Introduction
Outdoor air pollution has been classified as a human carcinogen. (1) The evidence for breast cancer risk is accumulating although the specific constituents driving the association are not well explored. (2) Particulate matter can be a vector for radioactive isotopes, most of which arise from naturally occurring radon gas, which has been associated with a higher risk of breast (3) and lung cancer. (4) We evaluated the association between residential ambient particle radioactivity (PR), a radiometric characteristic of airborne particulate matter, and incident breast cancer.
Methods
The Sister Study cohort includes 50,884 U.S. women ages 35-74 who had a sister diagnosed with breast cancer but no breast cancer history themselves and who were enrolled between 2003-2009. Participants completed an enrollment questionnaire including educational attainment and self-reported race (American Indian/Alaska Native, Asian, Black/ African American, Native Hawaiian/Pacific Islander, and White, with the option to select multiple categories) and ethnicity (Hispanic/Latina, with the option to provide country/ region of origin). The cohort was approved by the institutional review board of the National Institutes of Health. We used data with follow-up through 23 September 2019 (data release 9.0).
We excluded women with a preenrollment breast cancer diagnosis or who were lost to follow-up (n = 363), and those outside the conterminous United States or who were missing covariates (n = 1,328) or PR data (n = 46), leaving 49,147 women for analysis. Incident breast cancer cases (invasive and ductal carcinoma in situ) were ascertained via self-report and confirmed with medical records.
Ambient PR exposure was estimated using a spatiotemporal ensemble model based on the U.S. Environmental Protection Agency's Radiation Network (RadNet), a nationwide background environmental radiation monitoring network with gross beta particle activity data collected between 2001 and 2017 from 129 monitors. (5) The multistage exposure model incorporates gross beta PR (PR-[beta]) measurements from RadNet and predictors of emissions (e.g., ground-surface uranium, barometric pressure, soil characteristics, anthropogenic sources of radionucleotides) and transport of radon and its progeny [e.g., monthly average fine particulate matter (PM) with aerodynamic diameter [less than or equal to]2.5 [micro]m ([PM.sub.2.5]), relative humidity, air mass sources]. In the first stage, nine base learning models were selected to characterize the complex associations between particulate radioactivity and its predictors. Stage two used a nonnegative geographically and temporally weighted regression method to aggregate the predictions from the nine base learning models. This ensemble model had good accuracy, with a spatial cross-validation [R.sup.2] = 0.56. Estimated monthly levels of PR-[beta] (mBq/[m.sup.3]), a measure of the particle-bound beta-emitting radionuclides, at a 32-km spatial resolution, were averaged to annual estimates at the geocoded enrollment address based on enrollment year.
As described previously, annual average PM with aerodynamic diameter [less than or equal to] 10 [micro]m ([PM.sub.10]), [PM.sub.2.5], and nitrogen dioxide (N[O.sub.2]) levels were estimated at participant residences using a validated regionalized kriging model with spatial...