Living with cancer in a changing climate: Climate risks in high cancer mortality (CaM) areas.

448 Background: Climate change will impact the frequency and severity of extreme weather events. Cancer survivors may suffer disproportionate effects on mental health, care disruptions, morbidity, and mortality, yet evaluations of climate risks and cancer survivorship are lacking. We examined future climate risks faced by communities with high levels of CaM overall and by socioeconomic attributes. Methods: Data came from the Climate Vulnerability Index, a county-level measure of climate change risks (45 variables) and a baseline vulnerability index (BVI; 139 variables). Variables scored from 0 (least vulnerable) to 100 (most vulnerable) were categorized as high (rank >50) or low (rank <50) and linked to county-level CaM data from the SEER cancer registry. We compared the top quartile of the US population in counties with the highest CaM rates (55% of counties) to other areas. Using a training/validation strategy (2:1 ratio) and best subset selection with K-fold cross-validation, we previously identified a risk model with 6 climate change risk factors (RFs): weather-related events (hurricane, tornado, precipitation exposure; 3 factors), increased ozone/CO2 levels (1 factor), increased climate-related costs (1 factor), and future economic/productivity losses (1 factor). We now examine whether the risk model applies to high CaM counties with high and low levels (median split) of poverty, individuals aged 65 or older, low income, minority populations, unemployment, and no high school education. Results: Overall, N=3,139 counties were examined. In high CaM counties, 63.7% had high exposure (>3 factors) to the 6 climate RFs, compared to 33.1% in the low CaM counties, a threefold increase in the odds (OR=3.20, 95% CI, 2.72-3.76, p<.0001). Overall, the BVI-adjusted model C-statistic was 0.80 (unadjusted, 0.73). The association of high CaM and high exposure to climate RFs was evident for counties with both high and low levels of socioeconomic variables (Table). Conclusions: This first-of-its-kind ecological association study found that residing in counties with high CaM was associated with future climate change risks, including extreme weather, air pollution, climate costs, and economic losses. These adverse risks will likely impact all high CaM counties, regardless of sociodemographic attributes. Future research is needed to identify the mechanisms linking climate events to worse cancer outcomes, including decreased treatment tolerability, quality, or access. Association of high county-level CaM and exposure to climate RFs. County Attribute Level Odds Ratio 95% CI* Poverty High 3.19 2.54-4.02 Low 3.45 2.79-4.27 Age 65+ High 2.75 2.34-3.38 Low 4.55 3.67-5.65 Low Income High 3.34 2.64-4.24 Low 3.12 2.51-3.86 Minority High 3.78 3.06-4.68 Low 3.34 2.71-4.11 Unemployed High 4.52 3.56-5.74 Low 3.06 2.49-3.77 No High School High 3.09 2.45-3.89 Low 2.93 2.37-3.63 *p<.0001 for all comparisons.