Work

Long-Term Exposure to Air Pollution and Incidence of Type 2 Diabetes in the Nurses’ Health Study and Nurses’ Health Study II

Year: 2025

Type: article

Study design: Observational Study

Abstract: BACKGROUND: ) and T2DM incidence in the Nurses' Health Study (NHS) and Nurses' Health Study II (NHSII) cohorts of US women. METHODS: exposure and self-reported, clinician-diagnosed T2DM from 1992-2019. We adjusted for time-varying lifestyle factors, reproductive hormonal factors, and individual and neighborhood socioeconomic status (SES). Results were meta-analyzed. We evaluated whether relationships persisted at levels below the current US EPA National Ambient Air Quality Standards (NAAQS). Lastly, we examined multiplicative and additive interactions by body mass index (BMI), smoking status, physical activity, neighborhood SES, and region. RESULTS: , were physically active, and resided in the Northeast. CONCLUSIONS: , persisting even at levels below the current EPA NAAQS. https://doi.org/10.1289/EHP15673.

Source: Environmental Health Perspectives

DOI: 10.1289/ehp15673

Authors: Melissa R. Fiffer, Jie Chen, Emily L. Silva, Rachel C. Nethery, Qi Sun, Peter James, Stephanie T. Grady, Jeff D. Yanosky, Joel D. Kaufman, Francine Laden, Jaime E. Hart

Institutions: Harvard University, University of Illinois Chicago, Brigham and Women's Hospital, Harvard Pilgrim Health Care, University of California, Davis, Boston University, Pennsylvania State University, University of Washington

Language: English

Topic: Air Quality and Health Impacts

Subfield: Health, Toxicology and Mutagenesis

Field: Environmental Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $4,500

Funders: National Institutes of Health, National Heart, Lung, and Blood Institute, National Cancer Institute, National Institute of Environmental Health Sciences

Awards: G1498269757, Relationship Between Multiple Environmental Exposures and CVD Incidence and Survival: Vulnerability and Susceptibility, G1823106566, G2214254730, G318798123, Causal machine learning methods for studying the effects of environmental exposures on childhood cancer using natural experiments, Air Pollutants and Cardiovascular Risk: Investigating Thresholds with Pooled Cohorts and Electronic Health Records, G3850548428, G457819564, G5669212752, G9000014778, G9000024218, G9000041598, G9000099730, G9000147396, G9000157792, G9000162331, G9000221662, G9000260128

OpenAlex ID: W4410032135

FWCI: 3.978

Cites: 73

Cited by: 10

Related to: 10