Arterial stiffness is associated with depression in middle-aged men — the Maastricht Study
Bibliographic record
Abstract
BACKGROUND: Arterial stiffening may underlie the association between depression and cardiovascular disease (CVD), but reported data are inconsistent. We investigated the associations between aortic stiffness and major depressive disorder (MDD) and depressive symptoms, and whether these differed by sex and age. METHODS: We measured carotid to femoral pulse wave velocity (cfPWV) using applanation tonometry, and we assessed depression using the Mini-International Neuropsychiatric Interview (MINI) and the Patient Health Questionnaire-9 (PHQ-9) in a cohort of participants from The Maastricht Study. Logistic and negative binominal models were adjusted for age, type 2 diabetes mellitus (T2DM), mean arterial pressure (MAP) and CVD risk factors. RESULTS: We included 2757 participants in our analyses (48.8% men, mean age 59.8 ± 8.1 yr, 27% T2DM). We found that cfPWV was associated with MDD in men (fully adjusted odds ratio [OR] 2.36, 95% confidence interval [CI] 1.45-3.84), but not in women (OR 1.57, 95% CI 0.93-2.66), aged 60 years or younger. The ORs were not significant in individuals older than 60 years (men: OR 1.03, 95% CI 0.63-1.68; women: OR 0.64, 95% CI 0.32-1.31). Similarly, cfPWV was associated with a higher PHQ-9 score in men (rate ratio 1.28, 95% CI 1.09-1.52), but not in women (rate ratio 1.11, 95% CI 0.99-1.23), aged 60 years or younger. Associations were not significant in individuals older than 60 years (men: rate ratio 0.96, 95% CI 0.84-1.08; women: rate ratio 1.00, 95% CI 0.90-1.12). LIMITATIONS: We cannot rule out reversed causation in this cross-sectional study. CONCLUSION: Greater aortic stiffness is associated with MDD and depressive symptoms among middle-aged men and to a lesser extent in women, whereas this association was not observed in old age.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".