The DOI matches its Crossref record; 88 of the 88 references it cites were found in a registry or an index.
A meta-analysis of prospective studies of coffee consumption and mortality for all causes, cancers and cardiovascular diseases
Abstract
Several prospective studies considered the relation between coffee consumption and mortality. Most studies, however, were underpowered to detect an association, since they included relatively few deaths. To obtain quantitative overall estimates, we combined all published data from prospective studies on the relation of coffee with mortality for all causes, all cancers, cardiovascular disease (CVD), coronary/ischemic heart disease (CHD/IHD) and stroke. A bibliography search, updated to January 2013, was carried out in PubMed and Embase to identify prospective observational studies providing quantitative estimates on mortality from all causes, cancer, CVD, CHD/IHD or stroke in relation to coffee consumption. A systematic review and meta-analysis was conducted to estimate overall relative risks (RR) and 95 % confidence intervals (CI) using random-effects models. The pooled RRs of all cause mortality for the study-specific highest versus low (≤1 cup/day) coffee drinking categories were 0.88 (95 % CI 0.84-0.93) based on all the 23 studies, and 0.87 (95 % CI 0.82-0.93) for the 19 smoking adjusting studies. The combined RRs for CVD mortality were 0.89 (95 % CI 0.77-1.02, 17 smoking adjusting studies) for the highest versus low drinking and 0.98 (95 % CI 0.95-1.00, 16 studies) for the increment of 1 cup/day. Compared with low drinking, the RRs for the highest consumption of coffee were 0.95 (95 % CI 0.78-1.15, 12 smoking adjusting studies) for CHD/IHD, 0.95 (95 % CI 0.70-1.29, 6 studies) for stroke, and 1.03 (95 % CI 0.97-1.10, 10 studies) for all cancers. This meta-analysis provides quantitative evidence that coffee intake is inversely related to all cause and, probably, CVD mortality.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“one recent meta-analysis paper showed that heavy coffee consumption was not associated with risk of CVD mortality.20”
From Long-Term Coffee Consumption and Risk of Cardiovascular Disease: A Systematic Review and a Dose–Response Meta-Analysis of Prospective Cohort Studies (2014) · cites this paper as [20]
Citations
Cites
Measuring inconsistency in meta-analyses
Higgins, J. P. T., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003) · BMJ · doi:10.1136/bmj.327.7414.557 · Cited by 63,139
Bias in meta-analysis detected by a simple, graphical test
Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997) · BMJ · doi:10.1136/bmj.315.7109.629 · Cited by 56,722
Meta-analysis of Observational Studies in Epidemiology<SUBTITLE>A Proposal for Reporting</SUBTITLE>
Stroup, D. F. (2000) · JAMA · doi:10.1001/jama.283.15.2008 · Cited by 20,623
Operating characteristics of a rank correlation test for publication bias
Begg, C. B., & Mazumdar, M. (1994) · Biometrics · doi:10.2307/2533446 · Cited by 16,955
Methods for Trend Estimation from Summarized Dose-Response Data, with Applications to Meta-Analysis
Greenland, S., & Longnecker, M. P. (1992) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a116237 · Cited by 2,353
Hamling, J., Lee, P. N., Weitkunat, R., & Ambühl, M. (2007) · Statistics in Medicine · doi:10.1002/sim.3013 · Cited by 649
Association of Coffee Drinking with Total and Cause-Specific Mortality
Freedman, N. D., Park, Y., Abnet, C. C., Hollenbeck, A. R., & Sinha, R. R. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1112010 · Cited by 597
Thelle, D. S., Arnesen, E., & Førde, O. H. (1983) · New England Journal of Medicine · doi:10.1056/nejm198306163082405 · Cited by 493
Coffee, CYP1A2 genotype, and risk of myocardial infarction
Cornelis, M. C., El-Sohemy, A., Kabagambe, E. K., & Campos, H. (2006) · JAMA · doi:10.1001/jama.295.10.1135 · Cited by 490 · cited 1×
“and the fact that studies included in these meta-analyses did not consider genetic variants associated with coffee drinking, such as CYP1A2, which is responsible for more than 95 % of caffeine metabolism, and consequently of the effects of caffeine and coffee consumption [80].”
BackgroundTobacco, alcohol, and caffeine use: A review of their interrelationships.
Istvan, J. A., & Matarazzo, J. D. (1984) · Psychological Bulletin · doi:10.1037/0033-2909.95.2.301 · Cited by 485
Research works printed but not linked: 1
- Jacobsen BK, Bjelke E, Kvale G, Heuch I. Coffee drinking, mortality, and cancer incidence: results from a Norwegian prospective study. J Natl Cancer Inst. 1986;76(5):823–31.
Cited by
Sorted by citations
Coffee consumption and health: umbrella review of meta-analyses of multiple health outcomes
Poole, R., Kennedy, O. J., Roderick, P., Fallowfield, J. A., Hayes, P. C., & Parkes, J. (2017) · BMJ · doi:10.1136/bmj.j5024 · Cited by 835
Ding, M., Bhupathiraju, S. N., Satija, A., van Dam, R. M., & Hu, F. B. (2014) · Circulation · doi:10.1161/circulationaha.113.005925 · Cited by 565
“Moreover, a number of additional studies have been published since the publication of these meta-analyses, and 1 recent meta-analysis showed that heavy coffee consumption was not associated with risk of CVD mortality.(20) To examine the dose–response association of coffee consumption with CVD risk, we conducted a syst…”
Coffee, Caffeine, and Health Outcomes: An Umbrella Review
Grosso, G., Godos, J., Galvano, F., & Giovannucci, E. L. (2017) · Annual Review of Nutrition · doi:10.1146/annurev-nutr-071816-064941 · Cited by 531
The Rotterdam Study: 2016 objectives and design update
Albert Hofman, D., Brusselle, G., Murad, S. D., van Duijn, C. M., Franco, O. H., Goedegebure, A., Ikram, M. A., Klaver, C. C. W., Nijsten, T. E. C., Peeters, R. P., et al. (2015) · European Journal of Epidemiology · doi:10.1007/s10654-015-0082-x · Cited by 385
Maternal obesity during pregnancy and cardiovascular development and disease in the offspring
Gaillard, R. (2015) · European Journal of Epidemiology · doi:10.1007/s10654-015-0085-7 · Cited by 322
Metadata
- Authors
- Malerba, S., Turati, F., Galeone, C., Pelucchi, C., Verga, F., La Vecchia, C., & Tavani, A.
- Affiliations
- Università Cattolica del Sacro Cuore (IT)
- Mario Negri Institute for Pharmacological Research (IT)
- University of Milan (IT)
- University of Turin (IT)
- Corresponding author
- Malerba, Stefano
- Venue
- European Journal of Epidemiology
- Published
- 2013-07
- Volume
- 28
- Issue
- 7
- Pages
- 527-539
- ISSN
- 0393-2990 (ISSN-L)
- 1573-7284
- OpenAlex
- W2109219983
- Cited by
- 119
- References
- 88
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 6 · 2023: 4 · 2022: 7 · 2021: 6 · 2020: 10 · 2019: 8 · 2018: 11 · 2017: 20 · 2016: 8 · 2015: 19 · 2014: 13 · 2013: 2
- FWCI
- 1.75
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- European Journal of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Fondazione Italiana per la Ricerca sul Cancro
- Topics
- Health Sciences › Medicine › Pharmacology (medical) › Coffee research and impacts
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Health Sciences › Medicine › Pathology and Forensic Medicine › Alcohol Consumption and Health Effects
- Keywords
- coffee consumption, mortality, all-cause mortality, cancer mortality, cardiovascular mortality, coronary artery disease, ischemic heart disease, stroke, relative risk
- MeSH terms
- Cardiovascular Diseases, Cause of Death, Coffee, Humans, Mortality, Neoplasms, Prospective Studies, Risk Factors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review