Long-term exposure to particulate air pollution and components in relation to breast cancer risk: A nested case-control study in the E3N-Generations cohort

BACKGROUND: components, as well as their combined effects, in the French E3N-Generation cohort. METHODS: ) of pollutants at residential addresses were estimated using the CHIMERE chemistry-transport model from 1990 to the index date. Exposure assessment included nine PM components: ammonium, sulfate, black carbon, polychlorobiphenyl-153 (PCB153), nitrate, benzo[a]pyrene, cadmium, dioxins, and Saharan dust. We evaluated single-pollutant effects using logistic regressions, and mixture effects using Quantile G-computation (QGC) and Bayesian Kernel Machine Regression (BKMR). RESULTS: Significant positive associations with breast cancer (Odds Ratios and confidence intervals for one SD increase (controls distribution) were found for ammonium (OR = 1.19; 95%CI: 1.05-1.35), sulfate (OR = 1.17; 95%CI: 1.02-1.35), PCB153 (OR = 1.17; 95%CI: 1.08-1.26), nitrate (OR = 1.16; 95%CI: 1.01-1.33), black carbon (OR = 1.12; 95%CI: 1.05-1.20), cadmium (OR = 1.05; 95%CI: 1.00-1.11). QGC showed a positive association with breast cancer for a one-quartile increase in joint exposure (OR = 1.22; 95% CI: 1.00-1.50) with cadmium and nitrate as major contributors. BKMR confirmed a significant positive association between the exposure to the mixture and breast cancer. CONCLUSION: The consistency between single-pollutant and mixture analyses supports a role for multiple PM components acting jointly on breast cancer risk. These results suggest that the chemical composition of PM, rather than individual pollutants alone, is a key determinant of breast cancer risk, highlighting the importance of considering pollutant composition in air pollution research.