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Am J Drug Alcohol Abuse. Author manuscript; available in PMC 2016 November 01. Published in final edited form as: Am J Drug Alcohol Abuse. 2015 November ; 41(6): 479–488. doi:10.3109/00952990.2015.1058812.

The association between alcohol use and cardiovascular disease among people living with HIV: A systematic review Natalie E. Kelso, David S. Sheps, and Robert L. Cook Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA

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Abstract Background—People living with HIV-infection (PLWH) have higher prevalence and earlier onset of cardiovascular disease (CVD), compared to uninfected populations. It is unclear how alcohol consumption is related to CVD among PLWH. Objectives—The objectives of this review was to summarize the current literature and strength of evidence regarding alcohol consumption as a risk factor for CVD among PLWH, to generate summary estimates for the effect of alcohol consumption on CVD outcomes, and to make recommendations for clinical practice and future research based on the findings and limitations of existing studies.

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Methods—A systematic review was conducted using Pubmed/Medline to identify relevant peerreviewed articles published between January 1, 1999 and January 1, 2014. After critical review of the literature, 13 studies were identified. Risk ratios were extracted or calculated and sample size weighted summary estimates were calculated. Results—The prevalence of a CVD diagnosis or event ranged from 5.7%–24.0%. The weighted pooled crude effect sizes were 1.75 (95% CI 1.06, 3.17) for general and 1.78 (95% CI 1.09, 2.93) for heavy alcohol use on CVD. The pooled adjusted effect size was 1.37 (95% CI 1.02, 1.84) for heavy alcohol use on CVD. Pooled estimates differed by CVD outcome and alcohol measure; alcohol consumption was most significant for cerebral/ischemic events. Conclusion—HIV clinicians should consider risk factors that are not included in the traditional risk factor framework, particularly heavy alcohol consumption. Neglect of this risk factor may lead to underestimation of risk, and thus under-treatment among PLWH.

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Keywords HIV-infection; cardiovascular disease; alcohol; risk factors; review People living with HIV (PLWH) are living longer with the introduction of antiretroviral therapy (ART)1. As this population has aged, mortality related to chronic illness has

Address correspondence to Natalie E. Kelso, Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, 2004 Mowry Road, PO Box 100231, Gainesville, FL 32610, USA. [email protected]. Declaration of interest The authors report no real or perceived vested interests that relate to this article that could be construed as a conflict of interest.

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increased2. Cardiovascular disease (CVD) is attributable for 30% of deaths among those with well-controlled viral load (≤500 copies/ml)3, compared to 23.5% in the general US population4. Many clinicians and researchers rely on the validated Framingham Risk Score (FRS) to assess CVD risk, which considers age, cholesterol (total and HDL), blood pressure, smoking, and diabetes to predict 10-year risk for incident CVD5. While this score has been validated to apply in different cultures and races, it yields less accurate risk estimates for PLWH, due to risk factors not included in the FRS that are highly prevalent among PLWH6,7. Investigators have more recently utilized the D:A:D risk score, developed by the Data Collection on Adverse Effects of Anti-HIV Drugs group8, to assess CVD risk among PLWH. This risk score was developed in light of the need for a tailored CVD risk assessment tool for PLWH and includes traditional CVD risk factors and HIV related risk factors (current use of abacavir, indinavir, or lopinavir). The D:A:D score is used to classify 5-year probability for CVD as low (10%)9. The FRS and D:A:D scores do not include non-traditional risk factors, such as alcohol use. Currently, the impact of alcohol consumption on the development of CVD among PLWH is unclear.

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Moderate alcohol use may be protective against CVD and related events among the general population, such as myocardial infarction and stroke, compared to abstainers (odds ratio [OR] range 0.31–0.9610–15). Heavy alcohol use has been indicated as a significant risk factor for CVD compared to abstainers (OR range 1.05–5.3510–15), featuring a classic Jshaped curve. However, recent investigations indicate incongruent findings. One metaanalysis showed significantly increased risk only among those with alcohol use disorder, and no difference in risk among lifetime chronic heavy drinkers, compared to lifetime abstainers16. Further, alcohol consumption at any level is detrimental to cardiovascularrelated risk, such as atrial fibrillation17, while another study found that alcohol use at any level was cardio-protective among those with hypertension, compared to abstinence18. The relationship between alcohol consumption and CVD has not been well described among PLWH. Heavy alcohol use among PLWH is nearly twice the rate compared to uninfected populations19, with 15–20% reporting hazardous use and 17–33% reporting binge drinking20, 21.

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Alcohol use is significantly associated with CVD risk factors, including dyslipidemia22–23, type II diabetes22, 25, tobacco use26 and depressive symptoms27. Alcohol consumption may also increase CVD among PLWH through chronic inflammation and immune activation, well-established risk factors for CVD28. HIV-infection alone results in increased inflammation and strain on the immune system29–32. Hazardous alcohol use independently increases inflammation33. Chronic inflammation increases the risk for microbial translocation, a process that occurs when the integrity of the endothelial wall of the gastrointestinal (GI) tract is compromised34, leading to more pro-inflammatory processes 34–36. This pathway of epithelial degradation can be linked to the increase of Ddimer plasma levels, which is associated with blood clotting and cardiovascular complications34–35. Alcohol use alone increases risk for microbial translocation, especially among persons with alcohol use disorders; however, even non-dependent heavy drinkers feature increased GI tract permeability that requires two weeks of abstinence to regain normal epithelial integrity36. Am J Drug Alcohol Abuse. Author manuscript; available in PMC 2016 November 01.

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Those with HIV are 50% more likely to develop CVD when controlling for CVD- and HIVrelated risk factors, compared to uninfected populations37. Only two studies have been conducted for which the main objective was to assess the relationship between alcohol consumption and CVD among PLWH38,39. However, numerous studies have assessed alcohol use as a covariate in answering a different question regarding CVD outcomes in this population40–50. Developing an in-depth understanding of the relationship between alcohol use and CVD has implications for better identification of PLWH that may be at high risk for CVD, which could lead to greater prevention of this comorbid chronic illness. By reviewing the peer-reviewed literature, we aim to 1) summarize the current literature and strength of evidence regarding alcohol consumption as a risk factor for CVD among PLWH, 2) generate summary measures for the effects of alcohol consumption on CVD outcomes, and to 3) make recommendations for clinical practice and future research based on the findings and limitations of existing studies.

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Methods

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Pubmed/Medline was used to identify relevant peer-reviewed articles published between January 1, 1999 and January 1, 2014. The following MeSH terms were used: ‘HIV or human immunodeficiency virus or AIDS or acquired immunodeficiency syndrome’ AND ‘myocardial infarction or embolism or acute coronary syndrome or angina pectoris or aortic aneurysm or cardiovascular disease or cardiovascular system or carotid artery disease or coronary disease or coronary artery disease or heart failure or peripheral arterial disease or peripheral vascular disease or stroke’. Case reports, case series, editorials, abstracts from scientific meetings, comments, systematic reviews, news, newspaper articles, or articles that English copy was not available were excluded. Titles of all articles were screened for relevance; abstracts of articles with seemingly applicable titles were reviewed for eligibility. Titles and/or abstracts were excluded if it was clear that inclusion criteria were not met, particularly if PLWH was not the population under study, if hard clinical CVD outcomes were not used, or if any of the previously mentioned publication types were not adequately filtered through the Pubmed/Medline search process (specifically case reports). Most of the excluded articles were excluded for more than one of the aforementioned reasons. Articles with abstracts that were appropriate for further review were retrieved for full-text review. Eligible studies included observational or randomized controlled trials that met the following criteria: (1) measured CVD diagnoses or events as the outcome, (2) assessed any measurement of alcohol consumption as a covariate, (3) reported a crude or adjusted risk estimate in the form of risk ratio (RR), odds ratio (OR), or hazard ratio (HR) of alcohol consumption on CVD outcome or reported the information necessary to calculate the risk estimate, (4) stratified the analysis by HIV status and (5) included those 16 years of age or older. Thirteen studies met criteria for inclusion (Figure 1). Potential sources of bias were examined by noting the following qualities of each study: 1) validity of CVD assessment, 2) validity of alcohol measurement, 3) temporality of alcohol consumption and CVD assessment and 4) whether effects were adjusted for possible confounders.

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Measures

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The outcome of interest was CVD diagnosis, including coronary heart disease (CHD), cardiovascular or cerebrovascular disease, myocardial infarction (MI), stroke, ischemic heart disease. Subclinical cardiovascular outcomes were not considered (such as those indicated by carotid intima media thickness CIMT or coronary calcium scores). The studies were categorized as having a valid outcome classification if standard diagnostic tests (e.g., noninvasive imaging or invasive procedure, such as cardiac catheterization), validated measures (ICD-9/10 codes with review of medical chart or standardized diagnosis tests) were used to diagnose CVD. Studies with less valid outcome classification used self-report (Rose Chest Pain Questionnaire51) and/or ICD-9/10 codes alone to classify CVD without verification through standardized diagnostic tests or chart review, as these have been shown to be less valid measures52–54.

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Any measure of alcohol consumption was acceptable for inclusion. Differentiation of heavy and/or moderate alcohol consumption, temporality of measurement (exposure precedes outcome), and type of measurement (multiple time-points, cumulative lifetime exposure, or single time-point) were of particular interest. Studies were classified as using valid (specified level of alcohol use; alcohol measure preceded CVD outcome; cumulative alcohol use or use at multiple times points was measured) or less valid (no specified level of alcohol use measured; cross-sectional measure of exposure and outcome; alcohol use was measured at a single time-point) measurements of alcohol consumption. Data extraction

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The following information was extracted from the included studies: authors, year of publication, study design, study period, sample size, mean sample age, sample location, gender proportion, CVD measure, alcohol use definition, crude and adjusted risk ratios, and 95% confidence intervals (95% CIs). Because raw data were not available for all of the studies identified, exploratory summary estimates were calculated, weighted by sample size55. First each study was assign a weight based on sample size, with n=100 being assigned a weight of 1.0. Second, risk ratios and confidence intervals were log(ln) transformed to effect sizes, and multiplied by the studies unique weight. Third, the weights and weighted effect sizes were respectively summed. The summed weighted effect size was divided by the summed weight, giving a pooled weighted effect size. Finally, pooled effect sizes and relative confidence intervals were transformed back to risk ratios.

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Study characteristics are summarized in Table 1. Of the 13 studies included, 6 were crosssectional, 3 were cohort, and 4 were nested case-control studies. The mean age across studies ranged from about 34 to 53 years. Males made up the majority of the samples in all but one study. In general, the prevalence of a CVD diagnosis or event ranged from 5.7%– 24.0% (average 16.2%), excluding nested case-control studies. CVD prevalence varied greatly depending on the specificity of the CVD outcome (cerebral events 14.7%46; cardiomyopathy 17.7–24%48, 49; angina pectoris 20.4%50; combined CVD outcomes 5.7– 14.6%39, 47). Incidence of any CVD outcome among prospective studies ranged from

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0.4/1000–7.5/1000 person-years38,44,45. Two studies had 1) a valid measure of CVD, 2) a valid measurement of alcohol consumption that distinguished heavy use, 3) a measure of alcohol consumption that preceded the CVD outcome, and 4) an adjusted risk estimate38, 41. Two studies had 3 of the 4 specified qualities, six studies featured 2, two study featured 1, and one study featured none of these qualities. Nine studies used valid classifications of CVD. Less-valid CVD classification was used by four of the studies, with three studies utilizing medical registries or ICD-9/10 diagnostic codes only; one study used both ICD-9/10 codes and self-report. Five studies measured a combined CVD outcome and 8 studies measured a specific CVD type (four on cerebral ischemic events/stroke, two on cardiomyopathy, one on acute MI, and one on angina pectoris).

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Measurement of alcohol consumption among these studies varied greatly. Of the studies, three used less valid, dichotomous measures of general alcohol use. While 10 studies used valid measures, specifying a level of alcohol consumption, only three studies distinguished incremental levels of consumption (number of drinks per day or week). Temporality of alcohol consumption on CVD outcome was evaluable in seven studies. The type of alcohol consumed (wine, beer, etc.) was not assessed in any of the studies.

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Twelve of the studies calculated or provided enough information to calculate a crude risk ratio. Crude effect estimates of general alcohol use (1.36–3.44), moderate use (0.44–1.31), and heavy use or abuse/dependence (0.68–40.57) on CVD had large ranges across studies and wide 95% CIs within studies (Figure 2). The sample size weighted, pooled crude risk ratios were 1.75 (95% CI 1.06, 3.17) for general and 1.78 (95% CI 1.09, 2.93) for heavy alcohol. Nearly all of the studies that measured heavy use indicated a crude risk estimate trending toward increased risk for CVD, compared to non-heavy use. Four studies provided adjusted risk estimates (Figure 3). In general, studies that presented adjusted estimates featured smaller 95% CI ranges within studies and less variation in estimates across studies, compared to crude estimates. The sample size weighted, pooled adjusted risk ratio was 1.37 (95% CI 1.02, 1.84) for heavy alcohol use. Adjusted estimates tended to indicate that heavy alcohol use was associated with increased risk for CVD, compared to non-heavy use. Pooled estimates differed between studies with similar CVD outcome and alcohol measure (cerebral/ischemic events OR 1.76, 95% CI 1.12, 2.79; combined/any CVD OR 1.05, 95% CI 0.30, 3.71) and the alcohol effect was strongest among studies of cerebral or ischemic events. Study Summaries

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Key information about each study in included in Table 1, however additional information is provided here. Belloso et al. (2010)40 utilized a retrospective cohort study of patients receiving HIV-related care, across 8 sites in Latin America, to conduct a nested case-control analysis of the risk factors for CVD. The study sample consisted of 40 cases, and 120 controls matched on gender and age-group. Standardized diagnostic criteria were used to identify cases of CVD through medical chart review. History of alcohol abuse preceded CVD diagnosis and was identified through retrospective chart review and was not significantly associated with increased risk for CVD (OR 1.14; 95% CI 0.27, 4.75).

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Carrieri et al. (2012)38 conducted an 11-year prospective cohort study, across 47 clinics in France, to assess the impact of ART and alcohol consumption on CVD. Medical records were evaluated and validated by cardiologists to determine the outcome of cardiovascular events. Alcohol consumption was measured in alcohol units (AU) consumed per day, was measured at multiple time points, and preceded incident CVD. Moderate users had a significantly lower crude (OR 0.44; 95% CI 0.24, 0.81) and adjusted risk (OR 0.38; 95% CI 0.20, 0.71) for incident CVD, while heavy users did not feature significant crude (OR 1.04; 95% CI 0.30, 3.58) or adjusted risk (OR 0.46; 95% CI 0.13, 1.63), compared to abstainers. Adjusted analyses included demographic, psychosocial (including smoking), and clinical characteristics.

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A study by Corral et al. (2009)41 utilized data from a prospective cohort study of PLWH, recruited from a teaching hospital in Spain, to create a nested case-control study on the incidence of and risk factors for cerebrovascular ischemic events. The sample included cases of diagnosed ischemic stroke or TIA (n=25) during the 12-year study period and unmatched controls enrolled from the same clinic (n=100). The outcome was identified through CT and/or MRI reviewed by at least 1 neurologist. A binary measure of alcohol consumption history of > 50g/day (considered alcohol abuse) was obtained through retrospective review of medical charts. Alcohol abuse was higher in cases (32%) than controls (5%) and was associated with an increased crude (OR 8.94; 95% CI 2.6, 30.6) and adjusted risk (OR 7.13; 95% CI 1.69, 30.11) for ischemic events. The adjusted analysis included smoking, previous diagnosis of AIDS, CD4 count, HIV viral load, and duration of HAART.

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Durand et al. (2011)42 conducted a nested case-control analysis of two administrative databases widely used in Québec, Canada for those with public insurance to assess the association between ART and acute MI, selecting up to 10 controls per case within the HIVinfected cohort that did not have an acute MI, matched on age, gender, and cohort entry date Acute MI was assessed by diagnostic codes and review of discharge summaries. A dichotomous measure of alcohol abuse at any time before acute MI or end of follow-up was identified through the administrative databases. Alcohol abuse was slightly lower among those with acute MI than those without (11% vs. 16%, respectively) and was not associated with risk for acute MI (OR 0.68; 95% CI 0.38, 2.21).

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A second study conducted by Durand et al. (2013)43 assessed the risk factors for incident spontaneous intracranial hemorrhage (ICH) in the same sample above. Cases with ICH were identified through diagnostic codes only. A dichotomous measurement of baseline alcohol abuse, preceding the outcome, was accessed through diagnostic codes. The same nested case-control methods were used as the previous study. The sample included 29 cases and 228 controls. Alcohol abuse was significantly higher among cases than controls (34% vs. 12%, respectively) and was associated with an increased crude risk for ICH (OR 3.98; 95% CI 1.50, 10.55), compared to no abuse. Using the multi-centered Veterans Aging Cohort Study (VACS), Freiberg et al. (2010)39 conducted a cross-sectional study of the relationship between alcohol consumption and CVD. CVD was measured through ICD-9 or CPT codes and by self-report. The Alcohol Use Identification Test (AUDIT)56 was used to assess frequency and quantity of alcohol

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consumption; ICD-9 codes were used to identify history of abuse/dependence. Alcohol consumption and CVD were assessed at the same time point, limiting temporal evaluation. When compared to infrequent/moderate drinking, hazardous drinking (OR 1.35; 95% CI 1.01, 1.79) and abuse/dependence (OR 1.51; 95% CI 1.09, 2.09) were associated with increased risk for CVD, controlling for age, race, and CVD risk factors. The risk estimates increased somewhat after adding education and HIV-related risk factors to the previous model (hazardous: OR 1.43; 95% CI 1.05, 1.94; abuse/dependence: OR 1.55; 95% CI 1.07, 2.23; past drinking: OR 1.33; 95% CI 0.99, 1.80).

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Justice et al. (2008)44 conducted a retrospective cohort study of two large databases containing information on PLWH to assess the risk factors for incident ICH: The US Veterans Health Information System-Virtual Cohort and The California state Medicaid HIV databases. Incident ICH was identified through ICD-9 codes only. Alcohol abuse/ dependence was obtained from the administrative databases. Temporality of alcohol use/ dependence was not reported. Abuse/dependence was higher among those with incident ICH, compared to those without incident ICH (Veterans: 33% vs. 20%; Medicaid: 15% vs. 10%, respectively) and was associated with a higher crude risk for ICH in both cohorts (Veterans: OR 1.97; 95% CI 0.96, 4.08; Medicaid: OR 1.69; 95% CI 1.28, 2.26). After combining both cohorts, the risk of alcohol abuse/dependence on incident ICH was 1.40 (95% CI 1.07, 1.83), controlling for age, race, vascular disease, liver disease, AIDS, and cohort type.

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A longitudinal cohort study was conducted by Lichtenstein et al. (2010)45 to evaluate the impact of CD4+ T cell count on incident CVD (MI, stroke, CAD, angina, and peripheral arterial disease) among 10 HIV clinics. Baseline alcohol consumption level and incident CVD were identified through trained medical chart abstraction, and data were reviewed for quality assurance. Translating crude CVD incidence rates into incident rate ratios with no drinking as the reference, those that drank 14 drinks/week had 1.26, 1.31, and 1.89 times the odds for incident CVD, although this was insignificant. Data were not available to calculate 95% confidence intervals; therefore, these estimates could not be included in the pooled estimates.

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A cross-sectional study by Longo-Mbenza et al. (2011)46 evaluated risk factors associated with ischemic stroke among 116 PLWH, recruited at a teaching hospital in the Democratic Republic of Congo, Africa. Evaluation of clinical symptoms, cardiac enzymes (CKMB, troponin), and tests (electrocardiograms, transthoracic electrocardiography, and coronary angiograms) were used for standardized diagnosis of ischemic stroke, based on diagnostic definitions from the National Institute of Neurological Disorders and Stroke criteria. A dichotomous variable of excessive alcohol use was assessed; definition of excessive use was not reported. Alcohol consumption and history of ischemic stroke were assessed at the same time point, limiting temporal evaluation. Excessive alcohol use was higher among the stroke (94%) versus non-stroke group (28.6%), and was associated with an increased crude risk for stroke (OR 40.6; 95% CI 5.1, 320.6). Orlando et al. (2012)47 consecutively recruited men living with HIV on ART from a metabolic clinic to investigate the cross-sectional association between ectopic fat and

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cardiovascular events. Cardiovascular events were identified through medical chart abstraction, and were verified using standardized CVD criteria. Self-report of current alcohol consumption (any vs. none) was used. Alcohol consumption and history of CVD were assessed at the same time point, limiting temporal evaluation. Alcohol consumption was higher among those with CVD (48%), compared to those without CVD (40.7); however, the crude association between alcohol use and CVD was insignificant (OR 1.40; 95% CI 0.69, 2.83), compared to abstinence.

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Roy et al. (1999)48 consecutively recruited newly diagnosed PLWH, admitted to a hospital for HIV-related complications, to assess risk factors of cardiomyopathy. M-mode and twodimension echocardiograms was used to measure diffuse left ventricular hypokinesia (with fractional shortening of ≤24%) and left ventricular dilation (end diastolic dimension ≥59mm). A dichotomous variable of excessive alcohol use was used; the definition was not described. Excessive alcohol use and prevalent cardiomyopathy were assessed at the same time point, limiting temporal evaluation. There was no statistically significant difference in excessive alcohol use among those with cardiomyopathy (25%), compared to those without cardiomyopathy (20%; OR 1.31; 95% CI 0.40, 4.26).

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In 2007, Twagirumukiza et al.49 conducted a cross-sectional analysis on the prevalence and risk factors of dilated cardiomyopathy among untreated PLWH consecutively enrolled from two teaching hospitals in Rwanda, Africa. Echocardiograms measured diffuse left ventricular hypokinesia and dilation. Diffuse left ventricular hypokinesia was considered present if ejection fraction was less than 45%; dilation was considered present if enddiastolic volume index was over 80 ml/m2. A non-specific, dichotomous measure of current general alcohol consumption was used. Alcohol use and prevalent cardiomyopathy were assessed at the same time point, limiting temporal evaluation. Alcohol use was higher among those with dilated cardiomyopathy (80.3%), compared to those without (54.2%) and was associated with an increased crude risk for dilated cardiomyopathy (OR 3.44; 95% CI 1.78, 6.73), compared to abstinence.

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A cross-sectional study of the risk factors for angina pectoris was conducted by Zirpoli et al. (2012)50. The study sample included PLWH who were recruited from two hospitals in Brazil, and who had no history of CHD, MI, or revascularization surgery before HIV diagnosis. Angina pectoris was assessed by the validated Rose Chest Pain Questionnaire 52. Those with definite or possible angina were considered positive for the outcome. A nonspecific, dichotomous measurement of alcohol use was used; details of the measure were not provided. Alcohol consumption and angina pectoris were assessed at the same time point, limiting temporal evaluation. Alcohol use was more prevalent among those with angina pectoris and associated with increased crude risk for angina (OR 1.36; 95% CI 0.90–2.07), compared to abstinence.

Discussion Our review suggests that standardized and validated assessments of clinical CVD are commonly used, although many studies focused on different measures of CVD. Assessment of alcohol consumption is far from standard when conducting research regarding the risk

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factors of CVD among PLWH, with only 13 articles being identified for this review. Although most studies distinguished heavy alcohol consumption, many of these were binary. The use of binary measurements is a potential limitation, since this measurement does not allow the assessment of gradient effects of alcohol consumption on CVD. Nearly all studies assessing heavy alcohol consumption indicated an increased risk for CVD, after adjusting for other risk factors. Carrieri et al. (2012)38 found moderate alcohol consumption to be associated with lower risk for CVD. Together, these results suggest a possible J-shaped curve in the relationship between alcohol consumption and CVD among PLWH. However, more research is needed to further substantiate this non-linear relationship among PLWH. Sample characteristics varied across studies. All but one sample was primarily male, with females representing less than one-third in 10 samples. Among the studies that reported, females accounted for 3% to 46% of those with the CVD outcome of interest. Additionally, no studies stratified analyses by gender. Due to the low representation of females, results may not be generalizable to women living with HIV-infection.

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Limitations

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Several limitations exist across all of the studies regarding classification of CVD, measurement of alcohol consumption, generalizability, and the resulting estimates, as previously noted. Additionally, some studies lacked description of sampling strategy or alcohol consumption ascertainment and categorization. Although some studies provided adjusted estimates of alcohol consumption risk on CVD, several CVD-related factors were not controlled for (e.g., smoking status, body mass index, hypertension, diabetes, LDL and HDL cholesterol, and triglyceride level), which may have resulted in inaccurate estimates. Notably, there was greater consistency of risk ratios between studies that controlled for confounders, compared to the studies using unadjusted risk ratios. Outcome misclassification is a potential limitation for all studies, but to a greater degree among studies that used less valid outcome classification.

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Limitations of this systematic review include the fact that the data presented in many studies were collected across the pre- and post-ART eras. Links between access to ART and CVD risk57 and type58 have been indicated in extent research. However, the studies with adjusted estimates that control for ART use should be less effected by this source of confounding. Second, only articles published in the past 15-years were considered for review; however, it has been within this timeframe that CVD has been widely recognized as a seriously health outcome among PLWH. Because the search strategy was not limited to articles that had a MeSH term or keyword of ‘alcohol’, we were able to include many studies that included alcohol consumption as a covariate that may not have been captured otherwise. Third, because raw data was not available among all studies, traditional meta-analysis methods could not to be conducted. Related, there was apparent heterogeneity of CVD type, alcohol consumption measurement, sample characteristics, and type of risk ratio calculated across the studies. Because raw data were not available to assess heterogeneity of effects, and fixed and random pooled estimates, we conducted less valid methods to calculate exploratory pooled estimates, which we believe are helpful in understanding the state of the current literature.

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While alcohol consumption is almost always restricted to self-report, utilization of more valid instruments that assess the frequency and quantity of standard alcohol units are recommended, such as the AUDIT56. Future research should also include alcoholic beverages types consumed (wine, beer, liquor) as a potential research focus in order to understand unique properties that are cardio-protective or harmful. While traditional assessment of alcohol consumption has relied on self-report, there are several biological biomarkers that can be utilized to verify and even improve self-report59. Phosphatidylethanol (PEth), a metabolite of alcohol measured in blood, has shown to be a useful biomarker of alcohol consumption that is highly correlated with number of drinking days during the 21 days prior to testing60. Further, concurrent use of the PEth test and selfreport was associated with increased report of 3-month alcohol consumption from 6% to 34% in women and 35% to 48% in men61. Longitudinal assessment of alcohol consumption over time is also recommended to effectively assess whether health effects change as alcohol consumption changes. Alcohol consumption risk estimates of CVD should be adjusted for possible confounding factors, as unadjusted risk estimates may lead to inaccurate estimation. Finally, future research should include on HIV-infected females, as this population was understudied in this review. In conclusion, alcohol use has been linked to CVD in PLWH and is a factor that can confer substantial risk, similarly to that of increased cholesterol and other traditional CVD risk factors. Clinicians should consider risk factors that are not included in the FRS, yet are quite salient among PLWH, particularly alcohol consumption. Neglect of this risk factor may lead to underestimation of risk, and thus under-treatment among PLWH.

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Author Manuscript Author Manuscript Figure 1.

Study Selection Process.

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Author Manuscript Author Manuscript Figure 2.

Author Manuscript

Crude effect sizes of alcohol use on cardiovascular disease by study. Reference for ‘Any Use’ is no alcohol use; aReference is abstinent to low alcohol use; bReference is no alcohol abuse or dependence; cReference is less than ‘excessive’ alcohol use; OR = odds ratio; 95% CI= confidence interval; Square marker refers to the study effect size; Diamond marker refers to pooled effect size. Horizontal line refers to the 95% CI; Vertical line refers to an OR of 1.0, indicating no effect. Horizontal lines reaching the end of the graph indicate OR or upper 95% CI limit is above 15.0.

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Author Manuscript Author Manuscript Figure 3.

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Adjusted effect sizes of heavy alcohol use on cardiovascular disease by study providing adjusted risk estimates. aReference is abstinent to low alcohol use; bReference is less than ‘excessive’ alcohol use; cReference is infrequent to moderate alcohol use; dReference is no alcohol abuse or dependence; OR = odds ratio; 95% CI= confidence interval; Square marker refers to the study effect size; Diamond marker refers to pooled effect size; Horizontal line refers to the 95% CI; Vertical line refers to an OR of 1.0, indicating no effect. Horizontal lines reaching the end of the graph indicate upper 95% CI limit is above 15.0.

Author Manuscript Am J Drug Alcohol Abuse. Author manuscript; available in PMC 2016 November 01.

NCC

CO

NCC

NCC

NCC

CS

CO

CO

CS

CS

Belloso (40) 2010

Carrieri (38) 2012

Corral (41) 2009

Durand (42) 2011

Durand (43) 2013

Freiberg (39) 2010

Justice (44) 2008

Lichtenstein (45) 2010

Longo-Mbenza (46) 2011

Am J Drug Alcohol Abuse. Author manuscript; available in PMC 2016 November 01.

Orlando (47) 2012

2005–2009

2004–2008

2002–2009

1997–2003

2002–2006

1985–2007

1985–2007

1996–2008

1997–1999

1997–2007

Study Period

583

116

2005

S1: 16,541 S2: 28,023

2,422

257

1,209

125

1,154

160

Study Size

53 [CVD] 47 [No CVD]

45.3 [Male] 42.5 [Female]

42

39–46

49.1

39.6

49.0 [Cases] 47.5 [Controls]

46.8 [Cases] 45.8 [Controls]

37.7

Not reported

Mean Age (years)

Italy

Dominican Republic of Congo

USA

USA

USA

Canada

Canada

Spain

France

Latin America

Location

Author Manuscript

Study Design

100

46.6

76.4

S1: 98 S2: 79

100

78

78

76

78

70

Male (%)

Author Manuscript

First Author (ref) year

MI, coronary revascularization, stroke, or peripheral vascular disease

Ischemic stroke

MI, non-embolic/nonhemorrhagic stroke, CAD, angina, or peripheral arterial disease

Intracranial hemorrhage

Angina or CHD, an MI, CHF or stroke or TIA

Intracranial hemorrhage

Acute MI

Cerebral ischemic events

MI, stroke, CHD, peripheral arterial disease, and cardiovascular survey for coronary disease

Acute MI, CVD requiring an invasive procedure, or stroke

CVD measure

5.7

Alcohol use

Excessive drinking

Abstinence (Ref) 14 drinks/week Missing

0.4 – 3.0

14.7

Alcohol abuse or dependence

Infrequent to moderate ≤ 14 drinks/ week with no binge drinking (Ref) Hazardous > 14 drinks/week or binge drinking Alcohol abuse/dependence

Alcohol abuse

Alcohol abuse at any time before outcome or end of follow-up

S1: 0.4 S2: 4.0

14.6

N/A

N/A

Alcohol consumption > 50 g/day

Abstainers (Ref) Moderate ≤ 4(3) AU/day for men(women) Heavy >4(3) AU/day for men(women)

7.5

N/A

History of admission because of alcohol-related conditions or a history of alcohol consumption that compromises daily activities

Alcohol Use Definition

N/A

CVD Prevalence (%) Incidence (per 1000 person years)

Author Manuscript

Characteristics of study populations (N=13).

40.7

38.0

50.0 34.0 6.0 4.0 6.0

S1: 20.3 S2: 9.6

45.9 33.2 20.9

14.8

15.2

10.4

18.8 75.3 5.9

6.8

Alcohol Use Prevalence (%)

1.40 (0.69, 2.83)NS

40.57 (5.13, 320.6)

14 drinks/week: 1.89c

1.97 (0.96, 4.06)NS 1.69 (1.27, 2.23)

3.98 (1.50, 10.55)

0.68 (0.38, 2.21)NS

8.94 (2.6, 30.6)

Moderate 0.44 (0.24, 0.81) Heavy 1.04 (0.3, 3.58)NS

1.14 (0.27, 4.75)NS

Crude Risk Estimate

Combined 1.40 (1.07, 1.83)

Hazardous 1.35 (1.01, 1.79)a 1.43 (1.05, 1.94)b Abuse/Dependence 1.51 (1.09, 2.09)a 1.55 (1.07, 2.23)b

7.13 (1.69, 30.1)

Moderate 0.38 (0.20, 0.71) Heavy 0.46 (0.13, 1.63)NS

Adjusted Risk Estimate

Author Manuscript

Table 1 Kelso et al. Page 17

CS

CS

Twagirumukiza (49) 2007

Zirpoli (50) 2012

2007–2008

2005

1994–1995

584

416

84

39.8 [Male] 36.8 [Female]

34.6

38.8

Mean Age (years)

Latin America

Rwanda

USA

Location

63.2

62

77

Male (%)

Angina pectoris

Cardiomyopathy

Cardiomyopathy

CVD measure

20.4

17.7

24.0

Alcohol use

Alcohol use

Excessive alcohol consumption

Alcohol Use Definition

42.9

58.7

21.4

Alcohol Use Prevalence (%)

1.36 (0.90, 2.07)NS

3.44 (1.78, 6.73)

1.31 (0.40, 4.26)NS

Crude Risk Estimate

Adjusted Risk Estimate

Adjusted model 2;

95% CI not available.

c

b

Adjusted model 1;

a

Not Significant; CVD, cardiovascular disease; MI, myocardial infarction; CHD, coronary heart disease; CHF, congestive heart failure; CAD, coronary artery disease; Ref, reference; 95% CI, 95% confidence interval; CS, cross-sectional; CC, nested case-control; CO, cohort; S1, virtual cohort sample; S2, California state Medicaid-derived sample;

NS

CS

Roy (48) 1999

Study Size

Author Manuscript

Study Period

Author Manuscript

Study Design

Author Manuscript

First Author (ref) year

Author Manuscript

CVD Prevalence (%) Incidence (per 1000 person years)

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