Lean Mass, Muscle Strength, and Muscle Quality in Retired Rugby Players: The UK Rugby Health Project
Bibliographic record
Abstract
Abstract Although athletes from sports such as rugby have greater lean mass and strength during their playing careers, little is known about these characteristics post-retirement. Therefore, this study investigated lean mass, strength, and muscle quality in retired elite and amateur rugby players and non-contact athletes. Retired elite male rugby players (n=42, 43.9±10.3 y; 101.1±13.4 kg; 1.82±0.09 m), amateur rugby players (n=46, 48.0±10.5 y; 98.9±16.6 kg; 1.79±0.07 m) and non-contact athletes (n=30, 51.3±12.5 y; 91.3±13.4 kg; 1.79±0.07 m) received one total body dual-energy X-ray absorptiometry assessment of appendicular lean mass (ALM) and ALM index (ALMI). Grip strength was measured, and muscle quality (grip strength/unit of arm lean mass) was calculated. Sarcopenia was identified as ALMI<7.23 kg/m2 and handgrip strength<37.2 kg. Total lean mass, ALM and grip strength were greater in the elite rugby compared to amateur rugby and non-contact groups (p<0.01). There were no significant differences in muscle quality or sarcopenia prevalence. Retired elite rugby players had greater lean mass and grip strength than amateur rugby and non-contact athletes, although muscle quality was similar. The greater lean mass and strength might reflect genetic influences or previous participation in a highly physical sport.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".