Influence of Summertime Climate on Total Daily Physical Activity Values in Older, Community-Dwelling Adults
Bibliographic record
Abstract
Higher ambient temperatures, particularly when combined with excess humidity (Humidex) may negatively influence daily physical activity (PA) levels of older adults, but there is little quantitative data available on the effect of summertime weather. PURPOSE: To assess the relationship between temperature and humidity on accelerometer measured PA values in older adults. METHODS: Forty-eight healthy community-dwelling older adults (77.6 ± 4.7yrs; range 71-89yrs; 36 females) living in southwestern Ontario (Latitude 43° T N) wore a waist-borne accelerometer during waking hours for one 7-consecutive day period between 05.30.06-08.09.06. Hourly temperatures were obtained from meteorological records and linked to hourly accelerometer PA values. RESULTS: Mean daytime (7:00hr-19:00hrs) recorded PA values (ct/min) were 201.8 ± 106.2. PA participation was highly variable among individuals. Polynomial regression of the second order revealed a curvilinear relationship between temperature and PA of r2=.023. Mean PA values reported when mean daytime temperature was < 25°C were 207.5 (range 13.4–614.6). When ambient temperature rose above 25°C, mean PA declined by 15% (mean 176.8; range 26.8-329.6). A similar curvilinear relationship was observed between PA and Humidex, r2=.017. As Humidex values rose, mean daily PA values continued to decline. Above 28°C, mean PA was1 83.6, with a narrower range of 53.4-227.5.Figure: Temperature 7h to 19hCONCLUSION: When ambient daytime temperatures rose above 25°C, the PA levels of these older adults decreased substantially and the contribution of Humidex may have further reduced their daily PA. Appropriate PA assessment must account for the potential influence of climate upon daily reported PA values.
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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".