Short Severe Energy Restriction with Refueling Reduces Body Mass without Altering Training-Associated Performance Improvement
Bibliographic record
Abstract
PURPOSE: We investigated short-term (9 d) exposure to low energy availability (LEA) in elite endurance athletes during a block of intensified training on self-reported well-being, body composition, and performance. METHODS: Twenty-three highly trained race walkers undertook an ~3-wk research-embedded training camp during which they undertook baseline testing and 6 d of high energy/carbohydrate (HCHO) availability (40 kcal·kg FFM -1 ·d -1 ) before being allocated to 9 d continuation of this diet ( n = 10 M, 2 F) or a significant decrease in energy availability to 15 kcal·kg FFM -1 ·d -1 (LEA: n = 10 M, 1 F). A real-world 10,000-m race walking event was undertaken before (baseline) and after (adaptation) these phases, with races being preceded by standardized carbohydrate fueling (8 g·kg body mass [BM] -1 for 24 h and 2 g·kg BM -1 prerace meal). RESULTS: Dual-energy x-ray absorptiometry-assessed body composition showed BM loss (2.0 kg, P < 0.001), primarily due to a 1.6-kg fat mass reduction ( P < 0.001) in LEA, with smaller losses (BM = 0.9 kg, P = 0.008; fat mass = 0.9 kg, P < 0.001) in HCHO. The 76-item Recovery-Stress Questionnaire for Athletes, undertaken at the end of each dietary phase, showed significant diet-trial effects for overall stress ( P = 0.021), overall recovery ( P = 0.024), sport-specific stress ( P = 0.003), and sport-specific recovery ( P = 0.012). However, improvements in race performance were similar: 4.5% ± 4.1% and 3.5% ± 1.8% for HCHO and LEA, respectively ( P < 0.001). The relationship between changes in performance and prerace BM was not significant ( r = -0.08 [-0.49 to 0.35], P = 0.717). CONCLUSIONS: A series of strategically timed but brief phases of substantially restricted energy availability might achieve ideal race weight as part of a long-term periodization of physique by high-performance athletes, but the relationship between BM, training quality, and performance in weight-dependent endurance sports is complicated.
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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 | 0.000 |
| 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) | 0.002 | 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 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".