A Preliminary Analysis of the Inter‐Individual Determinants of Whole‐Body Heat Exchange in 100 Young Men and Women during Exercise in the Heat
Bibliographic record
Abstract
It is well established that several inter‐individual factors ( e.g ., physical characteristics, aerobic fitness, others) independently modulate human thermoeffector responses (sweat secretion and cutaneous vasodilation) and the resulting changes in evaporative and dry heat exchange during exercise‐induced heat stress. However, less is known regarding the relative contribution of those factors to explaining inter‐individual variations in heat exchange or whether that contribution is modified by the heat load employed for exercise eliciting a matched rate of metabolic heat production. We therefore used direct calorimetry to assess whole‐body evaporative and dry heat exchange in a large, heterogeneous sample of young men ( n = 57) and women ( n = 43) during three, 30‐min bouts of cycling performed at light (men/women; 300/250 W), moderate (400/325 W) and heavy (500/400 W) fixed rates of metabolic heat production, each followed by a 15‐min recovery, in dry heat (40°C, ~12% relative humidity). Metabolic heat production, evaporative and dry heat exchange as well as the evaporative heat loss requirement (E req ; metabolic heat production ± dry heat exchange) were measured throughout, with an average of the final five minutes of each exercise period used for statistical analysis. Relationships between the dependent (evaporative and dry heat exchange) and relevant independent variables (body mass, body surface area, body surface area‐to‐mass ratio, body fat, peak aerobic power, metabolic heat production, E req ) were assessed using Pearson's correlation coefficient ( r ), while step‐wise, multiple‐linear regression analyses was performed to quantify the proportion (%) of variation (coefficient of determination; R 2 ) in each dependent variable explained by the independent variables. Strong, positive associations were observed between E req and evaporative heat loss (all p<0.01), especially during heavy exercise (men: r = 0.62; women: r = 0.82), which explained 19–67% of individual variation. Peak aerobic power was also positively related to evaporative heat loss in men and women, albeit only during moderate and heavy exercise ( r = 0.33 to 0.43; all p<0.05), explaining a further 5–9% of variation. Dry heat exchange shared moderate‐to‐strong, negative associations with body mass and surface area for all exercise intensities in men and women ( r = −0.29 to −0.55; all p<0.05), which explained 9–30% of variation. Observations from this preliminary analysis indicate that E req , body morphology and peak aerobic power are important determinants of inter‐individual variations in whole‐body heat exchange among men and women during exercise eliciting matched rates of metabolic heat production in dry heat, with the strength of those relationships being dependent on the exercise‐induced heat load. Support or Funding Information Funded by the Government of Ontario and Natural Sciences and Engineering Research Council of Canada. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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".