Prevalence Of Running In Extreme Heat Across The Northern Hemisphere
Bibliographic record
Abstract
The American College of Sports Medicine proposes that competitive running events should be postponed or cancelled when the wet bulb globe temperature (WBGT) exceeds 28 °C to mitigate the risk of exertional heat illness (EHI) among participants. While these guidelines protect runners during competition, the prevalence of individuals who run under conditions which could increase their risk of EHI remains largely unknown. PURPOSE: To describe the prevalence of running in ambient conditions which exceed a WBGT of 28 °C, and heat-related symptoms during training between April and September 2022, inclusively. METHODS: A total of 274 participants (30.8 ± 5.2 y, 234 males) across the Northern Hemisphere provided over 1.7 million minutes of outdoor running data. Additionally, 210 participants (77%) responded to a survey about their experience with heat-related symptoms. Environmental conditions for each run were aggregated from National Oceanic and Atmospheric Administration datasets at a 0.5° × 0.5° resolution. RESULTS: 62 participants (22%) engaged in at least one run where WBGT was >28 °C (Range: 1 - 35 runs). Of the 29,031 runs, 344 (1.2%) were conducted with a peak WBGT >28 °C, and WBGT was >28 °C at the start of 285 runs (82.8%). Of the runs where average pace was ≥3 m/s (n = 173), 149 runs (86.6%) were ≥ 5 km in distance. Runs where peak WBGT exceeded 28 °C were commenced later in the day (WBGT ≤28 °C: 12 h14 ± 20 mins, >28 °C: 13 h55 ± 55 mins, p < 0.001). Of those who completed the survey, 42.8% reported experiencing at least one heat-related symptom during training (fatigue: 85%, muscle cramps: 34%, serious discomfort: 23%, nausea: 22%, gastrointestinal distress: 21%, headache: 14%, and/or vomiting: 6%), with elevated symptom frequency per month associated with increases in monthly mean peak WBGT in training (No symptoms: 15.3 ± 5.4 °C, 1 symptom: 18.4 ± 5.5 °C, 2 symptoms: 18.6 ± 4.7 °C, 3 symptoms: 18.8 ± 3.4 °C, 4 symptoms: 18.3 ± 5.4 °C, +5 symptoms: 20.7 ± 3.6 °C, p < 0.001). CONCLUSIONS: Approximately 1.2% of all runs between April and September 2022 were conducted where peak WBGT exceeded 28 °C, and over 22% of all participants completed at least one run when WBGT was >28 °C. An elevated frequency of heat-related symptoms per month may be associated with the mean peak WBGT experienced during training. Support by NSERC (RGPIN-2022-05096)
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".