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.