Shared and distinct pathways from anxiety disorder and depression to cardiovascular disease: a UK Biobank prospective cohort study
Bibliographic record
Abstract
AIMS: Although anxiety disorder and depression increase the risk of cardiovascular disease, few studies have examined their underlying mechanisms systematically, particularly contrasting the difference between the two of them. Our study aimed to examine the extent to which lifestyle, physical and metabolic factors mediate the associations of anxiety disorder and depression with incident CVD. METHODS: A prospective cohort study was conducted using UK Biobank. Anxiety disorder, depression, and incident CVD were ascertained through linkage to hospital and death records. A causal mediation analysis was performed for anxiety disorder and depression, separately examining multiple potential lifestyle, physical, and metabolic mediators. Cox proportional hazard models and log-linear models were used to derive indirect effect estimates and proportions mediated. RESULTS: A total of 254,695 participants were included. Both anxiety disorder (HR 1.62, 95% CI 1.15-2.13) and depression (HR 2.15, 95% CI 1.75-2.64) were associated with CVD after adjusting for sociodemographic confounders. Among lifestyle and physical factors, the strongest mediators were current smoking and higher waist-hip ratio which accounted for 11.9% and 13.4% of the excess risk from anxiety disorder, and 17.3% and 14.0% from depression, respectively. The strongest metabolic mediators were systolic blood pressure for anxiety disorder (10.4%) and CRP (10.8%) for depression. Systolic blood pressure was the weakest mediator for depression (4.3%). CONCLUSIONS: Lifestyle and physical pathways to incident CVD may be common to both anxiety disorder and depression, but shared metabolic pathways seem unlikely. Our findings inform which risk factors to target among people with anxiety disorder or depression in order to reduce their higher risk of developing CVD.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".