Physical Activity and Trajectories of Cardiovascular Health Indicators During Early Childhood
Bibliographic record
Abstract
OBJECTIVES: Cardiovascular disease prevention should begin in childhood. However, the influence of physical activity on cardiovascular health in early childhood is unknown. Our purpose in this study was to determine the effect of physical activity on trajectories of cardiovascular health indicators during early childhood. METHODS: This prospective, observational cohort study (Health Outcomes and Physical Activity in Preschoolers) enrolled 418 3- to 5-year-olds with annual assessments for 3 years. Total physical activity (TPA) and moderate-to-vigorous physical activity (MVPA) were measured over 7 days via accelerometry. Cardiovascular health indicators included cardiovascular fitness (exercise time on a maximal treadmill test [treadmill time] and 1-minute heart rate recovery), resting arterial stiffness (whole-body pulse wave velocity and carotid β stiffness index), and seated systolic blood pressure. Data were analyzed by using linear mixed-effects modeling; effects are reported as unstandardized estimates (Est). RESULTS: There were main effects of TPA and MVPA on treadmill time (Est = 0.004 [P = .005] and 0.008 [P = .001], respectively) and heart rate recovery (Est = 0.05 [P < .001] and 0.08 [P < .001], respectively). There was a main effect of TPA on pulse wave velocity (Est = −0.001; P = .02) and an MVPA × time interaction (Est = −0.002; P = .01). For carotid β stiffness index, the effect of a TPA × time interaction was not significant (Est = −0.002; P = .051); however, there was a significant MVPA × time interaction (Est = −0.003; P = .03). MVPA was associated with a slower rate of change in systolic blood pressure for girls (Est = 0.06; P = .009). CONCLUSIONS: Children who engage in higher levels of physical activity during early childhood have better cardiovascular health indicators, with more intense physical activity (ie, MVPA) attenuating the stiffening of arteries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".