Effect of Age on Physiological Heat Strain during Hot and Humid Heat Exposure – The Human Heat Stress Project
Bibliographic record
Abstract
Introduction: A direct consequence of climate change is an increased frequency, intensity, and duration of extreme heat events that pose heightened health risks globally. Aging is associated with a greater risk of heat-related hospitalization and mortality. It remains unclear if these greater health risks are due to greater physiological heat strain during exposure to a hot environment. OBJECTIVE & HYPOTHESIS: The objective of this study is to determine the effect of age on physiological strain during hot and humid heat exposure. We hypothesized that older adults would experience a greater increase in core temperature and heart rate, and greater dehydration compared to young and middle-aged adults. METHODOLOGY: Nine young (18-39 years, 6 females), 5 middle-aged (40-64 years, 3 males), and 3 older (65-88 years, 3 females) healthy adults were exposed to a 38°C environment with 60% humidity inside an environmental chamber for 4 hours. To simulate activities of daily living, participants performed 10 minutes of treadmill walking or cycling every hour at an energy expenditure of ~3.5 METs. Participants could drink water ad libitum. Rectal temperature and heart rate were recorded continuously. Dehydration was calculated as the relative change in nude body mass from pre- to post-exposure. Data are reported as mean ± standard deviation. Results: Rectal temperature increased by 0.3 ± 0.2°C in older adults, 0.2 ± 0.2°C in middle-aged adults, and 0.4 ± 0.3°C in young adults. Heart rate increased by 8 ± 6 bpm in older adults, 6 ± 5 bpm in middle-aged adults, and 10 ± 7 bpm in younger adults. The level of dehydration was 1.3 ± 1.0 % in older adults, 0.9 ± 0.6% in middle-aged adults, and 0.4 ± 0.3% in young adults. Conclusion: These preliminary results suggest that thermal and cardiac strain during hot and humid heat exposure do not differ as a function of age. However, older adults appear to experience greater dehydration. The clinical implications of these differences remain to be determined. FUNDING: Canadian Institutes of Health Research. This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.
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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 | 0.001 | 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 | 0.001 |
| 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".