Occupational inhalant exposures and longitudinal lung function decline
Bibliographic record
Abstract
Background Airborne exposures at the workplace are believed to be associated with lung function decline. However, longitudinal studies are few, and results are conflicting. Methods Participants from two general population-based cohorts, the Copenhagen City Heart Study and the Copenhagen General Population Study, with at least two lung function measurements were followed for a mean of 9 years (range 3–27 years). Occupational exposure was assigned to each year of follow-up between the two lung function measurements by a job exposure matrix. Associations between mean occupational exposure per year and mean annual decline in forced expiratory volume in 1 s (FEV1) were investigated using linear mixed-effects models according to cohort and time period (1976–1983 and 2003–2015). We adjusted for sex, height, weight, education, baseline FEV1and pack-years of smoking per year during follow-up. Results A total of 16 144 individuals were included (mean age 48 years and 43% male). Occupational exposure to mineral dusts, biological dusts, gases and fumes and a composite category was not associated with FEV1decline in analyses with dichotomised exposure. In analyses with an indexed measure of exposure, gases and fumes were associated with an FEV1change of −5.8 mL per unit per year (95% CI −10.8– −0.7 mL per unit per year) during 1976–1983, but not during 2001–2015. Conclusion In two cohorts from the Danish general population, occupational exposure to dusts, gases and fumes was not associated with excess lung function decline in recent years but might have been of importance decades ago.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".