Defining Sex‐ and Age‐Specific Initial Stay Times for Continuous Heavy‐Intensity Work in Hot Environments Before Heat‐Mitigation Controls Are Implemented—Part B
Bibliographic record
Abstract
RATIONALE: Industry guidelines recommend work-rest schedules to prevent unsafe core temperature elevations (> 38.0°C or > Δ1.0°C above baseline resting) in an "average" worker exposed to occupational heat stress. While permissible initial work durations (initial stay times [IST]) before implementing rest schedules have been suggested, existing data are limited to moderate-intensity efforts. OBJECTIVES: The objective of this study was to assess whether factors of sex and age influence IST during heavy-intensity work. METHODS: We assessed work durations before reaching unsafe core temperature thresholds (i.e., > 38.0°C or > Δ1.0°C above baseline resting) among young (18-30 years) and older (50-69 years) males and females during simulated heavy-intensity work at 26°C, 29°C, and 32°C wet-bulb globe temperatures (WBGT). FINDINGS: The likelihood of surpassing a core temperature of 38.0°C significantly increased at 32°C WBGT (hazard ratio [95% confidence interval]: 2.0 [1.5, 2.7], p = 0.001), but not at 29°C WBGT (1.1 [0.9, 1.4], p = 0.342), compared to 26°C WBGT. Median (interquartile range) durations to reach 38.0°C across groups were 32 (23-52), 29 (23-47), and 26 (18-35) minutes at 26°C, 29°C, and 32°C WBGT, respectively. The likelihood of reaching Δ1.0°C above baseline resting significantly increased at both 32°C (3.8 [2.6, 5.4], p < 0.001) and 29°C WBGT (1.5 [1.1, 2.0], p < 0.001), with median durations being 55 (40-82), 42 (35-56), and 33 (29-42) min, respectively. Older females were more likely to reach 38.0°C (2.4 [1.3, 4.3], p = 0.004) and Δ1.0°C above baseline resting (2.5 [1.4, 4.7], p = 0.003) compared to young males. No other sex- or age-related differences were detected (p > 0.145). IMPACT: These findings highlight the heightened vulnerability of older females during heavy-intensity occupational heat stress, emphasizing the need for tailored guidelines to ensure equitable workforce protection.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".