Exploring the link among eating behaviour, diet quality, and relative energy deficiency in sports risk in elite Canadian volleyball male athletes
Bibliographic record
Abstract
Abstract Male volleyball athletes may be at risk of inadequate energy and carbohydrate intake. This may increase their risk of relative energy deficiency in sport (REDs) and impair a variety of physiological and psychological systems involved with performance and health. This study explored the eating behaviours and diet quality of international elite volleyball male athletes and their association on hormones associated with acute energy deficit and primary serum REDs indicators outlined in the International Olympic Committee REDs Clinical Assessment Tool 2. Methods: Using a retrospective design, 30 male athletes from a national indoor volleyball programme were assessed using DXA bone mineral density, hematological analysis, anthropometry, restrained eating behaviour via the Three-Factor Eating Questionnaire-R18 and the Athlete Diet Index (ADI) questionnaire. Results: All participants met or exceeded dietary recommendations for health and sport with ADI mean score of 95.2/125 ± 10.5. Restraint eating was inversely associated with insulin ( r = − 0.37; p < 0.05). Both the ADI total and core nutrition sub-scores were inversely associated with free-triiodothyronine ( r = − 0.58; p < 0.01) but not with total testosterone, insulin or leptin. Conclusion: Male volleyball athletes at risk of inadequate energy intake may not necessarily demonstrate signs of poor diet quality.
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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 | 0.001 | 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".