Impact of habitual sedentary patterns on popliteal artery endothelial-dependent vasodilation in healthy adults
Bibliographic record
Abstract
Introduction: Acute, laboratory-based bouts of prolonged sitting attenuate lower-limb arterial endothelial-dependent vasodilation. However, the impact of habitual sedentary patterns on popliteal artery endothelial health is unclear. We tested the hypothesis that greater habitual total sedentary time, more time spent in prolonged sedentary bouts, and fewer sedentary breaks would be associated with worse popliteal flow-mediated dilation (FMD) responses. Methods: This cross-sectional study used 98 healthy participants (19–77 years, 53 females) that wore an activPAL monitor on the thigh for 6.4 ± 0.8 days to objectively measure sedentary activity and completed a popliteal ultrasound assessment to determine FMD. Both relative (%baseline diameter) and absolute (mm) FMD were calculated. Using bivariate correlation and multiple regression analyses, we examined if there were relationships between sedentary outcomes and FMD while statistically controlling for any potential confounders. Results: In the multiple regression model, age ( p = 0.006, β = −0.030, 95% CI = −0.051, −0.009) and total time in sedentary bouts > 1 hour ( p = 0.031, β = −0.005, 95% CI = −0.009, −0.001) were independent predictors of relative FMD. Age (β = −0.002, 95% CI = −0.003, −0.001), mean blood flow (β = 0.013, 95% CI = 0.002, 0.024), moderate-intensity physical activity (β = 155.9E −5 , 95% CI = 22.4E −5 , 289.4E −5 ), sedentary breaks (β = 0.036, 95% CI = 0.007, 0.066), and total time spent in sedentary bouts > 1 hour (β = −25.02E −5 , 95% CI = −47.67E −5 , −2.378E −5 ) were predictors of absolute FMD (all, p < 0.047). All independent outcomes remained significant after partially controlling for all other predictor variables (all, p < 0.031). Conclusions: Habitual prolonged sedentary bouts and sedentary breaks, but not total sedentary time, were predictors of popliteal endothelial-dependent vasodilatory function. The patterns by which sedentary time is accumulated may be more important than the total sedentary time on lower-limb arterial health.
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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".