Association between Body Composition and Sport Injury in Canadian Adolescents
Bibliographic record
Abstract
Purpose: To examine the association between overweight or obesity and sport injury in a population-based sample of Canadian adolescents. Methods: Cross-sectional analyses were performed using the Canadian Community Health Survey (2009–2010), a nationally representative sample (n=12,407) of adolescents aged 12–19 years. Body composition was quantified using BMI, grouping participants into healthy weight, overweight, or obese. The outcome of interest was acute or repetitive strain injury sustained during sport in the previous year. We examined the relationship between sport injury and overweight or obesity compared with healthy weight using multivariate logistic regression, controlling for sex, ethnicity, physical activity, and socio-economic status. We also examined the interaction between physical activity and body composition in a secondary analysis with a subset of active adolescents. Results: No significant relationship was found between being overweight and sport injury (odds ratio [OR]=1.04, 95% CI: 0.92, 1.17); however, a protective effect was seen between obesity and sport injury (OR=0.67, 95% CI: 0.53, 0.84). Secondary analysis revealed that overweight youths with the highest activity level (quartile 4) did have increased odds of sport injury (OR=1.38, 95% CI: 1.04, 1.83), yet obese youths with a moderate activity level (quartile 2) were protected compared with healthy-weight youths (OR=0.46, 95% CI: 0.24, 0.91). Conclusions: Further examination of active adolescents is warranted. Studies should consider sport-specific differences and comprehensive measurement of exposure to sport.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".