Consumption of dietary caffeine and coffee in physically active populations: physiological interactions
Bibliographic record
Abstract
Caffeine is a proven ergogenic aid, increasing athletic performance, endurance, and mental chronometry at doses as low as 1-3 mg.kg-1. As coffee is a readily available and commonly ingested form of caffeine, the two are often equated. However, coffee also contains hundreds of other biologically active compounds, many of which are metabolically distinct from caffeine. The purpose of this review was to examine the prevalence of coffee and (or) caffeine consumption among elite Canadian athletes, and to delineate the effects of coffee and caffeine on physical activity, weight maintenance, performance, and metabolism. A total of 270 self-reported 3-day food records were examined for caffeine intake from athletes registered with Canadian Sport Centres in 2005 and 2006. Athletes ranged in age from 16-45 years, and competed in 38 different sports. Results showed that 30% of athletes ingested >1 mg.kg-1.day-1 from a variety of sources. Average daily intake was 0.85 +/- 13 mg.kg-1. Caffeine intake was not correlated with any 1 sport; the 10 highest caffeine users were athletes from 9 different sports, including skill, endurance, and power sports. No differences were noted for average caffeine ingestion between summer and winter sports. High caffeine intakes corresponded to coffee ingestion, with the 25 highest individual intakes (193-895 mg.day-1) from coffee drinkers. In summary, it can be concluded that the majority of high-level Canadian athletes consume dietary caffeine primarily in the form of coffee. However, levels consumed are insufficient to elicit performance enhancement. Potential detrimental effects of caffeine consumption on exercise performance include gastric upset, withdrawal, sleep disturbance, and interactions with other dietary supplements.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".