Effect of cold beverages on whole‐body heat exchange in young and older males during intermittent exercise in the heat
Bibliographic record
Abstract
Abstract Background To mitigate health risks associated with occupational heat stress, workers are advised to adhere to a work‐rest regimen, and hydrate regularly. However, it remains unclear if beverage temperature influences whole‐body heat exchange during work‐rest cycles, and if responses differ in older workers who have a blunted heat loss capacity. Methods Ten young (mean [SD]: 22 [3] years) and 10 older (60 [4] years) males performed four 15‐min bouts of moderate‐intensity cycling at a fixed rate of metabolic heat production (200 W·m−2), each interspersed by 15‐min rest in dry heat (40°C, ~12% relative humidity). On separate days, participants consumed either ice‐slurry (~0°C), standardized to provide a heat transfer capacity of 75 kJ·m−2, or an identical mass of warm fluid (37.5°C) before the first and third exercise bouts. Evaporative and dry heat exchange (direct calorimetry) and metabolic heat production (indirect calorimetry) were measured continuously to determine cumulative heat storage (summation of heat loss and heat gain) over the entire protocol. Rectal temperature was also measured continuously. Results Relative to warm fluid, ice‐slurry ingestion reduced cumulative heat storage in young (69 [181] vs. 216 [94] kJ) and older males (90 [104] vs. 254 [140] kJ, main effect: p < 0.01), but was unaffected by age (p = 0.49). However, rectal temperature was unaffected by beverage temperature in both groups (all p ≥ 0.15). Conclusion We show that cold fluid ingestion is an appropriate administrative control for both young and older males as it can mitigate increases in body heat content during moderate‐intensity work‐rest cycles in dry heat.
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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 | 0.000 |
| 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".