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Assessment of long-term exposure to traffic-related air pollution: An exposure framework

Journal of Exposure Science & Environmental Epidemiology volume 35, pages 493–501 (2025) Cite this article

Abstract

Background

Exposure to ambient air pollution is associated with morbidity and mortality, making it an important public health concern. Emissions from motorized traffic are a common source of air pollution but evaluating the contribution of traffic-related air pollution (TRAP) emissions to health risks is challenging because it is difficult to disentangle the contribution of individual air pollution sources to exposure contrasts in an epidemiological study.

Objective

This paper describes a new framework to identify whether air pollution differences reflect contrasts in TRAP exposures. Because no commonly measured pollutant is entirely specific to on-road motor vehicles, this exposure framework combined information on pollutants, spatial scale (i.e., geographic extent), and exposure assessment methods and their spatial scale to determine whether the estimated effect of air pollution in a given study was related to differences in TRAP.

Methods

The exposure framework extended beyond the near-road environment to include differences in exposure to TRAP at neighborhood resolution ( ≤ 5 km) across urban, regional, and national scales. It also embedded a stricter set of criteria to identify studies that provided the strongest evidence that exposure contrasts were related to differences in traffic emissions.

Results

Application of the framework to the transparent selection of epidemiological studies for a systematic review produced insights on assessing and improving comparability of TRAP exposure measures, particularly for indirect measures such as distances from roads. It also highlighted study design challenges related to the duration of measurements and the structure of epidemiological models.

Impact statement

This manuscript describes a new exposure framework to identify studies of traffic-related air pollution, a case study of its application in an HEI systematic review, and its implications for exposure science and air pollution epidemiology experts. It identifies challenges and provides recommendations for the field going forward. It is important to bring this information to the attention of researchers in air pollution exposure science and epidemiology because applying the broader lessons learned will improve the conduct and reporting of studies going forward.

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Data availability

All data generated or analyzed during this study are included in this published article or HEI Special Report 23, available at https://www.healtheffects.org/publication/systematic-review-and-meta-analysis-selected-health-effects-long-term-exposure-traffic. The datasets generated during and/or analyzed during the current study are also available from the corresponding author on reasonable request.

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Acknowledgements

We thank the consultants to the Traffic Review Panel, external peer reviewers, and contractor team for their expertise, cooperation, and enthusiasm. We would specifically thank Frank Kelly, Tim Nawrot, and Gregory Wellenius as consultants to the Panel, and Eva Tanner for help with the outside peer review process of the HEI review. In addition, we would like to thank Bert Brunekreef, Dan Greenbaum, Robert O’Keefe, Rashid Shaikh, and Annemoon Van Erp for valuable guidance. Finally, the data extraction team of Ron Kappeler, Alan da Silveira Fleck, Pascale Haddad, Leonie Hoffmann, Lara Lüthi, Margaux Sadoine, Zoe Roth, Elina Wüthrich, Eleanne van Vliet, and Martha Ondras made this work possible.

Funding

Research described in this article was conducted under contract to the HEI, an organization jointly funded by the United States Environmental Protection Agency (EPA) (Assistance Award No. CR-83998101) and certain motor vehicle and engine manufacturers. The views expressed in this article are those of the authors and do not necessarily reflect the views of the Health Effects Institute or its sponsors.

Author information

Authors and Affiliations

  1. Health Effects Institute, Boston, MA, USA

    Allison P. Patton & Hanna Boogaard

  2. Swiss Tropical and Public Health Institute, Allschwil, Switzerland

    Danielle Vienneau & Meltem Kutlar Joss

  3. University of Basel, Basel, Switzerland

    Danielle Vienneau & Meltem Kutlar Joss

  4. Dalla Lana School of Public Health and Dept. of Civil and Mineral Engineering, University of Toronto, Toronto, ON, Canada

    Jeffrey R. Brook

  5. Department of Environmental and Occupational Health, School of Public Health, University of Montreal, Montreal, QC, Canada

    Audrey Smargiassi

  6. Centre de recherche en santé publique, Université de Montréal et CIUSSS du Centre-Sud-de-l’Île-de-Montréal (CReSP), Montréal, QC, Canada

    Audrey Smargiassi

  7. Department of Biostatistics, University of Washington, Seattle, WA, USA

    Adam A. Szpiro

  8. Center for Environmental Research and Children’s Health, Division of Epidemiology, University of California Berkeley School of Public Health, Berkeley, CA, USA

    Sharon K. Sagiv

  9. Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece

    Evangelia Samoli

  10. Institute for Occupational, Social and Environmental Medicine, Centre for Health and Society, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany

    Barbara Hoffmann

  11. Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA

    Howard H. Chang

  12. Population Health Research Institute, St. George’s University of London, London, UK

    Richard W. Atkinson

  13. Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA

    Jennifer Weuve

  14. Environmental Health Group, School of Public Health, Imperial College, London, UK

    Francesco Forastiere

  15. Sonoma Technology, Inc, Petaluma, CA, USA

    Fred W. Lurmann

  16. Institute for Risk Assessment Sciences, Environmental Epidemiology, Utrecht University, Utrecht, Netherlands

    Gerard Hoek

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  1. Allison P. Patton
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HB designed the study and supervised the work. FF and FWL chaired the panel. MKJ, HB, and APP carried out the search strategy, selection, and extraction of data. APP and HB wrote the first version of the manuscript. APP, HB, DV, JRB, AS, FWL, and GH led development and application of the exposure framework and revised early versions of the manuscript. AAS, SKS, ES, BH, HHC, RWA, JW, and FF provided additional interpretation of the exposure framework and its application to epidemiological studies. All authors contributed to development and refinement of the methods and their application, provided feedback on the work, and made a significant contribution to the work reported. All authors take public responsibility for the manuscript content and have approved the final version.

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Correspondence to Allison P. Patton.

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Supplementary information

41370_2024_731_MOESM1_ESM.docx (download DOCX )

Supplemental materials in a separate PDF include details on the exposure framework (Supplemental Tables 1-4) and an expanded description of the traffic specificity ranking of studies.

Reproducibility and Quality Checklist (download PDF )

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Patton, A.P., Boogaard, H., Vienneau, D. et al. Assessment of long-term exposure to traffic-related air pollution: An exposure framework. J Expo Sci Environ Epidemiol 35, 493–501 (2025). https://doi.org/10.1038/s41370-024-00731-5

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