Abstract
ABSTRACT
Introduction
Counties in persistent poverty (PP) have higher cancer‐related mortality rates. Intersectionality with race and rurality is present; individuals identifying as Black residing in rural PP counties have the highest cancer‐related mortality rates. However, heterogeneity exists throughout counties (e.g., demographics). To date, few studies evaluated the effect of small‐area PP residence on individual‐level survival and intersectionality with race and rurality.
Methods
This retrospective cohort utilized Alabama Statewide Cancer Registry data of adults with breast, prostate, colorectal, or lung cancer. The exposure was NCI‐designated 2010 census tract‐level PP (tracts with ≥ 20% population below poverty line for ≥ 30 years) at diagnosis and the outcome was overall survival from date of diagnosis to death or end of follow‐up. Associations were estimated via sequential Cox proportional hazards models first with PP as the only predictor then adjusting for demographics (age, race, sex [colorectal, lung]), demographics plus clinical characteristics (stage, subtype [breast], and first course treatment), and finally demographics, clinical characteristics, and social determinants (rurality, insurance status). We also performed a decomposition analysis of the association between PP and survival through race and rurality.
Results
In the fully adjusted model, living in a PP‐tract was associated with higher risk of death among those with breast (hazard ratio [95% CI]: 1.18 [1.09–1.27]), prostate (1.21 [1.11–1.31]), and lung cancer (1.09 [1.05–1.14]) compared to living in a non‐PP‐tract. Race and rurality were independently associated with higher risk of death across cancers. Individuals identifying as Black residing in a rural PP‐tract had the highest magnitude of risk for all cancers.
Conclusions
Living in a PP‐tract is associated with higher risk of death among patients with breast, prostate, and lung cancer in Alabama. This association is complicated by race and rurality. Multilevel interventions tailored to local context may help overcome adverse effects of social characteristics on cancer outcomes.