The Mediterranean Athlete’s Nutrition: Are Protein Supplements Necessary?
Bibliographic record
Abstract
(1) Background: It is recommended that an athlete, in order to ensure correct nutrition and performance, should consume between 1.2 and 2.0 g/kg/day of protein, while the daily recommended protein intake for a non-athlete is 0.8and 0.9 mg/kg/day. It is unclear if athletes living in Mediterranean countries are able to meet protein requirements without supplementation, since Mediterranean diet de-emphasizes meat and meat products. (2) Methods: 166 athletes (125 males) enrolled between 2017 and 2019 were required to keep a dietary journal for three consecutive days (2 workdays and 1 weekend day). Athletes had to be >18 years old, train in a particular sport activity more than 3 h a week and compete at least at an amateur level. Journal data were collected and then translated into macro-nutrient content (grams of protein, carbohydrates, and lipids) by a nutritionist. (3) Results: The protein intake reported by this specific population vary slightly from the Academy of Nutrition and Dietetics (AND), Dietitians of Canada (DC), and the American College of Sports Medicine (ACSM) joint statement recommendation level. Average protein levels without protein supplementation fell within the protein guidelines. Counterintuitively, the intake among those who supplemented their diet with protein was higher compared with those who did not, even when excluding the contribution of supplements. Although the majority of subjects participating in the study were able to meet protein intake recommended for athletes without protein supplementation, 27% of athletes were below the guideline range. (4) Conclusions: these data suggest that athletes' nutrition should be more often evaluated by a nutritionist and that they will benefit from increasing their nutritional knowledge in order to make better food choices, resorting to protein supplementation only when effectively needed.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".