple aggregation.<h4>Policy implications</h4>Findings provide alternative cut-points for multiple measures of rurality and support the consideration of utilizing continuous measures of rurality in order to guide future research and policymakers.The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care AssociationUrban-rural differences in cancer mortality: Operationalizing rurality.PMC10902199R37 CA266193Franks JAKenzik KMBhatia SDavis ESfalseUrban-rural differences in cancer mortality: Operationalizing rurality.<h4>Objective</h4>To assess urban-rural differences in cancer mortality across definitions of rurality as (1) established binary cut-points, (2) data-driven binary cut-points, and (3) continuous.<h4>Methods</h4>We used Surveillance, Epidemiology, and End Results (SEER) data between 2000 and 2016 to identify incident adult screening-related cancers. Analyses were based on one testing and four validation cohorts (all n = 26,587). Urban-rural status was defined by Rural-Urban Continuum Codes, National Center for Health Statistics codes, and the Index of Relative Rurality. Each was modeled using established binary cut-points, data-driven cut-points, and as continuous. The primary outcome was 5-year cancer-specific mortality.<h4>Results</h4>Compared to established cut-points, data-driven cut-points classified more patients as rural, resulted in larger White populations in rural areas, and yielded 7%-14% lower estimates of urban-rural differences in cancer mortality. Further, hazard of cancer mortality increased 4%-67% with continuous rurality measures, revealing important between-unit differences.<h4>Conclusions</h4>Different cut-points introduce variation in urban-rural differences in mortality across definitions, whereas using urban-rural measures as continuous allows rurality to be conceptualized as a continuum, rather than a simple aggregation.<h4>Policy implications</h4>Findings provide alternative cut-points for multiple measures of rurality and support the consideration of utilizing continuous measures of rurality in order to guide future research and policymakers.2024-01-01T00:00:00Z2024 Mar2025-04-04T00:48:15.402Z2025-04-04T00:48:15.402ZS-EPMC109021993764465010.1111/jrh.12792