Air Pollution, Clustering of Particulate Matter Components, and Breast Cancer in the Sister Study: A U.S.-Wide Cohort.
Autor: | White, Alexandra J.1 Alexandra.white@nih.gov, Keller, Joshua P.2, Zhao, Shanshan3, Carroll, Rachel4, Kaufman, Joel D.5, Sandler, Dale P.1 |
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Předmět: |
*Air pollution
*Nitrogen oxides *Particulate matter Breast tumor diagnosis Breast tumor risk factors Breast cancer Confidence intervals Longitudinal method Population geography Research Research funding Risk assessment Mathematical variables Proportional hazards models Ductal carcinoma Data analysis software Descriptive statistics |
Zdroj: | Environmental Health Perspectives. Oct2019, Vol. 127 Issue 10, p107002-1-107002-9. 9p. |
Abstrakt: | Background: Particulate matter (PM) is a comp lex mixture. Geograp hic variations in PM may exp lain the lack of consistent associations with breast " color:blue;" >cancer. Objective: We aimed to evaluate the relationship between air p ollution, PM comp onents, and breast cancer risk in a United States-wide p rosp ective " color:blue;" >cohort. Methods: We estimated annual average ambient residential levels of p articulate matter <2.5 p m and <10 p m in aerodynamic diameter (PM2.5 and PM10, resp ectively) and nitrogen dioxide (NO2) using land-use regression for 47,433 Sister Study p articip ants (breast " color:blue;" >cancer-free women with a sister with breast cancer) living in the contiguous United States. Cox p rop ortional hazards regression was used to estimate hazard ratios (HRs) and 95% " color:blue;" >con- fidence intervals (Cis) for risk associated with an interquartile " color:blue;" >range (IQR) increase in p ollutants. Predictive £-means were used to assign p articip ants to clusters derived from " color:blue;" >PM2.5 comp onent p rofiles to evaluate the imp act of heterogeneity in the " color:blue;" >PM2.5 mixture. For " color:blue;" >PM2.5, we investigated effect measure modification by comp onent cluster membership and by geograp hic region without regard to air p ollution mixture. Results: During follow-up (mean = 8.4y), 2,225 invasive and 623 ductal carcinoma in situ (DCIS) cases were identified. PM2.5 and NO2 were associated with breast cancer " color:blue;" >over all " color:blue;" >[HR= " color:blue;" >1.05 (95% CI:0.99, 1.11) and 1.06 (95% " color:blue;" >CI: " color:blue;" >1.02, " color:blue;" >1.11), " color:blue;" >resp ectively] " color:blue;" >and with " color:blue;" >DCIS " color:blue;" >but " color:blue;" >not " color:blue;" >with " color:blue;" >invasive cancer. Invasive breast cancer was associated with " color:blue;" >PM2.5 only in the Western United States " color:blue;" >[HR " color:blue;" >=1.14 (95% " color:blue;" >CI: " color:blue;" >1.02,1.27)] and NO2 only in the Southern United States " color:blue;" >[HR " color:blue;" >=1.16 (95% " color:blue;" >CI: " color:blue;" >1.01, " color:blue;" >1.33)]. " color:blue;" >PM2.5 " color:blue;" >was " color:blue;" >associated " color:blue;" >with " color:blue;" >a " color:blue;" >higher " color:blue;" >risk " color:blue;" >of " color:blue;" >invasive " color:blue;" >breast " color:blue;" >cancer " color:blue;" >among " color:blue;" >two " color:blue;" >of " color:blue;" >seven " color:blue;" >identified comp osition- " color:blue;" >based clusters. A higher risk was observed " color:blue;" >[HR " color:blue;" >= " color:blue;" >1.25 " color:blue;" >(95% " color:blue;" >CI: " color:blue;" >0.97, " color:blue;" >1.60)] " color:blue;" >in " color:blue;" >a " color:blue;" >Ca lifornia-based " color:blue;" >cluster " color:blue;" >characterized " color:blue;" >by " color:blue;" >low " color:blue;" >S and " color:blue;" >high " color:blue;" >Na and nitrate " color:blue;" >(NO3" ) fractions and for another Western United States cluster " color:blue;" >[HR " color:blue;" >= " color:blue;" >1.60 (95% CI: " color:blue;" >0.90, 2.85)], characterized by high fractions of Si, Ca, K, and Al. Conclusion: Air p ollution measures were related to both invasive breast cancer and DCIS within certain geograp hic regions and PM comp onent " color:blue;" >clusters, http s://doi.org/10.1289/EHP5131 [ABSTRACT FROM AUTHOR] |
Databáze: | GreenFILE |
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