Cardiovascular disease as a mediator in the relationship between lifestyle risk factors and cognitive outcomes: a scoping review
Bibliographic record
Abstract
Dementia is a major global health challenge and lifestyle modification is a key prevention strategy. Cardiovascular disease (CVD) is hypothesized to mediate lifestyle-dementia relationships, but empirical evidence is unclear. Mediation analysis offers insight into causal mechanisms beyond traditional associations. This scoping review synthesizes the limited available studies applying mediation analysis to examine whether CVD mediates associations between lifestyle factors (smoking, alcohol use, diet, physical activity) and cognitive outcomes in adults aged 45 and older. Of 1309 records screened, five studies met the inclusion criteria, reflecting a small, heterogeneous evidence base. Most examined physical activity (n = 4), with two reporting partial mediation by composite CVD risk scores. Evidence for diet (n = 2) and alcohol (n = 1) was inconclusive, and no studies assessed smoking. Overall, evidence for CVD as a mediator remains tentative, sparse, and inconsistent, highlighting major methodological gaps and an urgent need for robust studies to clarify whether cardiovascular health underpins lifestyle-related dementia risk. HIGHLIGHTS: Five studies were identified that used mediation analysis to explore the role of cardiovascular disease in the relationship between lifestyle risk factors and dementia. Cardiovascular disease may partially mediate the impact of physical activity on brain health. Diet and alcohol consumption showed no clear mediation effects by cardiovascular disease on cognition. Longitudinal, well-powered studies with robust mediation frameworks are urgently needed to evaluate vascular pathways and optimize dementia prevention strategies targeting modifiable lifestyle factors.
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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 | 0.009 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".