Alcohol use and cardiovascular health outcomes: a comparison across age and gender in the Winnipeg Health and Drinking Survey Cohort
Bibliographic record
Abstract
BACKGROUND: research has reliably demonstrated cardioprotection from regular alcohol use. Heavy episodic drinking (HED), however, negates these beneficial effects and increases the risk of cardiovascular disease (CVD). The impact of age on the health effects of episodic drinking has not been evaluated. OBJECTIVE: to examine the association between alcohol volume and pattern of consumption on the risk of cardiovascular morbidity and mortality across the lifespan. DESIGN AND SETTING: prospective, community-based cohort study of adults in Winnipeg, Manitoba, Canada. SUBJECTS: a total of 1,154 participants (580 men and 574 women) aged 18-64 surveyed at baseline (1990-91) on alcohol consumption levels and pattern of use. METHODS: usual alcohol consumption was measured using a quantity-frequency approach. HED was estimated by asking participants how often they consumed eight or more drinks in one sitting in the past year. Questions were asked separately for wine, beer and spirits. Surveillance for cardiovascular events was conducted for 10 years (i.e. up to age 74 years). Diagnoses of CVD were obtained via health utilization records. Cox proportional hazard models were derived for both genders and for 'young adults' (baseline age 18-34), 'middle-aged adults' (baseline age 35-49) and 'older adults' (baseline 50-64). Models were adjusted for marital status, cigarette smoking status and educational level. RESULTS: Reduced risk of CVD was associated with usual consumption, whereas an increased risk was associated with HED. Among male usual drinkers, cardioprotection was afforded only to middle and older age groups. The benefits of regular consumption were seen only in the youngest age group among women. The heaviest usual consumption category was associated with a decreased risk of CVD in men. Heavy episodic drinking increased the risk of coronary heart disease in middle-aged men and was marginally significant in middle-aged women. Risk of hypertension was elevated in older men with heavy episodic drinking. CONCLUSIONS: The well-established relationship between regular alcohol consumption and decreased risk of CVD may not become evident until middle age or older in men. Women may benefit from usual consumption at a much younger age. In both sexes, however, these beneficial effects of alcohol use are negated when alcohol is consumed in a heavy episodic drinking pattern, particularly for middle-aged and older men.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".