Caffeine intake and its sources: A review of national representative studies
Bibliographic record
Abstract
Aim of this review is to summarize current daily caffeine intake of children, adolescents, and adults, and trends in caffeine intake over the past decade. A literature search was conducted (1997-2015) which yielded 18 reports on nationally representative studies, describing caffeine consumption of over 275,000 children, adolescents and adults. The data revealed that mean total daily caffeine intake in children, adolescents, and adults is below caffeine intake recommendations such as those stated by Health Canada (2.5 mg/kg bw/day for children and adolescents, and 400 mg/day for adults) and the European Food Safety Authority, EFSA (3 mg/kg bw/day for children and adolescents, and 400 mg/day for adults). Total daily caffeine intake has remained stable in the last 10-15 years, and coffee, tea and soft drinks are the most important caffeine sources. Across all age groups, energy drinks contribute little to total caffeine intake. The highest potential for reducing daily caffeine intake is by limiting coffee consumption, and in some countries and age groups, by reducing tea and soft drink consumption.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".