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Record W4317181617 · doi:10.1289/isee.2022.p-0066

Narrative Review of Long-Term Exposure to Traffic-Related Air Pollution on Dementia and Related Outcomes in Older Adults

2022· article· en· W4317181617 on OpenAlexaff
Martha Ondras, Hanna Boogaard, Allison P. Patton, Richard Atkinson, Jeffrey R. Brook, Howard H. Chang, Gerard Hoek, Barbara Hoffmann, Sharon K. Sagiv, Evangelia Samoli, Audrey Smargiassi, Adam A. Szpiro, Danielle Vienneau, Frederick Lurmann, Francesco Forastiere, Jennifer Weuve

Bibliographic record

VenueISEE Conference Abstracts · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsUniversité de MontréalPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsDementiaMedicineConfoundingObservational studyPublication biasEpidemiologyGerontologyPopulationMeta-analysisEnvironmental healthInformation biasDiseaseSelection biasPathology

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS As part of an extensive systematic review on the associations of important clinical health outcomes with exposure to traffic-related air pollution (TRAP), an independent Panel appointed by the Health Effects Institute considered the emerging literature on dementia-related outcomes and Parkinson’s disease, two areas of significant public health interest. METHODS The Panel systematically searched the PubMed and LUDOK electronic databases for observational epidemiological studies from 1980 through 2019 on long-term exposure to TRAP and dementia-related outcomes and Parkinson’s disease prevalence in the general population. Study selection and data extraction were conducted according to a defined protocol, and a novel framework was used to identify which studies provided information on TRAP exposure. Conclusions regarding the level of confidence in the presence of an association were based on a narrative assessment. The Panel decided a priori not to conduct formal confidence and risk of bias assessments and meta-analyses because this is an emerging area of research. RESULTS The Panel reviewed 15 studies on dementia-related outcomes and six studies of Parkinson’s disease. Evidence for an association of dementia-related outcomes with TRAP was mixed; studies of cognition and incident dementia generally found adverse associations while findings on cognitive decline were null. Evidence for an association of TRAP with Parkinson’s disease was inconsistent with some potential for systematic bias. Limitations of the body of literature included its small size, potential for bias due to outcome misclassification, selection and attrition bias, and adjustments for confounding that did not align with plausible pathways between TRAP exposure and outcomes. CONCLUSIONS The Panel’s confidence in the association of TRAP with dementia-related outcomes was low to moderate, while confidence in the association with Parkinson’s disease was low. Future systematic reviews will benefit from the continued growth in this literature. KEYWORKS: narrative review, traffic-related air pollution, dementia, cognitive decline

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.301
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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