Traffic related air pollution and noise on cardiovascular outcomes: a systematic review
Bibliographic record
Abstract
Objective: This study financed by the National Collaborating Centre for Environmental Health aim of this review was to assess the confounding effect of one traffic-related exposure (noise or air pollutants) on the association between the other exposure and cardiovascular outcomes. Methods: A systematic review of English and French literature was conducted with the bibliographic databases Medlines and Embase. The confounding effects in studies were assessed by using the change in the point estimate with a cut-off point 10%. Results: The literature search yield 180 articles; 9 articles met our selection criteria. For most studies, the modification of the association between traffic-related noise or air pollutants vis-à-vis cardiovascular outcomes produced changes in point estimates lower than 10%. However, the results were inconsistent when assessing the effects on blood pressure, which may underlie the presence of a small confounding effect. Conclusion: The results from this review suggest that important confounding of cardiovascular effects by traffic-related noise or reported air pollutants is unlikely. Studies with a standardized methodology and assessing the effects of specific traffic-related pollutants are needed to properly assess confounding effects.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".