Respiratory health, occupation and the healthy worker effect
Bibliographic record
Abstract
BACKGROUND: Workers are exposed to physical, chemical and other hazards in the workplace, which may impact their respiratory health. AIMS: To examine the healthy worker effect in the Canadian working population and to identify the association between occupation and respiratory health. METHODS: Data from four cycles of the Canadian Health Measures Survey were utilized. The current occupation of employed participants was classified into 10 broad categories based on National Occupation Category 2011 codes. Data relating to 15 400 subjects were analysed. RESULTS: A significantly lower proportion of those in current employment than those not in current employment reported respiratory symptoms or diseases or had airway obstruction. Similarly, those currently employed reported better general health and had greater mean values for percent-predicted forced vital capacity (FVC), forced expiratory volume in one second (FEV1), forced expiratory flow between 25% and 75% of FVC (FEF25-75%) and FEV1/FVC ratio. Among males, females and older age groups, significant differences were observed for almost all the respiratory outcomes for those in current employment. Those in 'Occupations unique to primary industry' had a significantly greater likelihood of regular cough with sputum and ever asthma and had lower mean values of percent-predicted FEV1/FVC and FEF25-75% than those in 'Management occupations'. Those in 'Health occupations' had the highest proportion of current asthma. CONCLUSIONS: Participants in current employment were healthier than those not in current employment providing further support for the healthy worker effect. Those in 'Occupations unique to primary industry' had an increased risk of adverse respiratory outcomes and reducing workplace exposures in these occupations has the potential to improve their respiratory health.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".