• Introduction
  • Conclusions
  • Article Information

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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The purpose of this study is to evaluate the safety, tolerability and effectiveness of V117957, compared to placebo, in subjects with alcohol use disorder (AUD) who experience insomnia associated with alcohol cessation.

The purpose of this project is to identify biomarkers by discovery of genomic and metabolomic markers associated with response to acamprosate treatment. To achieve this we will use “pharmacometabolomics-informed pharmacogenomics” such as generation a panel of iPSCs (stem cells) to discover biomarkers.  A new prospective randomized placebo-controlled trial of 3 month long treatment with acamprosate/placebo will provide new biospecimens, in addition to previously collected biospecimens, to enable the search for genetic and metabolomic biomarkers associated with sobriety or relapse in participants of this new study.

The purposes of this study are to demonstrate the feasibility of assessing delayed dim light melatonin onset (DLMO) in patients with comorbid AUD and DSWPD utilizing a combination of questionnaires and laboratory assay of salivary melatonin levels, and to examine the impact of low-dose melatonin on SOL and overall sleep quality in patients withcomorbid AUD and DSWPD with delayed DLMO compared to those without delayed DLMO.

The purpose of this study is to evaluate the safety of acamprosate in individuals with alcohol-use disorder (AUD) and alcohol-related liver disease.

The primary aim of this study is to define a comprehensive digital phenotype that predicts risk for near-future relapse or relapse in alcohol use in patients with alcohol-associated liver disease.

The secondary aim of this study is to assess the relationship between this digital phenotype and markers of disease severity outcome, including MELD score and readmission rates.

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Alcohol use and dementia: new research directions

Affiliations.

  • 1 Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia.
  • 2 The Matilda Centre for Research in Mental Health and Substance Use, The University of Sydney, Sydney, Australia.
  • 3 Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom.
  • PMID: 33394727
  • DOI: 10.1097/YCO.0000000000000679

Purpose of review: Alcohol is gaining increased recognition as an important risk factor for dementia. This review summarises recent evidence on the relationship between alcohol use and dementia, focusing on studies published from January 2019 to August 2020.

Recent findings: Epidemiological data continues to yield results consistent with protective effects of low-to-moderate alcohol consumption for dementia and cognitive function. However, recent literature highlights the methodological limitations of existing observational studies. The effects of chronic, heavy alcohol use are clearer, with excessive consumption causing alcohol-related brain damage. Several pathways to this damage have been suggested, including the neurotoxic effects of thiamine deficiency, ethanol and acetaldehyde.

Summary: Future research would benefit from greater implementation of analytical and design-based approaches to robustly model the alcohol use-dementia relationship in the general population, and should make use of large, consortia-level data. Early intervention to prevent dementia is critical: thiamine substitution has shown potential but requires more research, and psychosocial interventions to treat harmful alcohol use have proven effective. Finally, diagnostic criteria for alcohol-related dementia require formal validation to ensure usefulness in clinical practice.

Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.

Publication types

  • Alcohol Drinking / epidemiology*
  • Alcohol Drinking / prevention & control
  • Alcoholism / epidemiology
  • Alcoholism / prevention & control
  • Dementia / epidemiology*
  • Dementia / prevention & control
  • Ethanol / administration & dosage*
  • Ethanol / adverse effects*
  • Observational Studies as Topic
  • Protective Agents / administration & dosage
  • Protective Agents / pharmacology
  • Risk Assessment
  • Protective Agents
  • Open access
  • Published: 21 March 2024

Neuroimaging studies of cannabidiol and potential neurobiological mechanisms relevant for alcohol use disorders: a systematic review

  • Tristan Hurzeler   ORCID: orcid.org/0000-0002-6472-6615 1 , 2 ,
  • Joshua Watt 2 ,
  • Warren Logge 1 , 2 ,
  • Ellen Towers 1 , 2 ,
  • Anastasia Suraev 3 ,
  • Nicholas Lintzeris 1 , 4 ,
  • Paul Haber 1 , 2 &
  • Kirsten C. Morley 1 , 2  

Journal of Cannabis Research volume  6 , Article number:  15 ( 2024 ) Cite this article

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Metrics details

The underlying neurobiological mechanisms of cannabidiol’s (CBD) management of alcohol use disorder (AUD) remains elusive.

Aim We conducted a systematic review of neuroimaging literature investigating the effects of CBD on the brain in healthy participants. We then theorise the potential neurobiological mechanisms by which CBD may ameliorate various symptoms of AUD.

Methods This review was conducted according to the PRISMA guidelines. Terms relating to CBD and neuroimaging were used to search original clinical research published in peer-reviewed journals.

Results Of 767 studies identified by our search strategy, 16 studies satisfied our eligibility criteria. The results suggest that CBD modulates γ-Aminobutyric acid and glutamate signaling in the basal ganglia and dorso-medial prefrontal cortex. Furthermore, CBD regulates activity in regions associated with mesocorticolimbic reward pathways; salience, limbic and fronto-striatal networks which are implicated in reward anticipation; emotion regulation; salience processing; and executive functioning.

Conclusion CBD appears to modulate neurotransmitter systems and functional connections in brain regions implicated in AUD, suggesting CBD may be used to manage AUD symptomatology.

Introduction

The medical, psychological, and social sequelae of alcohol use disorder (AUD) are major global public health concerns. Harmful alcohol consumption is linked to many physical and mental health complications and is responsible for 5.1% of the global burden of disease (Griswold et al. 2018 ; WHO 2018 , 2021 ). AUD, particularly when moderate to severe, is a chronic relapsing disorder, characterized by compulsive alcohol-seeking and consumption despite negative repercussions to both physical and mental health (Haber, Riordan, & Morley 2021 ). A wealth of research suggests that neurobiological changes to various neurotransmitter systems and brain circuits underpin the behaviour and psychology which maintains AUD (Koob & Volkow 2016 ). Primary neurotransmitter systems influenced by prolonged and heavy alcohol consumption include dopaminergic, γ-aminobutyric acidergic (GABA)-ergic, glutamatergic, serotonergic, and opioidergic (Chastain 2006 ; Vitale, Iannotti, & Amodeo 2021 ). Pharmacotherapy can be useful, in conjunction with psychosocial support, for reducing the core symptoms of AUD (such as reducing craving, habitual seeking behaviours, and withdrawal) and achieving abstinence or aiding the control of consumption (Morley et al. 2021 ). However, there currently exists a paucity of medications available to treat AUD (Morley 2021 ).

Neuroimaging literature has identified specific neurocircuit and biochemical alterations thought to be responsible for the observed cognitive and behavioural changes associated with AUD. Changes to mesocorticolimbic reward pathways, following steep increases in opioid and D1 signaling into the ventral striatum, leads to increases in reward anticipation and salience attribution to drug-related cues which leads to increased drug-seeking behaviours (Koob & Volkow 2016 ). Further, reduced signaling of dopaminergic systems in reward and limbic networks leads to negative emotion, anhedonia, and heightened stress (Koob & Volkow 2016 ). Finally, fronto-striatal network and fronto-cortical dysregulation leads to reduced executive functioning and emotion regulation (Jentsch & Taylor 1999 ). Understanding the brain correlates of AUD and implementing neuroimaging techniques to identify the methods by which novel pharmacotherapies may modulate these correlates provide a method for more effective and tailored treatments.

Over the past few years there has been an influx of research exploring CBD as a potential pharmacotherapy for a variety of indications due to its wide-ranging therapeutic effects and favourable safety profile (José A Crippa et al. 2018 ). CBD is the second most abundant chemical constituent of the Cannabis sativa plant and, unlike Δ9-tetrahydrocannabinol (THC), is non-intoxicating and has nil potential for abuse or dependence (Arout, Haney, Herrmann, Bedi, & Cooper, 2022 ; Bergamaschi et al. 2011 ; Haney et al. 2016 ; Leweke et al. 2012 ; McCartney et al. 2022 ; Schoedel et al. 2018 ). CBD has shown to possess affinity for multiple targets including the modulation of serotoninergic, dopaminergic, glutamatergic, GABAergic (Scopinho et al. 2011 ) and endocannabinoid signaling (Corroon, Felice, & Medicine 2019 ). This multi-target action of CBD may explain the various therapeutic properties including antiepileptic (Devinsky et al. 2016 ; Talwar, Estes, Aparasu, & Reddy, 2022 ), anxiolytic (Berger et al. 2022 ; Bhattacharyya & et al. 2018 ; Stefan J. Borgwardt et al. 2008 ; Paolo Fusar-Poli et al. 2010 ; Jadoon, Tan, & O’Sullivan 2017 ; Wilson et al. 2019a ), neuroprotective (José A Crippa et al. 2018 ), and anti-inflammatory and antioxidant effects (Mandolini et al. 2018 ; Mechoulam et al. 2007 ; Ren et al. 2009 ). This combination of potential therapeutic effects suggests that CBD might be particularly well suited to management of alcohol use disorder. In fact, CBD may modulate drug craving and seeking behaviours. CBD has been shown to reduce craving and anxiety in heroin users (Hurd et al. 2019 ), as well as stress and drug cue alcohol reinstatement, voluntary alcohol consumption, withdrawal symptoms and alcohol induced relapse behaviours in preclinical models of alcohol dependence (Viudez-Martínez et al. 2018a , b , c ; A. Viudez-Martínez et al. 2018a ,  b ,  c ). This suggests that CBD could protect from further damage of alcohol due to its neuroprotective and anti-oxidant properties which could improve executive functioning, but may also modulate key disorder characteristics which precipitate relapse such as heightened anxiety (Skelley et al. 2020 ) and craving in response to alcohol cues and stressors (Hurd et al. 2019 ). Neuroimaging techniques provide valuable insights into the structure and function of the brain and may explain the relationship between the pharmacological action of CBD and its behavioural and psychological effects (Hargreaves et al. 2015 ; Nathan et al. 2014 ; Wong et al. 2009 ). However, there has currently been no attempt to compile and compare neuroimaging studies to examine whether the converging neurobiological effects of CBD are relevant to AUD. To establish the current understanding of the neurobehavioral mechanisms of action of CBD on the human brain, and its pharmacotherapeutic potential for AUD, we examined common neuroimaging techniques including, magnetic resonance spectroscopy (MRS), magnetic resonance imaging (MRI, including both functional and structural imaging), single photon emission computed tomography (SPECT) and positron emission tomography (PET). MRI is a non-invasive technique that produces anatomical images of the brain used to investigate both structural and functional aspects of the brain. Structural MRI provides a snapshot of brain anatomy in time while functional MRI (fMRI) can identify brain activity occurring during a variety of cognitive and functional activities of the brain in real-time. Specific cognitive phenomena can be targeted by presenting participants with specific tasks, known as task fMRI (tfMRI) (Heeger & Ress 2002 ; Linden et al. 1999 ; Worsley & Friston 1995 ) or also conducted in task-free paradigms known as resting state fMRI (rsfMRI) (Fox & Raichle 2007 ; Raichle et al. 2001 ). Magnetic resonance spectroscopy (MRS) is an imaging modality that can identify the presence and density of a variety of neurometabolites in the brain. Finally, nuclear imaging techniques PET and SPECT use radiotracers which are absorbed by the body and the resulting emission of positrons (in the case of PET) and gamma rays (in the case of SPECT) provides a measure of cellular and molecular function. The destination of the radiotracers indicates the location of changes in metabolic and other physiological processes such as blood flow, and regional chemical absorption.

This review aimed to systematically examine studies using these imaging techniques to elucidate the neurobehavioural and neuropsychological effects of CBD, as well as provide insights into the potential mechanism of CBD in the management of key symptoms of AUD.

This review follows the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines for systematic reviews (Moher et al. 2009 ). Prior to the commencement of the data extraction, this review was registered with the international prospective register of systematic reviews (PROSPERO # CRD42021272561). The original protocol can be accessed on the PROSPERO website.

Search strategy

Terms relating to CBD, and neuroimaging were used to search EMBASE, PubMed, Medline and PsycINFO databases. This search strategy used a combination of MeSH heading and key words and used two main sections. These sections related to “cannabidiol” and a section relating to imaging techniques i.e. (MRS OR Magnetic Resonance Spectroscopy OR Spectroscopy OR Metabolite Concentrations OR magnetic resonance spectroscopy OR MRS OR functional magnetic resonance imaging OR fMRI OR resting state functional OR magnetic resonance imaging OR rsfMRI OR structural magnetic resonance imaging OR MRI OR magnetic resonance spectroscopy OR PET OR positron emission tomography). The search was re-run in June 2022 to capture any new publications.

Study selection

Once all the database searches had been completed and duplicate studies removed, a multi-stage screening process was performed by one author (TH). Studies were screened in the following order i) title ii) abstract iii) full-text article. Titles were screened to ensure studies used CBD as the active medication and that neuroimaging outcomes were the key measure of interest. Abstracts were then further assessed to ensure only human studies were included. In the final stage, all remaining studies had a full-length text review to ensure that the study satisfied more specific inclusion criteria.

Eligibility criteria

Studies which investigated the effect of CBD on the brain using either MRI, fMRI, MRS, SPECT or PET in human subjects were included. All eligible studies also had to include an experimental group that received CBD which did not fit diagnostic criteria for a mental health disorder. Studies were excluded if they were post-mortem, animal investigations, non-brain MRI studies, or examined the effect of cannabis rather than CBD. Review and non-English articles were excluded. The reference list of all eligible studies was also manually searched to identify any additional publications.

Data extraction

The following data was extracted from all eligible studies: author, year of publication, number of participants in patient and control groups, age, proportion of males and females, clinical condition and diagnosis (patients only), matching factors in controls, neuroimaging paradigm, scanner specifics, outcome variables including: i) structural brain changes; ii) CBD-modulated brain activity (as measured through the blood oxygen level dependent [BOLD] response) or functional connectivity; iii) CBD-induced alterations in metabolites such as glutamate, GABA, and glutamine; iv) CBD-induced alterations in metabolism of blood PET.

Quality assessment

Risk of bias was assessed by the AXIS for cross-sectional studies or the Cochrane Risk of Bias (Sterne et al. 2019 ) for randomised trials with both crossover and parallel designs. The risk of bias assessment was assessed independently by two authors (KM and JW) and any discrepancies were resolved by discussion between the two authors with consultation available from a third party if required.

General overview of study selection process

The primary search identified 767 records from four databases see Fig. 1 in  Appendix  . After removing duplicates, 599 items remained. Titles were screened first and items that did meet eligibility criteria were removed leaving 113 studies. After screening abstracts, 53 studies remained. Finally, the full-texts were screened leaving 16 studies for inclusion in the review. Before publication, a secondary search in June 2022 identified four new studies that were included in the final version of the review. The 20 included studies all administered CBD orally with 19 studies dosing 600 mg CBD and one 400 mg CBD. Fourteen of the 20 included studies were task-based fMRI, four were rsfMRI, one study was an MRS study, and one study used SPECT imaging Although search terms related to SPECT were not included in the search strategy, this study was included due to its pertinence to the focus of this review. Additionally, various studies were used the same or similar participant samples as depicted by the colour categorisations of the outer ring of the sunburst plot (Fig. 2 in the Appendix ). In “ Functional MRI ” section we detail functional (subdivided into rsfMRI and different task paradigms) and neurochemical findings (Tables 1 and 2 ).

Functional MRI (fMRI)

Resting state fmri.

Four resting state fMRI studies (Bloomfield et al. 2020 ; Grimm et al. 2018 ; Pretzsch, Voinescu, et al. 2019 ; Wall et al. 2022 ) were identified. These studies examined brain activation by either measuring spontaneous low frequency fluctuations in BOLD signal while participants remain at rest in a MRI machine or cerebral blood flow (CBF) via the use of a technique called arterial spin labelling (ASL; (Barbier, Lamalle, & Décorps 2001 )).

Firstly, in a double-blind, randomised, placebo-controlled (DBRCT) crossover study, 13 males with autism spectrum disorder (ASD) and 17 neurotypical males (mean [SD] age = 30.85 [9.79] years and 28.47 [6.55] years for ASD and neurotypical participants, respectively) received a single dose of 600 mg CBD or placebo (Pretzsch, Voinescu, et al., 2019 ). Participants were scanned 2 h after drug administration. CBD significantly increased spontaneous fluctuations in BOLD signal across both groups in the right fusiform gyrus ( p  = 0.041) and in the cerebellar vermis ( p  = 0.048) which post-hoc analyses demonstrated were driven by an effect in participants with ASD ( p FWE  = 0.029 and p FWE  = 0.045; for fusiform and vermis clusters, respectively). Following a post-hoc seed-based analysis of functional connectivity in these regions of interest (ROIs), CBD was not shown to have a significant effect on vermal or fusiform functional connectivity with any other regions for neurotypical participants.

In another study (Grimm et al. 2018 ), 16 healthy male participants (demographic information not available) were included in a DBRCT crossover study with three separate arms and one-week intervals between scans. Participants were scanned 75 min following the consumption of either 10 mg THC, 600 mg CBD, or matched placebo. Seed-based analysis on four ROIs in the striatum, including the caudate (left and right) and putamen (left and right) were examined for connectivity with the rest of the brain. CBD administration led to an increase of fronto-striatal functional connectivity relative to placebo. Specifically, relative to placebo, those who were administered CBD showed a significant increase in connectivity between the right putamen seed ( p  < 0.03), and three clusters in the right prefrontal cortex (PFC). However, the analysis did not establish directionality.

In a crossover DBRCT, 15 participants (mean [SD] age = 24.1 [5.0] years, female = 60%) were administered either 600 mg CBD or placebo on separate days. The washout period was not reported, however, based on previous studies using the same sample, we can infer that the washout period was ≥ 1-week. Regional CBF was measured at rest 3 h after drug administration (Bloomfield et al. 2020 ). Compared to placebo, CBD administration significantly increased CBF in the hippocampus (15 mL/100 g/min [CI 5.78–24.21, p  = 0.004]). CBF increased in the orbitofrontal cortex ( p  = 0.019) by 10.04 mL/100 g/min (CI, 1.90–18.19). However, only the effect in the hippocampus survived Bonferroni correction.

Finally, a crossover DBRCT was used to examine the effects of CBD on the striato-cortical connectivity of 23 healthy participants administered 600 mg CBD or a matched placebo (≥ 1-week washout period) 150 min before an MRI scan (mean [SD] age 23.8 [4.3] years, female = 53%)(Wall et al. 2022 ). CBD significantly decreased functional connectivity between subregions of the striatum, including limbic striatum activity with the lateral frontal cortex and the right hemisphere insula ( p  < 0.05), and between the sensorimotor striatum and cerebellum ( p  < 0.05). However, increased connectivity was observed between the associative striatum (regions receiving information from the associative areas of the cortex) and posterior parietal lobes (extending into the parieto-occipital sulcus and into the left posterior cingulate) ( p  < 0.05).

Task based fMRI

Task-fMRI was the most common paradigm used to investigate the effect of CBD, with 14 of the 20 included studies employing task-fMRI. However, these 14 task fMRI studies comprised of data pertaining from three participant samples. In eight studies (Bhattacharyya et al. 2012 ; Bhattacharyya et al. 2014 ; Bhattacharyya et al. 2009 ; Bhattacharyya et al. 2010 ; S. J. Borgwardt et al. 2008 ; P. Fusar-Poli et al. 2010 ; Fusar-Poli et al. 2009 ; T. T. Winton-Brown et al. 2011 ), 15 male participants (mean [SD] age 26.7 [5.7]) were scanned using a crossover DBRCT, pseudo randomisation and a within group study design. Participants were either given THC 10 mg, CBD 600 mg or placebo 1 h prior to a task-fMRI scan with 1-month intervals between scanning sessions. Furthermore, four studies (Bhattacharyya, Wilson, Appiah-Kusi, O'Neill, et al., 2018 ; Davies et al. 2020 ; Wilson et al. 2019b ) scanned one sample consisting of 19 healthy controls (HC) and 33 clinical high risk (CHR) for psychosis (mean [SD] age of 23.4 [4.8] and 24.3 [4.73]; 49% and 42% female, respectively). In these DBRCT parallel-arm studies, CHR participants were given 600 mg CBD or placebo, while HC did not receive any medication, 3 h prior to a scan. Finally, two more studies (Bloomfield et al. 2022 ; Lawn et al. 2020 ) examined 24 participants (mean [SD] age 23.6 [4.12], female = 50%), however, the study by Lawn et al. ( 2020 ) excluded one participant because they did not complete the MID task correctly (mean [SD] age 23.74 [4.2], female = 52%). In this crossover DBRCT, participants were given 600 mg oral dose of CBD or matched placebo and were scanned 150 min later with a 7-day washout period. Experimental tasks applied across all three participant samples included go/no-go (Bhattacharyya et al. 2010 ; S. J. Borgwardt et al. 2008 ), oddball tasks (Bhattacharyya et al. 2012 , 2014 ), verbal paired memory (Bhattacharyya et al. 2009 , 2010 ), fearful faces tasks (Bhattacharyya et al. 2010 ; Bloomfield et al. 2022 ; Davies et al. 2022 ; Davies et al. 2020 ; P. Fusar-Poli et al. 2010 ; Fusar-Poli et al. 2009 ), monetary incentive delay (Lawn et al. 2020 ; Wilson et al. 2019b ), and passive visual and auditory presentations (T. T. Winton-Brown et al. 2011 ). The results are summarised by experimental task here.

Go/No go and oddball tasks

In go/no go tasks, participants are required to respond to appropriate, target “go” stimuli and not respond to inappropriate, “no-go” stimuli (Rubia et al. 2006 ). The number of false responses to “no-go” indicates inhibition capacity. Go/no-go tasks can be combined with oddball tasks to measure participants’ responses to novel stimuli, and ability to discriminate between salient or non-salient information. To do this, participants are presented with a series of repetitive stimuli that are irregularly interrupted by novel stimuli (the oddball stimulus) thereby providing information about how participants respond to novelty. S. J. Borgwardt et al., ( 2008 ) reported no significant drug effects on the combined go/no-go and oddball task performance, although there were different activation patterns on the ‘no-go’ relative to oddball trials between placebo and CBD conditions. Placebo administration revealed significant hyperactivation in the inferior and medial frontal gyri, the anterior insula, the anterior cingulate gyrus, and the supplementary motor area for ‘no-go’ compared to oddball condition ( p  < 0.0025). CBD administration showed hyperactivation in middle and superior temporal gyrus, insula, and posterior cingulate gyrus for ‘no-go’ compared to oddball condition ( p  < 0.0025). In comparison to placebo and for ‘no-go’ relative to oddball trials, CBD was associated with reduction in activity in the left insula and left superior and transverse temporal gyri ( p  < 0.01) . Bhattacharyya et al. ( 2012 ) , in a secondary analysis of S. J. Borgwardt et al., ( 2008 ), reported results from a go/no-go task with added oddball stimuli to account for the novelty of ‘no-go’stimuli. Response latencies across all task conditions were significantly reduced in CBD groups compared to placebo ( p  = 0.01) with a trend towards higher reduction in response latency to oddball than standard stimuli ( p  > 0.01). During the task, CBD attenuated activation in clusters in the left medial PFC ( p  = 0.01) and augmented activation in clusters in the right caudate, parahippocampal gyrus, insula, precentral gyrus, and thalamus ( p  = 0.02), relative to placebo. In a follow-up analysis, seed clusters in the inferior frontal, dorsal, striatal and posterior hippocampal foci were selected as ROIs due to their involvement in processing deviant, rare or novel stimuli (Rubia, Smith, Brammer, & Taylor, 2007 ) and were shown to be functionally connected to multiple brain regions during the oddball task (Bhattacharyya et al. 2014 ). CBD attenuated functional connectivity from the inferior frontal gyrus seed cluster with a cluster with peaks in the left anterior lobe of the cerebellum, left thalamus, and lingual gyrus ( p  < 0.001) and attenuated functional connectivity with the right insula ( p  = 0.043). In the dorsal striatum seed cluster CBD augmented the functional connectivity of the left dorsal striatum with the body of the left caudate nucleus and the left inferior frontal gyrus ( p  = 0.008) and attenuated functional connectivity with the left anterior cingulate and the left medial frontal gyrus ( p  = 0.007). In the hippocampal seed cluster, functional connectivity of the left posterior hippocampal cluster with the left parahippocampal gyrus was augmented by CBD ( p  = 0.0045), whereas the functional connectivity between the right parahippocampal gyrus, the left posterior cingulate, and the tail of the left caudate was attenuated in the CBD condition ( p  = 0.004).

Verbal paired memory task

The verbal paired memory tasks used in the selected articles were adapted from the paired associate learning subtest of the Wechsler Memory Scale–Revised (Wechsler 1987 ). This task primarily assesses episodic memory and induces activity in various areas associated with memory. Bhattacharyya et al. ( 2009 ) investigated the impact of CBD on mediotemporal and PFC activation during a verbal paired association task. Performance on the task was not significantly affected by treatment. However, CBD administration did modulate regions associated with memory consolidation and including insula, mediotemporal gyrus, lingual gyrus, precuneus, and precentral gyrus activation during repeated encoding ( p  < 0.05) and the hippocampus during recall blocks relative to placebo ( p  = 0.01).

A similar study incorporating the verbal paired memory task by task (Bhattacharyya, Wilson, Appiah-Kusi, O'Neill, et al., 2018 ), in which CHR participants who received CBD demonstrated greater activation in the precentral gyrus compared to placebo, coupled with reduced activation in the parahippocampus extending to the superior temporal gyrus and cerebellum ( p  = 0.003) and precentral gyrus ( p  ≤ 0.003) during encoding phases. Additionally, CHR participants who received CBD showed greater activation than placebo in regions including the medial frontal gyrus, right precentral gyrus and adjacent cingulate gyrus, and the left cingulate gyrus and caudate body ( p  ≤ 0.002) during the recall phase of the task (Bhattacharyya, Wilson, Appiah-Kusi, O'Neill, et al., 2018 ). Generally, these activation patterns signified a trend towards the normalisation of activity in these regions and resembling activation patterns observed in HC.

Fearful faces

During the fearful faces task, images of faces that exhibit varying levels of fearful expressions are presented to the participants to elicit activity associated with emotional processing and anxiety responses (Keedwell, et al. 2005 ; Morris et al. 1996 ). Fusar-Poli et al. ( 2009 ) demonstrated that CBD reduced activity in the amygdala ( p  = 0.0012) and the anterior and posterior cingulate cortex ( p  = 0.00065 and p  = 0.000432 respectively) while participants were processing intensely fearful faces. Moreover, CBD reduced activity in the posterior lobe of the cerebellum for moderately fearful face stimuli compared to placebo. Concurrently recorded electrodermal psychophysiological responses also demonstrated reduced skin conductance response (SCR) fluctuations for intensely fearful expression stimuli ( p  < 0.05) but not neutral or mildly fearful faces. This reduction of SCR fluctuations is a proxy for physiological arousal (Bach, Friston, & Dolan, 2010 ). The suppression of amygdala as well as the anterior cingulate covaried with the reductions in the number of SCR fluctuations ( r  = 0.524; p  = 0.049) and, as reported in a later study (Bhattacharyya et al. 2010 ), a trend level anxiolytic effect as indexed by the State Trait Anxiety Inventory ( r  = 0.551, p  = 0.017). Finally, the effect of CBD in modulating prefrontal-subcortical connectivity during emotion processing was investigated in a follow-up analysis (P. Fusar-Poli et al. 2010 ). CBD treatment led to significant disruption of forward connectivity between the amygdala and anterior cingulate observed in the placebo group while participants responded to fearful faces ( p  = 0.035).

In a DBRCT parallel arm study, the effect of CBD on both the mediotemporal and striatal function (Davies et al. 2020 ) was examined. Subsequently, the relationship between mediotemporal function and serum cortisol level during the fearful faces paradigm was examined in the same sample but using different techniques (Davies et al. 2022 ). During the processing of fearful faces, CHR participants in the placebo condition experienced greater activity in parahippocampal gyrus ( p  ≤ 0.003) and reduced activity in the striatum ( p  ≤ 0.002) compared to HC. Moreover, CHR participants receiving CBD, versus those who received placebo, showed hypoactivation in the parahippocampal gyrus and amygdala ( p  ≤ 0.002) and greater activation in the putamen ( p  ≤ 0.001). In the healthy control group, higher cortisol induced by social stress led to lower parahippocampal activation ( p  = 0.023) . CHR participants who received placebo showed a statistically significant difference between parahippocampal activation and cortisol when compared to controls who did not receive any treatment ( p  = 0.033). When CHR participants received CBD, they showed a similar relationship between cortisol and parahippocampal activation compared to healthy controls ( p  = 0.67). Conversely, Bloomfield et al ( 2022 ) demonstrated no significant drug effects on brain responses to emotional faces from any category (open-mouth happy/angry/neutral) when comparing CBD to placebo administered groups. However, this task did slightly differ from the previous face task as it used happy, fearful and neutral faces from the NimStim stimulus set (Tottenham et al. 2009 ).

Monetary incentive delay

Monetary Incentive Delay (MID) tasks present stimuli as cues that precede a monetary reward stimulus and can be used to measure the anticipation and feedback phases of reward processing (Knutson & Greer 2008 ). (Wilson et al. 2019a ) demonstrated that CBD attenuated the observed hyper-activity in the left insula/parietal operculum in the CHR group which occurred during reward and loss anticipation stages of the task ( p  = 0.035) (Wilson et al. 2019 ). Additionally, (Lawn et al. 2020 ) revealed that a whole brain analysis resulted in insufficient statistical evidence to suggest that CBD modulated reward-related brain activity to a greater degree than placebo.

Passive listening and viewing of stimuli

Viewing and listening passively during an fMRI scan allows for the investigation of the neural correlates of visual and auditory processing (Brown et al. 2004 ). T. Winton-Brown et al. ( 2011 ) investigated the effect of CBD on visual (checkboards) and auditory processing (speech). During passive auditory processing, CBD increased activation in temporal cortex bilaterally extending medially to the insulae and caudally to the hippocampi and parrahipocampal gyri compared to placebo ( p  ≤ 0.007). During auditory processing, CBD also reduced activation in posterolateral parts of the left superior temporal gyri-incorporating portions of supramarginal gyrus, the insula, and posterior middle temporal gyrus ( p  = 0.002). During passive visual processing, CBD increased activation in the right occipital lobe, with the largest increases in the lingus gyrus, cuneus, and middle and inferior occipital gyrus ( p  = 0.0065). This study demonstrates that CBD modulates a variety of regions during passive visual and auditory processing.

Magnetic Resonance Spectroscopy (MRS)

(Pretzsch, Freyberg, et al. 2019 ) investigated the effects of 600 mg of CBD on GABA and Glx (glutamine/glutamate) (N = 34 with ASD, mean [SD] age of 28.47 [6.55] years; N = 17 neurotypical controls) measured 2 h after drug administration. In the basal ganglia (BG), CBD increased Glx in both groups ( p uncorr  = 0.070); in the DMPFC, CBD decreased Glx in both groups ( p uncorr  = 0.055). There was a significant voxel × drug interaction effect ( p uncorr  = 0.033) in both groups, CBD increased Glx in the BG and decreased Glx in the DMPFC (this effect did not survive Bonferroni-correction). CBD increased GABA + in the control group (surviving Bonferroni-correction (p corr  = 0.004)). This group × drug interaction was largely driven by changes in the DMPFC ( p uncorr  = 0.038).

The search revealed only one study that had utilised SPECT methodology. Crippa et al. examined 400 mg of CBD versus placebo in a crossover DBRCT ( N  = 10, 7 day washout period) on resting blood flow using SPECT 110 min post-drug administration (J. A. Crippa et al. 2004 ). ROIs associated with limbic and paralimbic networks were selected a priori. Compared to placebo, CBD decreased uptake of a radiotracer contrast in clusters in the medio portion of the left amygdala-hippocampal complex and uncus extending into the hypothalamus and the superior section of the left posterior cingulate gyrus ( p  < 0.001). CBD also showed comparably increased activity in a cluster in the mediotemporal cortex including the left parahippocampal gyrus extending to include the left fusiform gyrus ( p  < 0.001). CBD was also associated with decreased subjective anxiety and increased mental sedation ( p  < 0.001) however there was no correlation between the mood scales and the ECD uptake (Table 1 ) .

Table 2  depicts the risk of bias as per each domain of the Cochrane RoB (Sterne et al. 2019 ). The randomisation processes for all studies were rated as having a low risk of bias (Domain 1). Some concerns were noted with respect to period and crossover effects (domain S) whereby some studies reported limited washout periods (e.g. 1-week ( Bloomfield et al. 2022 ; J. A. Crippa et al. 2004 ; Grimm et al. 2018 ; Lawn et al. 2020 ; Wall et al. 2022 ) or did not provide sufficient information regarding the washout period (Bloomfield et al. 2020 ). Although the half-life of CBD has previously been suggested to be up to 32 h (Ujváry & Hanuš, 2016 ) suggesting that 7 days may be a sufficient washout period, recent work showed that CBD has a long window of detection in plasma of up to 4 weeks post-drug administration (McCartney et al. 2022 ). No studies were considered to have risk of bias due to deviations from intended interventions (Domain 2) and there was low risk of bias due to missing data (Domain 3). Some potential concerns of bias in the outcomes that were measured (Domain 4) only were due to the potential of residual response due to test design. Concerns noted in the selection of reported results (Domain 5) were due to the majority of studies having no published pre-determined statistical analysis plan which may suggest potential vulnerability to selective analyses and reporting biases particularly relevant to fMRI data Table 3 .

This review synthesised neuroimaging literature examining the effects of CBD on neurobiology in healthy subjects and to further consider whether CBD may have promise in the management of AUD. We identified 20 neuroimaging studies that examined CBD in a healthy sample since 2004 which revealed broad modulatory effects across several brain regions and networks. Below we synthesise these results according to neuroimaging modality and then in light of converging neurobiological correlates associated with addictive behaviours.

Functional MRI was by far the most common neuroimaging modality accounting for 90% of the studies reviewed. Resting state fMRI was the focus of four studies presented in this review. Three studies demonstrated that CBD significantly modulated functional connectivity (Grimm et al. 2018 ) (Wall et al. 2022 ) and CBF (Bloomfield et al. 2020 ). CBD was shown to increase fronto-striatal coupling, from a seed in the right putamen to the PFC (Grimm et al. 2018 ); as well as increasing connectivity between “associative” striatum and parietal regions (Wall et al. 2022 ). Furthermore, CBD was observed to increase CBF to the hippocampus (Bloomfield et al. 2020 ). CBD was also demonstrated to produce minor decreases in functional connectivity in limbic and sensorimotor regions (Wall et al. 2022 ). However, one study showed non-significant differences between CBD and placebo on whole brain BOLD activity (Pretzsch, Voinescu, et al. 2019 ).Fourteen Task-based fMRI articles, published between 2008 – 2022, used task paradigms to examine reward processing, salience attribution, emotion regulation and executive functioning following CBD administration. During go/no-go and oddball tasks, which tests response inhibition and salience attribution, CBD was found to reduce activity in the left insula and left superior and transverse temporal gyri (S. J. Borgwardt et al. 2008 ). Further, while reducing response latencies, CBD was demonstrated to attenuate activation in left medial PFC and augment activation in right caudate, parahippocampal gyrus, insula, precentral gyrus and thalamus (Bhattacharyya et al. 2012 ). Increased fronto-striatal connectivity and reduced mediotemporal-prefrontal connectivity was also reported during attentional salience tasks following CBD administration (Bhattacharyya et al. 2014 ). During a learning and memory, verbal paired task, CBD was observed to modulate insula, midtemporal gyrus, lingual gyrus, precuneus, and precentral gyrus during repeated encoding phases and modulated hippocampus during recall. However, none of these results reached threshold for less than one false positive cluster (Bhattacharyya et al. 2009 ). During an emotional regulation and processing task, CBD administration led to a lower number of SCR fluctuations for intensely fearful stimuli, but not neutral or mildly fearful stimuli. This lower SCR covaried with reduced activity in the amygdala and anterior and posterior cingulate cortex (Fusar-Poli et al. 2009 ). Additionally, CBD was found to disrupt forward connectivity between the amygdala and anterior cingulate while participants responded to fearful faces (P. Fusar-Poli et al. 2010 ). This result is supported by another study by (Davies et al. 2022 ) whereby CBD administration decreased activation in the parahippocampal gyrus and amygdala and increased activation in the putamen during emotion processing in a CHR sample, and also normalised the relationship between cortisol and parahippcampal activation. This effect of CBD on brain activity during emotional processing was not replicated in a later study (Bloomfield et al. 2022 ), however, this study did not yield a significant task effect in response to neutral vs fear faces unlike previous studies which may explain the conflicting results. Functional MRI during MID tasks, which probe anticipation and feedback of reward processing, yielded mixed results. While CBD slowed reaction times in one study with attenuation of the hyperactivation of left insula/parietal operculum in a CHR sample (Wilson et al. 2019b ), another study failed to observe any significance differences in whole brain modulation (Lawn et al. 2020 ).Only two other studies were identified by the search strategy, focusing on neurometabolie presence and cerebral blood flow. One study used MRS (Pretzsch, Freyberg, et al. 2019 ). This study demonstrated that CBD modulates primary inhibitory and excitatory neurometabolites by increasing the inhibitory neurotransmitter GABA + in BG and DMPFC while increasing the excitatory Glx (glutamate + glutamine) in the BG but decreasing in the DMPFC relative to placebo-treated individuals. Additionally, one SPECT imaging study satisfied the inclusion criteria to be included in this review (J. A. Crippa et al. 2004 ). These authors found that CBD decreased cerebral blood flow to clusters in the medio portion of the left amygdala-hippocampal complex and uncus extending into the hypothalamus and the superior section of the left posterior cingulate gyrus. CBD was also shown to increase activity in a cluster in the mediotemporal cortex including the left parahippocampal gyrus extending to include the left fusiform gyrus.

These results suggest that CBD may modulate certain neurobiological correlates of addictive behaviors. There is a well-researched link between chronic heavy alcohol use impairs reward processing, salience attribution, emotion regulation and executive functioning (including inhibition control, working memory and self-monitoring) through the perturbation of various brain networks implicated in the development and maintenance of AUD (Koob & Volkow 2016 ). Some of these networks include the mesocorticolimbic (MCL), salience, fronto-striatal, and the limbic networks (Koob & Volkow 2016 ). These networks rely on various neurotransmitter systems including dopamine, opioid, endocannabinoid, serotonin, GABA, and glutamate systems. It has previously been suggested that CBD may normalise this perturbed neurocircuitry and subsequently support positive behavioural changes (Fagundo et al. 2013 ). Here, neuroimaging findings support the notion that CBD may modulate neurocircuitry implicated in the maintenance of AUD.

Mesocorticolimbic and salience attribution networks, which are responsible for reward processing and salience attribution, are functionally and anatomically linked (McCutcheon et al. 2019 ). The cannabinoid 1 receptors (CB 1 R), of which CBD is a negative allosteric modulator (NAM), are commonly located on the presynaptic terminals of dopaminergic neurons (Fitzgerald et al. 2012 ; Laprairie et al. 2015 ). Therefore, CBD may normalise the increased reward and salience attribution to alcohol associate cues by down regulating dopaminergic signalling in both the MCL and salience network. Evidence of this can be seen through CBD’s effect on the insula which is a major junction for both the mesolimbic (McCutcheon et al. 2019 ) and salience networks (Goulden et al. 2014 ; Peyron, Laurent, & Garcia-Larrea, 2000 ; Seeley et al. 2007 ). Various studies presented in this review suggest that CBD may attenuate both insula activity (Wilson et al. 2019a ); Bhattacharyya et al. 2012 ) and functional connectivity (Wall et al. 2022 ). Thus, CBD may act to normalise hyper-signalling in the insula found in those with AUD, reducing both salience attribution and the reward processing. Indeed, the insula has been shown to have a major role in interoception (Critchley 2004 ) and patients with lesions in the insula have been observed to show attenuated craving and abstinence from cigarettes (Naqvi et al. 2007 ). Furthermore, CBD was shown to modulate the hypothalamus, the amygdala, the thalamus, the anterior cingulate cortex, and the hippocampus which may be an indication that CBD may not only modulate the salience and reward processing but also emotion regulation.

Prolonged alcohol use can commonly lead to negative emotional states and impairment in limbic neurocircuitry and emotional processing (Jansen et al. 2019 ; Oscar-Berman & Marinković, 2007 ). Several studies have observed heightened activation in the amygdala in those with AUD relative to controls during fMRI affect reactivity tasks (Gilman et al. 2008 ; O'Daly et al. 2012 ). Across the studies included in this review, CBD induced modulation of the hippocampus during recall (Bhattacharyya et al. 2009 ); attenuation of the amygdala and ACC during fearful faces paradigms (Bhattacharyya et al. 2010 ; Bloomfield et al. 2022 ; Davies et al. 2022 ; Davies et al. 2020 ; P. Fusar-Poli et al. 2010 ; Fusar-Poli et al. 2009 ); decreased connectivity between the amygdala and the anterior cingulate during emotion processing (P. Fusar-Poli et al. 2010 ); normalisation of parahippocampal activity during encoding processes (Bhattacharyya, Wilson, Appiah-Kusi, O'Neill, et al. 2018 ) and fear processing (Davies et al. 2020 ); and the relationship between cortisol and parahippocampal activity in CHR participants during fear processing (Davies et al. 2022 ). These results support the idea that CBD administration demonstrates interactions with limbic, particularly amygdala and ACC, activity as well as the functional connectivity between the amygdala and ACC. This modulation of the limbic network may be due to a number of mechanisms such as NAM action on CB 1 Rs (Campos & Guimarães 2008 ; Russo et al. 2005 ), alterations 5-HT1A in the amygdala and hippocampus and/or the release of pro-opiomelanocortin, corticotropin-releasing factor and glucocorticoid receptor gene expression following acute stress exposure (Viudez-Martínez, García-Gutiérrez, & Manzanares 2018 ).

Finally, CBD may induce improvements in reward processing, salience attribution and emotion regulation due to top-down control through increased fronto-striatal functional connectivity. In this review, several studies demonstrated increased fronto-striatal connectivity following CBD administration (Bhattacharyya et al. 2014 ; Grimm et al. 2018 ) (Wall et al. 2022 ) and therefore, improved executive functioning. In the context of AUD, deficits in executive functioning have been thought to be due to deficits of GABAergic signalling from the PFC (George et al. 2012 ). Further, glutamatergic projections from the PFC to the VTA in rats controls dopaminergic activity in the mesocortical pathway (Geisler & Wise 2008 ). This excitatory signalling to the VTA has been suggested to be involved in increasing conditioned behaviour and incentive salience in the presence of alcohol related cues (Lapish, Seamans, Judson Chandler, & Research 2006 ). To this degree, one study demonstrated CBD to increase GABAergic but decrease glutaminergic signalling from the DMPFC (Pretzsch, Freyberg, et al. 2019 ) which may therefore be relevant to alcohol recovery by improving both executive functioning and reducing cue induced craving and conditioned alcohol-seeking behaviour.This review identified several limitations in the studies that have utilised neuroimaging methods to examine the effect of CBD on the brain. Firstly, with regards to fMRI studies, there was a lack of consistency of imaging tasks and substantial methodological heterogeneity across the studies which therefore limit conclusions regarding CBD-induced neurobiological modulations to be relatively task specific. In addition, the 20 studies found in our search were obtained from only 6 different participant samples following completion of long neuroimaging protocols (see the outer ring of the sunburst plot, See Appendix Fig. 2). Thus, it is possible that the literature base may be subject to some bias due to sample specific effects and limited heterogeneity. Comprehensive and longer neuroimaging protocols may be vulnerable to task fatigue (Wylie, et al. 2020 ) and poorer data collection due to movement artifacts and scanner drift (Kopel et al. 2019 ). Moreover, there was diversity with regards to the timing between drug administration, scan time and also washout periods between sessions in crossover studies. In addition, the lack of pre-published protocols may lead to selective analyses which may be particularly relevant for fMRI studies. Additionally, as a meta-analysis could not be conducted due to the number of outcome variables, there may be involuntary bias in reporting results which were unintentionally favoured. Finally, while this review provides evidence for CBD’s modulation of neurocircuitry implicated in AUD-related behaviours, certain results suggest some non-significant results (Bloomfield et al. 2022 ; Lawn et al. 2020 ) and some are conflicting (Bloomfield et al. 2020 ; J. A. Crippa et al. 2004 ). Further, as results presented here may not translate to effects in AUD clinical profiles, directly examining the effect of CBD in AUD participants is required before determining the mechanisms by which CBD may function as a therapeutic use in this population. Recommendations for future research include publication of protocols to reduce deviation from protocol bias and selective analyses, optimised study design to reduce participant fatigue, ensuring a sufficiently long washout period between the crossover sessions, and consistent drug-scan administration time relative to peak plasma CBD concentrations.

In conclusion, previous research suggests that CBD may affect salience, reward, emotion generation and regulation and executive control (including inhibition control, working memory and self-monitoring) processes. These processes are highly relevant to alcohol seeking behaviours, suggesting that CBD may have potential in the management of alcohol use disorder. Although not supported by all the studies presented, the majority of the neuroimaging literature presented in this systematic review suggests that CBD may normalise these processes through its effect on mesocorticolimbic, limbic, salience and fronto-striatal signalling. Various limitations may explain some of the discrepancy in results including heterogenous methodological designs, the same or similar participant samples being used across different studies, variable drug administration times, possible carryover effects and participant fatigue due to long imaging protocols. Given the relevance of the networks affected by CBD in this review in alcohol seeking behaviour and relapse, research into the effect of CBD on brain and behaviour in populations with AUD to determine any potential role for management is warranted.

Availability of data and materials

Not applicable.

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figure 1

PRISMA flow chart. Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) flow diagram of the study selection process. EM = Embase; Med = Medline; PI = PsycINFO; PM = PubMed; MRI = magnetic resonance imaging; fMRI = functional MRI; rsfMRI = resting state fMRI; MRS = magnetic resonance spectroscopy; PET = positron emission tomography

figure 2

Sunburst chart. The proportion of studies using each neuroimaging modality in the inner ring. Each colour in the outer ring indicates a different participant sample

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Why alcohol-use research is more important than ever

Nih's george koob talks about how addiction changes the brain and the rise in alcohol-related deaths.

Alcohol use disorder is a common but serious condition that affects how the brain functions.

Alcohol use disorder is a common but serious condition that affects how the brain functions.

George Koob, Ph.D.

  George Koob, Ph.D.

Alcohol use disorder (AUD) affects roughly 15 million people in the U.S. People with the condition may drink in ways that are compulsive and uncontrollable, leading to serious health issues.

"It's the addiction that everyone knows about, but no one wants to talk about," says George Koob, Ph.D., the director of the National Institute on Alcohol Abuse and Alcoholism (NIAAA).

As NIAAA celebrates an important milestone this year—its 50th anniversary—the institute's research is more important than ever. Like NIAAA reported earlier this year, alcohol-related health complications and deaths as a result of short-term and long-term alcohol misuse are rising in the U.S.

"Alcohol-related harms are increasing at multiple levels—from emergency department visits and hospitalizations to deaths," Dr. Koob says. He spoke about NIAAA efforts that are working to address this and how people can get help.

What has your own research focused on?

I started my career researching the science of emotion: how the brain processes things like reward and stress. Later, I translated this to alcohol and drug addiction and investigating why some people go from use to misuse to addiction, while others do not.

What are some major breakthroughs NIAAA has made in this area?

We now understand how alcohol affects the brain and why it causes symptoms of AUD . This has far-reaching implications for everything from prevention to treatment. We also understand today that AUD physically changes the brain. This has been critical in treating it as a mental disorder, like you would treat major depressive disorder.

Other breakthroughs have been made in screening and intervention, and in the medications available for treatment. All of this has led to a better understanding of how the body changes when one misuses alcohol and the proactive actions we can take to prevent alcohol misuse.

What is a misconception that people have about AUD?

Many people don't realize how common AUD is. There are seven times more people affected by AUD than opioid use disorder, for example. It doesn't discriminate against who it affects. People also don't realize that AUD is a brain disorder that actually changes how the brain functions. Severe AUD is associated with widespread injury to the brain, though some of the effects might be partially reversible.

What's next for NIAAA?

For five decades, the institute has studied how alcohol affects our health, bringing greater awareness to alcohol-related health issues and providing better options for diagnosis and treatment. Recent research has focused on areas such as the genetics of addiction, links between excessive alcohol use and mental health and other disorders, harm to long-term brain health that can be caused by adolescent alcohol use, and the effects of prenatal alcohol exposure, among others.

"We want everyone from pharmacists and nurses to addiction medicine specialists to know more about alcohol and addiction." - George Koob, Ph.D.

Currently, we are working on a number of initiatives. One is education. We want everyone from pharmacists and nurses to addiction medicine specialists to know more about alcohol and addiction. We're also working on prevention resources for middle school-aged adolescents. Other goals include understanding recovery and what treatments work best for people and why. We're also learning more about alcohol's effects on sleep and pain, and we have ongoing efforts in medication development.

Finally, we're learning more about the impact of alcohol on women and older adults. Women have begun to catch up to men in alcohol consumption and alcohol-related harms. Women are more susceptible to some of the negative effects that alcohol has on the body, from liver disease to certain cancers. Further, more older adults are binge drinking and this places them at greater risk of alcohol-medication interactions, falls, and health problems related to alcohol misuse.

How can someone get help?

If alcohol is negatively affecting you or someone you know, seek help from someone you respect. For example, a primary care doctor or clergy member. There are a number of online resources from NIAAA, like the NIAAA Alcohol Treatment Navigator® , an online resource to help people understand AUD treatment options and search for professionally led, evidence-based alcohol treatment nearby. There's also Rethinking Drinking SM , an interactive website to help individuals assess and change their drinking habits. Also, know that there is hope. Many people recover from AUD and lead vibrant lives.

July 16, 2020

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The association between alcohol consumption and sleep disorders among older people in the general population

  • Annie Britton 1 ,
  • Linda Ng Fat 1 &
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The relationship between alcohol consumption and sleep disturbance is complex. The association of alcohol dependence with insomnia is likely to be bidirectional in nature. Alcohol use is common among older people in many societies and the prevalence of insomnia tends to increase with age, therefore this group warrants particular consideration. We explored the cross sectional and long term (30 years) associations between alcohol drinking (volume and hazardous drinking) and sleep duration and insomnia in a general population study of older adults (6,117 male and female civil servants followed for 30 years). For men, drinking more than 21 units (approximately 168 grams) of alcohol per week, compared with not drinking, was associated with waking several times a night (odds ratio 1.30, confidence intervals 1.02–1.66). Men who maintained a heavy volume of drinking over the three decades of observation, or who had an unstable consumption pattern, tended to have worse sleep profiles in terms of waking tired and waking several times. Sustained male hazardous drinking (as measured by the AUDIT-C scale) was also associated with worse sleep profiles. Findings for women were not so clear. In this population based setting, drinking high volumes of alcohol may contribute to the prevalence of sleep problems in older age, particularly for men. People in this age group should be discouraged from using alcohol as a sleep aid.

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Introduction

Inadequate sleep is estimated to affect about one in five adults 1 . Insomnia symptoms (short sleep and disturbed sleep) are associated with an increased risk of a range of chronic health conditions, such as diabetes 2 , hypertension 3 and all-cause mortality 4 .

The relationship between alcohol consumption and sleep disturbance is complex. Alcohol acts as a sedative and reduces sleep onset latency 5 , and as such, may be used proactively to relieve insomnia 6 . However, there is evidence that alcohol consumption also disrupts sleep, particularly the period of rapid eye movement (REM) sleep 7 . The perpetual use of alcohol as a sleep aid may be a counterproductive long-term strategy as alcohol disrupts sleep quality and intensifies the need to consume more alcohol 8 . The association of alcohol dependence with insomnia may be bidirectional in nature 9 .

Heavy consumption of alcohol over an extended period of time leads to increased tolerance and this tolerance is accompanied by adaptation of the neurotransmitter systems 5 . Furthermore, long-term consequences of alcohol may lead to changes in sleep regulation. The influence of alcohol on sleep therefore needs to be evaluated by exploring both the short term effects on sleep (cross sectional data) and the long-term consequences (longitudinal data of repeated measures). At present, most literature is based on cross-sectional studies and thus cannot assess direction of effects 6 .

Alcohol consumption among the elderly has increased 10 and the prevalence of insomnia tends to increase with age 11 , therefore this age group warrants particular consideration.

This paper will address the following aims: (1) to explore the cross-sectional association between alcohol drinking and sleep problems in a general population study of older adults and (2) to explore the long term association between typologies of alcohol drinking and chronic sleep problems. To our knowledge, this is the first paper to utilize individual longitudinal repeat data on sleep and alcohol in this way.

The Whitehall II study was established in 1985 as a longitudinal study to examine the socioeconomic gradient in health and disease among 10,308 civil servants (6895 men and 3413 women) 12 . All civil servants aged 35–55 years in 20 London-based departments were invited to participate by letter and 73% agreed. Baseline examination (Phase 1) took place during 1985–1988 and involved a clinical examination and a self-administered questionnaire containing sections on demographic characteristics, health, lifestyle factors, work characteristics, social support and life events. Subsequent phases of data collection have alternated between postal questionnaire alone and postal questionnaire accompanied by a clinical examination.

The University College London Medical School Committee on the ethics of human research approved the Whitehall II study all research was performed in accordance with relevant guidelines/regulations. Written informed consent was obtained at baseline and renewed at each contact. Whitehall II data, protocols, and other metadata are available to bona fide researchers for research purposes. (Data sharing policy is available at http://www.ucl.ac.uk/whitehallII/data-sharing ).

During three decades of follow-up, repeated measures were obtained via a self-completed questionnaire of insomnia symptoms and sleep duration and repeated measures of alcohol consumption and problem drinking.

Assessment of Sleep measures

Sleep duration was assessed at phases 1 (1985–88), 5 (1997–99), 7 (2002–04, 9 (2007–09), and 11 (2012–13) by asking participants: “how many hours of sleep do you have on an average week night?” Respondent choices were: 5 hours or less, 6 hours, 7 hours, 8 hours, and 9 hours or more”.

Sleep disturbances were assessed at phases 5, 7, 9, and 11 using the 4-item Jenkins Scale 13 . This scale includes 4 questions on “having trouble falling asleep”, “waking up several times per night,” “having trouble staying asleep,” “waking up after the usual amount of sleep feeling tired and worn out” (i.e., waking without feeling refreshed) over past 30 days; all items have a 6-point response scale (1 = never; 2 = 1–3 days; 3 = 4–7 days; 4 = 8–14 days; 5 = 15–21 days; 6 = 22–30 days).

All sleep variables were dichotomized to form groups that were, as closely as possible, similar in size in relation to the total sample. These were as follows; Sleep duration (<7 versus 7+ hours (reference)), Trouble staying asleep over 30 days (4+ v. <4 days), Trouble falling asleep (1+ v. 0 days), Wake as usual but tired (1+ v. 0 days), Wake several times a night, (4+ v. <4 days). Dichotomization in this way allowed for a large enough sample to use in statistical analyses when stratifying by men and women. For all sleep variables the sleep category corresponding to better sleep was treated as the reference category.

Chronic sleep problems were defined as those when participants who reported a sleep problem (based on the above dichotomy) at three or more data collection phases over the follow-up period.

Assessment of alcohol consumption

Volume of consumption (phases 1, 3, 5, 7, 9, 11).

Participants were asked to report the number of alcoholic drinks they had consumed in the last 7 days. Drinks were converted into UK units of alcohol (whereby one unit is equivalent to 8 g of ethanol) using a conservative estimate of one UK unit for each measure of spirits and glass of wine, and two UK units for each pint of beer. These converted measurements were then summed to define the total weekly number of UK units consumed. Participants who did not drink alcohol in the past year were classified as ‘non-drinkers’.

Retrospective alcohol life-course grid

Life course alcohol consumption was defined using decade based grids 14 (Appendix  1 ) starting with information in the teens (16–19 years) and spanning to the eighties (and older) on the three components of the AUDIT-C questionnaire: frequency of consumption, number of drinks on a typical drinking day, and frequency of consuming six or more drinks in a single occasion. AUDIT-C cases were defined as those scoring 5 or more points 15 . Non-drinkers (participants who did not drink alcohol in the previous year) were excluded from the classification (Appendix  2 )

Alcohol typologies based on volume

Typologies of alcohol consumption over the measurement periods were then created 16 : (1) Stable None, (2) Stable moderate, (3) Stable heavy, (4) Unstable moderate (at least half of the phases were moderate), (5) Unstable heavy and (6) Former drinkers (previously reported consumption but none in the most recent phase). “Moderate” (within UK guidelines 17 (1–14 [8–112 g] units per week), and “Heavy” (above guidelines (15 + units). When an individual reported moderate and heavy on an equal number of occasions, participants were assigned to the unstable heavy drinking group. There were 44 participants who did not fall into either of the categories and were excluded.

Hazardous drinking over follow-up

Participants were considered to be chronically hazardous drinkers if they were AUDIT-C positive on three of more data collection phases (in the retrospective alcohol life-course grid).

Cross-sectional associations were explored using phase 11 data. Longitudinal associations used data from phases 1 through to 11. Logistic regression analyses with the sleep variables as the outcome variable, and alcohol variables as the main exposure, were performed in Stata v15, adjusting for age. Models were carried out separately for the different alcohol measurements, and were stratified by men and women.

In 2012–2013, 70.9% of the original cohort who were still alive (age range 61–81 years), participated in phase 11. Of these 6,318 men and women, 6117 (96.8%) had data on alcohol and sleep. Men consumed more alcohol than women with 15.7% consuming 21 or more units per week compared to only 2.4% of women (Table  1 ). 30.5% men and 12.8% women scored more than 5 on the AUDIT score, indicating hazardous drinking.

The most common drinking typologies over the three decades of observation were stable moderate drinkers (21.2%) and unstable moderate (29.2%). Women were more likely to report being former drinkers than men (24.8% and 12.8% respectively) (Table  2 ). Chronic hazardous drinking was indicated in 38% men and 17% women.

In terms of sleep problems, men were more likely to report sleeping less than 7 hours per night than women (63.7% men compared to 54.4% women). However, women were more likely to report trouble falling asleep (69.6% compared to 49.5% men) (Table  1 ). Over the thirty years follow up, women generally reported more chronic sleep problems than men (Table  2 ). More than half the women studied reported trouble falling asleep, waking tired, and/or waking several times a night.

Cross sectional analyses between alcohol (both volume and hazardous) and sleep problems found that men drinking more than 21 units per week or drinking hazardously were more likely to have disturbed sleep parameters than those not drinking in the past week or not drinking hazardously (Table  3 ). For example, men drinking 21+ units were more likely to wake several times a night than non-drinkers (OR 1.30 CI:1.02–1.66). For women, the picture is less clear. There is a suggestion that those women drinking more than 21 units were less likely to have short sleep (less than 7 hours) compared to non-drinkers (OR 0.39 CI: 0.19–0.81).

The relationship between longitudinal alcohol typologies and chronic sleep problems reflected the cross-sectional picture (Table  4 ). For men, compared to stable moderate drinkers, those who were stable heavy drinkers were more likely to wake tired (RRR 1.37 CI: 1.02–1.84) and wake several times a night (RRR 1.52 CI: 1.13–2.05). For women there were less clear risks associated between drinking and sleep problems.

In this large, population based study of older adults, we found that, for men, drinking more than 21 units per week, compared with not drinking, was associated with disturbed sleep (cross sectional analyses). Those who maintained this heavy volume of drinking over the three decades of observation, or who drank in a potentially hazardous pattern tended to have worse sleep profiles in terms waking tired and waking several times. The findings were not so clear among women and the reasons for sex differences warrants further research.

In a recent cross-sectional population study of 187,950 adults in the United States short sleep prevalence was higher among adults who consumed any alcohol compared with those who never consume alcohol 18 . Our findings contrast with this study in that we did not find strong association between drinking and sleep duration. The disparity may, in part, be due to ethnic differences. Jackson et al . note that the prevalence of short sleep across alcohol consumption patterns was more variable among whites, and the majority of Whitehall II participants are white.

There are few other longitudinal population based studies with which to compare our findings. Most are based on alcoholics in clinic settings 19 . Among 1,920 community dwelling men and women, those with persistent alcohol dependence had higher odds of insomnia that those without alcohol dependence over a fifteen year follow-up 20 . Whilst we did not measure alcohol dependence, we did find such an association between hazardous drinking and disturbed sleep in our data.

Our finding that those who have trouble falling asleep were more likely to be persistent heavy drinking suggests that they may be using alcohol as a sedative. This is partially corroborated in an earlier study on same population. The Whitehall II participants were asked about reasons for change in drinking over the last 10 years and an increase in consumption was cited as a means to help get to sleep was by 6% of men and 5% of women 21 .

Our study has limitations. For instance, we used self-reported alcohol consumption data and self-reported sleep data and therefore these measures may be at risk of reporting bias. The population may not be representative of all older adults in the UK and it is unlikely that the full spectrum of drinking behavior is represented. However, the mean consumption is similar to that reported in representative studies, such as Health Survey for England and English Longitudinal study of Ageing 22 . Another limitation is that we were not able to capture fully patterns of consumption in terms of binging. Drinking appears to have differential effects on sleep depending on chronic versus acute dosage 18 Our cut-offs for drinking exposures and sleep problems are largely arbitrary and it is possible to other subtle relationships are masked. Findings using self-reported sleep can only support the hypothesis that alcohol impacts on underlying sleep architecture (for example reduction or suppression of REM sleep), which would need to be confirmed by overnight polysomnography sleep studies. Despite these limitations, this study has important strengths. The repeated collection of alcohol and sleep data over such a long period is unique. We were thus able to look at long-term drinking typologies and persistent sleep problems over three decades.

In this population based setting, drinking high volumes of alcohol or drinking hazardously may contribute to the prevalence of sleep problems in older age. Those with disrupted sleep should consider reducing alcohol consumption and people in this age group, particularly men, should be discouraged from using alcohol as a sleep aid. It is well recognized that sleep problems have a significant impact on quality of life with increased morbidity and mortality seen in population studies 3 . Identifying people at risk of sleep disturbances as a result of their drinking may have important public health benefits.

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Acknowledgements

The Whitehall II study is supported by the UK Medical Research Council (MR/K013351/1; G0902037), BritishHeart Foundation (RG/13/2/30098), and the US National Institutes of Health (R01HL36310; R01AG013196).

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Britton, A., Fat, L.N. & Neligan, A. The association between alcohol consumption and sleep disorders among older people in the general population. Sci Rep 10 , 5275 (2020). https://doi.org/10.1038/s41598-020-62227-0

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Alcohol and Your Brain: The Latest Scientific Insights

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  • Transient memory loss, “blackouts,” and hangovers related to alcohol consumption are brain health risks.
  • Alcohol use disorder (alcoholism) is a risk factor for developing dementia.
  • Heavy or excessive alcohol consumption is dangerous to the brain for a number of reasons.
  • The impact of mild to moderate alcohol consumption (1-3 drinks a day) on brain function is less clear.

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Depending on who you ask, you might be told to drink a few glasses of red wine a day or to avoid alcohol altogether. The reasons for such recommendations are many, but, by and large, they tend to stem from a study someone read about or saw reported in the news.

So why is it so hard to know whether alcohol is good or bad for us—especially for our brains? In this post, we’ll explore the current science and some practical ideas on how to approach the topic.

What Is Alcohol Anyway?

When people talk about drinking “alcohol,” they’re almost always referring to the consumption of ethanol. Ethanol is a natural product that is formed from the fermentation of grains, fruits, and other sources of sugar. It’s found in a wide range of alcoholic beverages including beer, wine, and spirits like vodka, whiskey, rum, and gin.

Evidence for human consumption of alcohol dates back over 10,000 years. Consumption of alcohol has and continues to serve major roles in religious and cultural ceremonies around the world. But unlike most food products, in the last century, alcohol has been wrapped up in nearly perpetual controversy over its moral effects and health implications.

How Does Alcohol Impact the Brain?

As anyone who’s consumed alcohol knows, ethanol can directly influence brain function. Ethanol is classified as a “depressant” because it has a generally slowing effect on brain activity through activation of γ-aminobutyric acid (GABA) pathways.

In an acute sense, consumption of alcohol can lead to uninhibited behavior, sedation, lapses in judgment, and impairments in motor function. At higher levels, the effects can progress to coma and even death.

The Known Brain-Damaging Effects of Excess Alcohol

There is no debate here: Excessively high levels of alcohol consumption over short periods of time are toxic and potentially deadly, specifically because of its effects on the brain.

One critical fact to understand about the overall and brain-specific effects of alcohol is that the entirety of the debate around the risk/benefit ratio concerns mild to moderate alcohol consumption. As it relates to the effects of high amounts of alcohol on the body and brain, the research is consistent: It’s a very bad choice.

High amounts of alcohol use are causal risk factors in the development of disease in the heart, liver, pancreas, and brain (including the brains of children in utero). In fact, 1 in 8 deaths in Americans aged 20-64 is attributable to alcohol use. When it comes to adults, excessive alcohol use can cause multiple well-defined brain issues ranging from short-term confusion to dementia .

What Is “Excessive” or “High” Alcohol Use?

Key to the nuance in the conversation about alcohol use are definitions. Across the board, “excessive” or “high” alcohol use is linked to worse overall and brain health outcomes. So what does that mean?

While definitions can be variable, one way to look at this is the consumption of 4 or more drinks on an occasion (for women) and 5 or more for men. Additionally, excess alcohol is defined as drinking more than 8 drinks a week (women) and 15 a week (men), or consuming alcohol if you are pregnant or younger than age 21.

Beyond this, by definition, consuming enough alcohol to cause a “brownout,” “blackout,” hangover, or other overt brain symptomatology is evidence that the alcohol you’ve consumed is creating problems in your brain. Alcohol use disorder (or alcoholism ) is also a clear issue for the brain. It has been linked to a higher risk for dementia, especially early-onset dementia in a study of 262,000 adults, as well as to smaller brain size .

Is There a “Safe” Amount of Alcohol for the Brain?

In a highly publicized article from Nature Communications , researchers looked at brain imaging data from nearly 37,000 middle-aged to older adults and cross-referenced their brain scans with their reported alcohol consumption. The findings were profound: People who drank more alcohol had smaller brains, even in people drinking only one or two alcoholic beverages a day.

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Conversely, other recent data suggest a lower risk for dementia in people consuming a few alcoholic beverages a day. This includes a 2022 study showing that in around 27,000 people, consuming up to 40 grams of alcohol (around 2.5 drinks) a day was linked to a lower risk for dementia versus abstinence in adults over age 60. A much larger study of almost 4 million people in Korea noted that mild to moderate alcohol consumption was linked to a lower risk for dementia compared to non-drinking.

How Do We Make Sense of This Data?

When it comes to the bottom line as it relates to alcohol consumption and brain health, the data are rather solid on some fronts, and a bit less so on others. There’s also the potential for confounding variables, including the fact that many people like to drink alcohol to enjoy and enhance social bonds (which we know are beneficial for the brain). Here’s a summary of what the most recent research is telling us.

  • Experiencing transient memory loss, “blackouts,” or hangovers related to alcohol consumption is overt evidence of threats to brain health.
  • The impact of mild to moderate alcohol consumption (1-3 drinks a day) on brain function is less clear, but it seems unreasonable to start alcohol use for brain health.

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Volume 44 Issue 1 14 March 2024

Sleep-Related Predictors of Risk for Alcohol Use and Related Problems in Adolescents and Young Adults

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Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania

PURPOSE: Growing evidence supports sleep and circadian rhythms as influencing alcohol use and the course of alcohol use disorder (AUD). Studying sleep/circadian–alcohol associations during adolescence and young adulthood may be valuable for identifying sleep/circadian-related approaches to preventing and/or treating AUD. This paper reviews current evidence for prospective associations between sleep/circadian factors and alcohol involvement during adolescence and young adulthood with an emphasis on the effects of sleep/circadian factors on alcohol use.

SEARCH METHODS: The authors conducted a literature search in PsycInfo, PubMed, and Web of Science using the search terms "sleep" and "alcohol" paired with "adolescent" or "adolescence" or "young adult" or "emerging adult," focusing on the title/abstract fields, and restricting to English-language articles. Next, the search was narrowed to articles with a prospective/longitudinal or experimental design, a sleep-related measure as a predictor, an alcohol-related measure as an outcome, and confirming a primarily adolescent and/or young adult sample. This step was completed by a joint review of candidate article abstracts by two of the authors.

SEARCH RESULTS: The initial search resulted in 720 articles. After review of the abstracts, the list was narrowed to 27 articles reporting on observational longitudinal studies and three articles reporting on intervention trials. Noted for potential inclusion were 35 additional articles that reported on studies with alcohol-related predictors and sleep-related outcomes, and/or reported on candidate moderators or mediators of sleep–alcohol associations. Additional articles were identified via review of relevant article reference lists and prior exposure based on the authors' previous work in this area.

DISCUSSION AND CONCLUSIONS: Overall, the review supports a range of sleep/circadian characteristics during adolescence and young adulthood predicting the development of alcohol use and/or alcohol-related problems. Although sleep treatment studies in adolescents and young adults engaging in regular and/or heavy drinking show that sleep can be improved in those individuals, as well as potentially reducing alcohol craving and alcohol-related consequences, no studies in any age group have yet demonstrated that improving sleep reduces drinking behavior. Notable limitations include relatively few longitudinal studies and only two experimental studies, insufficient consideration of different assessment timescales (e.g., day-to-day vs. years), insufficient consideration of the multidimensional nature of sleep, a paucity of objective measures of sleep and circadian rhythms, and insufficient consideration of how demographic variables may influence sleep/circadian–alcohol associations. Examining such moderators, particularly those related to minoritized identities, as well as further investigation of putative mechanistic pathways linking sleep/circadian characteristics to alcohol outcomes, are important next steps.

Introduction

Abundant cross-sectional data indicate that alcohol use and related problems are accompanied by disruptions to sleep and circadian rhythms. 1 Alcohol's negative impacts on sleep are well established, especially in adults, and a smaller body of literature also reports alcohol's disruption of circadian rhythms. 2-4 Growing evidence supports sleep and circadian factors as influencing alcohol use and related problems, including as risk factors for the initial development of use and problems, as predictors for relapse in individuals with alcohol use disorder (AUD), and as targets for intervention. 2,5-7 Given the marked changes in sleep and circadian rhythms that occur throughout adolescence into young adulthood, 5 paralleling the time frame when initial alcohol use and development of alcohol-related problems are most likely to occur, 8 there may be particular value to studying the association between sleep/circadian rhythms and alcohol during this developmental stage.

Sleep and Circadian Changes in Adolescence and Beyond

As a result of living on a rotating planet with alternating light and dark periods, humans and most other living organisms have evolved to experience internal biological rhythms lasting approximately 24 hours. 9 These circadian rhythms modulate the timing of many, if not most, physiological, behavioral, and psychological processes, including the sleep-wake cycle, with the goal of optimizing temporal relationships with the environment and with one another. Notably, the timing of circadian rhythms is not static but shows developmental changes. Starting with the onset of puberty, the timing of sleep and circadian rhythms shifts later throughout adolescence, peaking around age 20 before reversing course and slowly shifting earlier over the rest of the life span. 10,11 The changes in sleep timing are driven by both biological and sociocultural factors and thus can vary based cross-nationally 12 and on sociodemographic characteristics. 11,13 Biological factors include the changes in circadian rhythms as well as changes in homeostatic sleep propensity, which accumulates more slowly during adolescence. 14 Exposure to blue light (e.g., via electronic devices) in the evening can exacerbate these tendencies toward later sleep and circadian timing. 15,16

Although the need for sleep remains relatively stable during this period—with recommendations for 8 to 10 hours/night in youth ages 13 to 17 and for 7 to 9 hours/night in people age 18 and older—actual sleep duration tends to decrease, especially on school/work nights. 14,17 This reduction in sleep duration is driven in part by a mismatch between the tendency for later sleep/circadian timing and relatively early school schedules, particularly during middle school and high school. This mismatch, termed circadian misalignment or social jet lag, not only results in insufficient sleep duration, but also can contribute to difficulty falling asleep on school nights, daytime sleepiness on school days, and large swings in sleep timing and duration on weekdays versus weekends. 14 Such swings tend to manifest as later sleep timing and shorter sleep duration, especially for those with later circadian timing. 18 Although the effects of early school start times are most systematic during secondary education, circadian misalignment and the associated constellation of sleep problems can persist well after high school. Regardless of etiology, insomnia, insufficient sleep, and social jet lag remain prevalent in the years after high school graduation into people's twenties, 18-20 although prevalence varies based on sociodemographic characteristics. 21

Sleep is multifactorial, and as illustrated above, different facets of sleep are interrelated in complex ways. 22,23 Circadian misalignment and social jet lag are often accompanied by a constellation of sleep-related problems and thus cannot be adequately captured by only assessing sleep quality, sleep duration, or sleep timing, especially if not distinguishing between school days or workdays and free days.

Alcohol Trajectories in Adolescence and Beyond

The developmental span from adolescence to young adulthood is a time of increasing alcohol use and related problems. 8 Alcohol use then tends to decline in early adulthood as individuals begin to "mature out" due to increases in adult responsibilities. 24 Further, both earlier initiation of alcohol use and more rapid progression from initiation to intoxication have been found to predict problematic alcohol use later on. 25-27 Multiple explanatory mechanisms are thought to underlie the onset and progression of risky alcohol use in adolescence through early adulthood. In particular, heightened sensation seeking and impulsivity have been consistently identified as potential risk factors for problematic alcohol use 28-33 and are related to sleep and circadian factors. 34,35

Overview of Alcohol's Effects on Sleep

The effects of alcohol on sleep and, to a lesser extent, circadian rhythms in adult samples have been thoroughly and recently reviewed, 2-4 so are only briefly discussed here. Given the bidirectional relationships between sleep and alcohol use, a brief summary of the evidence for alcohol's effects on sleep and circadian rhythms is warranted as it provides important context in interpreting observational data where it is impossible to fully parse these bidirectional effects.

Alcohol administration studies in adults have assessed alcohol's acute effects on sleep via polysomnography, which measures brain activity (electroencephalography [EEG]), eye movements, muscle activity, and cardiac activity. These studies found that during the first half of the night, alcohol tends to shorten the time it takes to fall asleep (sleep onset latency [SOL]), reduce nighttime wakefulness (i.e., decrease wake after sleep onset [WASO]), decrease rapid eye movement (REM) sleep, and increase the deepest of the non-REM sleep stages (i.e., slow-wave sleep). 2 (See Box: Glossary of Sleep-related Terms for more detailed definitions.) However, during the second half of the night, alcohol tends to acutely increase WASO and reduce sleep efficiency (the percentage of time spent asleep relative to the time spent attempting to sleep), while leading to a rebound in REM sleep. 2 Overall, polysomnography studies suggest that adults spend more time awake on nights after consuming alcohol. 2 Some sex differences in the acute effects of alcohol have been noted, as described below.

Glossary of Sleep-related Terms

Actigraphy: Noninvasive and objective method of measuring rest-activity patterns, and thereby estimating sleep-wake characteristics, via a wearable device containing an accelerometer. Most typically worn on the wrist.

Chronotype: Tendency toward relatively earlier or relatively later timing of the circadian clock, often as indexed by timing of the sleep-wake schedule. Conceptually overlaps with circadian preference and/or morningness-eveningness—the self-reported preference for relatively earlier (morningness) or later (eveningness) patterns of activity and sleep.

Circadian misalignment: Mismatch between the timing of the behavioral sleep-wake schedule and that of the circadian clock, most obviously observed in the context of shiftwork and jet lag.

Eveningness: Self-reported preference for relatively later timing of sleep and activity. In contrast to morningness, a self-reported preference for relatively earlier timing of sleep and activity. See chronotype.

Polysomnography: A multiparameter assessment of sleep that includes electroencephalography (EEG) to assess brain activity, electrooculography (EOG) to assess eye movements, electromyography (EMG) to assess muscle activity, and electrocardiography (ECG) to assess cardiac activity. Often respiratory airflow, respiratory effort, and pulse oximetry are also measured. Typically applied in laboratory-based settings, although streamlined polysomnography-type devices are increasingly used in home settings.

Sleep efficiency: The percentage of time spent asleep relative to the time spent attempting to sleep.

Sleep onset latency (SOL): The amount of time it takes to fall asleep.

Slow-wave sleep: The deepest of three stages of non-rapid eye movement (non-REM) sleep.

Social jet lag: A specific type of circadian misalignment in which school and/or work obligations cause a mismatch between the imposed sleep-wake schedule on school days or workdays, whereas individuals return to their desired sleep-wake schedules (relatively more aligned with their circadian clocks) on free days. More common are individuals with a late chronotype (tendency toward evening circadian preference).

Wake after sleep onset (WASO): The amount of time spent awake during nighttime awakenings that occur after initially falling asleep.

Acute alcohol effects in adolescents have been much less studied, but findings suggest some distinctions from the effects observed in adults. In a study with 24 participants ages 18 to 21 (12 women) with a mean breath alcohol content of 0.084% at lights out, alcohol's effects were broadly similar but with less evidence of benefits for sleep. Specifically, adolescents did not exhibit the decrease in SOL or the REM rebound, 36 and although alcohol appeared to increase delta power (EEG activity in the 1–4 Hz range; typically highest during slow-wave sleep) during the first few sleep cycles, it simultaneously increased alpha power (EEG activity in the 8–13 Hz range; associated with quiet wakefulness) in frontal regions. 37 This alpha-delta pattern in response to alcohol has been observed in some but not all prior studies 38,39 and is thought to reflect disrupted sleep. No sex differences were reported.

As reviewed by Koob and Colrain, 2 alcohol's effects on sleep—when alcohol use is more chronic and/or when people who chronically use alcohol (i.e., patients with AUD) abstain from drinking—can diverge from the acute effects of alcohol in complex ways too nuanced to adequately review here. Generally, chronic alcohol use is associated with worse sleep (e.g., more insomnia, longer SOL and WASO), although sleep may intermittently improve on drinking nights; similarly, abstinence is typically associated with initial worsening of sleep with some incremental improvement over time. 2 Various sleep abnormalities persist in individuals with AUD, even with long-term abstinence (> 30 days). A recent meta-analysis of cohort studies in broader samples underscores the general conclusion that chronic alcohol use does not improve sleep overall, and likely increases the likelihood of developing sleep disorders over time. 40

Although intensive longitudinal studies cannot confirm causality or directionality, analyses of day-to-day alcohol–sleep associations in young adults suggested that drinking on a given day was associated with later sleep timing that night. 41,42 Interestingly, such analyses offered mixed evidence for whether drinking worsened 43 or improved 42 sleep. Additionally, some studies in young adults have shown that cannabis use may mitigate alcohol's effects on sleep, 43,44 although these studies require replication, and the relevant mechanisms remain unknown.

Alcohol's effects on sleep also depend on the timing of alcohol consumption; for example, a study in middle-aged men administered alcohol 6 hours before bedtime found no benefit for SOL. 45 This likely was due to a combination of the temporal dynamics of the biphasic response to alcohol and circadian variation in the response to alcohol. While the literature on alcohol effects on circadian rhythms is more limited, particularly in humans, 3,4 studies have suggested disruption of melatonin and core body temperature rhythms. Multiple animal studies have indicated that acute and chronic alcohol use disrupted the circadian system's response to light, which is the most important cue (zeitgeber, or time giver) for entraining to the 24-hour day. 46,47

Although parallel effects in humans were not supported by one study in healthy adults reporting light or regular but not heavy alcohol use, 48 more recent work suggested reduced retinal responsivity to light in a group of adults who drank heavily. Light or regular drinking has previously been defined as "consumption of one to five standard alcoholic drinks/week" and no more than three episodes of binge drinking in the past year. 49 Heavy drinking has been defined by the National Institute on Alcohol Abuse and Alcoholism as five or more drinks on any day or 15 or more drinks per week for men, or four or more drinks on any day or eight or more drinks per week for women (see https://go.nih.gov/TiogZz9 ). However, there is no standardized definition of either "light/regular drinking" or "heavy drinking" across the studies described in this article.

The present paper reviews current evidence for prospective associations between sleep/circadian factors and alcohol involvement during adolescence and young adulthood, with an emphasis on the effects of sleep/circadian factors on alcohol use and related outcomes. This focus was selected in part because identifying modifiable sleep–alcohol relationships during this developmental period offers the potential for shifting the trajectory for alcohol-related problems before they develop into chronic AUD. This article also describes and discusses potential mechanisms by which sleep may influence alcohol use and problems, as well as potential important differences in sleep–alcohol associations based on key moderators, such as assigned sex at birth; lesbian, gay bisexual, transgender, queer/questioning, intersex, and asexual (LGBTQIA+) identities; and racial and ethnic identities.

Search Methods

The initial search of the existing literature was conducted on July 18, 2022, in PsycInfo, PubMed, and Web of Science using the search terms "sleep" and "alcohol" paired with "adolescent" or "adolescence" or "young adult" or "emerging adult," in the title or abstract fields; results were restricted to English-language articles but had no restriction by date. Next, the search was narrowed by including only articles that had a prospective/longitudinal or experimental design, included a sleep-related measure as a predictor, assessed an alcohol-related measure as an outcome, and had a sample primarily composed of adolescents and/or young adults. Based on these search terms, the resulting ages of participants in the articles ranged from ages 12 to 30. Table 1 offers information on age ranges in specific studies. Two of the authors completed this step by conducting a joint review of candidate article abstracts.

Results of the Literature Search

The initial search resulted in 720 articles (174 in PsycInfo, 305 in PubMed, and 241 in Web of Science). After review of the abstracts to identify articles that met all the key search criteria, the list was narrowed to 27 articles reporting on observational longitudinal studies and three articles reporting on experimental studies (specifically, two intervention trials). Noted for potential inclusion were 35 additional articles that reported on studies with alcohol-related predictors and sleep-related outcomes, and/or reported on candidate moderators or mediators of sleep–alcohol associations. An additional 104 articles cited here were identified via a variety of methods, including review of relevant article reference lists and prior exposure based on the authors' previous work in this area. Finally, while this review focused on sleep/circadian–alcohol associations in human studies, a few select findings from three animal studies 46,47,50 were included when they appeared particularly complementary to the human findings and/or helped speak to a gap in the human literature.

Results of the Reviewed Studies

Longitudinal sleep and alcohol studies.

Overall, the existing literature—based on 27 articles, including three intensive longitudinal studies—provides consistent evidence that a range of sleep/circadian factors during adolescence predicts later alcohol involvement. These included difficulties with falling or staying asleep, lower overall sleep quality, shorter sleep duration, daytime sleepiness, later sleep timing and/or chronotype (i.e., tendency for relatively earlier or later sleep-wake timing), and variable sleep timing and/or social jet lag (see Box: Glossary of Sleep-related Terms ). Alcohol-related outcomes assessed included metrics of both quantity and frequency of use, binge or heavy drinking episodes, alcohol intoxication, alcohol-related consequences/problems, AUD symptoms, and alcohol craving. Table 1 provides a summary of the longitudinal studies, including sample composition, study design, and timescale; which multidimensional sleep variables were predictive of alcohol outcomes; and whether differences across assigned sex, gender identity, and racial/ethnic identity were assessed.

*Age was rounded to 1 decimal place; demographic (sex/gender and race/ethnicity) percentages were rounded to whole numbers. No studies clarified whether assigned sex at birth or gender identity was assessed and reported. Therefore, the language (e.g., sex vs. gender) in the original article was retained. When possible, race/ethnicity terms were standardized to be consistent with National Institutes of Health categories. In some cases, the published papers did not specify the racial/ethnic identities beyond "White" and "non-White" (or "Caucasian" and "non-Caucasian," for which "White" and "non-White" were substituted).

†Sleep variables based on insomnia symptoms without numerical data to calculate efficiency were categorized under "Satisfaction."

Note: ADD Health, National Longitudinal Study of Adolescent to Adult Health; AUD, alcohol use disorder; ECHO, Etiology of Childhood Obesity studies; IDEA, Identifying the Determinants of Eating and Activity; M , mean; MLS, Michigan Longitudinal Study; NCANDA, National Consortium on Alcohol and Neurodevelopment in Adolescence; SD , standard deviation; SUD, substance use disorder.

A majority of the articles 5,6,51-63 also reported on other substance outcomes, particularly use of nicotine/tobacco and cannabis/marijuana, with findings suggesting that sleep-related risk for substance use may not be specific to alcohol. Indeed, the overall literature suggests a transdiagnostic scenario where multiple aspects of sleep/circadian disturbance (e.g., insomnia, sleep loss, delayed phase) increase the risk for alcohol and other substance use disorders as well as for other psychiatric disorders. 64

Although this review focuses primarily on the period of adolescence through young adulthood, two papers based on the Michigan Longitudinal Study 61,62 and one paper based on a study in Hong Kong 65 reported that childhood sleep problems predicted later substance use, indicating that relationships between sleep and substance use are not specific to adolescents. Notably, childhood sleep tends to predict adolescent sleep, 62,65 which could partially explain the association with adolescent substance use, but also suggests the potential value of starting early with sleep-focused prevention and/or intervention efforts. Indeed, one study reported prospective sleep–substance use associations entirely within the fourth through sixth grades, and implicated inhibitory control as a potential mediator. 66 Although that study's findings contrasted with one of the papers from the Michigan Longitudinal Study (which did not support inhibitory control as a mediator in the sleep–alcohol associations), 62 changes in mood regulation, impulsivity, and/or poor decision-making remain plausible mechanisms in the longitudinal associations between childhood sleep problems and later substance use.

Several caveats are important to consider when interpreting the existing literature. First, multiple articles relied on the same longitudinal datasets; thus, 14 out of 27 longitudinal papers were based on six studies. Second, earlier studies tended to focus on only one or two sleep characteristics and were thus unable to treat sleep as a multidimensional construct. Third, papers based on more recent studies, seemingly designed to specifically consider sleep, were more likely to employ a multidimensional sleep framework. 5,6,41,53,67-69 Fourth, except for two intensive longitudinal studies 41,42 that used actigraphy—a wearable device containing an accelerometer to measure rest-activity patterns—most studies relied on self-reported sleep and are subject to the relevant biases. For example, beyond typical retrospective biases associated with self-report, there are also longstanding observations of subjective-objective discrepancies in sleep, particularly in individuals with insomnia disorder. 70 Also, none of the studies included objective circadian predictors (e.g., dim light melatonin onset) despite cross-sectional evidence that circadian timing is related to alcohol outcomes. 49,71 Fifth, observational designs cannot assess causation and directionality and therefore must be interpreted with caution. Relatedly, one recent co-twin study indicated that sleep-related risk for alcohol misuse exists over and above genetic and environmental factors. 72 However, other emerging research using genetic methods has yielded more mixed results whether the relationships between sleep/circadian characteristics and substance use should be attributed to shared genetic variance or pleiotropy 73-75 or suggests a causal relationship from sleep to substance misuse. 76

Some of the included studies tested putative mediators of the sleep–alcohol relationship, such as behavioral inhibition, attention problems, and internalizing/externalizing symptoms; however, the results have been inconsistent (see below for further discussion). Furthermore, given that a tendency toward relatively late timing of the sleep-wake schedule (i.e., a later chronotype) is often associated with worse sleep among adolescents and young adults, 77 sleep characteristics are a putative mediator of the association between chronotype and alcohol-related risk. However, existing studies often have not supported this for alcohol 78 or other outcomes such as depression. 79,80 One study in late adolescents and young adult veterans reported that insomnia severity statistically mediated the association between depression or symptoms of post-traumatic stress disorder and alcohol use and related consequences. 81

The time frame of assessment varied substantively across the studies, with intensive longitudinal designs narrowing the focus to day-to-day relationships whereas the more traditional longitudinal studies ranged from months to multiple years between assessments. These varying time frames are important when considering that distinct mechanistic pathways may be operating within different timescales. For example, studies with annual or multiannual time points may be speaking more to the cumulative effects of sleep/circadian characteristics, although few studies have directly tested this. 65 Interestingly, the intensive longitudinal designs (e.g., ecological momentary assessment [EMA]) appear more likely to find more nuanced associations between sleep and alcohol. For example, some EMA evidence from young adult samples suggests that better sleep efficiency 42 or quality 41 on a given night predicts more alcohol use the following day, although those findings emerged from samples with participants with sleep problems who consume alcohol. EMA findings from a much wider age range (ages 20 to 73) suggest that age may moderate sleep–alcohol associations; the younger group (age < 49) showed associations between worse sleep quality and more subsequent alcohol use whereas the older group (age > 50) drank more following nights of better sleep quality. 82

The complex findings in EMA studies speak to the relevance of considering the multidimensional nature of sleep. In one study of undergraduate students who consumed alcohol (mean age = 20.5 years), shorter sleep and earlier wake times (based on actigraphy) and better sleep quality (based on self-report) all predicted more alcohol use the next day. 41 In the combined model that included all the sleep predictors simultaneously, only waking earlier and better perceived sleep quality upon waking predicted more alcohol use. One interpretation of this is that shortened sleep led to deeper, more consolidated sleep, perceived in turn as higher quality, although it remains possible that shorter sleep may have impacted other intervening mechanisms (e.g., impaired cognitive control). Alternatively, as the authors suggested, late adolescents and young adults may be more likely to socialize and drink when feeling refreshed, especially given that drinking among adolescents and young adults primarily occurs in social contexts. 83 Collectively, these findings suggest the value of considering multidimensional sleep relationships with alcohol using designs that allow consideration of both short-term (i.e., day-to-day) and longer-term (i.e., months-to-years) timescales, such as embedding an EMA burst design within a longitudinal study, as done by Graupensperger and colleagues. 51 Relatedly, such designs allow parsing of between-person and within-person effects, which may well reveal distinct sleep–alcohol associations at the between-person and within-person levels.

In summary, the published longitudinal data indicate that multiple sleep and/or circadian characteristics prospectively predict alcohol-related outcomes during adolescence through young adulthood. However, the current literature is limited by overreliance on a relatively small number of longitudinal studies, largely relying on self-report measures, and insufficient consideration of the multidimensional nature of sleep. Important next steps include, but are not limited to, consideration of different timescales, including within the same study design, and examination of key mediators and moderators of sleep–alcohol associations.

Experimental Sleep and Alcohol Studies

At present, experimental evidence of causal effects of sleep on alcohol-related outcomes is based solely on insomnia treatment studies in individuals with heavy alcohol use and/or AUD, most of which are from samples older than adolescents or young adults. A systematic review and meta-analysis of nine studies of primarily middle-aged adults 7 concluded that insomnia treatment, particularly behavioral treatment, improved sleep quality and reduced depression in individuals with AUD. The authors found no definitive benefit of insomnia treatment for reducing alcohol use, although the relapse rates in two trials of cognitive-behavioral therapy for insomnia (CBT-I) were considerably lower (11% and 15%) than might be expected for adults in AUD treatment. 84 Caution is warranted in drawing strong conclusions about the potential impact on alcohol-related outcomes based on these studies, however, as the review also noted limitations related to small samples, relatively short follow-up periods, and not focusing on participants who were concurrently engaged in AUD treatment. These limitations reflect the fact that the studies generally were designed to focus on sleep outcomes rather than alcohol outcomes. Moreover, these studies varied in whether the patients were seeking or engaged in AUD treatment, and whether they were required to be abstinent at study start.

The limited published data from two sleep treatment studies in late adolescents and emerging adults are broadly consistent with the prior literature in adults, suggesting that sleep disturbance in the context of heavy alcohol use is amenable to nonpharmacological interventions; however, it remains unclear whether improving sleep measurably reduces alcohol involvement. A novel web-based intervention including both sleep and alcohol content improved sleep quality and sleep-related impairment in heavy-drinking college students, 85 although it did not outperform a control condition (psychoeducation about sleep hygiene) and did not significantly improve actigraphy-based sleep outcomes. Interestingly, although alcohol use through a 3-month follow-up declined in both conditions, reductions were larger in the control condition. The results suggested that greater reductions in sleep-related impairment may predict greater reductions in drinking (medium-to-large effect size), but those findings were not statistically significant.

Related work by Fucito and colleagues suggested that heavy-drinking college students were more receptive to sleep-focused interventions (even if they included content related to drinking) than to purely alcohol-focused interventions. 86 This may be due to less stigma associated with sleep treatment. Aside from direct effects of sleep treatment on alcohol outcomes, this could mean that sleep treatment may provide a "foot in the door" for individuals with sleep and alcohol problems. Accordingly, Fucito and colleagues are currently conducting a sleep intervention trial that focuses on sleep hygiene in young adults ages 18 to 25 who drink heavily. 87

A more recent study tested the efficacy of CBT-I in 56 young adults ages 18 to 30 who reported monthly binge drinking and met criteria for insomnia disorder. 88,89 The study differed from prior CBT-I and alcohol studies in the sample age and that participants were still actively drinking at the start of CBT-I. The only alcohol-related treatment component was the standard sleep hygiene recommendation to reduce alcohol use before bedtime. With regard to sleep outcomes, CBT-I reduced self-reported insomnia severity relatively better than the sleep hygiene control condition, although neither treatment significantly improved actigraphy-based sleep efficiency. 88,89 Although drinking quantity and drinking-related consequences both decreased over time, these outcomes were not differentially better during CBT-I. 88 However, although insomnia improvements were not related to changes in drinking, they did mediate the reduction in alcohol-related consequences in the CBT-I group. A secondary analysis reported greater (albeit modest) reductions in alcohol craving for the CBT-I group than for the control group that, again, were statistically mediated by improvements in insomnia. 89 However, those reductions in alcohol craving were not sustained at the 1-month follow-up assessment.

In summary, the existing experimental literature on sleep predictors of alcohol outcomes during adolescence and young adulthood is confined to a handful of trials testing nonpharmacological sleep interventions in individuals reporting heavy drinking and/or AUD. Consistent with the parallel literature in adult samples, such interventions appear beneficial for sleep-related outcomes but with no clear impact on alcohol-related outcomes. However, a preliminary finding of CBT-I reducing alcohol craving is worth further investigation, as is the further development of sleep-focused treatments, perhaps including more consideration of circadian factors.

Potential Mediators and Moderators

Prior reviews have examined plausible mechanisms linking sleep/circadian disturbances to alcohol use and alcohol-related problems, with a particular emphasis on reward function. 90-92 A recent review by the authors 91 proposed a broader conceptual model that considered both positive and negative reinforcement pathways, and noted that elevated impulsivity may exacerbate either pathway. While this model may have heuristic value, it is not without limitations. These include not explicitly addressing bidirectional effects (i.e., alcohol effects on sleep/circadian function) or incorporating plausible factors that influence which pathway is most salient for a particular individual or at a given time. Further, research on sleep–alcohol associations has largely been conducted with samples of predominantly White-identifying individuals and has largely not explored possible differences in associations between sleep and alcohol across assigned sex, racial and ethnic identities, and for LGBTQIA+ individuals. The following sections offer some preliminary evidence of the importance of including diverse samples in future investigations and of examining differences in associations to ensure generalizability of future treatments and to inform culturally responsive interventions for both sleep/circadian disturbances and AUD.

Mechanisms related to positive reinforcement

Extensive cross-sectional, longitudinal, and experimental evidence from both human and preclinical studies has supported the influence of sleep/circadian factors on reward-related processes and underlying physiology 92 and, in turn, the relevance of reward-related processes to risk for alcohol use and related problems. 28,93,94

Although relevant human experimental studies probing sleep/circadian effects on reward-related processes have been more scarce than animal models, experimental sleep deprivation protocols have demonstrated causal effects on reward-related brain function in healthy adolescent and young adult samples. 95-97 For example, experimentally imposed circadian misalignment reduced the neural response to monetary reward and during response inhibition in healthy adolescents without regular substance use. 98 The analyses included objective measures of sleep duration and alertness, thus suggesting circadian effects on reward function beyond those of insufficient sleep. However, these studies have focused on non-alcohol rewards. In contrast to emerging animal research suggesting circadian misalignment during adolescence alters reward circuitry function and increases alcohol use during adulthood, 50 almost no published human studies have examined sleep/circadian effects on alcohol cue reactivity and/or its neural correlates. Furthermore, few existing studies have combined sleep/circadian effects, reward, and alcohol outcomes, although one cross-sectional analysis found that "eveningness"—the self-reported preference for relatively later timing of sleep and activity—was associated with altered neural processing of reward, which in turn is associated with greater alcohol use and AUD symptoms. 99 A longitudinal analysis in the same study found that the prospective association between eveningness and AUD symptoms was statistically mediated by the medial prefrontal cortex response to monetary reward. 52 Most recently, a study reported that an objective measure of circadian misalignment (measured on a Thursday) prospectively predicted a lower neural response to monetary reward (measured on a Friday) in late adolescents with regular alcohol use. 100 However, the reduced neural response to reward did not prospectively predict alcohol use that weekend, but rather was associated with more binge drinking episodes at baseline. Finally, in the aforementioned CBT-I trial in adolescents and young adults reporting heavy alcohol use and insomnia, the investigators found evidence of relatively larger reductions in delay discounting (large rewards only) in the CBT-I group, although this was not mediated by insomnia severity. However, there was no apparent effect on negative affect, suggesting that improved sleep may have relatively greater effects on reward-related processes. 89

Some evidence suggests sleep/circadian modulation of the stimulating effects of alcohol (e.g., increases in energy and excitement). This may be particularly relevant during adolescence, when alcohol may be relatively more stimulating and less sedating than in adulthood. 101-103 Notably, a relatively more stimulating response to alcohol is a risk factor for AUD. Thus, adolescents at high risk for AUD endorsed greater alcohol-induced stimulation and stronger wanting for alcohol compared to adolescents at low risk for AUD. 104 Moreover, young adults reporting greater stimulation after alcohol administration were more likely to have developed AUD by 10-year follow-up. 105 In laboratory-based sleep studies in late adolescents and emerging adults, acute alcohol administration did not reduce SOL, 36 especially when consumed in the evening, 106 suggesting the stimulating rather than sedating effects also may be influenced by time of administration. Furthermore, later sleep timing was associated with greater self-reported stimulation response following alcohol administration in the laboratory (at least in White male participants). 107

Lastly, sleep/circadian factors may be relevant to positive reinforcement-related alcohol cognitions. Adolescents and young adults tend to report more motives attributed to improving their social experiences and enhancing enjoyment versus motives related to attenuating negative affect (i.e., coping). 108 Given that eveningness is associated with increased alcohol motives across the board, 109 including enhancement and social motives, it is possible that the tendency toward later sleep/circadian timing in this age group contributes to reasons for using alcohol.

Mechanisms related to negative reinforcement

Adverse life events and stress levels disrupt sleep and prospectively predict AUD outcomes, both on a longitudinal basis during adolescence into adulthood, 110,111 and more proximally (day to day). 112,113 Furthermore, demonstrating sleep- or drinking-related reactivity to stress heralds the risk for sleep- 114 or alcohol-related problems 115 in the future.

Several lines of evidence indicate that sleep problems, perhaps driven by stress and/or anxiety, may lead to using alcohol as a coping method, thus implicating negative reinforcement pathways. Studies suggest that about 10% (range 6% to 16%) of adolescents and young adults report using alcohol as a sleep aid, with higher rates in individuals with heavier alcohol use and/or worse sleep. 116-118 Interestingly, one longitudinal study of adolescents with and without AUD found that their use of alcohol as a sleep aid declined over time, dropping by half from baseline to 5-year follow-up; this may reflect adolescents' learning that alcohol's effectiveness at promoting sleep declines with regular use. 119

Compared to "good sleepers," adults with insomnia may experience relatively greater tension reduction and deeper sleep (based on slow-wave sleep) in response to alcohol, underscoring why they might initially turn to alcohol as a sleep aid. Although experimental evidence suggests they rapidly develop tolerance to these effects, these individuals often persist in choosing alcohol as a sleep aid. 120,121 Similarly, young adults with insomnia who regularly use alcohol reported better sleep efficiency on drinking days, seemingly due to shorter SOL, in a recent EMA study, 42 and reported sleeping worse on nights when they avoided alcohol in the 2 hours before bed. 122 In contrast with the experimental study, 120 the association with better sleep efficiency remained even after accounting for number of consecutive drinking days. 42 Notably, these associations were not observed for actigraphy-based sleep efficiency.

Sleep also may modulate effects of stress on alcohol use. Along with associations with drinking motives in general (see above), eveningness in college students was associated with worse coping with stress, which in turn may predict drinking to cope. 109 Another study found that late chronotypes had both more adverse childhood experiences and greater alcohol use during young adulthood. 123

Craving-related mechanisms

Craving—a criterion for diagnosis of AUD and widely studied as a proximal predictor of alcohol use—is a complex construct, with apparent contributions of both positive- and negative-reinforcement processes. 124 Recent studies have offered preliminary evidence that alcohol craving is influenced by sleep/circadian factors. Two studies reported the presence of a 24-hour rhythm in alcohol craving, 125,126 suggesting modulation by circadian rhythms, although the studies were mixed in whether sleep characteristics predicted the timing or amplitude of the craving rhythm. Lower sleep quality was associated with elevated tonic (i.e., long-term) craving as determined using the Obsessive-Compulsive Drinking Scale, but not with cue-induced craving (as measured using the Alcohol Urge Questionnaire) during a cue reactivity paradigm in patients with AUD. 127 Finally, less sleep predicted more alcohol craving the next day in an EMA study, 51 and reductions in insomnia severity mediated reductions in alcohol craving in a CBT-I trial. 89

Relatedly, growing evidence implicates a role for the orexin/hypocretin system in sleep-alcohol associations via both negative reinforcement and reward-related processes. Orexin/hypocretin regulates wakefulness, reward seeking, and other motivated behavior, including alcohol craving and alcohol seeking; in turn, the orexin/hypocretin system is modulated by acute and chronic stress. 128,129 Ongoing trials are testing whether suvorexant, a dual orexin receptor antagonist, can reduce both alcohol craving and insomnia symptoms. 130,131

Impulsivity-related mechanisms

Similar to craving, the multifaceted construct of "impulsivity" may be relevant to both positive and negative reinforcement pathways in understanding sleep/circadian-related risk for alcohol involvement. In general, facets of impulsivity are considered a key risk factor for the development of heavy alcohol use and related problems. 29,32 Importantly, impulsivity facets may differentially relate to alcohol use through both positive and negative reinforcement pathways. For example, negative urgency, or acting rashly in response to strong negative mood, may reflect drinking to cope with negative mood/stress whereas positive urgency may reflect expecting alcohol to increase arousal. 132

Multiple sleep/circadian characteristics have been linked to impulsivity domains (e.g., Kang et al. 34,35 ). For example, recent prospective evidence in adolescents suggested that both sleep duration and insomnia were bidirectionally associated with impulse control. 133 Recent studies found that later chronotype was associated with greater impulsivity overall (e.g., Kang et al. 34 ), including greater self-reported trait- and state-level impulsivity across multiple subdimensions in White male drinkers. 134 Also, as noted above, experimentally imposed circadian misalignment reduced neural activation in the right inferior frontal gyrus during response inhibition in healthy and non–substance-using adolescents. 98

Moderation by assigned sex and gender identity

Studies found that both sleep/circadian characteristics and risk for problematic alcohol use vary by assigned sex at birth (sex); however, there has been insufficient attention to the role of sex in sleep/circadian–alcohol associations. This is important as rates of AUD among female individuals have risen 84% in the past decade, compared to a 34% increase among male individuals. 135,136 Consistent with this trend, alcohol use has risen for women but not men. 137 Prior research found that female individuals reported higher levels of disturbed sleep (e.g., insomnia), 138 while male individuals tended to report later sleeping times. 139 Recent findings suggest that sleep/circadian characteristics differentially contribute to alcohol risk for male and female individuals. Indeed, recent longitudinal studies found that male individuals in particular may be at heightened alcohol-related risk attributed to sleeplessness 138,140 and later weekday/weekend bedtime. 6 However, other studies observed stronger associations between multiple sleep characteristics (e.g., total sleep time, sleep efficiency, nighttime awakenings) and alcohol-related risks among female individuals. 5,141 Factors that may contribute to increases in alcohol use and sleep disturbance among female individuals may include heightened drinking to cope with negative affect and stress. 142-144 However, these studies did not clarify whether they were measuring assigned sex or gender identity (the term "identity" is used to reflect that race and gender are social constructs 145 and that the vast majority of research on humans asks participants to self-identify their race and gender).

Inequities in sleep 146,147 and alcohol use 148 exist for individuals with minoritized gender identities (e.g., transgender, nonbinary, gender-fluid). Importantly, a recent study examining factors that influenced sleep among individuals who identified as transgender found that one-third of the sample endorsed feelings of internalized shame (i.e., distress, anxiety, and dysphoria attributed to their identity) as reason for sleep disturbance. 149

Inequities in sleep duration 150 and alcohol use 151 also exist among individuals with minoritized sexual orientations (e.g., lesbian, gay, queer, bisexual). However, only one cross-sectional study has examined whether sleep/circadian characteristics contribute to inequities in alcohol problems and whether these associations present differently among subgroups of people with minoritized sexual orientations (e.g., bisexual women, gay men). 152 The study found that compared to heterosexual men, gay men were less likely to experience short sleep duration and reported consuming fewer alcohol drinks per day. Lesbian and bisexual women, when compared to heterosexual women, reported a greater number of alcoholic drinks per day and were more likely to use sleep medication. Further, bisexual women were more likely to experience short sleep duration and to be diagnosed with a sleep disorder compared to heterosexual women.

It is important to place these findings within a minority stress model framework, where individuals with minoritized identities are exposed to identity-based stressors 153 that occur at both interpersonal and systemic levels. 154 Identity-based stressors—defined as chronic modes of stress attributed to discrimination and internalized stigma directed at one's minoritized identity (e.g., sexual, gender, or racial identities)—are prominent predictors of health inequities, including alcohol behaviors and sleep disturbances, among individuals with minoritized sexual and gender identities. 146,155,156 However, further examination of possible differential associations between sleep indices and alcohol behaviors is needed.

Moderation by racial and ethnic identities

As a function of sociohistorical context and multiple levels of discrimination, inequities in sleep health and alcohol problems have been shown for individuals with minoritized racial and ethnic identities. 157-162 Significantly less research has examined if sleep disturbances related to discrimination contribute to the inequities in alcohol problems and whether the associations between sleep and alcohol differ among individuals with different racial or ethnic identities. Structural racism affects neighborhood-level factors that impact sleep (e.g., noise pollution) and alcohol use (e.g., alcohol outlet density), and neighborhood socioeconomic indicators (i.e., income, crime rates, discrimination) have been implicated in inequities in sleep, which may contribute to downstream poor health outcomes. 163 Specifically, studies have identified that individuals with low socioeconomic status tend to inhabit urban areas, which may be more hazardous and noisier and may have higher levels of crime. Such neighborhood characteristics have been found to be associated with greater rates of chronic sleep disturbance, 164 which in turn have been linked to heightened alcohol consumption among adolescents as reviewed above (also see Edwards, Reeves, and Fishbein 165 ). As individuals with minoritized racial and ethnic identities may be more socioeconomically disadvantaged as a result of sociohistorical structural and interpersonal discrimination, these youth may be at greater risk for poor sleep quality in addition to elevated risk for alcohol use. These environmental factors may also affect associations between sleep and alcohol differently for individuals with minoritized racial or ethnic identities. All of these potential associations have direct implications for prevention and treatment.

Cross-sectional evidence suggests that alcohol use may be more disruptive to sleep for Black individuals relative to White individuals. Among men with AUD, Black men had more severe sleep disturbances compared to White men. 166 Based on National Health Interview survey data collected between 2004 and 2015, sleep duration and sleep quality were highest in Black individuals who never consumed alcohol (i.e., lifetime abstention) and worsened as alcohol use involvement increased. 167 For White individuals, this pattern was more variable. Importantly, the racial differences in this study were more pronounced for women than men, demonstrating the importance of examining intersectionality.

Research examining associations between sleep and alcohol use in minoritized racial or ethnic groups beyond Black or African American individuals is nascent. However, consistent with research with predominantly White samples, binge drinking in adolescence has been shown to relate to poorer sleep quality in young adulthood for Mexican American and American Indian (as defined in the article) individuals. 168

Studies examining how sleep may differentially affect alcohol use and experiences while drinking across racial and ethnic groups are even more sparse. Preliminary research found that later sleep timing was related to increased sensitivity to the stimulating effects of alcohol for White men but not Black men; 107 however, no differences existed in associations with 24-hour rhythms in alcohol craving for Black and White young adults. 125

Other possible moderators

Multiple other moderators of the relationship between sleep/circadian factors and alcohol use are plausible but have received little attention to date, including the role of age and/or developmental stage. An exploratory analysis of the longitudinal data from the National Consortium on Alcohol and Neurodevelopment in Adolescence study 5 found a different pattern of sleep/circadian predictors of binge alcohol severity at middle- and high-school age time points versus post–high-school age time points. This difference could reflect context, given systematic early school start times versus more flexibility in schedules after high school (i.e., college and/or employment), but more research is needed to replicate and further clarify this finding.

Sleep/circadian-related risk for alcohol outcomes also may be moderated by the stage of alcohol use and related problems, potentially varying as individuals progress through the three-stage cycle framework of AUD—binge/intoxication, negative affect/withdrawal, and preoccupation/anticipation as described by Koob and Colrain. 2 The shift from enhancement motives/positive reinforcement in the binge/intoxication phase to coping motives/negative reinforcement in the withdrawal/negative affect stage could be paralleled by a shift in relevant sleep/circadian pathways. That is, accumulating alcohol use/problems may contribute to more chronic and/or more distinct sleep/circadian disturbances, which in turn may maintain or exacerbate alcohol involvement. Additionally, sleep problems have been identified as a risk factor for relapse during early abstinence in individuals with AUD. 2

Conclusions and Future Directions

Based on the above discussion, future research on the intersection between sleep and alcohol should address existing gaps related to both research methodology and specific questions addressed. For example, future studies should employ assessment batteries able to assess multidimensional sleep/circadian characteristics and should include both self-report and objective measures, particularly objective assessments not yet sufficiently leveraged in this literature, such as the Multiple Sleep Latency Test to assess daytime sleepiness. Research also can benefit from the use of combined longitudinal and intensive longitudinal designs, such as EMA bursts within a larger longitudinal study framework, which will allow consideration of both different timescales and parsing of between-person (trait) and within-person (state) effects.

Such studies should further explore the role of relevant moderators, with particular attention to sleep–alcohol associations for individuals with minoritized identities. Equally important is consideration of the association between sleep and cannabis use, including simultaneous use with alcohol, given the high prevalence of this practice in late adolescents and young adults and evidence suggesting somewhat opposing effects of both substances on sleep. Examination of potential differences in sleep–alcohol associations across international samples could help determine how varying cultural contexts may differentially influence sleep, alcohol use, and their association.

Furthermore, experimental research is needed to demonstrate causal effects of sleep/circadian manipulations on alcohol-related risk. Additionally, experimental studies using approaches such as forced desynchrony or ultradian sleep-wake protocols could help parse the role of circadian versus sleep homeostatic contributions in modulating alcohol-related processes (e.g., alcohol craving).

Other research gaps to be addressed include the clarification of potential shared genetic variance and/or pleiotropic contributions to sleep–alcohol associations, which should further clarify trait- versus state-level effects, as well as investigation of different mechanistic pathways linking sleep to alcohol outcomes. These ideally should allow for comparison of distinct pathways within the same dataset and include not only the putative mechanisms described above (e.g., reward function, negative reinforcement, impulsivity) but also others that may well be worth consideration, such as hypothalamic-pituitary-adrenal axis function.

Finally, research gaps exist with respect to treatment of adolescents and young adults with both alcohol problems and sleep problems. Rigorous treatment studies in this population are needed that go beyond CBT-I to include attention to circadian factors, and with sufficient follow-up periods to better elucidate differential effects on alcohol.

Overall, the existing longitudinal and experimental evidence indicates that a range of sleep/circadian characteristics during adolescence and young adulthood influence risk for the development of alcohol use and/or related problems. Although studies in late adolescents and young adults engaging in regular and/or heavy drinking show that sleep treatment can improve sleep in those individuals, as well as potentially reduce alcohol craving and alcohol-related consequences, no studies in any age group have yet demonstrated that improving sleep reduces drinking behavior. Future research embedding intensive longitudinal studies within prospective research studies is needed to understand the underlying mechanistic pathways from sleep and circadian rhythm to differential alcohol use behaviors and problems as there is evidence that specific sleep indices may relate to certain AUD criteria. 169 Such studies could hold promise for informing treatment for both sleep problems and AUD.

Acknowledgments

This work was supported by the National Institutes of Health grants R01 AA025626, R01 AA025617, R01 AA026249, and T32 AA007453.

Correspondence

Address correspondence concerning this article to Brant P. Hasler, University of Pittsburgh School of Medicine, Department of Psychiatry, 3811 O'Hara Street, Pittsburgh, PA 15213; Email: [email protected]

Disclosures

The authors declare no competing financial or nonfinancial interests.

Publisher's note

Opinions expressed in contributed articles do not necessarily reflect the views of the National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health. The U.S. government does not endorse or favor any specific commercial product or commodity. Any trade or proprietary names appearing in Alcohol Research: Current Reviews are used only because they are considered essential in the context of the studies reported herein.

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Even a Little Alcohol Can Harm Your Health

Recent research makes it clear that any amount of drinking can be detrimental. Here’s why you may want to cut down on your consumption beyond Dry January.

An illustration of a collection of alcohol bottles and drinks in a coupe glass, a high ball glass and a martini glass. The background is black and the bottles and glasses appear to be melting and slightly blurred, with streaks of burgundy and warm yellow and orange tones streaming into a puddle in the foreground.

By Dana G. Smith

Sorry to be a buzz-kill, but that nightly glass or two of wine is not improving your health.

After decades of confusing and sometimes contradictory research (too much alcohol is bad for you but a little bit is good; some types of alcohol are better for you than others; just kidding, it’s all bad), the picture is becoming clearer: Even small amounts of alcohol can have health consequences.

Research published in November revealed that between 2015 and 2019, excessive alcohol use resulted in roughly 140,000 deaths per year in the United States. About 40 percent of those deaths had acute causes, like car crashes, poisonings and homicides. But the majority were caused by chronic conditions attributed to alcohol, such as liver disease, cancer and heart disease.

When experts talk about the dire health consequences linked to excessive alcohol use, people often assume that it’s directed at individuals who have an alcohol use disorder. But the health risks from drinking can come from moderate consumption as well.

“Risk starts to go up well below levels where people would think, ‘Oh, that person has an alcohol problem,’” said Dr. Tim Naimi, director of the University of Victoria’s Canadian Institute for Substance Use Research. “Alcohol is harmful to the health starting at very low levels.”

If you’re wondering whether you should cut back on your drinking, here’s what to know about when and how alcohol impacts your health.

How do I know if I’m drinking too much?

“Excessive alcohol use” technically means anything above the U.S. Dietary Guidelines ’ recommended daily limits. That’s more than two drinks a day for men and more than one drink a day for women.

There is also emerging evidence “that there are risks even within these levels, especially for certain types of cancer and some forms of cardiovascular disease,” said Marissa Esser, who leads the alcohol program at the Centers for Disease Control and Prevention.

The recommended daily limits are not meant to be averaged over a week, either. In other words, if you abstain Monday through Thursday and have two or three drinks a night on the weekend, those weekend drinks count as excessive consumption. It’s both the cumulative drinks over time and the amount of alcohol in your system on any one occasion that can cause damage.

Why is alcohol so harmful?

Scientists think that the main way alcohol causes health problems is by damaging DNA. When you drink alcohol, your body metabolizes it into acetaldehyde, a chemical that is toxic to cells. Acetaldehyde both “damages your DNA and prevents your body from repairing the damage,” Dr. Esser explained. “Once your DNA is damaged, then a cell can grow out of control and create a cancer tumor.”

Alcohol also creates oxidative stress, another form of DNA damage that can be particularly harmful to the cells that line blood vessels. Oxidative stress can lead to stiffened arteries, resulting in higher blood pressure and coronary artery disease.

“It fundamentally affects DNA, and that’s why it affects so many organ systems,” Dr. Naimi said. Over the course of a lifetime, chronic consumption “damages tissues over time.”

Isn’t alcohol supposed to be good for your heart?

Alcohol’s effect on the heart is confusing because some studies have claimed that small amounts of alcohol, particularly red wine, can be beneficial. Past research suggested that alcohol raises HDL, the “good” cholesterol, and that resveratrol, an antioxidant found in grapes (and red wine), has heart-protective properties.

However, said Mariann Piano, a professor of nursing at Vanderbilt University, “There’s been a lot of recent evidence that has really challenged the notion of any kind of what we call a cardio-protective or healthy effect of alcohol.”

The idea that a low dose of alcohol was heart healthy likely arose from the fact that people who drink small amounts tend to have other healthy habits, such as exercising, eating plenty of fruits and vegetables and not smoking. In observational studies, the heart benefits of those behaviors might have been erroneously attributed to alcohol, Dr. Piano said.

More recent research has found that even low levels of drinking slightly increase the risk of high blood pressure and heart disease, and the risk goes up dramatically for people who drink excessively. The good news is that when people stop drinking or just cut back, their blood pressure goes down . Alcohol is also linked to an abnormal heart rhythm, known as atrial fibrillation , which raises the risk of blood clots and stroke.

What types of cancer does alcohol increase the risk for?

Almost everyone knows about the link between cigarette smoking and cancer, but few people realize that alcohol is also a potent carcinogen. According to research by the American Cancer Society, alcohol contributes to more than 75,000 cases of cancer per year and nearly 19,000 cancer deaths.

Alcohol is known to be a direct cause of seven different cancers : head and neck cancers (oral cavity, pharynx and larynx), esophageal cancer, liver cancer, breast cancer and colorectal cancer. Research suggests there may be a link between alcohol and other cancers as well, including prostate and pancreatic cancer, although the evidence is less clear-cut.

For some cancers, such as liver and colorectal, the risk starts only when people drink excessively. But for breast and esophageal cancer, the risk increases, albeit slightly, with any alcohol consumption. The risks go up the more a person drinks.

“If somebody drinks less, they are at a lower risk compared to that person who is a heavy drinker,” said Dr. Farhad Islami, a senior scientific director at the American Cancer Society. “Even two drinks per day, one drink per day, may be associated with a small risk of cancer compared to non-drinkers.”

Which condition poses the greatest risk?

The most common individual cause of alcohol-related death in the United States is alcoholic liver disease, killing about 22,000 people a year . While the risk rises as people age and alcohol exposure accumulates, more than 5,000 Americans in their 20s, 30s and 40s die from alcoholic liver disease annually.

Alcoholic liver disease has three stages: alcoholic fatty liver, when fat accumulates in the organ; alcoholic hepatitis, when inflammation starts to occur; and alcoholic cirrhosis, or scarring of the tissue. The first two stages are reversible if you stop drinking entirely; the third stage is not.

Symptoms of alcoholic liver disease include nausea, vomiting, abdominal pain and jaundice — a yellow tinge to the eyes or skin. However, symptoms rarely emerge until the liver has been severely damaged.

The risk of developing alcoholic liver disease is greatest in heavy drinkers, but one report stated that five years of drinking just two alcoholic beverages a day can damage the liver. Ninety percent of people who have four drinks a day show signs of alcoholic fatty liver.

How do I gauge my personal risk for alcohol-related health issues?

Not everyone who drinks will develop these conditions. Lifestyle factors such as diet, exercise and smoking all combine to raise or lower your risk. Also, some of these conditions, such as esophageal cancer, are pretty rare, so increasing your risk slightly won’t have a huge impact.

“Every risk factor matters,” Dr. Esser said. “We know in public health that the number of risk factors that one has would go together into an increased risk for a condition.”

A pre-existing condition could also interact with alcohol to affect your health. For example, “people who have hypertension probably should not drink or definitely drink at very, very low levels ,” Dr. Piano said.

Genes play a role, too. For instance, two genetic variants, both of which are more common in people of Asian descent, affect how alcohol and acetaldehyde are metabolized. One gene variant causes alcohol to break down into acetaldehyde faster, flooding the body with the toxin. The other variant slows down acetaldehyde metabolism, meaning the chemical hangs around in the body longer, prolonging the damage.

So should I cut back — or stop drinking altogether?

You don’t need to go cold turkey to help your health. Even reducing a little bit can be beneficial, especially if you currently drink over the recommended limits. The risk “really accelerates once you’re over a couple of drinks a day,” Dr. Naimi said. “So people who are drinking five or six drinks a day, if they can cut back to three or four, they’re going to do themselves a lot of good.”

Light daily drinkers would likely benefit by cutting back a bit, too. Try going a few nights without alcohol: “If you feel better, your body is trying to tell you something,” said George Koob, director of the National Institute on Alcohol Abuse and Alcoholism.

Notably, none of the experts we spoke to called for abstaining completely, unless you have an alcohol use disorder or are pregnant. “I’m not going to advocate that people completely stop drinking,” Dr. Koob said. “We did prohibition, it didn’t work.”

Generally, though, their advice is, “Drink less, live longer,” Dr. Naimi said. “That’s basically what it boils down to.”

A More Mindful Approach to Drinking

If you consume alcohol, but are looking for a healthier approach to drinking, here are some tips..

  Consider the Dangers : Heart disease risk increases along with   our  alcohol consumption . Drinking can also lead to cancer and liver and kidney disease.

  ‘Go Dry’ for a Month: If you tend to overindulge, one month off from drinking can be an opportunity to examine your alcohol use .

 Cut Back:  You don’t need to abstain to rein in your alcohol consumption. Here are some tips to develop healthier drinking habits.

 Try Meditation: Mindfulness and strategies from cognitive behavioral therapy can also help you be more intentional about your relationship to drinking .

 Enjoy Your Drink: Learn to savor that glass of wine the way a connoisseur would — it starts with a shift in perspective  and a few best practices .

ScienceDaily

Low social status increases risk of health problems from alcohol problems

People with low income or education levels may benefit from screening for alcohol-related conditions.

Men and women with lower income or education levels are more likely to develop medical conditions related to alcohol abuse compared to similar individuals with a higher socioeconomic status. Alexis Edwards of Virginia Commonwealth University, US, and colleagues report these findings in a new study published March 19 in the open access journal PLOS Medicine .

The World Health Organization estimates that harmful alcohol use accounts for 5.1% of the global burden of disease and injury worldwide, and results in three million deaths each year. Excessive alcohol consumption can also take an economic toll. Previous studies have identified links between a person's socioeconomic status and alcohol use, but currently it is unclear how an individual's social class impacts their future risk of acquiring alcohol-related medical conditions, like alcoholic liver disease.

In the new study, researchers used a model that follows people over time to estimate their risk of developing medical conditions from alcohol abuse using two indicators for socioeconomic status: income and education level. The researchers analyzed data from more than 2.3 million individuals in a Swedish database to show that both men and women with a lower income or education level were more likely to develop these conditions. The associations held true, even when researchers controlled for other relevant factors, such as marital status, history of psychiatric illness and having a genetic predisposition to abuse alcohol.

The new findings are important for understanding which populations are most likely to suffer from medical conditions resulting from alcohol abuse, and contribute to a growing body of literature on health disparities that stem from socioeconomic factors. The researchers recommend that individuals with lower income or education levels might warrant additional screening by clinicians to evaluate their alcohol consumption and identify related conditions.

The authors add, "Among individuals with an alcohol use disorder, those with lower levels of education or lower incomes are at higher risk for developing an alcohol-related medical condition, such as cirrhosis or alcoholic cardiomyopathy. Additional screening and prevention efforts may be warranted to reduce health disparities."

  • Public Health Education
  • Diseases and Conditions
  • Chronic Illness
  • Disorders and Syndromes
  • Poverty and Learning
  • Public Health
  • STEM Education
  • Quality of life
  • Sex education

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Materials provided by PLOS . Note: Content may be edited for style and length.

Journal Reference :

  • Alexis C. Edwards, Sara Larsson Lönn, Karen G. Chartier, Séverine Lannoy, Jan Sundquist, Kenneth S. Kendler, Kristina Sundquist. Socioeconomic position indicators and risk of alcohol-related medical conditions: A national cohort study from Sweden . PLOS Medicine , 2024; 21 (3): e1004359 DOI: 10.1371/journal.pmed.1004359

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March 21, 2024

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How neural inhibition could reduce alcohol use

by The Scripps Research Institute

alcohol use

Neuroscientists at Scripps Research have found that inhibiting neurons involved in the body's stress response may reduce alcohol consumption in people who have both post-traumatic stress disorder (PTSD) and alcohol use disorder (AUD)—even if they still experience trauma-related anxiety.

The findings were published in Molecular Psychiatry in a paper titled "Chemogenetic inhibition of central amygdala CRF-expressing neurons decreases alcohol intake but not trauma-related behaviors in a rat model of post-traumatic stress and alcohol use disorder . "

These discoveries are helping untangle the complex role that stress and trauma play in neurological disorders like PTSD and AUD, while also informing the development of new treatment options for people who experience both these conditions simultaneously.

"Traumatic experiences in life can increase vulnerability to alcohol drinking and exacerbate symptoms of depression and anxiety," says senior author Marisa Roberto, Ph.D., the Schimmel Family Endowed Chair and vice chair of the Department of Molecular Medicine. "Alcohol is often used as a coping strategy to blur trauma-associated memories and diminish negative emotional states."

PTSD and AUD are often comorbid, so understanding their underlying neurological mechanisms in tandem is crucial. About 6% of the U.S. population will develop PTSD at some point, according to the U.S. Department of Veterans Affairs , and people with PTSD have a 30% lifetime prevalence of AUD . However, few pharmaceutical therapies exist to treat the disorders together.

Roberto's team previously created a model in which rats develop symptoms similar to what people with comorbid PTSD and AUD experience: aggression, anxiety, hyperarousal, disturbed sleep and increased alcohol consumption. In this new study, they compared these rats with those that did not exhibit anxiety-like behaviors by giving each group access to both alcohol and water.

Compared with unstressed rats, those that were stressed exhibited higher levels of peripheral stress hormones, and various genes in the central amygdala, including one that encodes for the neuropeptide known as corticotropin-releasing factor (CRF), were also shown to be altered in stressed rats.

CRF exists in the central amygdala, a part of the brain that's altered by excessive drinking and is responsible for processing fear. Stress causes neural release of CRF, which plays a key role in regulating physiological responses to the emotion. Prior research with rats has shown that inhibiting neurons that express CRF reduces alcohol consumption.

After identifying that the stressed rats expressed higher levels of CRF in the amygdala, the researchers then inhibited CRF-producing neurons in the stressed group. As expected, they found that this decreased alcohol consumption—but it didn't mitigate anxiety as they initially thought it would.

"We were surprised to see that the anxiety phenotypes were not reduced when silencing CRF expressing neurons in the central amygdala, suggesting other neuropeptide co-factors might be at play," says the study's first author, Bryan Cruz, Ph.D., a postdoctoral fellow at Scripps Research.

The results suggest that CRF plays a role in alcohol use among those with comorbid PTSD and AUD. Still, the researchers conclude that future studies need to disentangle the neurological mechanisms behind stress-related alcohol consumption and trauma-induced anxiety.

"Understanding the neurobiology of PTSD-AUD is key for development of future intervention strategies for this devastating comorbidity," says Roberto. "We speculate that other neuropeptides with anti-stress properties may be involved in PTSD-AUD."

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National Institute on Alcohol Abuse and Alcoholism (NIAAA)

Semaglutide shows promise as a potential alcohol use disorder medication.

Wednesday, March 13, 2024

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This article was first published in  NIAAA Spectrum   Volume 16, Issue 1.

Intramural scientists at the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and the National Institute on Drug Abuse (NIDA), and collaborators from The Scripps Research Institute, found that  semaglutide reduces alcohol consumption and binge-like drinking in a rodent model of alcohol misuse . Published in the June 2023 issue of the journal JCI Insight, the study adds to growing preclinical evidence that the glucagon-like peptide-1 (GLP-1) system plays a role in alcohol and other substance use disorders, and that GLP-1 receptor agonists show potential for treating people with alcohol use disorder (AUD).

GLP-1 is a gut hormone that stimulates insulin secretion after eating, which promotes a feeling of fullness, helps to regulate blood sugar, and reduces hunger cravings. Semaglutide and other GLP-1 agonists—medications that bind to GLP-1 receptors and mimic their effects—are currently used as treatments for diabetes and obesity.

“Parts of the brain that drive eating behaviors overlap extensively with the drive to use alcohol or other substances,” explained Lorenzo Leggio, M.D., Ph.D., and Leandro Vendruscolo, Pharm.D., Ph.D., two of the senior authors of the study. They added that there is also overlap between the brain mechanisms that regulate overeating and those that contribute to the development and maintenance of substance use disorders, including AUD. Dr. Leggio is Chief of the joint NIDA/NIAAA Clinical Psychoneuroendocrinology and Neuropsychopharmacology Section. He also serves as the NIDA Clinical Director and Deputy Scientific Director. Dr. Vendruscolo is Chief of the Stress and Addiction Neuroscience Unit, a joint laboratory of NIDA and NIAAA.

Previous rodent studies demonstrated that GLP-1 receptor agonists suppressed the rewarding effects of alcohol and reduced alcohol consumption. Dr. Leggio and his colleagues noted that, compared with other GLP-1 receptor agonists, semaglutide is more potent, has a higher affinity for its receptor, and is longer acting. Together, these characteristics make semaglutide a promising candidate for preclinical investigation and clinical translational studies in people with AUD.

In the current study, the researchers demonstrated that semaglutide reduced binge-like alcohol drinking in both male and female mice, and that the effect was dose-dependent (i.e., greater amounts of semaglutide led to greater reductions in binge alcohol intake). The researchers also tested semaglutide in rats that were made dependent on alcohol through long-term exposure to alcohol vapor. They found that semaglutide reduced alcohol intake in this animal model, again with no sex differences.

Dr. Leggio’s team concluded that “the present finding that semaglutide suppresses alcohol intake in different animal models of alcohol misuse provides compelling support for testing semaglutide in future clinical trials in people with AUD.”

Reference:  Chuong V, Farokhnia M, Khom S, Pince CL, Elvig SK, Vlkolinsky R, Marchette RC, Koob GF, Roberto M, Vendruscolo LF, Leggio L. The glucagon-like peptide-1 (GLP-1) analogue semaglutide reduces alcohol drinking and modulates central GABA neurotransmission. JCI Insight. 2023;8(12):e170671. PubMed PMID:  37192005

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Vanderbilt launches AUD Research and Education Center with prestigious $8.9 million NIH grant

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A five-year, $8.9 million grant from the National Institutes of Health will help establish the Vanderbilt AUD Research and Education Center and bolster Vanderbilt University’s leadership in neuroscience, addiction research and innovative approaches to the study of alcohol use disorder.

This grant provides support for collaborative efforts among diverse researchers at Vanderbilt and from across the country, enhancing Vanderbilt’s role in alcohol and addiction research locally and nationally.

“This milestone underscores our unwavering commitment to solving society’s most pressing problems, like understanding the complexities of the brain and addiction, epitomizing the spirit of Discovery Vanderbilt,” Provost C. Cybele Raver said. “Through interdisciplinary collaboration, we aim to drive impactful change in understanding and treating alcohol use disorder, advancing health outcomes nationwide.”

VAREC’s innovative “precision neuroscience” approach will leverage human and animal models to identify the causes of AUD and potential treatments, as well as providing public education on the disorder. This newly established center will facilitate collaboration with the Vanderbilt Center for Addiction Research, which has similar goals.

The grant’s principal investigators are Erin Calipari, director of VCAR and assistant director of VAREC, and Danny Winder, chair of the Department of Neurobiology at UMass Chan Medical School, along with Jennifer Blackford, VAREC’s associate director and director of research at the Munroe-Meyer Institute at the University of Nebraska Medical Center.

Erin Calipari

“By focusing on precise circuits within the brain that control specific aspects of alcohol-associated behavior … we can understand exactly how repeated alcohol use changes the brain,” Calipari said. “Understanding these aspects of the disorder can lead to developing more targeted treatment strategies to ease symptoms of the disorder and improve treatment outcomes in individuals who are suffering.”

Another primary objective for VAREC will be education and outreach, which will be achieved by translating complex scientific findings into accessible information for the public. The center plans to engage the community and spark interest in addiction science through podcasts, webinars and a unique near-peer mentoring program.

With its dual focus on research and dissemination, VAREC aims to not only bolster Vanderbilt’s research capabilities but also enhance its standing as a hub for scientific discovery and public education on AUD.

The center plans to establish a course and provide scholarships for researchers from across the country to learn innovative neuroscience technologies at Vanderbilt, according to Calipari. “Through this course,” she said, “we are hoping to enrich the science community and give people access to the amazing resources at Vanderbilt.”

Also in the plans is a summer student program with stipends for students from underrepresented communities to work in addiction labs on campus. “The hope,” Calipari said, “is that we can get the next generation excited about doing addiction work.”

“Addiction is a disease. Promoting a deeper understanding of addiction fosters compassion and paves the way for solutions that can bring healing and hope to those affected by it,” said John Kuriyan, dean of the School of Medicine Basic Sciences. “The Vanderbilt Center for Addiction Research is an established leader in the field of addiction research. Its mission to unravel the causes of substance use disorders and bridge the gap between research and public awareness empowers individuals, communities and health care professionals alike.”

With the launch of VAREC, the center’s leaders anticipate making great strides in AUD research, educating the public and making a tangible difference in the community. “The great thing about this project (grant) is that it’s renewable at the end of the funding period,” Calipari said. “This work will continue at Vanderbilt far into the future.”

For more information on Vanderbilt’s addiction work, visit the VCAR website .

Keep Reading

Vanderbilt Center for Addiction Research joins Discovery Vanderbilt; Calipari appointed director  

Vanderbilt Center for Addiction Research joins Discovery Vanderbilt; Calipari appointed director  

Erin Calipari receives $2M to study how alcohol use disorder develops in the brain

Erin Calipari receives $2M to study how alcohol use disorder develops in the brain

Watch now: Lab-to-Table Conversation: Beyond Addiction: Therapeutic Developments and Societal Impact

Watch now: Lab-to-Table Conversation: Beyond Addiction: Therapeutic Developments and Societal Impact

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Alcohol use: Weighing risks and benefits

Drinking alcohol is a health risk regardless of the amount.

Research on alcohol suggests a sobering conclusion: Drinking alcohol in any amount carries a health risk. While the risk is low for moderate intake, the risk goes up as the amount you drink goes up.

Many people drink alcohol as a personal preference, during social activities, or as a part of cultural and religious practices. People who choose not to drink make that choice for the same reasons. Knowing your personal risk based on your habits can help you make the best decision for you.

The evidence for moderate alcohol use in healthy adults is still being studied. But good evidence shows that drinking high amounts of alcohol are clearly linked to health problems.

Here's a closer look at alcohol and health.

Defining moderate alcohol use

Moderate alcohol use may not mean the same thing in research studies or among health agencies.

In the United States, moderate drinking for healthy adults is different for men and women. It means on days when a person does drink, women do not have more than one drink and men do not have more than two drinks.

Examples of one drink include:

  • 12 fluid ounces (355 milliliters) of regular beer
  • 5 fluid ounces (148 milliliters) of wine
  • 1.5 fluid ounces (44 milliliters) of hard liquor or distilled spirits

Health agencies outside the U.S. may define one drink differently.

The term "moderate" also may be used differently. For example, it may be used to define the risk of illness or injury based on the number of drinks a person has in a week.

Risks of moderate alcohol use

The bottom line is that alcohol is potentially addictive, can cause intoxication, and contributes to health problems and preventable deaths. If you already drink at low levels and continue to drink, risks for these issues appear to be low. But the risk is not zero.

For example, any amount of drinking increases the risk of breast cancer and colorectal cancer. As consumption goes up, the risk goes up for these cancers. It is a tiny, but real, increased risk.

Drinking also adds calories that can contribute to weight gain. And drinking raises the risk of problems in the digestive system.

In the past, moderate drinking was thought to be linked with a lower risk of dying from heart disease and possibly diabetes. After more analysis of the research, that doesn't seem to be the case. In general, a healthy diet and physical activity have much greater health benefits than alcohol and have been more extensively studied.

Risks of heavy alcohol use

Heavy drinking, including binge drinking, is a high-risk activity.

The definition of heavy drinking is based on a person's sex. For women, more than three drinks on any day or more than seven drinks a week is heavy drinking. For men, heavy drinking means more than four drinks on any day or more than 14 drinks a week.

Binge drinking is behavior that raises blood alcohol levels to 0.08%. That usually means four or more drinks within two hours for women and five or more drinks within two hours for men.

Heavy drinking can increase your risk of serious health problems, including:

  • Certain cancers, such as colorectal cancer, breast cancer and cancers of the mouth, throat, esophagus and liver.
  • Liver disease.
  • Cardiovascular disease, such as high blood pressure and stroke.

Heavy drinking also has been linked to intentional injuries, such as suicide, as well as accidental injury and death.

During pregnancy, drinking may cause the unborn baby to have brain damage and other problems. Heavy drinking also may result in alcohol withdrawal symptoms.

When to avoid alcohol

In some situations, the risk of drinking any amount of alcohol is high. Avoid all alcohol if you:

  • Are trying to get pregnant or are pregnant.
  • Take medicine that has side effects if you drink alcohol.
  • Have alcohol use disorder.
  • Have medical issues that alcohol can worsen.

In the United States, people younger than age 21 are not legally able to drink alcohol.

When taking care of children, avoid alcohol. And the same goes for driving or if you need to be alert and able to react to changing situations.

Deciding about drinking

Lots of activities affect your health. Some are riskier than others. When it comes to alcohol, if you don't drink, don't start for health reasons.

Drinking moderately if you're otherwise healthy may be a risk you're willing to take. But heavy drinking carries a much higher risk even for those without other health concerns. Be sure to ask your healthcare professional about what's right for your health and safety.

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  • Rethinking drinking: Alcohol and your health. National Institute on Alcohol Abuse and Alcoholism. https://www.rethinkingdrinking.niaaa.nih.gov/. Accessed Jan. 8, 2024.
  • 2020-2025 Dietary Guidelines for Americans. U.S. Department of Health and Human Services and U.S. Department of Agriculture. https://www.dietaryguidelines.gov. Accessed Jan. 8, 2024.
  • Scientific Report of the 2020 Dietary Guidelines Advisory Committee. Alcoholic beverages. U.S. Department of Health and Human Services and U.S. Department of Agriculture. https://www.dietaryguidelines.gov/2020-advisory-committee-report. Accessed Jan. 8, 2024.
  • Canada's guidance on alcohol and health. Canadian Centre on Substance Use and Addiction. https://www.ccsa.ca/canadas-guidance-alcohol-and-health. Accessed Jan. 9, 2024.
  • Science around moderate alcohol consumption. Centers for Disease Control and Prevention. https://www.cdc.gov/alcohol/fact-sheets/moderate-drinking.htm. Accessed Jan. 9, 2024.
  • Alcohol use and your health. Centers for Disease Control and Prevention. https://www.cdc.gov/alcohol/fact-sheets/alcohol-use.htm. Accessed Jan. 9, 2024.

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Nudging the public’s thirst for draught alcohol-free beers could significantly reduce alcohol-associated harms.

research study alcohol use

Press release issued: 21 March 2024

Making alcohol-free beer more widely available on draught in pubs and bars may help people switch from alcoholic to alcohol-free beer, a new study published in Addiction today [21 March], has found. Pubs and bars taking part in the University of Bristol-led trial saw an increase in sales of healthier non-alcoholic draught beer.

In partnership with Bristol City Council (BCC), researchers from the University's Tobacco and Alcohol Research Group (TARG) recruited 14 pubs and bars across the city that were willing to change the drinks that they offered on draught for a limited period. Previous research by the same group, using an online experiment as a proxy for real-world behaviour, showed that increasing the proportion of alcohol-free options make people more likely to select an alcohol-free drink over an alcoholic drink.

In the current study, the participating pubs and bars offered only alcoholic beer on draught for two weeks, and an alcohol-free option on draught for two weeks, and did this twice (over eight weeks in total). The order in which this happened was randomised. The researchers measured the amount of alcoholic and alcohol-free beer sold, as well as the total monetary takings, across the different periods.

The researchers found that when an alcohol-free option was available the pubs and bars sold, on average, 29 litres less of alcoholic beer per week, equivalent to 51 pints and a five per cent reduction in sales. However, this was replaced by an equivalent increase in sales of alcohol-free beer, suggesting customers were simply selecting a different option. Importantly, there was no net impact on overall monetary takings, suggesting that the change wasn’t hurting the financial bottom line of the participating pubs and bars.

Even small changes in drinking behaviour could have an important public health benefit. A five per cent reduction in consumption, if scaled up over a larger number of pubs and bars, could substantially reduce the harms associated with alcohol.

The research team from Bristol’s TARG, said: "Although alcohol-free options have been available for a while in pubs and bars, they have not had the same visual prominence as alcoholic drinks and are rarely served on draught.

"Our study showed that providing front-of-bar draught non-alcoholic options could lead to some customers switching from alcoholic drinks. This does not restrict consumer choice, in fact it increases the options available to the customer, and at the same time could reduce population levels of alcohol consumption and improve public health.

"We're grateful to Bristol Health Partners' Drug and Alcohol HIT for providing a collaborative platform to work with the Council’s public health and night-time economy teams."

Christina Gray, Director for Communities and Public Health at Bristol City Council , added: "As part of our drug and alcohol strategy, BCC looks to reduce the harms that can be caused by alcohol, while supporting people to change behaviour. This research demonstrates that increased availability of no and low alcohol options in hospitality settings encourages customers to switch to healthier options, but does not have a negative economic impact on the hospitality business. This enables customers to make healthier choices, whilst enjoying the positive benefits of community and socialisation that night time economy spaces provide across Bristol."

The study was funded by the University of Bristol’s Medical Research Council Integrative Epidemiology Unit (MRC IEU), National Institute for Health and Care Research Bristol Biomedical Research Centre (NIHR Bristol BRC), Bristol Health Partners Drug and Alcohol Health Integration Team (grant recipient AA), and the Wellcome Trust -funded Behaviour Change by Design collaboration between the University of Bristol and the University of Cambridge.

The research team comprised Katie De-Loyde, Jennifer Ferrar, Joe Matthews, Olivia Maynard, Angela Attwood and Marcus Munafò at the University of Bristol; Mark Pilling, University of Cambridge; Gareth Hollands, University College London ; Natasha Clarke, Bath Spa University, and Tiffany Wood and Carly Heath at Bristol City Council.

‘The impact of introducing alcohol-free beer options in bars and public houses on alcohol sales and revenue: a randomised crossover field trial’ by Olivia Maynard, Angela Attwood and Marcus Munafò et al. in Addiction

Further information

About the National Institute for Health and Care Research (NIHR) The mission of the National Institute for Health and Care Research (NIHR) is to improve the health and wealth of the nation through research. We do this by:

  • Funding high quality, timely research that benefits the NHS, public health and social care;
  • Investing in world-class expertise, facilities and a skilled delivery workforce to translate discoveries into improved treatments and services;
  • Partnering with patients, service users, carers and communities, improving the relevance, quality and impact of our research;
  • Attracting, training and supporting the best researchers to tackle complex health and social care challenges;
  • Collaborating with other public funders, charities and industry to help shape a cohesive and globally competitive research system;
  • Funding applied global health research and training to meet the needs of the poorest people in low and middle income countries.

NIHR is funded by the Department of Health and Social Care. Its work in low and middle income countries is principally funded through UK Aid from the UK government.

About National Institute for Health and Care Research Bristol Biomedical Research Centre (NIHR Bristol BRC) National Institute for Health and Care Research Bristol Biomedical Research Centre ’s (NIHR Bristol BRC) innovative biomedical research takes science from the laboratory bench or computer and develops it into new drugs, treatments or health advice. Its world-leading scientists work on many aspects of health, from the role played by individual genes and proteins to analysing large collections of data on hundreds of thousands of people. Bristol BRC is unique among the NIHR’s 20 BRCs across England, thanks to its expertise in ground-breaking population health research.

About Bristol Health Partners Bristol Health Partners is an Academic Health Science Centre. It aims to maximise the region’s health research, and to transform the understanding, prevention and treatment of key health problems faced by people who live in Bristol, North Somerset and South Gloucestershire. The organisations involved are part of Bristol Health Partners voluntarily, and it is funded by contributions from the partners. 

Bristol Health Partners’ Drug and Alcohol Health Integration Team (HIT) brings together public health experts, academics, doctors and other professionals to reduce the harm that can be caused by alcohol and substance use.

research study alcohol use

Scientists identify potential neural pathway to treat alcohol dependency in trauma survivors

I n a recent study, neuroscientists from Scripps Research discovered that targeting specific neurons involved in the brain’s stress response could potentially reduce alcohol consumption in individuals suffering from both post-traumatic stress disorder (PTSD) and alcohol use disorder (AUD). Published in Molecular Psychiatry , this research offers a promising direction for developing new treatment strategies for people grappling with these interlinked disorders.

Individuals with PTSD are at a heightened risk of developing AUD, often using alcohol as a coping mechanism to mitigate the symptoms of PTSD, such as anxiety, depression, and the distress from traumatic memories. This self-medication hypothesis suggests that alcohol may temporarily reduce the emotional pain and stress associated with PTSD, albeit with long-term negative consequences.

Existing pharmacotherapies to simultaneously address PTSD and AUD are scarce and often inadequate. The overlapping symptoms and mutual reinforcement of PTSD and AUD complicate treatment approaches, highlighting an urgent need for novel therapeutic strategies that can target both conditions effectively.

“Traumatic experiences in life can increase vulnerability to alcohol drinking and exacerbate symptoms of depression and anxiety,” explained senior author Marisa Roberto, the Schimmel Family Endowed Chair and vice chair of the Department of Molecular Medicine. “Alcohol is often used as a coping strategy to blur trauma-associated memories and diminish negative emotional states.”

Prior research indicated that corticotropin-releasing factor (CRF) plays a crucial role in stress and alcohol drinking behaviors, particularly through its action in the central amygdala, a brain region involved in processing fear and stress responses. The new study aimed to investigate whether inhibiting CRF-expressing neurons in this region could reduce alcohol consumption in a rat model of comorbid PTSD and AUD, thereby identifying a potential therapeutic target.

Roberto’s team previously developed a rat model that mimics the symptoms observed in individuals with concurrent PTSD and AUD, including aggression, anxiety, heightened alertness, sleep disturbances, and elevated alcohol intake. In their new research, they compared these rats against a group that did not display these behaviors.

The study utilized a total of 121 Wistar rats, divided into groups to explore the effects of stress and subsequent alcohol consumption. The researchers employed a “2-hit” model that first exposed rats to a stress-inducing procedure followed by a period of voluntary alcohol consumption.

To induce stress, the rats underwent familiar footshock stress procedures in an inhibitory avoidance apparatus, designed to simulate traumatic events. This involved administering footshocks to the rats in a context that they could learn and remember, mimicking the way traumatic memories can trigger stress responses in humans.

Following the stress induction, all rats were given access to alcohol in a two-bottle choice setup, allowing them to choose between water and a 20% alcohol solution. This phase aimed to assess voluntary alcohol consumption post-trauma exposure.

Rats subjected to the stress induction procedure exhibited increased voluntary alcohol consumption compared to their unstressed counterparts. This finding aligns with the hypothesis that stress and trauma can escalate alcohol use, mirroring the patterns observed in individuals with comorbid PTSD and AUD.

To probe the neural underpinnings further, a subset of rats underwent a procedure to inhibit CRF-expressing neurons within the central amygdala through a chemogenetic technique, employing Designer Receptors Exclusively Activated by Designer Drugs (DREADDs). This approach allowed the researchers to selectively inhibit these CRF-producing neurons by administering a specific drug, thereby assessing the direct impact of CRF neuronal activity on alcohol consumption and stress-related behaviors.

The researchers found that inhibiting the activity of CRF-producing neurons in the central amygdala of stressed rats resulted in a marked decrease in alcohol consumption. This pivotal result suggests that CRF neurons in the central amygdala play a crucial role in mediating stress-induced alcohol use, offering a potential target for therapeutic interventions.

Interestingly, the inhibition of CRF-expressing neurons did not reduce anxiety-like behaviors in the rats, even though it decreased alcohol consumption. This observation indicates that while CRF activity in the central amygdala contributes to alcohol use in the context of stress, it may not be the sole mediator of anxiety and trauma-related behaviors.

“We were surprised to see that the anxiety phenotypes were not reduced when silencing CRF expressing neurons in the central amygdala, suggesting other neuropeptide co-factors might be at play,” said Bryan Cruz, the study’s first author and a postdoctoral fellow at Scripps Research.

While the study offers promising avenues for therapeutic intervention, it also acknowledges its limitations, including the need for further research to clarify the role of other neuropeptides and molecular systems involved in PTSD and AUD. The use of animal models, while invaluable, calls for cautious extrapolation of findings to human conditions, highlighting the necessity for continued exploration in diverse experimental settings.

Looking ahead, the researchers emphasize the importance of disentangling the specific neurological mechanisms underlying stress-related alcohol consumption and trauma-induced anxiety. This endeavor not only seeks to refine our understanding of these complex conditions but also to pave the way for innovative treatment strategies that can address the nuanced needs of individuals afflicted by the debilitating comorbidity of PTSD and AUD.

“Understanding the neurobiology of PTSD-AUD is key for development of future intervention strategies for this devastating comorbidity,” Roberto said. “We speculate that other neuropeptides with anti-stress properties may be involved in PTSD-AUD.”

The study, “ Chemogenetic inhibition of central amygdala CRF-expressing neurons decreases alcohol intake but not trauma-related behaviors in a rat model of post-traumatic stress and alcohol use disorder ,” was authored by Bryan Cruz, Valentina Vozella, Vittoria Borgonetti, Ryan Bullard, Paula C. Bianchi, Dean Kirson, Luisa B. Bertotto, Michal Bajo, Roman Vlkolinsky, Robert O. Messing, Eric P. Zorrilla, and Marisa Roberto.

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Alcohol use disorder.

Sara M. Nehring ; Richard J. Chen ; Andrew M. Freeman .

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Last Update: August 8, 2023 .

  • Continuing Education Activity

Alcohol use disorder (AUD) remains a significant issue in the United States, affecting many individuals. Although the exact cause of AUD is not fully understood, several factors are believed to contribute to its development. These factors include the home environment, peer interactions, genetic predisposition, cognitive functioning, and the presence of certain personality disorders. This activity provides a comprehensive review of the evaluation and management of AUD, emphasizing the crucial role of the interprofessional team in recognizing and effectively managing this condition.

  • Screen patients for alcohol use disorder using validated assessment tools (eg, AUDIT and CAGE questionnaire) to identify individuals at risk.
  • Apply appropriate pharmacological and non-pharmacological treatments (eg, Alcoholics Anonymous or 12-Step programs) for individuals with alcohol use disorder.
  • Collaborate with interdisciplinary teams of healthcare providers to develop comprehensive treatment plans and provide integrated care for individuals with alcohol use disorder.
  • Coordinate and facilitate appropriate follow-up care, relapse prevention strategies, and ongoing support and counseling services for individuals with alcohol use disorder.
  • Introduction

Alcohol use disorder (AUD) is a prevalent psychiatric condition in the United States, characterized by problematic and unhealthy patterns of alcohol consumption. It is a well-recognized disorder that encompasses a broad spectrum of symptoms and behaviors associated with alcohol misuse. AUD affects a significant portion of the population, making it one of the most widespread psychiatric disorders in the country. The consequences of alcohol misuse extend beyond individual health, impacting various aspects of society, including social dynamics, economic factors, and public health.

Estimates of complications related to alcohol misuse vary; however, certain studies indicate that up to 40% of individuals have experienced adverse effects associated with alcohol misuse. According to the data obtained from the 2015 National Survey on Drug Use and Health, it was found that out of the surveyed population, approximately 138.3 million individuals aged 12 and older reported active alcohol use in the United States. Among this group, 48.2% of individuals admitted to having engaged in binge-drinking episodes within the 30 days preceding the survey. Among those who reported binge drinking, 26% of individuals acknowledged heavy alcohol use, defined as engaging in binge drinking for 5 or more days within the previous 30 days, accounting for 12.5% of the total alcohol users surveyed. These data indicate that 5.9% (or 15.7 million) of individuals in the United States aged 12 and older meet the criteria for AUD (refer to the image for the specific criteria). In addition, alcohol-related issues contribute to more than 85,000 deaths annually in the country. [1] [2] [3]

Furthermore, motor vehicle accidents, dementia, depression, homicide, and suicide have all been linked to AUD.

Diagnosis of AUD

According to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), AUD is classified based on the presence of 2 or more of the following criteria within 12 months:

  • Alcohol is often taken in more significant amounts or consumed longer than intended.
  • A persistent desire or unsuccessful efforts exist to reduce or control alcohol use.
  • A significant amount of time is spent on activities necessary to obtain or use alcohol or recover from the effects of alcohol.
  • Craving or a strong desire or urge to consume alcohol.
  • Regular alcohol use leads to an inability to meet essential responsibilities at work, school, or home.
  • Continued use of alcohol despite having persistent or recurrent social or interpersonal problems caused or exacerbated by the effects of alcohol.
  • Significant reduction of important social, occupational, or recreational activities due to alcohol use.
  • Recurrent alcohol use in situations in which it is physically hazardous.
  • Continued use of alcohol despite knowing a persistent or recurrent physical or psychological issue is likely to have been caused or exacerbated by alcohol.
  • The need for significantly increased amounts of alcohol to attain intoxication or the desired effect.
  • A substantial reduction in the desired effect even with continued use of the same amount of alcohol.
  • The presence of the typical withdrawal syndrome of alcohol.
  • Frequent consumption of alcohol (or a closely related substance, such as a benzodiazepine) to alleviate or prevent the onset of withdrawal symptoms.

Based on the number of criteria met, a patient can be classified as having a mild AUD (if they meet 2 or 3 criteria), moderate AUD (if they meet 4 or 5 criteria), or severe AUD (if they meet more than 6 criteria).

According to the 2015 National Survey on Drug Use and Health, 11.8% of survey respondents met the criteria for AUD. Among individuals with AUD, the severity of the disorder varied. Specifically, 67.4% had mild AUD, 18.8% had moderate AUD, and 13.8% had severe AUD. [4]  Notably, patients with the most severe form of AUD often seek treatment more frequently and experience a chronic relapsing course. [5]

Although the pathogenesis of AUD is not completely understood, multiple factors are believed to contribute to its development. These actors encompass environmental influences such as home environments, peer interactions, genetic elements, and cognitive functioning. AUDs also occur with psychiatric disorders such as schizophrenia, depression, and various personality disorders. [6] [7] [8] [9]  Co-occurrence of these psychiatric disorders and AUDs often leads to a worsened prognosis for both disorders. [7]

Evidence supports the influence of specific genes on an individual's susceptibility to developing AUDs. Variants of alcohol dehydrogenase ( ADH1B ) and aldehyde dehydrogenase ( ALDH2 ) genes are considered to have a protective effect against the development of AUDs. [10] [11]  Certain genes identified as potential risk factors associated with increased susceptibility to developing AUDs include, but are not limited to, GABRG2 and GABRA2 , COMT Val 158Met , DRD2 Taq1A , and KIAA0040 . [12] [13] [14] [15]   

  • Epidemiology

According to the 2016 National Survey on Drug Use and Health conducted by the Substance Abuse and Mental Health Administration, an estimated 43 million individuals in the United States aged 12 and older were reported to have a substance use disorder. Among them, 29 million individuals had an AUD, while 2.7 million had a disorder related to illicit drug use. These statistics establish alcohol as the most prevalent substance misused in the United States.

Among individuals diagnosed with both AUD and an illicit drug disorder, 1.8 million were adolescents (aged 12-17), 5.5 million were young adults (aged 18-25), and 16.8 million were adult individuals (aged 26 or older). Furthermore, out of those with a substance use disorder, 19.4 million individuals (aged 18 or older) also experienced a co-occurring mental illness. [16] [17] [18]

In general, AUDs tend to be more prevalent in individuals with lower levels of education and lower income.

On a global scale, AUDs impact a significant number of people, with an estimated 240 million individuals being affected worldwide, notably in regions such as Europe and the Americas.

  • Pathophysiology

Multiple theories have been proposed to explain the development of AUDs in individuals. Some evidence-supported theories include positive-effect regulation, negative-effect regulation, pharmacological vulnerability, and deviance proneness.

Positive-effect regulation theory suggests that certain individuals consume alcohol to seek positive rewards, such as to experience euphoria or pleasure. They may use alcohol to enhance positive emotions or social experiences.

Negative-effect regulation theory suggests that individuals may turn toward consuming alcohol to cope with negative emotions or distressing situations. [19]  Alcohol consumption can be a self-medication strategy to alleviate symptoms of depression, anxiety, or feelings of worthlessness.

Pharmacological vulnerability theory emphasizes individual differences in how they respond to the acute and chronic effects of alcohol. Specific individuals may be more susceptible to the rewarding effects of alcohol or have a reduced capacity for efficient alcohol metabolism, thereby increasing their vulnerability to developing AUDs.

Deviance proneness theory proposes that individuals with a history of deviant behavior or inadequate socialization during childhood may be more prone to developing an AUD. In this theory, alcohol consumption can become a strategy for self-medication to alleviate symptoms of depression, anxiety, or feelings of worthlessness. 

In addition, an individual's gender can also influence the development of AUDs. [20]  

  • Toxicokinetics

The metabolism of alcohol (ethanol) primarily occurs in the liver by the enzyme cytosolic alcohol dehydrogenase (ADH). This enzymatic reaction involves the reduction of nicotinamide adenine dinucleotide (NAD+) and produces acetaldehyde as a byproduct.

Acetaldehyde is subsequently metabolized by the enzyme aldehyde dehydrogenase (ALDH), which oxidizes it to form acetate. Acetate then enters into various metabolic pathways. ADH is also present in the gastrointestinal tract, contributing to the initial metabolism of ethanol during its ingestion, also known as first-pass metabolism. [21] [22]  

The cytochrome P450 system, particularly the enzyme CYP2E1, plays a role in alcohol metabolism, although to a lesser extent than ADH. In chronic alcohol users, this pathway is upregulated, leading to an increased rate of alcohol metabolism. [21] [22] [23]

The metabolism of alcohol is affected by various factors. Generally, females tend to eliminate alcohol consumption faster than males. However, females have a slower first-pass metabolism due to lower levels of ADH, resulting in higher initial blood alcohol concentration following alcohol consumption. [24]  

During pregnancy, the fetal liver metabolizes alcohol slower due to incomplete expression of enzymes CYP2E1 and ADH. As a result, the developing fetus is exposed to alcohol for a prolonged period, increasing the risks of fetal alcohol spectrum disorders.

In addition, there is evidence of a potential age-related decline in alcohol elimination. [22]  Furthermore, certain studies propose that Native Americans may metabolize alcohol faster due to the expression of beta-3 Class 1 ADH isoforms than individuals who express only the beta-1 Class 1 ADH isoform.

Alcohol metabolism is generally slower in a fasting state, which is attributed to the decreased levels of ADH observed during fasting. [25]  Conversely, consuming food can enhance liver blood flow, and the presence of sugars, such as fructose, allows a substrate for the regeneration of NAD+ from ADH. This conversion enables NAD+ to participate in the oxidation of alcohol. [25]

The time of day also impacts alcohol elimination from the body, with the highest rates of elimination observed late in the evening. Heavy drinking can affect the rate of alcohol elimination from the body, which is likely attributed to the increased expression of the CYP2E1 enzyme. However, this increase in alcohol elimination rate eventually slows down in individuals with advanced liver disease. [22]

Medications that function as ADH inhibitors can slow down the rate of alcohol elimination. H2 receptor blockers can also inhibit ADH, thereby reducing the first-pass metabolism in the stomach and potentially increasing blood alcohol levels. [22]

  • History and Physical

While gathering patient history, it has been observed that individuals with AUDs often report engaging in binge drinking episodes of consuming 4 or more drinks in a single session. To further assess the likelihood of AUDs in individuals, healthcare professionals may utilize screening tools such as the CAGE questionnaire. A score of 2 or greater on the CAGE questionnaire typically indicates the need for further evaluation and potential diagnosis of AUDs. The CAGE questionnaire comprises 4 questions as listed below:  

  • Have you ever felt the need to  Cut down on your drinking?
  • Have you ever been  Annoyed by people criticizing your drinking?
  • Have you ever felt Guilty about your alcohol consumption?
  • Have you ever felt the need for an Eye-opener to steady your nerves or get rid of a hangover?

Patients with AUDs may report additional symptoms, including frequent falls, blackout spells, instability, or visual impairment. They may also report experiencing seizures, tremors, confusion, emotional disorders, and a pattern of frequently changing jobs following a few days of abstinence from alcohol. Social challenges such as job loss, separation or divorce, estrangement from family, or homelessness may also arise. In addition, sleep disturbances are also frequently reported.

Patients may be asymptomatic or present with hypertension or insomnia in the early stages. In the later stages, as the condition progresses, patients may report additional symptoms such as nausea or vomiting, hematemesis, abdominal distension, epigastric pain, weight loss, jaundice, or other signs of liver dysfunction.

To screen for AUDs, the US Preventive Services Task Force recommends the following tools:

  • The 10-Question AUDIT (AUDs Identification Test)
  • The 3-Question AUDIT (AUDIT-C)
  • Single-Question Screening Test

During an examination, patients with AUDs may display signs of cerebellar dysfunction, such as ataxia or difficulty with fine motor skills. They may also exhibit other physical manifestations, including slurred speech, tachycardia, memory impairment, nystagmus, disinhibited behavior, or hypotension. Tremors, confusion or changes in mental status, asterixis, ruddy palms, jaundice, ascites, and other indications of advanced liver disease may also be observed in patients with AUDs. Other signs of liver disease associated with AUD may include hepatomegaly or splenomegaly in the early stages and the presence of spider angiomata, the development of cirrhosis, and liver shrinkage in the advanced stage of liver disease. 

Complications arising from alcohol usage may manifest as bleeding disorders, anemia, gastritis, ulcers, or pancreatitis. Laboratory tests may indicate anemia, thrombocytopenia, coagulopathy, hyponatremia, hyperammonemia, or decreased vitamin B12 and folate levels as the advanced liver disease progresses.

Evaluation of patients with suspected AUDs should involve a comprehensive assessment of their alcohol consumption habits. It is essential to inquire about the frequency and quantity of alcohol consumed by the individual. Standardized screening tools, such as the CAGE questionnaire and the screening questions for AUD (see Image . DSM 5 Criteria for Alcohol Use Disorder.), can help identify problematic drinking patterns in individuals with AUDs. Furthermore, obtaining a detailed family history of AUDs and substance use disorders, as well as personal and family history of any psychiatric disorders, is essential for the evaluation process.

The evaluation should include screening for any medical or behavioral complications related to alcohol use. This comprehensive evaluation may involve assessing for potential issues such as macrocytic anemia, elevated liver enzymes, coagulation disorders, pancreatitis, frequent falls, occupational difficulties, relationship issues, and aberrant behaviors (such as risky sexual activity or impulsiveness). [26] [27]

Alcohol biomarkers can assist in the evaluation process in patients with AUDs. Indirect biomarkers, including AST, ALT, GGT, mean corpuscular volume (MCV), and carbohydrate-deficient transferrin (CDT), can provide insights into the extent of alcohol-related organ damage. Direct biomarkers, such as alcohol and ethyl glucuronide levels, can help in the detection of recent alcohol consumption directly. Measuring CDT and phosphatidylethanol (PEth) can serve as a marker for long-term alcohol use or to monitor prolonged abstinence. [28] [29]

  • Treatment / Management

Treatment approaches for substance use disorders, including AUDs, often involve a combination of nonpharmacological and pharmacological interventions. Nonpharmacological or psychologically based treatment methods include motivational interviewing, motivational enhancement therapy (MET), and cognitive behavioral therapy (CBT).

Motivational interviewing is a counseling approach that aims to assist individuals in recognizing and addressing their current problems and encourages them to make positive changes in their behavior. This approach is particularly effective for individuals who may feel ambivalent or uncertain about changing their behavior or quitting alcohol.

The primary objective of motivational interviewing is to enhance an individual's intrinsic motivation for change by addressing and resolving their ambivalence. Motivational interviewing is a therapeutic approach that aims to elicit and enhance an individual's intrinsic motivations or self-motivations for making positive changes in their lives. [30] [31]  A Cochrane review conducted on the topic concluded that motivational interviewing is a more effective approach compared to no treatment when it comes to reducing the severity of substance use. [32]  

MET is a manual-based intervention that incorporates the principles of motivational interviewing. It aims to strengthen the motivation and commitment of an individual to change their alcohol use behaviors. Through a personalized assessment, MET helps individuals to explore their alcohol use patterns. On the other hand, CBT is a therapeutic approach that emphasizes the connection between thoughts, behaviors, and emotions. CBT aims to assist patients in recognizing triggers and underlying factors that influence their behavior. [33] [34]

In addition to MET and CBT, other therapies are available to treat patients with AUDs. One of the therapies includes 24-hour residential facilities, commonly known as "inpatient rehab," which provide comprehensive treatment for individuals with alcohol-related medical and psychiatric complications or comorbidities. Furthermore, there are various programs, such as Alcoholics Anonymous (AA) or 12-Step programs, that focus on group support and mentorship. These programs can be valuable sources of assistance for individuals in maintaining abstinence. AUD is a chronic condition; many individuals may experience lapses or setbacks during recovery. Therefore, the intensity and duration of therapy may vary based on individual needs and circumstances. [35] [36]

Several pharmacological options can be combined with nonpharmacological approaches to enhance the treatment outcomes of AUDs. These medications include naltrexone, acamprosate, and disulfiram. [37]  

Naltrexone is a primarily mu-opioid receptor antagonist. It was initially approved by the US Food and Drug Administration (FDA) in 1994 as a pill that can be administered daily. [38]  In 2006, an extended-release injectable formulation of naltrexone was also approved by FDA, which can be administered once every 30 days. Naltrexone works by reducing the effects of endogenous opioids on the reinforcement of drinking alcohol. [39]  Numerous studies have demonstrated the effectiveness of naltrexone in reducing the frequency of drinking days and median drinking days and increasing the number of days of abstinence and continuous abstinence. [40] [41] [42]  Caution should be taken when administering naltrexone to patients with a co-occurring opioid-use disorder, as improperly timed medication administration can result in significant opioid withdrawal.

Acamprosate is a medication approved by the FDA in 2004 to treat AUDs. It is derived from taurine and is believed to function as a glutamate agonist. [43]   Although the exact mechanism by which acamprosate works remains unclear, it is believed to involve the modulation of inhibitory and excitatory neurotransmitters in the brain, promoting a balanced state between them. [44]  Based on a Cochrane review comprising 24 randomized clinical trials, it has been observed that acamprosate reduces the risk of relapse to drinking and enhances cumulative abstinence rates. [45]  

Disulfiram, approved by the FDA in 1951, functions by inhibiting ALDH, resulting in the accumulation of acetaldehyde in the body. When individuals consume alcohol while taking disulfiram, they experience a disulfiram reaction characterized by symptoms such as flushing, headache, shortness of breath, dizziness, and diaphoresis, among other symptoms. In severe cases, these reactions can lead to shock and subsequent death. The primary purpose of disulfiram is to create a fear of these adverse reactions, thereby motivating patients to abstain from alcohol. [46]

Other medications that have demonstrated efficacy in treating patients with AUDs, but have not yet received FDA approval, include gabapentin and topiramate. Gabapentin is typically prescribed as an anticonvulsant and for neuropathic pain management. It is believed to modulate central stress systems and correct dysregulation caused by alcohol use and cessation. [47]  There is also evidence that suggests that gabapentin decreases alcohol cravings. [48]  Topiramate, another anticonvulsant medication, has demonstrated mechanisms of action that make it effective for treating patients with AUDs. However, current literature indicates that topiramate is associated with a reduction in drinking days, an increase in abstinent days, and an overall decrease in alcohol cravings. [47] [49]

According to the American Psychiatric Association practice guidelines: [50]

  • Patients with suspected AUDs should undergo evaluation for other psychiatric illnesses and co-occurring substance use.
  • Physiological biomarkers should be used as an adjunct to assess the severity of a patient's alcohol use.
  • The treatment goals should be discussed and agreed upon between the patient and the healthcare provider.
  • The potential risks to oneself and others from continued alcohol use should be openly discussed.
  • Hospitalization is recommended for patients experiencing severe alcohol withdrawal symptoms. Admission should also be considered for those with no social support, major psychiatric disorders, and a history of relapse.
  • Patients should receive a person-centered treatment plan that includes pharmacological and nonpharmacological treatments, eg, the AA program.
  • Patients should be encouraged to remove all alcohol from their homes as a positive step toward supporting their recovery process.
  • Naltrexone and acamprosate are first-line pharmacotherapy options for patients who prefer medication and have not responded to nonpharmacological methods.
  • Disulfiram can be used for patients who have not responded to naltrexone or acamprosate.
  • Second-line medications of choice include gabapentin and topiramate.
  • Differential Diagnosis

AUDs often occur concurrently with other conditions as individuals attempt to self-treat 1 or more of these conditions. Common disorders include:

  • Posttraumatic stress disorder
  • Bipolar disorder
  • Panic disorder
  • Anxiety disorder
  • Dysthymic disorder
  • Major depression

AUD is a significant and potentially harmful condition. According to the World Health Organization (WHO), AUDs are responsible for at least 3 million deaths annually, with a higher prevalence in men than women. In addition to the risk of death, AUDs are associated with various adverse outcomes, including:

  • Motor vehicle collisions
  • Esophageal, oral, liver, and breast cancers
  • Homicide and suicide
  • Hemorrhagic stroke

Identifying and treating AUDs early can help minimize the risks associated with this condition. Early intervention and timely treatment offer several advantages in mitigating the negative consequences and potential harm caused by AUDs.

  • Deterrence and Patient Education

Patient education and deterrence play essential roles in addressing AUDs.

  • Individuals with alcohol use disorder often display poor dietary choices, which can result in deficiencies of essential nutrients such as folate. Therefore, addressing and educating patients about the importance of maintaining a healthy diet is crucial.
  • While engaging with patients who consume alcohol, it is essential to have open discussions about the risks they pose to themselves and others, including their physical and mental health.
  • Patients with AUDs often benefit from regular and frequent engagement to make progress and stay motivated in their treatment.
  • Discussions about a patient's AUD should be approached in a non-confrontational and non-judgemental manner to enhance the therapeutic relationship.
  • Encouraging a healthy diet comprising fruits and vegetables is essential for individuals with AUDs for their overall well-being.
  • Pearls and Other Issues

Here are some additional considerations related to AUDs:

  • Complications arising from AUDs extend beyond physical health. They can significantly impact various aspects of a patient's life, including their socioeconomic status, mental health, interpersonal relationships, employment, and overall physical well-being.
  • Early intervention in AUD is crucial for preventing further harm and promoting recovery. Regular and ongoing non-judgemental discussions between the patient and healthcare provider are vital.
  • Acknowledging the patient's successes along their recovery journey and providing appropriate resources to support their continued efforts during each visit are essential for their well-being.
  • Discussions should focus on identifying and addressing the barriers that may prevent individuals with AUDs from seeking cessation or assistance. By understanding these barriers, healthcare providers can collaborate with patients to explore new approaches that can improvise the likelihood of successfully overcoming the challenges associated with AUDs.
  • Enhancing Healthcare Team Outcomes

AUD is a highly prevalent condition in the United States. Unfortunately, many individuals with this disorder do not seek medical attention until they encounter health issues or become entangled in legal complications. The consequences of AUDs extend beyond mere addiction, profoundly impacting the lives of family members and friends and causing disruptions in interpersonal and professional relationships.

It is uncommon for individuals with AUDs to seek help on their own proactively. Most alcoholics never receive necessary medical attention due to a lack of screening by healthcare providers. However, considering the increasing prevalence of AUDs, a national agenda has been established to address this issue. As part of this agenda, all healthcare professionals must be vigilant in identifying individuals with AUDs and making appropriate referrals to ensure they receive the necessary support for their recovery.

Primary care physicians, nurse practitioners, and pharmacists are pivotal in educating patients and raising awareness about the detrimental effects of alcohol consumption. Within inpatient settings, it is essential to offer counseling services, especially to individuals who are identified as having AUDs. Considering many individuals with AUDs may also experience psychiatric issues, including a mental health nurse in their outpatient care is highly beneficial for comprehensive patient support. 

Clinicians should encourage patients to attend AA meetings and consider involving their family members in recovery. If AA attendance alone proves insufficient, clinicians may need to explore pharmacological therapies as an additional intervention to assist patients with AUDs. CBT should also be offered to patients with AUDs. To ensure comprehensive care, adopting an interprofessional team approach involving various healthcare professionals to support individuals with AUDs is necessary.  

AUDs have no therapeutic benefits and pose significant disruptions in families and relationships. By providing appropriate interventions, support, and education, clinicians can actively contribute to the well-being and recovery of individuals affected by AUDs.

The prognosis for many patients with AUDs is challenging, with less than 20% to 30% achieving abstinence. In addition, the organ damage caused by alcohol is irreversible, further emphasizing the urgency of addressing the issue. To mitigate the impact of alcohol, it is crucial to provide comprehensive education to the patient and their family members about the destructive consequences of alcohol use. Referring patients to AA programs is a recommended course of action, as AA provides a supportive community and a structured approach to recovery. However, it is worth noting that compliance with AA attendance is often low, and alternative interventions may be necessary to enhance treatment outcomes. [1] [26]  

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DSM 5 Criteria for Alcohol Use Disorder Contributed by Sara M Nehring

Disclosure: Sara Nehring declares no relevant financial relationships with ineligible companies.

Disclosure: Richard Chen declares no relevant financial relationships with ineligible companies.

Disclosure: Andrew Freeman declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

  • Cite this Page Nehring SM, Chen RJ, Freeman AM. Alcohol Use Disorder. [Updated 2023 Aug 8]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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  • Published: 21 March 2024

Prevalence and correlates of hazardous alcohol drinking and drug use among female sex workers and men who have sex with men in Mozambique

  • Cynthia Semá Baltazar   ORCID: orcid.org/0000-0001-8901-2240 1 ,
  • Rachid Muleia   ORCID: orcid.org/0000-0001-8721-085X 1 ,
  • Auria Ribeiro Banze   ORCID: orcid.org/0000-0001-7384-4632 1 &
  • Makini Boothe   ORCID: orcid.org/0000-0002-5362-5106 2  

BMC Public Health volume  24 , Article number:  872 ( 2024 ) Cite this article

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Hazardous drinking and drug consumption are associated with an increased risk of HIV due to the complex interplay of factors influencing decision-making capability, stigma and social marginalization. In this study, we explore the patterns of hazardous alcohol and drug use and correlates of risk factors among female sex workers (FSW) and men who as sex with men (MSM) in Mozambique.

We conducted a secondary data analysis of bio-behavioral surveys (BBS) among FSW and MSM using a respondent-driven sampling methodology conducted in five main urban areas of Mozambique from 2019 to 20. The survey included a standardized questionnaire, where hazardous drinking was assessed (using AUDIT-C scores ≥ 4 for men, ≥ 3 for women) and drug use in the last year (FSW). Chi-squared test was used to analyze the association between socio-demographic and behavioral variables, and multivariate logistic regression measured the impact of the associated factors.

The prevalence of hazardous alcohol drinking was 47.1% (95% CI:44.8–49.5) for FSW and 46.5 (95% CI: 44.0–49.0) for MSM. Current drug use was reported in 13.3% of FSW. FSW engaging in hazardous alcohol drinking reported more sexual partners in the last month than those no reporting hazardous alcohol use (55.3% vs. 47,1%, p  < 0.001), higher rates of self-reported STIs in the last year (62,5% vs. 48,2%, p  < 0.001), physical (53.5% vs. 46.7%, p  < 0.0001) and sexual violence (54.7% vs. 44.2%, p  < 0.001), and HIV prevalence (55.2% vs. 44.2 p  < 0.001). Among MSM with hazardous alcohol drinking, there was a higher prevalence of self-reported STIs (52.8% vs. 45.4%, p  < 0.001), experiences of sexual violence (18.0% vs. 8.3%, p  < 0.001), and HIV prevalence (53.0% vs. 46.3%, p  < 0.001). In addition, FSW who reported illicit drug use were more likely to self-reported HIV own risk (14.2% vs. 9.7%), early start sexual activity (15.4% vs. 5.3%), self-reported STIs (17.9% vs. 10.2%), and experiences of both physical (17.4% vs. 7.0%) and sexual violence (18.6% vs. 8.9%).

There is an immediate need for the introduction and integration of comprehensive substance use harm mitigation and mental health interventions into HIV prevention programs, particularly those targeting key populations in Mozambique.

Peer Review reports

HIV/AIDS is one of the world’s major public health challenges. Progress in the prevention and treatment of HIV/AIDS is not advancing at the same rate as the general population around the world, especially among the key populations with female sex workers (FSW) having a 30 times higher risk of acquiring HIV, and gay and other men who have sex with men (MSM), with 28 times greater risk than adults aged 15–49 years [ 1 ].

Some studies have documented that the elevated risk of acquiring HIV and other sexually transmitted infections (STI) is exacerbated by the use of illicit drugs and alcohol, particularly when multiple layers of stigma exist related to sex work, homosexuality, and violence as occurs in HIV key population [ 2 , 3 , 4 ]. Alcohol use can also co-occur with illicit drug use, and several studies reported a consistent and positive association of alcohol and drug use with sexual violence, and unprotected sexual intercourse among FSW and MSM [ 4 , 5 ]. For these key populations, substance use often leads to poor decision-making and riskier behaviors, while also making them face more stigma and social exclusion, all of which contribute to the spread of HIV [ 6 , 7 , 8 ].

In sub-Saharan Africa, drinking is closely linked to unprotected sex, starting sex at a young age, and having multiple partners. Some research also points to higher risks when alcohol is used with other drugs [ 2 ]. The use of drugs and alcohol in FSW has been described as a coping mechanism to numb the challenges associated with the conditions of sex work and a facilitator for clients’ requests and wishes. Those data suggest that interventions to reduce drug and alcohol use may be important to prevent HIV and other sexually transmitted infections among high-risk. Thereby targeting these behavioral health factors, we can enhance the overall impact of public health initiatives designed to control and eliminate the spread of HIV [ 4 , 6 , 8 , 9 ].

Furthermore, it is essential to consider the broader impact of substance use on mental health, social functioning, and overall well-being. The harmful use of substances not only increases the risk of HIV but also contributes to a range of mental health issues, disrupts social relationships, and deteriorates the overall quality of life of individuals. Addressing these broader implications is a critical component of public health initiatives aiming to control and eliminate the spread of HIV [ 10 , 11 , 12 , 13 ].

The WHO Global Information System on Alcohol and Health has developed The Alcohol Use Disorders Identification (AUDIT), an instrument to screen hazardous and harmful alcohol consumption, drinking behavior, and alcohol-related problems in healthcare settings and surveys [ 14 ]. The AUDIT tool can provide more accurate insights into the intricate links between alcohol consumption and risky sexual behavior [ 2 ].

Over the past few years, there has been increased advocacy to focus interventions among key populations, especially in low- and middle-income countries. The Global AIDS Strategy 2021–2026: End Inequalities emphasizes tackling inequalities, with equitable and equal access to HIV services to close the gaps preventing progress toward ending AIDS [ 15 , 16 ]. Low engagement in services and subsequent low treatment outcomes among key population groups represent inequalities requiring specific attention.

Mozambique is one of the global countries most affected by the HIV epidemic, with an HIV prevalence of 12.5% in the general adult population, according to the recent Mozambique Population-based HIV Impact Assessments (PHIA) survey [ 17 ]. The 5th National Strategic Plan in Response to HIV/AIDS (2021–2025) prioritizes interventions for key populations, including FSW and MSM [ 18 ]. The contribution of alcohol and drug consumption to high-risk sexual behavior among FSWs and MSMs in Mozambique is not well documented.

In this context, recognizing the higher HIV prevalence among key populations, we conducted a secondary data analysis to describe patterns of substance use among FSW and MSM, who are particularly vulnerable to HIV infection and to assess the associated risk factors. This analysis was based on data from the second bio-behavioral surveys (BBS) conducted in Mozambique between 2019 and 2020. Understanding these patterns of hazardous alcohol and drug use is a crucial component in informing comprehensive HIV prevention efforts, especially in populations where the interplay of substance use and HIV risk is most pronounced.

Methodology

Survey design, participants, recruitment, and sampling.

The second round of BBS among FSW and MSM in Mozambique was implemented between 2019 and 2020 in five major urban areas in the country (Maputo, Beira, Nampula, Zambezia, and Tete).

The two surveys used the same respondent driven sampling (RDS) methodology, a peer-to-peer sampling methodology widely used to recruit high-risk and hidden populations. In this method, initial respondent, identified as “seeds,” are recruited based on their role in the community, and they are issued coupons used to invite additional participants from within their network to participate in the study. RDS sampling methodology uses responses about a participant’s personal network size to apply adjustments to the sample data that represent the larger target population in the specific geographic location. The weights represent the probability of selection. An estimator is used to produce weights for each participant that are used to generate population proportions of estimates and corresponding standard errors. Details about the survey methodology are described elsewhere [ 19 ].

FSW were eligible to participate in the survey if they were 15 years of age or older (FSW aged 15–17 are officially considered sexually exploited minors and for the purpose of the study are classified as emancipated minors and were therefore allowed to provide written informed consent to participate in the survey); reported receiving money or goods in exchange for sex from someone other than a steady partner in the six months preceding the survey; live, work or socialize in the survey area; and had a valid referral coupon. Following the formative assessment, in each city we selected three seeds, and each seed was offered five coupons. In Maputo, Beira, Tete, Quelimane and Nampula, 419, 521, 519, 514 and 519 FWS were recruited to participate to participate in the study, respectively. The sample size for each city was calculated following WHO 2017 bio-behavioral survey guidelines for populations at higher risk of HIV infection [ 20 ]. The BBS surveys carried out with FSW in Mozambique included young women aged 15–17. This decision is well documented and was made after careful consideration, drawing on evidence from previous research indicating that this data is crucial for devising effective policies and programs targeted at this high-risk HIV group [ 19 , 21 , 22 , 23 ].

MSM were eligible if they were biologically male; 18 years of age or older; reported oral or anal sex with another male in the 12 months preceding the survey; live, work or socialize in the survey area; and had a valid coupon. In both surveys Exclusion criteria included inability to provide informed consent or being under influence of alcohol and drugs. For MSM, the sample size calculation followed a similar approach as that for FWS. In the survey, 530 MSM were recruited in Maputo city, 527 in Beira, 559 in Tete, 525 in Quelimane, and 528 in Nampula. Further details on sample size calculation can be found in the report available at www.ins.gov.mz .

An interview using a standardized questionnaire was followed by two sequential rapid HIV tests (Determine™ and Uni-Gold™), along with pre-and post-test counseling on site, in line with Mozambique Ministry of Health guidelines [ 24 ].

Outcome variables

Bio-behavior variables were assessed using the WHO Biobehavioral Survey Guidelines for populations at risk for HIV [ 25 ]. Participants were asked about alcohol use and illicit drug consumption. Drug use was measured by asking participants the following questions, “During the last 12 months have you consumed any illicit drug (drugs without medical permission)?” and “Which drug did you use?” Responses included injectable (cocaine and heroin) and non-injectable drugs.

We adopted the Alcohol Use Disorders Identification (AUDIT) instrument developed by the WHO Global Information System on Alcohol and Health to screen hazardous and harmful alcohol consumption, drinking behavior and alcohol-related problems in healthcare settings and surveys [ 14 ]. While the AUDIT provides an in-depth screening for hazardous, harmful, and potentially dependent drinking with a scoring range of 0 to 40, the AUDIT-C offers a more streamlined assessment of severe binge drinking (heavy drinking and/or active alcohol abuse or dependence), suitable for rapid screening in primary care settings, with a scoring system ranging from 0 to 12. This distinction makes AUDIT-C particularly useful in our study for identifying individuals engaging in risky drinking behaviors [ 2 , 14 ]. For the purpose of this study, The 3 AUDIT questions analyzed were “How often did you have a drink containing alcohol in the past year?”, “How many drinks containing alcohol did you have on a typical day when you were drinking in the past year? ”, and “How often did you have six or more drinks on one occasion in the past year?” a composite score was calculated depending on the responses.

We utilized a cut-off score of 4 for men and 3 for women, as recommended in clinical guidelines. This threshold was chosen to identify individuals with risky drinking behaviors effectively. For the purpose of our analysis, the AUDIT-C score was treated as a binary variable: scores at or above the cut-off indicated hazardous alcohol use, while scores below suggested lower-risk consumption. This binary categorization allowed us to clearly delineate between participants with potentially harmful drinking patterns and those without, facilitating a more focused investigation into the correlates of hazardous alcohol use within the study population.

Exploratory variables

Explanatory variables were chosen based on the literature and programmatic importance including socio-demographic variables, HIV infection, self-reported STIs in the past 12 months, experience with violence (physical and sexual), comprehensive HIV knowledge (which entails a thorough understanding of how HIV is transmitted, prevented, and managed), own HIV risk perception, and health-seeking behaviors: access of health and health services in the last 12 months, self-reported STI (symptoms or diagnosis), and HIV test. High-risk social and sexual behaviors including hazardous drinking (defined by-Audit C), drug use, age of first sex work experience, number of sexual partners during the last month and condom use were also included.

Self-reported STIs were assessed by responding “yes” to at least one of the following questions: “During the last six months, have you had an abnormal discharge from your vagina, anus or penis?”, “During the last six months, have you had a sore or ulcer near your vagina, anus or penis?,” and “In the last six months, did someone inform you that you had or could have a sexually transmitted infection?”

Data analysis

Responses from the FSW and MSM, BBS surveys conducted during 2019–2020 were aggregated across survey-cities to produce pooled estimates for each population. Aggregate weighted estimates were computed using the RDS R package to analyze self-reported alcohol and drug use prevalence [ 26 ]. To produce aggregate weighted estimates, we considered the Gile’s successive sampling (RDS-SS) estimator, which accounts for the self-reported network sizes of participants, recruitment patterns and estimated size of the study population [ 27 ]. Details in the estimated size population for both FSW and MSM can be found in respective main reports. Unweighted bivariate analyses by Chi-square test were performed to identify risk factors associated with self-reported alcohol and drug use. The sample size of MSM reporting drug use was small ( n  = 36) and therefore were not included this sub-analysis.

All the analyses were done using the R statistical software 4.2.2 [ 28 ]. The code to run all the analyses is available upon request and approval.

Ethical considerations

The bio-behavioral survey among key populations adhered to stringent ethical measures that were rigorously observed. Participants provided written informed consent, and the study protocols received approval from the Institutional Ethics Committee (CIE-INS) and Mozambican National Bioethics Committee for Health (CNBS). To ensure confidentiality, personal identifiers were not collected, and survey responses were anonymized. Data were stored securely, accessible only to authorized personnel, and were encrypted to maintain privacy. The research team received comprehensive training in ethical research practices, with an emphasis on safeguarding participant confidentiality given the sensitivity of the data. Moreover, the study was subject to regular ethical audits to ensure adherence to established ethical standards and protection of participants’ rights and welfare. Minor FSWs [ 14 , 15 , 16 ], were connected with the Office for Women and Children of the Mozambican police, under the Ministry of the Interior. This office facilitates access to the legal system within a secure environment for victims of violence. Additionally, these women were directed to the Mozambican League of Human Rights, which offers legal advice at no cost.

Socio-demographic characteristics

A total of 2,567 FSW and 2,669 MSM from survey cities participated in the study. The majority of FSW were < 25 years old (60.5%), single/ (61.1%) and had secondary/high education (72.8%). Among MSM participants the majority were < 25 years (78%), single (89.2%) and had secondary or high education (99.0%). The overall HIV prevalence among FSW participants was 26.5% and among MSM was (7.0%). Main socio-demographic and health characteristics are summarized in Table  1 .

Hazardous alcohol and illicit drug among FSW and MSM

Among FSW in the five survey cities, nearly half (47,1%), reported hazardous drinking and 12.4% reported illicit drugs use. The prevalence of hazardous drinking among of MSM was 46.5% (Table  2 ).

Risk factors associated with hazardous drinking among FSW and MSM

Among the sub-sample of FSW who met AUDIT-C criteria for hazardous drinking, the median age was 24 years old (range:15–58). Hazardous drinking was more frequent in FSW participants from Maputo city (61.7% vs. 56.3% from Tete, 54.5% from Beira and 41.4% from Quelimane), > 25 years (54.3% vs. 42.5% for 15–24, p  < 0.001) and those cohabitating or married (53.1% vs. 53.1% for widowed/divorced/separated and 43.5% for single, p  < 0.001). More FSW participants with hazardous drinking behaviors reported having 2 or more clients in the last month (55.3% vs. 43.7% FSW with 1 client, p  = 0.003), had higher STI self-reported (62,5% vs. 48,2%, p  < 001) within the last month, had a higher own HIV risk perception (53.3% vs. 42.6% low), experience more physical (53.5% vs. 46.7%, p  < 0.0001) and sexual violence (54.7% vs. 44.2%, p  < 0.001) in the last 12 months preceding the survey, and were infected with HIV (55.2% vs. 44.2 p  < 0.001) (Table  3 ).

MSM participants with hazardous drinking had a median age of 22 years old (range:18–61). Hazardous drinking was more frequent in MSM participants from Beira City (66.1% vs. 59.9% from Maputo, 59.9% from Tete, 26.3% from Nampula and 24.9 from Quelimane) younger MSM participants aged 19–24 years old (61.6% vs. 42.5% for 25 years and older, p  < 0.001), and widowed/divorced/separated (65.9% vs. 59.3% cohabitating/married and 44.0% single). Most MSM participants with hazardous drinking had their first sexual experience with other men after 18 years of age (54.7% vs. 47.0 from 15 to 18, p  < 0.001), had a higher HIV risk perception (53.4% vs. 45.8 low), higher self-reported STI (52.8% vs. 45.4%, p  < 001. HIV infection was also more frequent among MSM participants reporting hazardous drinking (53.0% vs. 46.3 p  < 0.001) (Table  3 ).

Risk factors associated with illicit drug use among FSW

Among the sub-sample of FSW participant who use illicit drug use in the last 12 months before the survey the median age was 22 years old (range 15–22). Illicit drug use in the past year was more frequent among FSW from Maputo City (25.5% vs. 13.7% from Beira, 10.5% Tete, 8.4% Quelimane and 6.3% from Nampula p  < 0.001), and among FSW in a union (15.5% vs. 13.0% single and 10.7% widowed/divorced/separated, p  = 0.003). More FSW that used illicit drugs had a high perception of their own HIV risk (14.2% vs. 9.7% low perception, p  = 0.005) and have their first sexual experience when younger than 15 years old (15.4% vs. 12.6% for 15–17 years old and 5.3% for more than 24 years old, p  < 0.001). More FSW who used drugs self-reported an STI in the last year (17.9% vs. 10.2% those did not, p  < 0.001), and experienced physical (17.4% vs. 7.0% those that did not, p  < 0.001) and sexual violence (18.6% vs. 8.9% those that did not, p  < 0.001) in the last year before the survey (Table  4 ).

Our findings indicate a high prevalence of hazardous alcohol consumption among FSW and MSM where close to half are considered at risk according to the AUDIT-C scale, which is consistent with the literature [ 5 , 6 , 29 , 30 ]. For FSW, hazardous drinking use may serve as a coping mechanism to deal with the nature of their work (stress, violence, criminalization and stigmatization), while for MSM, alcohol consumption may serve as a mechanism to deal with stigma and related stress [ 4 , 30 ]. These results emphasize the need for alcohol risk reduction programmes for key populations specifically focused on the adoption of safer drinking practices integrated into HIV prevention packages.

In our study, hazardous drinking was more frequent among MSM with younger age. This likely mirrors social behavior related to alcohol use in the general population to enhance pleasure, to be more social, and/or life histories of traumatic experiences such as sexual orientation-based discrimination and childhood sexual abuse [ 31 ]. Several studies demonstrate alcohol use in younger ages to be associated with a greater number of lifetime sexual partners, non-protected sexual intercourse, elevated levels of depressive symptoms, and alcohol abuse later in life [ 29 , 31 , 32 ]. Within younger MSM, where there is an increased risk of acquiring HIV compared to their older counterparts, alcohol use preceding sexual intercourse represents an increase risk for the acquisition of HIV and other STI [ 7 , 31 , 33 ].

Nearly half (47.1%) of our FSW participants reported hazardous drinking, a figure that aligns closely with the 41% prevalence of hazardous/harmful/dependent alcohol use among FSWs reported in 32 low- and middle-income countries. This rate is substantially higher than the global prevalence of alcohol use disorders among women in the general population, which stands at 5.1% [ 5 ]. Unweighted pooled estimates conducted in our study demonstrate that FSW with hazardous alcohol consumption have an increased number of sexual partners, a higher occurrence of self-reported STI, higher perception of their own HIV risk, and have higher HIV prevalence. Other studies demonstrate that hazardous alcohol consumption likely account for the positive association between frequency of drinking and increased number of clients [ 2 ]. Previous studies have demonstrated long-term links between alcohol consumption and HIV infection in the general population [ 4 , 15 , 34 ]. Particularly among FSW Alcohol affects decision-making about negotiating for safer sex, which can increase risk of HIV and other STI transmission [ 8 ]. In addition hazardous heavy drinking and drug use have also been associated with poor adherence to antiretroviral therapy (ART) among HIV positive people and the interaction between all those substances usually leads to a higher susceptibility to co-morbidities and opportunistic infections [ 8 , 35 ]. The high burden of alcohol use among FSWs also carries serious health and social implications, as excess alcohol consumption is linked with a range of adverse physical and mental health outcomes, underscoring the need for targeted interventions in this population [ 4 , 8 , 36 ].

Physical and sexual violence is recognized as a widespread public health problem and a violation of human rights. We found FSWs that use alcohol are enmeshed in a dynamic of physical and sexual violence victimization. A prior study conducted among FSW in the country found a high prevalence of physical and sexual violence, confirming the need for specific interventions to address this vulnerability [ 23 ]. Furthermore, it’s important to note that while sex work is not criminalized in Mozambique [ 37 ], it remains highly stigmatized, and the legal system does not include specific protections for sex workers, creating additional challenges for those affected by alcohol-related issues.

“While our study found a prevalence of illicit drug use among FSW participants at 13.3%, it is noteworthy that the systematic review by Iversen et al. identified a higher pooled prevalence of lifetime illicit drug use among sex workers globally at 35% [ 38 ]. It is important to note that the prevalence of drug use among FSWs is a complex issue that is influenced by various factors such as social, economic, and cultural determinants. Consequently, the prevalence of drug use among FSWs may vary across different regions and countries. However, the risk profile of FSWs who use illicit drugs in our study is consistent with what has been observed in other studies among key populations (KP) in Mozambique. These studies consistently show that drug use tends to occur more frequently in younger individuals with a higher number of sexual partners, and it is associated with higher HIV and STI prevalence [ 19 , 39 ]. Several additional studies demonstrate that there is a strong relationship between substance use and unsafe sexual practices that increases the risk for HIV and STIs [ 7 , 30 , 36 , 40 , 41 , 42 ]. Additionally, FSW may use substances as a coping mechanism to numb the challenges associated with their sexual practices, which can also contribute to hazardous drinking [ 36 , 40 , 41 , 42 ].

Our study had some potential limitations. First, we measured the alcohol and drug use consumption by self-report thus, the data might be under-reported due to social desirability bias. Second, due to missing data we were not able to assess the drug consumption among MSM. Third, like other cross-sectional surveys, we could not assess cause-and-effect relationships, for example it was not possible to assess whether hazardous drinking behaviors and illicit drug use preceded sexual risk behaviors. Fourth, the FSW and MSM network assessed in the study may be missing important sub-groups (E.g. FSW and MSM with higher economic status) and therefore may not capture the specific drug and alcohol behaviors of these sub-populations. In addition, the analysis of pooled results from across the survey cities may affect the representativeness of sample to the general KP population in the survey cities. Finally, these findings need to be interpreted with caution and cannot be generalized to the entire MSM and FSW population in the survey cities nor at the national level. Although we were able to find significant association between the outcome variables and the exposure, we did not provide the strength of the association, considering that the analysis was more descriptive than inferential. Therefore, results should be interpreted with caution. Additionally, it should be noted that RDS is only valid within each area.

The data from this study indicate that hazardous drinking use are associated with behaviors that increase the risk of HIV among FSW and MSM, and illicit drug among FSW. As these two groups are among the most vulnerable populations for HIV, there is a need to integrate substance abuse screening, referral, and treatment into HIV prevention and treatment services. Additional studies are needed to further explore the relationship between alcohol consumption, illicit drug use and mental health issues among these populations to inform efforts that address the inequalities of the HIV epidemic.

Data availability

The Mozambique National Institute of Health (INS) provides full access to all study information and data sets in their data repository. This resource is available to researchers who fulfill the criteria for accessing confidential data. The data originates from the Bio-Behavioral Survey (BBS) studies. Researchers interested in these data sets can contact the authors or obtain further information through the INS website at www.ins.gov.mz .

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Acknowledgements

The authors wish to extend their sincere gratitude to all the study participants for their valuable contributions. We also acknowledge the dedication and hard work of the study teams, whose expertise and commitment were instrumental in the implementation of this study. Furthermore, we express our appreciation to all the institutions that provided unwavering support and resources, enabling the successful execution of this study.

This paper used data from a survey supported by the Global Fund to Fight AIDS, Tuberculosis and Malaria (Global Fund). The findings and conclusions in this article are those of the authors and do not represent the official position of the funding agencies.

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Cynthia Semá Baltazar, Rachid Muleia & Auria Ribeiro Banze

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NLC conceptualized and wrote the manuscript. RM conducted data analysis. CSB provided critical revision. All authors equally contributed to writing from their own perspectives and editing the manuscript and approved the final manuscript.

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Correspondence to Cynthia Semá Baltazar .

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Ethical clearance and participant consent were secured for the survey. The Institutional Ethics Committee (CIE-INS) and the National Bioethics Committee for Health in Mozambique (CNBS) provided ethical approval, ensuring compliance with ethical standards. Participants provided written informed consent. Specifically, special ethical approval to include FSW 15–17 was provided, who were classified as financially independent and living independently from their parents. Personal identifiers were not collected from participants, except for their consent form signatures, which were safely stored. The study did not involve individuals under the age of 15 for FSWs and under the age of 18 MSM, nor did it include illiterate participants. The Mozambique National Institute of Health granted the necessary administrative permissions to access the raw data for this analysis. This data was anonymized, containing no identifiable personal information.

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Semá Baltazar, C., Muleia, R., Ribeiro Banze, A. et al. Prevalence and correlates of hazardous alcohol drinking and drug use among female sex workers and men who have sex with men in Mozambique. BMC Public Health 24 , 872 (2024). https://doi.org/10.1186/s12889-024-18273-8

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Received : 08 August 2023

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Published : 21 March 2024

DOI : https://doi.org/10.1186/s12889-024-18273-8

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