The prevalence and characterisation of energy drink consumption in North America: A systematic review
Bibliographic record
Abstract
OBJECTIVES: Energy drinks (ED), which contain high levels of caffeine, are widely popular and their consumption is increasing, especially among young people who may have limited understanding of the associated risks. The aim of this study was to identify the prevalence of ED consumption in North America (Canada, Mexico and the US) and to characterise ED consumers. STUDY DESIGN: Systematic review. METHODS: A systematic review of studies estimating the prevalence of ED consumption was conducted. The characteristics of the studies, populations included, consumption assessment and prevalence of consumption were recorded. Study quality was evaluated using an adaptation of the Newcastle-Ottawa scale. A descriptive analysis of the results was performed. RESULTS: In total, 91 studies conducted in North America were included. All studies were of low to moderate quality. The prevalence of ED consumption was assessed using different temporalities in different studies, which made it impossible to reach a conclusion about the prevalence in North America. Across all populations and temporalities, a considerable range of ED prevalence was observed. It is noteworthy that in studies of university students, weekly ED consumptions >60 % were reported. ED consumption was associated with being male and the co-consumption of alcohol, tobacco and marijuana or cannabis. CONCLUSIONS: Results show that ED consumption was highly heterogeneous and widely prevalent, especially among younger populations. This review provides information to help guide and design appropriate public health measures and strategies.
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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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".