Paradoxical Linkage between Mental Health and Social Implications of COVID-19 crisis in Gay, Bisexual Men and transgenders in Eastern Europe and Central Asia: Results of Survey among the Hornet Mobile App Users

Paradoxical Linkage between Mental Health and Social Implications of COVID-19 crisis in Gay, Bisexual Men and transgenders in Eastern Europe and Central Asia: Results of Survey among the Hornet Mobile App Users | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Paradoxical Linkage between Mental Health and Social Implications of COVID-19 crisis in Gay, Bisexual Men and transgenders in Eastern Europe and Central Asia: Results of Survey among the Hornet Mobile App Users Maksym Kasianczuk, Serhii Salnikov, Sean Howell, Alex Garner, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8996854/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background. Limited data exists on how COVID-19 restrictions have affected LGBT in the Eastern Europe and Central Asia (EECA) region. Methods. It was conducted a cross-sectional survey in 2020, involving 5,037 Hornet users in EECA. Results and discussion. A part of the sample belongs to vulnerable groups (lower social status, racial/ethnic minorities, etc). The economic circumstances of GBT were impacted: 21% lost at least 2/3 of income; 21% lost jobs; and 24% found themselves in extreme poverty. More vulnerable populations felt heavily struck (f. e. a food intake had been shortened among transgender people 41% vs 21% among cisgender ones). Despite the limitation of physical freedom and economic losses, the level of depression and anxiety did not exceed the bounds of mild deviations (PHQ-4: 4.7, 95% CI: 4.6–4.8). Conclusions. The data presented suggests the readiness of EECA GBT communities to face future crises. Sociology COVID-19 crisis GBT EECA economic impact mental health disparities Figures Figure 1 Figure 2 Introduction In 2020, COVID-19 became a huge challenge, leading to global restrictions on personal freedoms [ 1 ] . Since May 2020, COVID-19 started having impact on Eastern Europe and Central Asia (EECA) 1 . Countries of the region declared a state of emergency, shutting down schools, restaurants, and shops, suspending operation of the public transport, etc. Although there was a range of publications on the consequences of the COVID-19 crisis in the region [ 2 , 3 ] , its impact on the well-being of vulnerable populations, such as gay and bisexual men, has been poorly studied [ 4 – 6 ] . Existing evidence shows lesbian, gay, bisexual, and transgender (LGBT) people are most vulnerable and disproportionately impacted by crises like COVID-19 or military conflicts [ 7 , 8 ] . Data about LGBT people in the EECA region remains limited [ 9 ] . Mental health challenges. A comparison of cisgender heterosexual people with non-heterosexual and transgender individuals in the United States [ 10 ] demonstrated that during the COVID-19 LGBT people faced more mental health challenges, than cisgender heterosexual people. Compared to gays and lesbians, people with other non-heterosexual orientations had higher levels of depression, anxiety, and chronic stress; bisexual women and lesbians experienced more mental health issues compared to bisexual and gay men [ 11 ] . LGBT showed high levels of stress [ 12 , 13 ] . Data from various countries show the same results [ 4 , 6 , 14 – 16 ] . Other factors also include homo- or transphobic attitudes of health workers in the context of COVID-19 crisis [ 17 ] . The COVID-19 aggravated existing issues, such as the psychological climate in couples [ 14 , 18 , 19 ] , uncertainty about the future, discontinuation of HIV treatment [ 20 , 21 ] and access to HIV services [ 4 , 21 , 22 ] . Economic challenges during COVID-19. The situation of LGBT people worsened [ 4 , 21 , 22 ] . The unequal effect of the COVID-19 related restrictions has been documented in the general population as well [ 23 ] . Vulnerability to COVID-19 was higher in the Brazilian population of bisexual and heterosexual people who have same-sex contacts compared to homosexual people, in cisgender men compared to cisgender women and in people over 50 years of age compared to younger people aged 18–29 [ 15 ] . Analysis of large-scale data from the United States showed that during the COVID-19 epidemic transgender people were much more economically vulnerable than lesbian, gay, bisexual, and heterosexual people [ 24 ] . Changes in sexual life during COVID-19. Some studies showed that number of partners increased during the COVID-19 [ 25 – 27 ] , which could be seen as a strategy to cope with the lockdown-related stress [ 19 ] ; while others, on the contrary, recorded a decrease in this indicator [ 13 , 28 ] . Intersectional impact. Differences in the impact on mental health and economic well-being suggest intersectional and multidimensional linkages between the social and health-related implications of the pandemic and the LGBT agenda [ 15 ] . Thus, the examples of Great Britain and Brazil showed that marginalization of the LGBT communities led to their specific survival strategies [ 29 ] , increased the risks of substance abuse or condomless sexual practices, while such maladaptive behaviours increased the chances of health deterioration among LGBT people compared to heterosexual people [ 30 ] . The COVID-19 had a more devastating impact on the LGBT youth than on the older people [ 21 , 31 ] due to the aggravation of internalized homophobia and dysfunctional family relations. The impact on HIV-positive LGBT people was also intersectional, as they faced higher levels of unemployment, income inequality, and intimate partner violence even before the epidemic. Social restrictions, such as being isolated and having less access to health care, had a negative effect on the life of people living with HIV [ 30 , 32 ] . Even though COVID-19 related restrictions were harmful in many ways, they also contributed to some positive changes for the LGBT communities, such as internationalization of local movements, greater cohesion, and bigger sense of belonging to the community, at least in Japan [ 33 ] and Nigeria [ 20 ] . Some participants of a study in Canada [ 34 ] reported that lockdown restrictions reduced the pressure of traditional gender expectations due to reduction of face-to-face interactions. Thus, the literature on the social implications of COVID-19 for the LGBT community is essentially limited to the Western World and South America, with the region of EECA almost not covered. The EECA region is characterized by economic instability, military and political conflicts, and inequality in access to social services for men who have sex with men (MSM) [ 35 ] , with high levels of external [ 36 ] and internal homophobia [ 37 ] . Our research aims to fill in the gaps in knowledge on the effect of COVID-19 on gay and bisexual men as well as transgender people (GBT) in the EECA region. The main hypothesis is the unequal effect of government-enacted restrictions on the personal freedoms due to COVID-19 on the economic and mental well-being of more and less vulnerable groups of GBT in the EECA region. Methods A cross-sectional survey conducted among users of the Hornet mobile app from March to May 2020. Participants were asked to complete an online questionnaire about health and quality of life during the COVID-19 epidemic. Participants must be at least 18 years old, provide their informed consent, and were identified as male. The survey procedures were reviewed and approved by the Institutional Review Board of the Johns Hopkins School of Public Health (USA). More details on the methodology of the survey can be found elsewhere [ 38 ] . In the present study, we focus on the 5,037 participants from fourteen countries from the EECA region. The countries are assembled into three groups (Fig. 1 ) corresponding to geopolitical and cultural characteristics that emerged following the dissolution of the Soviet Union in 1991. Participants were asked about the effect of the COVID-19 crisis on their economic status, mental health, and quality of life. We performed an analysis of the bivariate distributions of sociodemographic factors, such as HIV status, being a member of a racial/ethnic minority, and immigrant status. We examined differences among the groups using Pearson’s Chi square test (χ 2 ) and Cramèr’s V test with a significance level of α < 0.05 for categorical variables and comparison of the mean values for the PHQ-4 depression and anxiety scale. The calculations were performed in R [ 39 ] . Results Sample characteristics A total of 5,037 GBT participated to the survey in the EECA countries. The largest number were coming from the Russian Federation (76% or 3,847), and Ukraine (12% or 604). Participants per sexual and gender identity and per subregions are presented in Fig. 2 . Eastern Europe accounts for 18%, Russia for 76%, and Central Asia and Caucasus for 6%. Table 1 presents the characteristics per subregion. The average age was 31 (range 18–75 years old). Almost half (52%) defined their socio-economic status as upper middle or higher, and 44% believe that their income allows them to cover basic needs well or very well, while 49% reported that their total family income was not enough to get by. Two thirds (66%) had university education. Most identified as gay (74%), while the rest selected other options of transgender or non-binary identity. 12% stated that they belonged to a racial or ethnic minority, at least 1% live illegally (do not have a citizenship or residence permit) and about one tenth is immigrants of the first or second generation. Also, 11% indicated that they were living with HIV (90% were taking ARVs). Restrictions imposed due to COVID-19 affected 69% of respondents. In terms of differences between subregions, there are more young adults from Eastern European countries compared to Russia and the Caucasus and Central Asia (31% vs. 26%); in the Caucasus and Central Asia compared to Eastern Europe and Russia, there are more bisexual men (32% vs. 21 and 18%, respectively), people from ethnic minorities (24% vs. 10 and 12%, respectively), and immigrants (18% vs. 12 and 10%, respectively), as well as those without a university degree (60% vs. 55 and 52%, respectively). GBTs from the Russian Federation and Central Asia experienced more restrictions due to COVID-19 than GBTs from Eastern Europe (73 and 83% vs. 69%, respectively). Table 1 Socio-demographic characteristics of the sample, % (CCA — Caucasus and Central Asia, EE — Eastern Europe, RF — Russian Federation) Variable Whole sample, N = 5,037 EE, N = 888 RF, N = 3,847 CCA, N = 302 Age, years 18–24 (young adults) 27 31 26 29 25–44 (adults) 64 58 66 64 45+ (senior adults) 9 11 9 7 Statistics for differences between subregions X 2 (4) = 20.27, p < 0.001, Cramèr’s V = 0.045 Gender identity Cisgender men 96 97 96 94 Trans or non-binary 4 3 4 6 Statistics for differences between subregions X 2 (2) = 5.576, p = 0.060, Cramèr’s V = 0.034 Sexual orientation Gay 74 74 75 59 Bisexual 19 21 18 32 Queer, pansexual, or other 7 5 7 8 Statistics for differences between subregions X 2 (4) = 44.35, p < 0.001, Cramèr’s V = 0.066 Education Less than 6 years 8 8 7 9 Between 6 and 12 years 13 10 13 16 Trade school or vocational training 13 15 12 15 Some university but no degree 19 21 19 21 University degree or more 47 45 48 39 Refuse to answer < 1 < 1 < 1 1 Statistics for differences between subregions X 2 (10) = 25.33, p = 0.005, Cramèr’s V = 0.050 Citizenship or residence permit in country, where respondent lives Yes 86 87 86 83 No 1 1 1 2 Don’t know/Refuse to answer 13 12 13 16 Statistics for differences between subregions X 2 (4) = 7.976, p = 0.092, Cramèr’s V = 0.028 Immigrant Status Parents are native 83 80 85 74 First-generation 4 5 2 9 Immigrant 7 7 8 9 Unsure/Refuse to answer 6 8 5 8 Statistics for differences between subregions X 2 (6) = 56.78, p < 0.001, Cramèr’s V = 0.075 Racial/ethnic minority Yes 12 10 12 24 No 75 76 76 54 Don’t know/Refuse to answer 13 14 12 22 Statistics for differences between subregions X 2 (4) = 79.22, p < 0.001, Cramèr’s V = 0.089 Socioeconomic status Lower 7 7 6 7 Lower middle 41 39 42 35 Upper middle or upper 52 54 51 57 Refuse to answer < 1 < 1 < 1 1 Statistics for differences between subregions X 2 (6) = 10.22, p = 0.116, Cramèr’s V = 0.032 How well can you cover your basic needs (e.g., food, clothing, housing, transport, education, health care) with your current income? Fairly or very well 44 46 44 42 Not at all to somewhat 49 48 49 50 Refuse to answer 6 6 6 8 Statistics for differences between subregions X 2 (4) = 3.627, p = 0.459, Cramèr’s V = 0.019 If we take the overall monthly income of your family, how easy is it for your family to get by? Easily 39 39 39 38 Don’t know, can’t or don’t want to answer 13 12 12 17 With difficulty 49 49 49 45 Statistics for differences between subregions X 2 (4) = 5.629, p = 0.229, Cramèr’s V = 0.024 Government restricted the movement I am completely restricted or quarantined, and I cannot leave my house or quarantine location 7 6 7 18 I am somewhat restricted or advised to leave my house only for essentials 62 43 66 66 There are no restrictions on my movement 31 51 27 15 Refuse to answer < 1 0 0 2 Statistics for differences between subregions X 2 (6) = 306.8, p < 0.001, Cramèr’s V = 0.175 HIV status HIV negative 72 72 73 70 HIV positive 11 9 12 9 Don’t know/Refuse to answer 16 19 15 21 Statistics for differences between subregions X 2 (4) = 15.80, p = 0.003, Cramèr’s V = 0.039 From 1 to 12% were members of especially vulnerable populations, as in addition to the LGBT stigma they had at least one other vulnerability: older adults, trans and non-binary persons, racial/ethnic minorities, immigrants, people with lower socioeconomic status or low level of education, without citizenship or residence permit, HIV+. That is why, we will focus on comparing the effect of anti-epidemic measures on the economic well-being and health of people from these subgroups with the impact on others. Economic impact COVID-19 crisis had a significant impact on the economic well-being of GBT in the EECA region (Table 2 ). Thus, 21% lost their jobs due to the COVID-19 crisis; 61% partly lost their income; 24% had to limit food intake. In the Caucasus and Central Asia compared to Eastern Europe and the Russian Federation, a greater percentage of GBTs lost two-thirds of their income (27% vs. 19 and 21%, respectively) and had to reduce meal size (24% vs. 19 and 19%, respectively). Table 2 Implications of the COVID-19 crisis in terms of changes in the personal economic status, % (CCA — Caucasus and Central Asia, EE — Eastern Europe, RF — Russian Federation) Variable Whole sample, N = 5,037 EE, N = 888 RF, N = 3,847 CCA, N = 302 Lost job due to COVID-19 Yes 21 20 22 21 No 30 29 30 24 Refuse to answer or Not applicable (I don’t have a job, I already lost it, I’m retired, I’m a student etc.) 49 51 48 55 Statistics for differences between subregions X 2 (4) = 8.476, p = 0.076, Cramèr’s V = 0.029 Anticipated income reduction due to COVID-19 0% 29 29 29 30 1–29% 21 24 21 13 30–59% 19 18 19 20 60–100% 21 19 21 27 Refuse to answer 9 9 9 10 Statistics for differences between subregions X 2 (8) = 20.78, p = 0.008, Cramèr’s V = 0.045 Cutting meals or reducing meal size due to COVID-19 Yes 19 18 19 24 No 67 67 68 61 Don’t know/Refuse to answer 14 15 13 15 Statistics for differences between subregions X 2 (6) = 12.80, p = 0.046, Cramèr’s V = 0.036 As shown in Table 3 , changes in the economic status were mostly associated with respondents’ education: the highest share of those who lost their jobs were among people without university degree; socioeconomic status before the crisis: four third of respondents with low socioeconomic status lost their job due to COVID-19, and two thirds reported cutting meal; and movement restrictions: 49% of those whose movement was completely restricted lost their jobs, and 30% had to cut their meal. Access to food was also associated with age, gender identity, sexual orientation, as well as belonging to ethnic/racial minority. Table 3 Linkage of changes in the economic status due to COVID-19 crisis with the key sociodemographic indicators, % (missings excluded) Lost job Anticipated income reduction from 60 to 100% Cutting meals or reducing meal size Age, years 18–24 44 (N = 530) 12 (N = 1,352) 25 (N = 1,100) 25–44 42 (N = 1,786) 8 (N = 3,228) 22 (N = 2,859) 45+ 40 (N = 253) 5 (N = 457) 18 (N = 412) Statistics for differences between subgroups X 2 (2) = 1.316, p = 0.518, Cramèr’s V = 0.023 X 2 (2) = 33.67, p < 0.001, Cramèr’s V = 0.082 X 2 (2) = 6.930, p = 0.031, Cramèr’s V = 0.040 Gender identity Cis 41 (N = 2,400) 8 (N = 4,687) 21 (N = 4,091) Trans or non-binary 56 (N = 89) 14 (N = 181) 41 (N = 148) Statistics for differences between subgroups X 2 (1) = 7.395, p = 0.007, Cramèr’s V = 0.057 X 2 (1) = 6.974, p = 0.008, Cramèr’s V = 0.040 X 2 (1) = 30.07, p < 0.001, Cramèr’s V = 0.086 Sexual orientation Gay 42 (N = 1,906) 8 (N = 3,730) 22 (N = 3,279) Bisexual 40 (N = 513) 11 (N = 978) 24 (N = 817) Queer, pansexual, or other 48 (N = 150) 13 (N = 329) 30 (N = 275) Statistics for differences between subgroups X 2 (2) = 3.110, p = 0.211, Cramèr’s V = 0.035 X 2 (2) = 16.20, p = 0.003, Cramèr’s V = 0.057 X 2 (2) = 10.58, p = 0.005, Cramèr’s V = 0.049 Belonging to a racial/ethnic minority Yes 53 (N = 325) 8 (N = 604) 32 (N = 526) No 39 (N = 1,961) 8 (N = 3,774) 19 (N = 3,331) Don’t know/Refuse to answer 54 (N = 283) 15 (N = 659) 34 (N = 514) Statistics for differences between subgroups X 2 (2) = 43.66, p < 0.001, Cramèr’s V = 0.130 X 2 (2) = 30.93, p < 0.001, Cramèr’s V = 0.078 X 2 (2) = 86.26, p < 0.001, Cramèr’s V = 0.140 Education Less than 6 years 52 (N = 186) 23 (N = 332) 32 (N = 316) Between 6 and 12 years 41 (N = 296) 25 (N = 577) 28 (N = 540) Trade school or vocational training 50 (N = 321) 30 (N = 574) 35 (N = 549) Some university but no degree 53 (N = 446) 29 (N = 888) 25 (N = 847) University degree or more 36 (N = 1,315) 20 (N = 2,206) 16 (N = 2,107) Statistics for differences between subgroups X 2 (4) = 59.54, p < 0.001, Cramèr’s V = 0.152 X 2 (4) = 45.82, p < 0.001, Cramèr’s V = 0.100 X 2 (4) = 133.4, p < 0.001, Cramèr’s V = 0.175 Immigrant status Parents are native 41 (N = 2,148) 8 (N = 4,189) 21 (N = 3,671) First generation 48 (N = 88) 9 (N = 180) 32 (N = 161) Immigrant 51 (N = 181) 12 (N = 377) 30 (N = 313) Statistics for differences between subgroups X 2 (2) = 9.462, p = 0.009, Cramèr’s V = 0.063 X 2 (2) = 5.529, p = 0.063, Cramèr’s V = 0.034 X 2 (2) = 23.62, p < 0.001, Cramèr’s V = 0.075 Socioeconomic status Lower 72 (N = 147) 9 (N = 332) 63 (N = 286) Lower middle 55 (N = 989) 8 (N = 2,074) 28 (N = 1,792) Upper middle or Upper 30 (N = 1,427) 10 (N = 2,619) 13 (N = 2,283) Statistics for differences between subgroups X 2 (2) = 239.1, p < 0.001, Cramèr’s V = 0.305 X 2 (2) = 2.285, p = 0.319, Cramèr’s V = 0.021 X 2 (2) = 430.4, p < 0.001, Cramèr’s V = 0.314 HIV status HIV negative 41 (N = 1,883) 9 (N = 3,649) 21 (N = 3,176) HIV positive 46 (N = 300) 7 (N = 563) 25 (N = 502) Don’t know/Refuse to answer 44 (N = 386) 11 (N = 825) 25 (N = 693) Statistics for differences between subgroups X 2 (2) = 3.085, p = 0.214, Cramèr’s V = 0.035 X 2 (2) = 7.876, p = 0.019, Cramèr’s V = 0.040 X 2 (2) = 6.712, p = 0.034, Cramèr’s V = 0,039 Government restricted the movement I am completely restricted or quarantined, and I cannot leave my house or quarantine location 49 (N = 113) 14 (N = 237) 30 (N = 188) I am somewhat restricted or advised to leave my house only for essentials 43 (N = 1,985) 9 (N = 3,910) 22 (N = 3,417) There are no restrictions on my movement 36 (N = 466) 9 (N = 883) 23 (N = 761) Statistics for differences between subgroups X 2 (2) = 9.125, p = 0.010, Cramèr’s V = 0.060 X 2 (2) = 12.31, p = 0.006, Cramèr’s V = 0.049 X 2 (2) = 6.263, p = 0.043, Cramèr’s V = 0.038 Impact on mental well-being As for the mental health situation, 33% reported that they felt depressed most of the time over the last two weeks, 35% had a feeling of anxiety, 30% reported little interest and 24% could not control worrying. These four items form the PHQ-4 mental health scale [ 40 ] , with the higher score indicating more frequent manifestation of symptoms. The mean score 4.7 (95% CI: 4.6–4.8) shows that the respondents have mild symptoms of depression and anxiety disorders. Table 4 demonstrates differences in the severity of symptoms among different groups. Since most respondents were from Russia (76%), it was among them that the main inequalities in the severity of symptoms emerged. Thus, during the first wave of COVID-19, people from Caucasus and Central Asia compared to other subregions’ countries, young GBT people were more affected compared to people 25+, transgender people, those who identify themselves as other than gay or bisexual, immigrants or their children compared to native-born residents, and GBT people from racial or ethnic minorities, GBTs of low social status and with insufficient income, as well as those who lost their jobs during the epidemic, lost more than two third of their income, or were forced to limit their diet. Restrictions affected the severity of depressive symptoms only in Eastern Europe. The severity of depression and anxiety only in the case of transgender people from Russia, people with a very low social status who lost their jobs and two third of their income and were forced to limit food, was within the boundaries of moderate disorders, while for everyone else it did not go beyond mild range. Table 4 Average PHQ-4 scores and 95% CI in different sub-groups (missings excluded, CCA — Caucasus and Central Asia, EE — Eastern Europe, RF — Russian Federation). Scores are rated as normal (0–2), mild (3–5), moderate (6–8), and severe (9–12) depression and anxiety Variable EE RF CCA Age, years 18–24 5.4 [4.9–5.9] 5.5 [5.3–5.7] 5.7 [4.8–6.5] 25–44 4.7 [4.3–5.0] 4.5 [4.4–4.6] 5.3 [4.7–5.9] 45+ 3.8 [3.1–4.6] 4.0 [3.6–4.4] 4.0 [1.8–6.2] Gender identity Cisgender men 4.7 [4.5–5.0] 4.6 [4.5–4.7] 5.4 [4.9–5.9] Trans or non-binary 5.3 [3.5–7.1] 6.0 [5.3–6.7] 5.5 [3.3–7.7] Sexual orientation Gay 4.9 [4.6–5.2] 4.7 [4.6–4.8] 5.5 [4.9–6.1] Bisexual 4.3 [3.7–4.8] 4.1 [3.9–4.4] 4.9 [4.0–5.8] Queer, pansexual, or other 5.5 [4.3–6.7] 5.3 [4.8–5.8] 6.2 [4.5–7.9] Education Less than 6 years 5.7 [4.6–6.7] 5.2 [4.7–5.7] 5.8 [4.1–7.5] Between 6 and 12 years 5.1 [4.3–6.0] 4.8 [4.4–5.1] 5.8 [4.4–7.3] Trade school or vocational training 5.5 [4.8–6.1] 5.0 [4.6–5.3] 4.9 [3.9–6.0] Some university but no degree 4.5 [4.0–5.0] 5.2 [4.9–5.5] 5.7 [4.7–6.8] University degree or more 4.5 [4.1–4.9] 4.3 [4.1–4.5] 5.0 [4.2–5.8] Citizenship or residence permit in country, where respondent lives Yes 4.8 [4.5–5.1] 4.6 [4.5–4.8] 5.4 [4.9–5.9] No 5.7 [0.3–11] 5.4 [3.5–7.2] 3.4 [0–7.7] Immigrant Status Parents are native 4.7 [4.5–5.0] 4.6 [4.4–4.7] 5.1 [4.6–5.7] First-generation 4.4 [3.3–5.6] 5.5 [4.7–6.3] 6.3 [4.6–8.1] Immigrant 5.0 [3.9–6.1] 5.3 [4.7–5.8] 5.5 [3.5–7.4] Racial/ethnic minority Yes 4.9 [4.0–5.7] 5.5 [5.1–5.8] 5.7 [4.7–6.7] No 4.7 [4.4–4.9] 4.5 [4.4–4.6] 5.3 [4.6–5.9] Socioeconomic status Lower 6.7 [5.8–7.6] 7.0 [6.5–7.5] 7.4 [4.9–9.9] Lower middle 4.9 [4.5–5.3] 5.2 [5.0–5.4] 5.8 [5.1–6.6] Upper middle or upper 4.4 [4.1–4.7] 3.9 [3.8–4.1] 4.8 [4.2–5.4] How well can you cover your basic needs (e.g., food, clothing, housing, transport, education, health care) with your current income? Fairly or very well 4.1 [3.8–4.5] 3.6 [3.4–3.7] 4.1 [3.5–4.7] Not at all to somewhat 5.5 [5.1–5.8] 5.6 [5.5–5.8] 6.4 [5.7–7.1] If we take the overall monthly income of your family, how easy is it for your family to get by? Easily 4.0 [3.7–4.4] 3.5 [3.4–3.7] 4.1 [3.4–4.7] With difficulty 5.4 [5.0–5.7] 5.6 [5.4–5.8] 6.4 [5.7–7.1] Government restricted the movement I am completely restricted or quarantined, and I cannot leave my house or quarantine location 6.4 [4.6–8.2] 5.4 [4.7–6.1] 4.2 [2.8–5.6] I am somewhat restricted or advised to leave my house only for essentials 4.9 [4.7–5.2] 4.7 [4.6–4.8] 5.6 [5.1–6.2] There are no restrictions on my movement 4.0 [3.5–4.5] 4.4 [4.1–4.7] 4.6 [3.3–5.9] HIV status HIV negative 4.9 [4.6–5.2] 4.6 [4.5–4.7] 5.3 [4.7–5.9] HIV positive 4.2 [3.5–4.8] 4.5 [4.1–4.9] 5.3 [3.3–7.2] Lost job Yes 6.2 [5.6–6.7] 6.0 [5.7–6.2] 7.2 [6.1–8.2] No 3.8 [3.4–4.2] 3.4 [3.2–3.6] 4.3 [3.3–5.2] Anticipated income reduction from 60 to 100% Yes 5.8 [5.2–6.4] 6.1 [5.9–6.3] 6.5 [5.6–7.5] No 4.5 [4.2–4.8] 4.2 [4.1–4.4] 4.9 [4.3–5.4] Cutting meals or reducing meal size Yes 6.9 [6.4–7.5] 7.0 [6.8–7.3] 7.5 [6.6–8.3] No 4.2 [3.9–4.5] 4.0 [3.8–4.2] 4.4 [3.8–4.9] Discussion Our purpose was to demonstrate the effect of the COVID-19 crisis on the economic well-being and mental health of GBT in EECA. We assumed that this impact would be different for groups with different social vulnerabilities. Survey participants were affected by the restrictions introduced due to COVID-19. COVID-19 related measures resulted in worsening economic situation, which led to a reduction in income (in 40% of cases by more than a third). A fifth part stated that it restricted their opportunities to have meals, which aligns with the share of economically vulnerable respondents. The most affected were GBTs from the Caucasus and Central Asia. We showed strong linkages between the belonging to especially vulnerable subgroups with the negative implications of COVID-19 related measures. Thus, young adults and people who did not identify as gay often saw their income decrease by more than two-thirds and were forced to reduce meal size; trans and nonbinary people, racial or ethnic minorities, people with a primary education, immigrants, and those who described their social status as low were more likely to lose jobs, income and access to food. The relationship between HIV status and economic losses was more complex: HIV-positive, HIV-negative, and those who did not know their status lost their jobs equally often; incomes decreased somewhat more often among people who did not know their status; and food was forced to be restricted more often by HIV-positive people or people without HIV status. In terms of the severity of depression and anxiety symptoms, it should be noted that the impact of the epidemic was rather weak, since the PHQ-4 scale values did not go beyond mild disorders. The severity of mental health disorders varied both in subregions (the most affected were GBTs from the Caucasus and Central Asia) and in groups differing in social vulnerability. Economic vulnerability seemed to be associated with mental health problems in all subregions, but gender identity and sexual orientation were associated with the severity of symptoms only among respondents from Russia. Thus, it seems reasonable to assume that economic losses could have been the main reason for the deterioration of mental health during the first wave of the epidemic. Data from other countries indicate that the COVID-19 epidemic increased the prevalence of suicidal ideations and attempts among men [ 41 ] and aggravated mental health situation in the general population [ 31 ] . As opposed to other regions, in EECA, depression and anxiety levels among GBT during the COVID-19 crisis were not high. These paradoxical results showing that despite the restrictions and economic losses, depression and anxiety levels did not exceed the bounds of mild deviations from the norm, are aligned with another face-to-face study among MSM conducted in Ukraine in 2021 [ 42 ] , which demonstrated that during the spread of the Omicron variant of COVID-19, depression and anxiety levels were within the normal range. The linkage between younger age and higher depression and anxiety levels may be associated with higher average indicators of internalized homonegativity among younger subgroups of gay and bisexual men (as shown for the Russian Federation in [ 37 ] ). The nature of linkages between socio-economic vulnerabilities of GBT during the first wave of the COVID-19 (with the factors mostly non-specific for LGBT people associated with the changes in economic status and moderate symptoms of mental health disorders, see Table 3 and Table 4 ) may indicate that belonging to gay and bisexual (and partly trans) community can be a factor of social vulnerability, but, unlike in other regions of the world, it is not a determinant in this regard. Unfortunately, we do not have data that would allow us to compare other groups described in the publications, such as hetero- and non-heterosexual people, men, and women, etc. One possible explanation could be a higher pre-crisis level of chronic stress due to internalized homo- or transphobia [ 37 ] . In this regard higher LGBT resilience could be viewed as a tolerance to stress. Considering further research, we would propose that LGBT, who have more access to social support, could demonstrate not only more resilience in crises, but also less impact on their mental health after a crisis. Limitations of the data presented are primarily associated with the pilot nature of the study. Potential inaccuracies may occur due to the following factors: (1) the data analysed were obtained in a cross-sectional survey, which cannot provide information on the causal connection between the epidemic and the observed changes. When we talk about the “effect,” in fact we mean the respondents’ subjective perception that the changes observed by them were actually caused by the restrictions at the time of the rapid spread of COVID-19; (2) the survey only covered the Hornet mobile app users, but despite the existence of a global user community, it cannot be representative of the entire community of gay and bisexual men, as people in different countries and groups have uneven access to mobile connection and Internet; (4) when participating in the survey, respondents could choose their preferred language (English, Spanish, Russian, French or Turkish). It was assumed that people from EECA countries know either Russian or English, which limited the participation of people from countries, where the knowledge of these languages is not widespread. Conclusions Data on the effect of the social restrictions imposed in response to the COVID-19 on LGBT people are limited, especially in the region of Eastern Europe and Central Asia. A cross-sectional online survey of a non-random sample of 5,037 Hornet mobile app GBT users, who reside in the EECA countries, was conducted in March–May 2020. It demonstrated that COVID-19 crisis worsened the economic situation of the GBT. However, the data on mental health changes are paradoxical and differ from similar data from other regions of the world. Despite the restrictions on physical freedom and economic losses, the levels of depression and anxiety in EECA did not exceed the bounds of mild deviations from the norm. Social changes caused by the COVID-19 crisis had more severe consequences for the more vulnerable people, such as trans and non-binary people, members of racial or ethnic minorities, people with low educational level or low socioeconomic status, and young people. The results demonstrate the intersectional effects of restrictions on the physical, social, and mental well-being of GBT. The negative implications of the COVID-19 crisis affected the entire population in the EECA region, but more economically vulnerable subgroups have suffered the most. Declarations Author Contributions Statement MK, SS, and EL — analysis and interpretation of the data, and the drafting of the paper; SH, AG, and SB — the conception and design of the survey, revising it critically for intellectual content; MK, SS, SH, AG, SB, and EL — the final approval of the version to be published. All authors agree to be accountable for all aspects of the work. Ethics Statement: The survey procedures were reviewed and approved by the Institutional Review Board of the Johns Hopkins School of Public Health (USA) Disclosure statement: the authors report there are no competing interests to declare Data availability statement: the data associated with a paper cannot be made open without the permission of HORNET LTD and LGBT Foundation Funding details: this work was not supported by funding References Onyeaka H, Anumudu CK, Al-Sharify ZT, Egele-Godswill E, Mbaegbu P (2021) COVID-19 pandemic: A review of the global lockdown and its far-reaching effects. Sci Prog 104(2):003685042110198. https://doi.org/10.1177/00368504211019854 Zhang SX, Chen J (2021) Scientific evidence on mental health in key regions under the COVID-19 pandemic – meta-analytical evidence from Africa, Asia, China, Eastern Europe, Latin America, South Asia, Southeast Asia, and Spain. 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T., Huang, P., Cerasuolo, D., Bishop, A., … Howell,S. (2021). Economic, Mental Health, HIV Prevention and HIV Treatment Impacts of COVID-19 and the COVID-19 Response on a Global Sample of Cisgender Gay Men and Other Men Who Have Sex with Men. AIDS and Behavior, 25(2), 311–321. https://doi.org/10.1007/s10461-020-02969-0 R Core Team (2020) R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/ Kroenke K, Spitzer RL, Williams JBW, Lowe B (2009) An Ultra-Brief Screening Scale for Anxiety and Depression: The PHQ-4. Psychosomatics 50(6):613–621. https://doi.org/10.1176/appi.psy.50.6.613 Seidler ZE, Wilson MJ, Oliffe JL, Fisher K, O’Connor R, Pirkis J, Rice SM (2023) Suicidal ideation in men during COVID-19: an examination of protective factors. BMC Psychiatry 23(1):46. https://doi.org/10.1186/s12888-023-04539-9 Kasianchuk M, Titar I, Salnikov S, Ohorodnik O, Kulchynska R, Sazonova Y, Andrianova I, Sheiko O, Sichkar S, Trofymenko O (2023) Report on biological and behavioral survey among men who have sex with men in Ukraine (2021) Footnotes Countries of the EECA region: Armenia, Azerbaijan, Belarus, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Moldova, Russian Federation, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8996854","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":598592888,"identity":"52d9ed76-f7d4-4fad-8714-82a3f4d0cc4b","order_by":0,"name":"Maksym Kasianczuk","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEElEQVRIiWNgGAWjYJCCAwwMCQwMzBCOAT+ITCggRYtkA0iLAUGLEuAsA4MDYAq3Wt32M4aHbjCkycu3Mz978OPPYWPj86sTPzwwYJDnFzuAVYvZmbSEwzkMOYYbDrOZG/bwHDYzu/F2swTQYYYzZydg13Ig+QBQSwXjBmYGM2kGicM2ZjfObgBpSTC4jUPL+YcNIC3285vZv0kzGBy2MZ5xdvMPvFpugG3JSWw4zAO0JeGwmQF/7zb8ttx4BvSLQVryhsM8ZZI9B9KNJW7wbrNIMJDA7ZfzOcafcyqSbef3H98m8eOPtWF//9nNN39U2MjzS2PXAgEosSABVimBRzkG4D9AiupRMApGwSgYAQAAydthZP+U4RwAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0003-0701-3595","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Maksym","middleName":"","lastName":"Kasianczuk","suffix":""},{"id":598592889,"identity":"873b065d-5b31-4efc-9cf0-270d38853b58","order_by":1,"name":"Serhii Salnikov","email":"","orcid":"https://orcid.org/0000-0002-9547-9709","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Serhii","middleName":"","lastName":"Salnikov","suffix":""},{"id":598592890,"identity":"adbf613c-23f7-4db9-85d5-a433095a1a3a","order_by":2,"name":"Sean Howell","email":"","orcid":"https://orcid.org/0000-0001-9703-8950","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Sean","middleName":"","lastName":"Howell","suffix":""},{"id":598592891,"identity":"fa999672-829f-4fdf-bc07-4132c894cb86","order_by":3,"name":"Alex Garner","email":"","orcid":"https://orcid.org/0000-0003-2889-4600","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Alex","middleName":"","lastName":"Garner","suffix":""},{"id":598592892,"identity":"13513d31-b883-49b7-94cf-cb2a105507f6","order_by":4,"name":"Stefan Baral","email":"","orcid":"https://orcid.org/0000-0002-5482-2419","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Stefan","middleName":"","lastName":"Baral","suffix":""},{"id":598592893,"identity":"287cbd2e-576b-4353-9232-624d31ae079c","order_by":5,"name":"Erik Lamontagne","email":"","orcid":"https://orcid.org/0000-0002-6394-0070","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Erik","middleName":"","lastName":"Lamontagne","suffix":""}],"badges":[],"createdAt":"2026-02-28 16:33:10","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8996854/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8996854/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103812069,"identity":"95536cd3-38e0-4679-a2c8-d728ae180805","added_by":"auto","created_at":"2026-03-03 08:27:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":79354,"visible":true,"origin":"","legend":"\u003cp\u003eParticipating countries, per subregion: Central Asia and Caucasus in blue, Eastern Europe in red, Russian Federation in brown\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8996854/v1/20fafafb0a126dcc06152cfc.png"},{"id":103812152,"identity":"368f978a-0e38-4e65-bd77-92606c7604b9","added_by":"auto","created_at":"2026-03-03 08:28:13","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":17273,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of survey respondents by subregions and SOGI, X\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e(4) = 44.35, p \u0026lt; 0.001, Cramèr’s V = 0.066.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCCA — Caucasus and Central Asia, EE — Eastern Europe, RF — Russian Federation\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8996854/v1/db21e782ed07660ac411bd24.jpg"},{"id":103812165,"identity":"3773574f-8961-4a94-9239-d00e72a88e93","added_by":"auto","created_at":"2026-03-03 08:28:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1938298,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8996854/v1/0b62ec32-136d-4e77-96b1-3529b8c34bac.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eParadoxical Linkage between Mental Health and Social Implications of COVID-19 crisis in Gay, Bisexual Men and transgenders in Eastern Europe and Central Asia: Results of Survey among the Hornet Mobile App Users\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn 2020, COVID-19 became a huge challenge, leading to global restrictions on personal freedoms \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Since May 2020, COVID-19 started having impact on Eastern Europe and Central Asia (EECA)\u003csup\u003e1\u003c/sup\u003e. Countries of the region declared a state of emergency, shutting down schools, restaurants, and shops, suspending operation of the public transport, etc.\u003c/p\u003e \u003cp\u003eAlthough there was a range of publications on the consequences of the COVID-19 crisis in the region \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e, its impact on the well-being of vulnerable populations, such as gay and bisexual men, has been poorly studied \u003csup\u003e[\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eExisting evidence shows lesbian, gay, bisexual, and transgender (LGBT) people are most vulnerable and disproportionately impacted by crises like COVID-19 or military conflicts \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Data about LGBT people in the EECA region remains limited \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMental health challenges.\u003c/b\u003e A comparison of cisgender heterosexual people with non-heterosexual and transgender individuals in the United States \u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e demonstrated that during the COVID-19 LGBT people faced more mental health challenges, than cisgender heterosexual people. Compared to gays and lesbians, people with other non-heterosexual orientations had higher levels of depression, anxiety, and chronic stress; bisexual women and lesbians experienced more mental health issues compared to bisexual and gay men \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. LGBT showed high levels of stress \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Data from various countries show the same results \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOther factors also include homo- or transphobic attitudes of health workers in the context of COVID-19 crisis \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe COVID-19 aggravated existing issues, such as the psychological climate in couples \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e, uncertainty about the future, discontinuation of HIV treatment \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e and access to HIV services \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEconomic challenges during COVID-19.\u003c/b\u003e The situation of LGBT people worsened \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. The unequal effect of the COVID-19 related restrictions has been documented in the general population as well \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Vulnerability to COVID-19 was higher in the Brazilian population of bisexual and heterosexual people who have same-sex contacts compared to homosexual people, in cisgender men compared to cisgender women and in people over 50 years of age compared to younger people aged 18\u0026ndash;29 \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Analysis of large-scale data from the United States showed that during the COVID-19 epidemic transgender people were much more economically vulnerable than lesbian, gay, bisexual, and heterosexual people \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eChanges in sexual life during COVID-19.\u003c/b\u003e Some studies showed that number of partners increased during the COVID-19 \u003csup\u003e[\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e, which could be seen as a strategy to cope with the lockdown-related stress \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e; while others, on the contrary, recorded a decrease in this indicator \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIntersectional impact.\u003c/b\u003e Differences in the impact on mental health and economic well-being suggest intersectional and multidimensional linkages between the social and health-related implications of the pandemic and the LGBT agenda \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Thus, the examples of Great Britain and Brazil showed that marginalization of the LGBT communities led to their specific survival strategies \u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e, increased the risks of substance abuse or condomless sexual practices, while such maladaptive behaviours increased the chances of health deterioration among LGBT people compared to heterosexual people \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe COVID-19 had a more devastating impact on the LGBT youth than on the older people \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e due to the aggravation of internalized homophobia and dysfunctional family relations.\u003c/p\u003e \u003cp\u003eThe impact on HIV-positive LGBT people was also intersectional, as they faced higher levels of unemployment, income inequality, and intimate partner violence even before the epidemic. Social restrictions, such as being isolated and having less access to health care, had a negative effect on the life of people living with HIV \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEven though COVID-19 related restrictions were harmful in many ways, they also contributed to some positive changes for the LGBT communities, such as internationalization of local movements, greater cohesion, and bigger sense of belonging to the community, at least in Japan \u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e and Nigeria \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Some participants of a study in Canada \u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e reported that lockdown restrictions reduced the pressure of traditional gender expectations due to reduction of face-to-face interactions.\u003c/p\u003e \u003cp\u003eThus, the literature on the social implications of COVID-19 for the LGBT community is essentially limited to the Western World and South America, with the region of EECA almost not covered.\u003c/p\u003e \u003cp\u003eThe EECA region is characterized by economic instability, military and political conflicts, and inequality in access to social services for men who have sex with men (MSM) \u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e, with high levels of external \u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e and internal homophobia \u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur research aims to fill in the gaps in knowledge on the effect of COVID-19 on gay and bisexual men as well as transgender people (GBT) in the EECA region.\u003c/p\u003e \u003cp\u003eThe main hypothesis is the unequal effect of government-enacted restrictions on the personal freedoms due to COVID-19 on the economic and mental well-being of more and less vulnerable groups of GBT in the EECA region.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eA cross-sectional survey conducted among users of the Hornet mobile app from March to May 2020. Participants were asked to complete an online questionnaire about health and quality of life during the COVID-19 epidemic. Participants must be at least 18 years old, provide their informed consent, and were identified as male. The survey procedures were reviewed and approved by the Institutional Review Board of the Johns Hopkins School of Public Health (USA). More details on the methodology of the survey can be found elsewhere \u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e. In the present study, we focus on the 5,037 participants from fourteen countries from the EECA region. The countries are assembled into three groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) corresponding to geopolitical and cultural characteristics that emerged following the dissolution of the Soviet Union in 1991.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eParticipants were asked about the effect of the COVID-19 crisis on their economic status, mental health, and quality of life.\u003c/p\u003e \u003cp\u003eWe performed an analysis of the bivariate distributions of sociodemographic factors, such as HIV status, being a member of a racial/ethnic minority, and immigrant status. We examined differences among the groups using Pearson\u0026rsquo;s Chi square test (χ\u003csup\u003e2\u003c/sup\u003e) and Cram\u0026egrave;r\u0026rsquo;s V test with a significance level of α\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for categorical variables and comparison of the mean values for the PHQ-4 depression and anxiety scale. The calculations were performed in R \u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003eSample characteristics\u003c/h2\u003e\n \u003cp\u003eA total of 5,037 GBT participated to the survey in the EECA countries. The largest number were coming from the Russian Federation (76% or 3,847), and Ukraine (12% or 604). Participants per sexual and gender identity and per subregions are presented in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. Eastern Europe accounts for 18%, Russia for 76%, and Central Asia and Caucasus for 6%.\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e presents the characteristics per subregion. The average age was 31 (range 18\u0026ndash;75 years old). Almost half (52%) defined their socio-economic status as upper middle or higher, and 44% believe that their income allows them to cover basic needs well or very well, while 49% reported that their total family income was not enough to get by. Two thirds (66%) had university education. Most identified as gay (74%), while the rest selected other options of transgender or non-binary identity. 12% stated that they belonged to a racial or ethnic minority, at least 1% live illegally (do not have a citizenship or residence permit) and about one tenth is immigrants of the first or second generation. Also, 11% indicated that they were living with HIV (90% were taking ARVs). Restrictions imposed due to COVID-19 affected 69% of respondents.\u003c/p\u003e\n\u003cp\u003eIn terms of differences between subregions, there are more young adults from Eastern European countries compared to Russia and the Caucasus and Central Asia (31% vs. 26%); in the Caucasus and Central Asia compared to Eastern Europe and Russia, there are more bisexual men (32% vs. 21 and 18%, respectively), people from ethnic minorities (24% vs. 10 and 12%, respectively), and immigrants (18% vs. 12 and 10%, respectively), as well as those without a university degree (60% vs. 55 and 52%, respectively). GBTs from the Russian Federation and Central Asia experienced more restrictions due to COVID-19 than GBTs from Eastern Europe (73 and 83% vs. 69%, respectively).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSocio-demographic characteristics of the sample, % (CCA \u0026mdash; Caucasus and Central Asia, EE \u0026mdash; Eastern Europe, RF \u0026mdash; Russian Federation)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWhole sample, N\u0026nbsp;=\u0026nbsp;5,037\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEE, N\u0026nbsp;=\u0026nbsp;888\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRF, N\u0026nbsp;=\u0026nbsp;3,847\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCCA, N\u0026nbsp;=\u0026nbsp;302\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026ndash;24 (young adults)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026ndash;44 (adults)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45+ (senior adults)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStatistics for differences between subregions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;20.27, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender identity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCisgender men\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTrans or non-binary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStatistics for differences between subregions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;5.576, p\u0026thinsp;=\u0026thinsp;0.060, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eSexual orientation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBisexual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQueer, pansexual, or other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStatistics for differences between subregions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;44.35, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLess than 6 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBetween 6 and 12 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTrade school or vocational training\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSome university but no degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUniversity degree or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRefuse to answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStatistics for differences between subregions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(10)\u0026thinsp;=\u0026thinsp;25.33, p\u0026thinsp;=\u0026thinsp;0.005, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eCitizenship or residence permit in country, where respondent lives\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDon\u0026rsquo;t know/Refuse to answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStatistics for differences between subregions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;7.976, p\u0026thinsp;=\u0026thinsp;0.092, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eImmigrant Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eParents are native\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFirst-generation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eImmigrant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnsure/Refuse to answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStatistics for differences between subregions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(6)\u0026thinsp;=\u0026thinsp;56.78, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eRacial/ethnic minority\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDon\u0026rsquo;t know/Refuse to answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStatistics for differences between subregions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;79.22, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocioeconomic status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLower middle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUpper middle or upper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRefuse to answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStatistics for differences between subregions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(6)\u0026thinsp;=\u0026thinsp;10.22, p\u0026thinsp;=\u0026thinsp;0.116, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eHow well can you cover your basic needs (e.g., food, clothing, housing, transport, education, health care) with your current income?\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFairly or very well\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot at all to somewhat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRefuse to answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStatistics for differences between subregions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;3.627, p\u0026thinsp;=\u0026thinsp;0.459, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eIf we take the overall monthly income of your family, how easy is it for your family to get by?\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEasily\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDon\u0026rsquo;t know, can\u0026rsquo;t or don\u0026rsquo;t want to answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWith difficulty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStatistics for differences between subregions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;5.629, p\u0026thinsp;=\u0026thinsp;0.229, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eGovernment restricted the movement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI am completely restricted or quarantined, and I cannot leave my house or quarantine location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI am somewhat restricted or advised to leave my house only for essentials\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThere are no restrictions on my movement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRefuse to answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStatistics for differences between subregions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(6)\u0026thinsp;=\u0026thinsp;306.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eHIV status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHIV negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHIV positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDon\u0026rsquo;t know/Refuse to answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStatistics for differences between subregions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;15.80, p\u0026thinsp;=\u0026thinsp;0.003, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eFrom 1 to 12% were members of especially vulnerable populations, as in addition to the LGBT stigma they had at least one other vulnerability: older adults, trans and non-binary persons, racial/ethnic minorities, immigrants, people with lower socioeconomic status or low level of education, without citizenship or residence permit, HIV+. That is why, we will focus on comparing the effect of anti-epidemic measures on the economic well-being and health of people from these subgroups with the impact on others.\u003c/p\u003e\n\u003cp\u003eEconomic impact\u003c/p\u003e\n\u003cp\u003eCOVID-19 crisis had a significant impact on the economic well-being of GBT in the EECA region (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Thus, 21% lost their jobs due to the COVID-19 crisis; 61% partly lost their income; 24% had to limit food intake.\u003c/p\u003e\n\u003cp\u003eIn the Caucasus and Central Asia compared to Eastern Europe and the Russian Federation, a greater percentage of GBTs lost two-thirds of their income (27% vs. 19 and 21%, respectively) and had to reduce meal size (24% vs. 19 and 19%, respectively).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eImplications of the COVID-19 crisis in terms of changes in the personal economic status, % (CCA \u0026mdash; Caucasus and Central Asia, EE \u0026mdash; Eastern Europe, RF \u0026mdash; Russian Federation)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWhole sample, N\u0026nbsp;=\u0026nbsp;5,037\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEE, N\u0026nbsp;=\u0026nbsp;888\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRF, N\u0026nbsp;=\u0026nbsp;3,847\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCCA, N\u0026nbsp;=\u0026nbsp;302\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eLost job due to COVID-19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRefuse to answer or Not applicable (I don\u0026rsquo;t have a job, I already lost it, I\u0026rsquo;m retired, I\u0026rsquo;m a student etc.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStatistics for differences between subregions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;8.476, p\u0026thinsp;=\u0026thinsp;0.076, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnticipated income reduction due to COVID-19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;29%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u0026ndash;59%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026ndash;100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRefuse to answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStatistics for differences between subregions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(8)\u0026thinsp;=\u0026thinsp;20.78, p\u0026thinsp;=\u0026thinsp;0.008, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eCutting meals or reducing meal size due to COVID-19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDon\u0026rsquo;t know/Refuse to answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStatistics for differences between subregions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(6)\u0026thinsp;=\u0026thinsp;12.80, p\u0026thinsp;=\u0026thinsp;0.046, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, changes in the economic status were mostly associated with respondents\u0026rsquo; education: the highest share of those who lost their jobs were among people without university degree; socioeconomic status before the crisis: four third of respondents with low socioeconomic status lost their job due to COVID-19, and two thirds reported cutting meal; and movement restrictions: 49% of those whose movement was completely restricted lost their jobs, and 30% had to cut their meal. Access to food was also associated with age, gender identity, sexual orientation, as well as belonging to ethnic/racial minority.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLinkage of changes in the economic status due to COVID-19 crisis with the key sociodemographic indicators, % (missings excluded)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLost job\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAnticipated income reduction from 60 to 100%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCutting meals or reducing meal size\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026ndash;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (N\u0026thinsp;=\u0026thinsp;530)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (N\u0026thinsp;=\u0026thinsp;1,352)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (N\u0026thinsp;=\u0026thinsp;1,100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026ndash;44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42 (N\u0026thinsp;=\u0026thinsp;1,786)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (N\u0026thinsp;=\u0026thinsp;3,228)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (N\u0026thinsp;=\u0026thinsp;2,859)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (N\u0026thinsp;=\u0026thinsp;253)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (N\u0026thinsp;=\u0026thinsp;457)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (N\u0026thinsp;=\u0026thinsp;412)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStatistics for differences between subgroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;1.316, p\u0026thinsp;=\u0026thinsp;0.518, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;33.67, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;6.930, p\u0026thinsp;=\u0026thinsp;0.031, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender identity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (N\u0026thinsp;=\u0026thinsp;2,400)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (N\u0026thinsp;=\u0026thinsp;4,687)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (N\u0026thinsp;=\u0026thinsp;4,091)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTrans or non-binary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56 (N\u0026thinsp;=\u0026thinsp;89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (N\u0026nbsp;= 181)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (N\u0026thinsp;=\u0026thinsp;148)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStatistics for differences between subgroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(1)\u0026thinsp;=\u0026thinsp;7.395, p\u0026thinsp;=\u0026thinsp;0.007, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(1)\u0026thinsp;=\u0026thinsp;6.974, p\u0026thinsp;=\u0026thinsp;0.008, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(1)\u0026thinsp;=\u0026thinsp;30.07, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eSexual orientation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42 (N\u0026thinsp;=\u0026thinsp;1,906)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (N\u0026thinsp;=\u0026thinsp;3,730)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (N\u0026thinsp;=\u0026thinsp;3,279)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBisexual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (N\u0026thinsp;=\u0026thinsp;513)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (N\u0026thinsp;=\u0026thinsp;978)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (N\u0026thinsp;=\u0026thinsp;817)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQueer, pansexual, or other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 (N\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (N\u0026nbsp;=\u0026nbsp;329)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (N\u0026thinsp;=\u0026thinsp;275)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStatistics for differences between subgroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;3.110, p\u0026thinsp;=\u0026thinsp;0.211, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;16.20, p\u0026thinsp;=\u0026thinsp;0.003, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;10.58, p\u0026thinsp;=\u0026thinsp;0.005, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eBelonging to a racial/ethnic minority\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53 (N\u0026thinsp;=\u0026thinsp;325)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (N\u0026thinsp;=\u0026thinsp;604)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (N\u0026thinsp;=\u0026thinsp;526)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (N\u0026thinsp;=\u0026thinsp;1,961)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (N\u0026thinsp;=\u0026thinsp;3,774)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (N\u0026thinsp;=\u0026thinsp;3,331)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDon\u0026rsquo;t know/Refuse to answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54 (N\u0026thinsp;=\u0026thinsp;283)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (N\u0026thinsp;=\u0026thinsp;659)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (N\u0026thinsp;=\u0026thinsp;514)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStatistics for differences between subgroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;43.66, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;30.93, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;86.26, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLess than 6 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52 (N\u0026thinsp;=\u0026thinsp;186)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (N\u0026thinsp;=\u0026thinsp;332)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (N\u0026thinsp;=\u0026thinsp;316)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBetween 6 and 12 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (N\u0026thinsp;=\u0026thinsp;296)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (N\u0026thinsp;=\u0026thinsp;577)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (N\u0026thinsp;=\u0026thinsp;540)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTrade school or vocational training\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50 (N\u0026thinsp;=\u0026thinsp;321)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (N\u0026thinsp;=\u0026thinsp;574)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (N\u0026thinsp;=\u0026thinsp;549)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSome university but no degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53 (N\u0026thinsp;=\u0026thinsp;446)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (N\u0026thinsp;=\u0026thinsp;888)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (N\u0026thinsp;=\u0026thinsp;847)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUniversity degree or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36 (N\u0026thinsp;=\u0026thinsp;1,315)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (N\u0026thinsp;=\u0026thinsp;2,206)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (N\u0026thinsp;=\u0026thinsp;2,107)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStatistics for differences between subgroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;59.54, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;45.82, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;133.4, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eImmigrant status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eParents are native\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (N\u0026thinsp;=\u0026thinsp;2,148)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (N\u0026nbsp;=\u0026nbsp;4,189)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (N\u0026thinsp;=\u0026thinsp;3,671)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFirst generation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 (N\u0026thinsp;=\u0026thinsp;88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (N\u0026nbsp;= 180)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (N\u0026thinsp;=\u0026thinsp;161)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eImmigrant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51 (N\u0026thinsp;=\u0026thinsp;181)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (N\u0026thinsp;=\u0026thinsp;377)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (N\u0026thinsp;=\u0026thinsp;313)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStatistics for differences between subgroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;9.462, p\u0026thinsp;=\u0026thinsp;0.009, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;5.529, p\u0026thinsp;=\u0026thinsp;0.063, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;23.62, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocioeconomic status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72 (N\u0026thinsp;=\u0026thinsp;147)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (N\u0026thinsp;=\u0026thinsp;332)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63 (N\u0026thinsp;=\u0026thinsp;286)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLower middle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55 (N\u0026thinsp;=\u0026thinsp;989)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (N\u0026nbsp;=\u0026nbsp;2,074)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (N\u0026thinsp;=\u0026thinsp;1,792)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUpper middle or Upper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (N\u0026thinsp;=\u0026thinsp;1,427)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (N\u0026thinsp;=\u0026thinsp;2,619)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (N\u0026thinsp;=\u0026thinsp;2,283)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStatistics for differences between subgroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;239.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;2.285, p\u0026thinsp;=\u0026thinsp;0.319, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;430.4, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.314\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eHIV status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHIV negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (N\u0026thinsp;=\u0026thinsp;1,883)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (N\u0026nbsp;=\u0026nbsp;3,649)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (N\u0026thinsp;=\u0026thinsp;3,176)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHIV positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 (N\u0026thinsp;=\u0026thinsp;300)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (N\u0026nbsp;=\u0026nbsp;563)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (N\u0026thinsp;=\u0026thinsp;502)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDon\u0026rsquo;t know/Refuse to answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (N\u0026thinsp;=\u0026thinsp;386)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (N\u0026thinsp;=\u0026thinsp;825)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (N\u0026thinsp;=\u0026thinsp;693)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStatistics for differences between subgroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;3.085, p\u0026thinsp;=\u0026thinsp;0.214, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;7.876, p\u0026thinsp;=\u0026thinsp;0.019, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;6.712, p\u0026thinsp;=\u0026thinsp;0.034, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0,039\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eGovernment restricted the movement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI am completely restricted or quarantined, and I cannot leave my house or quarantine location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (N\u0026thinsp;=\u0026thinsp;113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (N\u0026nbsp;=\u0026nbsp;237)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (N\u0026thinsp;=\u0026thinsp;188)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI am somewhat restricted or advised to leave my house only for essentials\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (N\u0026thinsp;=\u0026thinsp;1,985)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (N\u0026nbsp;=\u0026nbsp;3,910)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (N\u0026thinsp;=\u0026thinsp;3,417)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThere are no restrictions on my movement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36 (N\u0026thinsp;=\u0026thinsp;466)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (N\u0026thinsp;=\u0026thinsp;883)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (N\u0026thinsp;=\u0026thinsp;761)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStatistics for differences between subgroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;9.125, p\u0026thinsp;=\u0026thinsp;0.010, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;12.31, p\u0026thinsp;=\u0026thinsp;0.006, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;6.263, p\u0026thinsp;=\u0026thinsp;0.043, Cram\u0026egrave;r\u0026rsquo;s V\u0026thinsp;=\u0026thinsp;0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ch3\u003eImpact on mental well-being\u003c/h3\u003e\n\u003cp\u003eAs for the mental health situation, 33% reported that they felt depressed most of the time over the last two weeks, 35% had a feeling of anxiety, 30% reported little interest and 24% could not control worrying. These four items form the PHQ-4 mental health scale \u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e, with the higher score indicating more frequent manifestation of symptoms. The mean score 4.7 (95% CI: 4.6\u0026ndash;4.8) shows that the respondents have mild symptoms of depression and anxiety disorders.\u003c/p\u003e\n\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e demonstrates differences in the severity of symptoms among different groups. Since most respondents were from Russia (76%), it was among them that the main inequalities in the severity of symptoms emerged. Thus, during the first wave of COVID-19, people from Caucasus and Central Asia compared to other subregions\u0026rsquo; countries, young GBT people were more affected compared to people 25+, transgender people, those who identify themselves as other than gay or bisexual, immigrants or their children compared to native-born residents, and GBT people from racial or ethnic minorities, GBTs of low social status and with insufficient income, as well as those who lost their jobs during the epidemic, lost more than two third of their income, or were forced to limit their diet. Restrictions affected the severity of depressive symptoms only in Eastern Europe. The severity of depression and anxiety only in the case of transgender people from Russia, people with a very low social status who lost their jobs and two third of their income and were forced to limit food, was within the boundaries of moderate disorders, while for everyone else it did not go beyond mild range.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAverage PHQ-4 scores and 95% CI in different sub-groups (missings excluded, CCA \u0026mdash; Caucasus and Central Asia, EE \u0026mdash; Eastern Europe, RF \u0026mdash; Russian Federation). Scores are rated as normal (0\u0026ndash;2), mild (3\u0026ndash;5), moderate (6\u0026ndash;8), and severe (9\u0026ndash;12) depression and anxiety\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRF\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCCA\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026ndash;24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.4 [4.9\u0026ndash;5.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5 [5.3\u0026ndash;5.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.7 [4.8\u0026ndash;6.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026ndash;44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.7 [4.3\u0026ndash;5.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.5 [4.4\u0026ndash;4.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.3 [4.7\u0026ndash;5.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.8 [3.1\u0026ndash;4.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0 [3.6\u0026ndash;4.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0 [1.8\u0026ndash;6.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender identity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCisgender men\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.7 [4.5\u0026ndash;5.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.6 [4.5\u0026ndash;4.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.4 [4.9\u0026ndash;5.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTrans or non-binary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.3 [3.5\u0026ndash;7.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.0 [5.3\u0026ndash;6.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5 [3.3\u0026ndash;7.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eSexual orientation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.9 [4.6\u0026ndash;5.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.7 [4.6\u0026ndash;4.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5 [4.9\u0026ndash;6.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBisexual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.3 [3.7\u0026ndash;4.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.1 [3.9\u0026ndash;4.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.9 [4.0\u0026ndash;5.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQueer, pansexual, or other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5 [4.3\u0026ndash;6.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.3 [4.8\u0026ndash;5.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.2 [4.5\u0026ndash;7.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLess than 6 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.7 [4.6\u0026ndash;6.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.2 [4.7\u0026ndash;5.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.8 [4.1\u0026ndash;7.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBetween 6 and 12 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.1 [4.3\u0026ndash;6.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.8 [4.4\u0026ndash;5.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.8 [4.4\u0026ndash;7.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTrade school or vocational training\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5 [4.8\u0026ndash;6.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.0 [4.6\u0026ndash;5.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.9 [3.9\u0026ndash;6.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSome university but no degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.5 [4.0\u0026ndash;5.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.2 [4.9\u0026ndash;5.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.7 [4.7\u0026ndash;6.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUniversity degree or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.5 [4.1\u0026ndash;4.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.3 [4.1\u0026ndash;4.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.0 [4.2\u0026ndash;5.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eCitizenship or residence permit in country, where respondent lives\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.8 [4.5\u0026ndash;5.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.6 [4.5\u0026ndash;4.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.4 [4.9\u0026ndash;5.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.7 [0.3\u0026ndash;11]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.4 [3.5\u0026ndash;7.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.4 [0\u0026ndash;7.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eImmigrant Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eParents are native\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.7 [4.5\u0026ndash;5.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.6 [4.4\u0026ndash;4.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.1 [4.6\u0026ndash;5.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFirst-generation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.4 [3.3\u0026ndash;5.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5 [4.7\u0026ndash;6.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.3 [4.6\u0026ndash;8.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eImmigrant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.0 [3.9\u0026ndash;6.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.3 [4.7\u0026ndash;5.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5 [3.5\u0026ndash;7.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eRacial/ethnic minority\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.9 [4.0\u0026ndash;5.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5 [5.1\u0026ndash;5.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.7 [4.7\u0026ndash;6.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.7 [4.4\u0026ndash;4.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.5 [4.4\u0026ndash;4.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.3 [4.6\u0026ndash;5.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocioeconomic status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.7 [5.8\u0026ndash;7.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.0 [6.5\u0026ndash;7.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.4 [4.9\u0026ndash;9.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLower middle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.9 [4.5\u0026ndash;5.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.2 [5.0\u0026ndash;5.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.8 [5.1\u0026ndash;6.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUpper middle or upper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.4 [4.1\u0026ndash;4.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.9 [3.8\u0026ndash;4.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.8 [4.2\u0026ndash;5.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eHow well can you cover your basic needs (e.g., food, clothing, housing, transport, education, health care) with your current income?\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFairly or very well\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.1 [3.8\u0026ndash;4.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.6 [3.4\u0026ndash;3.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.1 [3.5\u0026ndash;4.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot at all to somewhat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.5 [5.1\u0026ndash;5.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.6 [5.5\u0026ndash;5.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.4 [5.7\u0026ndash;7.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eIf we take the overall monthly income of your family, how easy is it for your family to get by?\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEasily\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0 [3.7\u0026ndash;4.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.5 [3.4\u0026ndash;3.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.1 [3.4\u0026ndash;4.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWith difficulty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.4 [5.0\u0026ndash;5.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.6 [5.4\u0026ndash;5.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.4 [5.7\u0026ndash;7.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eGovernment restricted the movement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI am completely restricted or quarantined, and I cannot leave my house or quarantine location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.4 [4.6\u0026ndash;8.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.4 [4.7\u0026ndash;6.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.2 [2.8\u0026ndash;5.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI am somewhat restricted or advised to leave my house only for essentials\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.9 [4.7\u0026ndash;5.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.7 [4.6\u0026ndash;4.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.6 [5.1\u0026ndash;6.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThere are no restrictions on my movement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0 [3.5\u0026ndash;4.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.4 [4.1\u0026ndash;4.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.6 [3.3\u0026ndash;5.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eHIV status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHIV negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.9 [4.6\u0026ndash;5.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.6 [4.5\u0026ndash;4.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.3 [4.7\u0026ndash;5.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHIV positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.2 [3.5\u0026ndash;4.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.5 [4.1\u0026ndash;4.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.3 [3.3\u0026ndash;7.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eLost job\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.2 [5.6\u0026ndash;6.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.0 [5.7\u0026ndash;6.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.2 [6.1\u0026ndash;8.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.8 [3.4\u0026ndash;4.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.4 [3.2\u0026ndash;3.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.3 [3.3\u0026ndash;5.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnticipated income reduction from 60 to 100%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.8 [5.2\u0026ndash;6.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.1 [5.9\u0026ndash;6.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.5 [5.6\u0026ndash;7.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.5 [4.2\u0026ndash;4.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.2 [4.1\u0026ndash;4.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.9 [4.3\u0026ndash;5.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eCutting meals or reducing meal size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.9 [6.4\u0026ndash;7.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.0 [6.8\u0026ndash;7.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.5 [6.6\u0026ndash;8.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.2 [3.9\u0026ndash;4.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.0 [3.8\u0026ndash;4.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.4 [3.8\u0026ndash;4.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur purpose was to demonstrate the effect of the COVID-19 crisis on the economic well-being and mental health of GBT in EECA. We assumed that this impact would be different for groups with different social vulnerabilities.\u003c/p\u003e \u003cp\u003eSurvey participants were affected by the restrictions introduced due to COVID-19. COVID-19 related measures resulted in worsening economic situation, which led to a reduction in income (in 40% of cases by more than a third). A fifth part stated that it restricted their opportunities to have meals, which aligns with the share of economically vulnerable respondents. The most affected were GBTs from the Caucasus and Central Asia.\u003c/p\u003e \u003cp\u003eWe showed strong linkages between the belonging to especially vulnerable subgroups with the negative implications of COVID-19 related measures. Thus, young adults and people who did not identify as gay often saw their income decrease by more than two-thirds and were forced to reduce meal size; trans and nonbinary people, racial or ethnic minorities, people with a primary education, immigrants, and those who described their social status as low were more likely to lose jobs, income and access to food. The relationship between HIV status and economic losses was more complex: HIV-positive, HIV-negative, and those who did not know their status lost their jobs equally often; incomes decreased somewhat more often among people who did not know their status; and food was forced to be restricted more often by HIV-positive people or people without HIV status.\u003c/p\u003e \u003cp\u003eIn terms of the severity of depression and anxiety symptoms, it should be noted that the impact of the epidemic was rather weak, since the PHQ-4 scale values did not go beyond mild disorders. The severity of mental health disorders varied both in subregions (the most affected were GBTs from the Caucasus and Central Asia) and in groups differing in social vulnerability. Economic vulnerability seemed to be associated with mental health problems in all subregions, but gender identity and sexual orientation were associated with the severity of symptoms only among respondents from Russia. Thus, it seems reasonable to assume that economic losses could have been the main reason for the deterioration of mental health during the first wave of the epidemic.\u003c/p\u003e \u003cp\u003eData from other countries indicate that the COVID-19 epidemic increased the prevalence of suicidal ideations and attempts among men\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e and aggravated mental health situation in the general population \u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. As opposed to other regions, in EECA, depression and anxiety levels among GBT during the COVID-19 crisis were not high. These paradoxical results showing that despite the restrictions and economic losses, depression and anxiety levels did not exceed the bounds of mild deviations from the norm, are aligned with another face-to-face study among MSM conducted in Ukraine in 2021 \u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e, which demonstrated that during the spread of the Omicron variant of COVID-19, depression and anxiety levels were within the normal range.\u003c/p\u003e \u003cp\u003eThe linkage between younger age and higher depression and anxiety levels may be associated with higher average indicators of internalized homonegativity among younger subgroups of gay and bisexual men (as shown for the Russian Federation in \u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eThe nature of linkages between socio-economic vulnerabilities of GBT during the first wave of the COVID-19 (with the factors mostly non-specific for LGBT people associated with the changes in economic status and moderate symptoms of mental health disorders, see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) may indicate that belonging to gay and bisexual (and partly trans) community can be a factor of social vulnerability, but, unlike in other regions of the world, it is not a determinant in this regard. Unfortunately, we do not have data that would allow us to compare other groups described in the publications, such as hetero- and non-heterosexual people, men, and women, etc. One possible explanation could be a higher pre-crisis level of chronic stress due to internalized homo- or transphobia \u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e. In this regard higher LGBT resilience could be viewed as a tolerance to stress.\u003c/p\u003e \u003cp\u003eConsidering further research, we would propose that LGBT, who have more access to social support, could demonstrate not only more resilience in crises, but also less impact on their mental health after a crisis.\u003c/p\u003e \u003cp\u003eLimitations of the data presented are primarily associated with the pilot nature of the study. Potential inaccuracies may occur due to the following factors: (1) the data analysed were obtained in a cross-sectional survey, which cannot provide information on the causal connection between the epidemic and the observed changes. When we talk about the \u0026ldquo;effect,\u0026rdquo; in fact we mean the respondents\u0026rsquo; subjective perception that the changes observed by them were actually caused by the restrictions at the time of the rapid spread of COVID-19; (2) the survey only covered the Hornet mobile app users, but despite the existence of a global user community, it cannot be representative of the entire community of gay and bisexual men, as people in different countries and groups have uneven access to mobile connection and Internet; (4) when participating in the survey, respondents could choose their preferred language (English, Spanish, Russian, French or Turkish). It was assumed that people from EECA countries know either Russian or English, which limited the participation of people from countries, where the knowledge of these languages is not widespread.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eData on the effect of the social restrictions imposed in response to the COVID-19 on LGBT people are limited, especially in the region of Eastern Europe and Central Asia.\u003c/p\u003e \u003cp\u003eA cross-sectional online survey of a non-random sample of 5,037 Hornet mobile app GBT users, who reside in the EECA countries, was conducted in March\u0026ndash;May 2020. It demonstrated that COVID-19 crisis worsened the economic situation of the GBT. However, the data on mental health changes are paradoxical and differ from similar data from other regions of the world. Despite the restrictions on physical freedom and economic losses, the levels of depression and anxiety in EECA did not exceed the bounds of mild deviations from the norm. Social changes caused by the COVID-19 crisis had more severe consequences for the more vulnerable people, such as trans and non-binary people, members of racial or ethnic minorities, people with low educational level or low socioeconomic status, and young people.\u003c/p\u003e \u003cp\u003eThe results demonstrate the intersectional effects of restrictions on the physical, social, and mental well-being of GBT. The negative implications of the COVID-19 crisis affected the entire population in the EECA region, but more economically vulnerable subgroups have suffered the most.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMK, SS, and EL \u0026mdash; analysis and interpretation of the data, and the drafting of the paper; SH, AG, and SB \u0026mdash; the conception and design of the survey, revising it critically for intellectual content; MK, SS, SH, AG, SB, and EL \u0026mdash; the final approval of the version to be published. All authors agree to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Statement:\u003c/strong\u003e The survey procedures were reviewed and approved by the Institutional Review Board of the Johns Hopkins School of Public Health (USA)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure\u0026nbsp;statement:\u003c/strong\u003e the authors report there are no competing interests to declare\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u0026nbsp;\u0026nbsp;\u003c/strong\u003ethe data associated with a paper cannot be made open without the permission of HORNET LTD and LGBT Foundation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;details:\u003c/strong\u003e this work was not supported by funding\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eOnyeaka H, Anumudu CK, Al-Sharify ZT, Egele-Godswill E, Mbaegbu P (2021) COVID-19 pandemic: A review of the global lockdown and its far-reaching effects. 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BMC Psychiatry 23(1):46. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12888-023-04539-9\u003c/span\u003e\u003cspan address=\"10.1186/s12888-023-04539-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKasianchuk M, Titar I, Salnikov S, Ohorodnik O, Kulchynska R, Sazonova Y, Andrianova I, Sheiko O, Sichkar S, Trofymenko O (2023) Report on biological and behavioral survey among men who have sex with men in Ukraine (2021)\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e Countries of the EECA region: Armenia, Azerbaijan, Belarus, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Moldova, Russian Federation, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"LGBT Foundation","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"COVID-19 crisis, GBT, EECA, economic impact, mental health, disparities","lastPublishedDoi":"10.21203/rs.3.rs-8996854/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8996854/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cb\u003eBackground.\u003c/b\u003e Limited data exists on how COVID-19 restrictions have affected LGBT in the Eastern Europe and Central Asia (EECA) region.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMethods.\u003c/b\u003e It was conducted a cross-sectional survey in 2020, involving 5,037 Hornet users in EECA.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResults and discussion.\u003c/b\u003e A part of the sample belongs to vulnerable groups (lower social status, racial/ethnic minorities, etc). The economic circumstances of GBT were impacted: 21% lost at least 2/3 of income; 21% lost jobs; and 24% found themselves in extreme poverty. More vulnerable populations felt heavily struck (f. e. a food intake had been shortened among transgender people 41% vs 21% among cisgender ones).\u003c/p\u003e \u003cp\u003eDespite the limitation of physical freedom and economic losses, the level of depression and anxiety did not exceed the bounds of mild deviations (PHQ-4: 4.7, 95% CI: 4.6\u0026ndash;4.8).\u003c/p\u003e \u003cp\u003e \u003cb\u003eConclusions.\u003c/b\u003e The data presented suggests the readiness of EECA GBT communities to face future crises.\u003c/p\u003e","manuscriptTitle":"Paradoxical Linkage between Mental Health and Social Implications of COVID-19 crisis in Gay, Bisexual Men and transgenders in Eastern Europe and Central Asia: Results of Survey among the Hornet Mobile App Users","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-03 08:25:07","doi":"10.21203/rs.3.rs-8996854/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"821e5f8b-859e-4d88-9e50-d7ce0ae60642","owner":[],"postedDate":"March 3rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":63703359,"name":"Sociology"}],"tags":[],"updatedAt":"2026-03-03T08:25:07+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-03 08:25:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8996854","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8996854","identity":"rs-8996854","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}