Association of dietary phytochemical index and mental health in women: a cross-sectional study
Bibliographic record
Abstract
Previous studies have shown that unhealthy dietary patterns are among the most important modifiable risk factors in the development of mental health disorders. We examined the association of dietary phytochemical index (DPI) with symptoms of depression, anxiety and psychological distress in Iranian women. In this cross-sectional study, a total of 488 women aged 20-50 years old attending health centres in the south of Tehran in 2018 were included. A validated and reliable FFQ was used for dietary assessment. Symptoms of depression, anxiety and psychological distress were assessed using a validated depression, anxiety, stress scales questionnaires with twenty-one-items. DPI was estimated using the following formula: (daily energy derived from phytochemical-rich foods (kJ)/total daily energy intake (kJ))×100. The mean age of the study participants was 31·9 (sd 7·7) years. The prevalence of depressive symptoms, anxiety and psychological distress among study participants was 34·6, 40·6 and 42·4 %, respectively. After controlling for potential confounders, women in the highest tertile of DPI had a lower prevalence of depressive symptoms (OR 0·22; 95 % CI 0·12, 0·38) and anxiety (OR 0·33; 95 % CI 0·20, 0·55), as well as psychological distress (OR 0·30; 95 % CI 0·18, 0·49) compared with those in the lowest tertile. In conclusion, we found a significant association between DPI and mental health in women. Prospective studies are needed to confirm these findings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".