Assessment of Food Cravings, Food Intake, and Weight Status Among Saudi Adults in Central and Western Regions of Saudi Arabia: A Retrospective, Cross-Sectional Study
Bibliographic record
Abstract
Mohammed Zaid Aljulifi,1 Atheer Ayed M Alshutayli,2 Ahmed Mohammed A Kaseb,3 Faisal Mohammed Asiri,4 Renad Ibrahim Alzahrani,5 Nawaf Amer H Alharbi,5 Ghadeer Yahya Almasabi,5 Mudhawi Faisal Alsuliman,6 Mohammad Shakil Ahmad,1 Riyaz Ahmed Shaik1 1Department of Family and Community Medicine, College of Medicine, Majmaah University, Majmaah, 11952, Saudi Arabia; 2College of Medicine, Qassim University, Qassim, Saudi Arabia; 3College of Medicine, Majmaah University, Majmaah, 11952, Saudi Arabia; 4College of Medicine, Prince Sattam bin Abdulaziz University, Al-kharj, Saudi Arabia; 5College of Medicine, Umm Alqura University, Makkah, Saudi Arabia; 6College of Medicine, King Faisal University, Al-Ahsa, Saudi ArabiaCorrespondence: Mohammed Zaid Aljulifi, Department of Family and Community Medicine, College of Medicine, Majmaah University, P O Box: 11952, Majmaah, Saudi Arabia, Email m.aljulifi@mu.edu.saPurpose: The aim of this study was to assess the frequency and intensity of food cravings among adults in Central and Western Saudi Arabia.Patients and Methods: This retrospective, cross-sectional study was conducted using online questionnaires. The collected data were analyzed using SPSS version 24.0.Results: A sample of 432 individuals was investigated, which was almost evenly split between men (50.5%) and women (49.5%). Body mass index (BMI) of most participants fell within the normal (31.9%) and overweight (32.6%) categories, highlighting a fairly balanced distribution of these BMI ranges. The obesity category included 24.5% of participants, raising concerns about potential obesity-related health issues. A significant proportion of participants had irregular meal-taking patterns. Overall, snacks and fruits were most frequently consumed daily, whereas eating with family was the least frequent activity. Finally, p-values from an assessment of food cravings and their effects on BMI indicated various levels of significance. Cravings for salty foods (p=0.008), the influence of emotional factors on food cravings (p=0.03), eating due to sadness even when not hungry (p=0.01), challenges in resisting or controlling food cravings (p=0.04), and feelings of guilt or regret after indulging in cravings (p=0.000) were all significant factors, suggesting potential links with BMI.Conclusion: Food craving involves a complex interplay of different factors, including emotional states and social cues, with varying levels of self-control and associated guilt or regret. Keywords: body mass index, obesity, meal-taking pattern, Food Cravings
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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 | 0.000 | 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".