The Influence Of Menstrual Status On Lower Body Plyometric Performance In Female Rugby League Athletes
Bibliographic record
Abstract
Oestrogen may modulate force development through alterations to muscle contractile properties. However, whether menstrual cycle (MC) phase or hormonal contraceptive (HC) use influences plyometric performance is inconclusive, in part due to the poor assessment of hormonal profiles. PURPOSE: To examine plyometric performance across the MC and between naturally menstruating athletes and HC users, employing gold standard protocols regarding menstrual status. METHODS: Eighteen Tier 2-3 National Rugby League Indigenous Women’s Academy athletes [n = 7 naturally menstruating, 21 ± 4 yr, 71.5 ± 8.4 kg vs n = 11 HC users (n = 7 implant, n = 3 combined oral contraceptive pill, n = 1 injection), 22 ± 4 yr, 77.2 ± 12.8 kg], attended a 5-week training camp. Plyometric tests implementing 3 repetitions of the countermovement jump (CMJ) and squat jump (SJ) on a force plate were completed at MC phase 1 (low oestrogen/progesterone concentrations) and 4 (higher oestrogen/progesterone) by naturally menstruating athletes, with HC users tested at two equally spaced time points, avoiding the withdrawal bleed. MC phase was assessed via; onset of menstruation, 8 weeks of MC tracking, urinary ovulation kits and retrospective phase confirmation through serum oestrogen and progesterone concentrations. The highest jump at each test was analysed within individuals and between groups using linear mixed models. RESULTS: Jump height, force, velocity and rate of force development did not differ across MC phase or between groups (p > 0.05). However, naturally menstruating athletes produced greater impulse at 50 ms in phase 4 (37.9 ± 8.1 Ns) than phase 1 (37.2 ± 5.8 Ns, p = 0.045) during the SJ, although there were no differences at 100, 150 or 200 ms (p > 0.05). Additionally, relative mean power was greater in phase 4 (2.85 ± 0.45 W·kg-1) than phase 1 (2.44 ± 0.40 W·kg-1, p = 0.021) in the CMJ. CONCLUSION: Our findings suggest that MC phase and HC use may not alter absolute plyometric performance. However, MC phase may influence early (50 ms) force expression in the SJ and mean power output in the CMJ. Further research including other MC phases is required to fully understand the effects of oestrogen and elucidate underpinning mechanisms.This project was funded by the Australian Catholic University, Wu Tsai Human Performance Alliance and Australian Institute of Sport.
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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 | 0.000 | 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) | 0.001 | 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".