Residential particulate matter and distance to roadways in relation to mammographic density: results from the Nurses' Health Studies. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: DuPre, Natalie; Hart, Jaime; Bertrand, Kimberly; Kraft, Peter; Laden, Francine; Tamimi, Rulla
• Is Part Of: Breast cancer research. Volume 19:Issue 1(2017)
• Page Start: 1
• Page End: 10
• Publication Date: 2017-12
• Subjects: Air pollution -- Particulate matter -- Mammographic density -- Epidemiology; Breast -- Cancer -- Periodicals; 616.99449
• DOI: 10.1186/s13058-017-0915-5
• Languages: English
• ISSNs: 1465-542X

Abstract

Abstract Background High mammographic density is a strong, well-established breast cancer risk factor. Three studies conducted in various smaller geographic settings reported inconsistent findings between air pollution and mammographic density. We assessed whether particulate matter (PM) exposures (PM2.5, PM2.5–10, and PM10 ) and distance to roadways were associated with mammographic density among women residing across the United States. Methods The Nurses' Health Studies are prospective cohorts for whom a subset has screening mammograms from the 1990s (interquartile range 1990–1999). PM was estimated using spatio-temporal models linked to residential addresses. Among 3258 women (average age at mammogram 52.7 years), we performed multivariable linear regression to assess associations between square-root-transformed mammographic density and PM within 1 and 3 years before the mammogram. For linear regression estimates of PM in relation to untransformed mammographic density outcomes, bootstrapped robust standard errors are used to calculate 95% confidence intervals (CIs). Analyses were stratified by menopausal status and region of residence. Results Recent PM and distance to roadways were not associated with mammographic density in premenopausal women (PM2.5 within 3 years before mammogram β = 0.05, 95% CI –0.16, 0.27; PM2.5–10 β = 0, 95%, CI –0.15, 0.16; PM10 β = 0.02, 95% CI –0.10, 0.13) and postmenopausal women (PM2.5 within 3 years before mammogram β = –0.05, 95% CI –0.27, 0.17; PM2.5–10 β = –0.01, 95% CI –0.16, 0.14; PM10 β = –0.02, 95% CI –0.13, 0.09). Largely null associations were observed within regions. Suggestive associations were observed among postmenopausal women in the Northeast (n = 745), where a 10-μg/m3 increase in PM2.5 within 3 years before the mammogram was associated with 3.4 percentage points higher percent mammographic density (95% CI –0.5, 7.3). Conclusions These findings do not support that recent PM or roadway exposures influence mammographic density. Although PM was largely not associated with mammographic density, we cannot rule out the role of PM during earlier exposure time windows and possible associations among northeastern postmenopausal women.