Habitual alcohol consumption is associated with lower cardiovascular stress responses – a novel explanation for the known cardiovascular benefits of alcohol?
Bibliographic record
Abstract
In contrast to heavy alcohol consumption, which is harmful, light to moderate drinking has been linked to reduced cardiovascular morbidity and mortality. Effects on lipid status or clotting do not fully explain these benefits. Exaggerated cardiovascular responses to mental stress are detrimental to cardiovascular health. We hypothesized that habitual alcohol consumption might reduce these responses, with potential benefits. Advanced magnetic resonance techniques were used to accurately measure cardiovascular responses to an acute mental stressor (Montreal Imaging Stress Task) in 88 healthy adults (∼1:1 male:female). Salivary cortisol and task performance measures were used to assess endocrine and cognitive responses. Habitual alcohol consumption and confounding factors were assessed by questionnaire. Alcohol consumption was inversely related to responses of heart rate (HR) (r = -0.31, p = 0.01), cardiac output (CO) (r = -0.32, p = 0.01), vascular resistance (r = 0.25, p = 0.04) and mean blood pressure (r = -0.31, p = 0.01) provoked by stress, but not to stroke volume (SV), or arterial compliance changes. However, high alcohol consumers had greater cortisol stress responses, compared to moderate consumers (3.5 versus 0.7 nmol/L, p = 0.04). Cognitive measures did not differ. Findings were not explained by variations in age, sex, social class, ethnicity, physical activity, adrenocortical activity, adiposity, smoking, menstrual phase and chronic stress. Habitual alcohol consumption is associated with reduced cardiac responsiveness during mental stress, which has been linked to lower risk of hypertension and vascular disease. Consistent with established evidence, our findings suggest a mechanism by which moderate alcohol consumption might reduce cardiovascular disease, but not high consumption, where effects such as greater cortisol stress responses may negate any benefits.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".