Статья для зачёта - 2010 год / Статья для зачёта - 2010 год
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RESEARCH REPORT |
doi:10.1111/j.1360-0443.2006.01317.x |
Prevalence of HIV, hepatitis C and syphilis among injecting drug users in Russia: a multi-city study
Tim Rhodes1, Lucy Platt1, Svetlana Maximova2, Evgeniya Koshkina3, Natalia Latishevskaya4, Matthew Hickman1, Adrian Renton1, Natalia Bobrova1, Tamara McDonald5 & John V. Parry5
Centre for Research on Drugs and Health Behaviour and Unit for International Public Health and Development, Imperial College London, UK,1 Faculty of Social Sciences, Altai State University, Barnaul, Russia,2 National Scientific Centre of Addictions, Moscow, Russia,3 Volgograd Medical Academy, Volgograd, Russia4 and Sexually Transmitted and Blood-Borne Virus Laboratory, Health Protection Agency, Colindale, London, UK5
ABSTRACT
Objectives To estimate the prevalence of HIV, hepatitis C virus (HCV) and syphilis in injecting drug users (IDUs) in Russia. Methods Unlinked anonymous cross-sectional survey of 1473 IDUs recruited from non-treatment settings in Moscow, Volgograd and Barnaul (Siberia), with oral fluid sample collection for HIV, HCV antibody (anti-HIV, anti-HCV) and syphilis testing. Results Prevalence of antibody to HIV was 14% in Moscow, 3% in Volgograd and 9% in Barnaul. HCV prevalence was 67% in Moscow, 70% in Volgograd and 54% in Barnaul. Prevalence of positive syphilis serology was 8% in Moscow, 20% in Volgograd and 6% in Barnaul. Half of those HIV positive and a third of those HCV positive were unaware of their positive status. Common risk factors associated with HIV and HCV infection across the cities included both direct and indirect sharing of injecting equipment and injection of home-produced drugs. Among environmental risk factors, we found increased odds of anti-HIV associated with being in prison in Moscow, and some association between official registration as a drug user and anti-HIV and anti-HCV. No associations were found between sexual risk behaviours and anti-HIV in any city. Conclusions HIV prevalence among IDUs was markedly higher than city routine surveillance data suggests and at potentially critical levels in terms of HIV prevention in two cities. HCV prevalence was high in all cities. Syphilis prevalence highlights the potential for sexual risk and sexual HIV transmission. Despite large-scale testing programmes, knowledge of positive status was poor. The scaling-up of harm reduction for IDUs in Russia, including sexual risk reduction, is an urgent priority.
Keywords Hepatitis C, harm reduction, HIV, injecting drug use, syphilis, Russia.
Correspondence to: Tim Rhodes, The Centre for Research on Drugs and Health Behaviour, The Reynolds Building, St Dunstan’s Road, Imperial College London, London W6 8RP, UK. E-mail: t.rhodes@imperial.ac.uk
Submitted 21 April 2005; initial review completed 15 June 2005; final version accepted 3 August 2005
INTRODUCTION
Despite indication of levelling out in the number of new HIV cases reported nationally to the Ministry of Health, the Russian HIV epidemic is one of the fastest growing in the world. Russia contributes approximately 70% of cumulative HIV cases in the eastern, central, southeastern and central Asian region [1]. Over 80% of HIV cases reported since 1996 have been associated with injecting drug use (IDU), and the evidence indicates that multiple HIV outbreaks have occurred among IDUs in different cities, over a decade after HIV transmission peaked in western Europe [2]. In one earlier survey of community-recruited IDUs in Togliatti City, we found 56% (234/418) HIV positive, half of whom
were under 25 years, and 87% (357/411) HCV positive [3].
Furthermore, there is high background prevalence of sexually transmitted infections (STIs) in the Russian population, with syphilis prevalence peaking in 1997 at 275 per 100 000 population and remaining high by 2002 at 120 per 100 000 population [4]. Little is known about the prevalence of syphilis among Russian IDUs. Recent suggestion of increasing sexual HIV transmission in Russia, and high levels of engagement in sex work by female IDUs, raises the concern that sexual mixing between IDUs and their sexual partners might facilitate a shift towards a more generalized HIV epidemic [5].
There is a strong emphasis on population screening in Russia, with around 20 million HIV screening tests con-
© 2006 The Authors. Journal compilation © 2006 Society for the Study of Addiction |
Addiction, 101, 252–266 |
ducted annually. Despite this there are few reliable city estimates of HIV, hepatitis C virus (HCV) and syphilis prevalence among IDUs, especially in populations sampled outside drug treatment or health service settings. Recognizing the urgent need to foster evidence-based prevention of blood-borne and STIs in Russia and the eastern European region more broadly, we undertook the largest community-recruited survey to date of IDUs in Russia to measure HIV, HCV and syphilis prevalence.
METHODS
We conducted an unlinked anonymous cross-sectional survey of 1473 IDUs recruited from non-treatment settings in Moscow (n = 455), Volgograd (n = 517) and Barnaul, Siberia (n = 501) in September and October 2003. All participants had injected drugs in the last 4 weeks. IDUs were recruited in multiple sites in community settings by a team of trained ‘indigenous fieldworkers’ who also administered the interview-based survey [6,7]. Community recruitment settings included street locations, respondents’ homes and cafés. Indigenous fieldworkers were defined as interviewers who were current or former drug users, had established professional experience in the substance misuse field or had privileged access to injecting drug user networks. Indigenous fieldworkers may act to reduce the bias arising from socially desirable responses in behavioural data [6,7]. As in similar studies [2], measures to ensure data quality and minimize network bias included: limiting the number of interviews per fieldworker to two per day and a total of 40 interviews throughout the fieldwork; random spot-checks in the field; and validation follow-up interviews with 10% of participants. IDUs received HIV prevention materials (including needles and syringes) as well as chocolates and cigarettes for their participation. The study had ethical approval from the Riverside Local Research Ethics Committee and the support of the Russian Ministry of Health National Scientific Centre for Research on Addictions.
Anti-HCV, anti-HIV and syphilis antibody testing
Oral fluid specimens were obtained using the OraSure device (Epitope Inc., OR, USA) and screened for antibodies to HCV (anti-HCV) and HIV (anti-HIV). Specimens were screened for anti-HCV using a UK Health Protection Agency (HPA) modified Ortho HCV 3.0 enhanced SAVe enzyme-linked immunosorbent assay (ELISA) [8]. For anti-HIV, the Oral Fluid Vironostika HIV-1 Microelisa System (BioMérieux, Inc., NC, USA) was used [9,10]. Specimens reactive on initial testing were subject to confirmatory testing using Detect HIV (Biostat Diagnostics, UK) and HIV blot 2.2 Western blot assay (AbbotMurex,
HIV, HCV and syphilis among Russian IDU |
253 |
UK). These blot assays employ a modified protocol developed for use with oral fluid by the UK HPA [11]. Antibodies to Treponema pallidum were tested using a commercial test Murex ICE Syphilis (AbbotMurex) modified for use with oral fluid by the UK HPA (J. Parry, personal communication, 2005).
Statistical analysis
Associations between antibodies to HIV and hepatitis C and covariates were explored univariably and by multiple logistic regression. The outcomes were positive antibodies to HIV (anti-HIV) and hepatitis C (anti-HCV), and odds ratios associated with infection. Risk factors associated with positive T. pallidum cases are reported elsewhere [12]. Intra-cluster correlation coefficients were calculated to measure the degree to which observations from individuals recruited by the same interviewer were correlated and general estimating equations (GEE) were used to adjust for any correlation. All multivariable analysis followed a conceptual framework approach [13]. This involved classifying variables into the five groups displayed in Tables 1–4, with the analysis conducted in three stages: (i) separate univariable models explored each of the variables alone with the outcome; (ii) variables associated with the outcome in univariable analysis to a significance level of P = 0.2 were included in separate multivariable models for each group; and (iii) variables reaching a significance level of P = 0.2 in each of the five multivariable models were then included in one overall multivariable model. In addition, variables excluded at the first stage were added at the secondand third-stage models to assess their association with the outcome variable in the presence of other variables.
RESULTS
A total of 1473 IDUs were recruited into the study. Twothirds (70.5%) were male, half (50%) were aged under 25 years, one-fifth (20%) had injected for 2 years or less and most (81%) injected less than daily. The most commonly injected drug in the last 4 weeks was heroin (72%). Approximately a quarter (26%) had injected home-produced drugs in the last 4 weeks, including ‘hanka’ or ‘mak’ (liquid derivatives of opium poppy straw) or ‘vint’ (a liquid methamphetamine).
In the last 4 weeks, approximately one-sixth (14%) reported injecting with needles and syringes used previously by others, and 84% reported injecting with shared injecting paraphernalia other than needles or syringes, including ‘frontloading’ (whereby a drug solute is squirted from a donor syringe into another by removing the needle), injecting with filters previously used by others, filling their syringe from a ‘working syringe’ used by
© 2006 The Authors. Journal compilation © 2006 Society for the Study of Addiction |
Addiction, 101, 252–266 |
254 Tim Rhodes et al.
Table 1 Univariable and multivariable risk factors for antibodies to HIV among injecting drug users in Moscow.
|
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|
|
Unadjusted |
|
|
Adjusted |
|
|
No HIV+/total |
% HIV + |
|
|
|
|
|
|
|
|
|
|
|
|
|
||
Variable |
|
OR |
95% CI |
|
OR |
95% CI |
||
|
|
|||||||
|
|
|
|
|
|
|
|
|
Demographic indicators |
|
|
|
|
|
|
|
|
Sex group |
|
|
|
|
|
|
|
|
Men |
36/268 |
13.4% |
1.0 |
|
|
|
|
|
Female non-sex worker |
15/104 |
14.4% |
1.1 |
0.57–2.09 |
1.5 |
0.68–3.47 |
||
Female sex worker |
4/30 |
13.3% |
1.0 |
0.32–2.89 |
1.8 |
0.45–6.87 |
||
Age (years) |
|
|
|
|
|
|
|
|
20 or less |
9/54 |
16.7% |
1.0 |
|
1.0 |
|
||
21–24 |
20/114 |
17.5% |
1.0 |
0.43–2.53 |
1.1 |
0.39–3.05 |
||
25–29 |
20/150 |
13.3% |
0.7 |
0.34–1.55 |
0.5 |
0.16–1.46 |
||
30+ |
6/85 |
7.1% |
0.4 |
0.15–1.01 |
0.2 |
0.05–1.0 |
||
Education |
|
|
|
|
|
|
|
|
Secondary |
38/251 |
15.1% |
1.0 |
|
1.0 |
|
||
Attended higher |
17/147 |
11.6% |
0.8 |
0.37–1.66 |
1.0 |
0.47–2.03 |
||
Main source of income in last 4 weeks |
|
|
|
|
|
|
|
|
Regular work |
23/160 |
14.4% |
1.0 |
|
1.0 |
|
||
Other |
31/233 |
13.3% |
0.9 |
0.46–1.67 |
1.1 |
0.53–2.22 |
||
History of injecting drug use |
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|
|
|
|
|
|
|
Duration of injection (years) |
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|
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|
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|
|
|
2 years or less |
2/40 |
5.0% |
1.0 |
|
1.0 |
|
||
3–5 |
9/92 |
9.8% |
2.5 |
0.74–8.72 |
2.5 |
0.29–21.8 |
||
6–9 |
33/167 |
19.8% |
5.3 |
1.18–23.7 |
4.4 |
0.53–35.5 |
||
10+ |
11/103 |
10.7% |
2.5 |
0.56–11.2 |
1.3 |
0.14–12.1 |
||
Last day injected, number of times injected |
|
|
|
|
|
|
|
|
2+ |
14/180 |
7.8% |
1.0 |
|
1.0 |
|
||
Once |
40/220 |
18.2% |
2.6 |
1.38–5.02 |
2.4 |
1.12–5.05 |
||
Frequency of injecting |
|
|
|
|
|
|
|
|
< daily |
47/324 |
14.5% |
1.0 |
|
1.0 |
|
||
Daily |
6/71 |
8.5% |
0.6 |
0.27–1.39 |
0.6 |
0.19–1.60 |
||
Main drug injected in the last 4 weeks |
|
|
|
|
|
|
|
|
Heroin |
35/246 |
14.2% |
1.0 |
|
1.0 |
|
||
Vint or mak |
10/93 |
10.6% |
0.7 |
0.34–1.43 |
1.0 |
0.42–2.55 |
||
Ever injected home made drugs? |
|
|
|
|
|
|
|
|
No |
0/38 |
0.0% |
– |
– |
|
|
|
|
Yes |
55/365 |
15.1% |
– |
– |
|
– |
– |
|
Injecting risk behaviours |
|
|
|
|
|
|
|
|
Injected with a used needle or syringe in the last 4 weeks? |
|
|
|
|
|
|
||
No |
12.8% |
|
1.0 |
|
1.0 |
|
||
Yes |
8/59 |
13.6% |
1.1 |
0.52–2.12 |
0.5 |
0.18–1.50 |
||
Shared a spoon, filter or injected with prefilled syringe in last 4 weeks? |
|
|
|
|
|
|
||
No |
28/213 |
13.1% |
1.0 |
1.0 |
|
|
|
|
Yes |
27/190 |
14.2% |
1.0 |
0.71–1.33 |
0.8 |
0.40–1.70 |
||
Ever injected with used needles or syringes? |
|
|
|
|
|
|
|
|
No |
8/130 |
6.2% |
1.0 |
|
1.0 |
|
||
Yes |
43/245 |
17.6% |
3.1 |
1.23–7.77 |
3.5 |
1.43–8.36 |
||
Sexual risk behaviours |
|
|
|
|
|
|
|
|
Number of sex partners in the last 12 months |
|
|
|
|
|
|
|
|
0/1 |
19/140 |
13.6% |
1.0 |
|
1.0 |
|
||
2+ |
33/254 |
13.0% |
0.9 |
0.59–1.47 |
1.2 |
0.56–2.39 |
||
Self reported history of STI |
|
|
|
|
|
|
|
|
No |
38/225 |
16.9% |
1.0 |
1.0 |
|
|
|
|
Yes |
15/168 |
8.9% |
0.5 |
0.25–0.85 |
0.3 |
0.15–0.70 |
||
OR = odds ratio 95% CI = 95% confidence interval. Final model adjusted for last day injected, number of times injected; ever injected with used needles or syringes; history of STIs and registered as an IDU at a Narcology Service and history of prison.
© 2006 The Authors. Journal compilation © 2006 Society for the Study of Addiction |
Addiction, 101, 252–266 |
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HIV, HCV and syphilis among Russian IDU |
255 |
|||||
Table 1 Cont. |
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Unadjusted |
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Adjusted |
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No HIV+/total |
% HIV + |
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||
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Variable |
|
OR |
95% CI |
OR |
95% CI |
||||
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Environmental indicators |
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Have you ever been in prison? |
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No |
32/294 |
10.9% |
1.0 |
|
1.0 |
|
|
||
Yes |
22/108 |
20.4% |
1.9 |
1.46–2.53 |
2.2 |
1.0–4.65 |
|||
Registered as an IDU? |
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No |
30/286 |
10.5% |
1.0 |
|
1.0 |
|
|
||
Yes |
20/88 |
22.7% |
2.4 |
1.26–4.65 |
2.3 |
1.12–5.05 |
|||
OR = odds ratio 95% CI = 95% confidence interval. Final model adjusted for last day injected, number of times injected; ever injected with used needles or syringes; history of STIs and registered as an IDU at a Narcology Service and history of prison.
Table 2 Univariable and multivariable analysis of risk factors associated with HIV among injecting drug users in Volgograd.
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Unadjusted |
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Adjusted |
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No HIV+/total |
% HIV + |
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||
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Variable |
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OR |
95% CI |
OR |
95% CI |
|||
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|
Demographic indicators |
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|
Sex group |
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|
|
Male |
9/361 |
2.5% |
1.0 |
|
1.0 |
|
||
Female non-SW |
3/83 |
3.6% |
1.5 |
0.39–5.5 |
1.2 |
0.73–1.90 |
||
Female SW |
1/34 |
2.9% |
1.2 |
0.1–9.6 |
1.21 |
0.50–2.97 |
||
Age (years) |
|
|
|
|
|
|
|
|
20 or less |
1/69 |
1.4% |
1.0 |
|
1.0 |
|
||
21–24 |
3/183 |
1.6% |
1.1 |
0.12–11.08 |
0.8 |
0.7–9.44 |
||
25–29 |
6/186 |
3.2% |
2.3 |
0.27–19.2 |
0.8 |
0.06–10.2 |
||
30+ |
3/42 |
7.1% |
5.2 |
0.52–52.04 |
2.7 |
0.19–38.5 |
||
Education |
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|
|
|
|
|
|
Secondary |
9/350 |
2.6% |
1.0 |
|
1.0 |
|
||
Attended higher |
4/125 |
3.2% |
1.3 |
0.37–4.14 |
2.2 |
0.55–8.63 |
||
Main source of income |
|
|
|
|
|
|
|
|
Regular work |
8/157 |
5.1% |
1.0 |
|
1.0 |
|
||
Other |
5/318 |
1.6% |
0.3 |
0.09–0.92 |
0.2 |
0.048–0.75 |
||
Drug use |
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|
|
|
|
|
|
Duration of injection (years) |
|
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|
|
|
|
|
|
5 or less |
7/269 |
2.6% |
1.0 |
|
1.0 |
|
||
More than 5 |
6/211 |
2.8% |
1.1 |
0.36–3.31 |
0.3 |
0.076–1.29 |
||
Last day injected, number of times injected |
|
|
|
|
|
|
|
|
Once |
6/333 |
1.8% |
1.0 |
|
1.0 |
|
||
2+ |
7/147 |
4.8% |
2.7 |
0.90–8.25 |
3.0 |
0.75–11.9 |
||
Frequency of injection |
|
|
|
|
|
|
|
|
< Daily |
6/401 |
1.5% |
1.0 |
|
1.0 |
|
||
Daily |
7/77 |
9.1% |
6.6 |
2.15–20.2 |
6.9 |
1.91–25.08 |
||
Main drug injected in the last 4 weeks |
|
|
|
|
|
|
|
|
Heroin |
11/397 |
2.8% |
1.0 |
|
– |
|
||
Vint |
1/53 |
1.9% |
0.7 |
0.08–5.33 |
– |
– |
||
Other |
1/24 |
4.2% |
1.5 |
0.19–12.3 |
– |
– |
||
Ever injected home made drugs? |
|
|
|
|
|
|
|
|
No |
12/355 |
3.4% |
1.0 |
|
1.0 |
|
||
Yes |
1/125 |
0.8% |
0.2 |
0.03–1.79 |
0.4 |
0.05–3.47 |
||
Injecting risk behaviours |
|
|
|
|
|
|
|
|
Injected with used n/s in last 4 weeks? |
|
|
|
|
|
|
|
|
No |
11/418 |
2.6% |
1.0 |
|
1.0 |
|
||
Yes |
2/59 |
3.4% |
1.3 |
0.28–6.01 |
0.3 |
0.02–3.21 |
||
© 2006 The Authors. Journal compilation © 2006 Society for the Study of Addiction |
Addiction, 101, 252–266 |
256 |
Tim Rhodes et al. |
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Table 2 Cont. |
|
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|
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|
|
|
|
|
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|
|
|
|
|
|
|
Unadjusted |
|
|
Adjusted |
|
|
No HIV+/total |
% HIV + |
|
|
|
|
|
|
|
|
|
|
|
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|
||
Variable |
|
OR |
95% CI |
|
OR |
95% CI |
||
|
|
|||||||
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|
|
|
|
|
Used communal spoon or glass in last 3 weeks |
|
|
|
|
|
|
|
|
No |
5/217 |
2.3% |
1.0 |
|
1.0 |
|
||
Yes |
8/259 |
3.1% |
1.4 |
0.44–4.19 |
0.7 |
0.16–2.77 |
||
Ever injected with used needles or syringes? |
|
|
|
|
|
|
|
|
No |
5/181 |
2.8% |
1.0 |
|
1.0 |
|
||
Yes |
8/279 |
2.9% |
1.0 |
0.33–3.23 |
0.5 |
0.10–1.94 |
||
Injected with n/s previously used by sex partner in last 12 months |
|
|
|
|
|
|
||
No |
8/404 |
2.0% |
1.0 |
|
1.0 |
|
||
Yes |
3/30 |
10.0% |
5.5 |
1.37–21.9 |
9.6 |
1.95–47.04 |
||
Sexual risk behaviours |
|
|
|
|
|
|
|
|
Total number of sex partners in last 12 months |
|
|
|
|
|
|
|
|
0/1 |
8/188 |
4.3% |
1.0 |
|
1.0 |
|
||
2+ |
5/281 |
1.8% |
2.4 |
0.79–7.59 |
1.4 |
0.38–5.03 |
||
Have you ever had an STI? |
|
|
|
|
|
|
|
|
No |
7/306 |
2.3% |
1.0 |
|
1 |
|
||
Yes |
5/163 |
3.1% |
1.4 |
0.42–4.33 |
0.8 |
0.20–2.89 |
||
Environmental indicators |
|
|
|
|
|
|
|
|
Have you ever been in prison? |
|
|
|
|
|
|
|
|
No |
12/368 |
3.3% |
1.0 |
|
0 |
0 |
||
Yes |
1/108 |
0.9% |
0.3 |
0.04–2.16 |
0 |
0 |
||
Registered as a drug user at a narcology clinic? |
|
|
|
|
|
|
|
|
No |
6/350 |
1.7% |
1.0 |
|
1.0 |
|
||
Yes |
5/118 |
4.2% |
2.5 |
0.08–8.47 |
1.7 |
0.44–6.31 |
||
OR = odds ratio 95% CI = 95% confidence interval. Final model adjusted for main source of income in the last 4 weeks, frequency of injection and injection with used needle/syringe of sex partner in the last 12 months.
multiple people to distribute the drug solute or injecting with prefilled syringes (usually prefilled prior to purchase). The majority of the sample (82%) reported injecting less than daily. More than half (59%) reported
inconsistent condom use during vaginal sex with a nonpaying sexual partner in the last 4 weeks. Among female IDUs, 24% (105/433) had exchanged sex for money, drugs or goods in the last 4 weeks.
Table 3 Univariable and multivariable analysis of risk factors associated with HIV among injecting drug users in Barnaul.
|
|
|
|
|
|
|
|
Adjusted analysis |
|
||
|
|
|
|
|
|
|
|
|
|
||
|
|
|
|
Unadjusted analysis |
|
Logistic regression* |
GEE† |
|
|||
|
No HIV+/total |
% HIV + |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
||
|
|
|
|
|
|
|
|
|
|
||
Variable |
|
OR |
95% CI |
OR* |
95% CI |
OR† |
95% CI |
||||
|
|
|
|
|
|
|
|
|
|
|
|
Demographic indicators |
|
|
|
|
|
|
|
|
|
|
|
Sex worker |
|
|
|
|
|
|
|
|
|
|
|
Male |
31/343 |
9.0% |
1.0 |
|
1.0 |
|
1.0 |
|
|||
Female |
13/153 |
8.5% |
0.9 |
0.47–1.84 |
0.3 |
0.13–0.72 |
0.7 |
0.44–1.27 |
|||
Sex worker |
2/33 |
6.1% |
0.7 |
0.15–2.84 |
– |
|
0.5 |
0.19–0.12 |
|||
Age (years) |
|
|
|
|
|
|
|
|
|
|
|
< 20 |
12/145 |
8.3% |
1.0 |
|
1.0 |
|
1.0 |
|
|||
21–24 |
15/122 |
12.3% |
1.6 |
0.70–3.46 |
1.9 |
0.74–4.64 |
0.7 |
0.43–1.09 |
|||
25–29 |
10/113 |
8.8% |
1.1 |
0.45–2.59 |
1.3 |
0.48–3.59 |
0.9 |
0.43–1.09 |
|||
30 > |
7/116 |
6.0% |
0.7 |
0.27–1.87 |
1.2 |
0.36–3.99 |
1.0 |
0.34–2.20 |
|||
Education |
|
|
|
|
|
|
|
|
|
|
|
Secondary |
32/429 |
7.5% |
1.0 |
|
1.0 |
|
1.0 |
|
|||
Attended higher |
12/67 |
17.9% |
2.7 |
1.32–5.57 |
2.2 |
0.96–4.95 |
1.4 |
0.66–2.83 |
|||
© 2006 The Authors. Journal compilation © 2006 Society for the Study of Addiction |
Addiction, 101, 252–266 |
|
|
|
|
|
HIV, HCV and syphilis among Russian IDU |
257 |
||||||
Table 3 Cont. |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Adjusted analysis |
|
|
||
|
|
|
|
|
|
|
|
|
|
|
||
|
|
|
|
Unadjusted analysis |
|
Logistic regression* |
|
GEE† |
|
|
||
|
No HIV+/total |
% HIV + |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
||
Variable |
|
OR |
95% CI |
|
OR* |
95% CI |
|
OR† |
95% CI |
|||
|
|
|
||||||||||
|
|
|
|
|
|
|
|
|
|
|
|
|
Main source of income in last 4 weeks |
|
|
|
|
|
|
|
|
|
|
|
|
Regular work |
15/135 |
11.1% |
1.0 |
|
1.0 |
|
1.0 |
|
|
|||
Other |
29/356 |
8.1% |
0.7 |
0.37–1.37 |
0.67 |
0.33–1.39 |
0.8 |
0.57–1.05 |
||||
Drug use |
|
|
|
|
|
|
|
|
|
|
|
|
Duration of injection (years) |
|
|
|
|
|
|
|
|
|
|
|
|
2 years or less |
19/152 |
12.5% |
1.0 |
|
1.0 |
|
1.0 |
|
|
|||
3–5 |
7/105 |
6.7% |
0.1 |
0.20–1.24 |
0.72 |
0.27–1.93 |
0.8 |
0.28–2.25 |
||||
6–9 |
13/111 |
11.7% |
0.9 |
0.44–1.97 |
1.4 |
0.53–3.59 |
1.1 |
0.37–3.12 |
||||
10+ |
5/128 |
3.9% |
0.3 |
0.10–0.79 |
0.45 |
0.13–1.58 |
1.0 |
0.56–1.61 |
||||
Last day injected, number of days injected |
|
|
|
|
|
|
|
|
|
|
|
|
Once |
35/304 |
11.5% |
1.0 |
|
1.0 |
|
1.0 |
|
|
|||
2+ |
9/190 |
4.7% |
0.4 |
0.18–0.81 |
0.5 |
0.19–1.11 |
0.7 |
0.58–0.93 |
||||
Frequency of injection |
|
|
|
|
|
|
|
|
|
|
|
|
< Daily |
35/394 |
8.9% |
1.0 |
|
1.0 |
|
1.0 |
|
|
|||
Daily |
9/98 |
9.2% |
1.0 |
0.48–2.24 |
1.1 |
0.44–2.70 |
0.8 |
0.32–1.86 |
||||
Main drug injected in the last 4 weeks |
|
|
|
|
|
|
|
|
|
|
|
|
Mak + Vint |
8/219 |
3.7% |
1.0 |
|
1.0 |
|
1.0 |
|
|
|||
Heroin |
36/273 |
13.2% |
4.0 |
1.82–8.81 |
3.2 |
1.40–7.37 |
1.0 |
0.56–1.78 |
||||
Ever injected home made drugs? |
|
|
|
|
|
|
|
|
|
|
|
|
Yes |
35/443 |
7.9% |
1.0 |
|
1.0 |
|
1.0 |
|
|
|||
No |
9/53 |
17.0% |
2.4 |
1.07–5.28 |
1.0 |
0.39–2.62 |
1.0 |
0.35–2.73 |
||||
Injecting risk behaviours |
|
|
|
|
|
|
|
|
|
|
|
|
Injected with used n/s in last 4 weeks |
|
|
|
|
|
|
|
|
|
|
|
|
No |
40/420 |
9.5% |
1.0 |
|
1.0 |
|
1.0 |
|
|
|||
Yes |
4/72 |
5.6% |
0.6 |
0.19–1.61 |
0.38 |
0.11–1.34 |
0.9 |
0.61–1.37 |
||||
Used common spoon/glass in last 4 weeks? |
|
|
|
|
|
|
|
|
|
|
|
|
No |
17/325 |
5.2% |
1.0 |
|
1.0 |
|
1.0 |
|
|
|||
Yes |
27/160 |
16.9% |
3.7 |
1.93–6.98 |
4.7 |
2.29–9.62 |
1.7 |
1.10–2.56 |
||||
Filled up your syringe from a working syringe in last 4 weeks? |
|
|
|
|
|
|
|
|
||||
No |
6/111 |
5.4% |
1.0 |
|
1.0 |
|
1.0 |
|
|
|||
Yes |
38/374 |
10.2% |
2.0 |
0.81–4.81 |
5.0 |
1.75–14.1 |
1.2 |
0.74–2.08 |
||||
Ever injected with used n/s? |
|
|
|
|
|
|
|
|
|
|
|
|
No |
23/222 |
10.4% |
1.0 |
|
1.0 |
|
1.0 |
|
|
|||
Yes |
20/251 |
8.0% |
0.8 |
0.40–1.40 |
0.59 |
0.28–1.24 |
1.0 |
0.57–1.57 |
||||
Sexual risk behaviours |
|
|
|
|
|
|
|
|
|
|
|
|
Total number of sex partners in last 12 months |
|
|
|
|
|
|
|
|
|
|
||
2+ |
22/344 |
6.4% |
1.0 |
|
1.0 |
|
1.0 |
|
|
|||
0/1 |
20/145 |
13.8% |
2.3 |
1.23–4.44 |
3.6 |
1.70–7.65 |
1.4 |
0.67–2.75 |
||||
Have you ever had an STI? |
|
|
|
|
|
|
|
|
|
|
|
|
No |
29/295 |
9.8% |
1.0 |
|
1.0 |
|
1.0 |
|
|
|||
Yes |
15/199 |
7.5% |
0.8 |
0.39–1.43 |
1.33 |
0.64–2.81 |
0.8 |
0.47–1.45 |
||||
Environmental indicators |
|
|
|
|
|
|
|
|
|
|
|
|
Have you ever been in prison? |
|
|
|
|
|
|
|
|
|
|
|
|
No |
36/324 |
11.1% |
1.0 |
|
1.0 |
|
1.0 |
|
|
|||
Yes |
8/170 |
4.7% |
0.4 |
0.18–0.87 |
0.2 |
0.09–0.57 |
0.8 |
0.56–1.08 |
||||
Registered as a drug user at a narcology clinic? |
|
|
|
|
|
|
|
|
|
|
||
No |
32/389 |
8.2% |
1.0 |
|
1.0 |
|
1.0 |
|
|
|||
Yes |
12/98 |
12.2% |
1.6 |
0.77–3.15 |
1.9 |
0.78–4.47 |
1.4 |
0.90–2.02 |
||||
OR = odds ratio 95% CI = 95% confidence interval. *Logistic regression final model adjusted for sex, use of communal spoon/glass, filled syringe from a working syringe, number of sex partners and ever having been in prison. †GEE adjusted model, final model adjusted for number of times injected on last day of injection and use of communal spoon/glass.
© 2006 The Authors. Journal compilation © 2006 Society for the Study of Addiction |
Addiction, 101, 252–266 |
Addiction of Study the for Society 2006 © compilation Journal .Authors The 2006 ©
266–252 ,101 Addiction,
Table 4 Univariable risk factors associated with hepatitis C among injecting drug users in Moscow, Volgograd and Barnaul.
|
Moscow |
|
|
|
Volgograd |
|
|
|
Barnaul |
|
|
|
||
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Variable |
No ve+/total |
% + ve |
OR |
95% CI |
|
No + ve/total |
% + ve |
OR |
95% CI |
|
No + ve/total |
% + ve |
OR |
95% CI |
|
|
|||||||||||||
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Demographic |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Sex |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Male |
193/277 |
69.7% |
1.0 |
|
287/384 |
74.7% |
1.0 |
|
193/336 |
57.4% |
1.0 |
|
||
Female non-sex worker |
73/109 |
67.0% |
0.9 |
0.55–1.42 |
56/88 |
63.6% |
0.6 |
0.25–0.60 |
55/119 |
46.2% |
0.6 |
0.42–0.97 |
||
Female sex worker |
13/31 |
41.9% |
0.3 |
0.15–0.67 |
10/36 |
27.8% |
0.1 |
0.06–0.28 |
15/33 |
45.5% |
0.6 |
0.30–1.27 |
||
Age (years) |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
20 or less |
37/60 |
61.7% |
1.0 |
35/70 |
50.0% |
|
1.0 |
|
47/144 |
32.6% |
1.0 |
|
||
21–24 |
89/121 |
73.6% |
1.7 |
0.89–3.34 |
145/196 |
74.0% |
2.8 |
1.61–5.01 |
65/120 |
54.2% |
2.4 |
1.47–2.02 |
||
25–29 |
112/162 |
69.1% |
1.4 |
0.75–2.58 |
147/200 |
73.5% |
2.8 |
1.57–4.87 |
66/110 |
60.0% |
3.1 |
1.85–5.19 |
||
30+ |
58/91 |
63.7% |
1.1 |
0.56–2.14 |
28/44 |
63.6% |
1.8 |
0.80–3.79 |
85/114 |
74.6% |
6.0 |
3.5–10.5 |
||
Education |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Secondary1.0 |
183/272 |
67.3% |
1.0 |
|
257/369 |
69.6% |
|
1.0 |
|
|
233/423 |
|
55.1% |
|
Attended higher |
111/156 |
71.2% |
1.2 |
0.78–1.84 |
96/136 |
70.6% |
1.0 |
0.68–1.61 |
30/65 |
46.2% |
0.7 |
0.41–1.2 |
||
Main source of income in last 4 weeks |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Regular work |
130/175 |
74.3% |
1.0 |
|
130/172 |
75.6% |
1.0 |
|
80/132 |
60.6% |
1.0 |
|
||
Other |
161/249 |
64.7% |
0.6 |
0.41–0.97 |
221/332 |
66.6% |
0.6 |
0.42–0.98 |
180/351 |
51.3% |
0.7 |
0.45–1.03 |
||
Drug use |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Duration of injection (years) |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2 or less |
24/43 |
55.8% |
1.0 |
|
47/99 |
47.5% |
1.0 |
|
47/152 |
30.9% |
1.0 |
|
||
3–5 |
63/99 |
63.6% |
1.4 |
0.67–2.87 |
136/185 |
73.5% |
3.1 |
1.84–5.21 |
42/102 |
41.2% |
1.6 |
0.93–2.64 |
||
6–9 |
132/179 |
73.7% |
2.2 |
1.12–4.42 |
131/166 |
78.9% |
4.1 |
2.4–7.12 |
73/107 |
68.2% |
4.8 |
2.8–8.17 |
||
10+ |
74/110 |
67.3% |
1.6 |
0.79–3.35 |
41/60 |
68.3% |
2.4 |
1.2–4.67 |
101/127 |
79.5% |
8.7 |
5.0–15.1 |
||
Last day injected, number of days injected |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Once |
158/235 |
67.2% |
1.0 |
234/349 |
67.0% |
|
1.0 |
|
161/301 |
53.5% |
1.0 |
|
||
2+ |
136/196 |
69.4% |
1.1 |
0.73–1.66 |
121/161 |
75.2% |
1.5 |
0.98–2.26 |
100/185 |
54.1% |
1.0 |
0.71–1.5 |
||
Frequency of injection |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
< Daily |
232/347 |
66.9% |
1.0 |
295/422 |
69.9% |
|
1.0 |
|
189/386 |
49.0% |
1.0 |
|
||
Daily |
57/79 |
72.2% |
1.3 |
0.75–2.20 |
59/86 |
68.6% |
1.0 |
0.57–1.55 |
71/98 |
72.4% |
2.7 |
1.69–4.46 |
||
Main drug injected in last 4 weeks |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Heroin |
179/267 |
67.0% |
1.0 |
293/421 |
69.6% |
|
1.0 |
|
145/271 |
53.5% |
1.0 |
|
||
Vint + mak |
68/92 |
73.9% |
1.4 |
0.82–2.37 |
44/58 |
75.9% |
1.4 |
0.73–2.6 |
117/212 |
55.2% |
1.1 |
0.75–1.53 |
||
Other |
41/65 |
63.1% |
0.8 |
0.48–1.48 |
15/25 |
60.0% |
0.6 |
0.29–1.49 |
1/5 |
20% |
0.2 |
0.02–1.97 |
||
OR = odds ratio 95% CI = 95% confidence interval.
.al et Rhodes Tim 258
Addiction of Study the for Society 2006 © compilation Journal .Authors The 2006 ©
266–252 ,101 Addiction,
|
Moscow |
|
|
|
Volgograd |
|
|
|
Barnaul |
|
|
|
Variable |
No ve+/total |
% + ve |
OR |
95% CI |
No + ve/total |
% + ve |
OR |
95% CI |
No + ve/total |
% + ve |
OR |
95% CI |
|
|
|
|
|
|
|
|
|
|
|
|
|
Ever injected home made drugs |
|
|
|
|
|
|
|
|
|
|
|
|
No |
13/40 |
32.5% |
1.0 |
68/130 |
52.3% |
|
1.0 |
|
13/53 |
24.5% |
1.0 |
|
Yes |
283/394 |
71.8% |
5.3 |
2.64–10.6 |
287/380 |
75.5% |
2.8 |
1.9–4.3 |
250/435 |
57.5% |
4.2 |
2.2–8.0 |
Injecting risk behaviours |
|
|
|
|
|
|
|
|
|
|
|
|
Injected with used needles/syringes in the last 4 weeks? |
|
|
|
|
|
|
|
|
|
|
||
Yes |
236/356 |
66.3% |
1.0 |
304/444 |
68.5% |
|
1.0 |
|
219/414 |
52.9% |
1.0 |
|
No |
48/62 |
77.4% |
1.7 |
0.92–3.29 |
47/62 |
75.8% |
1.5 |
0.78–2.67 |
42/70 |
60.0% |
1.3 |
0.80–2.24 |
Front loaded in last 4 weeks? |
|
|
|
|
|
|
|
|
|
|
|
|
No |
251/386 |
65.0% |
1.0 |
334/481 |
|
69.4% |
1.0 |
|
230/446 |
51.6% |
1.0 |
|
Yes |
32/34 |
94.1% |
8.6 |
2.03–36.5 |
19/24 |
79.2% |
1.7 |
0.61–4.56 |
31/39 |
79.5% |
3.6 |
1.6–8.1 |
Used common spoon/glass in last 4 weeks? |
|
|
|
|
|
|
|
|
|
|
|
|
No |
177/296 |
59.8% |
1.0 |
159/236 |
|
67.4% |
1.0 |
|
166/320 |
51.9% |
1.0 |
|
Yes |
100/149 |
67.1% |
1.5 |
0.97–2.38 |
194/269 |
72.1% |
1.3 |
0.86–1.83 |
91/157 |
58.0% |
1.3 |
0.87–1.88 |
Placed your needle in a filter in which someone had previously put their n/s in last 4 weeks? |
|
|
|
|
|
|
|
|||||
No |
209/320 |
65.3% |
1.0 |
|
217/330 |
65.8% |
1.0 |
|
203/392 |
51.8% |
1.0 |
|
Yes |
70/93 |
75.3% |
1.6 |
0.96–2.73 |
138/177 |
78.0% |
1.8 |
1.2–2.81 |
56/87 |
64.4% |
1.7 |
1.03–2.7 |
Ever injected with used needles/syringes? |
|
|
|
|
|
|
|
|
|
|
|
|
No |
79/140 |
56.4% |
1.0 |
|
114/193 |
59.1% |
1.0 |
|
219/419 |
52.3% |
1.0 |
|
Yes |
198/259 |
76.4% |
2.5 |
1.61–3.89 |
227/296 |
76.7% |
2.3 |
1.54–3.38 |
44/69 |
63.8% |
1.6 |
0.95–2.72 |
Average reuse of the same needle |
|
|
|
|
|
|
|
|
|
|
|
|
Once |
133/222 |
59.9% |
1.0 |
|
259/376 |
68.9% |
1.0 |
|
166/342 |
48.5% |
1.0 |
|
1+ |
152/197 |
77.2% |
2.3 |
1.47–3.47 |
95/133 |
71.4% |
1.1 |
0.73–1.74 |
95/144 |
66.0% |
2.1 |
1.4–3.1 |
Environmental indicators |
|
|
|
|
|
|
|
|
|
|
|
|
Have you ever been in prison? |
|
|
|
|
|
|
|
|
|
|
|
|
No |
215/319 |
67.4% |
1.0 |
|
265/391 |
67.8% |
1.0 |
|
145/320 |
45.3% |
1.0 |
|
Yes |
80/114 |
70.2% |
1.1 |
0.72–1.81 |
87/115 |
75.7% |
1.5 |
0.92–2.38 |
117/166 |
70.5% |
2.9 |
1.93–4.3 |
Have you ever been in drug treatment? |
|
|
|
|
|
|
|
|
|
|
|
|
No |
177/283 |
62.5% |
1.0 |
|
182/283 |
64.3% |
1.0 |
|
160/344 |
46.5% |
1.0 |
|
Yes |
118/149 |
79.2% |
2.3 |
1.43–3.62 |
169/223 |
75.8% |
1.7 |
1.17–2.57 |
103/144 |
71.5% |
2.9 |
1.9–4.4 |
Registered as an IDU at a narcology clinic? |
|
|
|
|
|
|
|
|
|
|
|
|
No |
209/310 |
67.4% |
1.0 |
|
238/370 |
64.3% |
1.0 |
|
191/384 |
49.7% |
1.0 |
|
Yes |
79/91 |
86.8% |
2.5 |
1.34–4.47 |
108/128 |
84.4% |
3.0 |
1.78–5.05 |
69/96 |
71.9% |
2.6 |
1.6–4.2 |
OR = odds ratio 95% CI = 95% confidence interval.
259 IDU Russian among syphilis and HCV HIV,
260 Tim Rhodes et al.
HIV prevalence
The prevalence of anti-HIV was 14% (55/403, 95% CI 10.3–17.0%) in Moscow, 3% (13/477, 95% CI 1.3– 4.2%) in Volgograd and 9% (44/499, 95% CI 6.3– 11.3%) in Barnaul (Table 5). A third (34%) of those HIV antibody positive in the total sample self-reported as such. Between half (52% and 53% in Moscow and Barnaul, respectively) and three-quarters (74.5% in Volgograd) of IDUs had been HIV tested in the last year. Almost all (92%) of those anti-HIV positive were also anti-HCV positive.
Table 1 shows prevalence of anti-HIV in the survey sample by key characteristics of participants in Moscow. In the univariable analysis, prevalence and odds were higher among IDU who reported that on the last day of injection they only injected once (OR = 1.6, 95% CI 1.38– 5.02) and among those who had ever injected with a used needle or syringe (OR = 3.1, 95% CI 1.23–7.77). Of the environmental risk factors, odds of being positive to anti-HIV was higher among those who had ever been in prison (OR = 1.9, 95% CI 1.46–2.53) and among those who were registered as a drug user at the narcology service (OR = 2.4, 95% CI 1.26–4.65). Odds of being anti-HIV positive were lower among those who reported ever having a sexually transmitted infection (STI) (OR = 0.5, 95% CI 0.25–0.85). Prevalence and odds also increased by duration of injection.
After adjustment, five variables remained associated with anti-HIV in both standard logistic regression and GEE-adjusted models. There was no substantial difference in the GEE and logistic regression models indicating that there was limited clustering of risk behaviours related to fieldworkers, so only one set of figures are presented below (GEE estimates available on request). IDUs who reported that they had ever injected with used needles/ syringes were three times as likely to be anti-HIV positive than those who had not (OR 3.5, 95% CI 1.43–8.36). IDUs who reported a history of prison were twice as likely
to be found positive to anti-HIV than those who had never been in prison (OR = 2.2, 95% CI 1.0–4.65), and those officially registered at narcology (drug treatment) services were twice as likely to test positive to anti-HIV (OR = 2.3, 95% CI 1.12–5.05). IDUs who reported ever having an STI were less likely to test positive for anti-HIV (OR = 0.3, 95% CI 0.15–0.70). Those reporting on the last day that they injected they had injected once compared to twice were more likely to be positive to anti-HIV (OR = 2.4, 95% CI 1.12–5.05).
Table 2 shows univariable and multivariable risk factors for antibodies to HIV among IDU in Volgograd. The same variables were significant in both adjusted and unadjusted analyses. In the adjusted model, IDUs reporting that they had injected with a used needle/syringe of a sex partner in the last year were almost 10 times more likely to be found anti-HIV positive than those who had not (OR = 9.6, 95% CI 1.95–47.0). IDUs who reported injecting daily had increased odds of testing positive for anti-HIV (OR = 6.9, 95% CI 1.91–25.1) compared to those injecting less than daily. Finally, those who reported not having a regular job were less likely (OR = 0.2, 95% CI 0.05–0.75) to be positive for anti-HIV than those with a regular job. The small number of HIV cases in this city prevented the use of the GEE model.
Table 3 shows univariable and multivariable risk factors for antibodies to HIV among IDU in Barnaul. In the univariable analysis the following risk factors were associated with testing positive for antibodies to HIV: injecting heroin compared to home-made drugs (OR = 4.0 95% CI 1.82–8.81); use of communal spoon (OR = 3.7, 95% CI 1.93–6.98); having one or no sex partners in the last 12 months compared to having two or more (OR = 2.3, 95% CI 1.23–4.44); and never having injected homeproduced drugs (OR = 2.4 95% CI 1.07–5.28). Reduced odds of anti-HIV were associated with injecting twice on the last day of injection compared to once (OR = 0.4, 95% CI 0.18–0.81) and having been in prison (OR = 0.4, 95% CI 0.18–0.87). After adjustment, the logistic regression
Table 5 Antibodies to HIV, hepatitis C and syphilis among injecting drug users in Moscow, Volgograd and Barnaul, 2003. Values are numbers (percentages) of IDUs.
|
Moscow no. (%) |
Volgograd no. (%) |
Barnaul no. (%) |
|||
|
|
|
|
|
|
|
Total sample† |
455 |
(100) |
514 |
(100) |
504 |
(100) |
HIV |
55 |
(14) |
13 |
(3) |
44 |
(9) |
Tested in the last 12 months |
238 |
(52) |
383 |
(75) |
254 |
(53) |
Aware of positive anti-HIV result |
44 |
(24) |
1 |
(8) |
13 |
(30) |
HCV |
296 |
(68) |
353 |
(70) |
265 |
(54) |
Tested in last 12 months |
214 |
(47) |
377 |
(73) |
177 |
(35) |
Aware of positive anti-HCV result |
147 |
(50) |
224 |
(58) |
58 |
(23) |
Syphilis |
32 |
(8) |
93 |
(20) |
32 |
(6) |
Ever tested for an STI |
189 |
(43) |
174 |
(34) |
200 |
(40) |
†Numbers do not always add up to total because not all oral fluid samples produced a valid antibody result. |
|
© 2006 The Authors. Journal compilation © 2006 Society for the Study of Addiction |
Addiction, 101, 252–266 |
model indicated increased odds associated with anti-HIV for the following risk factors: female IDUs were less likely to be positive for anti-HIV than men (OR = 0.3, 95% CI 0.13–0.72); and participants who had been in prison were less likely to be positive to anti-HIV than those with no prison experience (OR = 0.2, 95% CI 0.09–0.57). Increased odds of HIV were associated with injecting heroin compared to vint or mak (OR = 3.2, 95% CI 1.40–7.37), use of a communal spoon (OR = 4.7, 95% CI 2.29–9.62) and injecting from a communal working syringe (OR = 5.0, 95% CI 1.75–14.1).
In Barnaul, there was strong evidence of clustering of HIV by fieldworkers. All HIV cases were found among respondents interviewed by two fieldworkers and all these respondents reported heroin as their main drug. This might suggest that the cases were concentrated in one or two networks recruited by fieldworkers. After adjustment with the GEE model, only two risk factors remained associated with being positive to anti-HIV. First, those who reported that on the last day of injection they had injected twice were slightly less likely be anti-HIV positive than those who had injected once (OR = 0.7, 95% CI 0.58– 0.93). Secondly, IDUs who reported sharing communal spoons for the preparation of drugs were more likely to be anti-HIV positive than those who had not (OR = 1.7, 95% CI 1.1–2.56).
HCV prevalence
The prevalence of anti-HCV was 68% (296/434, 95% CI 63.8–72.6%) in Moscow, 70% (353/507, 95% CI 65.6– 73.6%) in Volgograd and 54% (265/491, 95% CI 49.5– 58.4%) in Barnaul (Table 5). Half (48%) of those found HCV antibody positive in the total sample self-reported as such. Of those with a history of HCV testing and reporting their last test to be antibody negative (n = 454), 52% were anti-HCV positive. While most IDUs were HCV tested in the last year in Volgograd (73%), this was the case for only a third (35%) in Barnaul and a half (47%) in Moscow).
Table 4 summarizes univariable analysis of risk factors associated with anti-HCV for each of the three cities. For the Moscow sample, key univariable associations indicating increased odds of infection with anti-HCV included ever having injected with a used needle or syringe (OR = 2.5, 95% CI 1.61–3.89), a history of drug treatment (OR = 2.3, 95% CI 1.43–3.62) and being officially registered as a drug user at a narcology service (OR = 2.5, 95% CI 1.34–4.47). Decreased odds were associated with sex work (OR = 0.3, 95% CI 0.15–0.67) and not having a regular source of income (OR = 0.6, 95% CI 0.41–0.97).
In Volgograd, odds and prevalence of anti-HCV increased with age and duration of injection. IDUs who
HIV, HCV and syphilis among Russian IDU |
261 |
reported ever having injected home-produced drugs were more likely to test positive for anti-HCV (OR = 2.8, 95% CI 1.9–4.3). Additionally, increased odds were found among those who had injected using a filter (usually a cotton) used previously by someone else (OR = 1.8, 95% CI 1.2– 2.81) and those who reported ever having injected with a used needle/syringe (OR = 2.3, 95% CI 1.54–3.38). Increased odds were also associated with a history of drug treatment (OR = 2.3, 95% CI 1.17–2.57) and being officially registered as an IDU at a narcology service (OR = 3.0, 95% CI 1.78–5.05). Decreased odds were associated with sex work (OR = 0.1, 95% CI 0.06–0.28).
In Barnaul, odds and prevalence of anti-HCV increased with age and duration of injection. Participants who reported ever having injected home-produced drugs were 4.2 times as likely to be anti-HCV positive than those who had not (95% CI 2.2–8.0). Increased odds were also associated with frontloading (OR = 3.6, 95% CI 1.6–8.1), using with a filter that someone else had used previously (OR = 1.7, 95% CI 1.03–2.7) and reuse of the same needle more than once (OR = 2.1, 95% CI 1.4–3.1). Of the environmental variables, increased odds were associated with ever having been in prison (OR = 2.9, 95% CI 1.93–4.3), a history of drug treatment (OR = 2.9, 95% CI 1.9–4.4) and being officially registered as a drug user at a narcology service (OR = 2.6 95% CI 1.6–4.2).
Table 6 summarizes the risk factors associated with anti-HCV in each site in the multivariable analysis. In Moscow, the adjusted GEE model showed that prevalence and odds of anti-HCV was lower among female IDUs involved in sex work than men (OR = 0.2, 95% CI 0.08– 0.50). IDUs who reported ever having injected with used needles/syringes were almost three times as likely to be anti-HCV positive than those who had not (OR = 2.5, 95% CI 1.57–3.85) and those who reported being officially registered at a narcology service were almost twice as likely to be anti-HCV positive than those who were not (OR = 1.9, 95% CI 1.12–3.13). There was little difference between the adjusted GEE and the standard logistic regression model other than the logistic regression model indicated an association with history of drug treatment (OR = 1.8, 95% CI 1.5–2.98) rather than registration as an IDU and an association with ever having injected home-produced drugs (OR = 3.2, 95% CI 1.48–6.72).
In Volgograd, the adjusted GEE model again showed that female IDUs (OR = 0.7, 95% CI 0.51–0.95) and female IDU sex workers (OR = 0.3, 95% CI 0.11–0.66) were less likely to be anti-HCV positive than male IDUs. Prevalence and odds of testing positive for anti-HCV increased by duration of injection, participants who reported injecting between 3 and 5 years were 2.5 times more likely be found anti-HCV positive (OR = 2.4, 95% CI 1.55–3.66) and those who reported injecting between 6 and 9 years had almost three times the odds of testing
© 2006 The Authors. Journal compilation © 2006 Society for the Study of Addiction |
Addiction, 101, 252–266 |