Interactive effects of age and hydration state on human thermoregulatory function during exercise in hot‐dry conditions
Bibliographic record
Abstract
Abstract Aim Ageing and hypohydration independently attenuate heat dissipation during exercise; however, the interactive effects of these factors remain unclear. We assessed the hypothesis that ageing suppresses hypohydration‐induced reductions in whole‐body heat loss during exercise in the heat. Methods On two occasions, eight young (mean [SD]: 24 [4] years) and eight middle‐aged (59 [5] years) men performed 30‐minute bouts of light (heat production of 175 W m−2) and moderate (275 W m−2) cycling (separated by 15‐minute rest) in the heat (40°C, 15% relative humidity) when euhydrated and hypohydrated (~4% reduction in body mass). Heat production and whole‐body net heat exchange (evaporative heat loss + dry heat gain) were measured via indirect and direct calorimetry (respectively) and heat storage was calculated via their temporal summation. Results Net heat exchange was reduced, while heat storage was elevated, in the middle‐aged men during moderate exercise when euhydrated (both P ≤ 0.01). In the young, evaporative heat loss was attenuated in the hypohydrated vs euhydrated condition during light (199 ± 6 vs 211 ± 10 W m−2; P ≤ 0.01) and moderate (287 ± 15 vs 307 ± 13 W m−2; P ≤ 0.01) exercise, but was similar in the middle‐aged men, averaging 223 ± 6 and 299 ± 15 W m−2, respectively, across conditions (both P ≥ 0.32). Heat storage was thereby exacerbated by hypohydration in the young (both P < 0.01) but not the middle‐aged (both P ≥ 0.32) during both exercise bouts and, as a result, was similar between groups when hypohydrated (both P ≥ 0.50). Conclusion Hypohydration attenuates heat loss via sweating in young but not middle‐aged men, indicating that ageing impairs one’s ability to mitigate further sweat‐induced fluid loss during hypohydration.
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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) | 0.001 | 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".