Association between dietary behaviors and depression in adolescent girls
Bibliographic record
Abstract
BACKGROUND: The growing prevalence of depression has become a major public health problem. There is limited evidence regarding the relationship between dietary behaviors and depression. The present study was designed to evaluate the association between dietary behaviors and depression score. METHODS: A total of 933 Iranian adolescent girls aged 12 to 18 years were included in this cross-sectional study. Depression severity score was assessed using a validated Persian version of Beck's depression inventory. Dietary behaviors were pre-defined and assessed in ten domains using a standard questionnaire. To investigate the association between dietary behaviors and depression score, the linear regression analysis in crude and adjusted models was used. RESULTS: 67.7% of participants had no or minimal depression symptoms and 32.3% of participants were categorized with mild-to-severe depression symptoms. There were significant inverse relationships between main meal consumption (Beta: -0.141; 95% CI: - 3.644 to - 1.000; P = 0.001), snack consumption (Beta: -0.100; 95% CI: - 2.400 to - 0.317; P = 0.002), regular meal consumption (Beta: 0.23; 95% CI: 0.13-0.42; P = 0.001) and food chewing (Beta: -0.152; 95% CI: - 2.279 to - 0.753; P = 0.03) with depression score. These associations remained significant after adjustment for confounding variables. In addition, frequency of intra-meal fluid intake (Beta: 0.096; 95% CI: 0.288 to 1.535; P = 0.004) and spicy foods consumption (Beta: 0.076; 95% CI: 0.098 to 1.508; P = 0.02) were directly associated with depression score in the crude model. These significant relations were disappeared in full adjusted model. No significant association was found between breakfast consumption, intake of fried foods, chewing ability, and tooth loss with depression score (P > 0.05). CONCLUSIONS: Significant associations were observed between specific eating behaviors with depression score. 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 | 0.000 |
| 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) | 0.002 | 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".