Abstract
OBJECTIVE: to characterize the county variability of the impact of smoking elimination on rates of smoking-related cancers and explore whether common environmental indices predicted which metropolitan counties would experience high rates of smoking-related cancers even after smoking was eliminated. METHODS: Surveillance, Epidemiology, and End Results Program (SEER) and Environmental Protection Agency (EPA) data were obtained. County level cancer rates for 257 metropolitan SEER counties, including the observed rates and those predicted after eliminating smoking, were derived via multilevel regression modeling and age standardized to the 2016 SEER population. Associations between the EPA's Environmental Quality Index (EQI) scores and "Low Benefit" counties (counties that remain above the top 20th percentile of post-smoking elimination incidence rates) were explored via logistic regression. RESULTS: Reductions in smoking-related cancer incidence ranged from 58.4 to 3.2%. The overall EQI (OR = 1.96, 95% CI [1.34, 2.86]) and the air quality index (OR = 5.99, 95% CI [3.20, 11.22]) scores predicted higher odds of being a "Low Benefit" county. CONCLUSIONS: Substantial inequities in the post-smoking elimination cancer rates were observed; air pollution appears to be a primary explanation for this. Cancer prevention in metropolitan counties with high levels of air pollution should prioritize pollution control at least as much as tobacco control.