Long-Term Exposure to Environmental Mixtures and Risk of Type 2 Diabetes in Three U.S. Prospective Cohorts

Abstract Aims/hypothesis: To examine the risk of type 2 diabetes (T2D) associated with long-term simultaneous exposure to air pollution, noise, surrounding greenness, and neighborhood socioeconomic status (SES), in three U.S. adult prospective cohorts. Methods: We followed 235,101 health professionals from June 1992/1993 to T2D diagnosis, loss to follow-up, death, or May 2018/2019. Time-varying address-level exposures to modeled fine particles (PM2.5), nitrogen dioxide (NO2), nighttime noise, satellite-based greenness, and Census tract-level neighborhood SES were appended. We applied Cox proportional hazards models to assess the hazard ratios (HRs) and 95% confidence intervals (CIs) of incident T2D associated with environmental exposures, individually and collectively, adjusting for potential confounders. We used quantile g-computation to assess the joint association of the exposure mixture. Analyses were performed in individual cohorts and meta-analyzed using random-effects models. Results: We observed 22,029 incident T2D cases over 26 years of follow-up. In single-exposure models, T2D risk was (borderline) positively associated with PM2.5, NO2, and noise, and negatively associated with greenness and neighborhood SES. In multiexposure models, PM2.5 and NO2 associations attenuated and included unity, while greenness, noise, and neighborhood SES associations persisted: HRs (95% CIs) per interquartile range (IQR) increase were 1.05 (0.97–1.13), 0.99 (0.94–1.03), 0.96 (0.93–0.98), 1.04 (1.02–1.06), and 0.92 (0.88–0.97), respectively. The joint association derived from quantile g-computation for one IQR change across the mixture was 1.25 (1.15–1.35). Conclusions/interpretation: Simultaneous exposure to greater noise, lower greenness, and less advantaged neighborhoods was associated with increased T2D risk, whereas air pollution showed an inconsistent association.