Exploring the contribution of inter-individual factors to the development of physiological heat strain in older adults exposed to simulated indoor overheating
Bibliographic record
Abstract
Older adults are at elevated risk of heat-related mortality due to age-associated declines in thermoregulatory and cardiovascular function. However, the inter-individual factors that exacerbate physiological heat strain during heat exposure remain unclear, making it challenging to identify more heat-vulnerable subgroups. We therefore explored factors contributing to inter-individual variability in physiological responses of older adults exposed to simulated hot weather. Thirty-seven older adults (61–80 years, 16 females) rested for 8 h in 31 and 36 °C (45% relative humidity). Core (rectal) temperature, heart rate (HR), HR variability, mean arterial pressure (MAP), and cardiac autonomic responses to standing were measured at baseline and end-exposure. Bootstrapped least absolute shrinkage and selection operator regression was used to evaluate whether variation in these responses was related to type 2 diabetes (T2D, n = 10), hypertension ( n = 18), age, sex, body morphology, habitual physical activity levels, and/or heat-acclimatization. T2D was identified as a predictor of end-exposure HR (with vs. without: 13 beats/min (bootstrap 95% confidence interval: 6, 23)), seated MAP (−7 mmHg (−18, 1)), and the systolic pressure response to standing (20 mmHg (4, 36)). HR was also influenced by sex (female vs. male: 8 beats/min (1, 16)). No other predictors were identified. The inter-individual factors explored did not meaningfully contribute to the variation in body temperature responses in older adults exposed to simulated indoor overheating. By contrast, cardiovascular responses were exacerbated in females and individuals with T2D. These findings improve understanding of how inter-individual differences contribute to heat-induced physiological strain in older persons.
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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 | 0.002 |
| 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) | 0.000 | 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".