Breast Cancer Risk in Association with Atmospheric Pollution Exposure: A Meta-Analysis of Effect Estimates Followed by a Health Impact Assessment

Abstract

Background: The epidemiological literature of associations between atmospheric pollutant exposure and breast cancer incidence has recently strongly evolved.

Objectives: We aimed to perform a) a meta-analysis of studies considering this relationship, correcting for publication bias and taking menopausal status and cancer hormone responsiveness into account; and b) for the pollutants most likely to affect breast cancer, an assessment of the corresponding number of attributable cases in France and of the related economic costs.

Methods: We conducted a literature review and random-effects meta-analyses of epidemiological studies examining the association of fine particulate matter with aerodynamic diameter less than or equal to $2.5\mu m$ (${\mathrm{PM}}_{2.5}$), particulate matter with aerodynamic diameter less than or equal to 10 μm (${\mathrm{PM}}_{10}$), and ${\mathrm{NO}}_2$ long-term exposure with breast cancer incidence; additional analyses were stratified on menopausal status and on tumor hormone responsiveness status. The resulting dose-response functions were combined with modeled atmospheric pollutant exposures in 2013 for France, cancer treatments costs, lost productivity, and years of life lost, to estimate the number of breast cancers attributable to atmospheric pollution and related economic costs in France.

Results: The review identified 32, 27, and 36 effect estimates for ${\mathrm{PM}}_{2.5}$, ${\mathrm{PM}}_{10}$, and ${\mathrm{NO}}_2$, respectively. The meta-analytical relative risk estimates of breast cancer corrected for publication bias were 1.006 [95% confidence interval (CI): 0.941, 1.076], 1.047 (95% CI: 0.984, 1.113), and 1.023 (95% CI: 1.005, 1.041), respectively. ${\mathrm{NO}}_2$ estimated effects appeared higher in premenopausal than in postmenopausal women and higher for hormone responsive positive ($\text{ER}+/\text{PR}+$) than negative ($\text{ER}-/\text{PR}-$) breast cancers. Assuming a causal effect of ${\mathrm{NO}}_2$, we estimated that 1,677 (95% CI: 374, 2,914) new breast cancer cases were attributable to ${\mathrm{NO}}_2$ annually in France, or 3.15% (95% CI: 0.70, 5.48) of the incident cases. The corresponding tangible and intangible costs were estimated to be €$825\text{million}$ (low, high: 570, 1,080) per year.

Conclusion: These findings suggest that decreasing long-term ${\mathrm{NO}}_2$ exposure or correlated air pollutant exposures could lower breast cancer risk. https://doi.org/10.1289/EHP8419.

Figure 1.

Random-effects meta-analytical relative risk of breast cancer incidence associated with a $10\text{-}{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$ increase in exposure to particulate matter with an aerodynamic diameter below $2.5\mathrm{\mu }\mathrm{m}$ (${\mathrm{PM}}_{2.5}$; $N_{cases}=\mathrm{111,758}$, $N_{participants}=\mathrm{2,959,079}$). Note: CEANS, Cardiovascular Effects of Air Pollution and Noise in Stockholm; CECILE, Breast Cancer: Epidemiological Study on the Environment in Côte d’Or and Ille-et-Vilaine; CNBSS, Canadian National Breast Screening Study; DCH: Diet, Cancer and Health; DNC, Danish Nurse Cohort; EPIC, European Prospective Investigation into Cancer and Nutrition; HUBRO, Oslo Health Study; MEC, Multiethnic Cohort; NHSII, Nurses’ Health Study II cohort; ONPHEC, Ontario Population Health and Environment Cohort; VHM&PP, Vorarlberg Health Monitoring and Prevention Program.

Figure 2.

Funnel plots of the study-specific estimates of breast cancer relative risk associated with a $10\text{-}{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$ increase in exposure to (A) particulate matter with an aerodynamic diameter below $2.5{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$ (${\mathrm{PM}}_{2.5}$), (B) particulate matter with an aerodynamic diameter below $10{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$ (${\mathrm{PM}}_{10}$), and (C) nitrogen dioxide (${\mathrm{NO}}_2$). Black solid dots: study-specific relative risk estimates identified by the literature review and included in the meta-analysis; red hollow dots: imputed relative risk estimates by trim-and-fill analysis necessary to observe a symmetrical funnel plot; vertical lines: meta-analytical relative risk estimates based on fixed-effects meta-analysis, before, in black solid line, and after, in red dotted line, trim-and-fill analysis (fixed-effects, that assume no between-study heterogeneity, are required to assess potential for publication bias).

Figure 3.

Random-effects meta-analytical relative risk of breast cancer incidence associated with a $10\text{-}{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$ increase in exposure to particulate matter with an aerodynamic diameter below $10\mathrm{\mu }\mathrm{m}$ (${\mathrm{PM}}_{10}$; $N_{cases}=\mathrm{23,765}$, $N_{participants}=\mathrm{1,326,524}$). Note: AOK PLUS, Statutory Health Insurance Database in Saxony; CEANS, Cardiovascular Effects of Air pollution and Noise in Stockholm; CECILE, Breast Cancer: Epidemiological Study on the Environment in Côte d’Or and Ille-et-Vilaine; DCH, Diet, Cancer and Health; DNC, Danish Nurse Cohort; EPIC, European Prospective Investigation into Cancer and Nutrition; HUBRO, Oslo Health Study; MEC, Multiethnic Cohort; NHSII, Nurses’ Health Study II cohort; VHM&PP, Vorarlberg Health Monitoring and Prevention Program.

Figure 4.

Random-effects meta-analytical relative risk of breast cancer incidence associated with a $10\text{-}{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$ increase in exposure to nitrogen dioxide (${\mathrm{NO}}_2$; $N_{cases}=\mathrm{121,189}$, $N_{participants}=\mathrm{3,922,395}$). Breast cancer relative risk estimates from CNBSS, reported separately in premenopausal women (“CNBSS_pre”) and postmenopausal women (“CNBSS_post”). Note: AOK PLUS, Statutory Health Insurance Database in Saxony; CCSPBCM1, Case-control Study for Postmenopausal Breast Cancer in Montreal 1; CCSPBCM2, Case–control Study for Postmenopausal Breast Cancer in Montreal 2; CEANS, Cardiovascular Effects of Air pollution and Noise in Stockholm; CECILE, Breast Cancer: Epidemiological Study on the Environment in Côte d’Or and Ille-et-Vilaine; CNBSS, Canadian National Breast Screening Study; DCH, Diet, Cancer and Health; DNC, Danish Nurse Cohort; EPIC, European Prospective Investigation into Cancer and Nutrition; HUBRO, Oslo Health Study; MEC, Multiethnic Cohort; NECSS, National Enhanced Cancer Surveillance System; ONPHEC, Ontario Population Health and Environment Cohort; VHM&PP, Vorarlberg Health Monitoring and Prevention Program.

Figure 5.

Annual average concentration levels of (A) particulate matter with an aerodynamic diameter below $2.5{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$ (${\mathrm{PM}}_{2.5}$), (B) particulate matter with an aerodynamic diameter below $10{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$ (${\mathrm{PM}}_{10}$), and (C) nitrogen dioxide (${\mathrm{NO}}_2$), in France, in 2013. Data at the $1{\text{-km}}^2$ spatial resolution, from the national air pollution model developed by the French National Institute for Industrial Environment and Risks (Ineris) (Benmerad et al. 2017a).