Alarming High Levels of Energy Drinks Consumption among School Children in Hail, Northern of Saudi Arabia
Bibliographic record
Abstract
Saudi Arabia (KSA) is one among the countries for top energy drink markets. Amid growing controversies globally surrounding the increasing usage of energy drinks by children, it is felt important to understand how these trends are reflected in KSA. A cross-sectional survey was conducted to explore the trends of energy drink consumption among, and differences between, middle and secondary school children, and the associated socioeconomic and behavioral factors. Randomly selected 1006 male children from secondary and middle schools from Hail region in KSA were included in the study, using a self-administered validated questionnaire. Results revealed that about 60% of school children were current energy drink consumers. Secondary school children were significantly (P<0.001) higher than middle schoolers in terms of both frequency and quantity. Concomitantly, unhealthy dietary and lifestyle behaviors were reported in significantly higher proportions (P<0.001) among secondary school children. Home was the first place for exposure for majority of children while unreliable resources were the major sources of knowledge about energy drink composition and health effects. Poor knowledge concerning energy drink composition was reported. Taste and being energized were the major driving forces for energy drink consumption. Higher disposable income on hand and poor lifestyle behaviors were all significantly associated with energy drink consumption. It can be concluded that high proportion of energy drink consumption was reported among school children in Hail, with higher proportions in secondary than middle schools. This matter raises the significance of mounting awareness of community concerning the ingredients and potential hazards of energy drinks.
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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 | 0.001 | 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) | 0.002 | 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".