Body Composition Asymmetries in University Ice Hockey Players and Their Implications for Lower Back Pain and Leg Injury
Bibliographic record
Abstract
ABSTRACT: Resta, T, Frenette, S, Rizk, A, and Fortin, M. Body composition asymmetries in university ice hockey players and their implications for lower back pain and leg injury. J Strength Cond Res 36(10): 2830-2836, 2022-Right to left asymmetries in body composition have been examined across many sports, suggesting possible implications for lower back pain (LBP) and decreased level of performance. However, we are not aware of any study that has examined the presence and implications of morphological asymmetries in ice hockey players. The purpose of this study was to (a) investigate body composition asymmetries in female and male university-level ice hockey players and (b) examine whether the degree of body composition asymmetry is associated with the history of LBP and lower-limb injury (LLI). A total of 32 players (female = 18, male = 14) were included in this cross-sectional study (e.g., university research center setting). Dual-energy X-ray absorptiometry (DEXA) was used to acquire body composition measurements. The parameters of interest included bone mass, lean body mass, and fat mass, for the right and left sides and body segments (e.g., arm, leg, trunk, and total), separately. The history of LBP and LLI was obtained using a self-reported demographic questionnaire. The statistical significance for the study was set at p < 0.05. Our findings revealed significant side-to-side asymmetry in arm and total bone mass in females, with higher values on the right side. Both males and females also had significantly greater trunk lean body mass on the left side. With the exception of greater arm bone mass asymmetry being associated with LBP in the past 3 months, there was no other significant association between the degree of asymmetry with LBP and LLI. This study provides novel data regarding the presence of asymmetry in body composition in university-level ice hockey players. Monitoring body composition in athletes provides information that can be used by athletic trainers and strength and conditioning coaches to develop injury prevention, performance optimization, and targeted rehabilitation programs.
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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 | 0.000 |
| 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) | 0.005 | 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".