The Effect Of Sleep Deprivation On Thermoregulation In Older Adults During Exercise-Heat Stress
Bibliographic record
Abstract
Sleep deprivation has been shown to cause a deterioration in physical and cognitive function leading to performance reductions. While some reports suggest that it can cause impairments in thermoregulation, others have shown no effect. These disparate findings may in part be due to differences in the duration of the sleep deprivation employed and or the level of heat stress assessed. Further, prior reports have been limited to the evaluation of local heat loss responses of skin blood flow and sweating which may not accurately reflect whole-body heat loss. Additionally, no study to our knowledge has assessed responses in older adults who may be at greater risk of heat-related illness. PURPOSE: To assess the effect of 24-h of sleep deprivation on heat loss capacity in older men during exercise-heat stress. METHODS: On separate days, following either a night of normal sleep or 24-h of sleep deprivation, eight older men (mean [SD], age: 62 [2] yrs), completed an exercise heat-stress test consisting of three 30-min bouts of exercise at increasing fixed rates of metabolic heat production of 150, 200, and 250 W/m2, each separated by 15-minutes rest in the heat (40 °C, 15% relative humidity). Rates of whole-body heat loss (dry and evaporative heat loss, via direct calorimetry), metabolic heat production (via indirect calorimetry) and change in core (rectal) temperature (ΔTrec, difference from pre-exercise resting) were measured continuously and expressed as peak responses (mean of final 5-minutes of the final exercise bout; 250 W/m2). Responses between conditions were compared using paired samples t-tests (α = 0.05). RESULTS: Relative to a normal night of sleep there were no differences in evaporative (282 [36] vs. 276 [31] W/m2) or dry heat loss (-66 [15] vs.-67 [18] W/m2) following sleep deprivation at the end of exercise (both p > 0.42). As such, whole-body heat loss did not differ between a normal night of sleep and sleep deprivation (216 [26] vs. 209 [19] W/m2, p = 0.31). Consequently, body heat storage (92 [36] vs. 96 [26] kJ, p = 0.62) and the ΔTrec were similar between the normal and sleep deprived conditions (1.2 [0.3] and 1.2 [0.4] °C, p > 0.69). CONCLUSION: We showed that 24-h of sleep deprivation was not associated with a decrease in heat loss capacity in older males during exercise heat stress. Natural Sciences and Engineering Research Council of Canada and Mitacs
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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".