Sexual Identity, Stigma, and Depression: the Role of the "Anti-gay Propaganda Law" in Mental Health among Men Who Have Sex with Men in Moscow, Russia.

Depression is a major public health problem in the Russian Federation and is particularly of concern for men who have sex with men (MSM). MSM living in Moscow City were recruited via respondent-driven sampling and participated in a cross-sectional survey from October 2010 to April 2013. Multiple logistic regression models compared the relationship between sexual identity, recent stigma, and probable depression, defined as a score of ≥23 on the Center for Epidemiological Studies Depression scale. We investigated the interactive effect of stigma and participation in the study after the passage of multiple "anti-gay propaganda laws" in Russian provinces, municipalities, and in neighboring Ukraine on depression among MSM. Among 1367 MSM, 36.7% (n = 505) qualified as probably depressed. Fifty-five percent identified as homosexual (n = 741) and 42.9% identified as bisexual (n = 578). Bisexual identity had a protective association against probable depression (reference: homosexual identity AOR 0.71; 95%CI 0.52-0.97; p < 0.01). Those who experienced recent stigma (last 12 months) were more likely to report probable depression (reference: no stigma; AOR 1.75; 95%CI 1.20-2.56; p < 0.01). The interaction between stigma and the propaganda laws was significant. Among participants with stigma, probable depression increased 1.67-fold after the passage of the anti-gay laws AOR 1.67; 95%CI 1.04-2.68; p < 0.01). Depressive symptoms are common among MSM in Russia and exacerbated by stigma and laws that deny homosexual identities. Repeal of Russia's federal anti-gay propaganda law is urgent but other social interventions may address depression and stigma in the current context.

Comparison of Respondent Driven Sampling Estimators to Determine HIV Prevalence and Population Characteristics among Men Who Have Sex with Men in Moscow, Russia.

Analytically distinct estimators have been proposed for the calculation of population-based estimates derived from respondent-driven sampling (RDS), yet there have been few comparisons of the inferences from these estimators using empirical data. We compared estimates produced by unweighted analysis used to calculate sample proportions and by three available estimators that are used to calculate population proportions, RDS-I, RDS-II (Volz-Heckathorn), and Gile's RDS-SS. Data were derived from a cross-sectional, RDS study of men who have sex with men (MSM) conducted from October 2010 to April 2013 in Moscow, Russia (N = 1,376, recruitment depth: 31 waves). Analyses investigated the influence of key parameters: recruitment depth, homophily, and network size on sample and population estimates. Variability in results produced by the estimators and recruitment depth were statistically compared using the coefficient of variation (CV). Sample proportions had the least variability across different recruitment depths, compared to the RDS estimators. Population estimates tended to differ at lower recruitment depth but were approximately equal after reaching sampling equilibrium, highlighting the importance of sampling to greater recruitment depth. All estimators incorporate inverse probability weighting using self-reported network size, explaining the similarities in across population estimates and the difference of these estimates relative to sample proportions. Current biases and limitations associated with RDS estimators are discussed.