Tea and coffee consumption and risk of acute stroke: The INTERSTROKE Study
Bibliographic record
Abstract
BACKGROUND: Stroke is a leading global cause of death and disability. Daily tea/coffee intake is consumed by > 50% of populations and may represent an important population-level exposure. Therefore, it is first essential that we better understand the associations between the tea/coffee intake and stroke. AIMS: This research aims to generate hypotheses about the global associations between tea and coffee intake and stroke. These insights will identify interventions for stroke prevention that can be further explored using alternative study designs. METHODS: INTERSTROKE is a large international matched case-control study of first stroke from 32 countries. Participants were asked "how many cups do you drink each day?" of coffee, green tea, black tea, and other tea. Multivariable conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between intake and stroke. RESULTS: We included 13,462 cases and 13,488 controls from INTERSTROKE; mean age was 61.7 (13.4) years and 59.6% (n = 16,010) were male. Overall, 19.4% (n = 5239) did not consume tea/coffee, 47.0% (n = 12,666) consumed tea only, 14.9% (n = 4024) consumed coffee alone, and 18.6% (n = 5021) consumed both, with significant regional variations. After multivariable adjustment, there was no association between low/moderate coffee intake and stroke, but high consumption (> 4/day) was associated with higher odds of all stroke (OR = 1.37 (95% CI = 1.06-1.77)) or ischemic stroke (OR = 1.32 (95% CI = 1.00-1.74)). Tea consumption was associated with lower odds of all (OR = 0.81 (95% CI = 0.69-0.94) for highest intake) or ischemic stroke (OR = 0.81 (95% CI = 0.68-0.98) for highest intake). CONCLUSIONS: High coffee consumption was associated with higher odds of all or ischemic stroke; low-moderate coffee had no association with stroke. In contrast, tea consumption was associated with lower odds of stroke. These associations suggest that individuals consider avoiding high coffee consumption (⩾ five cups/day) to impact future stroke risk. DATA ACCESS STATEMENT: The design and rationale of INTERSTROKE was published previously. Individual participant data, or other documents are not available.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".