CLINICAL FACTORS ASSOCIATED WITH INCREASED SEDENTARY TIME IN VERY ACTIVE OLDER ADULTS
Bibliographic record
Abstract
Abstract Sedentary behavior (such as sitting) has been shown to be an independent risk factor for increased frailty and less successive aging, even in active individuals. Our study examined the clinical factors most associated with higher sedentary times (ST) in very active older adults. We recruited 54 adults from a Master’s ski team (Whistler, British Columbia; mean age 71.5±0.6 years, 55% female). Activity levels were measured using an accelerometer (SenseWear) worn continuously for 7 days. ST was defined as a lack of activity when not in the supine position, in order to exclude time spent sleeping. Potential predictor variables consisted of metabolic syndrome criteria (blood pressure, high density lipoprotein, waist circumference, triglyceride levels, fasting blood glucose), age, biological sex and heart rate. Predictors associated with ST (p<0.10) were entered into a stepwise multivariate regression model. Our subjects were extremely active, engaging in moderate to vigorous physical activity for 2.6±0.2 hours per day, greatly exceeding current activity guidelines. Despite these high activity levels, they were also sedentary for an average of 9.4±0.2 hours per day. Our final minimum effective model showed that waist circumference had a significant association with ST (Standardized β = 0.36±0.13, p=0.007), explaining 18% of the variation in ST. People are often subjectively unaware of how long they spend sedentary. Our study suggests, that in addition to promoting leisure time physical activity, physicians should also objectively measure ST in highly active older patients with high waist circumferences.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".