Abstract
Background:Particulate matter (PM) is a complex mixture. Geographic variations in PM may explain the lack of consistent associations with breast cancer.Objective:We aimed to evaluate the relationship between air pollution, PM components, and breast cancer risk in a United States-wide prospective cohort.Methods:We estimated annual average ambient residential levels of particulate matter and in aerodynamic diameter ( and , respectively) and nitrogen dioxide () using land-use regression for 47,433 Sister Study participants (breast cancer–free women with a sister with breast cancer) living in the contiguous United States. Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for risk associated with an interquartile range (IQR) increase in pollutants. Predictive k-means were used to assign participants to clusters derived from component profiles to evaluate the impact of heterogeneity in the mixture. For , we investigated effect measure modification by component cluster membership and by geographic region without regard to air pollution mixture.Results:During follow-up (), 2,225 invasive and 623 ductal carcinoma in situ (DCIS) cases were identified. and were associated with breast cancer overall [ (95% CI:0.99, 1.11) and 1.06 (95% CI:1.02, 1.11), respectively] and with DCIS but not with invasive cancer. Invasive breast cancer was associated with only in the Western United States [ (95% CI:1.02, 1.27)] and only in the Southern United States [ (95% CI:1.01, 1.33)]. was associated with a higher risk of invasive breast cancer among two of seven identified composition-based clusters. A higher risk was observed [ (95% CI: 0.97, 1.60)] in a California-based cluster characterized by low S and high Na and nitrate () fractions and for another Western United States cluster [ (95% CI: 0.90, 2.85)], characterized by high fractions of Si, Ca, K, and Al.Conclusion:Air pollution measures were related to both invasive breast cancer and DCIS within certain geographic regions and PM component clusters. https://doi.org/10.1289/EHP5131
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