Effect Of Water-loading On Weight Cutting And Performance In Elite Judo Athletes
Bibliographic record
Abstract
The use of water-loading to enhance weight cutting is getting increasingly popular in combat and weight category sports. Athletes are overdrinking water in order to increase urine production before engaging in a fluid restriction period in the belief that it will maximise fluid driven body mass loss. Research into this practice is lacking and further investigation is needed. PURPOSE: Determine the impact of a water-loading protocol in combination with dietary adjustments on acute body mass loss, natremia, urinary markers of hydration and arm crank performance in elite judo athletes. METHODS: Using a crossover design, 18 elite male judo athletes underwent 2, 6 days interventions interspersed by a washout period of 2 weeks. While following a controlled diet, athletes consumed either 40 mL/kg (control condition (CON)) or 80 mL/kg (water loading condition (WL)) on days 1-3, followed for both conditions by a fluid intake of 20 mL/kg on day 4. On day 5, fluid was restricted until 11h00, body mass was then measured and for the remaining of the day athletes consumed 60 mL/kg of fluid. On day 6, fluid was consumed ad libitum and arm crank performance measured between 9h00-12h00. RESULTS: Water-loading (2.4 ± 0.5%) produced a significantly (p = 0.03, effect size = 0.7) greater decrease in body mass, compared with CON (1.8 ± 0.5%). Urine specific gravity and osmolality became progressively lower over time with WL (p < 0.05), compared with CON. However, whole blood sodium concentration remained within the physiological range of 135-145 mmol/L throughout the WL condition. There were no significant differences in arm crank performance for maximum power (CON: 663 ± 103, WL: 677 ± 95 W) and mean power (CON: 330 ± 32, WL: 335 ± 35 W). CONCLUSION: Our results indicate that the water-loading protocol used in this study 1) improves acute body mass loss without affecting health or arm crank performance and; 2) should be considered by combat sports athletes looking to improve their weight cutting practices. Funding information : 1) Own the Podium i4G applied research program 2) INS Quebec PRIDI research grant
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".