Association between high ambient temperature and acute work-related injury: a case-crossover analysis using workers’ compensation claims data
Bibliographic record
Abstract
Objectives The aim of this study was to investigate the association between high ambient temperature and acute work-related injury, expanding on previous research in this area. Specifically we examined the relationship between both daytime and overnight temperatures and injury risk and disentangled physically demanding occupational exposures from exposure to outdoor working conditions. Methods A time-stratified case-crossover study design was used to examine the association between ambient temperatures and acute work-related injuries in Melbourne, Australia, 2002-2012, using workers' compensation claims to identify work-related injuries. The relationship was assessed for both daily maximum and daily minimum temperatures using conditional logistic regression. Results Significant positive associations between temperature and acute work-related injury were seen for younger workers (<25 years), with the odds of injury increasing by 1% for each 1 °C increase in daily minimum temperature, and by 0.8% for each 1 °C increase in daily maximum temperature. Statistically significant associations were also observed between daily maximum temperature and risk of injury for workers employed in the highest strength occupations and for male workers, and between daily minimum temperature and injury for all cases combined, female workers, workers aged 25-35 and ≥55 years, "light" and "limited" physical demand groups, and "in vehicle or cab" and "regulated indoor climate" workplace exposure groups. Conclusions Young workers, male workers and workers engaged in heavy physical work are at increased risk of injury on hot days, and a wider range of worker subgroups are vulnerable to injury following a warm night. In light of climate change projections, this information is important for informing injury prevention strategies.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".