Lee, Seulbi, Karvonen-Gutierrez, Carrie, Mukherjee, Bhramar, Herman, William H., Harlow, Siobán D., and Park, Sung Kyun
Supplemental Digital Content is available in the text., Background: Environmental phenols have been suggested as diabetogens but evidence from prospective cohort studies is limited. We examined associations between urinary concentrations of phenols and parabens, assessed at two time-points, and incident diabetes in the Study of Women’s Health Across the Nation (SWAN). Methods: We examined 1,299 women, aged 45–56 years, who were diabetes-free at baseline of the SWAN Multi-Pollutant Study (MPS) (1999–2000) and were followed through January 2017. Urinary concentrations of bisphenol-A, bisphenol-F, triclosan, 2,4-dichlorophenol, 2,5-dichlorophenol, benzophenone-3, methyl-paraben, ethyl-paraben, propyl-paraben, and butyl-paraben were measured twice at MPS baseline and 3 years later (2002–2003), and the two average concentrations were used as exposure variables. Associations of incident diabetes with individual phenols and parabens were examined using Cox regression. We evaluated the overall joint effects using quantile-based g-computation. Results: Adjusted hazard ratios (HRs) for incident diabetes of the third tertile compared with the first tertile of urinary concentrations were 0.40 (95% confidence interval [CI] = 0.29, 0.56) for methyl-paraben; 0.42 (0.30, 0.58) for propyl-paraben; 0.53 (0.38, 0.75) for 2,5-diclrorophenol; and 0.55 (0.39, 0.80) for benzophenone-3. Nonlinear associations were found for bisphenol-A and 2,4-dichlorophenol (significant positive associations in the second tertile but no associations in the third tertile compared with the first tertile). No significant associations were observed for the other individual chemicals or the joint effect of mixtures. Conclusions: Our findings do not support diabetogenic effects of urinary parabens which were inversely associated with incident diabetes among mid-life women. Epidemiologic findings for biomarkers with short half-lives and high within-person variability need to be interpreted with caution.