DEXA Body Composition Asymmetry Analysis and Association to Injury Risk and Low Back Pain in University Soccer Players
Bibliographic record
Abstract
Soccer is a laterally dominant sport owing to the repetitive nature of unilateral kicking. The relationship between functional and body composition asymmetries related to limb dominance in soccer players has yet to be established. When present, asymmetries can increase the risk of injury and low back pain. Our study investigated whether lateral dominance is associated with limb asymmetries in a comprehensive body composition assessment among varsity soccer players. Twenty-seven varsity soccer players (age 20.4 ± 1.7 years old; BMI 22.6 ± 4.6 kg/m2) participated in this study. Body composition was assessed through dual-energy X-ray absorptiometry scans. Results showed low lower limb asymmetry indices in both males (3.82%) and females (3.36%) compared to normal ranges. However, upper limb lean mass exhibited high asymmetry, surpassing thresholds in males (7.3%) and females (4.39%). Significant differences were found in total bone mass among males and total lean body mass among females. Male players exhibited higher asymmetry indices in both arm and trunk mass compared to females. Despite these asymmetries, no significant correlations were found between asymmetry indices and occurrences of lower limb injury or low back pain. The study suggests that while evaluating body composition for injury prevention in soccer shows potential, lateral dominance may be influenced by factors extending beyond sport-specific adaptations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".