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BMI indicates body mass index; SES, socioeconomic status.

a Variables smoking status, SES, drinking pattern, former drinker bias only, occasional drinker bias, median age, and gender were removed.

b Variables race, diet, exercise, BMI, country, follow-up year, publication year, and unhealthy people exclusion were removed.

eAppendix. Methodology of Meta-analysis on All-Cause Mortality and Alcohol Consumption

eReferences

eFigure 1. Flowchart of Systematic Search Process for Studies of Alcohol Consumption and Risk of All-Cause Mortality

eTable 1. Newly Included 20 Studies (194 Risk Estimates) of All-Cause Mortality and Consumption in 2015 to 2022

eFigure 2. Funnel Plot of Log-Relative Risk (In(RR)) of All-Cause Mortality Due to Alcohol Consumption Against Inverse of Standard Error of In(RR)

eFigure 3. Relative Risk (95% CI) of All-Cause Mortality Due to Any Alcohol Consumption Without Any Adjustment for Characteristics of New Studies Published between 2015 and 2022

eFigure 4. Unadjusted, Partially Adjusted, and Fully Adjusted Relative Risk (RR) of All-Cause Mortality for Drinkers (vs Nondrinkers), 1980 to 2022

eTable 2. Statistical Analysis of Unadjusted Mean Relative Risk (RR) of All-Cause Mortality for Different Categories of Drinkers for Testing Publication Bias and Heterogeneity of RR Estimates From Included Studies

eTable 3. Mean Relative Risk (RR) Estimates of All-Cause Mortality Due to Alcohol Consumption up to 2022 for Subgroups (Cohorts Recruited 50 Years of Age or Younger and Followed up to 60 Years of Age)

Data Sharing Statement

• Errors in Figure and Supplement JAMA Network Open Correction May 9, 2023

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Zhao J , Stockwell T , Naimi T , Churchill S , Clay J , Sherk A. Association Between Daily Alcohol Intake and Risk of All-Cause Mortality : A Systematic Review and Meta-analyses . JAMA Netw Open. 2023;6(3):e236185. doi:10.1001/jamanetworkopen.2023.6185

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Association Between Daily Alcohol Intake and Risk of All-Cause Mortality : A Systematic Review and Meta-analyses

• 1 Canadian Institute for Substance Use Research, University of Victoria, Victoria, British Columbia, Canada
• 2 Department of Psychology, University of Portsmouth, Portsmouth, Hampshire, United Kingdom
• Correction Errors in Figure and Supplement JAMA Network Open

Question   What is the association between mean daily alcohol intake and all-cause mortality?

Findings   This systematic review and meta-analysis of 107 cohort studies involving more than 4.8 million participants found no significant reductions in risk of all-cause mortality for drinkers who drank less than 25 g of ethanol per day (about 2 Canadian standard drinks compared with lifetime nondrinkers) after adjustment for key study characteristics such as median age and sex of study cohorts. There was a significantly increased risk of all-cause mortality among female drinkers who drank 25 or more grams per day and among male drinkers who drank 45 or more grams per day.

Meaning   Low-volume alcohol drinking was not associated with protection against death from all causes.

Importance   A previous meta-analysis of the association between alcohol use and all-cause mortality found no statistically significant reductions in mortality risk at low levels of consumption compared with lifetime nondrinkers. However, the risk estimates may have been affected by the number and quality of studies then available, especially those for women and younger cohorts.

Objective   To investigate the association between alcohol use and all-cause mortality, and how sources of bias may change results.

Data Sources   A systematic search of PubMed and Web of Science was performed to identify studies published between January 1980 and July 2021.

Study Selection   Cohort studies were identified by systematic review to facilitate comparisons of studies with and without some degree of controls for biases affecting distinctions between abstainers and drinkers. The review identified 107 studies of alcohol use and all-cause mortality published from 1980 to July 2021.

Data Extraction and Synthesis   Mixed linear regression models were used to model relative risks, first pooled for all studies and then stratified by cohort median age (<56 vs ≥56 years) and sex (male vs female). Data were analyzed from September 2021 to August 2022.

Main Outcomes and Measures   Relative risk estimates for the association between mean daily alcohol intake and all-cause mortality.

Results   There were 724 risk estimates of all-cause mortality due to alcohol intake from the 107 cohort studies (4 838 825 participants and 425 564 deaths available) for the analysis. In models adjusting for potential confounding effects of sampling variation, former drinker bias, and other prespecified study-level quality criteria, the meta-analysis of all 107 included studies found no significantly reduced risk of all-cause mortality among occasional (>0 to <1.3 g of ethanol per day; relative risk [RR], 0.96; 95% CI, 0.86-1.06; P  = .41) or low-volume drinkers (1.3-24.0 g per day; RR, 0.93; P  = .07) compared with lifetime nondrinkers. In the fully adjusted model, there was a nonsignificantly increased risk of all-cause mortality among drinkers who drank 25 to 44 g per day (RR, 1.05; P  = .28) and significantly increased risk for drinkers who drank 45 to 64 and 65 or more grams per day (RR, 1.19 and 1.35; P  < .001). There were significantly larger risks of mortality among female drinkers compared with female lifetime nondrinkers (RR, 1.22; P  = .03).

Conclusions and Relevance   In this updated systematic review and meta-analysis, daily low or moderate alcohol intake was not significantly associated with all-cause mortality risk, while increased risk was evident at higher consumption levels, starting at lower levels for women than men.

The proposition that low-dose alcohol use protects against all-cause mortality in general populations continues to be controversial. 1 Observational studies tend to show that people classified as “moderate drinkers” have longer life expectancy and are less likely to die from heart disease than those classified as abstainers. 2 Systematic reviews and meta-analyses of this literature 3 confirm J-shaped risk curves (protective associations at low doses with increasing risk at higher doses). However, mounting evidence suggests these associations might be due to systematic biases that affect many studies. For example, light and moderate drinkers are systematically healthier than current abstainers on a range of health indicators unlikely to be associated with alcohol use eg, dental hygiene, exercise routines, diet, weight, income 4 ; lifetime abstainers may be systematically biased toward poorer health 5 ; studies fail to control for biases in the abstainer reference group, in particular failing to remove “sick quitters” or former drinkers, many of whom cut down or stop for health reasons 2 ; and most studies have nonrepresentative samples leading to an overrepresentation of older White men. Adjustment of cohort samples to make them more representative has been shown to eliminate apparent protective associations. 6 Mendelian randomization studies that control for the confounding effects of sociodemographic and environmental factors find no evidence of cardioprotection. 7

We published 2 previous systematic reviews and meta-analyses that investigated these hypotheses. The first of these focused on all-cause mortality, 8 finding negligible reductions in mortality risk with low-volume alcohol use when study-level controls were introduced for potential bias and confounding, such as the widespread practice of misclassifying former drinkers and/or current occasional drinkers as abstainers (ie, not restricting reference groups to lifetime abstainers). 8 Our alcohol and coronary heart disease (CHD) mortality meta-analysis of 45 cohort studies 9 found that CHD mortality risk differed widely by age ranges and sex of study populations. In particular, young cohorts followed up to old age did not show significant cardio-protection for low-volume use. Cardio-protection was only apparent among older cohorts that are more exposed to lifetime selection biases (ie, increasing numbers of “sick-quitters” in the abstainer reference groups and the disproportionate elimination of drinkers from the study sample who had died or were unwell).

The present study updates our earlier systematic review and meta-analysis for all-cause mortality and alcohol use, 8 including studies published up to July 2021 (ie, 6.5 years of additional publications). The study also investigated the risk of all-cause mortality for alcohol consumption according to (1) median ages of the study populations (younger than 56 years or 56 years and older), replicating the methods of Zhao et al 9 ; (2) the sex distribution of the study populations, and (3) studies of cohorts recruited before a median age of 51 years of age and followed up in health records until a median age of at least 60 years (ie, with stricter rules to further minimize lifetime selection biases). Because younger cohorts followed up to an age at which they may experience heart disease are less likely to be affected by lifetime selection biases, 9 we hypothesized that such studies would be less likely to show reduced mortality risks for low-volume drinkers. Finally, we reran the analyses using occasional drinkers (<1 drink per week) as the reference, for whom physiological health benefits are unlikely. Occasional drinkers are a more appropriate reference group, given evidence demonstrating that lifetime abstainers may be biased toward ill health. 10

The present study updates the systematic reviews and meta-analyses described above 8 by including studies published up to July 2021 to investigate whether the risk differed for subgroups. The study protocol was preregistered on the Open Science Framework. 11 Inclusion criteria, search strategy, study selection, data extraction, and statistical analytical methods of the study are summarized in later sections (see eAppendix in Supplement 1 for more details).

The systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses ( PRISMA ) reporting guideline. 12 The review sought cohort studies of all-cause mortality and alcohol consumption. We identified all potentially relevant articles published up to July 31, 2021, regardless of language, by searching PubMed and Web of Science, through reference list cross-checking of previous meta-analyses (eFigure 1 in Supplement 1 ). There were 87 studies identified by Stockwell et al. 8 After inclusion of 20 new studies meeting inclusion criteria, there were a total of 107 cohort studies (eTable 1 in Supplement 1 ). 13 - 32

Three coders (J. Z., F. A., and J. C.) reviewed all eligible studies to extract and code data independently from all studies fulfilling the inclusion criteria. Data extracted included (1) outcome, all-cause mortality; (2) measures of alcohol consumption; (3) study characteristics, including cohort ages at recruitment and follow-up; (4) types of misclassification error of alcohol consumers and abstainers; (5) controlled variables in individual studies. Alcoholic drinks were converted into grams per day according to country-specific definitions if not otherwise defined. 33 , 34

We also assessed publication bias, heterogeneity, and confounding of covariates that might potentially affect the association of interest using several statistical approaches. 35 - 41 Relative risk (RR), including hazard ratios or rate ratios, were converted to natural log-transformed formats to deal with skewness. Publication bias was assessed through visual inspection of the funnel plot of log-RR of all-cause mortality due to alcohol consumption against the inverse standard error of log-RR 42 and Egger’s linear regression method. 36 We also plotted forest graphs of log-RR of all-cause mortality for any level of drinking to assess heterogeneity among studies. 42 The between-study heterogeneity of RRs were assessed using Cochran Q 37 and the I 2 statistic. 38 If heterogeneity was detected, mixed-effects models were used to obtain the summarized RR estimates. Mixed-effects regression analyses were performed in which drinking groups and control variables were treated as fixed-effects with a random study effect because of significant heterogeneity. 43

All analyses were weighted by the inverse of the estimated variance of the natural log relative risk. Variance was estimated from reported standard errors, confidence intervals, or number of deaths. The weights for each individual study were created using the inverse variance weight scheme and used in mixed regression analysis to get maximum precision for the main results of the meta-analysis. 42 In comparison with lifetime abstainers, the study estimated the mean RR of all-cause mortality for former drinkers (ie, now completely abstaining), current occasional (<9.1 g per week), low-volume (1.3-24.0 g per day), medium-volume (25.0-44.0 g per day), high-volume (45.0-64.0 g) and highest-volume drinkers (≥65.0 grams per day). The analyses adjusted for the potential confounding effects of study characteristics including the median age and sex distribution of study samples, drinker biases, country where a study was conducted, follow-up years and presence or absence of confounders. Analyses were also repeated using occasional drinkers as the reference group. We used t tests to calculate P values, and significance was set at .05. All statistical analyses were performed using SAS version 9.4 (SAS Institute) and the SAS MIXED procedure was used to model the log-transformed RR. 44 Data were analyzed from September 2021 to August 2022.

There were 724 estimates of the risk relationship between level of alcohol consumption and all-cause mortality from 107 unique studies 13 - 32 , 45 - 131 , including 4 838 825 participants and 425 564 deaths available for the analysis. Table 1 describes the sample characteristics of the metadata. Of 39 studies 13 , 15 , 18 , 21 , 23 - 26 , 29 , 31 , 45 - 47 , 49 , 50 , 52 - 54 , 57 - 59 , 62 , 64 , 70 , 80 , 81 , 85 , 87 , 91 , 94 , 96 , 100 , 104 , 107 , 118 , 124 , 125 , 127 , 130 reporting RR estimates for men and women separately, 33 14 , 17 , 48 , 51 , 61 , 63 , 66 , 68 , 69 , 72 , 76 , 79 , 83 , 84 , 86 , 88 , 90 , 92 , 93 , 97 , 98 , 101 , 103 , 105 , 109 - 111 , 113 - 115 , 119 , 120 , 128 were for males only, 8 16 , 65 , 73 , 99 , 102 , 108 , 112 , 123 for females only, and 30 13 , 19 - 22 , 26 - 30 , 32 , 55 , 56 , 67 , 71 , 74 , 75 , 77 , 78 , 82 , 84 , 89 , 95 , 106 , 116 , 117 , 121 , 122 , 126 , 129 for both sexes. Twenty-one studies 13 , 17 , 19 , 21 , 22 , 26 , 27 , 45 - 58 (220 risk estimates) were free from abstainer bias (ie, had a reference group of strictly defined lifetime abstainers). There were 50 studies 14 - 16 , 18 , 20 , 23 - 25 , 29 , 59 - 99 (265 risk estimates) with both former and occasional drinker bias; 28 studies 28 , 30 - 32 , 100 - 122 , 130 (177 risk estimates) with only former drinker bias; and 8 studies 123 - 129 , 131 (62 risk estimates) with only occasional drinker bias.

Unadjusted mean RR estimates for most study subgroups categorized by methods/sample characteristics showed markedly or significantly higher RRs for alcohol consumers as a group vs abstainers. Exceptions were for studies with less than 10 years of follow-up and those with some form of abstainer bias ( Table 1 ). Bivariable analyses showed that mortality risks for alcohol consumers varied considerably according to other study characteristics, such as quality of the alcohol consumption measure, whether unhealthy individuals were excluded at baseline, and whether socioeconomic status was controlled for ( Table 1 ).

No evidence of publication bias was detected either by inspection of symmetry in the funnel plot of log-RR estimates and their inverse standard errors (eFigure 2 in Supplement 1 ) or by Egger linear regression analysis (eTable 2 in Supplement 1 , all P > .05 for each study group). Significant heterogeneity was observed across studies for all drinking categories confirmed by both the Q statistic ( Q 723  = 5314.80; P  < .001) and I 2 estimates (all >85.87%). (See eFigure 3 in Supplement 1 for forest plot of unadjusted risk estimates of mortality risks for the 20 newly identified studies).

Pooled unadjusted estimates (724 observations) showed significantly higher risk for former drinkers (RR, 1.22; 95% CI, 1.11-1.33; P  = .001) and significantly lower risk for low-volume drinkers (RR, 0.85; 95% CI, 0.81-0.88; P  = .001) compared with abstainers as defined in the included studies ( Table 2 ; eFigure 4 in Supplement 1 ). In the fully adjusted model, mortality RR estimates increased for all drinking categories, becoming nonsignificant for low-volume drinkers (RR, 0.93; 95% CI, 0.85-1.01; P  = .07), occasional drinkers (>0 to <1.3 g of ethanol per day; RR, 0.96; 95% CI, 0.86-1.06; P  = .41), and drinkers who drank 25 to 44 g per day (RR, 1.05; 95% CI, 0.96-1.14; P  = .28). There was a significantly increased risk among drinkers who drank 45 to 64 g per day (RR, 1.19; 95% CI, 1.07-1.32; P  < .001) and 65 or more grams (RR, 1.35; 95% CI, 1.23-1.47; P  < .001). The Figure shows the changes in RR estimates for low-volume drinkers when removing each covariate from the fully adjusted model. In most cases, removing study-level covariates tended to yield lower risk estimates from alcohol use.

Table 2 presents the RR estimates when occasional drinkers were the reference group. In fully adjusted models, higher though nonsignificant mortality risks were observed for both abstainers and medium-volume drinkers (RR, 1.04; 95% CI, 0.94-1.16; P  = .44 and RR, 1.09; 95% CI, 0.96-1.25; P  = .19, respectively). There were significantly elevated risks for both high and higher volume drinkers (RR, 1.24; 95% CI, 1.07-1.44; P  = .004 and RR, 1.41; 95% CI, 1.23-1.61; . P  = 001, respectively).

As hypothesized, there was a significant interaction between cohort age and mortality risk ( P  = .02; F 601  = 2.93) and so RR estimates for drinkers were estimated in analyses stratified by median age of the study populations at enrollment ( Table 3 ). In unadjusted and partially adjusted analyses, older cohorts displayed larger reductions in mortality risk associated with low-volume consumption than younger cohorts. However, in fully adjusted analyses with multiple covariates included for study characteristics, these differences disappeared. Younger cohorts also displayed greater mortality risks than older cohorts at higher consumption levels. Among studies in which participants were recruited at age 50 years or younger and followed up to age 60 years (ie, there was likely reduced risk of lifetime selection bias) higher RR estimates were observed for all drinking groups vs lifetime abstainers. These differences were significant in all drinking groups except low-volume drinkers (eTable 3 in Supplement 1 ).

Across all levels of alcohol consumption, female drinkers had a higher RR of all-cause mortality than males ( P for interaction  = .001). As can be seen in Table 4 , all female drinkers had a significantly increased mortality risk compared with female lifetime nondrinkers (RR, 1.22; 95% CI, 1.02-1.46; P  = .03). Compared with lifetime abstainers, there was significantly increased risk of all-cause mortality among male drinkers who drank 45 to 64 g per day (RR, 1.15; 95% CI, 1.03-1.28; P  = .01) and drank 65 or more (RR, 1.34; 95% CI, 1.23-1.47; P  < .001), and among female drinkers who drank 25 to 44 g per day (RR, 1.21; 95% CI, 1.08-1.36; P  < .01), 45 to 64 g (RR, 1.34; 95% CI, 1.11-1.63; P  < .01) and 65 or more grams (RR, 1.61; 95% CI, 1.44-1.80; P  = .001).

In fully adjusted, prespecified models that accounted for effects of sampling, between-study variation, and potential confounding from former drinker bias and other study-level covariates, our meta-analysis of 107 studies found (1) no significant protective associations of occasional or low-volume drinking (moderate drinking) with all-cause mortality; and (2) an increased risk of all-cause mortality for drinkers who drank 25 g or more and a significantly increased risk when drinking 45 g or more per day.

Several meta-analytic strategies were used to explore the role of abstainer reference group biases caused by drinker misclassification errors and also the potential confounding effects of other study-level quality covariates in studies. 2 Drinker misclassification errors were common. Of 107 studies identified, 86 included former drinkers and/or occasional drinkers in the abstainer reference group, and only 21 were free of both these abstainer biases. The importance of controlling for former drinker bias/misclassification is highlighted once more in our results which are consistent with prior studies showing that former drinkers have significantly elevated mortality risks compared with lifetime abstainers.

In addition to presenting our fully adjusted models, a strength of the study was the examination of the differences in relative risks according to unadjusted and partially adjusted models, including the effect of removing individual covariates from the fully adjusted model. We found evidence that abstainer biases and other study characteristics changed the shape of the risk relationship between mortality and rising alcohol consumption, and that most study-level controls increased the observed risks from alcohol, or attenuated protective associations at low levels of consumption such that they were no longer significant. The reduced RR estimates for occasional or moderate drinkers observed without adjustment may be due to the misclassification of former and occasional drinkers into the reference group, a possibility which is more likely to have occurred in studies of older cohorts which use current abstainers as the reference group. This study also demonstrates the degree to which observed associations between consumption and mortality are highly dependent on the modeling strategy used and the degree to which efforts are made to minimize confounding and other threats to validity.

It also examined risk estimates when using occasional drinkers rather than lifetime abstainers as the reference group. The occasional drinker reference group avoids the issue of former drinker misclassification that can affect the abstainer reference group, and may reduce confounding to the extent that occasional drinkers are more like low-volume drinkers than are lifetime abstainers. 2 , 8 , 132 In the unadjusted and partially adjusted analyses, using occasional drinkers as the reference group resulted in nonsignificant protective associations and lower point estimates for low-volume drinkers compared with significant protective associations and higher point estimates when using lifetime nondrinkers as the reference group. In the fully adjusted models, there were nonsignificant protective associations for low-volume drinkers whether using lifetime abstainers or occasional drinkers as the reference group, though this was only a RR of 0.97 for the latter.

Across all studies, there were few differences in risk for studies when stratified by median age of enrollment above or below age 56 years in the fully adjusted analyses. However, in the subset of studies who enrolled participants aged 50 years or younger who were followed for at least 10 years, occasional drinkers and medium-volume drinkers had significantly increased risk of mortality and substantially higher risk estimates for high- and higher-volume consumption compared with results from all studies. This is consistent with our previous meta-analysis for CHD, 9 in which younger cohorts followed up to older age did not show a significantly beneficial association of low-volume consumption, while older cohorts, with more opportunity for lifetime selection bias, showed marked, significant protective associations.

Our study also found sex differences in the risk of all-cause mortality. A larger risk of all-cause mortality for women than men was observed when drinking 25 or more grams per day, including a significant increase in risk for medium-level consumption for women that was not observed for men. However, mortality risk for mean consumption up to 25 g per day were very similar for both sexes.

A number of limitations need to be acknowledged. A major limitation involves imperfect measurement of alcohol consumption in most included studies, and the fact that consumption in many studies was assessed at only 1 point in time. Self-reported alcohol consumption is underreported in most epidemiological studies 133 , 134 and even the classification of drinkers as lifetime abstainers can be unreliable, with several studies in developed countries finding that the majority of self-reported lifetime abstainers are in fact former drinkers. 135 , 136 If this is the case, the risks of various levels of alcohol consumption relative to presumed lifetime abstainers are underestimates. Merely removing former drinkers from analyses may bias studies in favor of drinkers, since former drinkers may be unhealthy, and should rightly be reallocated to drinking groups according to their history. However, this has only been explored in very few studies. Our study found that mortality risk differed significantly by cohort age and sex. It might be that the risk is also higher for other subgroups, such as people living with HIV, 137 a possibility future research should investigate.

The number of available studies in some stratified analyses was small, so there may be limited power to control for potential study level confounders. However, the required number of estimates per variable for linear regression can be much smaller than in logistic regression, and a minimum of at least 2 estimates per variable is recommended for linear regression analysis, 138 suggesting the sample sizes were adequate in all models presented. It has been demonstrated that a pattern of binge (ie, heavy episodic) drinking removes the appearance of reduced health risks even when mean daily volume is low. 139 Too few studies adequately controlled for this variable to investigate its association with different outcomes across studies. Additionally, our findings only apply to the net effect of alcohol at different doses on all-cause mortality, and different risk associations likely apply for specific disease categories. The biases identified here likely apply to estimates of risk for alcohol and all diseases. It is likely that correcting for these biases will raise risk estimates for many types of outcome compared with most existing estimates.

This updated meta-analysis did not find significantly reduced risk of all-cause mortality associated with low-volume alcohol consumption after adjusting for potential confounding effects of influential study characteristics. Future longitudinal studies in this field should attempt to minimize lifetime selection biases by not including former and occasional drinkers in the reference group, and by using younger cohorts (ie, age distributions that are more representative of drinkers in the general population) at baseline.

Accepted for Publication: February 17, 2023.

Published: March 31, 2023. doi:10.1001/jamanetworkopen.2023.6185

Correction: This article was corrected on May 9, 2023, to fix errors in the Figure and Supplement.

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2023 Zhao J et al. JAMA Network Open .

Corresponding Author: Jinhui Zhao, PhD, Canadian Institute for Substance Use Research, University of Victoria, PO Box 1700 STN CSC, Victoria, BC V8Y 2E4, Canada ( [email protected] ).

Author Contributions: Drs Zhao and Stockwell had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Zhao, Stockwell, Naimi, Churchill, Sherk.

Acquisition, analysis, or interpretation of data: Zhao, Stockwell, Naimi, Clay.

Drafting of the manuscript: Zhao, Stockwell, Clay.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Zhao, Churchill.

Obtained funding: Zhao, Stockwell, Sherk.

Administrative, technical, or material support: Zhao, Stockwell, Naimi.

Supervision: Zhao, Stockwell, Naimi.

Conflict of Interest Disclosures: Dr Stockwell reported receiving personal fees from Ontario Public Servants Employees Union for expert witness testimony and personal fees from Alko outside the submitted work. Dr Sherk reported receiving grants from Canadian Centre on Substance Use and Addiction (CCSA) during the conduct of the study. No other disclosures were reported.

Funding/Support: This study was partly funded by the CCSA as a subcontract for a Health Canada grant to develop guidance for Canadians on alcohol and health.

Role of the Funder/Sponsor: Health Canada had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. CCSA staff conducted a preliminary search to identify potentially relevant articles but did not participate in decisions about inclusion/exclusion of studies, coding, analysis, interpretation of results or approving the final manuscript.

Data Sharing Statement: See Supplement 2 .

Additional Contributions: We gratefully acknowledge contributions by Christine Levesque, PhD (CCSA), and Nitika Sanger, PhD (CCSA), who conducted a preliminary literature search for potentially relevant articles. We also acknowledge the leadership of Drs Catherine Paradis, PhD (CCSA), and Peter Butt, MD (University of Saskatchewan), who cochaired the process of developing Canada’s new guidance on alcohol and health, a larger project which contributed some funds for the work undertaken for this study. We are grateful to Fariha Alam, MPH (Canadian Institute for Substance Use and Research), for her help coding the studies used in this study. None of them received any compensation beyond their normal salaries for this work.

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• Open access
• Published: 13 November 2019

Evidence-based models of care for the treatment of alcohol use disorder in primary health care settings: protocol for systematic review

• Susan A. Rombouts 1 ,
• James Conigrave 2 ,
• Eva Louie 1 ,
• Paul Haber 1 , 3 &
• Kirsten C. Morley   ORCID: orcid.org/0000-0002-0868-9928 1  

Systematic Reviews volume  8 , Article number:  275 ( 2019 ) Cite this article

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Alcohol use disorder (AUD) is highly prevalent and accounts globally for 1.6% of disability-adjusted life years (DALYs) among females and 6.0% of DALYs among males. Effective treatments for AUDs are available but are not commonly practiced in primary health care. Furthermore, referral to specialized care is often not successful and patients that do seek treatment are likely to have developed more severe dependence. A more cost-efficient health care model is to treat less severe AUD in a primary care setting before the onset of greater dependence severity. Few models of care for the management of AUD in primary health care have been developed and with limited implementation. This proposed systematic review will synthesize and evaluate differential models of care for the management of AUD in primary health care settings.

We will conduct a systematic review to synthesize studies that evaluate the effectiveness of models of care in the treatment of AUD in primary health care. A comprehensive search approach will be conducted using the following databases; MEDLINE (1946 to present), PsycINFO (1806 to present), Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials (CENTRAL) (1991 to present), and Embase (1947 to present).

Reference searches of relevant reviews and articles will be conducted. Similarly, a gray literature search will be done with the help of Google and the gray matter tool which is a checklist of health-related sites organized by topic. Two researchers will independently review all titles and abstracts followed by full-text review for inclusion. The planned method of extracting data from articles and the critical appraisal will also be done in duplicate. For the critical appraisal, the Cochrane risk of bias tool 2.0 will be used.

This systematic review and meta-analysis aims to guide improvement of design and implementation of evidence-based models of care for the treatment of alcohol use disorder in primary health care settings. The evidence will define which models are most promising and will guide further research.

Protocol registration number

PROSPERO CRD42019120293.

Peer Review reports

It is well recognized that alcohol use disorders (AUD) have a damaging impact on the health of the population. According to the World Health Organization (WHO), 5.3% of all global deaths were attributable to alcohol consumption in 2016 [ 1 ]. The 2016 Global Burden of Disease Study reported that alcohol use led to 1.6% (95% uncertainty interval [UI] 1.4–2.0) of total DALYs globally among females and 6.0% (5.4–6.7) among males, resulting in alcohol use being the seventh leading risk factor for both premature death and disability-adjusted life years (DALYs) [ 2 ]. Among people aged 15–49 years, alcohol use was the leading risk factor for mortality and disability with 8.9% (95% UI 7.8–9.9) of all attributable DALYs for men and 2.3% (2.0–2.6) for women [ 2 ]. AUD has been linked to many physical and mental health complications, such as coronary heart disease, liver cirrhosis, a variety of cancers, depression, anxiety, and dementia [ 2 , 3 ]. Despite the high morbidity and mortality rate associated with hazardous alcohol use, the global prevalence of alcohol use disorders among persons aged above 15 years in 2016 was stated to be 5.1% (2.5% considered as harmful use and 2.6% as severe AUD), with the highest prevalence in the European and American region (8.8% and 8.2%, respectively) [ 1 ].

Effective and safe treatment for AUD is available through psychosocial and/or pharmacological interventions yet is not often received and is not commonly practiced in primary health care. While a recent European study reported 8.7% prevalence of alcohol dependence in primary health care populations [ 4 ], the vast majority of patients do not receive the professional treatment needed, with only 1 in 5 patients with alcohol dependence receiving any formal treatment [ 4 ]. In Australia, it is estimated that only 3% of individuals with AUD receive approved pharmacotherapy for the disorder [ 5 , 6 ]. Recognition of AUD in general practice uncommonly leads to treatment before severe medical and social disintegration [ 7 ]. Referral to specialized care is often not successful, and those patients that do seek treatment are likely to have more severe dependence with higher levels of alcohol use and concurrent mental and physical comorbidity [ 4 ].

Identifying and treating early stage AUDs in primary care settings can prevent condition worsening. This may reduce the need for more complex and more expensive specialized care. The high prevalence of AUD in primary health care and the chronic relapsing character of AUD make primary care a suitable and important location for implementing evidence-based interventions. Successful implementation of treatment models requires overcoming multiple barriers. Qualitative studies have identified several of those barriers such as limited time, limited organizational capacity, fear of losing patients, and physicians feeling incompetent in treating AUD [ 8 , 9 , 10 ]. Additionally, a recent systematic review revealed that diagnostic sensitivity of primary care physicians in the identification of AUD was 41.7% and that only in 27.3% alcohol problems were recorded correctly in primary care records [ 11 ].

Several models for primary care have been created to increase identification and treatment of patients with AUD. Of those, the model, screening, brief interventions, and referral to specialized treatment for people with severe AUD (SBIRT [ 12 ]) is most well-known. Multiple systematic reviews exist, confirming its effectiveness [ 13 , 14 , 15 ], although implementation in primary care has been inadequate. Moreover, most studies have looked primarily at SBIRT for the treatment of less severe AUD [ 16 ]. In the treatment of severe AUD, efficacy of SBIRT is limited [ 16 ]. Additionally, many patient referred to specialized care often do not attend as they encounter numerous difficulties in health care systems including stigmatization, costs, lack of information about existing treatments, and lack of non-abstinence-treatment goals [ 7 ]. An effective model of care for improved management of AUD that can be efficiently implemented in primary care settings is required.

Review objective

This proposed systematic review will synthesize and evaluate differential models of care for the management of AUD in primary health care settings. We aim to evaluate the effectiveness of the models of care in increasing engagement and reducing alcohol consumption.

By providing this overview, we aim to guide improvement of design and implementation of evidence-based models of care for the treatment of alcohol use disorder in primary health care settings.

The systematic review is registered in PROSPERO international prospective register of systematic reviews (CRD42019120293) and the current protocol has been written according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) recommended for systematic reviews [ 17 ]. A PRISMA-P checklist is included as Additional file  1 .

Eligibility criteria

Criteria for considering studies for this review are classified by the following:

Study design

Both individualized and cluster randomized trials will be included. Masking of patients and/or physicians is not an inclusion criterion as it is often hard to accomplish in these types of studies.

Patients in primary health care who are identified (using screening tools or by primary health care physician) as suffering from AUD (from mild to severe) or hazardous alcohol drinking habits (e.g., comorbidity, concurrent medication use). Eligible patients need to have had formal assessment of AUD with diagnostic tools such as Diagnostic and Statistical Manual of Mental Disorders (DSM-IV/V) or the International Statistical Classification of Diseases and Related Health Problems (ICD-10) and/or formal assessment of hazardous alcohol use assessed by the Comorbidity Alcohol Risk Evaluation Tool (CARET) or the Alcohol Use Disorders Identification test (AUDIT) and/or alcohol use exceeding guideline recommendations to reduce health risks (e.g., US dietary guideline (2015–2020) specifies excessive drinking for women as ≥ 4 standard drinks (SD) on any day and/or ≥ 8 SD per week and for men ≥ 5 SD on any day and/or ≥ 15 SD per week).

Studies evaluating models of care for additional diseases (e.g., other dependencies/mental health) other than AUD are included when they have conducted data analysis on the alcohol use disorder patient data separately or when 80% or more of the included patients have AUD.

Intervention

The intervention should consist of a model of care; therefore, it should include multiple components and cover different stages of the care pathway (e.g., identification of patients, training of staff, modifying access to resources, and treatment). An example is the Chronic Care Model (CCM) which is a primary health care model designed for chronic (relapsing) conditions and involves six elements: linkage to community resources, redesign of health care organization, self-management support, delivery system redesign (e.g., use of non-physician personnel), decision support, and the use of clinical information systems [ 18 , 19 ].

As numerous articles have already assessed the treatment model SBIRT, this model of care will be excluded from our review unless the particular model adds a specific new aspect. Also, the article has to assess the effectiveness of the model rather than assessing the effectiveness of the particular treatment used. Because identification of patients is vital to including them in the trial, a care model that only evaluates either patient identification or treatment without including both will be excluded from this review.

Model effectiveness may be in comparison with the usual care or a different treatment model.

Included studies need to include at least one of the following outcome measures: alcohol consumption, treatment engagement, uptake of pharmacological agents, and/or quality of life.

Solely quantitative research will be included in this systematic review (e.g., randomized controlled trials (RCTs) and cluster RCTs). We will only include peer-reviewed articles.

Restrictions (language/time period)

Studies published in English after 1 January 1998 will be included in this systematic review.

Studies have to be conducted in primary health care settings as such treatment facilities need to be physically in or attached to the primary care clinic. Examples are co-located clinics, veteran health primary care clinic, hospital-based primary care clinic, and community primary health clinics. Specialized primary health care clinics such as human immunodeficiency virus (HIV) clinics are excluded from this systematic review. All studies were included, irrespective of country of origin.

Search strategy and information sources

A comprehensive search will be conducted. The following databases will be consulted: MEDLINE (1946 to present), PsycINFO (1806 to present), Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials (CENTRAL) (1991 to present), and Embase (1947 to present). Initially, the search terms will be kept broad including alcohol use disorder (+synonyms), primary health care, and treatment to minimize the risk of missing any potentially relevant articles. Depending on the number of references attained by this preliminary search, we will add search terms referring to models such as models of care, integrated models, and stepped-care models, to limit the number of articles. Additionally, we will conduct reference searches of relevant reviews and articles. Similarly, a gray literature search will be done with the help of Google and the Gray Matters tool which is a checklist of health-related sites organized by topic. The tool is produced by the Canadian Agency for Drugs and Technologies in Health (CADTH) [ 20 ].

See Additional file  2 for a draft of our search strategy in MEDLINE.

Data collection

The selection of relevant articles is based on several consecutive steps. All references will be managed using EndNote (EndNote version X9 Clarivate Analytics). Initially, duplicates will be removed from the database after which all the titles will be screened with the purpose of discarding clearly irrelevant articles. The remaining records will be included in an abstract and full-text screen. All steps will be done independently by two researchers. Disagreement will lead to consultation of a third researcher.

Data extraction and synthesis

Two researchers will extract data from included records. At the conclusion of data extraction, these two researchers will meet with the lead author to resolve any discrepancies.

In order to follow a structured approach, an extraction form will be used. Key elements of the extraction form are information about design of the study (randomized, blinded, control), type of participants (alcohol use, screening tool used, socio-economic status, severity of alcohol use, age, sex, number of participants), study setting (primary health care setting, VA centers, co-located), type of intervention/model of care (separate elements of the models), type of health care worker (primary, secondary (co-located)), duration of follow-up, outcome measures used in the study, and funding sources. We do not anticipate having sufficient studies for a meta-analysis. As such, we plan to perform a narrative synthesis. We will synthesize the findings from the included articles by cohort characteristics, differential aspects of the intervention, controls, and type of outcome measures.

Sensitivity analyses will be conducted when issues suitable for sensitivity analysis are identified during the review process (e.g., major differences in quality of the included articles).

Potential meta-analysis

In the event that sufficient numbers of effect sizes can be extracted, a meta-analytic synthesis will be performed. We will extract effect sizes from each study accordingly. Two effect sizes will be extracted (and transformed where appropriate). Categorical outcomes will be given in log odds ratios and continuous measures will be converted into standardized mean differences. Variation in effect sizes attributable to real differences (heterogeneity) will be estimated using the inconsistency index ( I 2 ) [ 21 , 22 ]. We anticipate high degrees of variation among effect sizes, as a result moderation and subgroup-analyses will be employed as appropriate. In particular, moderation analysis will focus on the degree of heterogeneity attributable to differences in cohort population (pre-intervention drinking severity, age, etc.), type of model/intervention, and study quality. We anticipate that each model of care will require a sub-group analysis, in which case a separate meta-analysis will be performed for each type of model. Small study effect will be assessed with funnel plots and Egger’s symmetry tests [ 23 ]. When we cannot obtain enough effect sizes for synthesis or when the included studies are too diverse, we will aim to illustrate patterns in the data by graphical display (e.g., bubble plot) [ 24 ].

Critical appraisal of studies

All studies will be critically assessed by two researchers independently using the Revised Cochrane risk-of-bias tool (RoB 2) [ 25 ]. This tool facilitates systematic assessment of the quality of the article per outcome according to the five domains: bias due to (1) the randomization process, (2) deviations from intended interventions, (3) missing outcome data, (4) measurement of the outcome, and (5) selection of the reported results. An additional domain 1b must be used when assessing the randomization process for cluster-randomized studies.

Meta-biases such as outcome reporting bias will be evaluated by determining whether the protocol was published before recruitment of patients. Additionally, trial registries will be checked to determine whether the reported outcome measures and statistical methods are similar to the ones described in the registry. The gray literature search will be of assistance when checking for publication bias; however, completely eliminating the presence of publication bias is impossible.

Similar to article selection, any disagreement between the researchers will lead to discussion and consultation of a third researcher. The strength of the evidence will be graded according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach [ 26 ].

The primary outcome measure of this proposed systematic review is the consumption of alcohol at follow-up. Consumption of alcohol is often quantified in drinking quantity (e.g., number of drinks per week), drinking frequency (e.g., percentage of days abstinent), binge frequency (e.g., number of heavy drinking days), and drinking intensity (e.g., number of drinks per drinking day). Additionally, outcomes such as percentage/proportion included patients that are abstinent or considered heavy/risky drinkers at follow-up. We aim to report all these outcomes. The consumption of alcohol is often self-reported by patients. When studies report outcomes at multiple time points, we will consider the longest follow-up of individual studies as a primary outcome measure.

Depending on the included studies, we will also consider secondary outcome measures such as treatment engagement (e.g., number of visits or pharmacotherapy uptake), economic outcome measures, health care utilization, quality of life assessment (physical/mental), alcohol-related problems/harm, and mental health score for depression or anxiety.

This proposed systematic review will synthesize and evaluate differential models of care for the management of AUD in primary health care settings.

Given the complexities of researching models of care in primary care and the paucity of a focus on AUD treatment, there are likely to be only a few studies that sufficiently address the research question. Therefore, we will do a preliminary search without the search terms for model of care. Additionally, the search for online non-academic studies presents a challenge. However, the Gray Matters tool will be of guidance and will limit the possibility of missing useful studies. Further, due to diversity of treatment models, outcome measures, and limitations in research design, it is possible that a meta-analysis for comparative effectiveness may not be appropriate. Moreover, in the absence of large, cluster randomized controlled trials, it will be difficult to distinguish between the effectiveness of the treatment given and that of the model of care and/or implementation procedure. Nonetheless, we will synthesize the literature and provide a critical evaluation of the quality of the evidence.

This review will assist the design and implementation of models of care for the management of AUD in primary care settings. This review will thus improve the management of AUD in primary health care and potentially increase the uptake of evidence-based interventions for AUD.

Availability of data and materials

Not applicable.

Abbreviations

Alcohol use disorder

Alcohol Use Disorders Identification test

Canadian Agency for Drugs and Technologies in Health

The Comorbidity Alcohol Risk Evaluation

Cochrane Central Register of Controlled Trials

Diagnostic and Statistical Manual of Mental Disorders

Human immunodeficiency virus

10 - International Statistical Classification of Diseases and Related Health Problems

Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols

Screening, brief intervention, referral to specialized treatment

Standard drinks

World Health Organization

WHO. Global status report on alcohol and health: World health organization; 2018.

The global burden of disease attributable to alcohol and drug use in 195 countries and territories, 1990–2016. a systematic analysis for the Global Burden of Disease Study 2016. Lancet Psychiatry. 2018;5(12):987–1012.

Article   Google Scholar  

WHO. Global strategy to reduce the harmful use of alcohol: World health organization; 2010.

Rehm J, Allamani A, Elekes Z, Jakubczyk A, Manthey J, Probst C, et al. Alcohol dependence and treatment utilization in Europe - a representative cross-sectional study in primary care. BMC Fam Pract. 2015;16:90.

Morley KC, Logge W, Pearson SA, Baillie A, Haber PS. National trends in alcohol pharmacotherapy: findings from an Australian claims database. Drug Alcohol Depend. 2016;166:254–7.

Article   CAS   Google Scholar  

Morley KC, Logge W, Pearson SA, Baillie A, Haber PS. Socioeconomic and geographic disparities in access to pharmacotherapy for alcohol dependence. J Subst Abus Treat. 2017;74:23–5.

Rehm J, Anderson P, Manthey J, Shield KD, Struzzo P, Wojnar M, et al. Alcohol use disorders in primary health care: what do we know and where do we go? Alcohol Alcohol. 2016;51(4):422–7.

Le KB, Johnson JA, Seale JP, Woodall H, Clark DC, Parish DC, et al. Primary care residents lack comfort and experience with alcohol screening and brief intervention: a multi-site survey. J Gen Intern Med. 2015;30(6):790–6.

McLellan AT, Starrels JL, Tai B, Gordon AJ, Brown R, Ghitza U, et al. Can substance use disorders be managed using the chronic care model? review and recommendations from a NIDA consensus group. Public Health Rev. 2014;35(2).

Storholm ED, Ober AJ, Hunter SB, Becker KM, Iyiewuare PO, Pham C, et al. Barriers to integrating the continuum of care for opioid and alcohol use disorders in primary care: a qualitative longitudinal study. J Subst Abus Treat. 2017;83:45–54.

Mitchell AJ, Meader N, Bird V, Rizzo M. Clinical recognition and recording of alcohol disorders by clinicians in primary and secondary care: meta-analysis. Br J Psychiatry. 2012;201:93–100.

Babor TF, Ritson EB, Hodgson RJ. Alcohol-related problems in the primary health care setting: a review of early intervention strategies. Br J Addict. 1986;81(1):23–46.

Kaner EF, Beyer F, Dickinson HO, Pienaar E, Campbell F, Schlesinger C, et al. Effectiveness of brief alcohol interventions in primary care populations. Cochrane Database Syst Rev. 2007;(2):Cd004148.

O'Donnell A, Anderson P, Newbury-Birch D, Schulte B, Schmidt C, Reimer J, et al. The impact of brief alcohol interventions in primary healthcare: a systematic review of reviews. Alcohol Alcohol. 2014;49(1):66–78.

Bertholet N, Daeppen JB, Wietlisbach V, Fleming M, Burnand B. Reduction of alcohol consumption by brief alcohol intervention in primary care: systematic review and meta-analysis. Arch Intern Med. 2005;165(9):986–95.

Saitz R. ‘SBIRT’ is the answer? Probably not. Addiction. 2015;110(9):1416–7.

Shamseer L, Moher D, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. Bmj. 2015;350:g7647.

Bodenheimer T, Wagner EH, Grumbach K. Improving primary care for patients with chronic illness. Jama. 2002;288(14):1775–9.

Bodenheimer T, Wagner EH, Grumbach K. Improving primary care for patients with chronic illness: the chronic care model, part 2. Jama. 2002;288(15):1909–14.

CADTH. Grey Matters: a practical tool for searching health-related grey literature Internet. 2018 (cited 2019 Feb 22).

Higgins JPT. Thompson SG. Quantifying heterogeneity in a meta-analysis. 2002;21(11):1539–58.

Google Scholar  

Higgins JPT, Thompson SG, Deeks JJ. Altman DG. Measuring inconsistency in meta-analyses. 2003;327(7414):557–60.

Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ (Clinical research ed). 1997;315(7109):629–34.

Higgins JPT, López-López JA, Becker BJ, Davies SR, Dawson S, Grimshaw JM, et al. Synthesising quantitative evidence in systematic reviews of complex health interventions. BMJ Glob Health. 2019;4(Suppl 1):e000858–e.

Higgins, J.P.T., Sterne, J.A.C., Savović, J., Page, M.J., Hróbjartsson, A., Boutron, I., Reeves, B., Eldridge, S. (2016). A revised tool for assessing risk of bias in randomized trials. In: Chandler, J., McKenzie, J., Boutron, I., Welch, V. (editors). Cochrane methods. Cochrane database of systematic reviews, 10 (Suppl 1). https://doi.org/10.1002/14651858.CD201601 .

Schünemann H, Brożek J, Guyatt G, Oxman A, editor(s). Handbook for grading the quality of evidence and the strength of recommendations using the GRADE approach (updated October 2013). GRADE Working Group, 2013. Available from gdt.guidelinedevelopment.org/app/handbook/handbook.html ).

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KM and PH conceived the presented idea of a systematic review and meta-analysis and helped with the scope of the literature. KM is the senior researcher providing overall guidance and the guarantor of this review. SR developed the background, search strategy, and data extraction form. SR and EL will both be working on the data extraction and risk of bias assessment. SR and JC will conduct the data analysis and synthesize the results. All authors read and approved the final manuscript.

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Correspondence to Kirsten C. Morley .

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Supplementary information

Additional file 1..

PRISMA-P 2015 Checklist.

Additional file 2.

Draft search strategy MEDLINE. Search strategy.

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Rombouts, S.A., Conigrave, J., Louie, E. et al. Evidence-based models of care for the treatment of alcohol use disorder in primary health care settings: protocol for systematic review. Syst Rev 8 , 275 (2019). https://doi.org/10.1186/s13643-019-1157-7

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• Published: 08 November 2021

Acute effects of alcohol on social and personal decision making

• Hanna Karlsson 1   na1 ,
• Emil Persson   ORCID: orcid.org/0000-0003-2994-0541 2   na1 ,
• Irene Perini   ORCID: orcid.org/0000-0002-5972-0913 1 ,
• Adam Yngve   ORCID: orcid.org/0000-0003-1012-7286 1 ,
• Markus Heilig 1   na1 &
• Gustav Tinghög   ORCID: orcid.org/0000-0002-8159-1249 2 , 3   na1  

Neuropsychopharmacology volume  47 ,  pages 824–831 ( 2022 ) Cite this article

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Social drinking is common, but it is unclear how moderate levels of alcohol influence decision making. Most prior studies have focused on adverse long-term effects on cognitive and executive function in people with alcohol use disorders (AUD). Some studies have investigated the acute effects of alcohol on decision making in healthy people, but have predominantly used small samples and focused on a narrow selection of tasks related to personal decision making, e.g., delay or probability discounting. Here, we conducted a large ( n  = 264), preregistered randomized placebo-controlled study (RCT) using a parallel group design, to systematically assess the acute effects of alcohol on measures of decision making in both personal and social domains. We found a robust effect of a 0.6 g/kg dose of alcohol on both moral judgment and altruistic behavior, but no effects on several measures of risk taking or waiting impulsivity. These findings suggest that alcohol at low to moderate doses selectively moderates decision making in the social domain, and promotes utilitarian decisions over those dictated by rule-based ethical principles (deontological). This is consistent with existing theory that emphasizes the dual roles of shortsighted information processing and salient social cues in shaping decisions made under the influence of alcohol. A better understanding of these effects is important to understand altered social functioning during alcohol intoxication.

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Introduction.

There is a lack of systematic research on the effects of moderate alcohol intake on decision making in non-clinical populations. This may be related to the difficulties that go into designing these types of studies, and the fact that prior research has been primarily focused on the adverse consequences of alcohol use disorders (AUD) on physiology and behavior. Numerous studies have investigated impairments in interpersonal behavior and decision-making processes in patients with AUD, but these studies cannot disaggregate the direct effects of alcohol from functional consequences of alcohol-induced organ damage, such as e.g., well documented alcohol-induced regional gray matter loss in AUD [ 1 ].

In healthy volunteers, alcohol intake can influence incentive motivation through activation of canonical dopaminergic brain reward system, but these effects vary by gender and genetics [ 2 , 3 , 4 , 5 ]. Enhanced emotional reactivity and increased positive mood have also been linked to alcohol intake in non-threatening environments [ 6 , 7 ]. It is furthermore widely held that alcohol results in broad and non-selective impairments of cognitive function, but this notion has recently been questioned. A meta-analysis of studies that examined the effects of alcohol on event-related potentials suggests that alcohol intake results in relatively selective impairments of attention, automatic auditory processing, and performance monitoring [ 8 ]. Similarly, alcohol is commonly held to increase impulsivity, but available studies make it difficult to disentangle to what extent impulsivity is a cause vs. a consequence of alcohol use, and also point to the moderating influence of emotional states [ 9 ].

Few studies have examined acute effects of alcohol on motivated behavior and decision making under a level of experimental control that allows causal inferences. For instance, many of the existing studies have used survey data to compare the behavior of people who abuse alcohol to those who do not. Although there are also placebo-controlled laboratory studies, most of these have used small samples and focused on a narrow selection of tasks related to personal decision making, primarily risk taking and impulsivity [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ]. Even for these tasks, there is a lack of converging evidence. Some studies found increased risk taking due to alcohol [ 11 , 13 ], while others found no effect [ 10 , 12 , 14 , 15 , 19 , 20 ]. Similarly, waiting impulsivity has been found to increase [ 19 ] or decrease [ 16 ] following alcohol intake, but the majority of studies have found mixed or no effects [ 10 , 11 , 14 , 15 , 17 ]. Prototypical tasks for altruism and moral judgment have only been included in a minority of studies, with mixed results for both types of tasks [ 19 , 20 , 21 , 22 ]. In addition, some studies have used an observational field paradigm, typically approaching people in a bar with a structured questionnaire [ 22 , 23 , 24 ]. Whereas important insights can be obtained from these observational studies, they cannot provide answers about the causal relationship between alcohol intake and behavior, as they are inherently correlational, and also prone to selection bias.

Here, we therefore investigated how moderate acute alcohol intoxication influences basic social and personal decision making central to a wide variety of everyday behaviors: altruistic behavior and distributional preference, moral judgment, waiting impulsivity, and choice under risk. To this end, we conducted a preregistered (see https://osf.io/sf5em ) randomized placebo-controlled study, using a general task paradigm and a substantially larger sample ( n  = 264) than previous studies. We randomized participants to alcohol (0.6 and 0.51 g/kg for males and females, resp.) or placebo, and assessed moral judgment using standard sacrificial dilemmas (trolley problems) thought to probe the interaction between emotional intuitions and controlled cognitive processes in moral cognition [ 25 , 26 , 27 , 28 ]. Prosocial behavior was assessed using modified versions of the dictator game [ 29 , 30 ]. For risk taking, we used two different tasks, covering both intuitive-cognitive aspects of decision making, via standard prospect theory gambles [ 31 ], and more affect-laden decisions from experience, using the Balloon Analog Risk Task (BART; [ 32 ]). Finally, waiting impulsivity was assessed using a prototypical task that captures participants’ preferences for real monetary rewards delivered at different points in time [ 33 , 34 ]. We assessed both general discounting (over relatively short delays) and temporal inconsistency in discounting, known as present bias, which is a characteristic property of discounting models that feature a sharp rise in the discounting rate for rewards delivered closer to today, such as quasi-hyperbolic discounting [ 34 , 35 ].

Materials and methods

Ethics statement.

The study was approved by the Regional Ethical Review Board of Linköping (ref 2016/496-31) and all participants provided written informed consent.

Open science

The preregistration together with data, analysis codes (main analyses), and experimental materials are available via the project’s OSF repository ( https://osf.io/sf5em ). Individual level data for the main analyses are shown in Supplementary materials Fig. S 1 –S 4 . We preregistered six main questions of interest for this data collection; this paper is focused on the first four of them.

Participants

Healthy volunteers were recruited using advertisements in social media, flyers, and the Online Recruitment System for Economic Experiments ORSEE [ 36 ] at Linköping University, Sweden. Eligible participants were randomized to alcohol ( n  = 128) or placebo ( n  = 136). The groups were similar in terms of baseline characteristics, including age, sex, education, alcohol consumption as measured with AUDIT, and personality traits measured with NEO-FFI (Table  1 ). The distribution of AUDIT scores was also very similar in both groups, and shown in Supplementary Materials (Fig. S 1 ). Our final sample size is smaller than the pre-specified target of n = 300 because we had to stop enrolling participants due to the onset of the COVID-19 pandemic.

Study timeline

The study visit consisted of five phases (Fig.  1B ): screening, questionnaires for baseline assessments, treatment phase (intake of drink), decision-making tasks performed at a computer, and a finishing phase with end of session questionnaires. The study was conducted in a computer lab in sessions of up to 15 participants, who were seated in separate cubicles and did not interact with each other.

A CONSORT diagram of study participant. B study timeline. C time course of BrAC (mean ± SD).

Screening and eligibility

During the screening phase, prospective participants were evaluated for eligibility by a research nurse or a physician. Detailed eligibility criteria are provided in Supplementary Materials. In brief, subjects were excluded if they had any psychiatric disorder, were pregnant, had any previous neurological condition or if they were at risk of alcohol or other substance use disorders except nicotine. Alcohol Use Disorder Identification Test [AUDIT; [ 37 ]] was used to assess the presence of AUD or hazardous drinking. Weight and sex were noted. Breath alcohol concentration (BrAC) baseline was measured using a breathalizer. A total of 316 individuals were evaluated, and 265 were included. Of these, 129 were allocated to placebo and 136 were assigned to alcohol (Fig.  1A ).

Baseline assessments

Baseline personality traits were obtained using the NEO Five Factor Inventory [NEO-FFI; [ 38 ]]. The Symptom checklist-90 [SCL-90; [ 39 ]] was used to measure symptoms of anxiety and depression. The Family Tree Questionnaire [FTQ; [ 40 ]] was used to assess family history of alcohol problems. The Biphasic Alcohol Effect Scale [BAES; [ 41 ]] was used to measure stimulant and sedative effects of alcohol.

Alcohol administration

Participants were informed that they would receive alcohol, corresponding to a BrAC of 0.6‰ or placebo, and were randomized to one of these in a parallel group design (see Fig.  1A ). In the alcohol group, male participants received a 0.6 g/kg dose of alcohol using a 12% solution. The solution was made using 95% ethanol mixed with cranberry juice. To adjust for known differences in body water, women received 85% of the alcohol administered to men. In the placebo group participants received a 1% alcohol solution. In both groups, the drink was divided into three glasses. Participants in both the alcohol and placebo group were required to finish each glass within five minutes. After the last glass, participants had a break for 15 min before proceeding with the decision-making tasks. Breath alcohol concentration (BrAC) was measured at baseline, 25 min later, just before the decision-making tasks and after additional appr. 45 min, as soon as the participant finished the session. The Biphasic Alcohol Effect Scale [BAES; [ 41 ]] was performed every time BrAC was measured and the Drug Effect Questionnaire [DEQ; [ 42 ]] was measured the second and third time BrAC was measured.

Decision-making tasks

For detailed task description and instructions, see Supplementary Materials. In brief, tasks focused on four domains of decision making: waiting impulsivity, choice under risk, moral judgment, and prosocial behavior. Tasks were presented on a computer screen using Qualtrics and Inquisit software. Divider screens prevented participants from seeing each other’s responses. Tasks were presented in a block-randomized order. At the end of the experiment, one decision for each subject was randomly selected and paid out for real (using the cell phone payment system Swish) together with the show-up fee of 150 SEK (appr. $15) that participants received for participating in the study.

Waiting impulsivity

This was assessed using a prototypical task that measures participants’ preferences for rewards delivered at different points in time [ 33 , 34 ]. Participants chose repeatedly between smaller rewards delivered sooner (SS) and larger rewards delivered later (LL). We tested for two distinct types of discounting; a general form of impatience, based on the proportion of smaller-sooner choices each person made in the first block of items ( pr. smaller-sooner ), and a specific form of impatience known as present bias, which is based on the difference (for each participant) between choices made in the first and second blocks of items ( diff. pr. smaller-sooner ). Present bias is a characteristic property of discounting models that feature a sharp rise in the discounting rate for rewards delivered closer to today, such as quasi-hyperbolic discounting [ 34 , 35 ].

Risk taking

One of the tasks to examine risk taking used standard prospect-theory gambles [ 31 ]. We used incentivized binary choices between a lottery and a certain amount of money in three different domains: gain, loss, mixed. We used the proportion of choices where the gamble was our main dependent variable for each domain ( pr. risky choices ). Using this task enabled us to characterize choices after the expected patterns of prospect theory [ 31 ], which emphasizes greater risk aversion for gains than losses and disproportionate weighting of the loss component in mixed prospects.

The second task in this domain was the Balloon Analog Risk Task [BART; [ 32 ]], in which participants were presented with a picture of a balloon and could earn money by pumping up the balloon by clicking a button. Each click earned them 0.1 SEK and caused the balloon to incrementally inflate. If the balloon was overinflated, it exploded, and all money earned for that trial was lost. If instead participants had chosen to cash-out prior to the balloon exploding, the money earned for that trial was added to their sum for this task. Our main dependent variable was the average number of pumps per trial, excluding trials where the balloon exploded ( avg. pumps per balloon ).

Moral judgment

This was assessed using four sacrificial moral dilemmas (trolley problems) that involved a conflict between utilitarian and deontological moral foundations [ 25 , 43 , 44 ]. In each dilemma, participants were faced with the possibility of saving a certain number of people by sacrificing one individual. Killing the single person while saving the others is consistent with utilitarian judgment, while not pulling the switch is consistent with deontological judgment, whereby actively causing harm to another person is morally unacceptable regardless of overall consequences. The main dependent variable for moral judgment was based on participants’ responses to four moral dilemmas (switch, footbridge, fumes, and shark; see Supplementary materials for details), presented in random order, and calculated as the proportion of utilitarian choices made by each participant ( pr. utilitarian choices ).

Prosocial behavior

This was assessed using two different tasks, designed to measure both altruistic behavior and preference for equality versus efficiency in distributions. Both were modified versions of the dictator game [ 29 , 30 ].

In the first task, participants were endowed with 50 SEK (appr. $5) and decided how much of it to keep for themselves and how much to donate to a well-known charity organization (Swedish Heart-Lung Foundation). The main dependent variable was the amount donated ( donation to charity ).

In the second task, subjects chose repeatedly between binary allocations of money (for themselves and another anonymous participant). Each item featured a choice between an equal distribution and an unequal but more efficient distribution, for example 40 SEK (appr. $4) each vs 40 SEK for me and 50 SEK for the other participant. We used the proportion (for each person) of choices where the equal allocation was chosen over the more efficient allocation ( pr. equality ).

Statistical analysis

The main analysis plan was specified before data collection begun, see the preregistration for details. STATISTICA 13.0 (Dell Inc, Tulsa, OK) was used for all analyses. One-way ANOVA, with group (alcohol or placebo) as a between-subject factor, and a pre-set alpha=0.05, were the preregistered main tests. Subject-level data for main tests are provided in Supplementary Materials, Fig. S 1 –S 4 . Secondary analyses (not preregistered) additionally assessed the potential influence of baseline subject characteristics (age, sex, personality measures, and alcohol use as measured by the AUDIT). Covariates were retained in analysis models if they were a significant predictor, or if they reduced the residual variance by more than 10%; otherwise, they were excluded. In additional analyses (also not preregistered) we compared self-reported effects of alcohol (stimulant, sedative, strength of drug effect, desirability) across the two conditions, based on subjects’ responses to the Biphasic Alcohol Effect Scale (BAES) and the Drug Effect Questionnaire (DEQ).

No BrAC alcohol was detected in the placebo group at any timepoint, or in the alcohol group at baseline. In the alcohol group, a BrAC of appr. 0.5‰ was reached by the time behavioral testing started, and remained stable at that level until completion of testing (Fig.  1C ). Using the Biphasic Alcohol Effects Scale [ 41 ], the alcohol group showed the expected stimulant as well as sedative effects of alcohol compared to the placebo group. On the Drug Effects Questionnaire [ 42 ], there was a clear effect of alcohol on the “Feel drug” and “High” items (Fig.  2 ). Neither “Like” nor “Want more” items were affected. The proportion of participants who correctly guessed their allocation was 95.5% in the alcohol group, and 69% in the placebo group. No unexpected adverse events were noted.

A – D Mean responses on the Drug Effect Questionnaire (DEQ) before and after the decision-making tasks. Error bars indicate 95% Confidence Intervals. E , F Mean responses to the Biphasic Alcohol Effects Scale (BAES). Error bars indicate 95% Confidence Intervals. Significant alcohol effects for all items are indicated in the Results section.

Moral judgment in sacrificial dilemmas

Preference for utilitarian responding was increased in the alcohol group (one way ANOVA: F 1, 262  = 5.71, p  = 0.02; Cohen’s d = 0.29; Fig.  3A ). This remained unchanged when controlling for potential confounds. In the final ANCOVA, agreeableness ( p  < 0.01), gender ( p  = 0.06) and hazardous alcohol use, as measured with the AUDIT ([ 37 ]; p  = 0.02) contributed to the model, and all correlated negatively with utilitarian choices. Exploratory analyses indicated that the effect of alcohol on moral judgment was driven by the switch and fumes dilemmas, and to some extent the shark dilemma, while no corresponding effect was seen in the footbridge dilemma.

A Moral judgment. Main panel: overall proportion of utilitarian choices. Inset: proportion of participants in each group who chose the utilitarian option, for the respective scenario. B Donation to charity. Main panel: Total amount of money donated. Inset: distribution of amounts donated to the charity, by group. Ten Swedish kronor (SEK) was approximately equal to one USD at the time of the experiment. Tick marks on the x-axis show the midpoints of equally-sized bins (10 SEK wide), except at the endpoints, where bin size is smaller. Error bars indicate 95% Confidence Intervals. Sample size is n  = 128 for placebo and n  = 136 for alcohol.

Participants in the alcohol group donated more money to a charity ( F 1, 262  = 4.83, p  = 0.03; Cohen’s d = 0.27; Fig.  3B ). This remained unchanged when controlling for potential confound of baseline subject characteristics. In the final model, agreeableness ( p  < 0.01) and hazardous alcohol use as measured with the AUDIT ( p  = 0.02) significantly contributed to the model. Agreeableness was positively correlated with donations and AUDIT was negatively correlated.

Equality/efficiency tradeoffs did not differ between groups (0.27 ± 0.38 vs. 0.27 ± 0.39; F 1, 262  < 0.01, p  = 0.98); thus, participants in both groups were reluctant to pursue equality of resources if redistribution had a cost. This result remained unchanged when controlling for potential confounds. In the final model, age ( p  < 0.01), neuroticism ( p  < 0.01), extraversion ( p  < 0.01), openness ( p  = 0.02), conscientiousness ( p  = 0.01) and gender ( p  < 0.01) significantly contributed to the model. Openness correlated negatively with equality. Female gender, age, neuroticism, extraversion and conscientiousness correlated positively with equality.

Risk taking – prospect theory gambles & BART

Behavior in the prospect gambles was similar in the two groups (Fig.  4 ). There was a tendency for decreased risk taking in the alcohol group for gains (0.59 ± 0.29 vs. 0.65 ± 0.22; F 1, 262  = 3.58, p  = 0.06), but no effect, or trend in the loss (0.49 ± 0.22 vs. 0.45 ± 0.22; F 1, 262  = 1.72, p  = 0.19), or in the mixed domain (0.49 ± 0.21 vs. 0.47 ± 0.22; F 1, 262  = 0.64, p  = 0.42). When all three domains were combined, the alcohol and placebo groups were virtually indistinguishable (0.52 ± 0.18 vs. 0.52 ± 0.15; F 1,262  < 0.01, p  = 0.96; Cohen’s d = −0.01). This remained unchanged when controlling for potential confounds. In the final model, age ( p  < 0.01), extraversion ( p  = 0.01), conscientiousness ( p  = 0.03) and agreeableness ( p  = 0.06) significantly contributed to the model or showed a tendency to do so. Age and extraversion were positively correlated with risk taking, while agreeableness and conscientiousness were negatively correlated with risk taking.

A Mean proportion of trials where individuals chose the gamble over the certain option, separated by domain (gain, loss, mixed). Error bars indicate 95% Confidence Intervals calculated from t tests. B Distribution of the average number of pumps per balloon on the Balloon Analog Risk Task (BART). Sample size is n  = 128 for placebo and n  = 136 for alcohol, except for BART where two individuals in placebo and three in alcohol could not participate in the task due to software issues.

Similarly, there was no difference in risk taking on the Balloon Analog Risk Task (BART) between alcohol and placebo (Fig.  4 ; 43.4 ± 14.1 vs. 43.5 ± 14.2; F 1,257  < 0.01, p  = 0.99; Cohen’s d = −0.002). This remained unchanged when controlling for potential confounds. In the final model, neuroticism ( p  = 0.01) and conscientiousness ( p  = 0.05) were significant covariates. Both were negatively correlated with adjusted average number of pumps.

There was no statistically significant difference between groups for waiting impulsivity (0.24 ± 0.31 vs. 0.29 ± 0.31; F 1,262  = 2.21, p  = 0.14), or present bias (0.0007 ± 0.15 vs. 0.03 ± 0.18; F 1,262  = 2.59, p  = 0.11). Results were similar when all individual decisions were combined (0.24 ± 0.30 vs. 0.28 ± 0.29; F 1,262  = 1.25, p  = 0.26; Cohen’s d = −0.14). Thus, any possible effect of alcohol on waiting impulsivity was small and insignificant, and the bound on the 95% confidence interval in the hypothesized direction, i.e., increased waiting impulsivity following alcohol intake, was close to zero. These results remained unchanged when controlling for potential confounds.

We conducted a large, preregistered RCT to assess acute effects of alcohol on measures of decision making in personal and social domains. A 0.6 g/kg dose of alcohol did not influence personal decisions, but robustly moderated social decision making. In particular, subjects in the alcohol group showed an increased utilitarian preference in sacrificial moral dilemmas, and donated more money to charity in a modified dictator-game task. As an internal validation of these findings, we detected the expected effects of personality traits, independently of the alcohol effects. Although participants’ level of alcohol use, as measured by the AUDIT scale, correlated negatively both with their utilitarian decisions and charitable donations, the effects of alcohol on these outcomes did not interact with the level of alcohol use, and thus did not differ across the spectrum of use included in the study. For personal decision making, we did not find an effect of alcohol at the dose given on any of several risk-taking measures or waiting impulsivity. As an internal validation, we reliably replicated known patterns of results with all our tasks, e.g., increased risk seeking for losses and selective sensitivity to harmful actions across different moral dilemmas. Thus, our null findings are unlikely a result of compromised task calibration or unusual sample composition. Our findings are also unlikely to be explained by effects on elements of decision making that are related to impulse control, since, at the moderate level of alcohol intoxication used, we found no effects in tasks specifically designed to capture this dimension of behavior.

Our results for moral judgment, that subjects became increasingly utilitarian, differ from the few previous studies. Francis and colleagues [ 21 ] recently conducted a placebo-controlled study on moral judgment, using both traditional moral dilemmas and an adapted virtual-reality moral behavior task. They found no effects of alcohol on any of these tasks. In contrast, Duke and Bègue [ 22 ] found that alcohol intake correlated with increased utilitarian responding, but only on the footbridge dilemma and not on the switch dilemma, in a study conducted at two bars in France. However, the results from these two studies should be interpreted with caution, given the small sample sizes and the correlational nature of the data in the latter study. Our findings are contrary to what would be expected based on the widely held dual-process theory of moral cognition [ 25 , 28 ]. According to this theory, the effects of alcohol to increase emotional reactivity and weaken cognitive control should give increased preference for deontological rather than utilitarian actions. In fact, we find the opposite, i.e. increased utilitarian responding due to alcohol. A possible account of this finding is that acute alcohol intoxication primarily affects moral judgment through effects on its cognitive elements, and does so by subtly shifting the balance between perceived costs and benefits in the utilitarian calculation. This is broadly consistent with findings indicating an important role of frontocortical brain areas in social decision making [ 45 ], and a higher sensitivity of these neocortical structures to alcohol effects compared to subcortical brain structures that generate incentive salience and affective signals [ 1 ].

Acute effects of alcohol on altruistic behavior using real monetary rewards have hardly been assessed at all previously. Two previous studies found no effect or a tendency for a negative effect on altruism following alcohol intake [ 19 , 20 ]. In contrast, we found that alcohol made people more altruistic, donating a larger proportion of their money (around ten percentage points more than the placebo group) to charity. This is a modest effect size, but appears to be highly specific, as it was found at a modest dose of alcohol at which there were no discernible effects on impulsivity or risk taking. We had no a priori expectation about the direction of the effect on altruism. In principle, these results can also be rationalized using alcohol myopia theory [ 46 , 47 , 48 ], which emphasizes impaired attention and thus increased reliance on salient stimuli following acute alcohol intoxication. The need of the charity recipients is arguably a salient cue in the task that we used, and it is possible that this is what caused increased donations in the alcohol group.

Previous studies on personal decision making for risk and impulsivity have found mixed results [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 49 ], but most studies have been limited by a small sample size. Prior to our study, Bernhardt et al. [ 10 ] was probably the most well-powered study to date ( n  = 54 adolescent males in a within-subject design), and their results are similar to what we found, with no effects on waiting impulsivity or on risk taking in gain, loss, or mixed domains. Taken together, this strongly suggests that alcohol taken at moderated doses by healthy social drinkers has small or no effects on risk taking or waiting impulsivity. For the Balloon Analog Risk Task (BART), we are aware of only one previous study that was adequately powered, Rose et al. [ 50 ] with n  = 142 in a between-subjects design; e.g., all other studies reviewed by Harmon et al. [ 51 ] had <33 subjects per treatment cell. Interestingly, whereas Rose et al. found increased risk taking (more pumps) due to alcohol intake (Cohen’s d = 0.40 at a 0.6 g/kg dose of alcohol), our results clearly favored a no-effects interpretation, with the 95% confidence interval bounded at an effect size or appr. Cohen’s d = 0.25 in either direction. Thus, more studies are needed to determine the acute effects alcohol on the BART. Of note, while the BART is commonly viewed as a generic “risk taking task”, its original evaluation suggested that it may in fact be more related to sensation seeking and impaired behavioral inhibition [ 32 ], i.e. facets of the impulsivity distinct from those involved in trading off the magnitude of gains or losses vs. their probability.

Our study has several strengths as well as limitations. Among the former, it had a large sample size and a preregistered analysis plan. This is important given that prior studies are for the most part small and without transparent control of analytical flexibility. The combination of small sample sizes, high analytical flexibility and publication bias has been a perfect storm for generating irreproducible findings [ 52 , 53 , 54 , 55 ]. However, despite a larger sample than previous studies, we had insufficient power to conduct otherwise relevant subgroup analyses, for example based on gender or quantitative traits, beyond using them as covariates in the analysis. For the same reason, we did not attempt to capture biphasic effects of alcohol. Finally, we were not able to control for expectation effects by adding more conditions, while blinding was not successful. These limitations may affect the generalizability of our findings.

Some features of the study are both strengths and limitations. For instance, we ensured a high degree of experimental control, at the expense of assessing the effects of alcohol in a standardized, sterile laboratory environment. As expected under these conditions, while self-ratings of intoxication (“feeling effect” and “high”) were robustly influenced by alcohol, neither “liking” nor “wanting” ratings were affected. On one hand, this suggests that our findings are unlikely to be primarily driven by expectations, since expectations of alcohol effects are linked to experiencing alcohol in a naturalistic context. At the same time, alcohol effects on decision making under laboratory conditions may differ from those “in the wild”. Similarly, although we make a distinction between personal and social decision making in terms of outcomes, all decisions in our study were taken in private in front of a computer. Thus, future studies could extend our findings by investigating the effects of alcohol on social decisions made in a public setting (e.g., observed by an audience), where social signaling and reputational concerns also come into play.

Designing the experiment, we emphasized task comprehension, and all decisions that involved money were incentivized (participants were paid for one randomly drawn decision at the end). Payments were implemented via a standard cell phone transfer system in order to circumvent concerns about differential transactions costs in the waiting-impulsivity task [ 56 ]. However, as a potential side effect, this made the larger-later option in this task more attractive than we had anticipated, resulting in a more than usual amount of upper censoring (people who chose the larger-later option for all trials) for this task. Our results for waiting impulsivity should be interpreted with this limitation in mind. Similarly, our finding that alcohol did not influence impulsivity, may not generalize to higher doses, or other populations. Also, even at the dose used, effects on impulsivity might be present in people with substance use disorders, externalizing psychopathology, or both.

The pattern of our results suggests that alcohol selectively moderates decision making in the social domain, at least for low-moderate doses of alcohol. This is consistent with existing theory that emphasizes the dual roles of shortsighted information processing and salient social cues in shaping decisions under the influence of alcohol [ 46 ]. Our findings are obtained in social drinkers without any AUD, but have potentially important implications for attempts to understand the emergence of AUD. Most prior alcohol challenge studies have focused exclusively on personal decision making, but changes in social cognition, ultimately resulting in social marginalization and exclusion, are at the core of the addictive process [ 57 , 58 ]. It has recently been shown that communicating deontologically rather than utilitarian-motivated decisions may be more advantageous to signal trustworthiness as group member [ 59 , 60 ]. Impairments in the ability to signal trustworthiness caused by alcohol use could contribute to social marginalization. These alcohol-induced effects on social cognition are likely to interact with pre-existing vulnerabilities to influence social functioning. Our findings highlight the importance of taking the social dimension of decision making into account to better understand the process of developing AUD.

Taking a broader perspective, to policymakers and everyday decision-makers alike, it is useful to know that the influence of alcohol on decision making is sensitive to social cues. Whether alcohol is ultimately good or bad for people’s decisions will likely depend on context. Perhaps surprisingly, from the narrow perspective of our sample and the specific tasks that we used, social outcomes were more advantageous among people who were given alcohol compared to people who were not.

Xiao P, Dai Z, Zhong J, Zhu Y, Shi H, Pan P. Regional gray matter deficits in alcohol dependence: a meta-analysis of voxel-based morphometry studies. Drug Alcohol Depend. 2015;153:22–28.

Article   PubMed   Google Scholar  

Boileau I, Assaad JM, Pihl RO, Benkelfat C, Leyton M, Diksic M, et al. Alcohol promotes dopamine release in the human nucleus accumbens. Synapse. 2003;49:226–31.

Article   CAS   PubMed   Google Scholar  

Gilman JM, Ramchandani VA, Davis MB, Bjork JM, Hommer DW. Why we like to drink: a functional magnetic resonance imaging study of the rewarding and anxiolytic effects of alcohol. J Neurosci 2008;28:4583–91.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Urban NB, Kegeles LS, Slifstein M, Xu X, Martinez D, Sakr E, et al. Sex differences in striatal dopamine release in young adults after oral alcohol challenge: a positron emission tomography imaging study with [(11)C]raclopride. Biol Psychiatry. 2010;68:689–96.

Ramchandani VA, Umhau J, Pavon FJ, Ruiz-Velasco V, Margas W, Sun H, et al. A genetic determinant of the striatal dopamine response to alcohol in men. Mol Psychiatry. 2011;16:809–17.

Fairbairn CE, Sayette MA. The effect of alcohol on emotional inertia: a test of alcohol myopia. J Abnorm Psychol 2013;122:770–81.

Article   PubMed   PubMed Central   Google Scholar  

Sayette MA, Creswell KG, Dimoff JD, Fairbairn CE, Cohn JF, Heckman BW, et al. Alcohol and Group Formation: A Multimodal Investigation of the Effects of Alcohol on Emotion and Social Bonding. Psychol Sci 2012;23:869–78.

CE Fairbairn, D Kang, KD Federmeier, Alcohol and neural dynamics: a meta-analysis of acute alcohol effects on event-related brain potentials. Biol Psychiatry https://doi.org/10.1016/j.biopsych.2020.11.024 (2020).

Herman AM, Duka T. Facets of impulsivity and alcohol use: what role do emotions play? Neurosci Biobehav Rev 2019;106:202–16.

Bernhardt N, Obst E, Nebe S, Pooseh S, Wurst FM, Weinmann W, et al. Acute alcohol effects on impulsive choice in adolescents. J Psychopharmacol. 2019;33:316–25.

Bidwell LC, MacKillop J, Murphy JG, Grenga A, Swift RM, McGeary JE. Biphasic effects of alcohol on delay and probability discounting. Exp Clin Psychopharmacol. 2013;21:214–21.

Balodis IM, MacDonald TK, Olmstead MC. Instructional cues modify performance on the Iowa Gambling Task. Brain Cogn. 2006;60:109–17.

Lane SD, Cherek DR, Pietras CJ, Tcheremissine OV. Alcohol effects on human risk taking. Psychopharmacol. 2004;172:68–77.

Article   CAS   Google Scholar  

Richards JB, Zhang L, Mitchell SH, de Wit H. Delay or probability discounting in a model of impulsive behavior: effect of alcohol. J Exp Anal Behav. 1999;71:121–43.

Reynolds B, Richards JB, de Wit H. Acute-alcohol effects on the Experiential Discounting Task (EDT) and a question-based measure of delay discounting. Pharmacol Biochem Behav 2006;83:194–202.

Ortner CN, MacDonald TK, Olmstead MC. Alcohol intoxication reduces impulsivity in the delay-discounting paradigm. Alcohol Alcohol. 2003;38:151–6.

Adams S, Attwood AS, Munafò MR. Drinking status but not acute alcohol consumption influences delay discounting. Hum Psychopharmacol. 2017;32:e2617.

Article   PubMed Central   Google Scholar  

George S, Rogers RD, Duka T. The acute effect of alcohol on decision making in social drinkers. Psychopharmacol. 2005;182:160–9.

Corazzini L, Filippin A, Vanin P. Economic behavior under the influence of alcohol: an experiment on time preferences, risk-taking, and altruism. PLoS ONE. 2015;10:e0121530.

Bregu K, Deck C, Ham L, Jahedi S. The effects of alcohol use on economic decision making. South Economic J. 2017;83:886–902.

Article   Google Scholar  

Francis KB, Gummerum M, Ganis G, Howard IS, Terbeck S. Alcohol, empathy, and morality: acute effects of alcohol consumption on affective empathy and moral decision-making. Psychopharmacol. 2019;236:3477–96.

Duke AA, Bègue L. The drunk utilitarian: blood alcohol concentration predicts utilitarian responses in moral dilemmas. Cognition. 2015;134:121–7.

Burghart DR, Glimcher PW, Lazzaro SC. An expected utility maximizer walks into a bar…. J risk Uncertain. 2013;46:215–46.

Proestakis A, Espín AM, Exadaktylos F, Cortés Aguilar A, Oyediran OA, Palacio LA. The separate effects of self-estimated and actual alcohol intoxication on risk taking: a field experiment. J Neurosci Psychol Econ. 2013;6:115–35.

Greene JD, Nystrom LE, Engell AD, Darley JM, Cohen JD. The neural bases of cognitive conflict and control in moral judgment. Neuron. 2004;44:389–400.

Tinghög G, Andersson D, Bonn C, Johannesson M, Kirchler M, Koppel L, et al. Intuition and moral decision-making – the effect of time pressure and cognitive load on moral judgment and altruistic behavior. PLoS ONE. 2016;11:e0164012.

Persson E, Heilig M, Tinghög G, Capusan AJ. Using quantitative trait in adults with ADHD to test predictions of dual-process theory. Sci Rep. 2020;10:20076.

JD Greene, L Young, “The cognitive neuroscience of moral judgment and decision-making” in The Cognitive Neurosciences, D Poeppel, GR Mangun, MS Gazzaniga, Eds. (MIT Press, 2020).

Forsythe R, Horowitz JL, Savin NE, Sefton M. Fairness in simple bargaining experiments. Games Economic Behav. 1994;6:347–69.

Kahneman D, Knetsch JL, Thaler R. Fairness as a constraint on profit seeking: entitlements in the market. Am Economic Rev. 1986;76:728–41.

Google Scholar  

Kahneman D, Tversky A. Prospect theory: an analysis of decision under risk. Econometrica. 1979;47:263–91.

Lejuez CW, Read JP, Kahler CW, Richards JB, Ramsey SE, Stuart GL, et al. Evaluation of a behavioral measure of risk taking: the Balloon Analogue Risk Task (BART). J Exp Psychol Appl. 2002;8:75–84.

Hariri AR, Brown SM, Williamson DE, Flory JD, de Wit H, Manuck SB. Preference for immediate over delayed rewards is associated with magnitude of ventral striatal activity. J Neurosci. 2006;26:13213–7.

McClure SM, Laibson DI, Loewenstein G, Cohen JD. Separate neural systems value immediate and delayed monetary rewards. Science. 2004;306:503–7.

Laibson D. Golden eggs and hyperbolic discounting. Q J Econ. 1997;112:443–78.

Greiner B. Subject pool recruitment procedures: organizing experiments with ORSEE. J Economic Sci Assoc. 2015;1:114–25.

Saunders JB, Aasland OG, Babor TF, de la Fuente JR, Grant M. Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO Collaborative Project on Early Detection of Persons with Harmful Alcohol Consumption-II. Addiction. 1993;88:791–804.

PT Costa, RR McCrae, Revised NEO personality inventory (NEO PI-R) and NEP five-factor inventory (NEO-FFI): professional manual (Psychological Assessment Resources, Odessa, Fla. (P.O. Box 998, Odessa 33556), 1992), pp. vi, 101 p.

L Derogatis, SCL-90-R: Manual-II (Clinical Psychmetric Research, Towson, MD, 1983).

Mann RE, Sobell LC, Sobell MB, Pavan D. Reliability of a family tree questionnaire for assessing family history of alcohol problems. Drug Alcohol Depend. 1985;15:61–67.

Martin CS, Earleywine M, Musty RE, Perrine MW, Swift RM. Development and validation of the Biphasic Alcohol Effects Scale. Alcohol Clin Exp Res. 1993;17:140–6.

Morean ME, de Wit H, King AC, Sofuoglu M, Rueger SY, O'Malley SS. The drug effects questionnaire: psychometric support across three drug types. Psychopharmacol. 2013;227:177–92.

Thomson JJ. The trolley problem. Yale Law J. 1985;94:1395–415.

P Foot, Virtues and Vices and Other Essays in Moral Philosophy (Clarendon, Oxford. First published in 1978 by Blackwell publisher and University of California press, 2002).

Knoch D, Pascual-Leone A, Meyer K, Treyer V, Fehr E. Diminishing reciprocal fairness by disrupting the right prefrontal cortex. Science. 2006;314:829–32.

Steele CM, Josephs RA. Alcohol myopia. Its prized and dangerous effects. Am Psychol. 1990;45:921–33.

Steele CM, Southwick L. Alcohol and social behavior I: The psychology of drunken excess. J Pers Soc Psychol. 1985;48:18–34.

Steele CM, Critchlow B, Liu TJ. Alcohol and social behavior II: the helpful drunkard. J Pers Soc Psychol. 1985;48:35–46.

Breslin FC, Sobell MB, Cappell H, Vakili S, Poulos CX. The effects of alcohol, gender, and sensation seeking on the gambling choices of social drinkers. Psychol Addict Behav. 1999;13:243–52.

Rose AK, Jones A, Clarke N, Christiansen P. Alcohol-induced risk taking on the BART mediates alcohol priming. Psychopharmacol. 2014;231:2273–80.

Harmon DA, Haas AL, Peterkin A. Experimental tasks of behavioral risk taking in alcohol administration studies: a systematic review. Addict Behav. 2021;113:106678.

Open Science Collaboration, Estimating the reproducibility of psychological science. Science 349 (2015).

Munafò MR, Nosek BA, Bishop D, Button KS, Chambers CD, du Sert NP, et al. A manifesto for reproducible science. Nat Hum Behav. 2017;1:0021.

Ioannidis JPA. Why most published research findings are false. PLoS Med. 2005;2:e124.

Begley CG, Ellis LM. Raise standards for preclinical cancer research. Nature. 2012;483:531–3.

Cohen JD, Ericson KM, Laibson D, White JM. Measuring time preferences. J Econ Lit. 2020;58:299–347.

Heilig M, Epstein DH, Nader MA, Shaham Y. Time to connect: bringing social context into addiction neuroscience. Nat Rev Neurosci. 2016;17:592–9.

Heilig M, MacKillop J, Martinez D, Rehm J, Leggio L, Vanderschuren LJMJ. Addiction as a brain disease revised: why it still matters, and the need for consilience. Neuropsychopharmacology. 2021. https://doi.org/10.1038/s41386-020-00950-y .

Sacco DF, Brown M, Lustgraaf CJN, Hugenberg K. The adaptive utility of deontology: deontological moral decision-making fosters perceptions of trust and likeability. Evolut Psychological Sci. 2017;3:125–32.

Everett JA, Pizarro DA, Crockett MJ. Inference of trustworthiness from intuitive moral judgments. J Exp Psychol Gen. 2016;145:772–87.

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Acknowledgements

We are grateful to Åsa Axén, Sandra Boda, Sarah Gustavson, Lisbet Severin, Lina Koppel, Theodor Arlestig and David Andersson for assisting with data collection.

This work was supported by the Swedish Research Council (MH: 2013-07434; GT: 2018-01755) and the Swedish Research Council for Health, Working Life and Welfare (EP: 2020-00864). Funders had no role in study design, data collection, analysis, decision to publish, or preparation of the manuscript.

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These authors contributed equally: Hanna Karlsson, Emil Persson, Markus Heilig, Gustav Tinghög.

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Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, 581 83, Linköping, Sweden

Hanna Karlsson, Irene Perini, Adam Yngve & Markus Heilig

Department of Management and Engineering, Division of Economics, Linköping University, 581 83, Linköping, Sweden

Emil Persson & Gustav Tinghög

The National Center for Priority Setting in Health Care, Department of Medical and Health Sciences, Linköping University, 581 83, Linköping, Sweden

Gustav Tinghög

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MH and GT provided funding for the study. HK, EP, IP, MH, and GT designed the study. HK, AY and GT collected the data. HK and EP analyzed the data and drafted the manuscript. All authors revised the manuscript and approved the final manuscript for submission.

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Karlsson, H., Persson, E., Perini, I. et al. Acute effects of alcohol on social and personal decision making. Neuropsychopharmacol. 47 , 824–831 (2022). https://doi.org/10.1038/s41386-021-01218-9

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Received : 18 June 2021

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DOI : https://doi.org/10.1038/s41386-021-01218-9

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A Review of Alcohol-Related Harms: A Recent Update

Abedin iranpour.

1 HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran

Nouzar Nakhaee

2 Neuroscience Research Center, Kerman University of Medical Sciences, Kerman, Iran

In the early decades of the 20 th century, discussions regarding alcohol were dominantly directed toward its therapeutic uses, but authorities now state that any level of alcohol consumption poses negative effects on health. Over recent months, increased attention has been devoted to disease burdens attributable to alcohol use worldwide. As more and more studies are conducted to illuminate the harmful effects of alcohol on different body systems, the mounting evidence generated requires documentation and publication. The current review was aimed at providing an overview of the recent literature on the adverse consequences of alcohol consumption.

Introduction

Alcohol is widely believed to be the only psychoactive substance with addictive potential “that is not controlled at the international level by legally binding regulatory frameworks” despite its profound implications for populations and public health. 1 The adverse effects of alcohol on health has been the subject of a rising number of studies in recent years, 1 , 2 with such research asserting that even modest alcohol use contributes to over 60 acute and chronic health conditions. 3 Studies have also shown that alcohol consumption is associated with more than 200 diseases, although its pathogenicity and lethality through chronic illnesses depend on the amount and quality of alcohol consumed and the patterns that underlie its intake. 4

Some scholars suggested that drinking small amounts of alcohol helps prevent conditions such as diabetes, ischemic heart disease (IHD), dementia, and cognitive decline, but none of the seminal review studies reported a “safest level” of alcohol consumption. 1 , 3 Another major concern about alcohol intake is that its health implications that occur through the mechanisms of other diseases, especially cancers, are likely to be underreported. 5 Such consumption, for instance, is associated with 18% of suicides, 18% of interpersonal conflicts and violence, 27% of road accidents, 13% of epilepsy cases, 48% of liver cirrhosis cases, 26% of oral cancer cases, 20% of tuberculosis (TB) cases, 11% of colon cancer cases, 5% of breast cancer cases, and 7% of hypertension (HTN) and heart disease cases worldwide, as indicated by the World Health Organization (WHO). 6 The WHO report notably reflected the use of the term “harmful use”. 6 Even though experts believe that no level of alcohol consumption improves health. 1 In general, even moderate alcohol consumption considerably increases the overall risk of mortality, especially among young individuals. 7

Epidemiology

The latest WHO report showed that in 2016, about 43% of the population over the age of 15 years (2.3 billion people) had consumed alcohol in the preceding 12 months. 1 The report also indicated that the lowest and highest alcohol consumption rates (2.9% and 59.9%, respectively) were found among the populations belonging to the areas where the Regional Office for the Eastern Mediterranean (EMRO) and the Regional Office for Europe have jurisdiction, respectively. The total alcohol per capita consumption (APC) in 2016 was 6.4 liters, which does not reflect any change from the levels recorded in 2010. However, a decline and an increase in this level were observed in the European region and the Western Pacific and Southeast Asia, respectively. Nevertheless, the percentage of “current drinkers” all over the world in 2016 was generally 4.6% lower than that in 2000, mostly because of an increase in prevalence of former drinkers and much less due to increases in the proportion of people with no alcohol use in their lifetime. 1

Interestingly, 25.5% of the alcohol consumed globally is ingested illicitly or without proper supervision. The alcohol consumed in this manner includes homemade alcoholic drinks, medical and industrial alcohols that are misused as drinks, and other alcoholic beverages that are produced and sold illegally. This type of alcohol consumption occurs in EMRO countries and in the Region of the Americas (AMR) at rates of 70.2% and 1.1% out of the total, which are respectively the highest and lowest rates worldwide. 1 In 2016, the world’s average rate of heavy episodic drinking (HED) (defined as drinking 60 g or more of pure alcohol on at least a single occasion at least once per month) was 18.2%, and the highest and lowest rates were observed in European and EMRO countries with 26.4% and 0.5% of total consumption, respectively. HED is associated with alcohol poisoning and increased respiratory rate, heart rate, body temperature, and the gag reflex, which may lead to a coma and death. 1 Still in 2016, alcohol use was the most important risk factor for death in the age group of 15 to 49 years and the seventh leading risk factor for all deaths and disability-adjusted life years (DALYs). In the aforementioned age group, 5.3% of all deaths in the world (2.8 million deaths), 12.2% of all deaths among men, and 3.8% of all deaths among women, are related to alcohol consumption. 3 These statistics render alcohol deadlier than afflictions such as diabetes, TB, and acquired immune deficiency syndrome (AIDS). 1

Although populations belonging to the lower socioeconomic class consume alcohol to a smaller extent than the individuals of high economic standing, they exhibit higher morbidity and mortality rates because of the adverse effects stemming from their combination of alcohol consumption with other hazardous behaviors and conditions, such as smoking, poor diet, and obesity; lower socioeconomic groups also have a greater occurrence of HED. 8

Alcohol-related harms

To identify what the most harmful drug is in the world, British researchers recently conducted multi-criteria decision analysis to rank medications in this respect. 9 They found that in the United Kingdom (UK), the reputation of being the most dangerous substance in terms of overall harm to users and others belonged to alcohol. In another study on substance abuse, a scale called margin of exposure (MOE) [the ratio of the no observed adverse effect level (NOAEL) of a substance to the normal dose of exposure] was used to rank control measures for substance abuse and health risk assessment. 10 The researchers revealed that, on a population scale, alcohol was the only substance falling within the high-risk category. 10 In what follows, the latest developments in research on alcohol-related harms are discussed.

Since 1995, many studies have shown that consuming any amount of alcohol can increase the risk of cancer. These works, however, did not specify a threshold for the emergence of carcinogenetic effects from alcohol and suggested that the best way to avoid carcinogenicity was to abstain from alcohol consumption. 11 Alcohol has been demonstrated as directly increasing the risk of gastrointestinal (GI) cancers and indirectly contributing to the alteration of deoxyribonucleic acid (DNA) strands and oncogenesis. It exerts synergistic effects with other carcinogenic chemical agents, thereby elevating the potency of these substances in causing cancer. 11 Alcohol also increases the risk of cancer by lowering blood levels of antioxidants such as vitamins A and E, zinc and iron, and some B vitamins including folic acid and thiamine. Finally, alcohol increases the risk of cancer progression by weakening the immune system. 5 , 11 , 12

Aside from biological evidence, numerous epidemiological results pointed to the association between alcohol consumption and cancers of the throat, lung, esophagus, stomach, liver, rectum, and breast among women. 13 As regards all these cancers, the probability of incidence is higher in female alcohol users than males,1 with even modest alcohol intake elevating the likelihood of breast cancer contraction among the former. Sufficient epidemiological confirmation has also been derived as to the association between alcohol dosage and cancer risk (dose-response relationship) and the parallelity of increases in alcohol use and cancer risk. These studies found no difference in risk levels among different alcoholic beverages. 13 Overall, the relative risk of developing all types of cancers increases with alcohol use. 1 , 3 Certain studies indicated that alcohol consumption likewise raised the risk of cancer mortality by 5.8%. 13 The good news is that stopping alcohol consumption reduces the possibility of contracting laryngeal and pharyngeal cancers. 13

Liver diseases

Alcohol-induced liver diseases (ALDs) are currently the most common type of liver-related disorders in Europe. Patients suffering from ALD experience increased life expectancy when they abstain from alcohol use, as liver cirrhosis is directly related to alcohol consumption, even in modest amounts. 14 The research also found that alcohol consumption alone (without food) and intake on a daily basis led to a two to threefold increase in the incidence probability of the aforementioned disease. 14 In 2016, alcohol-induced liver cirrhosis caused 607000 deaths and 22.2 million DALYs worldwide. 1 On the whole, sufficient biological and epidemiological corroboration has been derived with respect to the negative effects of alcohol on liver health and its contribution to the development of liver diseases, such as hepatitis and cirrhosis. 15 Ample proof has also been obtained on the relationship between high alcohol consumption and the increased incidence of liver disease. 15 , 16

Kidney diseases

Research showed that moderate to high amounts of alcohol not only directly increases the risk of elevated albuminuria and the incidence of chronic kidney disease (CKD), but also causes kidney damage indirectly by increasing blood pressure. 17

Cardiovascular disorders

In general, alcohol consumption increases the chance of mortality from hypertensive heart diseases (HHDs) by 7%. 6 Specifically, a positive relationship was found between alcohol consumption and IHD, atrial fibrillation (AF), congestive heart failure (CHF), stroke, HHD, and cardiomyopathy-an association that strengthens with increasing alcohol use. High levels of alcohol consumption weaken the cardiac muscle, thereby leading to a condition called alcoholic cardiomyopathy (ACM), which was responsible for 25997 deaths worldwide in 2015. ACM is caused specifically by ethanol in alcohol and acetaldehyde (the first metabolite of alcohol in the body), both of which were confirmed as implicated in cardiomyopathy. 18 , 19 Alcohol also poses synergistic effects with other toxins and micronutrient deficiencies in the development or intensification of the aforementioned condition. 19

Evidence showed a direct association between alcohol use and systolic and diastolic HTN-a relationship that is three times stronger in women who consume substantial amounts of alcohol than in men who ingest the same levels. 20 , 21 This relationship has also been observed in modest drinkers, indicating that low alcohol consumption contributes to HTN. In a cohort study in North America on 8334 individuals aged 45 to 64 years, a positive linear relationship was observed between alcohol consumption even in small amounts and increased blood pressure over a six-year period. 22 The DALY due to alcohol-related cardiovascular diseases (CVDs) has been estimated at 2%. 1 Some cross-sectional studies have reported that modest alcohol use could protect a person against CVDs, but more recent longitudinal researches and systematic reviews contradicted this claim, illustrating how even low to moderate alcohol use is a risk factor for the previously-mentioned illnesses. 18 , 23

Respiratory diseases

Alcohol consumption is a major risk factor for community-acquired pneumonia (CAP), as demonstrated in a study wherein the daily ingestion of 10 to 20 g of alcohol elevated the risk of CAP by 8%. 24 Alcohol consumption, especially in large amounts, likewise poses a considerable threat of TB development and failure in treating this condition. 25 In a meta-analysis of case-control and cohort studies, 22.3% of TB cases and 2.23% of TB deaths were related to alcohol consumption. 26

Mental health

Alcohol is a depressant that influences our moods, thoughts, feelings, and actions by affecting our neurotransmitters. Although alcohol intake can lead to temporary stress relief and relaxation, its long-term consumption increases the incidence of major mental disorders, including severe depression and anxiety disorders. 27

Statistics showed that countries with high alcohol usage among their populations also exhibit high suicide rates. A positive correlation was discovered between alcohol consumption and psychological disorders that adversely affect mental health, causing depression, cognitive impairment, dysphoria (disinhibition), irritability, and impaired judgment. 27 , 28 These conditions result in two to three times increase in the risk of suicidal thoughts, suicide attempts, and completed suicide among alcohol users relative to the normal population. 27 , 28 A study also reported increases of up to 7 and 37 times in the risk of suicide immediately after alcohol consumption and after heavy drinking, respectively. 1

Across the world, alcohol is a crucial risk factor for intentionally inflicted and unintentionally acquired injuries. Previous studies focused on the role of alcohol in interpersonal street violence (often among men), but recent research has also investigated its implication in domestic violence, including sexual violence. According to a 2016 WHO report, interpersonal violence induced by alcohol consumption causes 90000 deaths every year. 1 Intake of alcohol is known to reduce inhibition and stimulate aggressive behaviors in men. 1

In addition to harming drinkers in a variety of ways, including causing physical injuries, alcohol consumption also harms people around those who consume the substance. These dangers are often referred to as externalities. High alcohol consumption in a population is generally positively correlated with increased violence. A study in the United States (US), for instance, revealed that 40% of victims of violence reported perpetrators being under the influence of alcohol, albeit the police confirmed this claim for only 21% of the cases. 29 In a study conducted in 14 countries, 50% of violence victims stated that they had consumed alcohol in the six hours before the incidents; among these victims, 49% attributed the cause of violence and injury to alcohol. 29 Several studies also reported a strong relationship between homicide and alcohol, especially when used in excess. As determined in a meta-analysis, 48% of victims and perpetrators had consumed alcohol before violent incidents, and 37% of offenders and 33% to 35% of victims had consumed alcohol to the point of intoxication. 1 , 29

Alcohol consumption is positively correlated with intentional harms, such as self-harm and interpersonal violence, as well as unintentional harms such as road accidents, poisoning, falling, fires, exposure to heat and hot substances, drowning, and exposure to mechanical forces. Unintentional injuries due to alcohol are dose-dependent and their serious effects often occur under blood alcohol levels of more than 0.05 g/dl. 2

Sexual health

The quality of sexual relationships is one of the most important determinants of the quality of life; it depends on a set of psychological, social, and physical factors. Dissatisfaction with sexual life is known to cause anger and aggression and lead to increased marital violence and reduced warmth, all of which can be further exacerbated by alcohol consumption. The prevalence of alcohol-related sexual problems between couples is unclear, mostly because people tend to refrain from disclosing these issues. Many people believe that alcohol consumption improves sex, but research demonstrated that alcohol dependence was positively correlated with the increased incidence of male sexual disorders, such as erectile dysfunction, unsatisfying orgasm, premature ejaculation, and loss of libido. These conditions worsen with increasing duration of dependence and amount of alcohol consumed throughout a day. 30 Studies likewise uncovered that by eliminating and relieving anxiety and inhibition, alcohol use increases a person’s desire to engage in unprotected sex (especially when aroused), have multiple sexual partners, and participate in forced sex. 1 , 31

Alcohol dependence is an equally serious risk factor for female sexual dysfunction. A study on women with alcohol dependence syndrome (ADS) showed that sexual disorders, such as low sexual desire, the inability to reach orgasm, dissatisfaction with orgasm, and low or lack of vaginal lubrication were significantly more prevalent among women with ADS than those who did not consume alcohol. 32

Academic performance

A significant proportion of individuals afflicted with alcohol use disorders (AUDs) are between the ages of 18 and 29, which is the age group to which most college students belong. Studies revealed that alcohol consumption damages mental health, unfavorably influences mental performance, and drives increased engagement in high-risk behaviors. Alcohol consumption also causes students to progressively engage in absenteeism, fall behind on schoolwork, perform poorly on exams, and overall, exhibit declined academic performance. 33 , 34

Fertility and pregnancy

More than 40 years has passed since alcohol became globally known as a teratogenic substance. In 1973, the term “fetal alcohol syndrome” (FAS) was used to describe abnormalities and disorders associated with alcohol consumption during pregnancy. Biological and epidemiological studies have comprehensively documented findings regarding the relationship between heavy drinking during pregnancy and risks to fetal health as well as the occurrence of developmental abnormalities, including stillbirth, spontaneous abortion, premature birth, intrauterine growth restriction, low birth weight, growth retardation, and neurodevelopmental disorders that bring about severe behavioral and cognitive abnormalities. 1 , 35 Some studies argued that modest drinking during pregnancy was not as destructive as heavy drinking, but these endeavors failed to provide sufficient evidence on the safety of moderate alcohol intake. 36 Considering the wide variety of standards that apply to alcohol consumption and the alcohol content of beverages, recommending a specific maximum dosage for pregnant women is difficult, which is why most researchers advise mothers to sto p consuming alcohol completely to avoid any potential effects on their babies. 37

In 2016, the US Centers for Disease Control and Prevention (CDC) recommended that women of childbearing age who were pregnant or intended to become pregnant should avoid consuming alcohol to prevent harmful effects on the fetus. 38 Every year, nearly 119000 babies with FAS are born around the world. These statistics are alarming because, in addition to causing mental disabilities and birth defects, FAS causes developmental disorders that affect later stages of life and increase the likelihood of academic failure, drug abuse, mental illness, and criminal behavior. 39

In general, the effects of alcohol consumption on women, especially during pregnancy, seem to be underestimated and underreported given that such intake typically poses indirect consequences, such as unwanted teenage pregnancy,sexually-transmitted diseases (STDs) and their implications, exposure to assault and rape, interpersonal and domestic violence, and alcohol-related road accidents. In these situations, women themselves are not under the influence of alcohol and are therefore rarely included as a population category affected by such incidents; the aforementioned conditions are also always considered common harms of alcohol rather than risks specific to women of reproductive age. 1

The findings of the latest scientific studies increasingly highlight the profound and extensive implications of alcohol-related harms for individuals and larger populations, casting doubt on previous hypotheses regarding alcohol potentially having favorable effects on certain conditions and explicitly indicating that no level of alcohol intake is safe. 8 Even articles that emphasize some benefits of alcohol consumption caution readers that the alcohol industry pays journalists to steer public opinion toward one that favors alcohol consumption. 40 Hence, it may be time to stop using the phrase “harmful use of alcohol” when describing the adverse effects of the substance, because this construction implies that alcohol can be taken in a positive manner. In reality, consuming even small amounts can be detrimental to health. Public education should also be updated to inform people about the latest scientifically supported results regarding the health implications of alcohol consumption.

Acknowledgments

We would like to thank the reviewers for their valuable comments.

Conflicts of Interest

The Authors have no conflict of interest.