Abstract
Background
Some but not all past studies reported associations between components of air pollution and breast cancer, namely fine particulate matter ≤ 2.5 μm (PM2.5) and nitrogen dioxide (NO2). It is yet unclear whether risks differ according to estrogen receptor (ER) and progesterone receptor (PR) status.
Methods
This analysis includes 47,591 women from the Sister Study cohort enrolled from August 2003-July 2009, in whom 1,749 invasive breast cancer cases arose from enrollment to January 2013. Using Cox proportional hazards and polytomous logistic regression, we estimated breast cancer risk associated with residential exposure to NO2, PM2.5, and PM10.
Results
While breast cancer risk overall was not associated with PM2.5 (Hazards ratio [HR] = 1.03; 95% CI: 0.96–1.11), PM10 (HR = 0.99; 95% CI: 0.98–1.00), or NO2 (HR = 1.02; 95% CI: 0.97–1.07), the association with NO2 differed according to ER/PR subtype (p = 0.04). For an interquartile range (IQR) difference of 5.8 parts per billion (ppb) in NO2, the relative risk (RR) of ER+/PR+ breast cancer was 1.10 (95% CI: 1.02–1.19), while there was no evidence of association with ER−/PR− (RR=0.92; 95% CI: 0.77–1.09; pinteraction=0.04).
Conclusions
Within the Sister Study cohort, we found no significant associations between air pollution and breast cancer risk overall. But we observed an increased risk of ER+/PR+ breast cancer associated with NO2.
Impact
Though these results suggest there is no substantial increased risk for breast cancer overall in relation to air pollution, NO2, a marker of traffic related air pollution, may differentially affect ER+/PR+ breast cancer.
Keywords: Air pollution, Breast cancer risk, Particulate matter, Nitrogen dioxide, Cancer survival
Introduction
Several studies suggest an association between breast cancer risk and exposure to ambient fine-particulate matter (PM2.5) and nitrogen dioxide (NO2), a marker of traffic-related air pollution (1–3). Most notably, a 2010 case-control study reported a 1.3-fold increased risk of breast cancer (95% CI of OR: 1.0–1.7) for every 5 ppb increase in NO2 assessed via a land-use regression spatial model (3). The California Teachers Study recently reported an increased risk for ER−/PR− breast cancer associated with endocrine disruptors present in ambient air, namely cadmium compounds and inorganic arsenic (4). However, to date, relatively few studies have investigated the link between air pollution and breast cancer subtypes. This analysis sought to investigate breast cancer risk in relation to primary components of air pollution, namely PM2.5, PM10, and NO2, and potential risk differences by breast cancer subtype.
Materials and Methods
The Sister Study, a cohort of 50,884 U.S. women between ages 35–74 whose sister had breast cancer (5), enrolled participants from 8/2003–7/2009, who were followed for a mean of 4.95 years. 2,089 breast cancer cases arose between enrollment and 1/2013, (of which 316 were in situ), with a mean time to breast cancer of 3.96 years. Air pollution exposure was not ascertained on 1,234 women (24 invasive and 6 in situ; 1,204 non-cases) predominantly because they lived outside the conterminous U.S., resulting in 1,749 invasive breast cancers and 47,591 non-cases for this analysis. Annual averages of air pollution concentration outside the residence were estimated at each participant’s home from a validated regionalized universal kriging model derived from regulatory monitors and a large suite of geographic covariates using previously described methods (6). For primary analyses, air pollution estimates were based on annual average concentrations at baseline home addresses, derived using monitoring data from 2006 (PM2.5 and NO2) and 2000 (PM10). The cross-validated R2 for PM2.5 NO2, and PM10 were 0.88, 0.85, and 0.53, respectively (6). HR and 95% CI were estimated using Cox proportional hazards models. Known breast cancer risk factors were considered for inclusion in the model if the factor was associated with both air pollution and breast cancer. Race, educational attainment, smoking status, and menopausal hormone therapy met these criteria. Results were unchanged when we adjusted for geography using splines. In subset analyses, (1) we examined the effect of air pollution separately for breast cancer subtypes, stratifying by ER/PR and stage, calculating RR and 95% CI using polytomous logistic regression; and (2) we examined residential air pollution concentrations derived from 1990’s estimates among those who had lived long-term at their current residence (i.e., excluding those who changed residences) in order to investigate associations of long-term air pollution with breast cancer.
Results
Breast cancer cases were more likely White, highly educated, and users of menopausal hormone therapy (Table 1). There was no association between invasive breast cancer overall and PM2.5, PM10, or NO2 (Table 2). However, the risk associated with NO2 differed when stratified by ER/PR (p = 0.04). NO2 was associated with a 1.10-fold increased risk of ER+/PR+ breast cancer (95% CI: 1.02–1.19 per IQR of 5.8 ppb) but not with ER−/PR− breast cancer (RR = 0.92; 95% CI: 0.77–1.09). We observed a borderline increased risk of breast cancer in situ in relation to NO2 (HR = 1.10; 95% CI: 0.99–1.24 per IQR of 5.8 ppb) (data not shown).
Table 1.
Characteristics of the study population
| Characteristic | Control subjects (N=47,591) | Case subjects (N=1,749)a | ||
|---|---|---|---|---|
|
| ||||
| mean | (SD) | mean | (SD) | |
| Age at enrollment | 55.1 | (9.0) | 56.9 | (8.9) |
| n | (%) | n | (%) | |
| Race/Ethnicity | ||||
| Non-Hispanic White | 40,750 | 83.5 | 1,528 | 86.4 |
| Non-Hispanic Black | 4,318 | 8.9 | 113 | 6.4 |
| Hispanic | 2,433 | 5.0 | 71 | 4.0 |
| Other | 1,236 | 2.5 | 55 | 3.2 |
| Unknown | 7 | 0.0 | 0 | 0.0 |
| Education | ||||
| Less than high school | 605 | 1.3 | 15 | 0.9 |
| Completed high school | 6,882 | 14.2 | 245 | 13.9 |
| Associate or technical degree | 16,473 | 33.9 | 545 | 30.8 |
| Bachelor’s degree | 13,058 | 26.9 | 490 | 27.7 |
| Graduate degree | 11,542 | 23.8 | 472 | 26.7 |
| Unknown | 11 | 0.0 | 1 | 0.0 |
| Body Mass Index | ||||
| <18.5 | 568 | 1.2 | 17 | 0.9 |
| 18.5–24.9 | 18,171 | 37.4 | 639 | 36.1 |
| 25.0–29.9 | 15,334 | 31.6 | 571 | 32.3 |
| 30.0–39.9 | 12,101 | 24.9 | 450 | 25.5 |
| ≥ 40.0 | 2,375 | 4.9 | 91 | 5.2 |
| Unknown | 17 | 0.0 | 0 | 0.0 |
| Smoking | ||||
| Never smoker | 26,183 | 53.9 | 920 | 52.0 |
| Former smoker | 18,251 | 37.6 | 716 | 40.5 |
| Current smoker | 4,070 | 8.4 | 131 | 7.4 |
| Unknown | 67 | 0.1 | 1.0 | 0.1 |
| Physical Activity (in Met-hours/week) | ||||
| 1st Quintile | 9,634 | 19.8 | 341 | 19.3 |
| 2nd Quintile | 9,627 | 19.8 | 360 | 20.4 |
| 3rd Quintile | 9,628 | 19.8 | 363 | 20.5 |
| 4th Quintile | 9,631 | 19.8 | 353 | 20.0 |
| 5th Quintile | 9,628 | 19.8 | 338 | 19.1 |
| Unknown | 423 | 0.9 | 13 | 0.7 |
| Hormone Replacement Therapy | ||||
| No, has never taken | 43,396 | 89.4 | 1,523 | 86.1 |
| Yes, is taking or took in the past | 4,962 | 10.2 | 238 | 13.5 |
| Unknown | 213 | 0.4 | 7 | 0.4 |
. excluding in situ breast cancer cases
Table 2.
The risk of invasive breast cancer associated with PM2.5, PM10, and NO2
| Air pollution | Control (N = 47,591) | Breast Cancer | Breast Cancer Subtype | p-valuee | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| All Cases (N = 1,749) | HRa,b,c | 95% CI | ER+/PR+ (n = 947) | RRb,c, d | 95% CI | ER−/PR− (n = 223) | RRb,c, d | 95% CI | |||||||
| Mean | SD | Mean | SD | Mean | SD | Mean | SD | ||||||||
| PM2.5 | 10.5 | 2.4 | 10.5 | 2.4 | 1.03 | 0.96–1.11 | 10.4 | 2.4 | 1.00 | 0.91–1.09 | 10.5 | 2.5 | 0.99 | 0.81–1.20 | 0.99 |
| PM10 | 22.2 | 5.8 | 22.2 | 6.0 | 0.99 | 0.98–1.00 | 22.2 | 6.1 | 1.02 | 0.96–1.09 | 21.9 | 5.4 | 0.96 | 0.83–1.10 | 0.69 |
| NO2 | 10.1 | 4.7 | 10.3 | 4.7 | 1.02 | 0.97–1.07 | 10.4 | 4.7 | 1.10 | 1.02–1.19 | 9.8 | 4.5 | 0.92 | 0.77–1.09 | 0.04 |
. Estimated using Cox proportional hazards.
. Units representing an increase in the IQR difference: PM2.5 = 3.6 μg/m3; PM10 = 5.8 μg/m3; NO2 = 5.8 parts per billion (ppb).
. Models adjusted for: age at diagnosis, race, educational attainment, smoking status, menopausal hormone therapy.
. Estimated using polytomous logistic regression.
. Test of interaction in the polytomous regression model.
Discussion
Our analysis did not suggest an association between air pollution and overall invasive breast cancer risk. Multiple studies (2, 3), but not all (4, 7), found that exposure to traffic-related air pollutants, particularly NO2, increased breast cancer risk. A potential explanation for differences among studies could be differing proportions of ER/PR subtypes, if as our data suggest, NO2 is only associated with ER+/PR+ breast cancer. NO2 probably serves as a marker for traffic-related pollution rather than a causal factor per se (3). As such, it may serve as a proxy for components of air pollution which affect estrogens, such as polycyclic aromatic hydrocarbons (PAH). PAHs have estrogenic properties, as shown by PAH binding to ER-β to induce transcriptional targets (8). Thus, there is biological plausibility for a differential role of air pollution by hormone receptor status. However, Liu et al reported that estrogen disruptors in ambient air were not associated with ER+/PR+, but rather with ER−/PR− breast cancer (their analysis did not report on NO2) (4).
This analysis using a prospective, large national sample which systematically evaluated air pollution using state-of-the-art spatial modeling is able to rule out a strong relationship between air pollution and breast cancer risk. One limitation is that air pollution exposure earlier in life could impact breast cancer risk; however, our analysis of long-term air pollution exposure showed results were unchanged. Replication of these results is needed before firm conclusions can be drawn regarding ER+/PR+ breast cancer risk in relation to traffic-related air pollution.
Acknowledgments
Financial Support: This work was funded in part by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01 ES 044005; PI: D.P. Sandler). This publication was also in part developed under STAR research assistance agreements (RD831697; PI: J.D. Kaufman; and RD83479601; PI: S. Vedal; Project Director: J.D. Kaufman) awarded by the U.S. EPA. It has not been formally reviewed by the EPA. The views expressed in this document are solely those of the authors and the EPA does not endorse any products or commercial services mentioned in this publication. Dr. Reding was supported by National Institute of Nursing Research career development award (R00 NR 012232; PI: K.W. Reding).
Footnotes
Conflict of Interest:
For co-author Dr. Joel D Kaufman
Entity: Health Effects Institute, Diesel Exhaust Epidemiology Panel
Relationship: Myself
Compensation: Compensated
Type: Minor ($10,000 or less).
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