Smoking drives lung cancer deaths, but race predicts breast/prostate mortality. New study reveals distinct community factors for each cancer type's outcomes.
Smoking rates emerged as the strongest predictor of lung and colorectal cancer mortality across US counties, while the proportion of non-Hispanic Black residents showed the highest association with breast and prostate cancer deaths, according to a cross-sectional analysis published in JAMA Network Open.1
The study reveals that no single community factor consistently predicts outcomes across all cancer types, suggesting the need for tailored interventions based on specific cancer profiles, lead author Elizabeth Y Rula, PhD, executive director, Harvey L. Neiman Health Policy Institute, in Reston, VA, and colleagues wrote.

The research examined 24 community measures, spanning health behaviors, socioeconomic conditions, environmental exposures, and healthcare access, to determine their relative importance in explaining county-level variations in screening, prevalence, and mortality for breast, colorectal, lung, and prostate cancers, the 4 cancer types that account for half of all new cancer diagnoses in the United States.1
Cancer imposes substantial human and economic costs on the US healthcare system. Approximately 40.5% of Americans will receive a cancer diagnosis during their lifetime, and the disease claims over 600,000 lives annually.2 By 2030, cancer-related healthcare costs could reach $246 billion, 34% higher than 2015 levels, with Medicare and Medicaid bearing 43% of this burden.3
The County Health Rankings model, an evidence-based model for how community characteristics impact health, suggests that 80% to 90% of health outcomes stem from factors outside medical care, including socioeconomic status (40-50%), health behaviors and lifestyle (30-40%), and environmental factors (5-10%).4,5 While previous research has established associations between individual community factors and health outcomes, this study sought to quantify their relative importance for specific cancer types using random forest algorithms, which can capture complex, nonlinear relationships that traditional regression models might miss, investigators explained.
The analysis of a nationally representative 5% sample of Medicare fee-for-service beneficiaries (87% aged 65 or older) revealed distinct patterns for each cancer outcome.
For breast cancer, the share of Hispanic residents was most strongly linked to screening rates, while lack of insurance and the proportion of non-Hispanic Black residents were most important for prevalence and mortality, respectively. Lung cancer outcomes were most shaped by environmental and behavioral factors—air pollution and access to primary care influenced screening, limited food access and uninsured rates affected prevalence, and smoking overwhelmingly drove mortality. For colorectal cancer, poverty, unemployment, and smoking emerged as leading factors across screening, prevalence, and mortality. For prostate cancer, environmental risks such as air toxics, indicators of poor physical health, and the proportion of non-Hispanic Black residents were key contributors.
Across cancer types, smoking consistently ranked among the top predictors of mortality, especially for lung and colorectal cancers, with geographic disparities most evident in the South. Socioeconomic hardship, such as poverty and severe housing problems, was also closely tied to lower screening rates and higher prevalence, particularly in the South and parts of the West and East Coast. Environmental exposures (air toxics, air pollution) and racial/ethnic composition (notably Hispanic and non-Hispanic Black population shares) added further context to disparities.
Although access to health care played a smaller overall role than socioeconomic or environmental factors, lack of insurance was notably important for cancer prevalence. Together, these findings underscore that improving cancer outcomes requires addressing the broader social, economic, and environmental conditions of communities—not just access to medical care.
The authors found that several factors demonstrated importance across multiple cancer types.
Among the study's limitations the researchers acknowledged that county-level analysis may mask substantial within-county variation, but smaller geographic units had insufficient sample sizes. The study design cannot establish causality, only associations. The Medicare-based sample limits generalizability to uninsured individuals and those under 65, which translates into missing screening recommendations that begin before Medicare eligibility.
The authors in their discussion reiterated that the importance of any of the individual measures studied varied with "no measure(s) consistently ranking at the top for all cancer types studied. Hence, individual measure importance must be considered uniquely for each outcome–cancer type combination," they stressed. "Our results are consistent with the literature demonstrating the importance of health behaviors and lifestyle, socioeconomic status, and environmental factors on population health"
Moreover, the findings support using both national factor rankings and geospatial mapping to guide cancer prevention efforts, an approach that will allow policymakers to prioritize high-impact factors nationally while addressing region-specific needs revealed through county-level patterns.
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