Higher Fat Mass Is Associated With a History of Knee Injury in Youth Sport
Bibliographic record
Abstract
Study Design Historical cohort study. Background History of a knee joint injury and increased fat mass are risk factors for joint disease. Objective The objective of this study was to examine differences in adiposity, physical activity, and cardiorespiratory fitness between youths with a 3- to 10-year history of sport-related intra-articular knee injury and uninjured controls. Methods One hundred young adults (aged 15–26 years; 55% female) with a sport-related intra-articular knee injury sustained 3 to 10 years previously and 100 controls matched for age, sex, and sport, who had no history of intra-articular knee injury, were recruited. Fat mass index (FMI) and abdominal fat (fat mass at the L1 to L4 vertebral levels) were derived using dual-energy X-ray absorptiometry. Physical activity and cardiorespiratory fitness were measured using the Godin Leisure-Time Exercise Questionnaire and the multistage 20-meter shuttle run test for aerobic fitness, respectively. Results Previously injured participants demonstrated higher FMI (within-pair difference, 1.05 kg/m2; 95% confidence interval [CI]: 0.53, 1.57) and abdominal fat (461 g; 95% CI: 228, 694) than uninjured controls. In multivariable linear regression analysis, previous injury was significantly associated with increased FMI. This increase was attenuated in those who participated in higher levels of physical activity or had higher estimated maximum volume of oxygen. Conclusion As a risk factor for osteoarthritis in an already susceptible group, excess adiposity is an undesirable trait in the potential pathway to joint disease. Increasing physical activity in this population may be a potential intervention to reduce adiposity thus impede disease initiation and/or progression. Level of Evidence Level 2b. J Orthop Sports Phys Ther 2017;47(2):80–87. doi:10.2519/jospt.2017.7101
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".