Dietary Patterns and Major Depression: Results from 15,262 Participants (International ALIMENTAL Study)
Bibliographic record
Abstract
BACKGROUND: Different patterns of food consumption may be associated with a differential risk of depression. Differences in dietary patterns between men and women and across different age groups have been reported, but their influence on the risk of depression has not been fully explored. OBJECTIVES: To investigate the associations between dietary patterns and risk of depression across sex and age groups to identify vulnerable subpopulations, which may inform targeted prevention and intervention strategies. METHODS: The ALIMENTAL study was a cross-sectional, online international survey conducted between 2021 and 2023. Dietary data were collected using a validated food frequency questionnaire; depression data were collected using a self-reported validated questionnaire. Principal component analysis (PCA) was applied to identify distinct food consumption patterns. Multivariate analyses were then conducted to assess the associations between these patterns and depression, adjusting for multiple potential confounders. RESULTS: Among 15,262 participants without chronic diseases or current psychotropic treatments, 4923 (32.2%) were classified in the depression group. Among those aged 18-34, the PCA-derived factor of ultra-processed foods consumption was significantly associated with increased risk of depression in both sexes with similar odds ratios (women 1.21, 95% confidence interval (CI): (1.15; 1.27), men 1.21, 95% CI: (1.07-1.18)). In women aged 18-34, the PCA factors for sodas (aOR 1.10, 95% CI: (1.06; 1.95) and canned and frozen foods (aOR 1.10, 95% CI: (1.04; 1.15) were associated with an increased risk of depression. In participants aged 35-54 years, the association between ultra-processed foods and depression was only observed in women (35-54 years: aOR 1.30, 95% CI: (1.20; 1.42), ≥55 years: 1.41, 95% CI: (1.11; 1.79)), with a significant association between a higher adherence to the PCA-derived "healthy diet" factor (e.g., fruits, nuts, green vegetables) and a lower risk of depression (35-54 years: aOR 0.82, 95% CI: (0.75; 0.89), ≥55 years: aOR 0.79, 95% CI: (0.64; 0.97)). CONCLUSIONS: These results show significant differences between men and women and between age groups regarding associations between dietary patterns and the risk of depression. These findings can help better target public health interventions.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".