Outdoor air pollution, exhaled 8-isoprostane and current asthma in adults: the EGEA study
Bibliographic record
Abstract
Associations between outdoor air pollution and asthma in adults are still scarce, and the underlying biological mechanisms are poorly understood. Our aim was to study the associations between 1) long-term exposure to outdoor air pollution and current asthma, 2) exhaled 8-isoprostane (8-iso; a biomarker related to oxidative stress) and current asthma, and 3) outdoor air pollution and exhaled 8-iso. Cross-sectional analyses were conducted in 608 adults (39% with current asthma) from the first follow-up of the French case–control and family study on asthma (EGEA; the Epidemiological study of the Genetic and Environmental factors of Asthma). Data on nitrogen dioxide, nitrogen oxides, particulate matter with a diameter ≤10 and ≤2.5 µm (PM10and PM2.5), road traffic, and ozone (O3) were from ESCAPE (European Study of Cohorts for Air Pollution Effects) and IFEN (French Institute for the Environment) assessments. Models took account of city and familial dependence. The risk of current asthma increased with traffic intensity (adjusted (a)OR 1.09 (95% CI 1.00–1.18) per 5000 vehicles per day), with O3exposure (aOR 2.04 (95% CI 1.27–3.29) per 10 µg·m−3) and with exhaled 8-iso concentration (aOR 1.50 (95% CI 1.06–2.12) per 1 pg·mL−1). Among participants without asthma, exhaled 8-iso concentration increased with PM2.5exposure (adjusted (a)β 0.23 (95% CI 0.005–0.46) per 5 µg·m−3), and decreased with O3and O3-summerexposures (aβ −0.20 (95% CI −0.39– −0.01) and aβ −0.52 (95% CI −0.77– −0.26) per 10 µg·m−3, respectively). Our results add new insights into a potential role of oxidative stress in the associations between outdoor air pollution and asthma in adults.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".