Effect-size data were entered and standardized before analysis. Odds ratios (ORs) were chosen for the effect size metric because the majority of studies compared 2 categories of alcohol use (eg, drinkers vs. nondrinkers; 72.5% of studies) on a dichotomous adherence indicator variable (eg, adherent vs. nonadherent, 77.5% of studies). Nine studies (20.5%) included multiple comparisons involving an alcohol-related indicator (eg, any use vs. none in addition to problematic vs. nonproblematic use or none). In order not to violate the assumption of independence of effect sizes, we did not include more than 1 comparison per study per analysis. Two alternative ways to extract effect sizes from these studies were explored: selecting the least extreme comparison (alternative 1; eg, any vs. no alcohol) and computing the average effect size (alternative 2). When studies included multiple adherence outcomes (eg, proportion of doses and timing of doses), 1 measure reflecting proportion of doses taken was selected because this was the primary outcome for most studies. If more than 1 adherence cutoff (eg, 90% and 100%) was evaluated in relation to drinking, the more stringent cutoff was used.
Under the random effects model, the point estimate and 95% CI for the combined studies was 0.548 (0.490 to 0.612), Z = −10.633, P < 0.001, indicating that those who used alcohol, or who drank relatively more, were 0.548 times as likely to be classified as adherent as compared with nonusers, or those who drank relatively less. Sensitivity analysis found no individual effect size to unduly influence the estimate of the overall effect; therefore, all were retained. The primary analysis used the most extreme comparison for those studies that included comparison of multiple drinking levels. As might be expected, alternative methods of effect-size extraction altered the estimate of the overall effect. Using alternative 1, the overall OR was estimated to be 0.628 (0.568 to 0.695), Z = −9.042, P < 0.001, indicating that when using the least extreme comparison per study, drinkers were 0.628 times as likely to be classified as adherent compared with nonusers. Using alternative 2, the overall OR was estimated to be 0.586 (0.531 to 0.647), Z = −10.647, P < 0.001, indicating that, when collapsing across multiple comparisons per study, alcohol users were 0.586 times as likely to be classified as adherent as nonusers.
Participants classified as problem drinkers, defined in accordance with NIAAA guidelines for at-risk drinking or based on meeting diagnostic criteria for a probable alcohol use disorder, were 0.474 (0.408 to 0.550) times as likely as nonproblem drinkers or abstainers to be classified as adherent (14 effect sizes, Q (13) = 13.034, Z = −9.803, P < 0.001). Among studies examining drinking thresholds classified as moderate (ie, falling short of problem drinking criteria), drinkers were 0.480 (0.360 to 0.639) times as likely as abstainers, or those who consumed less, to be adherent (6 effect sizes, Q (5) = 2.180, Z = −5.021, P < 0.001). Among studies examining any or global alcohol use (eg, any use in the past year vs. none), the combined OR was 0.604 (0.531 to 0.687) (20 effect sizes, Q (19) = 17.312, Z = −7.704, P < 0.001). Overlap in the CIs for the effect sizes by level of drinking intensity indicates that, although the effect sizes are significantly different from zero, they are not significantly different from each other.
Inspection of a funnel plot revealed slight asymmetry, which is an indicator of publication bias. The Trim and Fill Method65 indicated missing studies to the right of the mean. Eight studies were identified for trimming; the imputed point estimate was 0.638 (0.600 to 0.679). Because the imputed estimate is very close to observed estimate, 0.624 (0.585 to 0.664), and their CIs overlap considerably, publication bias seems to have been minimal.
This study provides the first meta-analytic evaluation of the association of alcohol use and antiretroviral adherence. Effect sizes for the combined studies suggested that those who used alcohol were 50%-60% as likely (OR = 0.548, 95% CI: 0.490 to 0.612) to be classified as adherent compared with those who abstained (or drank relatively less). Alcohol use that met or exceeded an objective threshold for problem drinking (defined as meeting NIAAA criteria for at-risk drinking or diagnostic criteria for an alcohol use disorder) was associated with the largest effect (OR = 0.474, 95% CI = 0.408 to 0.550), whereas the overall effect was smaller among studies examining any or global alcohol use (OR = 0.604, 95% CI = 0.531 to 0.687). Although these effect sizes were not significantly different from each other, they were significantly different from zero, and the point estimates can be viewed as broadly consistent with “dose-response” effects reported in previous studies.9,14,25,27
Several variables moderated the alcohol-adherence association. This association was stronger in samples that included a higher proportion of men, a finding that is inconsistent with previous reports suggesting that alcohol's effects on adherence are more prominent among women.28,29 The alcohol-adherence association was also stronger in samples with a lower reported prevalence of IDU. Given the established association of IDU with lower adherence, it is possible that any effects of alcohol on adherence are obscured in the context of IDU. The observation that effects were stronger in studies with larger samples presumably reflects greater statistical power. Aspects of alcohol use measurement also moderated the effects. Studies assessing both drinking quantity and frequency and those using the AUDIT (which assesses quantity and frequency) showed stronger effect sizes. A recent study found that when disaggregating the NIAAA at-risk drinking criteria into its 2 components (>4 drinks per day or >14 drinks per week), only the former predicted reduced adherence.26 Taken together, the available evidence suggests that drinking quantity is a more robust and important predictor of adherence than drinking frequency, a finding that seems consistent with dose-related alcohol effects on adherence.14,27 Dichotomous (compared with continuous) drinking outcomes were also associated with stronger effects, perhaps because studies using continuous measures tended to rely on global variables (eg, drinks per week) that did not index drinking quantity.
With respect to adherence assessment, moderator analyses indicated greater alcohol-related decrements in adherence in studies where adherence was defined using a higher criterion (eg, 100% vs. 90%). This result is consistent with event-level findings suggesting that alcohol's effects are more evident under more difficult adherence requirements66 and suggests that alcohol use might be particularly detrimental to achieving perfect or near perfect adherence. The alcohol-adherence association was also stronger when using continuous adherence measures. Continuous measures presumably afford greater statistical power and have been shown to explain the most variance in viral load.67 Incorporating continuous measures might allow more sensitive evaluation of alcohol-adherence associations in future studies. Finally, alcohol's effects on adherence were stronger when using assessment approaches other than self-report. Similarly, research on illicit drug use and adherence suggests that this association might be more reliable when using MEMS compared with self-report.68 Use of MEMS specifically was not a significant moderator in this study, perhaps due to low power given that only 4 studies used MEMS. Objective measures might be more likely to detect significant associations due to fewer sources of measurement error, including social desirability influences.67 Readers are referred elsewhere for comprehensive reviews of adherence assessment approaches.67,69,70
In addition to establishing provisional effect-size estimates, this study offers a basis for discussing methodologic and conceptual issues in research on alcohol and HAART adherence. A primary concern is the substantial heterogeneity in the measurement and definition of alcohol use across studies, which makes it difficult to compare and aggregate findings. Researchers are encouraged to use standardized assessment approaches that include validated and multidimensional measures of alcohol use. The AUDIT63 is a particularly useful measure given its brevity (10 items), established validity,71 and inclusion of items assessing drinking frequency, quantity, heavy episodes, and symptoms of alcohol dependence. Moreover, this measure is the recommended standard in primary care settings.64 Timeline followback approaches, although relatively more time consuming, are extremely useful for providing nuanced assessments of the daily covariation among drinking and adherence.25,26 Other event-level methods that permit fine-grained analyses72 warrant consideration in future studies. Relying solely on diagnostic criteria is probably less useful because traditional diagnostic schemes (and some brief screening methods) omit measures of drinking quantity, which is a significant limitation.73 Consistent with this reasoning, a recent study showed that drinking quantity/frequency, but not alcohol-related problems, predicted reduced adherence.35
Although the association of alcohol use and nonadherence is replicable and reliable, it remains difficult to speak to the causal nature of this association. The majority of studies included in this review were cross-sectional reports that evaluated global associations using retrospective measures of drinking and adherence. In a substantial proportion of studies, there was little or no overlap among the alcohol use and adherence assessment intervals. These limitations restrict the ability to infer causal effects and leave open the possibility that these associations could be attributable to other variables. If alcohol use is embedded in a broader context of problematic behaviors that also influence adherence, including IDU or other substance use, spurious associations could emerge (the association of tobacco use with nonadherence24 likely reflects this phenomenon). The possibility that alcohol use is simply a marker for broader substance use involvement cannot be ruled out based on the current analyses; however, our finding that the alcohol-adherence association was significantly stronger in the context of lower IDU argues against this possibility and suggests a unique association of alcohol with adherence. Moreover, recent studies using sophisticated measurement approaches25,26,66 provide compelling evidence that alcohol use is closely associated with decreased adherence. Continued use of these approaches would increase the ability to speak to causal associations. Researchers have also begun to examine specific intrapersonal and situational moderators of alcohol's effects on adherence.26,66 We suggest that future research should continue to evaluate potential moderators to clarify the conditions under which alcohol use is likely to influence adherence. Because the association of alcohol and nonadherence seems significant and reliable across studies, further efforts to evaluate global associations may do little to extend knowledge in this area. That noted, there is a dearth of research on this issue in developing countries and establishing basic associations of alcohol and adherence in these settings would be useful.
A notable aspect of this literature is the omission of theoretical frameworks for understanding alcohol's association with adherence. Of the studies included in this review, the vast majority did not discuss possible mechanisms for these effects. One intuitive mechanism is cognitive impairment, such that acute intoxication might interfere with one's capacity to plan for or remember dosing requirements.26 However, additional explanations are possible. Alcohol users might have decreased access to HAART74 or may use alcohol to reduce or avoid HIV-related negative mood states,75,76 a motive that could also lead one to neglect adherence requirements. It is also important to note that some patients intentionally skip medication doses when drinking due to misperceptions about possible toxic interactions.15,18,77 These various explanations each have unique theoretical and clinical implications for research and intervention at the intersection of alcohol and adherence. An important direction for future research is to specify mechanisms that explain the link between drinking and nonadherence, which should aid in identifying intervention targets. Such mechanisms are likely to involve cognitive factors such as alcohol-related beliefs, expectancies, and motives, in addition to environmental and event-level factors.
The present study has several limitations. Given that the measurement and definitions of drinking and adherence varied considerably across studies, effect sizes should be considered provisional and interpreted as relative (rather than absolute) estimates of the likelihood of nonadherence in the context of alcohol use. Although we imposed a relatively objective measure of drinking intensity in the stratification analyses, there was still heterogeneity within categories due to measurement differences across studies, and these analyses relied on a modest number of effect sizes. Results concerning significant moderators should also be interpreted with caution. Another limitation is the omission of unpublished studies, although there was minimal evidence of publication bias.
The current findings support the need for interventions that address alcohol use in the context of HAART.14,23 Given reported associations of alcohol use and immunologic function among those living with HIV/AIDS,9,19-22 successful alcohol interventions could potentially show salutary effects on disease progression and, theoretically, life expectancy.78 Few such interventions have been tested and more are needed.12 In a recent study,23 an alcohol/adherence intervention did not influence drinking but nonetheless led to improved adherence, decreased viral load, and increased CD4 cell counts, suggesting that adherence and biological outcomes can be improved even in the context of continued alcohol use. Similarly, meta-analytic research suggests that drug users often maintain adequate adherence, especially in the context of medical and psychosocial support.11 Interventions might therefore aim not only to reduce alcohol use but also to promote strategies for maximizing adherence among those who are unlikely or unwilling to cease drinking. These efforts will benefit from an improved characterization of alcohol's relation to adherence and identification of factors that mediate or moderate this association.
The authors thank Jacqueline M. Otto for her assistance with literature reviews.
1. Amico KR, Harman JJ, Johnson BT. Efficacy of antiretroviral therapy adherence interventions-research synthesis of trials, 1996 to 2004. J Acquir Immune Defic Syndr
2. Palella FJ, Delaney KM, Moorman AC, et al. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. N Engl J Med
3. Bartlett JA. Addressing the challenges of adherence. J Acquir Immune Defic Syndr
4. Bangsberg DR, Hecht FM, Charlebois ED, et al. Adherence to protease inhibitors, HIV-1 viral load, and development of drug resistance in an indigent population. AIDS
5. Bangsberg DR, Perry S, Charlebois ED, et al. Non-adherence to highly active antiretroviral therapy predicts progression to AIDS. AIDS
6. Quinn TC, Wawer MJ, Sewankambo N, et al. Viral load and heterosexual transmission of human immunodeficiency virus type 1. N Engl J Med
7. Simoni JM, Amico KR, Pearson CR, et al. Strategies for promoting adherence to antiretroviral therapy: a review of the literature. Curr Infect Dis Rep
8. Ammassari A, Trotta MP, Murri R, et al. Correlates and predictors of adherence to highly active antiretroviral therapy: overview of published literature. J Acquir Immune Defic Syndr
. 2002;31(Suppl 3):S123-S127.
9. Chander G, Lau B, Moore RD. Hazardous alcohol use: a risk factor for non-adherence and lack of suppression in HIV infection. J Acquir Immune Defic Syndr
10. Conigliaro J, Justice AC, Gordon AJ, et al. Role of alcohol in determining human immunodeficiency virus (HIV)-relevant outcomes: a conceptual model to guide the implementation of evidence-based interventions into practice. Med Care
11. Malta M, Magnanini MMF, Strathdee SA, et al. Adherence to antiretroviral therapy among HIV-infected drug users: a meta-analysis. Aids Behav
. In press. [Epub ahead of print, Nov. 2008].
12. Bryant KJ. Expanding research on the role of alcohol consumption and related risks in the prevention and treatment of HIV/AIDS. Subst Use Misuse
13. Galvan FH, Bing EG, Fleishman JA, et al. The prevalence of alcohol consumption and heavy drinking among people with HIV in the United States: results from the HIV cost and services utilization study. J Stud Alcohol
14. Samet JH, Horton NJ, Meli S, et al. Alcohol consumption and antiretroviral adherence among HIV-infected persons with alcohol problems. Alcohol Clin Exp Res
15. Brigido LFM, Rodrigues R, Casseb J, et al. Impact of adherence to antiretroviral therapy in HIV-1-infected patients at a university public service in Brazil. AIDS Patient Care STDS
16. Cook RL, Sereika SM, Hunt SC, et al. Problem drinking and medication adherence among persons with HIV infection. J Gen Intern Med
. 2001;16: 83-88.
17. Eldred LJ, Wu AW, Chaisson RE, et al. Adherence to antiretroviral and pneumocystis prophylaxis in HIV disease. J Acquir Immune Defic Syndr
18. Sankar A, Wunderlich T, Neufeld S, et al. Sero-positive African Americans' beliefs about alcohol and their impact on anti-retroviral adherence. AIDS Behav
19. Miguez MJ, Shor-Posner G, Morales G, et al. HIV treatment in drug abusers: impact of alcohol use. Addict Biol
20. Palepu A, Tyndall MW, Li K, et al. Alcohol use and incarceration adversely affect HIV-1 RNA suppression among injection drug users starting antiretroviral therapy. J Urban Health
21. Pence BW, Miller WC, Gaynes BN, et al. Psychiatric illness and virologic response in patients initiating highly active antiretroviral therapy. J Acquir Immune Defic Syndr
22. Samet JH, Cheng DM, Libman H, et al. Alcohol consumption and HIV disease progression. J Acquir Immune Defic Syndr
23. Parsons JT, Golub SA, Rosof E, et al. Motivational interviewing and cognitive-behavioral intervention to improve HIV medication adherence among hazardous drinkers: a randomized controlled trial. J Acquir Immune Defic Syndr
24. Peretti-Watel P, Spire B, Lert F, et al. Drug use patterns and adherence to treatment among HIV-positive patients: evidence from a large sample of French outpatients (ANRS-EN12-VESPA 2003). Drug Alcohol Depend
25. Braithwaite RS, McGinnis KA, Conigliaro J, et al. A temporal and dose-response association between alcohol consumption and medication adherence among veterans in care. Alcohol Clin Exp Res
26. Braithwaite RS, Conigliaro J, McGinnis KA, et al. Adjusting alcohol quantity for mean consumption and intoxication threshold improves prediction of nonadherence in HIV patients and HIV-negative controls. Alcohol Clin Exp Res
27. Tucker JS, Burnam MA, Sherbourne CD, et al. Substance use and mental health correlates of nonadherence to antiretroviral medications in a sample of patients with human immunodeficiency virus infection. Am J Med
28. Berg KM, Demas PA, Howard AA, et al. Gender differences in factors associated with adherence to antiretroviral therapy. J Gen Intern Med
29. Lazo M, Gange SJ, Wilson TE, et al. Patterns and predictors of changes in adherence to highly active antiretroviral therapy: longitudinal study of men and women. Clin Infect Dis
30. Murphy DA, Greenwell L, Hoffman D. Factors associated with antiretroviral adherence among HIV-infected women with children. Women Health
31. Murphy DA, Marelich WD, Hoffman D, et al. Predictors of antiretroviral adherence. Aids Care
32. Murphy DA, Belzer M, Durako SJ, et al. Longitudinal antiretroviral adherence among adolescents infected with human immunodeficiency virus. Arch Pediatr Adolesc Med
33. Spire B, Duran S, Souville M, et al. Adherence to highly active antiretroviral therapies (HAART) in HIV-infected patients: from a predictive to a dynamic approach. Soc Sci Med
34. Cook TD, Campbell DT. Quasi-Experimentation: Design and Analysis Issues for Field Settings
(1979). Boston: Houghton Mifflin Company; 1979.
35. Parsons JT, Rosof E, Mustanski B. Patient-related factors predicting HIV medication adherence among men and women with alcohol problems. J Health Psychol
36. Bonolo PD, Cesar CC, Acurcio FA, et al. Non-adherence among patients initiating antiretroviral therapy: a challenge for health professionals in Brazil. AIDS
37. Catz SL, Heckman TG, Kochman A, et al. Rates and correlates of HIV treatment adherence among late middle-aged and older adults living with HIV disease. Psychol Health Med
38. de Jong BC, Prentiss D, McFarland W, et al. Marijuana use and its association with adherence to antiretroviral therapy among HIV-infected persons with moderate to severe nausea. J Acquir Immune Defic Syndr
39. Golin CE, Liu HH, Hays RD, et al.A prospective study of predictors of adherence to combination antiretroviral medication. J Gen Intern Med
40. Heckman BD, Catz SL, Heckman TG, et al. Adherence to antiretroviral therapy in rural persons living with HIV disease in the United States. AIDS Care
41. Hicks PL, Mulvey KP, Chander G, et al. The impact of illicit drug use and substance abuse treatment on adherence to HAART. AIDS Care
42. Hinkin CH, Hardy DJ, Mason KI, et al. Medication adherence in HIV-infected adults: effect of patient age, cognitive status, and substance abuse. AIDS
. 2004;18(Suppl 1):S19-S25.
43. Holmes WC, Bilker WB, Wang H, et al. HIV/AIDS-specific quality of life and adherence to antiretroviral therapy over time. J Acquir Immune Defic Syndr
44. Holstad MKM, Pace JC, De AK, et al. Factors associated with adherence to antiretroviral therapy. J Assoc Nurses AIDS Care
45. Howard AA, Arnsten JH, Li YT, et al. A prospective study of adherence and viral load in a large multi-center cohort of HIV-infected women. AIDS
46. Johnson MO, Catz SL, Remien RH, et al. Theory-guided, empirically supported avenues for intervention on HIV medication nonadherence: findings from the healthy living project. AIDS Patient Care STDS
47. Kalichman SC, Rompa D. HIV treatment adherence and unprotected sex practices in people receiving antiretroviral therapy. Sex Transm Infect
48. Kleeberger CA, Phair JP, Strathdee SA, et al. Determinants of heterogeneous adherence to HIV-antiretroviral therapies in the multicenter AIDS cohort study. J Acquir Immune Defic Syndr
49. Liu H, Longshore D, Williams JK, et al. Substance abuse and medication adherence among HIV-positive women with histories of child sexual abuse. AIDS Behav
50. Martini M, Recchia E, Nasta P, et al. Illicit drug use: can it predict adherence to antiretroviral therapy? Eur J Epidemiol
51. Moatti JP, Carrieri MP, Spire B, et al. Adherence to HAART in French HIV-infected injecting drug users: the contribution of buprenorphine drug maintenance treatment. AIDS
52. Mohammed H, Kieltyka L, Richardson-Alston G, et al. Adherence to HAART among HIV-infected persons in rural Louisiana. AIDS Patient Care STDS
53. Moss AR, Hahn JA, Perry S, et al. Adherence to highly active antiretroviral therapy in the homeless population in San Francisco: a prospective study. Clin Infect Dis
54. Mugavero M, Ostermann J, Whetten K, et al. Barriers to antiretroviral adherence: the importance of depression, abuse, and other traumatic events. AIDS Patient Care STDS
55. Rothlind JC, Greenfield TM, Bruce AV, et al. Heavy alcohol consumption in individuals with HIV infection: effects on neuropsychological performance. J Int Neuropsychol Soc
56. Shannon K, Kerr T, Lai C, et al. Nonadherence to antiretroviral therapy among a community with endemic rates of injection drug use. J Int Assoc Physicians AIDS Care
57. Sharma M, Singh RR, Laishram P, et al. Access, adherence, quality and impact of ARV provision to current and ex-injecting drug users in Manipur (India): an initial assessment. Inl J Drug Policy
58. Sullivan PS, Campsmith ML, Nakamura GV, et al. Patient and regimen characteristics associated with self-reported nonadherence to antiretroviral therapy. PLoS ONE
59. Tesoriero J, French T, Weiss L, et al. Stability of adherence to highly active antiretroviral therapy over time among clients enrolled in the treatment adherence demonstration project. J Acquir Immune Defic Syndr
60. Wagner JH, Justice AC, Chesney M, et al. Patient- and provider-reported adherence: toward a clinically useful approach to measuring antiretroviral adherence. J Clin Epidemiol
61. Wilson TE, Barron Y, Cohen M, et al. Adherence to antiretroviral therapy and its association with sexual behavior in a national sample of women with human immunodeficiency virus. Clin Infect Dis
62. Ewing JA. Detecting alcoholism: the CAGE questionnaire. JAMA
63. Babor TF, Biddle-Higgins JC, Saunders JB, et al. AUDIT: The Alcohol Use Disorders Identification Test: Guidelines for Use in Primary Health Care
. Geneva, Switzerland: World Health Organization; 2001.
64. National Institute on Alcohol Abuse and Alcoholism. Helping Patients Who Drink Too Much. A Clinician's Guide
. 2005 Edition
. Washington, DC: National Institutes of Health, U.S. Department of Health and Human Services; 2005.
65. Duval SJ and Tweedie RL. Trim and fill: a simple funnel plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics
66. Parsons JT, Rosof E, Mustanski B. The temporal relationship between alcohol consumption and HIV-medication adherence: a multilevel model of direct and moderating effects. Health Psychol
67. Pearson CR, Simoni JM, Hoff P, et al. Assessing antiretroviral adherence via electronic drug monitoring and self-report: an examination of key methodological issues. AIDS Behav
68. Hinkin CH, Barelay TR, Castellon SA, et al. Drug use and medication adherence among HIV-1 infected individuals. AIDS Behav
69. Bova CA, Fennie KP, Knafl GJ, et al. Use of electronic monitoring devices to measure antiretroviral adherence: practical considerations. AIDS Behav
70. Simoni JM, Kurth AE, Pearson CR, et al. Self-report measures of antiretroviral adherence: a review with recommendations for HIV research and clinical management. AIDS Behav
71. Reinert DF, Allen JP. The alcohol use disorders identification test: an update of research findings. Alcohol Clin Exp Res
72. Stone AA, Shiffman S. Ecological momentary assessment (EMA) in behavorial medicine. Ann Behav Med
73. Martin CS, Chung T, Langenbucher JW. How should we revise diagnostic criteria for substance use disorders in the DSM-V? J Abnorm Psychol
74. Tucker JS, Orlando M, Burnam MA, et al. Psychosocial mediators of antiretroviral nonadherence in HIV-positive adults with substance use and mental health problems. Health Psychol
75. McKirnan DJ, Ostrow DG, Hope B. Sex, drugs and escape: a psychological model of HIV-risk sexual behaviours. AIDS Care
76. Nemeroff CJ, Hoyt MA, Huebner DM, et al. The cognitive escape scale: measuring HIV-related thought avoidance. AIDS Behav
77. Kalichman SC, Amaral CM, White D, et al. Prevalence and clinical implications of interactive toxicity beliefs regarding mixing alcohol and antiretroviral therapies among people living with HIV/AIDS. AIDS Patient Care STDS
78. Braithwaite RS, Conigliaro J, Roberts MS, et al. Estimating the impact of alcohol consumption on survival for HIV+ individuals. AIDS Care