Occupational exposure to inhaled pollutants and risk of airflow obstruction: a large UK population-based UK Biobank cohort
Bibliographic record
Abstract
BACKGROUND: Although around 10% to 15% of COPD burden can be attributed to workplace exposures, little is known about the role of different airborne occupational pollutants (AOP). The main aim of the study was to assess the effect size of the relationship between various AOP, their level and duration of exposure with airflow obstruction (AFO). METHODS: A cross-sectional analysis was conducted in 228 614 participants from the UK Biobank study who were assigned occupational exposure using a job exposure matrix blinded to health outcome. Adjusted prevalence ratios (PRs) and 95% CI for the risk of AFO for ever and years of exposure to AOPs were estimated using robust Poisson model. Sensitivity analyses were conducted for never-smokers, non-asthmatic and bi-pollutant model. RESULTS: Of 228 614 participants, 77 027 (33.7%) were exposed to at least one AOP form. 35.5% of the AFO cases were exposed to vapours, gases, dusts or fumes (VGDF) and 28.3% to dusts. High exposure to vapours increased the risk of occupational AFO by 26%. Exposure to dusts (adjusted PR=1.05; 95% CI 1.01 to 1.08), biological dusts (1.05; 1.01 to 1.10) and VGDF (1.04; 1.01 to 1.07) showed a significantly increased risk of AFO, however, statistically not significant following multiple testing. There was no significant increase in risk of AFO by duration (years) of exposure in current job. The results were null when restricted to never-smokers and when a bi-pollutant model was used. However, when data was analysed based on the level of exposure (low, medium and high) compared with no exposure, directionally there was increase in risk for those with high exposure to vapours, gases, fumes, mists and VGDF but statistically significant only for vapours. CONCLUSION: High exposure (in current job) to airborne occupational pollutants was suggestive of higher risk of AFO. Future studies should investigate the relationship between lifetime occupational exposures and COPD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".