The Socio-Economic Determinants of Energy Drink Consumption and Related Health Outcomes in Riyadh, Saudi Arabia
Bibliographic record
Abstract
OBJECTIVE: To estimate the prevalence and socio-economic determinants of energy drink (ED) consumption and related health outcomes in Riyadh, Saudi Arabia. METHODS: A self-report survey was used to collect data from 2,024 students (aged 13-20 years). Logistic regression was used to determine the relationship between ED consumption, diet and health-related outcomes. RESULTS: In total, 54% of young people reported ED consumption at least once and 25.5% at least weekly. The most common (38.65%) reason for ED consumption was the enjoyable flavour. Male students reported higher ED consumption compared to females (OR = 1.26, 95% CI 1.08 to 1.46). ED consumption was associated with an unhealthy diet (OR = 1.69, 95% CI 1.53 to 1.87), tobacco use (OR = 5.91, 95% CI 3.47 to 10.07), poor quality sleep (OR = 0.73, 95% CI 0.47 to 0.99). Those who regularly ate breakfast were less likely to report ED consumption (OR = 0.89, 95% CI 0.83 to 0.95). CONCLUSION: More than 1 in 2 young people reported ED consumption among a sample of Riyadh-based students. Consumption was found to be associated with a poor-quality diet and negative health outcomes. Findings suggest that there is a public health need to reduce the consumption of EDs among this population.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".