Association between clinically recorded alcohol consumption and initial presentation of 12 cardiovascular diseases: population based cohort study using linked health recordsBMJ 2017; 356 doi: https://doi.org/10.1136/bmj.j909 (Published 22 March 2017) Cite this as: BMJ 2017;356:j909
- Steven Bell, genetic epidemiologist1 2,
- Marina Daskalopoulou, research associate3,
- Eleni Rapsomaniki, biostatistician4,
- Julie George, honorary research associate4,
- Annie Britton, reader in epidemiology2,
- Martin Bobak, professor of epidemiology2,
- Juan P Casas, professor in clinical epidemiology and informatics4,
- Caroline E Dale, research fellow4,
- Spiros Denaxas, senior lecturer in biomedical informatics4,
- Anoop D Shah, specialty registrar4,
- Harry Hemingway, professor of clinical epidemiology4
- 1Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge CB1 8RN, UK
- 2Research Department of Epidemiology and Public Health, University College London, London WC1E 7HB, UK
- 3Department of Infection and Population Health, University College London, Royal Free Hospital, London NW3 2PF, UK
- 4Farr Institute of Health Informatics Research (London), University College London, London NW1 2DA, UK
- Correspondence to: S Bell
- Accepted 1 February 2017
Objectives To investigate the association between alcohol consumption and cardiovascular disease at higher resolution by examining the initial lifetime presentation of 12 cardiac, cerebrovascular, abdominal, or peripheral vascular diseases among five categories of consumption.
Design Population based cohort study of linked electronic health records covering primary care, hospital admissions, and mortality in 1997-2010 (median follow-up six years).
Setting CALIBER (ClinicAl research using LInked Bespoke studies and Electronic health Records).
Participants 1 937 360 adults (51% women), aged ≥30 who were free from cardiovascular disease at baseline.
Main outcome measures 12 common symptomatic manifestations of cardiovascular disease, including chronic stable angina, unstable angina, acute myocardial infarction, unheralded coronary heart disease death, heart failure, sudden coronary death/cardiac arrest, transient ischaemic attack, ischaemic stroke, intracerebral and subarachnoid haemorrhage, peripheral arterial disease, and abdominal aortic aneurysm.
Results 114 859 individuals received an incident cardiovascular diagnosis during follow-up. Non-drinking was associated with an increased risk of unstable angina (hazard ratio 1.33, 95% confidence interval 1.21 to 1.45), myocardial infarction (1.32, 1.24 to1.41), unheralded coronary death (1.56, 1.38 to 1.76), heart failure (1.24, 1.11 to 1.38), ischaemic stroke (1.12, 1.01 to 1.24), peripheral arterial disease (1.22, 1.13 to 1.32), and abdominal aortic aneurysm (1.32, 1.17 to 1.49) compared with moderate drinking (consumption within contemporaneous UK weekly/daily guidelines of 21/3 and 14/2 units for men and women, respectively). Heavy drinking (exceeding guidelines) conferred an increased risk of presenting with unheralded coronary death (1.21, 1.08 to 1.35), heart failure (1.22, 1.08 to 1.37), cardiac arrest (1.50, 1.26 to 1.77), transient ischaemic attack (1.11, 1.02 to 1.37), ischaemic stroke (1.33, 1.09 to 1.63), intracerebral haemorrhage (1.37, 1.16 to 1.62), and peripheral arterial disease (1.35; 1.23 to 1.48), but a lower risk of myocardial infarction (0.88, 0.79 to 1.00) or stable angina (0.93, 0.86 to 1.00).
Conclusions Heterogeneous associations exist between level of alcohol consumption and the initial presentation of cardiovascular diseases. This has implications for counselling patients, public health communication, and clinical research, suggesting a more nuanced approach to the role of alcohol in prevention of cardiovascular disease is necessary.
Registration clinicaltrails.gov (NCT01864031).
Contributors: SB and HH conceived the research question with additional input from MD, ER, AB, and MB. JG, SD, and HH participated in development of coding algorithms, the CALIBER research platform, and study design. ADS assisted in defining endpoints and the development of coding algorithms for other variables. SD linked, managed, and provided the data. SB carried out the statistical analysis and wrote the first draft of the manuscript. All authors provided additional intellectual content, contributed to critical revisions of the manuscript, and read and approved the final submitted version. SB is guarantor.
Funding: This work was supported by the National Institute for Health Research (RP-PG-0407-10314), Wellcome Trust (WT 086091/Z/08/Z), the Medical Research Council prognosis research strategy (PROGRESS) Partnership (G0902393/99558), and awards to establish the Farr Institute of Health Informatics Research at UCLPartners, from the Medical Research Council, Arthritis Research UK, British Heart Foundation, Cancer Research UK, Chief Scientist Office, Economic and Social Research Council, Engineering and Physical Sciences Research Council, National Institute for Health Research, National Institute for Social Care and Health Research, and Wellcome Trust (grant MR/K006584/1). SB and AB were supported by grants from the European Research Council (ERC-StG-2012- 309337_AlcoholLifecourse) and the Medical Research Council/Alcohol Research UK (MR/M006638/1). JG was funded by a NIHR doctoral fellowship (DRF-2009-02-50). ADS is supported by a clinical research training fellowship from the Wellcome Trust (0938/30/Z/10/Z). This article presents independent research funded in part by the NIHR. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health. The funders had no role in study design, data collection, analysis or interpretation, decision to publish, or preparation of the manuscript.
Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.
Ethical approval: The study was part of the CALIBER programme, approved by the MINAP Academic Group and by the CPRD independent scientific advisory committee.
Data sharing: Electronic health records are, by definition, considered “sensitive” data in the UK by the Data Protection Act and cannot be shared via public deposition because of information governance restrictions in place to protect patient confidentiality. The CALIBER data portal is available for consultation online at www.caliberresearch.org/. Access to data for external researchers (not affiliated with CALIBER investigators) is provided within the CALIBER “safe haven” environment, which currently requires researchers to be physically based in either UCL (clinical epidemiology group) or the London School of Hygiene and Tropical Medicine (Liam Smeeth). Access to data is available only once approval has been obtained through the individual constituent entities controlling access to the data. The primary care data can be requested via application to the Clinical Practice Research Datalink (https://www.cprd.com); secondary care data can be requested via application to the hospital episode statistics from the UK Health and Social Care Information Centre (www.hscic.gov.uk/hesdata); myocardial infarction registry data are available by application to the National Institute for Cardiovascular Outcomes Research Myocardial Ischaemia National Audit Project (www.ucl.ac.uk/nicor/audits/minap); and mortality data are available by application to the UK Office for National Statistics (www.ons.gov.uk/ons/index.html). The phenotype algorithms described in this paper are available via the CALIBER website at www.caliberresearch.org.
Transparency: The lead author affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned have been explained.
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