Adolescent eating behaviors in the UAE
Bibliographic record
Abstract
BACKGROUND: Obesity is the single most burdensome lifestyle disease, which has reached epidemic proportions. This study aimed to examine the eating behavior patterns and beliefs in a group of adolescents living in the United Arab Emirates (UAE). PROCEDURE: A questionnaire was administered to adolescents (aged 11 and 18 years) attending outpatients' clinics at governmental health facilities. Informed consent was obtained, and the questionnaire was available in English or Arabic languages. RESULTS: In all, 36 adolescent subjects participated in our study with 12 males and 24 females. UAE nationals constituted 72% of our participants and 28% were of other ethnic backgrounds; 75% were overweight to obese with 17% normal and 8% underweight. The majority of patients were healthy with only 6 patients suffering chronic medical diseases. We uncovered that in less than half of our cohort, the decision to eat came directly from the individuals themselves, but it was more influenced by their families. Food consumption was largely in response to physical hunger with the sensation perceived in the upper abdomen by one-third and the remainder localizing it to various other areas. Excessive caloric intake with frequent meals and snacks was also reported. Our study subjects decided what to consume mainly based on what appeared appetizing, followed by availability and cravings and to a lesser extent based on health recommendations. Excessive speed of food ingestion was self-reported in the majority of participants. Moreover, almost half of the adolescents were unable to turn down food offerings from their close family members and over one-fourth were unable to refuse food from other persons. Common symptoms reported included dysphoric mood, disordered sleep, decreased energy and concentration difficulties as well as low self-esteem. CONCLUSION: Our study uncovered certain eating behaviors in the cohort of adolescents, which may be important in promoting weight gain. These included misconceived hunger signals, excessive frequency, amount and speed of food consumption as well as more focus on food taste, inattentiveness to cravings and a strong social influence on food intake decisions. The findings of our study aim to shed some light on the eating patterns among adolescents and encourage research to investigate eating behaviors on an expanded scale evaluating ethnic, gender and age-related differences.
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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 | 0.000 | 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".