Obesity and Body Image Perception among the Community in Saudi Arabia: A Mini Literature Review
Bibliographic record
Abstract
Background: Obesity is a risk factor for several deadly diseases that have a substantial adverse influence on health. The early onset of diabetes, polycystic ovaries, hypertension, and other disorders are among the recent error number of problems that are a tracking factor for health. Individual obesity is the root cause of all these issues, particularly among young people. Aim: Based on current publications, this study aims to ascertain the prevalence rate of obesity and related risk factors among Saudi Arabian students. Method: A qualitative review of the literature was carried out by operationalizing the internet search engines Pub Med, Science Direct, Google Scholar, and Research Gate. Studies combine all the relevant information from 10 publications on obesity and students' body perceptions. All primary studies were carried out in English between 2017 and 2021. Conclusion: Obesity and body image perception are the most influential factors in a student's social life. These issues have an impact on the academic period as well. The study found that students' perceptions of body image and obesity influenced their participation in academic and extracurricular activities and various school management programs regarding expertise, performance, and selection criteria. It should be noted that school-age children should keep their diet and eating habits to protect themselves from the outside world, including social interaction, pathogens, and others.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".