Abstract C009: Estimating the true contribution of rural residence and area deprivation on cancer mortality
Authors: Kenzik Kelly , Davis Elizabeth , Franks Jeffrey , Bhatia Smita 
Published: December 2023

Introduction True estimation of the rural effect on cancer mortality requires causal inference methodology, consideration of area-level socioeconomic status and examination of area designations (e.g., measurement of rural vs urban). Methods Utilizing Surveillance, Epidemiology and End Results data we identified key incident cancers diagnosed between 2000 and 2016 at age ≥20 (n=3,788,273). Cancer types were selected based on prior evidence of rural mortality disparities. A 20% random sample was examined (n=757,655). Rurality was defined using the Rural Urban Continuum Codes (RUCC). County indicators were linked with the Area Deprivation Index (ADI, 0 least deprived to 100 highest deprivation). Standardized competing risk and survival models estimated causal impact of rural residence on cancer-specific mortality. All models controlled for age at diagnosis, sex, race/ethnicity, year of diagnosis, and ADI. We estimated rural residence and ADI’s attributable fraction to the probability of mortality. Models were run overall and by stage. Finally, we identified county measurement issues contributing to county rates discordant from hypothesized mortality rates (i.e., urban counties with mortality&gt;median or rural counties with mortality≤median).  Results Approximately 45% were diagnosed ≥65y, 51% were female, 71% non-Hispanic white, and 12% non-Hispanic Black. Cancer diagnoses included those with screening recommendations (70%), obesity related (57%), and tobacco-related cancers (21%). The majority of patients were diagnosed with in situ or localized disease (53%). The 5y standardized failure probability for cancer-specific mortality for rural patients was 33.9% vs. 31.6% among urban. Rural + high ADI mortality was 37.9% vs. 30.7% for urban + low ADI.  Rural residence attributable fraction to the probability of cancer mortality was 1.04% at Year 1, declining to 0.9% by Year 5. The rural fraction was highest among local stage disease (Y1 2.1% to Y5 1.9%). Attributable fraction of high ADI was 3.3% in Y1 to 2.9% in Y5, while the joint effect of rural+high ADI ranged from 4.3% in Y1 to 3.7% in Y5. Discordance between hypothesized and actual mortality was greater with urban/rural definitions vs  ADI cut-offs (i.e., ADI distinguishes between high and low mortality better). Among 256 urban counties, 21.7% (n=89) had a higher mortality rate than hypothesized (mortality rate &gt; median). Of those, 27 counties had no metropolitan area, but were “attached” to a nearby metro-area according to US Economic Research Service. When these 27 counties were reclassified as rural, the rural fraction was 1.4% at Y1 and 1.2% at Y5. This was a 35% and 26% relative increase, respectively.  Among 349 rural counties, 15% had mortality rates higher than expected. Conclusion: Rural residence holds a small independent contribution to cancer mortality; higher among localized disease and in areas with greater deprivation. Urban/rural county designations using standard metrics may mask high need urban counties, limiting eligibility to state or federal resources dedicated to rural areas.

Citation Format: Kelly Kenzik, Elizabeth Davis, Jeffrey Franks, Smita Bhatia. Estimating the true contribution of rural residence and area deprivation on cancer mortality [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C009.