Coffee consumption and cardiometabolic health: a comprehensive review of the evidence
Bibliographic record
Abstract
This review provides a comprehensive synthesis of longitudinal observational and interventional studies on the cardiometabolic effects of coffee consumption. It explores biological mechanisms, and clinical and policy implications, and highlights gaps in the evidence while suggesting future research directions. It also reviews evidence on the causal relationships between coffee consumption and cardiometabolic outcomes from Mendelian randomization (MR) studies. Findings indicate that while coffee may cause short-term increases in blood pressure, it does not contribute to long-term hypertension risk. There is limited evidence indicating that coffee intake might reduce the risk of metabolic syndrome and non-alcoholic fatty liver disease. Furthermore, coffee consumption is consistently linked with reduced risks of type 2 diabetes (T2D) and chronic kidney disease (CKD), showing dose-response relationships. The relationship between coffee and cardiovascular disease is complex, showing potential stroke prevention benefits but ambiguous effects on coronary heart disease. Moderate coffee consumption, typically ranging from 1 to 5 cups per day, is linked to a reduced risk of heart failure, while its impact on atrial fibrillation remains inconclusive. Furthermore, coffee consumption is associated with a lower risk of all-cause mortality, following a U-shaped pattern, with the largest risk reduction observed at moderate consumption levels. Except for T2D and CKD, MR studies do not robustly support a causal link between coffee consumption and adverse cardiometabolic outcomes. The potential beneficial effects of coffee on cardiometabolic health are consistent across age, sex, geographical regions, and coffee subtypes and are multi-dimensional, involving antioxidative, anti-inflammatory, lipid-modulating, insulin-sensitizing, and thermogenic effects. Based on its beneficial effects on cardiometabolic health and fundamental biological processes involved in aging, moderate coffee consumption has the potential to contribute to extending the healthspan and increasing longevity. The findings underscore the need for future research to understand the underlying mechanisms and refine health recommendations regarding coffee consumption.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".