Ovarian Suppression Impairs Sport Performance in Junior Elite Female Swimmers
Bibliographic record
Abstract
INTRODUCTION: Competitive female athletes restrict energy intake and increase exercise energy expenditure frequently resulting in ovarian suppression. The purpose of this study was to determine the impact of ovarian suppression and energy deficit on swimming performance (400-m swim velocity). METHODS: Menstrual status was determined by circulating estradiol (E2) and progesterone (P4) in ten junior elite female swimmers (15-17 yr). The athletes were categorized as cyclic (CYC) or ovarian-suppressed (OVS). They were evaluated every 2 wk for metabolic hormones, bioenergetic parameters, and sport performance during the 12-wk season. RESULTS: CYC and OVS athletes were similar (P > 0.05) in age (CYC = 16.2 ± 1.8 yr, OVS = 17 ± 1.7 yr), body mass index (CYC = 21 ± 0.4 kg·m, OVS = 25 ± 0.8 kg·m), and gynecological age (CYC = 2.6 ± 1.1 yr, OVS = 2.8 ± 1.5 yr). OVS had suppressed P4 (P < 0.001) and E2 (P = 0.002) across the season. Total triiodothyronine (TT3) and insulin-like growth factor (IGF-1) were lower in OVS (TT3: CYC = 1.6 ± 0.2 nmol·L, OVS = 1.4 ± 0.1 nmol·L, P < 0.001; IGF-1: CYC = 243 ± 1 μg·mL, OVS = 214 ± 3 μg·mL P < 0.001) than CYC at week 12. Energy intake (P < 0.001) and energy availability (P < 0.001) were significantly lower in OVS versus CYC. OVS exhibited a 9.8% decline in Δ400-m swim velocity compared with an 8.2% improvement in CYC at week 12. CONCLUSIONS: Ovarian steroids (P4 and E2), metabolic hormones (TT3 and IGF-1), and energy status markers (EA and EI) were highly correlated with sport performance. This study illustrates that when exercise training occurs in the presence of ovarian suppression with evidence for energy conservation (i.e., reduced TT3), it is associated with poor sport performance. These data from junior elite female athletes support the need for dietary periodization to help optimize energy intake for appropriate training adaptation and maximal sport performance.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".