Global trends in caffeine consumption and its sources in children, adolescents and adults
Bibliographic record
Abstract
Introduction: The aim of this study was to examine current trends in daily caffeine consumption, and its sources in children, adolescents and adults. Methods: A literature search was conducted to identify nationally representative surveys on caffeine intake and its sources, collected over the last decade. Results: Over the past decade, data on caffeine consumption of over N=100.000 children, adolescents, adults and elderly has been gathered in USA, Europe, Asia and Australia. Discussion and Conclusions: Mean intake across all age groups is in line with recommendations of EFSA and Health Canada, and total daily caffeine intake over the past decade remained stable. Implications for Practice or Policy: Efforts to better inform consumers about their daily caffeine consumption would benefit from labelling of caffeine levels in coffee, tea and carbonated soft drinks, since together these beverages contribute to more than 90% of total daily caffeine consumption.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".