Ceiling Fans During Bedrest As A Cooling Strategy For Older Adults During Indoor Overheating
Bibliographic record
Abstract
Recent guidance has recommended the use of electric fans as a sustainable cooling alternative to air conditioning for heat vulnerable populations. While fans may increase sweat evaporation and heat loss in healthy, young adults, evidence supporting their use in older adults is scarce. In this context, many health-care facilities and long-term care homes do not have air-conditioning and rely on ceiling fans to provide relief during daylong bedrest. While recent biophysical modelling has suggested that fans may provide a clinically meaningful cooling effect in temperatures below ~34 °C in older adults, the efficacy of ceiling fans in mitigating heat strain in these conditions is unknown. PURPOSE: To assess the effect of ceiling fans on thermal, cardiovascular, and perceptual strain in older adults during bedrest in a simulated overheated indoor environment. METHODS: We assessed the change in core temperature, heat rate, rate-pressure product and thermal discomfort before and after daylong indoor overheating (8-h, 31 °C, 45% relative humidity) with or without the use of a commercially available ceiling fan providing a standard airflow in 20 older adults (12 female, median age 71 [IQR: 68, 73]) resting on a medical bed. Data were analyzed with linear mixed-effects models (baseline adjusted; 2-tailed α = 0.05). RESULTS: The increase in rectal temperature from pre- to end-exposure was 0.1 [95% CI: 0.0, 0.2]°C lower with fan use (0.7 °C (SD 0.3 °C)) compared to control (0.9 °C (0.3 °C); P = 0.023). The pre-end-exposure change in heart rate was reduced 2 [0, 4] beats/min with a fan (11 (4) vs. 9 (5) beats/min in control; P = 0.032) but there were no between-condition differences in rate-pressure product (fan use - control difference: -125 [-474, 223] mmHg·beats/min, 712 (912) vs. 867 (633); P = 0.480) mmHg·beats/min). Self-reported thermal discomfort was reduced 9 [4, 14] units with a fan (12 (8) units) compared to control (3 (8) units; P < 0.001). CONCLUSIONS: Ceiling fans may improve thermal comfort but only had small benefits on core temperature and heart rate and little influence on rate-pressure product during bed rest when exposed to daylong indoor overheating. Fans should be paired with additional cooling strategies (e.g., ambient cooling). Supported by: Canadian Institutes of Health Research and Health Canada
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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 | 0.001 |
| 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".