Marked overlap between the HIV and injection drug use epidemics in St. Petersburg, Russia, puts many people in need of health services at risk for stigmatization based on both characteristics simultaneously. The current study examined the independent and interactive effects of internalized HIV and drug stigmas on health status and health service utilization among 383 people with HIV who inject drugs in St. Petersburg. Participants self-reported internalized HIV stigma, internalized drug stigma, health status (subjective rating and symptom count), health service utilization (HIV care and drug treatment), sociodemographic characteristics, and health/behavioral history. For both forms of internalized stigma, greater stigma was correlated with poorer health and lower likelihood of service utilization. HIV and drug stigmas interacted to predict symptom count, HIV care, and drug treatment such that individuals internalizing high levels of both stigmas were at elevated risk for experiencing poor health and less likely to access health services.

ObjectivesTo ascertain HIV prevalence among people who inject drug (injection drug users (IDUs)) in the Russian Federation and identify explanations for the disparity in different cities.DesignCross-sectional survey with serological testing for HIV and hepatitis C virus prevalent infections.Setting8 Russian cities—Irkutsk, Omsk, Chelyabinsk, Yekaterinburg, Naberezhnye Chelny, Voronezh, Orel and St Petersburg.ParticipantsIn 2007–2009 active IDUs were recruited by respondent-driven sampling with a target sample size of 300 or more in each city.Main outcome measuresParticipants were administered a questionnaire covering sociodemographics, injection risk and protective behaviours, sexual behaviours, HIV knowledge, experiences with drug treatment and harm reduction programmes and social networks. Participants were tested for HIV and hepatitis C by enzyme immunoassay. Data were analysed to identify individual-level, network-level and city-level characteristics significantly associated with HIV prevalence. Factors significant at p≤0.1 were entered into a hierarchical regression model to control for multicollinearity.ResultsA total of 2596 active IDUs were recruited, interviewed and tested for HIV and hepatitis C virus infection. HIV prevalence ranged from 3% (in Voronezh) to 64% (in Yekaterinburg). Although individual-level and network-level variables explain some of the difference in prevalence across the eight cities, the over-riding variable that seems to account for most of the variance is the emergence of commercial, as opposed to homemade, heroin as the predominant form of opioid injected.ConclusionsThe expansion of commercial heroin markets to many Russian cities may have served as a trigger for an expanding HIV epidemic among IDUs in that country.

BackgroundAutomatic stepwise subset selection methods in linear regression often perform poorly, both in terms of variable selection and estimation of coefficients and standard errors, especially when number of independent variables is large and multicollinearity is present. Yet, stepwise algorithms remain the dominant method in medical and epidemiological research.MethodsPerformance of stepwise (backward elimination and forward selection algorithms using AIC, BIC, and Likelihood Ratio Test, p = 0.05 (LRT)) and alternative subset selection methods in linear regression, including Bayesian model averaging (BMA) and penalized regression (lasso, adaptive lasso, and adaptive elastic net) was investigated in a dataset from a cross-sectional study of drug users in St. Petersburg, Russia in 2012–2013. Dependent variable measured health-related quality of life, and independent correlates included 44 variables measuring demographics, behavioral, and structural factors.ResultsIn our case study all methods returned models of different size and composition varying from 41 to 11 variables. The percentage of significant variables among those selected in final model varied from 100 % to 27 %. Model selection with stepwise methods was highly unstable, with most (and all in case of backward elimination: BIC, forward selection: BIC, and backward elimination: LRT) of the selected variables being significant (95 % confidence interval for coefficient did not include zero). Adaptive elastic net demonstrated improved stability and more conservative estimates of coefficients and standard errors compared to stepwise. By incorporating model uncertainty into subset selection and estimation of coefficients and their standard deviations, BMA returned a parsimonious model with the most conservative results in terms of covariates significance.ConclusionsBMA and adaptive elastic net performed best in our analysis. Based on our results and previous theoretical studies the use of stepwise methods in medical and epidemiological research may be outperformed by alternative methods in cases such as ours. In situations of high uncertainty it is beneficial to apply different methodologically sound subset selection methods, and explore where their outputs do and do not agree. We recommend that researchers, at a minimum, should explore model uncertainty and stability as part of their analyses, and report these details in epidemiological papers.Electronic supplementary materialThe online version of this article (doi:10.1186/s12874-015-0066-2) contains supplementary material, which is available to authorized users.

Background Injection drug use, infectious disease, and incarceration are inextricably linked in Russia. We aimed to identify factors associated with time to relapse (first opioid injection after release from prison) and using a non-sterile, previously used syringe at relapse in a sample of people who inject drugs in St. Petersburg. Methods We collected data on time from release to relapse among individuals with a history of incarceration, a subsample of a larger study among people who inject drugs. Proportional hazards and logistic regression were used to identify factors associated with time to relapse and injection with a non-sterile previously used syringe at relapse, respectively. Results The median time to relapse after release was 30 days. Factors that were independently associated with relapsing sooner were being a native of St. Petersburg compared to not being native (AHR: 1.64; 95% CI 1.15 – 2.33), unemployed at relapse compared to employed (AHR: 4.49; 95% CI 2.96 – 6.82) and receiving a previous diagnosis of HBV and HCV compared to no previous diagnosis (AHR: 1.49; 95% CI 1.03 – 2.14). Unemployment at relapse was also significant in modeling injection with a non-sterile, previously used syringe at relapse compared to those who were employed (AOR: 6.80; 95% CI 1.96 – 23.59). Conclusions Unemployment was an important correlate for both resuming opioid injection after release and using a non-sterile previously used syringe at relapse. Linkage to medical, harm reduction, and employment services should be developed for incarcerated Russian people who inject drugs prior to release.

Experiences of stigma are often associated with negative mental and physical health outcomes. The present work tested the associations between stigma and health-related outcomes among people with HIV who inject drugs in Kohtla-Järve, Estonia and St. Petersburg, Russia. These two cities share some of the highest rates of HIV outside of sub-Saharan Africa, largely driven by injection drug use, but Estonia has implemented harm reduction services more comprehensively. People who inject drugs were recruited using respondent-driven sampling; those who indicated being HIV-positive were included in the present sample (n=381 in St. Petersburg; n=288 in Kohtla-Järve). Participants reported their health information and completed measures of internalized HIV stigma, anticipated HIV stigma, internalized drug stigma, and anticipated drug stigma. Participants in both locations indicated similarly high levels of all four forms of stigma. However, stigma variables were more strongly associated with health outcomes in Russia than in Estonia. The St. Petersburg results were consistent with prior work linking stigma and health. Lower barriers to care in Kohtla-Järve may help explain why social stigma was not closely tied to negative health outcomes there. Implications for interventions and health policy are discussed.