Marc J. Gunter, PhD (*); Neil Murphy, PhD (*); Amanda J. Cross, PhD; Laure Dossus, PhD; Laureen Dartois, PhD; Guy Fagherazzi, PhD; Rudolf Kaaks, PhD; Tilman Kühn, PhD; Heiner Boeing, PhD; Krasimira Aleksandrova, PhD; Anne Tjønneland, MD, PhD; Anja Olsen, PhD; Kim Overvad, MD, PhD; Sofus Christian Larsen, PhD; Maria Luisa Redondo Cornejo, PhD; Antonio Agudo, PhD; María José Sánchez Pérez, MD, PhD; Jone M. Altzibar, PhD; Carmen Navarro, MD, PhD; Eva Ardanaz, MD, PhD; Kay-Tee Khaw, MB BChir; Adam Butterworth, PhD; Kathryn E. Bradbury, PhD; Antonia Trichopoulou, MD, PhD; Pagona Lagiou, MD, PhD; Dimitrios Trichopoulos, MD, PhD (†); Domenico Palli, MD; Sara Grioni, BSc; Paolo Vineis, MD, MPH; Salvatore Panico, MD, MSc; Rosario Tumino, MD; Bas Bueno-de-Mesquita, MD, PhD; Peter Siersema, MD, PhD; Max Leenders, PhD; Joline W.J. Beulens, PhD; Cuno U. Uiterwaal, MD, PhD; Peter Wallström, MD, PhD; Lena Maria Nilsson, PhD; Rikard Landberg, PhD; Elisabete Weiderpass, MD, PhD; Guri Skeie, PhD; Tonje Braaten, PhD; Paul Brennan, PhD; Idlir Licaj, PhD; David C. Muller, PhD; Rashmi Sinha, PhD; Nick Wareham, PhD, MBBS; Elio Riboli, MD, ScM
Note: All authors had full access to all of the data (including statistical reports and tables) in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. The authors are not affiliated with the listed funding institutions. Drs. Gunter and Murphy act as the guarantors of this article.
Acknowledgment: The authors thank the EPIC participants and staff for their valuable contribution to this research and Nicola Kerrison (MRC Epidemiology Unit, University of Cambridge) for managing the data for the InterAct Project.
Financial Support: The coordination of EPIC is financially supported by the European Commission Directorate-General for Health and Consumers and the International Agency for Research on Cancer. The national cohorts are supported by the Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l'Education Nationale, and Institut National de la Santé et de la Recherche Médicale (France); Deutsche Krebshilfe, Deutsches Krebsforschungszentrum, and Federal Ministry of Education and Research (Germany); Hellenic Health Foundation, Stavros Niarchos Foundation, and the Hellenic Ministry of Health and Social Solidarity (Greece); Italian Association for Cancer Research, National Research Council, and Associazione Iblea per la Ricerca Epidemiologica Ragusa, Associazione Volontari Italiani Sangue Ragusa, Sicilian Government (Italy); Dutch Ministry of Public Health, Welfare and Sport, Netherlands Cancer Registry, LK Research Funds, Dutch Prevention Funds, Dutch ZorgOnderzoek Nederland, World Cancer Research Fund International, and Statistics Netherlands (the Netherlands); European Research Council (grant ERC-2009-AdG 232997), NordForsk, and Nordic Centre of Excellence Programme on Food, Nutrition and Health (Norway); Health Research Fund, Regional Governments of Andalucía, Asturias, Basque Country, Murcia (no. 6236) and Navarra, and the Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública and Instituto de Salud Carlos II (RD12/0036/0018) (Spain); Swedish Cancer Society, Swedish Scientific Council, and Regional Government of Skåne and Västerbotten (Sweden); and Cancer Research UK, Medical Research Council, Stroke Association, British Heart Foundation, Department of Health, Food Standards Agency, and the Wellcome Trust (United Kingdom). Funding for the biomarker measurements in the subcohort was provided by grants to EPIC-InterAct from the European Community Framework Programme 6 and to EPIC-Heart from the Medical Research Council and the British Heart Foundation (joint award G0800270). Funding for the InterAct project was provided by the European Union Sixth Framework Programme (grant LSHM_CT_2006_037197). Dr. Muller's work was done during an International Agency for Research on Cancer Australia postdoctoral fellowship, supported by Cancer Council Australia. Dr. Palli was supported by a grant from the Associazione Italiana per la Ricerca sul Cancro.
Disclosures: Dr. Butterworth reports grants from the European Union Framework 7, the European Research Council, the U.K. Medical Research Council, the British Heart Foundation, and the U.K. National Institute for Health Research during the conduct of the study and from Biogen, Merck, and Pfizer outside the submitted work. Dr. Beulens reports grants from Unilever R&D and FrieslandCampina outside the submitted work. Authors not named here have disclosed no conflicts of interest. Disclosures can also be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M16-2945.
Editors' Disclosures: Christine Laine, MD, MPH, Editor in Chief, reports that she has no financial relationships or interests to disclose. Darren B. Taichman, MD, PhD, Executive Deputy Editor, reports that he has no financial relationships or interests to disclose. Cynthia D. Mulrow, MD, MSc, Senior Deputy Editor, reports that she has no relationships or interests to disclose. Deborah Cotton, MD, MPH, Deputy Editor, reports that she has no financial relationships or interest to disclose. Jaya K. Rao, MD, MHS, Deputy Editor, reports that she has stock holdings/options in Eli Lilly and Pfizer. Sankey V. Williams, MD, Deputy Editor, reports that he has no financial relationships or interests to disclose. Catharine B. Stack, PhD, MS, Deputy Editor for Statistics, reports that she has stock holdings in Pfizer and Johnson & Johnson.
Reproducible Research Statement:Study protocol and statistical code: Available from Dr. Gunter (e-mail, email@example.com). Data set: Requests for the data require formal approval by the EPIC principal investigators (e-mail, firstname.lastname@example.org).
Requests for Single Reprints: Marc Gunter, PhD, International Agency for Research on Cancer, 150 cours Albert Thomas, 69372 Lyon Cedex 08, France; e-mail, email@example.com.
Current Author Addresses: Drs. Gunter, Murphy, Dossus, and Brennan: International Agency for Research on Cancer (IARC), 150 cours Albert Thomas, 69372 Lyon CEDEX 08, France.
Drs. Cross, Vineis, Muller, and Riboli: Department of Epidemiology and Biostatistics, Imperial College London, St. Mary's Campus, Norfolk Place, Paddington, London W2 1PG, United Kingdom.
Drs. Dartois and Fagherazzi: Gustave Roussy, Espace Maurice Tubiana, Equipe E3N/E4N, 114 rue Edouard Vaillant, 94800 Villejuif, France.
Drs. Kaaks and Kühn: Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120 Heidelberg, Germany.
Drs. Boeing and Aleksandrova: German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany.
Drs. Tjønneland and Olsen: Danish Cancer Society, Strandboulevarden 49, DK-2100 København Ø, Denmark.
Dr. Overvad: Aarhus University, Bartholins Allé 2, Building 1260, 2.26, 8000 Aarhus C, Denmark.
Dr. Larsen: Research Unit for Dietary Studies, The Parker Institute, Copenhagen University Hospital, Bispebjerg og Frederiksberg, Nordre Fasanvej 57, Road 8-entrance 19, DK-2000 Frederiksberg, Denmark.
Dr. Redondo Cornejo: Public Health Directorate, Ciriaco Miguel Vigil, 9, 33006 Oviedo, Spain.
Dr. Agudo: Institut Català d'Oncologia (ICO), Unit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Av. Gran Via de l'Hospitalet 199-203, L'Hospitalet de Llobregat, Barcelona 08908, Spain.
Dr. Sánchez Pérez: Escuela Andaluza de Salud Pública, Cuesta del Observatorio, 4 - Campus Universitario de Cartuja s/n, Apdo. de Correos 2070 - 18080 Granada, Spain.
Dr. Altzibar: Public Health Department of Gipuzkoa, Basque Government, Avenida de Navarra, 4-20013 Donostia, San Sebastián, Spain.
Dr. Navarro: Epidemiology and Public Health Department, Murcia Health Council, Ronda de Levante 11, Murcia 3008, Spain.
Dr. Ardanaz: Epidemiology, Prevention and Promotion Health Service, Institute of Public Health Navarra, Leyre 15, 31003 Pamplona, Navarra, Spain.
Drs. Khaw and Butterworth: Department of Public Health & Primary Care, Strangeways Research Laboratory, Worts Causeway, Cambridge CB1 8RN, United Kingdom.
Dr. Bradbury: Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Oxford OX3 7LF, United Kingdom.
Dr. Trichopoulou: Hellenic Health Foundation, Kaisareias 13 & Alexandroupoleos, GR-115 27, Athens, Greece.
Dr. Lagiou: Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Kresge, Room 901, Boston, MA 02115.
Dr. Palli: Molecular and Nutritional Epidemiology Unit, ISPO (Cancer Study and Prevention Centre), Via delle Oblate 2, 50141, Florence, Italy.
Ms. Grioni: Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Via Giacomo Venezian, 1, 20133 Milano, Italy.
Dr. Panico: Dipartimento di Medicina Clinica e Sperimentale, Federico II University, Corso Umberto I, 40, 80138 Napoli, Italy.
Dr. Tumino: Tumor Registry, Department of Preventive Medicine, Provincial Health Ragusa, Via Dante 109, 97100 Ragusa, Italy.
Dr. Bueno-de-Mesquita: RIVM, Antonie van Leeuwenhoeklaan 9, 3721 MA, Bilthoven, PO Box 1, 3720 BA Bilthoven, the Netherlands.
Drs. Siersema and Leenders: Department of Gastroenterology and Hepatology, University Medical Centre, Heidelberglaan 100, 3584 CX Utrecht, the Netherlands.
Drs. Beulens and Uiterwaal: Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, Universiteitsweg 100, 3584 CG Utrecht, the Netherlands.
Dr. Wallström: Departmental Office for Clinical Sciences, Malmö, Clinical Research Centre, Post Box 50332, SE-202 13 Malmö, Sweden.
Dr. Nilsson: Department of Public Health and Clinical Medicine, University Hospital, 901 85 Umeå, Sweden.
Dr. Landberg: Department of Food Science, BioCenter, Swedish University of Agricultural Sciences, Almas Allé 8, 750 07 Uppsala, Sweden.
Drs. Weiderpass, Skeie, Braaten, and Licaj: Fakturaadresse, UiT Norges Arktiske Universitet, Fakturamottak, Postboks 6050 Langnes, 9037 Tromsø, Norway.
Dr. Sinha: Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, MSC 9776, Bethesda, MD 20892.
Dr. Wareham: MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, United Kingdom.
Author Contributions: Conception and design: M.J. Gunter, N. Murphy, H. Boeing, A. Tjønneland, M.J. Sánchez Pérez, E. Ardanaz, D. Trichopoulos, P. Vineis, R. Tumino, B. Bueno-de-Mesquita, M. Leenders, E. Weiderpass, P. Brennan, E. Riboli.
Analysis and interpretation of the data: M.J. Gunter, N. Murphy, A.J. Cross, K. Overvad, S.C. Larsen, E. Ardanaz, A. Trichopoulou, D. Trichopoulos, J.W.J. Beulens, E. Weiderpass, G. Skeie, D.C. Muller, R. Sinha, E. Riboli.
Drafting of the article: M.J. Gunter, N. Murphy, D. Trichopoulos, D. Palli, P. Vineis, L.M. Nilsson, E. Weiderpass, R. Sinha, E. Riboli.
Critical revision of the article for important intellectual content: M.J. Gunter, N. Murphy, A.J. Cross, L. Dossus, G. Fagherazzi, R. Kaaks, K. Aleksandrova, A. Tjønneland, A. Olsen, K. Overvad, S.C. Larsen, M.L. Redondo Cornejo, A. Agudo, J.M. Altzibar, C. Navarro, E. Ardanaz, A. Butterworth, K.E. Bradbury, A. Trichopoulou, P. Lagiou, D. Trichopoulos, D. Palli, S. Panico, R. Tumino, B. Bueno-de-Mesquita, P. Siersema, J.W.J. Beulens, C.U. Uiterwaal, P. Wallström, R. Landberg, E. Weiderpass, G. Skeie, T. Braaten, P. Brennan, I. Licaj, D.C. Muller, R. Sinha, N. Wareham, E. Riboli.
Final approval of the article: M.J. Gunter, N. Murphy, A.J. Cross, L. Dossus, L. Dartois, G. Fagherazzi, R. Kaaks, T. Kühn, H. Boeing, K. Aleksandrova, A. Tjønneland, A. Olsen, K. Overvad, S.C. Larsen, M.L. Redondo Cornejo, A. Agudo, M.J. Sánchez Pérez, J.M. Altzibar, C. Navarro, E. Ardanaz, K.T. Khaw, A. Butterworth, K.E. Bradbury, A. Trichopoulou, P. Lagiou, D. Trichopoulos, D. Palli, S. Grioni, P. Vineis, S. Panico, R. Tumino, B. Bueno-de-Mesquita, P. Siersema, M. Leenders, J.W.J. Beulens, C.U. Uiterwaal, P. Wallström, L.M. Nilsson, R. Landberg, E. Weiderpass, G. Skeie, T. Braaten, P. Brennan, I. Licaj, D.C. Muller, R. Sinha, N. Wareham, E. Riboli.
Provision of study materials or patients: T. Kühn, K. Overvad, M.L. Redondo Cornejo, J.M. Altzibar, E. Ardanaz, K.T. Khaw, D. Trichopoulos, J.W.J. Beulens, E. Weiderpass, G. Skeie, N. Wareham.
Statistical expertise: N. Murphy, D. Trichopoulos, E. Weiderpass, I. Licaj, D.C. Muller.
Obtaining of funding: R. Kaaks, A. Tjønneland, K. Overvad, K.T. Khaw, D. Trichopoulos, S. Panico, R. Tumino, E. Weiderpass, N. Wareham.
Administrative, technical, or logistic support: R. Kaaks, K. Overvad, E. Ardanaz, K.T. Khaw, D. Trichopoulos, P. Vineis, B. Bueno-de-Mesquita, E. Weiderpass.
Collection and assembly of data: M.J. Gunter, R. Kaaks, T. Kühn, H. Boeing, A. Tjønneland, K. Overvad, M.L. Redondo Cornejo, A. Agudo, M.J. Sánchez Pérez, C. Navarro, E. Ardanaz, K.T. Khaw, K.E. Bradbury, A. Trichopoulou, P. Lagiou, D. Trichopoulos, D. Palli, S. Grioni, S. Panico, R. Tumino, B. Bueno-de-Mesquita, J.W.J. Beulens, E. Weiderpass, G. Skeie, P. Brennan, N. Wareham, E. Riboli.
The relationship between coffee consumption and mortality in diverse European populations with variable coffee preparation methods is unclear.
To examine whether coffee consumption is associated with all-cause and cause-specific mortality.
Prospective cohort study.
10 European countries.
521 330 persons enrolled in EPIC (European Prospective Investigation into Cancer and Nutrition).
Hazard ratios (HRs) and 95% CIs estimated using multivariable Cox proportional hazards models. The association of coffee consumption with serum biomarkers of liver function, inflammation, and metabolic health was evaluated in the EPIC Biomarkers subcohort (n = 14 800).
During a mean follow-up of 16.4 years, 41 693 deaths occurred. Compared with nonconsumers, participants in the highest quartile of coffee consumption had statistically significantly lower all-cause mortality (men: HR, 0.88 [95% CI, 0.82 to 0.95]; P for trend < 0.001; women: HR, 0.93 [CI, 0.87 to 0.98]; P for trend = 0.009). Inverse associations were also observed for digestive disease mortality for men (HR, 0.41 [CI, 0.32 to 0.54]; P for trend < 0.001) and women (HR, 0.60 [CI, 0.46 to 0.78]; P for trend < 0.001). Among women, there was a statistically significant inverse association of coffee drinking with circulatory disease mortality (HR, 0.78 [CI, 0.68 to 0.90]; P for trend < 0.001) and cerebrovascular disease mortality (HR, 0.70 [CI, 0.55 to 0.90]; P for trend = 0.002) and a positive association with ovarian cancer mortality (HR, 1.31 [CI, 1.07 to 1.61]; P for trend = 0.015). In the EPIC Biomarkers subcohort, higher coffee consumption was associated with lower serum alkaline phosphatase; alanine aminotransferase; aspartate aminotransferase; γ-glutamyltransferase; and, in women, C-reactive protein, lipoprotein(a), and glycated hemoglobin levels.
Reverse causality may have biased the findings; however, results did not differ after exclusion of participants who died within 8 years of baseline. Coffee-drinking habits were assessed only once.
Coffee drinking was associated with reduced risk for death from various causes. This relationship did not vary by country.
European Commission Directorate-General for Health and Consumers and International Agency for Research on Cancer.
Appendix Table 1. Analytic Methods Used to Measure Liver Function, Circulatory Disease, and Metabolic Biomarkers*
Multivariable associations of serum liver function, circulatory disease, and metabolic biomarkers and all-cause mortality (n = 1597 deaths) among men and women, using sex-specific quartiles.
The multivariable model used Cox regression, with adjustment for body mass index (<22, 22–24.9, 25–29.9, 30–34.9, or ≥35 kg/m2), physical activity (inactive, moderately inactive, moderately active, or active), education (none, primary school, technical or professional school, secondary school, higher education [including university], or not specified), alcohol consumption (0, <5, 5–14.9, 15–29.9, or ≥30 g/d), smoking status (never, former, current, or missing/unknown), ever-use of contraceptive pill (yes, no, or unknown), menopausal status (premenopausal, postmenopausal, perimenopausal, surgically postmenopausal, or unknown), and ever-use of menopausal hormone therapy (yes, no, or unknown) and stratification by sex, age (1-y categories), and center. The albumin multivariable model was also adjusted for serum levels of ALT, ALP, AST, and GGT (all continuous and log-transformed). The ALP multivariable model was also adjusted for serum levels of ALT, AST, GGT, CRP, HDL-C, and total cholesterol (all continuous and some log-transformed). The ALT multivariable model was also adjusted for serum levels of ALP, AST, GGT, CRP, HDL-C, and total cholesterol (all continuous and some log-transformed). The AST multivariable model was also adjusted for serum levels of ALT, ALP, GGT, CRP, HDL-C, and total cholesterol (all continuous and some log-transformed). The GGT multivariable model was also adjusted for serum levels of ALT, ALP, AST, CRP, HDL-C, and total cholesterol (all continuous and some log-transformed). The CRP multivariable model was also adjusted for serum levels of HDL-C and total cholesterol (both continuous and log-transformed). First and fourth quartile cut points were <45 to ≥50 g/L for men and <44 to ≥49 g/L for women for albumin, <0.94 to ≥1.31 µkat/L for men and <0.87 to ≥1.29 µkat/L for women for ALP, <19 to ≥33 U/L for men and <14 to ≥23 U/L for women for ALT, <26 to ≥35 U/L for men and <23 to ≥31 U/L for women for AST, <0.35 to ≥0.75 µkat/L for men and <0.23 to ≥0.42 µkat/L for women for GGT, <5.14 to ≥20.57 nmol/L for men and <5.05 to ≥22.57 nmol/L for women for CRP, <5.2% to ≥5.7% for men and <5.3% to ≥5.7% for women for HbA1c, <1.2 to ≥1.6 mmol/L for men and <1.4 to ≥2.0 mmol/L for women for HDL-C, and <8.35 to ≥25.49 µmol/L for men and <6.57 to ≥23.03 µmol/L for women for lipoprotein(a). Trend tests across exposure groups were done by entering the category variables into the models as continuous terms. ALP = alkaline phosphatase; ALT = alanine aminotransferase; AST = aspartate aminotransferase; CRP = high-sensitivity C-reactive protein; GGT = γ-glutamyltransferase; HbA1c = glycated hemoglobin; HDL-C = high-density lipoprotein cholesterol; Q1 = first quartile; Q2 = second quartile; Q3 = third quartile; Q4 = fourth quartile.
Table 1. Baseline Characteristics of Study Participants, by Category of Daily Coffee Consumption
Appendix Table 2. Descriptive Information on EPIC Participant Countries
Table 2. Associations of Daily Coffee Consumption and All-Cause and Cause-Specific Mortality Among Men and Women
Table 3. Multivariable-Adjusted Mean Serum Levels of Liver Function, Circulatory Disease, and Metabolic Biomarkers Across Coffee Consumption Categories Among Men and Women (n = 14 800)*
Appendix Table 3. Multivariable Associations of Daily Caffeinated Coffee Consumption and All-Cause and Cause-Specific Mortality*
Appendix Table 4. Multivariable Associations of Daily Decaffeinated Coffee Consumption and All-Cause and Cause-Specific Mortality*
Adjusted cumulative incidence of all-cause mortality, by coffee consumption categories among men and women.
Flexible parametric survival models were used to allow direct estimation of the conditional cumulative incidence and thus absolute risk for death by sex and coffee consumption categories, with adjustment for body mass index (<22, 22–24.9, 25–29.9, 30–34.9, or ≥35 kg/m2); physical activity (inactive, moderately inactive, moderately active, or active); education (none, primary school, technical or professional school, secondary school, higher education [including university], or not specified); alcohol consumption (0, <5, 5–14.9, 15–29.9, or ≥30 g/d); smoking status and intensity (never, current [1–15, 16–25, or ≥26 cigarettes per day], or former [≤10, 11–<20, or ≥20 years since quitting]; current pipe, cigar, or occasional smoking; current vs. former; missing; or unknown); smoking duration (<10, 10–<20, 20–<30, 30–<40, or ≥40 years or unknown); ever-use of contraceptive pill (yes, no, or unknown); menopausal status (premenopausal, postmenopausal, perimenopausal, surgically postmenopausal, or unknown); ever-use of menopausal hormone therapy (yes, no, or unknown); and intake of total energy (in kilocalories per day), red and processed meat (in grams per day), and fruits and vegetables (in grams per day) (all continuous), with stratification by age (1-y categories) and center. Within these models, we used restricted cubic splines with 3 internal knots to model the baseline hazard, using attained age as the time scale. Model-based survival functions and their CIs were obtained from fitted models by coffee consumption category and sex, with other categorical covariates set to the most common category and continuous variables set to their sex-specific means. Categories were based on country-specific quartiles of coffee consumption after exclusion of nonconsumers. Quartile cutoffs were 500, 900, and 1300 mL/d in Denmark; 150, 280, and 450 mL/d in France; 261, 395, and 580 mL/d in Germany; 70, 140, and 240 mL/d in Greece; 60, 92, and 138 mL/d in Italy; 375, 500, and 750 mL/d in the Netherlands; 300, 420, and 540 mL/d in Norway; 50, 105, and 196 mL/d in Spain; 300, 400, and 601 mL/d in Sweden; and 83, 380, and 488 mL/d in the United Kingdom. Q1 = first quartile; Q2 = second quartile; Q3 = third quartile; Q4 = fourth quartile.
Appendix Table 5. Associations of Daily Coffee Consumption and Overall and Individual Cancer Mortality*
Subgroup analysis of association between daily coffee consumption and all-cause mortality among men and women.
Hazard ratios are for the comparison of participants in the highest quartile of consumption vs. nonconsumers. The multivariable model used Cox regression with adjustment for the covariates listed in the Statistical Analysis section of the text and stratification by age (1-y categories) and center. Categories were based on country-specific quartiles of coffee consumption after exclusion of nonconsumers. Quartile cutoffs were 500, 900, and 1300 mL/d in Denmark; 150, 280, and 450 mL/d in France; 261, 395, and 580 mL/d in Germany; 70, 140, and 240 mL/d in Greece; 60, 92, and 138 mL/d in Italy; 375, 500, and 750 mL/d in the Netherlands; 300, 420, and 540 mL/d in Norway; 50, 105, and 196 mL/d in Spain; 300, 400, and 601 mL/d in Sweden; and 83, 380, and 488 mL/d in the United Kingdom.
* Median was 12.6 g/d in men and 3.4 g/d in women.
† Median was 90.2 g/d in men and 60.3 g/d in women.
‡ Median was 324 g/d in men and 413 g/d in women.
Appendix Table 6. Associations of Daily Coffee Consumption and Cause-Specific Mortality, by Smoking Status*
Appendix Table 7. Associations of Daily Coffee Consumption and All-Cause Mortality, by Follow-up Time Categories*
Appendix Table 8. Multivariable Associations of Daily Coffee Consumption and All-Cause and Cause-Specific Mortality Among Men and Women After Exclusion of Deaths Occurring During the First 5 Years of Follow-up (n = 5247)*
Appendix Table 9. Multivariable Associations of Daily Coffee Consumption and All-Cause and Cause-Specific Mortality Among Men and Women After Exclusion of Deaths Occurring During the First 8 Years of Follow-up (n = 10 790)*
Appendix Table 10. Associations of Daily Coffee Consumption and All-Cause and Cause-Specific Mortality Among Participants Who Self-Reported Being in “Excellent” or “Good” Health at Baseline (n = 119 609)*
Appendix Table 11. Sensitivity Analysis to Assess the Possible Effect of an Unmeasured Confounder on the Observed Relationship Between Coffee Consumption and All-Cause Mortality*
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Two new studies published in Annals of Internal Medicine seem to confirm the mortality benefits of higher coffee consumption.
Miguel Cainzos-Achirica, Manel Pladevall-Vila, Usama Bilal
Johns Hopkins Medical Institutions, Hospital Universitari de Bellvitge, RTI Health Solutions, Henry Ford Health System, Drexel Dornsife School of Public Health
July 19, 2017
Selection Bias and Residual Confounding in the studies by Gunter and Park
To the Editor,We have read the recent studies by Gunter MJ et al.  and Park SY et al.  with great interest. Nevertheless, we believe there are two potential threats to the validity of both studies that are worth discussing. Daily coffee intake usually begins around age 20, in the context of adult student life or the incorporation to the job market. Nevertheless, median age at baseline in both studies was above 50 years. Thus, individuals from the source populations had had the opportunity to be exposed to coffee for a median of 30 years before study entry. This “prevalent user” design may have allowed the depletion of susceptible individuals from the coffee intake groups (who may have had events before qualifying for study entry), resulting in a “healthy survivor” exposed study population. “Incident user” –i.e., exposure-naïve– designs are considered the gold standard in observational pharmacoepidemiology, as the selection bias derived from inclusion of prevalent users is minimized and the associations are more consistent with those from randomized trials . Interestingly, in an analysis of the Precursors study by Klag and colleagues  in which baseline age was less than 30 (i.e., closer to an incident user design), there was a strong association between coffee use and cardiovascular events in multivariable analyses.The risk of residual confounding is also worth mentioning. In particular, socially conditioned behaviors such as coffee intake are challenging and subject to confounding by socioeconomic status (SES). As with studies of moderate alcohol consumption, these behaviors are strongly prevalent in higher SES groups, which in itself is a protective factor for health outcomes . While the authors did adjust for education, SES is a complex latent construct for which proxies (such as education, income, or occupation) are often measured with error, when at all measured, and may fail to fully capture the effect of SES. Importantly, in their sensitivity analysis assessing robustness to residual confounding, Gunter et al.  found that for a risk factor with a HR of 1.50 (within the realm of the feasible effect sizes of poverty ), there needs only be a 20% difference in the confounder between groups.In view of these limitations, we believe the reports of these studies in the general press may have exaggerated their causal significance. Future research on coffee intake and health should aim at including younger individuals and use more comprehensive measurements of SES.REFERENCES1. Gunter MJ, Murphy N, Cross AJ, et al. Coffee Drinking and Mortality in 10 European Countries: A Multinational Cohort Study. Ann Intern Med. 2017 Jul 11. doi: 10.7326/M16-2945.2. Park SY, Freedman ND, Haiman CA, et al. Association of Coffee Consumption With Total and Cause-Specific Mortality Among Nonwhite Populations. Ann Intern Med. 2017 Jul 11. doi: 10.7326/M16-2472.3. Danaei G, Tavakkoli M, Hernán MA. Bias in observational studies of prevalent users: lessons for comparative effectiveness research from a meta-analysis of statins. Am J Epidemiol. 2012;175(4):250-62.4. Klag MJ, Mead LA, LaCroix AZ, et al. Coffee intake and coronary heart disease. Ann Epidemiol. 1994;4(6):425-33.5. Galea S, Tracy M, Hoggatt KJ, et al. Estimated deaths attributable to social factors in the United States. Am J Public Health. 2011;101(8):1456-65.
Mika Kivimaki, Jane E. Ferrie
Department of Epidemiology and Public Health, University College London, UK
July 24, 2017
Effects of Coffee Consumption on Mortality Are Uncertain
Gunter and colleagues report that people in the highest quartile of coffee consumption have a 7%-10% higher risk of death compared to non-drinkers in a study of over 450,000 adults from 10 European countries.1 However, this association was reversed after adjustment for covariates. In the multivariable adjusted model, high coffee consumption is related to a 12% lower mortality risk in men and a 7% lower risk in women. The authors suggest that coffee may confer health benefits.The instability of the results in relation to covariate adjustments raised our concern about the validity of this conclusion. Here we elaborate on the possibility that the findings may be attributable to bias and confounding by unmeasured or imprecisely measured risk factors. For example, some diseases and symptoms related to hypersensitivity or intolerance to coffee consumption might also be linked to shorter life expectancy contributing to a spurious association between coffee consumption and mortality (NICE Evidence Search Caffeine. https://www.evidence.nhs.uk). Socioeconomic health determinants, such as income, occupational position and neighbourhood characteristics, are related to coffee consumption2 and mortality.2-4 Such factors may have affected the results but were not controlled for in the analyses. This interpretation is consistent with the result that the coffee consumption-mortality relation was more marked in men than women, as was the association between coffee consumption and education, another socioeconomic health resource.1According to calculations of the e-value,5 a single confounder, related to coffee consumption and mortality risk, and with a hazard ratio of 1.5 could entirely explain the 12% lower mortality in men with high coffee consumption. In women, the corresponding hazard ratio would be 1.4. Thus, even minor uncontrolled risk and protective factors, including those listed above, have, in combination, the potential to bias the findings by Gunter and colleagues.1 Indeed, Mendelian randomisation analyses, which are more protected from bias and confounding than the observational findings of Gunter and others, do not support protective effects for high coffee consumption in relation to cardiovascular disease or all-cause mortality.3The US NIH, with support from the alcohol industry, is starting a $100 million clinical trial to obtain a definitive answer to the question of whether moderate alcohol consumption prevents heart attacks. As coffee consumption is more widespread and possibly more amenable to change than alcohol consumption, a large-scale trial of coffee consumption is equally justified to obtain definite conclusions about its health effects. Professor Mika Kivimaki and Dr Jane E. Ferrie, University College London, UKEmail: firstname.lastname@example.orgConflict of interest: None declared.REFERENCES1. Gunter MJ, Murphy N, Cross AJ, Dossus L, Dartois L, Fagherazzi G et al. Coffee drinking and mortality in 10 European countries: A multinational cohort study. Ann Intern Med 2017 [ePub ahead of the print] doi:10.7326/M16-29452. Nordestgaard AT and Nordestgaard BG. Coffee intake, cardiovascular disease and all-cause mortality: observational and Mendelian randomization analyses in 95 000-223 000 individuals. Int J Epidemiol. 2016;45:1938-1952.3. Stringhini S, Carmeli C, Jokela M, Avendaño M, Muennig P, Guida F et al. Socioeconomic status and the 25 x 25 risk factors as determinants of premature mortality: a multicohort study of 1.7 million men and women. Lancet 2017;389:1229-37.4. Ludwig J, Sanbonmatsu L, Gennetian L, et al. Neighborhoods, obesity, and diabetes: a randomized social experiment. N Engl J Med 2011;365:1509–19.5. vander Weele T, Ding P. Sensitivity analysis in observational research: Introducing the E-value. Ann Intern Med 2017; [ePub ahead of the print] doi:10.7326/M16-2607.
Marc J. Gunter, PhD, Neil Murphy, PhD, David C. Muller, PhD, Elio Riboli, MD, ScM
International Agency for Research on Cancer
November 7, 2017
We thank the authors of the letters addressing our article and welcome further discussion on the study design and its results. We fully agree that the results from our analysis do not provide evidence for a causal relationship between coffee drinking and reduced risk of all-cause and cause-specific mortality. Unfortunately we are not able to control hyperbole generated by the lay press, though in our interactions with journalists we made every effort to stress the limitations of observational analyses. As suggested, a clinical trial could provide more definitive evidence on whether coffee drinking directly impacts health, and we would welcome such an initiativeBoth letters raised the prospect that residual confounding by socioeconomic status (SES) may have contributed to the observed inverse relationship between coffee consumption and mortality. As indicated, we used education level as a proxy for SES and while we agree that education is an imperfect measure of SES, it is a widely used indicator of latent SES and is strongly associated with mortality rates in the EPIC cohort (1). Using education as a surrogate marker of SES allowed the classification of all participants (including those not working or retired), is stable over the lifecourse, and can be accurately recorded allowing comparisons across the EPIC study. The inverse associations between coffee and mortality observed in our analysis were stable after we adjusted for education, and, importantly, coffee drinking across the 10 European countries was not related to education status and was not more common among those with healthier lifestyle habits. Further, while coffee drinking may have become more prevalent in countries such as the United Kingdom in recent years and could track with SES, such changes have not been observed in most other countries included in the study. We cannot exclude the possibility that survivor bias may have influenced the observed coffee consumption and mortality relationships. However, if survivor bias did significantly impact our results; we would expect the coffee drinking and mortality relationships to differ substantially by age. However, we did not detect any effect modification by age at recruitment categories (<45, 45-<60, and ≥60 years; P-interaction=0.94). Whilst this observation does not rule out an impact of survivor bias, it is an indication that any such impact is unlikely to be large.While we fully acknowledge the limitations of our analysis and urge caution in the interpretation of the results, we also wish to emphasize the striking consistency between our findings and those of several other large-scale studies conducted in the U.S. (2-4) and Asia (5). The impact of coffee drinking on health deserves further investigation. Yours Sincerely,Marc J. Gunter, PhD; Neil Murphy, PhD; David C Muller, PhD; Elio Riboli, MD, ScM1. Gallo V, Mackenbach JP, Ezzati M, Menvielle G, Kunst AE, Rohrmann S, et al. Social Inequalities and Mortality in Europe – Results from a Large Multi-National Cohort. PLOS ONE. 2012;7(7):e39013.2. Freedman ND, Park Y, Abnet CC, Hollenbeck AR, Sinha R. Association of Coffee Drinking with Total and Cause-Specific Mortality. New England Journal of Medicine: Massachusetts Medical Society; 2012:1891-904.3. Ding M, Satija A, Bhupathiraju SN, Hu Y, Sun Q, Han J, et al. Association of Coffee Consumption with Total and Cause-Specific Mortality in Three Large Prospective Cohorts. Circulation. 2015.4. Park S, Freedman ND, Haiman CA, Le Marchand L, Wilkens LR, Setiawan V. ASsociation of coffee consumption with total and cause-specific mortality among nonwhite populations. Annals of Internal Medicine. 2017;167(4):228-35.5. Saito E, Inoue M, Sawada N, Shimazu T, Yamaji T, Iwasaki M, et al. Association of coffee intake with total and cause-specific mortality in a Japanese population: the Japan Public Health Center–based Prospective Study. The American Journal of Clinical Nutrition. 2015;101(5):1029-37.
Gunter MJ, Murphy N, Cross AJ, Dossus L, Dartois L, Fagherazzi G, et al. Coffee Drinking and Mortality in 10 European Countries: A Multinational Cohort Study. Ann Intern Med. 2017;167:236–247. doi: 10.7326/M16-2945
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Published: Ann Intern Med. 2017;167(4):236-247.
Published at www.annals.org on 11 July 2017
Cardiology, Coronary Risk Factors, Dyslipidemia, Gastroenterology/Hepatology, Hematology/Oncology.
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