Case Study: Impact of Inter- and Intra-Day Energy Parameters on Bone Health, Menstrual Function, and Hormones in an Elite Junior Female Triathlete
Bibliographic record
Abstract
This observational case study examined the association of inter- and intraday energy intake and exercise energy expenditure with bone health, menstrual status and hematological factors in a female triathlete. The study spanned 7 months whereby energy intake and exercise energy expenditure were monitored three times (13 d); 16 blood samples were taken, urinary hormones were assessed for 3 months, and bone mineral density was measured twice. Energy availability tended to be sustained below 30 kcal/kg FFM/d and intraday energy intake patterns were often "back-loaded" with approximately 46% of energy consumed after 6 p.m. Most triiodothyronine values were low (1.1-1.2nmol/L) and supportive of reduced energy availability. The athlete had suppressed estradiol (105.1 ± 71.7pmol/L) and progesterone (1.79 ±1.19nmol/L) concentrations as well as urinary sex-steroid metabolites during the entire monitoring period. Lumbar spine (L1-L4) bone mineral density was low (age-matched Z-score -1.4 to -1.5). Despite these health related maladies the athlete was able to perform typical weekly training loads (swim: 30-40 km, bike: 120-300 km, run 45-70 km) and was competitive as indicated by her continued improvement in ITU World Ranking during and beyond the assessment period. There is a delicate balance between health and performance that can become blurred especially for endurance athletes. Education (athletes, coaches, parents) and continued monitoring of specific indicators will enable evidence-based recommendations to be provided and help reduced the risk of health related issues while maximizing performance gains. Future research needs to longitudinally examine how performance on standardized tests in each discipline (e.g., 800-m swim, 20-km time trial, 5-km run) is impacted when aspects of the female athlete triad are present.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".