Associations between PM2.5 and O3 exposures and new onset type 2 diabetes in regional and national samples in the United States

Tara P McAlexander; Victoria Ryan; Jalal Uddin; Rania Kanchi; Lorna Thorpe; Brian S Schwartz; April Carson; Deborah B Rolka; Samrachana Adhikari; Jonathan Pollak; Priscilla Lopez; Megan Smith; Melissa Meeker; Leslie A McClure

doi:10.1016/j.envres.2023.117248

Associations between PM_2.5 and O₃ exposures and new onset type 2 diabetes in regional and national samples in the United States

Environ Res. 2023 Dec 15;239(Pt 1):117248. doi: 10.1016/j.envres.2023.117248. Epub 2023 Oct 10.

Authors

Affiliations

¹ Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA. Electronic address: tpm58@drexel.edu.
² Department of Epidemiology and Biostatistics, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA.
³ Department of Epidemiology, The University of Alabama at Birmingham, Birmingham, AL, USA.
⁴ Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA.
⁵ Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
⁶ Department of Medicine, University of Mississippi Medical Center, Jackson, MS, 39213, USA.
⁷ Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA, USA.
⁸ Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

PMID: 37827369
DOI: 10.1016/j.envres.2023.117248

Abstract

Background: Exposure to particulate matter ≤2.5 μm in diameter (PM_2.5) and ozone (O₃) has been linked to numerous harmful health outcomes. While epidemiologic evidence has suggested a positive association with type 2 diabetes (T2D), there is heterogeneity in findings. We evaluated exposures to PM_2.5 and O₃ across three large samples in the US using a harmonized approach for exposure assignment and covariate adjustment.

Methods: Data were obtained from the Veterans Administration Diabetes Risk (VADR) cohort (electronic health records [EHRs]), the Reasons for Geographic and Racial Disparities in Stroke (REGARDS) cohort (primary data collection), and the Geisinger health system (EHRs), and reflect the years 2003-2016 (REGARDS) and 2008-2016 (VADR and Geisinger). New onset T2D was ascertained using EHR information on medication orders, laboratory results, and T2D diagnoses (VADR and Geisinger) or report of T2D medication or diagnosis and/or elevated blood glucose levels (REGARDS). Exposure was assigned using pollutant annual averages from the Downscaler model. Models stratified by community type (higher density urban, lower density urban, suburban/small town, or rural census tracts) evaluated likelihood of new onset T2D in each study sample in single- and two-pollutant models of PM_2.5 and O₃.

Results: In two pollutant models, associations of PM_2.5, and new onset T2D were null in the REGARDS cohort except for in suburban/small town community types in models that also adjusted for NSEE, with an odds ratio (95% CI) of 1.51 (1.01, 2.25) per 5 μg/m³ of PM_2.5. Results in the Geisinger sample were null. VADR sample results evidenced nonlinear associations for both pollutants; the shape of the association was dependent on community type.

Conclusions: Associations between PM_2.5, O₃ and new onset T2D differed across three large study samples in the US. None of the results from any of the three study populations found strong and clear positive associations.

MeSH terms

Data Collection
Diabetes Mellitus, Type 2* / epidemiology
Environmental Pollutants*
Humans
Odds Ratio
Particulate Matter / toxicity
United States / epidemiology

Substances

Environmental Pollutants
Particulate Matter