The relation between breakfast consumption and psychological symptoms among adults
Bibliographic record
Abstract
Background: Breakfast skipping was related to obesity and obesity has been associated with psychological disorders, but limited data are available linking breakfast consumption to psychological symptoms. Objective: The association between breakfast consumption and psychological disorders, including depression and anxiety, was studied among Iranian adults. Methods: This cross-sectional study was conducted on 4378 healthy adults in Isfahan, Iran. Breakfast consumption was assessed using a validated detailed dietary habits’ questionnaire; and depression and anxiety using an Iranian validated Hospital Anxiety and Depression Scale (HADS) questionnaire. Psychological distress was also examined by means of Iranian validated version of General Health Questionnaire. Findings: Overall, 611 numbers (13.95%) of study participants had anxiety, 1253 numbers (28.62%) depression, and 1015 numbers (23.18%) probable mental disorders symptoms. After controlling for the confounding variables, participants with every day breakfast consumption had lower odds for depression symptoms (OR: 0.49; 95% CI: 0.36-0.66) compared with those with the least frequent intake of breakfast, even after further adjustment for BMI (OR: 0.47; 95% CI: 0.34- 0.63). Frequent breakfast consumption was inversely associated with anxiety before and after controlling for BMI (P<0.001). The same findings were obtained for probable mental disorders (P<0.001). Conclusion: This study showed an inverse relation between breakfast consumption and symptoms of depression, anxiety, and probable mental disorders among Iranian adults. Further prospective studies are needed to confirm these findings.
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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".