A life‐time of hazardous drinking and harm to health among older adults: findings from the Whitehall II prospective cohort study

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Abstract

Aims

To investigate associations of life‐time hazardous and binge drinking with biomarkers of cardiometabolic health, liver function, cardiovascular disease (CVD) and mortality.

Design

Prospective cohort study with median follow‐up time to CVD incidence of 4.5 years.

Setting

London, UK: civil servants within the Whitehall II Study.

Participants

A total of 4820 drinkers aged 59–83 years with biological measurements during the 2011–12 survey.

Measurements

Hazardous drinking was defined as having an AUDIT‐C score ≥ 5 calculated at each decade of life, forming the following groups: never hazardous drinker, former early (stopping before age 50), former later (stopping after age 50), current hazardous drinker and consistent hazardous drinker (hazardous drinker at each decade of life).

Findings

More than half the sample had been hazardous drinkers at some point during their life‐time, comprising former early (< age 50) (19%), former later (≥ age 50) (11%), current (21%) and consistent hazardous drinker (AUDIT‐C ≥ 5 across life (5%). After adjusting for covariates, waist circumference was larger with more persistent hazardous drinking (e.g. compared with never hazardous drinkers, former early had increased waist circumference by 1.17 cm [95% confidence interval (CI) = 0.25‐2.08]; former later by 1.88 cm (CI = 0.77–2.98); current by 2.44 cm (CI = 1.50–3.34) and consistent hazardous drinker by 3.85 cm (CI = 2.23–5.47). Current hazardous drinkers had higher systolic blood pressure (2.44 mmHg, CI = 1.19–3.68) and fatty liver index scores (4.05 mmHg, CI = 2.92–5.18) than never hazardous drinkers. Current hazardous drinkers [hazard ratio (HR) = 2.75, CI = 1.44–5.22) had an elevated risk of stroke, and former later hazardous drinkers had an elevated risk of non‐CVD mortality (HR = 1.93, CI = 1.19–3.14) than never hazardous drinkers. Life‐time binge drinking was associated with larger waist circumferences and poorer liver function compared with never binge drinkers.

Conclusion

Hazardous drinking may increase cardiometabolic risk factors; this is made worse by persistent hazardous drinking throughout life, particularly in relation to weight gain, suggesting benefits of early intervention.

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Most cited references 41

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Alcohol use and burden for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

Maheswar Satpathy, Mika Kivimaki, Shafiu Mohammed … (2019)

Summary Background Alcohol use is a leading risk factor for death and disability, but its overall association with health remains complex given the possible protective effects of moderate alcohol consumption on some conditions. With our comprehensive approach to health accounting within the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we generated improved estimates of alcohol use and alcohol-attributable deaths and disability-adjusted life-years (DALYs) for 195 locations from 1990 to 2016, for both sexes and for 5-year age groups between the ages of 15 years and 95 years and older. Methods Using 694 data sources of individual and population-level alcohol consumption, along with 592 prospective and retrospective studies on the risk of alcohol use, we produced estimates of the prevalence of current drinking, abstention, the distribution of alcohol consumption among current drinkers in standard drinks daily (defined as 10 g of pure ethyl alcohol), and alcohol-attributable deaths and DALYs. We made several methodological improvements compared with previous estimates: first, we adjusted alcohol sales estimates to take into account tourist and unrecorded consumption; second, we did a new meta-analysis of relative risks for 23 health outcomes associated with alcohol use; and third, we developed a new method to quantify the level of alcohol consumption that minimises the overall risk to individual health. Findings Globally, alcohol use was the seventh leading risk factor for both deaths and DALYs in 2016, accounting for 2·2% (95% uncertainty interval [UI] 1·5–3·0) of age-standardised female deaths and 6·8% (5·8–8·0) of age-standardised male deaths. Among the population aged 15–49 years, alcohol use was the leading risk factor globally in 2016, with 3·8% (95% UI 3·2–4·3) of female deaths and 12·2% (10·8–13·6) of male deaths attributable to alcohol use. For the population aged 15–49 years, female attributable DALYs were 2·3% (95% UI 2·0–2·6) and male attributable DALYs were 8·9% (7·8–9·9). The three leading causes of attributable deaths in this age group were tuberculosis (1·4% [95% UI 1·0–1·7] of total deaths), road injuries (1·2% [0·7–1·9]), and self-harm (1·1% [0·6–1·5]). For populations aged 50 years and older, cancers accounted for a large proportion of total alcohol-attributable deaths in 2016, constituting 27·1% (95% UI 21·2–33·3) of total alcohol-attributable female deaths and 18·9% (15·3–22·6) of male deaths. The level of alcohol consumption that minimised harm across health outcomes was zero (95% UI 0·0–0·8) standard drinks per week. Interpretation Alcohol use is a leading risk factor for global disease burden and causes substantial health loss. We found that the risk of all-cause mortality, and of cancers specifically, rises with increasing levels of consumption, and the level of consumption that minimises health loss is zero. These results suggest that alcohol control policies might need to be revised worldwide, refocusing on efforts to lower overall population-level consumption. Funding Bill & Melinda Gates Foundation.

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The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test.

K Bush, D R Kivlahan, M McDonell … (1998)

To evaluate the 3 alcohol consumption questions from the Alcohol Use Disorders Identification Test (AUDIT-C) as a brief screening test for heavy drinking and/or active alcohol abuse or dependence. Patients from 3 Veterans Affairs general medical clinics were mailed questionnaires. A random, weighted sample of Health History Questionnaire respondents, who had 5 or more drinks over the past year, were eligible for telephone interviews (N = 447). Heavy drinkers were oversampled 2:1. Patients were excluded if they could not be contacted by telephone, were too ill for interviews, or were female (n = 54). Areas under receiver operating characteristic curves (AUROCs) were used to compare mailed alcohol screening questionnaires (AUDIT-C and full AUDIT) with 3 comparison standards based on telephone interviews: (1) past year heavy drinking (>14 drinks/week or > or =5 drinks/ occasion); (2) active alcohol abuse or dependence according to the Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition, criteria; and (3) either. Of 393 eligible patients, 243 (62%) completed AUDIT-C and interviews. For detecting heavy drinking, AUDIT-C had a higher AUROC than the full AUDIT (0.891 vs 0.881; P = .03). Although the full AUDIT performed better than AUDIT-C for detecting active alcohol abuse or dependence (0.811 vs 0.786; P<.001), the 2 questionnaires performed similarly for detecting heavy drinking and/or active abuse or dependence (0.880 vs 0.881). Three questions about alcohol consumption (AUDIT-C) appear to be a practical, valid primary care screening test for heavy drinking and/or active alcohol abuse or dependence.

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The Fatty Liver Index: a simple and accurate predictor of hepatic steatosis in the general population

Giorgio Bedogni, Stefano Bellentani, Lucia Miglioli … (2006)

Background Fatty liver (FL) is the most frequent liver disease in Western countries. We used data from the Dionysos Nutrition & Liver Study to develop a simple algorithm for the prediction of FL in the general population. Methods 216 subjects with and 280 without suspected liver disease were studied. FL was diagnosed by ultrasonography and alcohol intake was assessed using a 7-day diary. Bootstrapped stepwise logistic regression was used to identify potential predictors of FL among 13 variables of interest [gender, age, ethanol intake, alanine transaminase, aspartate transaminase, gamma-glutamyl-transferase (GGT), body mass index (BMI), waist circumference, sum of 4 skinfolds, glucose, insulin, triglycerides, and cholesterol]. Potential predictors were entered into stepwise logistic regression models with the aim of obtaining the most simple and accurate algorithm for the prediction of FL. Results An algorithm based on BMI, waist circumference, triglycerides and GGT had an accuracy of 0.84 (95%CI 0.81–0.87) in detecting FL. We used this algorithm to develop the "fatty liver index" (FLI), which varies between 0 and 100. A FLI < 30 (negative likelihood ratio = 0.2) rules out and a FLI ≥ 60 (positive likelihood ratio = 4.3) rules in fatty liver. Conclusion FLI is simple to obtain and may help physicians select subjects for liver ultrasonography and intensified lifestyle counseling, and researchers to select patients for epidemiologic studies. Validation of FLI in external populations is needed before it can be employed for these purposes.

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Author and article information

Contributors

Linda Ng Fat:

ORCID: https://orcid.org/0000-0002-7282-9526

l.ngfat@ucl.ac.uk

Journal

Journal ID (nlm-ta): Addiction

Journal ID (iso-abbrev): Addiction

Journal ID (doi): 10.1111/(ISSN)1360-0443

Journal ID (publisher-id): ADD

Title: Addiction (Abingdon, England)

Publisher: John Wiley and Sons Inc. (Hoboken )

ISSN (Print): 0965-2140

ISSN (Electronic): 1360-0443

Publication date (Electronic): 31 March 2020

Publication date (Print): October 2020

Volume: 115

Issue: 10 ( doiID: 10.1111/add.v115.10 )

Pages: 1855-1866

Affiliations

[ ¹ ] Research Department of Epidemiology and Public Health University College London London UK

[ ² ] British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care University of Cambridge, Strangeways Research Laboratory Cambridge UK

[ ³ ] National Institute for Health Research Blood and Transplant Unit in Donor Health and Genomics at the University of Cambridge, Strangeways Research Laboratory Cambridge UK

[ ⁴ ] Stroke Research Group, Department of Clinical Neurosciences Cambridge Biomedical Campus Cambridge UK

Author notes

[*] [* ] Correspondence to: Linda Ng Fat, Research Department of Epidemiology and Public Health, 1–19 Torrington Place, University College London, London, WC1E 7HB, UK. E‐mail: l.ngfat@ 123456ucl.ac.uk

Author information

Linda Ng Fat https://orcid.org/0000-0002-7282-9526

Steven Bell https://orcid.org/0000-0001-6774-3149

Annie Britton https://orcid.org/0000-0002-6412-5430

Article

Publisher ID: ADD15013 Other ID: ADD-19-0244.R2

DOI: 10.1111/add.15013

PMC ID: 7487058

PubMed ID: 32233123

SO-VID: baf2c9f1-17e8-4b9d-983e-3ea2c5177576

License:

This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

History

Date received : 17 March 2019

Date revision received : 19 July 2019

Date accepted : 12 February 2020

Page count

Figures: 3, Tables: 3, Pages: 12, Words: 4224

Funding

Funded by: Alcohol Research UK , open-funder-registry 10.13039/501100000280;

Award ID: MR/M006638/1

Funded by: European Research Council , open-funder-registry 10.13039/100010663;

Award ID: RG/13/2/30098

Funded by: Medical Research Council , open-funder-registry 10.13039/501100000265;

Award ID: MR/M006638/1

Funded by: US National Institutes of Health

Award ID: R01AG013196

Award ID: R01HL36310

Funded by: British Heart Foundation , open-funder-registry 10.13039/501100000274;

Award ID: RG/13/2/30098

Funded by: UK Medical Research Council

Award ID: G0902037

Award ID: MR/K013351/1

Funded by: European Research Council , open-funder-registry 10.13039/501100000781;

Award ID: ERC‐StG‐2012‐309337_AlcoholLifecourse

Funded by: UK Medical Research Council/Alcohol Research UK

Award ID: MR/M006638/1

Custom metadata

source-schema-version-number 2.0

cover-date October 2020

details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.3 mode:remove_FC converted:29.10.2020

ScienceOpen disciplines: Clinical Psychology & Psychiatry

Keywords: ageing,binge drinking,biomarkers,cardiometabolic,cardiovascular,hazardous consumption,liver function,mortality

Data availability:

ScienceOpen disciplines: Clinical Psychology & Psychiatry

Keywords: ageing, binge drinking, biomarkers, cardiometabolic, cardiovascular, hazardous consumption, liver function, mortality

A life‐time of hazardous drinking and harm to health among older adults: findings from the Whitehall II prospective cohort study

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Abstract

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UCL: UN SDG 03 Good Health and Well-Being

Most cited references 41

Alcohol use and burden for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test.

The Fatty Liver Index: a simple and accurate predictor of hepatic steatosis in the general population

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