Evidence Synthesis of Observational Studies in Environmental Health: Lessons Learned from a Systematic Review on Traffic-Related Air Pollution.


Journal

Environmental health perspectives
ISSN: 1552-9924
Titre abrégé: Environ Health Perspect
Pays: United States
ID NLM: 0330411

Informations de publication

Date de publication:
Nov 2023
Historique:
medline: 27 11 2023
pubmed: 22 11 2023
entrez: 22 11 2023
Statut: ppublish

Résumé

There is a long tradition in environmental health of using frameworks for evidence synthesis, such as those of the U.S. Environmental Protection Agency for its Integrated Science Assessments and the International Agency for Research on Cancer Monographs. The framework, Grading of Recommendations Assessment, Development, and Evaluation (GRADE), was developed for evidence synthesis in clinical medicine. The U.S. Office of Health Assessment and Translation (OHAT) elaborated an approach for evidence synthesis in environmental health building on GRADE. We applied a modified OHAT approach and a broader "narrative" assessment to assess the level of confidence in a large systematic review on traffic-related air pollution and health outcomes. We discuss several challenges with the OHAT approach and its implementation and suggest improvements for synthesizing evidence from observational studies in environmental health. We consider the determination of confidence using a formal rating scheme of up- and downgrading of certain factors, the treatment of every factor as equally important, and the lower initial confidence rating of observational studies to be fundamental issues in the OHAT approach. We argue that some observational studies can offer high-confidence evidence in environmental health. We note that heterogeneity in magnitude of effect estimates should generally not weaken the confidence in the evidence, and consistency of associations across study designs, populations, and exposure assessment methods may strengthen confidence in the evidence. We mention that publication bias should be explored beyond statistical methods and is likely limited when large and collaborative studies comprise most of the evidence and when accrued over several decades. We propose to identify possible key biases, their most likely direction, and their potential impacts on the results. We think that the OHAT approach and other GRADE-type frameworks require substantial modification to align better with features of environmental health questions and the studies that address them. We emphasize that a broader, "narrative" evidence assessment based on the systematic review may complement a formal GRADE-type evaluation. https://doi.org/10.1289/EHP11532.

Sections du résumé

BACKGROUND UNASSIGNED
There is a long tradition in environmental health of using frameworks for evidence synthesis, such as those of the U.S. Environmental Protection Agency for its Integrated Science Assessments and the International Agency for Research on Cancer Monographs. The framework, Grading of Recommendations Assessment, Development, and Evaluation (GRADE), was developed for evidence synthesis in clinical medicine. The U.S. Office of Health Assessment and Translation (OHAT) elaborated an approach for evidence synthesis in environmental health building on GRADE.
METHODS UNASSIGNED
We applied a modified OHAT approach and a broader "narrative" assessment to assess the level of confidence in a large systematic review on traffic-related air pollution and health outcomes.
DISCUSSION UNASSIGNED
We discuss several challenges with the OHAT approach and its implementation and suggest improvements for synthesizing evidence from observational studies in environmental health. We consider the determination of confidence using a formal rating scheme of up- and downgrading of certain factors, the treatment of every factor as equally important, and the lower initial confidence rating of observational studies to be fundamental issues in the OHAT approach. We argue that some observational studies can offer high-confidence evidence in environmental health. We note that heterogeneity in magnitude of effect estimates should generally not weaken the confidence in the evidence, and consistency of associations across study designs, populations, and exposure assessment methods may strengthen confidence in the evidence. We mention that publication bias should be explored beyond statistical methods and is likely limited when large and collaborative studies comprise most of the evidence and when accrued over several decades. We propose to identify possible key biases, their most likely direction, and their potential impacts on the results. We think that the OHAT approach and other GRADE-type frameworks require substantial modification to align better with features of environmental health questions and the studies that address them. We emphasize that a broader, "narrative" evidence assessment based on the systematic review may complement a formal GRADE-type evaluation. https://doi.org/10.1289/EHP11532.

Identifiants

pubmed: 37991444
doi: 10.1289/EHP11532
pmc: PMC10664749
doi:

Types de publication

Systematic Review Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

115002

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Auteurs

Hanna Boogaard (H)

Health Effects Institute, Boston, Massachusetts, USA.

Richard W Atkinson (RW)

Population Health Research Institute, St. George's University of London, London, United Kingdom.

Jeffrey R Brook (JR)

Occupational and Environmental Health Division, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.

Howard H Chang (HH)

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

Gerard Hoek (G)

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

Barbara Hoffmann (B)

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

Sharon K Sagiv (SK)

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

Evangelia Samoli (E)

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

Audrey Smargiassi (A)

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

Adam A Szpiro (AA)

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

Danielle Vienneau (D)

Swiss Tropical and Public Health Institute, Allschwil, Switzerland.
University of Basel, Basel, Switzerland.

Jennifer Weuve (J)

Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, USA.

Frederick W Lurmann (FW)

Sonoma Technology, Inc., Petaluma, California, USA.

Francesco Forastiere (F)

Environmental Research Group, School of Public Health, Imperial College London, London, United Kingdom.

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Classifications MeSH