Skip to main content

Some NLM-NCBI services and products are experiencing heavy traffic, which may affect performance and availability. We apologize for the inconvenience and appreciate your patience. For assistance, please contact our Help Desk at info@ncbi.nlm.nih.gov.

NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2006 Feb 2.
Published in final edited form as: Drug Alcohol Depend. 2005 Mar 2;79(2):251–256. doi: 10.1016/j.drugalcdep.2005.01.015

Alcohol use and HIV risk behaviors among HIV-infected hospitalized patients in St. Petersburg, Russia

Evgeny M Krupitsky a, Nicholas J Horton b, Emily C Williams c,e,f, Dmitri Lioznov a, Maria Kuznetsova a, Edwin Zvartau a, Jeffrey H Samet c,d,*
PMCID: PMC1360173  NIHMSID: NIHMS4058  PMID: 16002034

Abstract

Purpose: Russia has high per capita alcohol consumption and an injection-drug-use-driven HIV epidemic. However, the role of alcohol in the spread of HIV infection in Russia is largely unexplored. Thus, we assessed recent alcohol use and associated HIV risk behaviors among HIV-infected persons in St. Petersburg, Russia.

Methods: We recruited HIV-infected hospitalized patients from the Botkin Infectious Disease Hospital between June 2001 and March 2002. Interviewers assessed alcohol and drug use with the addiction severity index (ASI) and sex- and drug-risk behaviors with the risk assessment battery (RAB). Lifetime abuse or dependence diagnoses for alcohol and drugs were established by a physician with addiction medicine training.

Results: Among 201 subjects, diagnoses of abuse or dependence (AB/DEP) were common: 9% (19/201) had only alcohol AB/DEP; 39% (78/201) had alcohol and drug AB/DEP; 47% (95/201) had only drug AB/DEP; and 4% (9/201) had no diagnosis of alcohol or drug AB/DEP. Sex- and drug-risk behaviors varied significantly by substance use diagnosis. Subjects with any alcohol AB/DEP had higher sex-risk RAB scores than those with drug only AB/DEP (6.1 versus 3.9, p < .0001). Among subjects with any diagnosis of drug AB/DEP, having in addition an alcohol diagnosis was associated with unclean needle use in the last six months (33% (26/78) versus 21% (20/95), p = 0.08).

Conclusions: Lifetime alcohol diagnoses of abuse or dependence were present in nearly one-half of hospitalized HIV-infected patients in St. Petersburg, Russia and were associated with significantly higher sex-risk behaviors and borderline significantly higher drug-risk behaviors. As HIV infection spreads rapidly in Russia and Eastern Europe, these data support the need for HIV risk-reduction interventions in alcohol abusing populations and raise the potential of benefit by addressing alcohol use in HIV-infected populations.

Keywords: HIV risk, Alcohol abuse, Russia

1. Introduction

Over the past five years, reports of HIV infection in Russia have increased dramatically, with an estimated one million people already infected (Hamers and Downs, 2003). This represents an approximate 10-fold increase from 130,000 infections reported in 1999 (Grisin and Wallander, 2002; Stephenson, 2000). According to forecasts, there may be approximately five million HIV-infected individuals in the Russian Federation by 2007 (Anonymous, 2002). The majority of HIV infection in Russia is currently among injection drug users (IDUs) (Dehne et al., 2000; Krupitsky et al., 2004).

Injection drug use is increasingly common in Russia. The number of drug-dependent persons rose 10-fold from 1986 to 1998 and exceeded two million people (Koshkina, 2000). However, even more common than drug use in Russia is alcohol consumption. In fact, in Russia, alcohol consumption per capita is among the highest in the world, particularly for men (Nemtsov, 2000). Average alcohol consumption for Russian men has increased from 29 g per day in 1992 to 45 g per day in 2002 (Zohoori et al., 2003). Estimates of lifetime prevalence of alcohol dependence in the former Soviet Union may be as high as 69% in men (Pakriev et al., 1998) versus 18% (Grant, 1997) in US men.

Alcohol use has been shown to impact HIV infection with increased transmission risk and possible disease progression. Several studies have demonstrated that people with heavy alcohol use tend to engage in riskier behaviors, such as sex with multiple partners, unprotected vaginal and anal intercourse, and injection drug use (Bagnall et al., 1990; Fenaughty and Fisher, 1998; Halpern-Felsher et al., 1996). In Asia, drinking alcohol is often associated with the high-risk behavior of engaging in sex, usually unprotected, with a commercial sex worker (Fordham, 1995; Gibney et al., 2003; Kim et al., 1998; MacQueen et al., 1996; Poudel et al., 2004; Wee et al., 2004).

In the United States, HIV infection has been examined in substance abuse treatment settings where its prevalence is increased among alcohol-dependent persons (Avins et al., 1994; Mahler et al., 1994). Alcohol abuse in combination with other drug use may lead to even more frequent occurrences of risky sex- and drug-use behaviors. Increased alcohol consumption is associated with sexual HIV risk-taking behavior among female drug users (Rees et al., 2001). Among IDUs, alcohol use is associated with increased sex-risk behavior (Stein et al., 2001). Specifically, among HIV-infected individuals with a history of alcohol problems, at-risk drinking was associated with inconsistent condom use among active IDUs (Ehrenstein et al., 2004). There are mixed results concerning the impact of alcohol use on risky injection drug behavior (Rees et al., 2001; Stein et al., 2000). Reasons underlying the association between alcohol use and high-risk behaviors for HIV have been described and include decreased inhibitions and risk perception (Cooper, 2002; Fromme et al., 1999), belief that alcohol enhances sexual arousal (George et al., 2000), deliberate use of alcohol to excuse high-risk behavior (Dermen et al., 1998), and the indirect association that bars are common places to meet potential sexual partners (Purcell et al., 2001).

Further, recent reports in animals raise the possibility that alcohol consumption plays a permissive role for HIV replication, possibly resulting in higher HIV viral loads which would be associated with higher transmission risk (Stoltz et al., 2002). Finally, among HIV-infected patients with a history of alcohol problems who are receiving antiretroviral treatment, alcohol consumption was associated with higher HIV viral loads and lower CD4 cell counts, markers of HIV disease progression (Samet et al., 2003).

In light of Russia's epidemic spread of HIV, high alcohol consumption, and ongoing injection drug use, we sought to clarify if alcohol use among HIV-infected Russians exacerbated unsafe sex- and drug-use behaviors. Thus, we examined HIV risk behaviors and alcohol and drug use among hospitalized HIV-infected persons in St. Petersburg, Russia.

2. Methods

2.1. Study design

For 201 HIV-infected inpatients at an infectious disease hospital in St. Petersburg, Russia, researchers administered a survey and abstracted data from medical records in order to assess drug and alcohol use and severity, HIV risk behaviors, lifetime substance abuse, and dependence diagnoses. This study was approved by the Institutional Review Boards of Boston Medical Center and St. Petersburg Pavlov State Medical University.

2.2. Data collection

Data were collected between June 2001 and March 2002 at the Botkin Infectious Disease (ID) Hospital, an inpatient facility founded in 1882 for adult patients with infectious diseases in St. Petersburg, Russia. The 1200-bed hospital, staffed primarily by ID specialists, is the largest inpatient facility of its kind in Northwest Russia and is divided into departments (e.g. HIV/AIDS, hepatitis, and food-borne diseases) consisting of 40–50 beds each. It also has a surgery and maternity ward serving infected persons. In the 1990s and early 2000s, Botkin Hospital was the only inpatient site for HIV-infected individuals in St. Petersburg. All individuals admitted to the three departments that care for HIV-infected patients were eligible and asked to join the study. Most of the patients from these departments were admitted for initial presentation or exacerbations of viral hepatitis; 84% (201/240) of the approached patients agreed to participate. Study participants provided written informed consent prior to data collection. An interviewer assessed subjects in person using a standardized instrument to ascertain information including the following: demographics, HIV risk behaviors, alcohol consumption, and addiction severity. Diagnoses of lifetime alcohol or drug abuse or dependence were made through clinical assessment. Laboratory tests performed as part of clinical care were recorded. We obtained available serology results, liver function tests, and history of disease from medical records. All other data collected on subjects were obtained specifically for research purposes.

2.3. Measures of substance use and substance abuse and dependence

Within the first week of inpatient stay, subjects were evaluated for lifetime alcohol or drug abuse or dependence. Clinical diagnoses were made via assessment by an infectious disease specialist with training in addiction medicine (Maria Kuznetsova, MD) using criteria from the diagnostic and statistical manual of mental disorders–fourth edition (DSM-IV) (American Psychiatric Association, 1994). Additionally, interviewer assessment included standardized questions on alcohol and heroin use including the Michigan alcohol screening test (MAST)(Selzer, 1971), the time line follow back (TLFB) assessment (Sobell and Sobell, 1992), the addiction severity index (ASI) (McLellan et al., 1992), and the risk assessment battery (RAB) (Navaline et al., 1994), instruments with well-documented reliability and validity. For purposes of analysis, substance use diagnoses of abuse and dependence were combined resulting in four groups: alcohol only, alcohol and drug, drug only, and no diagnosis.

2.4. Primary outcome measure: HIV sex- and drug-risk behaviors

Estimates of sex- and drug-risk behaviors were derived from the risk assessment battery (RAB) (Navaline et al., 1994). This instrument sums the scores for individual items, for totals of 35 (sex-risk) and 25 (drug-risk). Scores are derived for both sex- and drug-risk behaviors via a series of questions including inquiries about numbers of sexual partners, usage of condoms, and sharing of needles.

Interviews were conducted in Russian. Standard survey elements already translated into Russian were used (i.e., MAST, ASI, TLFB, RAB). Other questions were translated from English to Russian, back-translated into English to check for accuracy, and then corrected.

2.5. Analysis

Fisher's exact (for categorical outcomes) and Kruskal–Wallis tests (for continuous outcomes) were used to compare subject substance use diagnosis with subject characteristics including risk behaviors for HIV infection. Reported p-values are two-tailed, and a p-value less than 0.05 was considered statistically significant. A multivariable linear regression was fit to predict RAB sex-risk subscale scores, as a function of diagnosis group, gender, and age. A logistic regression model, also controlling for gender and age, was fit to predict any needle sharing, for subjects with any drug diagnosis and injection use in the past six months. All analyses were carried out using SAS/STAT version 8.2 (SAS Institute, 2001).

3. Results

3.1. Subject characteristics

The characteristics of the 201 HIV-infected subjects are outlined in Table 1. Three-fifths (62%) were male, with a mean age of 27 years. The most common lifetime substance use diagnosis of abuse or dependence was drug only (47%), alcohol and drug (39%), and alcohol only (9%). Nine subjects (4%) had no substance use diagnosis. Assessments of past 30-day use of alcohol among those with any alcohol diagnosis (n = 97) revealed a mean of 28 g/day, the equivalent of approximately 2.5 standard drinks/day.

Table 1.

Demographic and substance abuse characteristics of HIV-infected persons in an infectious disease hospital in St. Petersburg, Russia (n = 201)

Characteristic Total cohort (n = 201)
Female 76 (38%)
Age 26.6 (8.17)
Current work 34 (17%)
Hep C (n = 200) 186 (93%)
Hep B (n = 123) 58 (47%)
Grams ethanol/day (n = 98) 28.19 (32.31)
MAST 6.58 (5.00)
Addiction severity index
 Medical status 0.72 (0.34)
 Employment 0.71 (0.29)
 Alcohol use 0.15 (0.22)
 Drug use 0.10 (0.16)
 Legal (law) 0.14 (0.27)
 Family (social) 0.31 (0.28)
 Psychiatric 0.56 (0.24)
Risk assessment battery
 Sex-risk subscale 4.98 (2.96)
 Always condom/no sex 69 (34%)
 Two or more partners 103 (51%)
 Drug-risk subscale 4.31 (5.54)
 Injected drugsa 94 (47%)
 Used others' needlesa 46 (23%)
 Shared their needles 71 (35%)
a

Refers to the 6 months prior to assessment.

3.2. Risk behaviors

Risk assessments yielded a sex-risk subscale mean score of 5.0 and a drug-risk subscale score of 4.3. More than half (103/201) of all subjects reported greater than two sexual partners in the past six months, and 66% (132/201) reported inconsistent condom use, with 23% (47/201) of all subjects reporting condom use none of the time. Forty-seven percent (94/201) of all subjects reported injecting drugs in the last six months with 23% (46/201) reporting using others' needles and 35% (71/201) reporting sharing their own needles.

Results from data stratified by lifetime substance use diagnosis are displayed in Table 2. Notable among the results are significant differences among substance abuse diagnostic groups for age (p < 0.0001), current work (p = 0.002) and antibodies to the hepatitis C virus (p < 0.0001).

Table 2.

Demographic and substance abuse characteristics of HIV-infected persons in an infectious disease hospital in St. Petersburg, Russia stratified by alcohol and drug abuse or dependence diagnoses (n = 201)

Characteristic Abuse or dependence diagnosis [n(%) or mean (S.D.)]
Alcohol only (n = 19) Alcohol + drug (n = 78) Drug only (n = 95) No diagnosis (n = 9) p-value
Female 7 (37%) 21 (27%) 43 (45%) 5 (56%)  0.05
Age 36 (10.9) 27.3 (6.9) 23.3 (6.0) 35.9 (9.1) <0.0001
Current work 6 (32%) 15 (19%) 12 (13%) 1 (11%)  0.0016
Hep C (n = 200) 14 (74%) 73 (95%) 92 (97%) 6 (67%) <0.0001
Hep B (n = 123) 7 (41%) 29 (60%) 20 (39%) 2 (29%)  0.13
Grams ethanol/day (n = 98) 43.85 (54.48) 24.68 (23.26) 2.37 (3.55) 2.92 (5.28) <0.0001
MAST 11.79 (4.77) 9.54 (4.57) 3.45 (2.71) 3.11 (2.71) <0.0001
Addiction severity index
 Medical status 0.82 (0.25) 0.71 (0.37) 0.69 (0.33) 0.76 (0.34)  0.29
 Employment 0.86 (0.25) 0.68 (0.31) 0.70 (0.28) 0.77 (0.23)  0.07
 Alcohol use 0.43 (0.32) 0.23 (0.22) 0.04 (0.06) 0.02 (0.04) <0.0001
 Drug use 0.00 (0.0) 0.09 (0.14) 0.13 (0.17) 0.00 (0.0) <0.0001
 Legal (law) 0.20 (0.34) 0.17 (0.30) 0.12 (0.24) 0.00 (0.0)  0.08
 Family (social) 0.37 (0.27) 0.32 (0.30) 0.29 (0.27) 0.25 (0.29)  0.56
 Psychiatric 0.68 (0.21) 0.58 (0.23) 0.51 (0.25) 0.59 (0.16)  0.03
Risk assessment battery
 Sex-risk subscale 5.95 (2.63) 6.17 (3.13) 3.86 (2.41) 4.89 (2.76) <0.0001
 Always condom/no sex 4 (21%) 23 (29%) 37 (39%) 4 (44%)  0.31
 2 or more partners 13 (68%) 52 (67%) 35 (37%) 3 (33%)  0.0003
 Drug-risk subscale 0.00 (0.0) 4.53 (5.68) 5.38 (5.67) 0.22 (0.67) <0.0001
 Injected drugsa 0 (0%) 39 (50%) 54 (57%) 1 (11%) <0.0001
 Used others' needlesa 0 (0%) 26 (33%) 20 (21%) 0 (0%)  0.004
 Shared their needles 0 (0%) 29 (37%) 42 (44%) 0(0%)  0.0003
a

Refers to the 6 months prior to assessment.

An unadjusted comparison between subjects with any diagnosis of alcohol abuse or dependence (i.e., alcohol only combined with alcohol and drug subjects) and those with only drug diagnoses reveals significantly higher sex-risk subscale scores (6.1 versus 3.9, p < 0.0001).

In multivariable linear regression, females had borderline significantly higher sex-risk scores (predicted scores 0.76 units higher than men, p = 0.07), while age was not a significant predictor (p = 0.78). Diagnosis group was a significant predictor of RAB sex-risk scores (F(3,195) = 11.36, p < 0.0001). There was a significant difference between the predicted RAB sex-risk subscale score for subjects with any alcohol diagnosis compared to those with drug-only diagnoses (F (1,195) = 22.1, p < .0001).

Additionally, in an assessment of use of unclean needles, a comparison between drug users with alcohol diagnoses (26/78, 33%) and drug users without (20/95, 21%) indicated that more subjects with alcohol diagnoses used unclean needles in the last six months (p = 0.08). While controlling for sex, age, and diagnosis (drug and alcohol diagnosis versus drug-only diagnosis, 1 df), multivariate logistic regression indicated that younger age was a significant predictor of needle sharing (OR = 1.07, 95% CI = 1.01–1.15 per year, p = 0.03); gender was not a significant predictor (OR for females relative to males = 0.9, 95% CI = 0.4–1.9). Diagnosis of drug and alcohol versus drug-only diagnosis was associated with increased odds of any sharing (OR = 2.5, 95% CI = 1.2–5.1, p = 0.02).

3.3. Laboratory data

Among 123 subjects with recorded serology test results, 47% (58) were hepatitis B surface antigen positive. When stratified by lifetime substance use diagnoses of abuse or dependence, positive results for hepatitis B antigens were detected in 41% (7/17), 60% (29/48), 40% (20/50) and 29% (2/7) of the alcohol only, alcohol and drug, drug-only and no-diagnosis groups, respectively.

Among 200 subjects with available data, hepatitis C antibodies were detected in 93% (186). When stratified by substance use diagnoses, hepatitis C antibodies were detected in 74% (14/19), 95% (73/77), 97% (92/95) and 67% (6/9) of the alcohol-only, alcohol and drug, drug-only and no-diagnosis groups, respectively.

4. Discussion

Among hospitalized HIV-infected patients in Russia, reports of alcohol use and high-risk behaviors for HIV transmission are common. While a majority of subjects were diagnosed with drug abuse or dependence, almost half (48%) of all subjects had lifetime diagnoses of alcohol abuse or dependence. Further, a majority of the total population reported inconsistent condom use and/or having two or more sexual partners in the last six months. This extent of risky sex is particularly disturbing in that for women, sex-risk behavior may be more significant to HIV seroconversion than drug-risk behavior (Strathdee et al., 2001). Strathdee et al. (2001) also found that among female IDUs sex risks (e.g., recent STD and sex trade) were more commonly associated with HIV seroconversion than drug-related risk behaviors. Forty-seven percent of all subjects reported injecting drugs in the last six months, and almost half of these reported using others' needles. The marked substance abuse and risk behaviors in this population of HIV-infected individuals are alarming.

The finding of an association between HIV risk behaviors and an alcohol abuse or dependence diagnosis is notable in that Russia's HIV epidemic has been nearly totally attributed to injection drug use (Dehne et al., 2000). We found that sex-risk was greater, as reflected in the RAB sex-risk subscores, with diagnoses of alcohol abuse or dependence. Also, an alcohol diagnosis was associated with increased odds of needle sharing. These findings are of particular importance given the fact that in Russia alcohol use is widespread, alcohol dependence is common, and HIV infection is epidemic. The small number of subjects diagnosed with “alcohol only” lifetime abuse or dependence is unique in two ways. First, these subjects were significantly older than the subjects with other substance use diagnoses. Second, co-infection with hepatitis C was common among a surprising number (74%) of alcohol-only subjects. In fact, co-infection with hepatitis B and, particularly C, was common in the entire cohort. This abnormal prevalence is likely a result of selection bias as reasons for hospitalization included acute hepatitis. Because the interview did not assess whether or not subjects ever used injection drugs, we cannot speculate on the means of transmission of hepatitis C to those with alcohol-only diagnoses. This may be a limitation of these data and implicate the need for further study of this population.

Our study has other noteworthy limitations. These data represent a cross-sectional perspective of the substance abuse and risk behaviors of a population of HIV-infected inpatients with substantial co-morbidity. Thus, inferences that may be drawn regarding the influence of alcohol on HIV risk behaviors in general populations are limited. However, as illness severity is typically greater in hospitalized patients, and sicker patients have been shown to have less drug- and sex-risk behaviors (Collins et al., 2001) use of such patients is likely to provide a conservative estimate of HIV risk. Additionally, because our population has already been infected with HIV, our data cannot address the relationship between HIV infection and use of alcohol or drugs. Further, the risk behaviors of those already infected with HIV may differ from those among non-infected individuals in Russia.

Despite these limitations, our data show that lifetime diagnoses of alcohol abuse or dependence were present in nearly one-half of hospitalized HIV-infected patients in St. Petersburg, Russia and were associated with significantly higher sex-risk behaviors and a trend toward higher drug-risk behaviors. As HIV spreads rapidly in Russia and Eastern Europe, addressing alcohol use in HIV-infected persons holds potential to decrease the transmission of HIV by lowering the prevalence of high sex- and drug-risk behaviors.

Acknowledgements

We gratefully acknowledge the intellectual contributions of Seville Meli, MPH and Naomi Freedner, MPH. This project was supported by a National Institute on Alcohol Abuse and Alcoholism Supplement to R01-AA11785.

References

  1. American Psychiatric Association . Diagnostic and Statistical Manual of Mental Disorders. 4th American Psychiatric Association; Washington D.C: 1994. [Google Scholar]
  2. Anonymous Report of the Epidemiological Service of the Ministry of Health Care of the Russian Federation. 2002 [Google Scholar]
  3. Avins AL, Woods WJ, Lindan CP, Hudes ES, Clark W, Hulley SB. HIV infection and risk behaviors among heterosexuals in alcohol treatment programs. JAMA. 1994;271:515–518. [PubMed] [Google Scholar]
  4. Bagnall G, Plant M, Warwick W. Alcohol, drugs and AIDS-related risks: results from a prospective study. AIDS Care. 1990;2:309–317. doi: 10.1080/09540129008257746. [DOI] [PubMed] [Google Scholar]
  5. Collins RL, Kanouse DE, Gifford AL, Senterfitt JW, Schuster MA, McCaffrey DF, Shapiro MF, Wenger NS. Changes in health-promoting behavior following diagnosis with HIV: prevalence and correlates in a national probability sample. Health Psychol. 2001;20:351–360. [PubMed] [Google Scholar]
  6. Cooper ML. Alcohol use and risky sexual behavior among college students and youth: evaluating the evidence. J. Stud. Alcohol Suppl. 2002:101–117. doi: 10.15288/jsas.2002.s14.101. [DOI] [PubMed] [Google Scholar]
  7. Dehne KL, Pokrovskiy V, Kobyshcha Y, Schwartlander B. Update on the epidemics of HIV and other sexually transmitted infections in the newly independent states of the former Soviet Union. AIDS. 2000;14(Suppl 3):75–84. [PubMed] [Google Scholar]
  8. Dermen KH, Cooper ML, Agocha VB. Sex-related alcohol expectancies as moderators of the relationship between alcohol use and risky sex in adolescents. J. Stud. Alcohol. 1998;59:71–77. doi: 10.15288/jsa.1998.59.71. [DOI] [PubMed] [Google Scholar]
  9. Ehrenstein V, Horton NJ, Samet JH. Inconsistent condom use among HIV-infected patients with alcohol problems. Drug Alcohol Depend. 2004;73:159–166. doi: 10.1016/j.drugalcdep.2003.10.011. [DOI] [PubMed] [Google Scholar]
  10. Fenaughty AM, Fisher DG. High-risk sexual behavior among drug users: the utility of a typology of alcohol variables. Sex. Transm. Dis. 1998;25:38–43. doi: 10.1097/00007435-199801000-00008. [DOI] [PubMed] [Google Scholar]
  11. Fordham G. Whisky, women and song: men, alcohol and AIDS in northern Thailand. Aust. J. Anthropol. 1995;6:154–177. [PubMed] [Google Scholar]
  12. Fromme K, D'Amico EJ, Katz EC. Intoxicated sexual risk taking: an expectancy or cognitive impairment explanation? J. Stud. Alcohol. 1999;60:54–63. doi: 10.15288/jsa.1999.60.54. [DOI] [PubMed] [Google Scholar]
  13. George WH, Stoner SA, Norris J, Lopez PA, Lehman GL. Alcohol expectancies and sexuality: a self-fulfilling prophecy analysis of dyadic perceptions and behavior. J. Stud. Alcohol. 2000;61:168–176. doi: 10.15288/jsa.2000.61.168. [DOI] [PubMed] [Google Scholar]
  14. Gibney L, Saquib N, Metzger J. Behavioral risk factors for STD/HIV transmission in Bangladesh's trucking industry. Soc. Sci. Med. 2003;56:1411–1424. doi: 10.1016/s0277-9536(02)00138-7. [DOI] [PubMed] [Google Scholar]
  15. Grant BF. Prevalence and correlates of alcohol use and DSM-IV alcohol dependence in the United States: results of the National Longitudinal Alcohol Epidemiologic Survey. J. Stud. Alcohol. 1997;58:464–473. doi: 10.15288/jsa.1997.58.464. [DOI] [PubMed] [Google Scholar]
  16. Grisin S, Wallander C. Russia's HIV/AIDS crisis: confronting the present and facing the future. CSIS HIV/AIDS Task Force. 2002 [Google Scholar]
  17. Halpern-Felsher BL, Millstein SG, Ellen JM. Relationship of alcohol use and risky sexual behavior: a review and analysis of findings. J. Adolesc. Health. 1996;19:331–336. doi: 10.1016/S1054-139X(96)00024-9. [DOI] [PubMed] [Google Scholar]
  18. Hamers FF, Downs AM. HIV in central and eastern Europe. Lancet. 2000;361:1035–1044. doi: 10.1016/S0140-6736(03)12831-0. [DOI] [PubMed] [Google Scholar]
  19. Kim J, Celentano DD, Crum RM. Alcohol consumption and sexually transmitted disease risk behavior: partner mix among male Korean university students. Alcohol. Clin. Exp. Res. 1998;22:126–131. [PubMed] [Google Scholar]
  20. Koshkina EA. The prevalence of the use of narcotics and other psychoactive substances in Russia today. Zh. Mikrobiol. Epidemiol. Immunobiol. 2000:15–19. [PubMed] [Google Scholar]
  21. Krupitsky E, Zvartau E, Karandashova G, Horton NJ, Schoolwerth KR, Bryant K, Samet JH. The onset of HIV infection in the Leningrad region of Russia: a focus on drug and alcohol dependence. HIV Med. 2004;5:30–33. doi: 10.1111/j.1468-1293.2004.00182.x. [DOI] [PubMed] [Google Scholar]
  22. MacQueen KM, Nopkesorn T, Sweat MD, Sawaengdee Y, Mastro TD, Weniger BG. Alcohol consumption, brothel attendance, and condom use: normative expectations among Thai military conscripts. Med. Anthropol. Q. 1996;10:402–423. doi: 10.1525/maq.1996.10.3.02a00070. [DOI] [PubMed] [Google Scholar]
  23. Mahler J, Yi D, Sacks M, Dermatis H, Stebinger A, Card C, Perry S. Undetected HIV infection among patients admitted to an alcohol rehabilitation unit. Am. J. Psychiatry. 1994;151:439–440. doi: 10.1176/ajp.151.3.439. [DOI] [PubMed] [Google Scholar]
  24. McLellan A, Kushner H, Metzger D, Peters R, Smith I, Grissom G, Pettinati H, Argeriou M. The Fifth Edition of the Addiction Severity Index. J. Subst. Abuse Treat. 1992;9:199–213. doi: 10.1016/0740-5472(92)90062-s. [DOI] [PubMed] [Google Scholar]
  25. Navaline HA, Snider EC, Petro CJ, Tobin D, Metzger D, Alterman AI, Woody GE. Preparations for AIDS vaccine trials. An automated version of the risk assessment battery (RAB): enhancing the assessment of risk behaviors. AIDS Res. Hum. Retroviruses. 1994;10(Suppl 2):281–283. [PubMed] [Google Scholar]
  26. Nemtsov AV. Estimates of total alcohol consumption in Russia, 1980–1994. Drug Alcohol Depend. 2000;58:133–142. doi: 10.1016/s0376-8716(99)00069-1. [DOI] [PubMed] [Google Scholar]
  27. Pakriev S, Vasar V, Aluoja A, Shlik J. Prevalence of ICD-10 harmful use of alcohol and alcohol dependence among the rural population in Udmurtia. Alcohol Alcohol. 1998;33:255–264. doi: 10.1093/oxfordjournals.alcalc.a008389. [DOI] [PubMed] [Google Scholar]
  28. Poudel KC, Jimba M, Okumura J, Joshi AB, Wakai S. Migrants' risky sexual behaviours in India and at home in far western Nepal. Trop. Med Int. Health. 2004;9:897–903. doi: 10.1111/j.1365-3156.2004.01276.x. [DOI] [PubMed] [Google Scholar]
  29. Purcell DW, Parsons JT, Halkitis PN, Mizuno Y, Woods WJ. Substance use and sexual transmission risk behavior of HIV-positive men who have sex with men. J. Subst. Abuse. 2001;13:185–200. doi: 10.1016/s0899-3289(01)00072-4. [DOI] [PubMed] [Google Scholar]
  30. Rees V, Saitz R, Horton NJ, Samet J. Association of alcohol consumption with HIV sex- and drug-risk behaviors among drug users. J. Subst. Abuse Treat. 2001;21:129–134. doi: 10.1016/s0740-5472(01)00190-8. [DOI] [PubMed] [Google Scholar]
  31. Samet JH, Horton NJ, Traphagen ET, Lyon SM, Freedberg KA. Alcohol consumption and HIV disease progression: are they related? Alcohol Clin. Exp. Res. 2003;27:862–867. doi: 10.1097/01.ALC.0000065438.80967.56. [DOI] [PubMed] [Google Scholar]
  32. SAS Institute Inc. SAS/STAT® Software: Changes and Enhancements, Release 8.2. SAS Institute Inc.; Cary, NC: 2001. [Google Scholar]
  33. Selzer ML. The Michigan alcoholism screening test: the quest for a new diagnostic instrument. Am. J. Psychiatry. 1971;127:1653–1658. doi: 10.1176/ajp.127.12.1653. [DOI] [PubMed] [Google Scholar]
  34. Sobell LC, Sobell MB. Timeline follow-back: a technique for assessing self-reported alcohol consumption. In: Litten R, Allen J, editors. Measuring Alcohol Consumption. The Human Press Inc; 1992. [Google Scholar]
  35. Stein MD, Anderson B, Charuvastra A, Friedmann PD. Alcohol use and sexual risk taking among hazardously drinking drug injectors who attend needle exchange. Alcohol Clin. Exp. Res. 2001;25:1487–1493. [PubMed] [Google Scholar]
  36. Stein MD, Hanna L, Natarajan R, Clarke J, Marisi M, Sobota M, Rich J. Alcohol use patterns predict high-risk HIV behaviors among active injection drug users. J. Subst. Abuse Treat. 2000;18:359–363. doi: 10.1016/s0740-5472(99)00070-7. [DOI] [PubMed] [Google Scholar]
  37. Stephenson J. HIV/AIDS surging in Eastern Europe. JAMA. 2000;284:3113–3114. doi: 10.1001/jama.284.24.3113. [DOI] [PubMed] [Google Scholar]
  38. Stoltz DA, Nelson S, Kolls JK, Zhang P, Bohm RP, Murphey-Corb M, Bagby GJ. Effects of in vitro ethanol on tumor necrosis factor-alpha production by blood obtained from simian immunodeficiency virus-infected rhesus macaques. Alcohol Clin. Exp. Res. 2002;26:527–534. [PubMed] [Google Scholar]
  39. Strathdee SA, Galai N, Safaiean M, Celentano DD, Vlahov D, Johnson L, Nelson KE. Sex differences in risk factors for HIV seroconversion among injection drug users: a 10-year perspective. Arch. Intern Med. 2001;161:1281–1288. doi: 10.1001/archinte.161.10.1281. [DOI] [PubMed] [Google Scholar]
  40. Wee S, Barrett ME, Lian WM, Jayabaskar T, Chan KW. Determinants of inconsistent condom use with female sex workers among men attending the STD clinic in Singapore. Sex Transm. Infect. 2004;80:310–314. doi: 10.1136/sti.2003.008342. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Zohoori N, Blanchette D, Popkin B. Carolina Population Center, University of North Carolina; Chapel Hill, NC: 2003. Monitoring health conditions in the Russian Federation: The Russian Longitudinal Monitoring Survey 1992–2002. Report submitted to the U.S. Agency for International Development. [Google Scholar]

RESOURCES