Impact of heat exposure on workers’ health and safety: a scoping review
Bibliographic record
Abstract
Several studies have synthesised the health impacts of occupational heat exposure, yet previous reviews were limited in scope and only focused on specific diseases, high-risk industries or selected countries. This scoping review aimed to summarise global epidemiological evidence on health outcomes associated with occupational heat exposure, examine factors that may modify heat-health associations among workers and identify knowledge gaps to inform the development of more effective jurisdiction-specific heat policies.A search strategy reflecting heat, worker and health was applied to Ovid MEDLINE, Ovid EMBASE, CINAHL and Web of Science, and grey literature of EuropePMC, ProQuest and SafetyLit, to retrieve studies investigating associations between occupational heat exposure and illness and injury. Studies were independently reviewed by two reviewers to assess eligibility. A narrative synthesis approach was used to compare, contrast and synthesise the most relevant findings.This review included 92 studies that estimated associations between heat and various health outcomes, including workplace illness and injury, heat-related illness and deaths, kidney diseases, cardiovascular diseases, cancer, abnormal bone mineral density, skin diseases, eye diseases, infertility and mortality. The included studies presented conflicting evidence on heat-health associations: some observed stronger risks with rising temperatures, some observed smaller positive or reduced risks at extreme temperatures and others reported no associations. The discrepancies may be explained by differences in heat measurements and outcome ascertainments, methodological limitations, geographical variations and the varying impacts of demographic, work-related and individual factors.Jurisdiction-specific heat policies are needed to protect workers from acute and chronic health conditions.
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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 | 0.014 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".