Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
Creating outdoor air pollution exposome metrics for assessing breast and lung cancer risks in the United States.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Boyle Joseph, Jones Rena R, White Alexandra J, Zhang Junfeng Jim, Vieira Verónica M, Fuemmeler Bernard F
Аннотация
BACKGROUND: Air pollution (AP) is a known cause of lung cancer (LC); growing evidence links AP with breast cancer (BC) risk. Many epidemiological studies analyze PM2.5, though AP is a complex mixture of many pollutants. New metrics are necessary to fully represent the carcinogenic constituents of AP. Therefore, we aimed to develop cancer-specific metrics to determine where and what types of AP drive incident cancers.
METHODS: We combined databases of AP across the continental US in 2005-2020, including the Risk-Screening Environmental Indicators (RSEI) model and CACES land-use regression-estimated concentrations of criteria air pollutants (CAP). We joined AP concentrations at census tracts and employed meta-analytic cancer-specific risk estimates to weight the CAP and produce a set of combined metrics (AP for BC (APBC), AP for LC (APLC)) from numerous sources.
RESULTS: APBC and APLC exhibited positive skew, with certain tracts having values approximately an order of magnitude above the mean, and were typically highest in large cities and along transportation corridors. Relative to RSEI, APBC and APLC were larger in certain regions including Los Angeles and New York City. Both varied with respect to race, ethnicity, and housing and exhibited significant spatial clustering.
CONCLUSION: We developed novel AP metrics incorporating emissions from industrial facilities, along transportation corridors, and from power plants to characterize cancer-specific risks.
IMPACT: Future research will use these metrics that represent multiple simultaneous sources of AP to identify specific constituents of the AP exposome relevant for BC and LC, informing strategies to reduce their incidence and disparities.
METHODS: We combined databases of AP across the continental US in 2005-2020, including the Risk-Screening Environmental Indicators (RSEI) model and CACES land-use regression-estimated concentrations of criteria air pollutants (CAP). We joined AP concentrations at census tracts and employed meta-analytic cancer-specific risk estimates to weight the CAP and produce a set of combined metrics (AP for BC (APBC), AP for LC (APLC)) from numerous sources.
RESULTS: APBC and APLC exhibited positive skew, with certain tracts having values approximately an order of magnitude above the mean, and were typically highest in large cities and along transportation corridors. Relative to RSEI, APBC and APLC were larger in certain regions including Los Angeles and New York City. Both varied with respect to race, ethnicity, and housing and exhibited significant spatial clustering.
CONCLUSION: We developed novel AP metrics incorporating emissions from industrial facilities, along transportation corridors, and from power plants to characterize cancer-specific risks.
IMPACT: Future research will use these metrics that represent multiple simultaneous sources of AP to identify specific constituents of the AP exposome relevant for BC and LC, informing strategies to reduce their incidence and disparities.