Obesity and Its Relationship with Occupational Injury in the Canadian Workforce
Bibliographic record
Abstract
Objectives. To examine associations between obesity and occupational injury. Methods. Participants consisted of a representative sample of 7,678 adult Canadian workers. Participants were placed into normal weight, overweight, and obese categories based on their body mass index. Different injury types, location, and external causes were measured. Logistic regression was used to estimate relationships. Results. By comparison to normal weight workers, obese workers were more likely to report any occupational injuries (odds ratio (OR) 1.40, 95% confidence interval (CI): 0.98-1.99) and serious occupational injuries (1.49, 0.99-2.26). These relationships were more pronounced for sprains and strains (1.80, 1.04-3.11), injuries to the lower limbs (2.14, 1.12-4.11) or torso (2.36, 1.13-4.93), and injuries due to falls (2.10, 0.86-5.10) or overexertion (2.08, 0.96-4.50). Female workers, workers ≥40 years, and workers employed in sedentary occupations were particularly vulnerable. Increased risks were not identified for overweight workers. Conclusions. Obese workers experienced 40-49% higher risks for occupational injury.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".