Serum androgen profile and physical performance in women Olympic athletes
Bibliographic record
Abstract
BACKGROUND: The role of endogenous androgens for body composition and physical performance in women athletes is still not elucidated. AIM: To examine the serum androgen profile in relation to body composition and physical performance in women Olympic athletes and to compare endocrine variables and body composition to controls. STUDY DESIGN: Cross-sectional study, conducted between 2011 and 2015 at the Women's Health Research Unit, Karolinska University Hospital, Stockholm. METHODS: Swedish women Olympic athletes (n=106) and age-matched and body mass index-matched sedentary controls (n=117) were included in the study. Blood sampling was performed in a rested, fasting state for the measurement of serum androgens and their metabolites by liquid chromatography-tandem mass spectrometry. Body composition was determined by dual-energy X-ray absorptiometry (controls n=100, athletes n=65). The athletes performed standardised performance tests (n=59) (squat jump (SJ) and countermovement jump (CMJ). RESULTS: The athletes demonstrated significantly higher levels of the precursor androgens dehydroepiandrosterone (DHEA) and 5-androstene-3β, 17β-diol (5-DIOL) and the metabolite etiocholanolone glucuronide (Etio-G), significantly lower levels of estrone (p<0.05, respectively), higher bone mineral density (p<0.001) and more lean mass (p<0.001) compared with controls. Serum levels of DHEA, 5-DIOL and Etio-G correlated positively to lean mass variables and physical performance in the athletes. DHEA and lean mass legs explained 66% of the variance in SJ, whereas lean mass explained 52% of the variance in CMJ. CONCLUSIONS: The present data suggest that endogenous androgens are associated with a more anabolic body composition and enhanced performance in women athletes. These results are of importance for the current discussion regarding hyperandrogenism in women athletes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".