A Preliminary Analysis of the Inter‐Individual Determinants of Whole‐Body Heat Exchange in 100 Young Men and Women during Exercise in the Heat
Notice bibliographique
Résumé
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 .
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».