The Relationship Between Objectively Measured Physical Activity, Sedentary Time, and Vascular Health in Children
Bibliographic record
Abstract
BACKGROUND: Physical activity (PA) is beneficially associated with arterial compliance in adults; however, whether this association persists in children is unclear. We examined the cross-sectional relationship of PA and sedentary time with arterial compliance in children. METHODS: Large and small artery compliance was determined by diastolic pulse contour analysis in 102 children aged 8-11 years (43 boys). We used accelerometers and age-specific cut points to classify activity as sedentary, light, or moderate-to-vigorous (MVPA). We also categorized MVPA according to bout length (0-5, 5-10, 10-20, and ≥20 min). Hierarchical linear regression examined: (i) the contribution of activity to large and small artery compliance (controlling for body surface area, systolic blood pressure, and body mass index (BMI)) and (ii) whether bouted MVPA was associated with arterial compliance independent of total MVPA. RESULTS: Activity variables did not explain any additional variance in large artery compliance beyond that captured by body surface area, BMI, and systolic blood pressure (P = 0.118 to P = 0.990). Light activity and MVPA explained an additional 5.8% (P = 0.003) and 2.7% (P = 0.043) of the variance in small artery compliance. MVPA accumulated in bouts was not significantly associated with small artery compliance after controlling for the total volume of MVPA (P = 0.784 to P = 0.923). CONCLUSIONS: Objectively measured PA is associated with small, but not large artery compliance in children aged 8-11 years. Future research should explore the influence of bout frequency and the effect of a PA.intervention on arterial compliance.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".