Accelerometer-based measures of sedentary behavior and cardiometabolic risk in active older adults
Bibliographic record
Abstract
PURPOSE: Sedentary behavior has been proposed as an independent cardio-metabolic risk factor even in adults who are physically active through recreational activity. Because little is known about the metabolic effects of sedentariness in seniors, the relationship between sedentary behavior and cardio-metabolic risk was examined in physically active older adults. METHODS: Fifty-four community dwelling men and women > 65 years of age (mean 71.5 years) were enrolled in this cross-sectional observational study. Subjects were in good health and free of known diabetes. Activity levels (sedentary, light, moderate to vigorous activity time per day) were recorded with accelerometers worn continuously for 7 days. Cardio-metabolic risk factors measured consisted of the American Heart Association diagnostic criteria for metabolic syndrome (waist circumference, triglycerides, high-density lipoprotein, systolic blood pressure and fasting glucose) as well as low-density lipoprotein (LDL). The relationships between activity measures and cardio-metabolic risk factors were examined. Significant variables were then entered into a stepwise multivariate regression model. RESULTS: All but one subject achieved exercise levels recommended by the American College of Sports Medicine. The average proportion of time spent at a sedentary activity level each day was 72.7%. From the regression analysis, the only significant association found between cardio-metabolic risk outcomes and activity predictors was between LDL and sedentary time, with LDL detrimentally associated with average sedentary time per day (Standardized Beta Correlation Coefficient 0.302, p < 0.05). CONCLUSION: Sedentary behavior is associated with an adverse metabolic effect on LDL in seniors, even those who meet guideline recommendations for an active "fit" adult.
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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 | 0.003 |
| 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 | 0.000 | 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".