Arterial compliance in young children: the role of aerobic fitness
Bibliographic record
Abstract
BACKGROUND: Reduced arterial compliance is reflective of vascular dysfunction, which promotes the atherosclerotic process, and is therefore an important predictor of vascular disease. In adults, obesity, age, aerobic fitness, oestrogens and race influence arterial compliance. Although stature and blood pressure are known to influence compliance in children, other determinants are less established. This investigation sought to determine the predictors of arterial compliance in children, assess the extent to which aerobic fitness is related to compliance, and compare compliance between girls and boys. METHODS: Participants (99 children aged 9-11 years, 55 boys) were assessed for aerobic fitness, physical activity level, blood pressure, body mass, percentage fat mass, height, maturity and arterial compliance (large and small). Predictors of compliance were determined using stepwise regression. Second, children were divided into quartiles according to fitness, and arterial compliance was compared using analysis of covariance (ANCOVA). Finally, differences in compliance between girls and boys were assessed using ANCOVA. RESULTS: We found that fitness, blood pressure and height accounted for 37% of the variance in large artery compliance. Mass, fitness, maturity and blood pressure accounted for 44% of the variance in small artery compliance. Children in the highest fitness quartile had greater compliance than children in the two lowest quartiles, by as much as 34%. There were no differences in compliance between girls and boys after adjusting for covariates. DISCUSSION: These data show that aerobic fitness is associated with arterial compliance in 9-11-year-old children, supporting the concept that physical fitness may exert a protective effect on the cardiovascular system.
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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".