Evaluation of Nutritional Intake in Canadian High-Performance Athletes
Bibliographic record
Abstract
OBJECTIVE: To determine the nutritional intake of Canadian high-performance athletes. DESIGN: Prospective survey study. SETTING: Canadian sport center athletes. PARTICIPANTS: Three hundred twenty-four high-performance athletes (114 males and 201 females; mean age 21.3 +/- 13 years) from 8 Canadian sport centers participated in the study. INTERVENTION: Subjects prospectively completed 3-day dietary records, reporting all food, fluid, and supplement consumption. MAIN OUTCOME MEASURES: Dietary records were analyzed for total calories, macronutrients, and micronutrients for food alone and food plus supplements for all subjects collectively and according to gender and competitive event. RESULTS: Average daily energy intake was 2533 +/- 843 Kcal/day with males consuming more calories than females (2918 +/- 927 and 2304 +/- 713 Kcal/day, respectively; P < 0.05). Both genders consumed below recommended levels. Carbohydrate, protein, and fat accounted for 53%, 19%, and 28% of daily calorie intake, respectively. Average daily carbohydrate and protein intake was 5.1 +/- 1.8 and 1.8 +/- 0.6 g/kg body weight, respectively. Protein intake, but not carbohydrate intake, met recommendations. Supplementation significantly increased athletes' energy, total carbohydrate, protein, and fat intake. Of 17 micronutrients assessed, intake ranged between 120% and 366% of recommended daily intake with food alone and between 134% to 680% of recommended daily intake with supplements. CONCLUSIONS: Canadian high-performance athletes do not consume adequate energy or carbohydrates. However, their intake of micronutrients exceed current recommended daily intakes, even when supplements are not considered, indicating that athletes make high-quality food choices. Supplementation significantly increased energy, macronutrient, and micronutrient intake.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".