Prevalence and predictors of colon and prostate cancer screening among volunteer firefighters: The United States Firefighter Cancer Assessment and Prevention Study.

BACKGROUND: Although firefighters have increased risk for colon and prostate cancer, limited information exists on screening practices for these cancers in volunteer firefighters who compose two-thirds of the US fire service. We estimated the prevalence of colon and prostate cancer screening among volunteer firefighters using eligibility criteria from 4 evidence-based screening recommendations and evaluated factors influencing screening. METHODS: We evaluated colon (n = 569) and prostate (n = 498) cancer screening prevalence in a sample of US volunteer firefighters using eligibility criteria from the US Preventive Services Taskforce (USPSTF), National Fire Protection Association, American Cancer Society, and National Comprehensive Cancer Network. We assessed associations with fire service experience, demographics, and cancer risk perception based on USPSTF guidelines. RESULTS: For those eligible based on USPSTF guidelines, colon and prostate cancer screening prevalence was 51.7% (95% CI: 45.7, 57.8) and 48.8% (95% CI: 40.0, 57.6), respectively. Higher odds of colon and prostate cancer screening were observed with older age and with some college education compared to those with less education. Fire service experience and cancer risk perception were not associated with screening practices. CONCLUSION: This is the first large study to assess colon and prostate cancer screening among US volunteer firefighters based on different screening guidelines. Our findings suggest gaps in cancer prevention efforts in the US volunteer fire service. Promoting cancer screening education and opportunities for volunteer firefighters by their fire departments, healthcare professionals, and public health practitioners, may help to address the gaps.

Prevalence and predictors of skin cancer screening among a sample of US volunteer firefighters.

BACKGROUND: Firefighters have a higher risk of melanoma incidence and mortality compared to the general population. In the United States (US), the National Fire Protection Association recommends all firefighters receive annual skin cancer screening through visual skin examination by a clinician. However, there is limited information on skin cancer screening practices among volunteer firefighters who comprise two-thirds of the US fire service. METHODS: This cross-sectional study of 552 US volunteer firefighters estimated the prevalence of skin cancer screening and evaluated associations with their fire service experience, demographics, sun protection practices, and cancer risk perception. RESULTS: The prevalence of receiving skin cancer screening among volunteer firefighters was 26.1% (95% confidence interval [CI]: 22.4, 29.8). The odds of being screened for skin cancer, compared to not being screened, were twice as high for firefighters who used sunscreen (odds ratio [OR]: 2.35, 95% CI: 1.48, 3.73) and who perceived their skin likely to burn with prolonged sun exposure (OR: 1.81, 95% CI: 1.10, 3.00). Older age, some college education, and family history of skin cancer were also positively associated with skin cancer screening. A positive exposure-response relationship was observed between more monthly firefighting calls and receiving screening. Cancer risk perception was not associated with screening. CONCLUSION: To our knowledge, this is the first large study to assess skin cancer screening among US volunteer firefighters. Our findings suggest gaps in skin cancer prevention efforts in the volunteer fire service. Additional assessment of skin cancer prevention practices within volunteer fire departments could help address these gaps.

Impact of Mobile Monitoring Network Design on Air Pollution Exposure Assessment Models.

Short-term mobile monitoring campaigns are increasingly used to assess long-term air pollution exposure in epidemiology. Little is known about how monitoring network design features, including the number of stops and sampling temporality, impacts exposure assessment models. We address this gap by leveraging an extensive mobile monitoring campaign conducted in the greater Seattle area over the course of a year during all days of the week and most hours. The campaign measured total particle number concentration (PNC; sheds light on ultrafine particulate (UFP) number concentration), black carbon (BC), nitrogen dioxide (NO2), fine particulate matter (PM2.5), and carbon dioxide (CO2). In Monte Carlo sampling of 7327 total stops (278 sites × 26 visits each), we restricted the number of sites and visits used to estimate annual averages. Predictions from the all-data campaign performed well, with cross-validated R2s of 0.51-0.77. We found similar model performances (85% of the all-data campaign R2) with ∼1000 to 3000 randomly selected stops for NO2, PNC, and BC, and ∼4000 to 5000 stops for PM2.5 and CO2. Campaigns with additional temporal restrictions (e.g., business hours, rush hours, weekdays, or fewer seasons) had reduced model performances and different spatial surfaces. Mobile monitoring campaigns wanting to assess long-term exposure should carefully consider their monitoring designs.

Potential Impacts of Different Occupational Outdoor Heat Exposure Thresholds among Washington State Crop and Construction Workers and Implications for Other Jurisdictions.

Occupational heat exposure is associated with substantial morbidity and mortality among outdoor workers. We sought to descriptively evaluate spatiotemporal variability in heat threshold exceedances and describe potential impacts of these exposures for crop and construction workers. We also present general considerations for approaching heat policy-relevant analyses. We analyzed county-level 2011-2020 monthly employment (Bureau of Labor Statistics Quarterly Census of Employment and Wages) and environmental exposure (Parameter-elevation Relationships on Independent Slopes Model (PRISM)) data for Washington State (WA), USA, crop (North American Industry Classification System (NAICS) 111 and 1151) and construction (NAICS 23) sectors. Days exceeding maximum daily temperature thresholds, averaged per county, were linked with employment estimates to generate employment days of exceedances. We found spatiotemporal variability in WA temperature threshold exceedances and crop and construction employment. Maximum temperature exceedances peaked in July and August and were most numerous in Central WA counties. Counties with high employment and/or high numbers of threshold exceedance days, led by Yakima and King Counties, experienced the greatest total employment days of exceedances. Crop employment contributed to the largest proportion of total state-wide employment days of exceedances with Central WA counties experiencing the greatest potential workforce burden of exposure. Considerations from this analysis can help inform decision-making regarding thresholds, timing of provisions for heat rules, and tailoring of best practices in different industries and areas.

Characterization of Annual Average Traffic-Related Air Pollution Concentrations in the Greater Seattle Area from a Year-Long Mobile Monitoring Campaign.

Growing evidence links traffic-related air pollution (TRAP) to adverse health effects. We designed an innovative and extensive mobile monitoring campaign to characterize TRAP exposure levels for the Adult Changes in Thought (ACT) study, a Seattle-based cohort. The campaign measured particle number concentration (PNC) to capture ultrafine particles (UFP), black carbon (BC), nitrogen dioxide (NO2), fine particulate matter (PM2.5), and carbon dioxide (CO2) at 309 roadside sites within a large, 1200 land km2 (463 mi2) area representative of the cohort. We collected about 29 two-minute measurements at each site during all seasons, days of the week, and most times of the day over a 1-year period. Validation showed good agreement between our BC, NO2, and PM2.5 measurements and monitoring agency sites (R2 = 0.68-0.73). Universal kriging-partial least squares models of annual average pollutant concentrations had cross-validated mean square error-based R2 (and root mean square error) values of 0.77 (1177 pt/cm3) for PNC, 0.60 (102 ng/m3) for BC, 0.77 (1.3 ppb) for NO2, 0.70 (0.3 µg/m3) for PM2.5, and 0.51 (4.2 ppm) for CO2. Overall, we found that the design of this extensive campaign captured the spatial pollutant variations well and these were explained by sensible land use features, including those related to traffic.