Migraine and air pollution: A systematic review
Bibliographic record
Abstract
Abstract Objective To systematically synthesize evidence from a broad range of studies on the association between air pollution and migraine. Background Air pollution is a ubiquitous exposure that may trigger migraine attacks. There has been no systematic review of this possible association. Methods We searched for empirical studies assessing outdoor air pollution and any quantified migraine outcomes. We included short‐ and long‐term studies with quantified air pollution exposures. We excluded studies of indoor air pollution, perfume, or tobacco smoke. We assessed the risk of bias with the World Health Organization's bias assessment instrument for air quality guidelines. Results The final review included 12 studies with over 4,000,000 participants. Designs included case‐crossover, case–control, time series, and non‐randomized pre–post intervention. Outcomes included migraine‐related diagnoses, diary records, medical visits, and prescriptions. Rather than pooling the wide variety of exposures and outcomes into a meta‐analysis, we tabulated the results. Point estimates above 1.00 reflected associations of increased risk. In single‐pollutant models, the percent of point estimates above 1.00 were carbon monoxide 5/5 (100%), nitrogen dioxide 10/13 (78%), ozone 7/8 (88%), PM 2.5 13/15 (87%), PM 10 2/2 (100%), black carbon 0/1 (0%), methane 4/6 (75%), sulfur dioxide 3/5 (60%), industrial toxic waste 1/1 (100%), and proximity to oil and gas wells 6/13 (46%). In two‐pollutant models, 16/17 (94%) of associations with nitrogen dioxide were above 1.00; however, more than 75% of the confidence intervals included the null value. Most studies had low to moderate risks of bias. Where differences were observed, stronger quality articles generally reported weaker associations. Conclusions Balancing the generally strong methodologies with the small number of studies, point estimates were mainly above 1.00 for associations of carbon monoxide, nitrogen dioxide, ozone, and particulate matter with migraine. These results were most consistent for nitrogen dioxide.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".