Multiple xenoestrogen air pollutants and breast cancer risk: Statistical approaches to investigate combined exposures effect

Studies suggested that exposure to air pollutants, with endocrine disrupting (ED) properties, have a key role in breast cancer (BC) development. Although the population is exposed simultaneously to a mixture of multiple pollutants and ED pollutants may act via common biological mechanisms leading to synergic effects, epidemiological studies generally evaluate the effect of each pollutant separately. We aimed to assess the complex effect of exposure to a mixture of four xenoestrogen air pollutants (benzo-[a]-pyrene (BaP), cadmium, dioxin (2,3,7,8-Tétrachlorodibenzo-p-dioxin TCDD)), and polychlorinated biphenyl 153 (PCB153)) on the risk of BC, using three recent statistical methods, namely weighted quantile sum (WQS), quantile g-computation (QGC) and Bayesian kernel machine regression (BKMR). The study was conducted on 5222 cases and 5222 matched controls nested within the French prospective E3N cohort initiated in 1990. Annual average exposure estimates to the pollutants were assessed using a chemistry transport model, at the participants' residence address between 1990 and 2011. We found a positive association between the WQS index of the joint effect and the risk of overall BC (adjusted odds ratio (OR) = 1.10, 95% confidence intervals (CI): 1.03-1.19). Similar results were found for QGC (OR = 1.11, 95%CI: 1.03-1.19). Despite the association did not reach statistical significance in the BKMR model, we observed an increasing trend between the joint effect of the four pollutants and the risk of BC, when fixing other chemicals at their median concentrations. BaP, cadmium and PCB153 also showed positive trends in the multi-pollutant mixture, while dioxin showed a modest inverse trend. Despite we found a clear evidence of a positive association between the joint exposure to pollutants and BC risk only from WQS and QGC regression, we observed a similar suggestive trend using BKMR. This study makes a major contribution to the understanding of the joint effects of air pollution.

Survival of bronchopulmonary cancers according to radon exposure

Introduction

Residential exposure is estimated to be responsible for nearly 10% of lung cancers in 2015 in France, making it the second leading cause, after tobacco. The Auvergne-Rhône-Alpes region, in the southwest of France, is particularly affected by this exposure as 30% of the population lives in areas with medium or high radon potential. This study aimed to investigate the impact of radon exposure on the survival of lung cancer patients.

Methods

In this single-center study, patients with a histologically confirmed diagnosis of lung cancer, and newly managed, were prospectively included between 2014 and 2020. Univariate and multivariate survival analyses were carried out using a non-proportional risk survival model to consider variations in risk over time.

Results

A total of 1,477 patients were included in the analysis. In the multivariate analysis and after adjustment for covariates, radon exposure was not statistically associated with survival of bronchopulmonary cancers (HR = 0.82 [0.54-1.23], HR = 0.92 [0.72-1.18], HR = 0.95 [0.76-1.19] at 1, 3, and 5 years, respectively, for patients residing in category 2 municipalities; HR = 0.87 [0.66-1.16], HR = 0.92 [0.76-1.10], and HR = 0.89 [0.75-1.06] at 1, 3, and 5 years, respectively, for patients residing in category 3 municipalities).

Discussion

Although radon exposure is known to increase the risk of lung cancer, in the present study, no significant association was found between radon exposure and survival of bronchopulmonary cancers.

Association between cumulative airborne dioxin exposure and non-Hodgkin's lymphoma risk in a nested case-control study within the French E3N cohort

BACKGROUND

Dioxins are a family of chemical molecules that are chlorinated, lipophilic, and bio-accumulative. They are thought to enhance the risk of non-lymphoma Hodgkin's due to their known carcinogenic properties (NHL). This is the first epidemiological research to investigate the relationship between repeated emissions of airborne dioxin exposure and the risk of NHL.

OBJECTIVE

A case-control study nested within the French E3N cohort of 98,995 women covered by the health insurance provider of the national education system evaluated the association between cumulative airborne dioxin exposure and NHL risk.

MATERIALS AND METHODS

NHL incident cases (368) and controls (368) were compared. Over the duration of the study, participants' residential histories and the locations of industrial sites were gathered (1990-2008). Using a Geographic Information System (GIS)-based exposure index, the cumulative exposure to airborne dioxins for each participant was calculated at the individual address level. The odds ratios (OR) and 95 % confidence intervals (CI) were calculated using multivariable conditional logistic regression models (CI).

RESULTS

The log-transformed continuous cumulative dioxin exposure index was substantially correlated with the risk of NHL (OR1.2 (95 % CI 1.0,1.4) for an increase in log-TEQ/m2 of 4.4, or one standard deviation). The combined chronic lymphocytic leukemia (CLL) and small lymphocytic lymphoma (SLL) subtype was significantly associated with NHL histological subtypes (OR 1.6 (95 % CI 1.1,2.3)).

CONCLUSION

The findings of this study demonstrate a significant positive correlation between cumulative airborne dioxin exposure and the risk of NHL in women, and more specifically, a significant positive association for the CLL & SLL subtype. These results help to support the attempts to reduce the exposure to dioxins in the air.

Traffic-Related Air Pollution and Breast Cancer Risk: A Systematic Review and Meta-Analysis of Observational Studies

Current evidence of an association of breast cancer (BC) risk with air pollution exposure, in particular from traffic exhaust, remains inconclusive, and the exposure assessment methodologies are heterogeneous. This study aimed to conduct a systematic review and meta-analysis on the association between traffic-related air pollution (TRAP) and BC incidence (PROSPERO CRD42021286774). We systematically reviewed observational studies assessing exposure to TRAP and BC risk published until June 2022, available on Medline/PubMed and Web of Science databases. Studies using models for assessing exposure to traffic-related air pollutants or using exposure proxies (including traffic density, distance to road, etc.) were eligible for inclusion. A random-effects meta-analysis of studies investigating the association between NO₂/NO_x exposure and BC risk was conducted. Overall, 21 studies meeting the inclusion criteria were included (seven case-control, one nested case-control, 13 cohort studies); 13 studies (five case-control, eight cohort) provided data for inclusion in the meta-analyses. Individual studies provided little evidence of an association between TRAP and BC risk; exposure assessment methods and time periods of traffic emissions were different. The meta-estimate on NO₂ exposure indicated a positive association (pooled relative risk per 10 µg/m³ of NO₂: 1.015; 95% confidence interval, CI: 1.003; 1.028). No association between NO_x exposure and BC was found (three studies). Although there was limited evidence of an association for TRAP estimated with proxies, the meta-analysis showed a significant association between NO₂ exposure, a common TRAP pollutant marker, and BC risk, yet with a small effect size. Our findings provide additional support for air pollution carcinogenicity.

Long-term exposure to nitrogen dioxide air pollution and breast cancer risk: A nested case-control within the French E3N cohort study

Nitrogen dioxide (NO₂) is an important air pollutant due to its adverse effects on human health. Yet, current evidence on the association between NO₂ and the risk of breast cancer lacks consistency. In this study, we investigated the association between long-term exposure to NO₂ and breast cancer risk in the French E3N cohort study. Association of breast cancer risk with NO₂ exposure was assessed in a nested case-control study within the French E3N cohort including 5222 breast cancer cases identified over the 1990-2011 follow-up period and 5222 matched controls. Annual mean concentrations of NO₂ at participants' residential addresses for each year from recruitment 1990 through 2011, were estimated using a land use regression (LUR) model. Multivariable conditional logistic regression models were used to compute odds ratios (ORs) and their 95% confidence intervals (CIs). Additional analyses were performed using NO₂ concentrations estimated by CHIMERE, a chemistry transport model. Overall, the mean NO₂ exposure was associated with an increased risk of breast cancer. In all women, for each interquartile range (IQR) increase in NO₂ levels (LUR: 17.8 μg/m³), the OR of the model adjusted for confounders was 1.09 (95% CI: 1.01-1.18). The corresponding OR in the fully adjusted model (additionally adjusted for established breast cancer risk factors) was 1.07 (95% CI: 0.98-1.15). By menopausal status, results for postmenopausal women were comparable to those for all women, while no association was observed among premenopausal women. By hormone receptor status, the OR of estrogen receptor positive breast cancer = 1.07 (95% CI: 0.97-1.19) in the fully adjusted model. Additional analyses using the CHIMERE model showed slight differences in ORs estimates. The results of this study indicate an increased risk of breast cancer associated with long-term exposure to NO₂ air pollution. Observing comparable effects of NO₂ exposure estimated by two different models, reinforces these findings.

The impact of left truncation of exposure in environmental case-control studies: evidence from breast cancer risk associated with airborne dioxin

In epidemiology, left-truncated data may bias exposure effect estimates. We analyzed the bias induced by left truncation in estimating breast cancer risk associated with exposure to airborne dioxins. Simulations were run with exposure estimates from a Geographic Information System (GIS)-based metric and considered two hypotheses for historical exposure, three scenarios for intra-individual correlation of annual exposures, and three exposure-effect models. For each correlation/model combination, 500 nested matched case-control studies were simulated and data fitted using a conditional logistic regression model. Bias magnitude was assessed by estimated odds-ratios (ORs) versus theoretical relative risks (TRRs) comparisons. With strong intra-individual correlation and continuous exposure, left truncation overestimated the Beta parameter associated with cumulative dioxin exposure. Versus a theoretical Beta of 4.17, the estimated mean Beta (5%; 95%) was 73.2 (67.7; 78.8) with left-truncated exposure and 4.37 (4.05; 4.66) with lifetime exposure. With exposure categorized in quintiles, the TRR was 2.0, the estimated OR_{Q5 vs. Q1} 2.19 (2.04; 2.33) with truncated exposure versus 2.17 (2.02; 2.32) with lifetime exposure. However, the difference in exposure between Q5 and Q1 was 18× smaller with truncated data, indicating an important overestimation of the dose effect. No intra-individual correlation resulted in effect dilution and statistical power loss. Left truncation induced substantial bias in estimating breast cancer risk associated with exposure with continuous and categorical models. With strong intra-individual exposure correlation, both models detected associations, but categorical models provided better estimates of effect trends. This calls for careful consideration of left truncation-induced bias in interpreting environmental epidemiological data.

Long-term atmospheric exposure to PCB153 and breast cancer risk in a case-control study nested in the French E3N cohort from 1990 to 2011

BACKGROUND

Although the genetic and hormonal risk factors of breast cancer are well identified, they cannot fully explain the occurrence of all cases. Epidemiological and experimental studies have suggested that exposure to environmental pollutants, especially those with potential estrogenic properties, as polychlorinated biphenyls (PCBs) may have a role in breast cancer development. Being the most abundantly detected in human tissues and in the environment, congener 153 (PCB153) is widely used in epidemiological studies as indicator for total PCBs exposure.

OBJECTIVES

We aimed to estimate the association between cumulative atmospheric exposure to PCB153 and breast cancer risk.

METHODS

We conducted a case-control study of 5222 cases and 5222 matched controls nested within the French E3N cohort from 1990 to 2011. Annual atmospheric PCB153 concentrations were simulated with the deterministic chemistry-transport model (CHIMERE) and were assigned to women using their geocoded residential history. Their cumulative PCB153 exposure was calculated for each woman from their cohort inclusion to their index date. Breast cancer odds ratios (ORs) associated with cumulative PCB153 exposure and their 95% confidence intervals (95% CIs) were estimated using multivariate conditional logistic regression models.

RESULTS

Overall, our results showed a statistically significant linear increase in breast cancer risk related to cumulative atmospheric exposure to PCB153 as a continuous variable (adjusted OR = 1.19; 95% CI: 1.08-1.31, for an increment of one standard deviation among controls (55 pg/m³)). Among women who became postmenopausal during follow-up, the association remained statistically significant (adjusted OR = 1.23; 95% CI: 1.09-1.39). In analyses by hormone receptors status, the positive association remained significant only for ER-positive breast cancer (adjusted OR = 1.18; 95% CI: 1.05-1.33).

DISCUSSION

This study is the first to have estimated the impact of atmospheric exposure to PCB153 on breast cancer risk. Our results showed a statistically significant increase in breast cancer risk, which may be limited to ER-positive breast cancer. These results warrant confirmation in further independent studies but raise the possibility that exposure to PCB153 increase breast cancer risk.

Risk of breast cancer associated with long-term exposure to benzo[a]pyrene (BaP) air pollution: Evidence from the French E3N cohort study

BACKGROUND

Benzo[a]pyrene (BaP) is an endocrine-disrupting pollutant formed during incomplete combustion of organic materials. It has been recognized as a reproductive and developmental toxicant, however epidemiological evidence of the long-term effect of ambient air BaP on breast cancer (BC) is limited. Thus we evaluated associations between ambient air BaP exposure and risk of BC, overall and according to menopausal status and molecular subtypes (estrogen receptor negative/positive (ER-/ER+) and progesterone receptor negative/positive (PR-/PR+)), stage and grade of differentiation of BC in the French E3N cohort study.

METHODS

Within a nested case-control study of 5222 incident BC cases and 5222 matched controls, annual BaP exposure was estimated using a chemistry-transport model (CHIMERE) and was assigned to the geocoded residential addresses of participants for each year during the 1990-2011 follow-up period. Multivariable conditional logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

Overall, cumulative airborne BaP exposure was significantly associated with the overall risk of BC, for each 1 interquartile range (IQR) increase in the concentration levels of BaP (1.42 ng/m³), the OR = 1.15 (95% CI: 1.04-1.27). However, by menopausal status, the significant positive association remained only in women who underwent menopausal transition (i.e. premenopausal women at inclusion who became postmenopausal at diagnosis), OR per 1 IQR = 1.20 (95% CI: 1.03-1.40). By hormone receptor status, positive associations were observed for ER+, PR + and ER + PR + BC, with ORs = 1.17 (95% CI: 1.04-1.32), 1.16 (95% CI: 1.01-1.33), and 1.17 (95% CI: 1.01-1.36) per 1 IQR, respectively. There was also a borderline positive association between BaP and grade 3 BC (OR per 1 IQR = 1.15 (95% CI: 0.99-1.34).

CONCLUSIONS

We provide evidence of increased risk of BC associated with cumulative BaP exposure, which varied according to menopausal status, hormone receptor status, and grade of differentiation of BC. Our results add further epidemiological evidence to the previous experimental studies suggesting the adverse effects of BaP.

Chronic Low-Dose Exposure to Xenoestrogen Ambient Air Pollutants and Breast Cancer Risk: XENAIR Protocol for a Case-Control Study Nested Within the French E3N Cohort

Background

Breast cancer is the most frequent cancer in women in industrialized countries. Lifestyle and environmental factors, particularly endocrine-disrupting pollutants, have been suggested to play a role in breast cancer risk. Current epidemiological studies, although not fully consistent, suggest a positive association of breast cancer risk with exposure to several International Agency for Research on Cancer Group 1 air-pollutant carcinogens, such as particulate matter, polychlorinated biphenyls (PCB), dioxins, Benzo[a]pyrene (BaP), and cadmium. However, epidemiological studies remain scarce and inconsistent. It has been proposed that the menopausal status could modify the relationship between pollutants and breast cancer and that the association varies with hormone receptor status.

Objective

The XENAIR project will investigate the association of breast cancer risk (overall and by hormone receptor status) with chronic exposure to selected air pollutants, including particulate matter, nitrogen dioxide (NO2), ozone (O3), BaP, dioxins, PCB-153, and cadmium.

Methods

Our research is based on a case-control study nested within the French national E3N cohort of 5222 invasive breast cancer cases identified during follow-up from 1990 to 2011, and 5222 matched controls. A questionnaire was sent to all participants to collect their lifetime residential addresses and information on indoor pollution. We will assess these exposures using complementary models of land-use regression, atmospheric dispersion, and regional chemistry-transport (CHIMERE) models, via a Geographic Information System. Associations with breast cancer risk will be modeled using conditional logistic regression models. We will also study the impact of exposure on DNA methylation and interactions with genetic polymorphisms. Appropriate statistical methods, including Bayesian modeling, principal component analysis, and cluster analysis, will be used to assess the impact of multipollutant exposure. The fraction of breast cancer cases attributable to air pollution will be estimated.

Results

The XENAIR project will contribute to current knowledge on the health effects of air pollution and identify and understand environmental modifiable risk factors related to breast cancer risk.

Conclusions

The results will provide relevant evidence to governments and policy-makers to improve effective public health prevention strategies on air pollution. The XENAIR dataset can be used in future efforts to study the effects of exposure to air pollution associated with other chronic conditions.

International Registered Report Identifier (IRRID)

DERR1-10.2196/15167

Chronic long-term exposure to cadmium air pollution and breast cancer risk in the French E3N cohort

Cadmium, due to its estrogen-like activity, has been suspected to increase the risk of breast cancer; however, epidemiological studies have reported inconsistent findings. We conducted a case-control study (4,059 cases and 4,059 matched controls) nested within the E3N French cohort study to estimate the risk of breast cancer associated with long-term exposure to airborne cadmium pollution, and its effect according to molecular subtype of breast cancer (estrogen receptor negative/positive [ER-/ER+] and progesterone receptor negative/positive [PR-/PR+]). Atmospheric exposure to cadmium was assessed using a Geographic Information System-based metric, which included subject's residence-to-cadmium source distance, wind direction, exposure duration and stack height. Adjusted odds ratios (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression. Overall, there was no significant association between cumulative dose of airborne cadmium exposure and the risk of overall, premenopausal and postmenopausal breast cancer. However, by ER and PR status, inverse associations were observed for ER- (ORQ5 vs. Q1  = 0.63; 95% CI: 0.41-0.95, ptrend  = 0.043) and for ER-/PR- breast tumors (ORQ4 vs. Q1  = 0.62; 95% CI: 0.40-0.95, ORQ5 vs. Q1  = 0.68; 95% CI: 0.42-1.07, ptrend  = 0.088). Our study provides no evidence of an association between exposure to cadmium and risk of breast cancer overall but suggests that cadmium might be related to a decreased risk of ER- and ER-/PR- breast tumors. These observations and other possible effects linked to hormone receptor status warrant further investigations.

Long-term airborne dioxin exposure and breast cancer risk in a case-control study nested within the French E3N prospective cohort

BACKGROUND

Dioxins, Group 1 carcinogens, are emitted by industrial chlorinated combustion processes and suspected to increase breast cancer risk through receptor-mediated pathways.

OBJECTIVES

We estimated breast cancer risk associated with airborne dioxin exposure, using geographic information system (GIS) methods and historical exposure data.

METHODS

We designed a case-control study (429 breast cancer cases diagnosed between 1990 and 2008, matched to 716 controls) nested within the E3N (Etude Epidémiologique auprès de femmes de la Mutuelle Générale de l'Education Nationale) cohort. Airborne dioxin exposure was assessed using a GIS-based metric including participants' residential history, technical characteristics of 222 dioxin sources, residential proximity to dioxin sources, exposure duration and wind direction. Odds ratios (OR) and 95% confidence intervals (CI) associated with quintiles of cumulative exposure were estimated using multivariate logistic regression models.

RESULTS

We observed no increased risk of breast cancer for higher dioxin exposure levels overall and according to hormone-receptor status. We however observed a statistically significant OR for Q2 versus Q1 overall (1.612, 95% CI: 1.042-2.493) and for estrogen-receptor (ER) positive breast cancer (1.843, 95% CI: 1.033-3.292).

CONCLUSIONS

Overall, as well as according to hormone-receptor status, no increased risk was observed for higher airborne dioxin exposure. The increased risk for low exposure levels might be compatible with non-monotonic dose-response relationship. Confirmation of our findings is required. Our GIS-based metric may provide an alternative in absence of ambient dioxin monitoring and may allow assessing exposure to other pollutants.

Development and performance evaluation of a GIS-based metric to assess exposure to airborne pollutant emissions from industrial sources

BACKGROUND

Dioxins are environmental and persistent organic carcinogens with endocrine disrupting properties. A positive association with several cancers, including risk of breast cancer has been suggested.

OBJECTIVES

This study aimed to develop and assess performances of an exposure metric based on a Geographic Information System (GIS) through comparison with a validated dispersion model to estimate historical industrial dioxin exposure for its use in a case-control study nested within a prospective cohort.

METHODS

Industrial dioxin sources were inventoried over the whole French territory (n > 2500) and annual average releases were estimated between 1990 and 2008. In three selected areas (rural, urban and urban-costal), dioxin dispersion was modelled using SIRANE, an urban Gaussian model and exposure of the French E3N cohort participants was estimated. The GIS-based metric was developed, calibrated and compared to SIRANE results using a set of parameters (local meteorological data, characteristics of industrial sources, e.g. emission intensity and stack height), by calculating weighted kappa statistics (wκ) and coefficient of determination (R2). Furthermore, as performance evaluation, the final GIS-based metric was tested to assess atmospheric exposure to cadmium.

RESULTS

The concordance between the GIS-based metric and the dispersion model for dioxin exposure estimate was strong (wκ median = 0.78 (1st quintile = 0.72, 3rd quintile =0.82) and R2 median = 0.82 (1st quintile = 0.71, 3rd quintile = 0.87)). We observed similar performance for cadmium.

CONCLUSIONS

Our study demonstrated the ability of the GIS-based metric to reliably characterize long-term environmental dioxin and cadmium exposures as well as the pertinence of using dispersion modelling to construct and calibrate the GIS-based metric.

Assessment of long-term exposure to airborne dioxin and cadmium concentrations in the Lyon metropolitan area (France)

Identifying the long-term effects of airborne pollutants requires the computation of the spatial and temporal variability of their concentration in air to estimate the exposure of the population. To estimate exposure levels of individuals in a breast cancer case control study nested in a national prospective cohort, we determine here the differential impact of a variety of cadmium and dioxin sources on urban air over a large urban area and over a period of almost 20years. To that end, we couple an emission model, to estimate dioxin and cadmium atmospheric annual releases, with an urban dispersion model in order to compute pollutant concentration fields at a fine temporal (1h) and spatial (25m) resolution. The reliability of the modelling chain is compared to two types of measurement: i) localized industrial emissions and ii) dioxin and cadmium air monitoring data (from 2007 to 2008), collected at a fixed station, placed in the city centre, as well as at three mobile short-term dioxin monitoring stations, located in the suburbs (the latter providing dioxin data, only). Comparisons between measured and estimated emissions show non-negligible difference, with a correlations for dioxin (r_s=0.42) and cadmium (r_s=0.41). Despite this, mean values between estimated emissions and emission measurements are close to each other, in particular for cadmium. Weekly average modelled concentrations show an overall good agreement with weekly average measured concentrations in spring and summer but are generally lower than monitored data in winter due to peak concentrations from diffuse sources representing an important proportion of emissions in 2007/2008. The model provides better results for cadmium than for dioxin. Despite the relevant errors in the model predictions, the model meets the validation criteria, defined by Chang and Hanna for an urban dispersion model. Simulation scenarios of air pollutant concentrations, reconstructed over the last 20years, show the effects of the variability of the pollutant sources over time with decreasing levels of dioxin and cadmium concentrations in air. This is primarily due to the reduction in localized industrial releases, which results in a general trend of homogenization of the exposure of the population. The model further allows us to dissociate the contribution of different types of pollutant sources on the population exposure. The impact on local concentrations due to industrial emissions, which were originally responsible for the major impact on air quality, is shown to drop over the years by 99% and 92% for dioxin and cadmium, respectively. Today, the major contributions are due to diffuse miscellaneous sources in the case of dioxin and to traffic-related emissions for cadmium. Average modelled concentrations at the study subjects' residential locations range from 10.2 to 82.1fg-TEQ/m³ for dioxin and 0.10 to 1.6ng/m³ for cadmium and are comparable with data from the literature. The study results will be essential to increase the accuracy of the assessment of long-term airborne dioxin and cadmium exposure and improve the results of epidemiological studies.