Heat-related illness among workers in British Columbia, Canada: Extreme hot weather in 2021 compared to 2001–2020
Bibliographic record
Abstract
OBJECTIVES: British Columbia (BC), Canada, experienced an unprecedented summer with record-breaking high temperatures in 2021. Yet the health impact has not been examined in occupational settings. This study aimed to characterize occupational heat-related illness (HRI) among BC workers estimated by incidence rates and associations between heatwaves and HRI, compare risks from 2021 and prior summers of 2001-2020, and assess differential impacts on worker groups by demographics and occupations. METHODS: We identified HRI from workers' compensation claims that occurred between June and August from 2001-2021 in BC. Incidence rates were calculated using working population estimates from Statistics Canada's Labour Force Survey. A time-stratified case-crossover design with conditional Poisson regression was used to examine the impact of heatwaves on occupational HRI. All analyses were stratified by year (2021 versus 2001-2020), age, sex, and occupation. RESULTS: Of the 521 claims identified, 107 (21%) occurred in 2021. Incidence rates for 2021 and prior summers were 3.97 [95% confidence interval (CI) 3.26-4.80] and 0.93 (95% CI 0.85-1.03) claims per 100 000 workers, respectively. This difference represents a 327% increase. Rates were higher in health occupations in 2021 versus 2001-2020. During 2001-2021, the risk of HRI during heatwave days was 4.33 (95% CI 2.98-6.27) times that during non-heatwave days, and the risk was higher among middle-aged workers and workers in trades, transport, and equipment operations. The 2021 heatwaves had greater impact on younger and female workers than those from prior summers. CONCLUSIONS: Heat is a crucial workplace hazard. Prevention strategies should prioritize at-risk workers and not be limited to heatwaves.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".