Effect of Coffee Consumption on Non-Alcoholic Fatty Liver Disease Incidence, Prevalence and Risk of Significant Liver Fibrosis: Systematic Review with Meta-Analysis of Observational Studies
Bibliographic record
Abstract
Background and aim: Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide. Given the anti-fibrotic and antioxidant properties of coffee, this systematic review and meta-analysis aims to provide updated results on the impact of coffee consumption on NAFLD incidence, prevalence, and risk of significant liver fibrosis. Methods: We conducted a comprehensive search in MEDLINE (OvidSP) and Scopus from January 2010 through January 2021. Relative risks for the highest versus the lowest level of coffee consumption were pooled using random-effects models. Heterogeneity and publication bias were evaluated using the Higgins’ I2 statistic and Egger’s regression test, respectively. Results: Eleven articles consisting of two case-control studies, eight cross-sectional studies, and one prospective cohort study were included in the meta-analysis. Of those, three studies with 92,075 subjects were included in the analysis for NAFLD incidence, eight studies with 9558 subjects for NAFLD prevalence, and five with 4303 subjects were used for the analysis of liver fibrosis. There was no association between coffee consumption and NAFLD incidence (RR 0.88, 95% CI 0.63–1.25, p = 0.48) or NAFLD prevalence (RR 0.88, 95% CI 0.76–1.02, p = 0.09). The meta-analysis showed coffee consumption to be significantly associated with a 35% decreased odds of significant liver fibrosis (RR 0.65, 95% CI 0.54–0.78, p < 0.00001). There was no heterogeneity (I2 = 11%, p = 0.34) and no evidence of publication bias (p = 0.134). Conclusion: This meta-analysis supports the protective role of coffee consumption on significant liver fibrosis in patients with NAFLD. However, the threshold of coffee consumption to achieve hepatoprotective effects needs to be established in prospective trials.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| 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".