Asthma Among Manitoba Workers: Results from the Manitoba Occupational Disease Surveillance System
Bibliographic record
Abstract
Background: This study characterized the risk of new-onset asthma among workers in Manitoba, Canada. Methods: Accepted time loss claims from the Workers' Compensation Board of Manitoba from 2006 to 2019, containing workers' occupations and industries, were linked with administrative health data from 1996 to 2020. After restricting the cohort to the first claim per person in an occupation and applying age and coverage exclusions, the cohort comprised 142,588 person-occupation combinations. Asthma cases were identified if workers had at least two medical records for asthma (International Classification of Diseases, Ninth Revision, 493) within a 12-month period, within the 2 years before 3 years after cohort entry. New-onset asthma was identified using a 3-year washout period. Asthma hazard ratios by occupation and industry were estimated using Cox proportional hazard models, adjusted for age, and stratified by sex. Results: Increased asthma risk was observed among workers with known asthmagen exposure, including male veterinary and animal health technologists and technicians (hazard ratio 3.97, 95% CI 1.78-8.86), male fish processing workers (3.40, 1.53-7.57), and male machining tool operators (2.91, 1.72-4.92). Increases were also observed for occupations with unknown or suspected allergens, including gas station attendants, drivers, mail/postal and related workers, public works and maintenance laborers, mine laborers and crane operators, and some indoor worker groups. Decreased risks were observed among nurses and residential and commercial installer and servicers. Conclusion: This database linkage study successfully identified occupations and industries with known sensitizing agents or irritants, and several occupation and industries not typically associated with work-related asthma, warranting further investigation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".