The association between dietary intake of magnesium and psychiatric disorders among Iranian adults: a cross-sectional study
Bibliographic record
Abstract
Findings from clinical trials on the effect of Mg supplementation on depression and anxiety are not generalisable to the community owing to high-dose intervention in short-term periods. Limited observational data are available linking dietary intake of Mg and psychiatric disorders. We aimed to investigate the association between dietary intake of Mg and psychiatric disorders in a large cross-sectional study on Iranian adults. A total of 3172 Iranian adults (with an age range of 18-55 years) were included in this study. Data on dietary intakes were collected using a validated dish-based 106-item semi-quantitative FFQ. To assess depression and anxiety, an Iranian validated version of the Hospital Anxiety and Depression Scale was used. Furthermore, psychological distress was examined using the General Health Questionnaire. The mean age of men and women was 38·4 (sd 8·2) and 35·1 (sd 7·4) years, respectively. In unadjusted analyses, we found that higher dietary Mg intake was associated with lower odds of anxiety among women (OR 0·61; 95 % CI 0·41, 0·90), such that after taking potential confounders into account women in the highest quintile of Mg intake had a 39 % lower odds of anxiety compared with those in the lowest quintile (OR 0·61; 95 % CI 0·40, 0·93). Moreover, deficient Mg intake was positively associated with anxiety among all women (OR 1·80; 95 % CI 1·19, 2·72) and also normal-weight women (OR 1·73; 95 % CI 1·01, 2·95). In addition, a significant inverse association was found between dietary Mg intake and depression among normal-weight men (OR 0·45; 95 % CI 0·20, 0·99) and overweight women (OR 0·45; 95 % CI 0·24, 0·85). In conclusion, dietary intake of Mg was inversely associated with depression and anxiety. However, such findings were not seen for psychological distress.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".