Completely Plant-Based Diets That Meet Energy Requirements for Resistance Training Can Supply Enough Protein and Leucine to Maximize Hypertrophy and Strength in Male Bodybuilders: A Modeling Study
Bibliographic record
Abstract
Despite increasing awareness of plant-based diets for health and athletic performance, athletes are cautioned that careful dietary monitoring is necessary. Whether commonly consumed plant-based diets are nutritionally adequate for maximal muscular hypertrophy remains unknown. This modeling study assessed the nutrient composition of completely plant-based diets scaled to the caloric demands of maximal muscle mass and strength development in adult male bodybuilders. To model calorie requirements, anthropometric data from bodybuilders were input into the Tinsley resting metabolic rate prediction equation, and an appropriate physical activity factor and calorie surplus were applied. Dietary data from a large cohort following completely plant-based diets were then scaled to meet these needs. Modeled intakes for nutrients of interest were calculated as 1.8 g/kg/day of protein and 2.75 g/meal of leucine, which surpass mean requirements for maximal increases in muscle mass and strength and muscle protein synthesis, respectively. Daily levels for all micronutrients, except vitamin D, also exceeded requirements. Saturated fat levels were aligned with dietary guidelines, although sodium levels exceeded recommended limits. Consumption of larger portions of commonplace plant-based diets, scaled to meet the energy demands of maximal accrual of muscle mass and strength, satisfied protein and leucine requirements without the need for additional planning.
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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 | 0.001 |
| 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".