Objectively-measured sedentary time and its association with markers of cardiometabolic health and fitness among cardiac rehabilitation graduates
Bibliographic record
Abstract
BACKGROUND: Sedentary time is an independent risk factor for cardiometabolic disease and mortality. It is unknown how much time individuals with coronary artery disease spend being sedentary or how their sedentary time relates to markers of health. The objectives of this study were to: (a) quantify sedentary time in a post-cardiac rehabilitation (CR) population, and (b) assess association with cardiometabolic risk, independent of moderate-to-vigorous physical activity. DESIGN: Cross-sectional. METHODS: As part of a larger trial, 263 recent CR graduates (∼10 days post-CR, mean age 63.6 ± 9.3 years, 75% male) wore an ActiGraph GT3X accelerometer during waking hours (≥4 days, ≥10 hours/day) to quantify sedentary time (≤150 counts per minute). Spearman correlations were computed to assess relationships between sedentary time (adjusted for wear time) with markers of cardiometabolic health and fitness. Significant markers were examined using multiple linear regressions. RESULTS: Participants spent an average of 8 hours/day sedentary (∼14 bouts/day). Sedentary time was negatively correlated with high-density lipoprotein and [Formula: see text]O2peak and positively correlated with triglycerides, body mass index and waist circumference. After adjusting for age, sex, medications and moderate-to-vigorous physical activity, hours/day of sedentary time remained significantly associated with log[Formula: see text]O2peak (β = -0.02, p = 0.001) and body mass index (β = 0.49, p = 0.02). CONCLUSIONS: Findings suggest that even among a group of post-CR individuals who are already probably more active than patients who have not undergone CR, sedentary time remains high and is associated with poorer cardiorespiratory fitness, suggesting a possible new area of focus among CR programs.
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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) | 0.002 | 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".