Urban–rural differences in cancer mortality: Operationalizing rurality.

Objective: 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. Methods: 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. Results: 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. Conclusions: 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. Policy Implications: 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. [ABSTRACT FROM AUTHOR]

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