Beyond Menstrual Dysfunction: Does Altered Endocrine Function Caused by Problematic Low Energy Availability Impair Health and Sports Performance in Female Athletes?
Bibliographic record
Abstract
Low energy availability, particularly when problematic (i.e., prolonged and/or severe), has numerous negative consequences for health and sports performance as characterized in relative energy deficiency in sport. These consequences may be driven by disturbances in endocrine function, although scientific evidence clearly linking endocrine dysfunction to decreased sports performance and blunted or diminished training adaptations is limited. We describe how low energy availability-induced changes in sex hormones manifest as menstrual dysfunction and accompanying hormonal dysfunction in other endocrine axes that lead to adverse health outcomes, including negative bone health, impaired metabolic activity, undesired outcomes for body composition, altered immune response, problematic cardiovascular outcomes, iron deficiency, as well as impaired endurance performance and force production, all of which ultimately may influence athlete health and performance. Where identifiable menstrual dysfunction indicates hypothalamic-pituitary-ovarian axis dysfunction, concomitant disturbances in other hormonal axes and their impact on the athlete's health and sports performance must be recognized as well. Given that the margin between podium positions and "losing" in competitive sports can be very small, several important questions regarding low energy availability, endocrinology, and the mechanisms behind impaired training adaptations and sports performance have yet to be explored.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".