Relationships between asthma and work exposures among non‐domestic cleaners in Ontario
Bibliographic record
Abstract
BACKGROUND: Cleaners have been reported to have increased risk for work-related asthma symptoms but few studies have studied non-domestic cleaners. In this study, we compared work-related asthma symptoms among cleaners and other building workers and determined associations with tasks. METHODS: School and racetrack workers in Ontario, Canada, completed a questionnaire to identify the prevalence of cleaning tasks, physician-diagnosed asthma, new-onset asthma, respiratory symptoms, and work-related asthma symptoms. RESULTS: Cleaners and controls had a similar prevalence of most asthma outcomes although female cleaners reported significantly more respiratory symptoms; odds ratio (OR), 2.59 confidence intervals (CI) 1.6-4.3, and work-related asthma symptoms, OR 3.90 (CI 2.1-7.4) compared with female controls with adjustment for age and smoking history. Male cleaners showed a non-significant trend to more physician-diagnosed asthma, adjusted OR 2.10 (CI 0.9-4.8) and work-related asthma symptoms, adjusted OR 1.53 (CI 0.8-3.0). The work-related asthma symptoms among men were significantly associated with waxing floors, OR 2.19 (CI 1.0-4.4); wax-stripping floors, OR 2.54 (1.2-5.2); spot-cleaning carpets, OR 2.20 (1.3-3.8); and cleaning tiles, OR 4.46 (1.0-19.3) and grout, OR 2.12 (1.1-4.0). CONCLUSIONS: Female cleaners have more asthma symptoms worse at work than controls. Work-related asthma symptoms among male cleaners were associated with a number of specific cleaning tasks. Findings suggest the need for school cleaners to have reduced exposure to cleaning chemicals and need for protective strategies during performance of tasks expected to exacerbate asthma, such as wax stripping.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".