Adult Asthma among Workers in Ontario. Results from the Occupational Disease Surveillance System
Bibliographic record
Abstract
Abstract Rationale Given that approximately 15% of new-onset adult asthma cases originate because of exposures in the workplace, there is a need for systematic and ongoing monitoring of risk among workers. Objectives To characterize the risk of new-onset adult asthma among workers in Ontario. Methods We used 575,379 provincial accepted time-loss workers’ compensation claimants data linked to physician billing data. Workers aged 15 to 65 years with a nonasthma compensation claim between January 1, 2002, and December 31, 2013, were eligible for inclusion. Cohort entry corresponded to the date of the claim. The case definition required two or more records for asthma within a 12-month period, within a 3-year time window after cohort entry. A 3-year washout period preceding cohort entry was used to exclude prevalent cases. Workers at risk of new-onset adult asthma were followed from cohort entry date to date of diagnosis, emigration, age 65 years, death, or end of study period. Cox regression models were used to generate birth year- and sex-adjusted hazard ratios (HRs) by occupation, industry, and exposures identified using a job exposure matrix. Sex-stratified risk estimates were also generated. Results Increased risks were detected among well-recognized groups, including bakers (HR, 1.60; 95% confidence interval [CI], 1.22–2.09) and painters and decorators (HR, 1.67; 95% CI, 1.23–2.28). In the job exposure matrix analysis, flour and isocyanates were associated with increased risk of asthma. Concrete finishers (HR, 1.93; 95% CI, 1.12–3.32) and shipping and receiving clerks (HR, 1.21; 95% CI, 1.03–1.43) also showed elevated risk, whereas results varied across woodworker groups. Decreased risks were detected for nursing and farming groups. Conclusions This practical data linkage approach was successful for examining associations across hundreds of jobs. Unexpected and previously unrecognized findings deserve further investigation and emphasize the importance of an ongoing system to guide research as well as prevention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".