The adherence to Mediterranean diet moderates the association between medical multi-morbidity and depressive symptoms in elderly outpatients
Bibliographic record
Abstract
Background \nDepressive symptoms in the elderly are related to the advancing of age, loss of life purpose, medical multi-morbidity, cognitive decline and social-economic problems mounting evidence suggests that lifestyle behaviors and certain dietary patterns may improve mood and overall well-being in older adults. In the present study we investigated (i) the association of adherence to Med-Diet with depressive symptoms and multi-morbidity in a cohort of geriatric medical outpatients and (ii) the role of Med-Diet in mediating the association between depressive symptoms and multi-morbidity. \n \nMethods \nMorbidity was assessed using the severity index of cumulative illness rating scale for geriatrics (CIRSG-SI). Montreal cognitive assessment (MoCA) and geriatric depression scale (GDS) were administrated to evaluate cognitive and depressive symptoms. Adherence to Med-Diet was evaluated using the Med-Diet 14-Item questionnaire (MDQ). Pearson correlation was used to test association between variables. The Preacher and Hayes’ strategy was used to test the mediational model. \n \nResults \nOne hundred and forty-three subjects were included in the study. Significant inverse correlations of MDQ with GDS (r = -0.317; P < 0.001) and CIRSG-SI (r = -0.247; P = 0.003) were found, with and without adjustment for potential confounders. A direct correlation between CIRSG-SI and GDS was also observed (r = 0.304; P = 0.001), with this association being moderated by MDQ (b = 0.386; P = 0.047). \n \nConclusion \nThese findings (i) add to the accumulating evidence that Med-Diet is crucially involved in the regulation of physical and mental health of elderly people, and (ii) suggest that a Mediterranean-style diet may contribute to protect elderly subjects with higher levels of polypathology/multi-morbidity from the development of depressive symptoms.
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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 | 0.002 |
| 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".