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. Author manuscript; available in PMC: 2021 Aug 1.
Published in final edited form as: Alcohol Clin Exp Res. 2020 Jul 3;44(8):1625–1635. doi: 10.1111/acer.14386

Reduction in World Health Organization (WHO) risk drinking levels and cardiovascular disease

Justin Knox a,b, Jennifer Scodes b, Katie Witkiewitz c, Henry R Kranzler d,e, Karl Mann f, Stephanie S O’Malley g, Melanie Wall a,b, Raymond Anton h, Deborah S Hasin a,b, Alcohol Clinical Trials (ACTIVE) Workgroup
PMCID: PMC7484295  NIHMSID: NIHMS1614776  PMID: 32619058

Abstract

Background

Reductions in World Health Organization (WHO) risk drinking levels have recently been shown to lower the risk of multiple adverse health outcomes, but prior work has not examined reductions in WHO risk drinking levels in relation to cardiovascular disease (CVD), the leading cause of death for men and women in the United States and of global mortality. This study examined associations between reductions in WHO risk drinking levels and subsequent risk for CVD.

Methods

In a US national survey (NESARC), 1,058 very-high-risk and high-risk drinkers participated in Wave 1 interviews (2001-2002) and Wave 2 follow-ups (2004-2005). Self-reported CVD history that was communicated to the participant by a doctor or other healthcare professional included: arteriosclerosis, hypertension, angina, tachycardia, or myocardial infarction. We used logistic regression to estimate adjusted odds ratios (aOR) evaluating relationships between ≥2-level reductions in WHO risk drinking levels from Wave 1 to Wave 2 and the risk of Wave 2 CVD, controlling for baseline characteristics.

Results

Reductions of ≥2 WHO risk drinking levels were associated with significantly lower odds of CVD in individuals who at Wave 1 were very-high-risk (aOR=0.58 [0.41-0.80]) or high-risk drinkers (aOR=0.81 [0.70-0.94]). Interaction terms showed that this relationship varied by age. Among individuals >40 years old at Wave 1, reductions of ≥2 WHO risk drinking levels were associated with significantly lower odds of CVD among very-high-risk drinkers (aOR=0.42 [0.28-0.63]) but not high-risk drinkers (p=0.50). Among individuals ≤40 years old at Wave 1, reductions of ≥2 WHO risk drinking levels were associated with significantly lower odds of CVD among high-risk drinkers (aOR=0.50 [0.37-0.69]) but not very-high-risk drinkers (p=0.27).

Conclusions

These results show that reductions in WHO risk drinking levels are associated with reduced CVD risk among very-high-risk and high-risk drinkers in the US general population, and provide further evidence that reducing high levels of drinking provides important benefit across multiple clinical domains.

Keywords: drinking reduction, WHO risk drinking levels, alcohol use disorder, cardiovascular disease, clinical trial outcome

Introduction

Alcohol use disorders (AUD) and heavy drinking are associated with increased risk of morbidity and mortality across the globe (Room et al., 2005, Rehm et al., 2003, Rehm et al., 2017), as well as many negative health outcomes, including cardiovascular disease (CVD) (Grant et al., 2017, Grant et al., 2015, Hasin et al., 2017, Centers for Disease Control and Prevention, 2018, Greenfield et al., 2015, Room et al., 2005, Rehm et al., 2003, Rehm et al., 2017, Roerecke and Rehm, 2010). The prevalence of AUD, heavy drinking, and per capita alcohol consumption have all increased in the United States in the past decade (Grant et al., 2017, Grant et al., 2015, Sacco et al., 2015), as has the prevalence of alcoholic liver disease (Doycheva et al., 2017), alcohol-related liver cirrhosis mortality (National Institute on Alcohol Abuse and Alcoholism, 2018), and all alcohol-related mortality (White et al., 2020). Because many individuals who have an AUD never receive treatment for it (Grant et al., 2017, Hasin et al., 2007, Grant et al., 2015, Cohen et al., 2007, Shield et al., 2014, Mann et al., 2017a, Mann et al., 2017b), increasing the treatment of AUD is an important public health priority (National Institute on Alcohol Abuse and Alcoholism).

The goal of AUD treatment is often total abstinence (DeMartini et al., 2014). However, many individuals with an AUD do not want to discontinue drinking completely, and not wanting to abstain completely has been identified as a primary reason that deters many with an AUD from seeking treatment (Mann et al., 2017a, Mann et al., 2017b, Probst et al., 2015, Tucker et al., 2004, Grant, 1997, McKellar et al., 2012). If drinking reductions without complete abstinence provide health benefits, then offering treatment options that include non-abstinent drinking reductions might expand interest in treatment (Mann et al., 2017a).

Increasing the number of effective medications available to treat AUD could also increase interest in treatment (National Institute on Alcohol Abuse and Alcoholism, 2017). At present, the FDA has approved only 3 medications: disulfiram, naltrexone and acamprosate. Currently, the FDA accepts two outcomes as evidence of efficacy in clinical trials: abstinence and no heavy drinking days (HDD; women: >3 drinks in a day, men: >4 in a day) (Food and Drug Administration, 2015). However, these outcomes are often difficult for patients to achieve (Falk et al., 2019). Thus, only accepting these two outcomes may be limiting clinical trials from detecting the efficacy of additional medications due to poor sensitivity. This is possibly a contributor to the limited number of medications for treating AUD that have been approved (Anton et al., 2012, Witkiewitz et al., 2015). An alternative endpoint to these two outcomes that the European Medicines Agency (EMA) accepts (Witkiewitz et al., 2017d, Maisto et al., 2018, Wilson et al., 2016, Food and Drug Administration, 2015) is a reduction of 2 or more levels in the World Health Organization (WHO) risk drinking levels, a 4-category classification system that consists of very-high, high, moderate and low risk drinkers (European Medicines Agency, 2010, World Health Organization, 2000). For the FDA to accept reductions of 2 or more WHO risk drinking levels as a third efficacy outcome, further research is needed on the health benefits associated with such drinking reductions.

Data from clinical (Witkiewitz et al., 2017c) and epidemiologic studies (Hasin et al., 2017) have been used to show that reductions in the WHO risk drinking levels are associated with health benefits. Using data from the COMBINE Trial, a large randomized trial of medications, behavioral therapies, and their combinations to treat alcohol dependence (Witkiewitz et al., 2017c, Anton et al., 2006), reductions in WHO risk drinking levels predicted several clinical improvements, including reductions in systolic blood pressure, liver enzyme levels, and quality of life (Witkiewitz et al., 2018), as well as alcohol consequences and improved mental health functioning (Witkiewitz et al., 2017b). In data from the 3-year follow-up of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), individuals who reduced their drinking from very-high risk and high-risk WHO risk drinking levels showed lower odds of alcohol dependence (Hasin et al., 2017), liver disease (Knox et al., 2018), psychiatric comorbidity (Knox et al., 2019a), and drug use disorder (Knox et al., 2019b) and greater improvement in mental health functioning (Hasin et al., 2017) than very-high risk and high-risk drinkers who did not reduce their drinking. These studies support the use of reductions in the WHO risk drinking levels as a valid clinical trial outcome that is clinically meaningful. However, acceptance of this endpoint would be further strengthened by additional information on whether these reductions improve how individuals feel or function (Stockings and Farrell, 2017), including with regard to their physical health.

For this study, we focus on whether reductions in WHO risk drinking levels reduce the risk of CVD. CVD describes a range of conditions that involve narrowed or blocked blood vessels that can lead to a heart attack (myocardial infarction), chest pain (angina) or stroke, including, arteriosclerosis, hypertension, and tachycardia. CVD is the leading cause of death for both men and women in the United States, accounting for 1 in every 4 deaths (Benjamin et al., 2019). Further, the average annual overall cost of CVD and stroke in the United States is over $35 billion (Benjamin et al., 2019). While there are conflicting results about whether there are cardiovascular benefits from low levels of alcohol use (Mukamal and Lazo, 2017, GBD 2016 Alcohol Collaborators, 2018), AUD and heavy drinking are known to be major risk factors for CVD (Roerecke and Rehm, 2014, Kodama et al., 2011, Roerecke and Rehm, 2010). In previous literature, drinking reductions, including those that involve non-abstinence, have been shown to be associated with improved CVD conditions (Nicolas et al., 2002, Xin et al., 2001, Charlet and Heinz, 2017), although in one meta-analysis, this was only observed among heavy drinkers (Roerecke et al., 2017). Because CVD is an important indicator of impaired health, its presence can be used to study the health benefits associated with reductions in the WHO risk drinking levels.

Therefore, we used data from baseline and 3-year follow-up among very-high-risk and high-risk drinkers who were part of a study sampled to be representative of the non-institutionalized US population to evaluate whether reductions in WHO drinking risk levels were associated with subsequent reductions in risk for CVD. We evaluated whether: 1) a reduction of two or more WHO risk drinking levels (the amount of reduction required by the EMA to show efficacy (European Medicines Agency, 2010, World Health Organization, 2000)) was associated with a reduced risk of CVD at follow-up; and 2) whether the benefits of a reduction of two or more WHO risk drinking levels varied by baseline age or alcohol dependence status.

Materials and Methods

Study design and participants

The NESARC baseline (Wave 1, 2001-2002; (Grant et al., 2004)) and three-year follow-up (Wave 2, 2004-2005; (Grant et al., 2009)) data were obtained through in-person interviews in participants’ homes. The study targeted non-institutionalized civilians ≥18 years in households and group quarters (e.g., group homes, dormitories). Black and Hispanic individuals and those aged 18–24 years were oversampled. Data were adjusted for oversampling and household- and person-level non-response (Grant et al., 2004, Grant et al., 2009, Compton et al., 2007). All procedures, including written informed consent, were reviewed and approved by the US Census Bureau and the Office of Management and Budget. The overall response rate in Wave 1 was 81.0%. Excluding ineligible respondents (e.g., those who died before follow-up), the overall Wave 2 response rate among Wave 1 participants was 86.9% (Grant et al., 2009). The weighted cumulative Wave 2 response rate (i.e., Wave 1 × Wave 2 rates) was 70.2% (Grant et al., 2009). Data from Wave 2 were adjusted for non-response and demographics to approximate the target population (Grant et al., 2009). Briefly, the NESARC 2 data were weighted to represent the design characteristics of the NESARC and to account for oversampling. These weight components included adjustments for non-response across sociodemographic characteristics and substance use or psychiatric diagnoses. The weights were included within the models to ensure that our estimates were representative of our target population. The current sample includes a total of 1,058 Wave 1 WHO very-high-risk (n=512) and high-risk (n=546) level drinkers who participated in Wave 2. We selected very-high-risk and high-risk drinkers at Wave 1 because these individuals are most likely similar to individuals who enroll in alcohol clinical trials.

Measures

The primary outcome for the current study was a Wave 2 binary variable representing cardiovascular disease (CVD), based on self-reported CVD history in the past 12 months, which participants also reported as having been communicated to the participant by a doctor or other healthcare professional. The variable was coded positive if any of the following conditions were positive: arteriosclerosis, hypertension, angina, tachycardia, myocardial infarction and other CVD.

The Alcohol Use Disorder and Associated Disabilities Interview Schedule-IV (AUDADIS-IV), a structured interview that covers numerous health topics, was administered by lay interviewers (Ruan et al., 2008, Grant et al., 2003). The reliability of the AUDADIS-IV alcohol consumption measures is very good to excellent (e.g., intraclass correlation coefficient=0.73–0.92 for mean daily ethanol consumption) (Ruan et al., 2008, Grant et al., 2003). We derived WHO risk drinking levels (World Health Organization, 2000) using the AUDADIS-IV alcohol consumption module and defined them based on estimated mean daily ethanol consumption (grams) in the prior 12 months (Table 1), including both non-drinking and drinking days. The four risk levels are defined in terms of US standard drinks (14 grams of pure ethanol) and include very-high-risk drinkers (>100 gm/day for men, >60 gm/day for women, or >7.1 or >4.3 standard drinks for men and women), high-risk drinkers (60-100 gm/day for men, 40-60 gm/day for women, or 4.3-7.1 standard drinks for men and 2.9-4.3 for women), moderate-risk drinkers (40-60 gm/day for men, 20-40 gm/day for women, or 2.9-4.3 standard drinks for men and 1.4-2.9 for women), and low-risk drinkers (1-40 gm/day for men, 1-20 gm/day for women, or <2.9 standard drinks for men and <1.4 for women). Abstainers, i.e., non-drinkers for at least a year prior to assessment, were treated as a separate risk level, consistent with previous studies (Knox et al., 2019a, Knox et al., 2018, Knox et al., 2019b, Hasin et al., 2017).

Table 1.

Prevalence of Wave 1 WHO risk drinking levels among drinkersa and prevalence of Wave 1 cardiovascular disease (CVD) within these WHO risk drinking levels.

Wave 1
WHO
risk
drinking
levelb 		Definition n Percent of
participants at
each WHO risk
level among
Wave 1
drinkers		 Prevalence of
any Wave 1
CVD within
each risk
level		 Hypertension Arteriosclerosis Angina Tachycardia Myocardial
infarction		 Other
CVD
Very high >100 g (>7.1 drinks) for men,
>60 g (>4.3 drinks) for women		 512 2.5% 21.4% 18.1% 1.5% 4.4% 7.0% 1.2% 1.6%
High 60–100 g (4.3–7.1 drinks) for men,
40–60 g (2.9–4.3 drinks) for women		 546 2.5% 19.8% 16.5% 0.3% 2.7% 2.2% 0.0% 1.6%
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a

Individuals who reported drinking at least one drink in the past year

b

American standard drinks (contains roughly 14 grams of pure alcohol).

Statistical analysis

We first obtained weighted proportions using NESARC 2 survey weights of individuals in the very-high-risk and high-risk WHO risk drinking levels at Wave 1 and estimated the number of individuals in each category with Wave 1 CVD. Then, we used logistic regression to examine the interaction between initial Wave 1 risk level (very-high risk vs. high risk) and changes between Wave 1 and Wave 2 WHO risk drinking levels (decreased by ≥2 levels vs. not decreased by ≥2 levels) on the prevalence of CVD at Wave 2. There was a significant 2-way interaction (p<.001), reflecting differential effects by Wave 1 WHO risk level. Thus, we modeled the effect of changes between Wave 1 and 2 WHO risk drinking levels on Wave 2 CVD using logistic regression, in which each initial Wave 1 risk drinking level was a stratum. We also conducted these analyses separately for the persistence of CVD at Wave 2 among individuals with any CVD condition at Wave 1, and for incidence of CVD at Wave 2 among individuals with no CVD condition at Wave 1. We also conducted the primary analyses separately for each CVD condition (arteriosclerosis, hypertension, angina, tachycardia, myocardial infarction and other CVD).

Participants’ Wave 1 risk level determined the number of possible reduction levels at Wave 2. Wave 1 very-high-risk drinkers could remain unchanged; decrease one, two, or three levels (non-abstinent reductions); or reduce to abstinence. Wave 1 high-risk drinkers could increase to very high risk, remain unchanged, decrease to moderate or low risk (non-abstinent reductions), or reduce to abstinence. We dichotomized these changes, dividing the groups into those who had ≥2-level reductions (decreased 2 levels, decreased 3 levels, reduced to abstinence) in WHO risk drinking levels and those who did not (increased 1 level, remained unchanged, decreased 1 level). Consistent with previous studies, the logistic regression models controlled for potential confounders (sex, age, education, race and ethnicity, smoking, body-mass index, health insurance, and Wave 1 psychiatric disorders) and also Wave 1 CVD. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) of Wave 2 CVD and CVD conditions were computed for ≥2-level reductions in WHO risk drinking level compared to the reference group (people with <2-level reductions in WHO risk drinking level). We calculated the adjusted prevalence of Wave 2 CVD and CVD conditions using covariates that were fixed at their marginal distribution in the sample.

Subsequently, we also explored two potential modifiers of the effects of ≥2-level reductions in WHO risk drinking level on any CVD. The first potential modifier was Wave 1 alcohol dependence (comparing individuals with and without this disorder). We looked for effect modification by alcohol dependence to account for the potential that drinking reductions were differentially beneficial among individuals whose alcohol use met criteria for disorder (Witkiewitz et al., 2020). The second potential modifier was age group (comparing individuals younger than 40 years old and those 40 years and older). We looked for effect modification by age group to account for the increasing risk of CVD as people age (Benjamin et al., 2019), with a noticeable increase in CVD prevalence starting around the age of 40 (Writing Group et al., 2016, Mozaffarian et al., 2015). We tested each of these potential moderators separately by adding to the models a 3-way interaction term of the potential modifier, by initial Wave 1 WHO risk drinking level, and by change between Wave 1 to 2 WHO risk drinking. If interactions were significant, we stratified subsequent models by the moderator and Wave 1 WHO risk drinking level when evaluating the relationship between ≥2 level reductions and CVD. All statistical tests were 2-sided, with significance set at p<0.05. To incorporate the complex clustered design and sampling weights of the NESARC, we fit all analyses with Proc Surveylogistic (SAS version 9.4).

We conducted three sets of sensitivity analyses: 1) we repeated the main analyses controlling for DSM-IV alcohol dependence at Wave 1; 2) we conducted the main analyses after excluding individuals who reported becoming abstinent by Wave 2 (i.e., no drinks in the past year) to determine whether the results apply to non-abstinent drinking reductions (rather than being driven primarily by abstinent reductions). In the main analyses, we also compared individuals who reported being abstinent at Wave 2 to those who had <2-level reductions, including moderate-risk drinkers; 3) we conducted the main analyses among all Wave 1 drinkers (n=21,925), disaggregated by increased drinking level, no change, and all levels of decreased drinking levels.

Results

At Wave 1, in all respondents who reported drinking at least one drink in the past year, 2.5% were very-high-risk drinkers and 2.5% were high-risk drinkers, (Table 1). At Wave 1, the prevalence of CVD was 21.4% in very-high-risk drinkers and 19.8% in high-risk drinkers. The Wave 1 prevalence of individual CVD conditions ranged from 1.2% (myocardial infarction) to 18.1% (hypertension) among very-high-risk drinkers and 0.0% (myocardial infarction) to 16.5% (hypertension) among high-risk drinkers.

Very-High-Risk Drinkers

Table 2 shows the adjusted prevalence of CVD at Wave 2 by changes in WHO risk drinking level, stratified by Wave 1 WHO risk drinking level. In Wave 1 very-high-risk drinkers with <2-level reductions in WHO risk drinking levels, 23.9% had Wave 2 CVD. In those who reduced their drinking by ≥2 WHO risk drinking levels at Wave 2, 15.3% had Wave 2 CVD. Thus, a reduction in WHO risk drinking levels of ≥2 predicted significantly lower odds of Wave 2 CVD (aOR [95% CI]=0.58 [0.41-0.80], p<.01).

Table 2.

Cardiovascular disease (CVD) at Wave 2 by Wave 1 WHO risk drinking level and change in WHO risk level between Waves 1 and 2.

Wave 1 WHO risk level
and change by Wave 2		 Wave 1 very-high-risk and high-risk drinkers (n=1,058)
n Adjusted
Prevalence of
Wave 2 CVD		 Adjusted OR
(95% CI)		 p-value
Wave 1 Very high risk
Not decreased by ≧2 levels 214 23.9% Reference
Decreased by ≧2 levels 298 15.3% 0.58 (0.41-0.80) 0.0012
Wave 1 High risk
Not decreased by ≧2 levels 266 23.1% Reference
Decreased by ≧2 levels 280 19.6% 0.81 (0.70-0.94) 0.0069
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a

Prevalence values are calculated from the same logistic regression used to obtain adjusted OR values which controls for Wave 1 covariates (sex, age, education, race and ethnicity, smoking, body-mass index, health insurance, presence of psychiatric condition, CVD).

Table 3 shows the adjusted prevalence of CVD at Wave 2 by changes in WHO risk drinking level among individuals with Wave 1 CVD, stratified by Wave 1 WHO risk drinking level. Of Wave 1 very-high-risk drinkers with <2-level reductions in WHO risk drinking levels, 62.9% had Wave 2 CVD, compared to 65.5% of those who reduced their drinking by ≥2 WHO risk drinking levels at Wave 2, a non-significant difference (p=0.73).

Table 3.

Cardiovascular disease (CVD) at Wave 2 among those with Wave 1 CVD (Persistence) by Wave 1 WHO risk drinking level and change in WHO risk level between Waves 1 and 2.

Wave 1 WHO risk level
and change by Wave 2		 Wave 1 very-high-risk and high-risk drinkers with Wave 1
CVD (n=241)
n Adjusted
Prevalence of
Wave 2 CVD		 Adjusted OR
(95% CI)		 p-value
Wave 1 Very high risk
Not decreased by ≧2 levels 60 62.9% Reference
Decreased by ≧2 levels 61 65.5% 1.12 (0.60-2.08) 0.7275
Wave 1 High risk
Not decreased by ≧2 levels 70 67.5% Reference
Decreased by ≧2 levels 50 59.4% 0.71 (0.51–0.97) 0.0314
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a

Prevalence values are calculated from the same logistic regression used to obtain adjusted OR values which controls for Wave 1 covariates (sex, age, education, race and ethnicity, smoking, body-mass index, health insurance, presence of psychiatric condition).

Table 4 shows the adjusted prevalence of CVD at Wave 2 by changes in WHO risk drinking level among individuals without Wave 1 CVD, stratified by Wave 1 WHO risk drinking level. Of Wave 1 very-high-risk drinkers with <2-level reductions in WHO risk drinking levels, 17.8% had Wave 2 CVD, compared to 8.2% of those who reduced their drinking by ≥2 WHO risk drinking levels at Wave 2. Thus, a reduction in WHO risk drinking levels of ≥2 predicted significantly lower odds of incident Wave 2 CVD (aOR [95% CI]=0.41 [0.28-0.62], p<.0001).

Table 4.

Cardiovascular disease (CVD) at Wave 2 among those without Wave 1 CVD (Incidence) by Wave 1 WHO risk drinking level and change in WHO risk level between Waves 1 and 2.

Wave 1 WHO risk level
and change by Wave 2		 Wave 1 very-high-risk and high-risk drinkers without Wave
1 CVD (n=817)
n Adjusted
Prevalence of
Wave 2 CVD		 Adjusted OR
(95% CI)		 p-value
Wave 1 Very high risk
Not decreased by ≧2 levels 154 17.8% Reference
Decreased by ≧2 levels 237 8.2% 0.41 (0.28-0.62) <.0001
Wave 1 High risk
Not decreased by ≧2 levels 196 15.4% Reference
Decreased by ≧2 levels 230 13.3% 0.84 (0.72–0.99) 0.0421
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a

Prevalence values are calculated from the same logistic regression used to obtain adjusted OR values which controls for Wave 1 covariates (sex, age, education, race and ethnicity, smoking, body-mass index, health insurance, presence of psychiatric condition).

High-Risk Drinkers

In Wave 1 high-risk drinkers with <2-level reductions in WHO risk drinking levels, 23.1% had Wave 2 CVD. In those who reduced their drinking by ≥2 WHO risk drinking levels at Wave 2, 19.6% had Wave 2 CVD. Thus, a reduction in WHO risk drinking levels of ≥2 predicted significantly lower odds of Wave 2 CVD (aOR [95% CI]=0.81 [0.70-0.94], p<.01).

Of Wave 1 high-risk drinkers with <2-level reductions in WHO risk drinking levels and Wave 1 CVD, 67.5% had Wave 2 CVD, compared to 59.4% of those who reduced their drinking by ≥2 WHO risk drinking levels at Wave 2. Thus, a reduction in WHO risk drinking levels of ≥2 predicted significantly lower odds of persistent Wave 2 CVD (aOR [95% CI]=0.71 [0.51-0.97], p=.03).

Of Wave 1 high-risk drinkers with <2-level reductions in WHO risk drinking levels and no Wave 1 CVD, 15.4% had Wave 2 CVD, compared to 13.3% of those who reduced their drinking by ≥2 WHO risk drinking levels at Wave 2. Thus, a reduction in WHO risk drinking levels of ≥2 predicted significantly lower odds of incident Wave 2 CVD (aOR [95% CI]=0.84 [0.72-0.99], p=.04).

Individual CVD conditions

Table 5 shows the relationship between reductions in WHO risk drinking levels and each of the CVD conditions. The results were generally similar to that of the main analysis (for all CVD conditions), with hypertension driving the relationship for very-high-risk drinkers and angina, myocardial infarction, and other CVD driving the relationship for high-risk-drinkers. Notably, in very-high-risk drinkers, compared to respondents with <2-level reductions in WHO risk drinking levels (the reference group), a reduction of ≥2 WHO risk drinking levels predicted significantly lower odds of Wave 2 hypertension and significantly higher odds of angina. In high-risk drinkers, compared to respondents with <2-level reductions in WHO risk drinking levels (the reference group), a reduction of ≥2 WHO risk drinking levels predicted significantly lower odds of Wave 2 angina, myocardial infarction, and other CVD.

Table 5.

Cardiovascular disease (CVD) conditions at Wave 2 by Wave 1 WHO risk drinking level and change in WHO risk level between Waves 1 and 2.

Wave 1 WHO risk level
and change by Wave 2		 Hypertension
n Adjusted
Prevalence at
W2		 Adjusted OR
(95% CI)		 p-value
Wave 1 Very high risk
Not decreased by ≧2 levels 214 21.1% Reference
Decreased by ≧2 levels 298 12.3% 0.52 (0.38-0.72) <.0001
Wave 1 High risk
Not decreased by ≧2 levels 266 16.0% Reference
Decreased by ≧2 levels 280 15.8% 0.98 (0.81-1.19) 0.8628
Wave 1 WHO risk level
and change by Wave 2		 Arteriosclerosis
n Adjusted
Prevalence at
Wave 2		 Adjusted OR
(95% CI)		 p-value
Wave 1 Very high risk
Not decreased by ≧2 levels 214 0.0% Reference
Decreased by ≧2 levels 298 0.0% 1.03 (0.40-2.65) 0.9476
Wave 1 High risk
Not decreased by ≧2 levels 266 0.0% Reference
Decreased by ≧2 levels 280 0.0% 1.21 (0.43-3.41) 0.7149
Wave 1 WHO risk level
and change by Wave 2		 Angina
n Adjusted
Prevalence at
Wave 2		 Adjusted OR
(95% CI)		 p-value
Wave 1 Very high risk
Not decreased by ≧2 levels 214 0.7% Reference
Decreased by ≧2 levels 298 1.9% 2.98 (1.32-6.73) 0.0084
Wave 1 High risk
Not decreased by ≧2 levels 266 1.7% Reference
Decreased by ≧2 levels 280 0.9% 0.51 (0.30-0.88) 0.0154
Wave 1 WHO risk level
and change by Wave 2		 Tachycardia
n Adjusted
Prevalence at
Wave 2		 Adjusted OR
(95% CI)		 p-value
Wave 1 Very high risk
Not decreased by ≧2 levels 214 2.9% Reference
Decreased by ≧2 levels 298 2.5% 0.85 (0.59-1.21) 0.3636
Wave 1 High risk
Not decreased by ≧2 levels 266 2.1% Reference
Decreased by ≧2 levels 280 1.9% 0.92 (0.78-1.08) 0.2997
Wave 1 WHO risk level
and change by Wave 2		 Myocardial infarctionb
n Adjusted
Prevalence at
Wave 2		 Adjusted OR
(95% CI)		 p-value
Wave 1 Very high risk
Not decreased by ≧2 levels 214 0.02% Reference
Decreased by ≧2 levels 298 0.04% 2.31 (0.58-9.15) 0.2323
Wave 1 High risk
Not decreased by ≧2 levels 266 0.03% Reference
Decreased by ≧2 levels 280 0.00% 0.10 (0.05-0.19) <.0001
Wave 1 WHO risk level
and change by Wave 2		 Other CVD
n Adjusted
Prevalence at
Wave 2		 Adjusted OR
(95% CI)		 p-value
Wave 1 Very high risk
Not decreased by ≧2 levels 214 0.4% Reference
Decreased by ≧2 levels 298 0.3% 0.79 (0.32-1.99) 0.6215
Wave 1 High risk
Not decreased by ≧2 levels 266 0.5% Reference
Decreased by ≧2 levels 280 0.2% 0.38 (0.18-0.78) 0.009
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a

Prevalence values are calculated from the same logistic regression used to obtain adjusted OR values which controls for a priori control covariates (sex, age, education, race and ethnicity, smoking, body-mass index, health insurance, presence of psychiatric condition, respective CVD condition).

b

Results of prevalence levels for myocardial infarction are reported out to two decimal places because of its low prevalence.

Effect Modification

Interaction terms indicated that the relationship between WHO risk drinking level reductions and CVD varied by age group (χ2(1)=10.7, p<0.01) but not alcohol dependence (χ2(1)=1.7, p=0.19). Therefore, we stratified the sample by age (<40 years old vs. ≥40 years old) (see Table 6).

Table 6.

Cardiovascular disease (CVD) at Wave 2 by Wave 1 WHO risk drinking level and change in WHO risk level between Waves 1 and 2 stratified by age group.

Participants 40 years old and older
Wave 1 WHO risk level
and change by Wave 2		 Wave 1 very-high-risk and high-risk drinkers (n=546)
n Adjusted
Prevalence of
Wave 2 CVD		 Adjusted OR
(95% CI)		 p-value
Wave 1 Very high risk
Not decreased by ≧2 levels 127 20.9% Reference
Decreased by ≧2 levels 120 10.0% 0.42 (0.28-0.63) <.0001
Wave 1 High risk
Not decreased by ≧2 levels 180 20.1% Reference
Decreased by ≧2 levels 119 21.2% 1.07 (0.88-1.29) 0.5044
Participants younger than 40 years old
Wave 1 WHO risk level>
and change by Wave 2		 Wave 1 very-high-risk and high-risk drinkers (n=512)
n Adjusted
Prevalence of
Wave 2 CVD		 Adjusted OR
(95% CI)		 p-value
Wave 1 Very high risk
Not decreased by ≧2 levels 87 29.0% Reference
Decreased by ≧2 levels 178 23.6% 0.75 (0.46-1.25) 0.2735
Wave 1 High risk
Not decreased by ≧2 levels 86 27.3% Reference
Decreased by ≧2 levels 161 16.0% 0.50 (0.37-0.69) <.0001
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a

Prevalence values are calculated from the same logistic regression used to obtain adjusted OR values which controls for a priori control covariates (sex, age, education, race and ethnicity, smoking, body-mass index, health insurance, presence of psychiatric condition, CVD).

Individuals ≥40 years old at Wave 1

In Wave 1 very-high-risk drinkers with <2-level reductions in WHO risk drinking levels, 20.9% had Wave 2 CVD. In those who reduced their drinking by ≥2 WHO risk drinking levels at Wave 2, 10.0% had Wave 2 CVD. Thus, a reduction in WHO risk drinking levels of ≥2 predicted significantly lower odds of Wave 2 CVD (aOR [95% CI]=0.42 [0.28-0.63], p<.0001). In Wave 1 high-risk drinkers with <2-level reductions in WHO risk drinking levels, 20.1% had Wave 2 CVD. In those who reduced their drinking by ≥2 WHO risk drinking levels at Wave 2, 21.2% had Wave 2 CVD; a non-significant difference (p=0.50).

Individuals <40 years old at Wave 1

In Wave 1 very-high-risk drinkers with <2-level reductions in WHO risk drinking levels, 29.0% had Wave 2 CVD. In those who reduced their drinking by ≥2 WHO risk drinking levels at Wave 2, 23.6% had Wave 2 CVD; a non-significant difference (p=0.27). In Wave 1 high-risk drinkers with <2-level reductions in WHO risk drinking levels, 27.3% had Wave 2 CVD. In those who reduced their drinking by ≥2 WHO risk drinking levels at Wave 2, 16.0% had Wave 2 CVD. Thus, a reduction in WHO risk drinking levels of ≥2 predicted significantly lower odds of Wave 2 CVD (aOR [95% CI]= 0.50 [0.37-0.69], p<.0001).

Sensitivity Analyses

We saw virtually no effect of controlling for a diagnosis of DSM-IV alcohol dependence at Wave 1 (results not shown). Restricting the main analyses to the 983 participants who did not reduce their drinking to abstinence at Wave 2 had virtually no effect on the results (Supplementary Table 1). Supplementary Table 2 shows the results of the main analyses restricted to the participants who reduced their drinking to abstinence at Wave 2, and includes Wave 1 moderate-risk drinkers who reduced their drinking to abstinence at Wave 2. In Wave 1 very-high-risk drinkers with <2-level reductions in WHO risk drinking levels, 26.8% had Wave 2 CVD. In very-high-risk drinkers who reduced their drinking to abstinence at Wave 2, 20.9% had Wave 2 CVD. Thus, reducing drinking to abstinence predicted significantly lower odds of Wave 2 CVD (aOR [95% CI]=0.72 [0.55-0.96], p=.03); an effect similar to that observed among all very-high-risk drinkers who reduced their drinking by ≥2 WHO risk drinking levels at Wave 2 (aOR [95% CI]=0.58 [0.41-0.80], p<.01). In Wave 1 high-risk drinkers with <2-level reductions in WHO risk drinking levels, 25.1% had Wave 2 CVD. In high-risk drinkers who reduced their drinking to abstinence at Wave 2, 28.9% had Wave 2 CVD. This was a non-significant difference (p=0.43); unlike the significant effect that was observed among all high-risk drinkers who reduced their drinking by ≥2 WHO risk drinking levels at Wave 2 (aOR [95% CI]=0.81 [0.70-0.94], p<.01). In Wave 1 moderate-risk drinkers with <2-level reductions in WHO risk drinking levels, 17.8% had Wave 2 CVD. In moderate-risk drinkers who were abstinent at Wave 2, 13.2% had Wave 2 CVD. Thus, the initiation of abstinence predicted significantly lower odds of Wave 2 CVD (aOR [95% CI]=0.70 [0.50-0.98], p=.04). Supplementary Table 3 shows the adjusted prevalence of CVD at Wave 2 by the disaggregated levels of changes in WHO risk drinking levels, stratified by all Wave 1 risk drinking levels.

Discussion

We examined whether reducing drinking by 2 or more WHO risk drinking levels in participants from a large national survey with a 3-year follow-up was associated with reduced risk of cardiovascular disease (CVD). We limited our analyses to respondents at Wave 1 who are of greatest clinical concern and most like participants in clinical trials for AUD: namely, those in the WHO very-high-risk and high-risk drinking levels. Results show that reductions of two or more WHO risk drinking levels were associated with significantly lower odds of CVD among very-high-risk and high-risk drinkers. This same result was observed both for the persistence of CVD at Wave 2 among individuals with CVD at Wave 1 and the incidence of CVD at Wave 2 among those without CVD at Wave 1. This was also the case regardless of whether these very-high-risk and high-risk drinkers initially met criteria for alcohol dependence. When we stratified by age group to account for the increasing risk of CVD as people age (Benjamin et al., 2019), with a noticeable increase in CVD prevalence starting around the age of 40 (Writing Group et al., 2016, Mozaffarian et al., 2015), the results showed that reductions of two or more WHO risk drinking levels are associated with significantly lower odds of CVD in very-high-risk drinkers ≥40 years old and high-risk drinkers <40 years old. These benefits were also generally similar across CVD conditions and held even when individuals who reduced their drinking to abstinence at Wave 2 were excluded. Results among individuals who reduced their drinking to abstinence at Wave 2 were also generally similar to all of those with 2 or more WHO risk drinking level reductions. Collectively, these findings provide further support for the health benefits associated with reductions in WHO risk drinking levels in individuals whose drinking is of greatest clinical concern (Falk et al., 2019).

These findings showing that drinking reductions among high-risk and very-high risk drinkers (≥4.3 drinks per day for men; ≥2.9 drinks per day for women) are associated with reduced risk of CVD are consistent with prior studies showing that heavy drinking and AUD are associated with greater risk of CVD (Roerecke and Rehm, 2014, Kodama et al., 2011, Roerecke and Rehm, 2010). The current findings are also in line with studies showing that drinking reductions are associated with improvement in CVD conditions (Charlet and Heinz, 2017), e.g., as blood pressure (Xin et al., 2001) cardiomyopathy (Nicolas et al., 2002). Across studies, CVD benefits were observed in both individuals who became abstinent and those who reduced their drinking but not to abstinence (Nicolas et al., 2002, Xin et al., 2001, Charlet and Heinz, 2017). In a meta-analysis, the CVD benefits of drinking reductions, including both abstinence and reduced drinking, were observed only among heavy drinkers (Roerecke et al., 2017). Our results are encouraging because they indicate that reductions in drinking at these levels are associated with short-term clinical benefit in terms of reduced CVD risk (Wood et al., 2018). Importantly, our findings expand upon previous studies by showing that the benefits of drinking reductions on CVD can be detected using the WHO risk drinking levels (World Health Organization, 2000).

Results also support using WHO risk drinking level reductions as an outcome measure in clinical trials of AUD treatments, as they are consistent with findings that drinking reductions, including those short of abstinence, are associated with health benefits (Rehm and Roerecke, 2013, Dawson et al., 2008, Roerecke et al., 2013, Roerecke et al., 2015, Witkiewitz et al., 2017a, Anton et al., 2006, Hasin et al., 2017, Knox et al., 2018, Knox et al., 2019a, Knox et al., 2019b). The need for additional therapeutic options for AUD has become more evident with national increases in per capita alcohol consumption, the prevalence of heavy drinking (Grant et al., 2017, Grant et al., 2015), AUD (Grant et al., 2017, Grant et al., 2015, Sacco et al., 2015), and all alcohol-related mortality (White et al., 2020). This is compounded by evidence that many individuals who drink heavily, including those with AUD, do not receive treatment (Grant et al., 2017, Hasin et al., 2007, Grant et al., 2015, Cohen et al., 2007, Shield et al., 2014). Documentation of the benefits of drinking reductions among individuals who drink at “unsafe levels,” including these findings regarding CVD, is of interest to the public, patients, substance use treatment providers, primary care providers, cardiologists, clinical trial researchers, and public health officials. Given the increasing public health burden of AUD (Grant et al., 2017, Grant et al., 2015), reducing alcohol consumption so as to decrease health problems has enormous cost-benefit potential.

The present study has limitations. Data were derived from self-report, with potential underreporting of both alcohol use and CVD. Further, diagnoses of CVD were based, not directly by medical providers, but rather, by participants’ reports of having been diagnosed by a doctor or other healthcare professional. Individuals who reduce their drinking may see a doctor or other healthcare professional less frequently, and thus may have less of an opportunity to receive a physician diagnosis of CVD conditions, potentially creating a spurious association between reductions in drinking and improved CVD outcomes as they are measured in this study. Future large-sample studies with direct medical examinations and long-term follow-up should be conducted to provide additional information. In addition, the data used for this study are from 2001-2005. Thus, additional studies should be conducted using more recent data. Also, these data show that reducing drinking is likely beneficial for CVD outcomes, but there are potential differences between a sample of heavy drinkers in the general population who reduce their drinking for whatever reason, and those who receive treatment as part of a clinical trial. Lastly, this study is not able to assess the durability of drinking reductions over time.

Despite these limitations, the data that were analyzed came from the NESARC, a large, rigorous epidemiological study with high response rates, detailed assessment of drinking at both waves, and a 3-year follow-up period. Further, the sample was a national one with good representation of participants across demographic groups that provided adequate statistical power to analyze reductions in WHO risk drinking levels, including those of individuals drinking at high-risk and very-high-risk levels.

In summary, this study showed that reductions of two or more WHO risk drinking levels were associated with significantly lower odds of subsequent CVD among very-high-risk and high-risk drinkers. Individuals with an AUD and those who engage in high risk drinking who are not interested in complete abstinence are less likely to pursue treatment that requires a goal of abstinence compared to treatment that also confers benefit but does not require abstinence. Thus, identifying non-abstinent treatment goals that confer clinical benefit could help to engage individuals who could benefit from alcohol treatment, but who might not otherwise be willing to receive it. Our results add to evidence that drinking reductions, including those that are not complete abstinence, are associated with health benefits for very heavy drinkers (those initially with WHO high-risk and very-high-risk drinking levels). In addition, drinking reductions defined by the WHO risk drinking levels can also be used as outcome indicators in clinic trials for treatments of AUD, which the European Medicines Agency has done (European Medicines Agency, 2010). Thus, these data support previous findings that show that WHO risk drinking level reductions can provide useful drinking goals to be considered with patients, and valid clinical trial outcome indicators. Clinical trials and other systematic treatment-outcome studies are needed to determine whether offering treatment with a goal of reducing alcohol consumption by 2 or more WHO risk drinking levels is more successful in recruiting participants who could benefit from the intervention than trials whose goals are abstinence, and how the outcomes of these approaches compare.

Supplementary Material

sup info

Acknowledgments

This work was supported by the National Institute on Alcohol Abuse and Alcoholism [R01AA025309], the National Institute on Drug Abuse [T32DA031099], the New York State Psychiatric Institute, and the Alcohol Clinical Trials Initiative (ACTIVE). The funding agencies 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.

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