Associations between long-term exposure to fine particulate matter and its constituents with lung cancer incidence: Evidence from a prospective cohort study in Beijing, China.

Association between long-term exposure to ambient fine particulate matter (PM) and lung cancer incidence is well-documented. However, the role of different PM constituents [black carbon (BC), ammonium (NH), nitrate (NO), organic matter (OM), and inorganic sulfate (SO)] remain unclear. The study aimed to specify the associations between PM constituents and lung cancer incidence. Based on a prospective cohort of 130,860 participants in Beijing, the present study utilized Cox model to explore the associations between PM constituents and lung cancer incidence. We further used mixed exposure models [weighted quantile sum (WQS) and quantile-based g-computation (Qgcomp)] and machine learning model [random forest model with SHapley Additive exPlanations (SHAP)] to specify the importance of each constituent. Results indicated that PM mass and its constituents were significantly associated with increased lung cancer incidence. The hazard ratios (HRs) and 95% confidence intervals (CIs) of 1-μg/m increase in the 5-year average concentrations were 1.01 (95% CI: 1.00, 1.02) for PM mass, 1.23 (95% CI: 1.06, 1.42) for BC, 1.15 (95% CI: 1.04, 1.27) for NH, 1.08 (95% CI: 1.02, 1.16) for NO, 1.04 (95% CI: 1.01, 1.06) for OM, and 1.08 (95% CI: 1.03, 1.15) for SO. Both the WQS and Qgcomp models assigned the two highest positive weights to BC and SO. SHAP analysis identified SO and BC as the first and third most important contributors, respectively. Our results indicated that PM mass and its constituents were significantly associated with lung cancer incidence, and BC and SO were the key constituents in these associations.