Time‐Varying Associations Between Physical Activity and Injury Risk Among Children
Bibliographic record
Abstract
BACKGROUND: Physical activity has time-varying associations with injury risk among children. While previous activity may predispose to injury through tissue damage, fatigue and insufficient recovery, it may protect against injury by strengthening tissues and improving fitness and skills. It is unclear what the relevant time window and relative importance of past activity are with regard to current injury risk in children. OBJECTIVES: The objectives of this study were to assess how previous activity patterns are associated with injury risk among children. METHODS: Our data source was the Childhood Health, Activity, and Motor Performance School Study Denmark (CHAMPS-DK), a prospective cohort study of Danish school children conducted between 2008 and 2014. We applied flexible weighted cumulative exposure methods within a Cox proportional hazards model to estimate the time-varying association between the number of weekly activity sessions and time-to-first injury in each school year. We estimated several models with varying time windows and compared goodness-of-fit. RESULTS: Out of 1667 study participants, 986 (59.1%) were injured at least once, with a total of 1752 first injuries across school years. The best-fitting model included 20 weeks of past physical activity. Higher levels of activity performed 10-20 weeks ago were associated with decreased injury risk, while higher levels of activity performed 2-9 weeks ago were associated with higher injury risks. Compared to those who remained minimally active for the entire past 20-week period, children who were highly active in the past 10 weeks after being minimally active 11-20 weeks ago had an injury hazard ratio of 1.63 (95% confidence interval 1.18, 2.23). CONCLUSIONS: Flexible weighted cumulative exposure methods suggest a complex temporal relationship between past physical activity history and injury in children.
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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 | 0.002 | 0.005 |
| 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 | 0.001 |
| 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".