Associations Between Perceived Parental Physical Activity and Aerobic Fitness in Schoolchildren
Bibliographic record
Abstract
BACKGROUND: Parental behavior is an important correlate of child health. The aim of this study was to investigate the association between perceived parental physical activity (PA) and schoolchildren's aerobic fitness. METHODS: English schoolchildren's (n = 4029, 54% boys, 10.0-15.9 yrs) fitness was assessed by 20 m shuttle run test and categorized using criterion-referenced standards. Parental PA was reported by the child. RESULTS: Boys and girls were more likely to be fit (OR 1.4, 95% CI 1.1-1.8; OR 1.5, 95% CI 1.1-2.0; respectively) if at least 1 parent was perceived as active compared with when neither parents were. Girls were even more likely to be fit (OR 1.8, 95% CI 1.2-2.8) if both parents were active. Associations between parental PA and child fitness were generally stronger when parent and child were of the same gender, although girls with active fathers were more likely (OR 2.5, 95% CI 1.7-3.7) to be fit compared with inactive fathers. CONCLUSION: Schoolchildren perceiving at least 1 parent as active are more likely to meet health-related fitness standards. Underlying mechanisms remain elusive, but same-gender associations suggest that social rather than genetic factors are of greater importance. Targeting parental PA or at least perceptions of parental PA should be given consideration in interventions aiming to improve child 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 | 0.001 | 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".