Search

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. Keywords: Breast cancer, Endocrine disruptors, Dioxins, Geographic information system, Tumor receptor

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 (rs=0.42) and cadmium (rs=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.