Abstract
Objective:
To examine the association of drug use stigma with antiretroviral therapy (ART) use and HIV viral suppression among people with HIV who inject drugs in India.
Design:
Cross-sectional bio-behavioral survey.
Methods:
Between 08/2016 and 05/2017, persons aged ≥18 years who reported injection drug use in the past two years were recruited via respondent-driven sampling (RDS) in 12 Indian cities (n≈1000/city). The analysis was restricted to participants with laboratory-confirmed HIV infection who self-reported a prior HIV diagnosis and were eligible for ART per concurrent national HIV treatment guidelines. Enacted and internalized drug use stigma were each measured by 5–6 item subscales. The study outcomes were HIV viral suppression (<150 copies/mL) and self-reported past 30-day ART use. RDS-II weighted multivariable logistic regression with a city-level random-intercept was used to estimate adjusted odds ratios (aOR) and corresponding 95% confidence intervals (CIs).
Results:
Among 971 ART-eligible participants previously diagnosed with HIV, 65.1% reported ART use and 56.1% were virally suppressed. Reporting any enacted stigma (vs. none) was associated with lower odds of ART use (aOR=0.26 [95%CI=0.15–0.44]) and viral suppression (aOR=0.49 [95%CI=0.31–0.78]). High internalized stigma scores (>median vs. ≤median) were associated with lower odds of viral suppression among participants aged ≥35 years (aOR=0.51 [95%CI=0.27–0.97]) but not among participants aged <35 years (aOR=1.22 [95%CI=0.57–2.60]). Similar associations were observed in analyses restricted to participants ever linked to HIV care.
Conclusions:
Drug use stigma may be a barrier to HIV viral suppression among people with HIV who inject drugs, thereby hindering efforts to achieve HIV control.
Keywords: stigma, discrimination, substance use disorder, people who use drugs, people who inject drugs, healthcare utilization, HIV non-suppression
Introduction
HIV viral suppression optimizes individual-level health, prevents onward HIV transmission, and contributes to population-level HIV control[1–3]. In most low- and middle-income countries, viral suppression among people who inject drugs (PWID) with HIV is still well below the UNAIDS “90-90-90” target for 2020[4,5]. Although lack of HIV diagnosis is a key barrier to viral suppression among many PWID[6], it is important to characterize residual barriers following HIV diagnosis such as social stigma.
Attention to address HIV stigma has increased globally[7]. However, drug use stigma is also pervasive worldwide and may impact HIV outcomes, particularly among PWID. In nearly all settings, drug use stigma manifests at the structural-level through the criminalization of drug use and related punitive laws and policies[8,9]. Drug use stigma also manifests at the individual-level through various mechanisms (e.g. enacted [i.e., experienced] and internalized [i.e., self-perceived] stigma), some of which have been associated with poorer perceived health status, lower attendance to general healthcare and HIV care visits, and lower CD4+ T-cell counts among PWID with HIV[10–12]. PWID with HIV have also voiced drug use stigma as a barrier to HIV care and antiretroviral therapy (ART) use and adherence[13–17]. There are limited quantitative data on the impact of stigmas, including drug use stigma, on viral suppression among PWID with HIV.
In India, PWID experience intense levels of drug use stigma and have suboptimal levels of HIV viral suppression[6,18,19]. In this multi-city, population-based study in India, we examine the associations of enacted and internalized drug use stigma with ART use and viral suppression among PWID previously diagnosed with HIV and eligible for ART.
Methods
Study population and procedures
Data were obtained from a cluster-randomized trial of integrated HIV prevention and treatment services among PWID and men who have sex with men in India [ClinicalTrials.gov identifier-NCT01686750][20,21]. The intervention did not impact population-level ART coverage or HIV viral suppression. This secondary analysis used data from the cross-sectional evaluation survey conducted among PWID between 08/2016–05/2017. In 12 cities, ~1000 PWID were recruited per city via respondent-driven sampling (RDS) with two seed participants per city and two referral coupons per participant. Eligible participants self-reported injection drug use in the past two years, provided informed oral consent, and had a valid RDS referral coupon. Participants completed face-to-face structured surveys administered by trained interviewers, provided a blood specimen, and received on-site rapid HIV testing and counseling per national guidelines. Among all participants who tested positive for HIV, CD4+ T-cell counts were measured using the FlowCARE PLG CD4 assay (Beckman Coulter, CA) and plasma HIV-1 RNA was measured using the RealTime HIV-1 assay (limit of detection=150 copies/mL; Abbott Park, IL). This study was approved by the institutional review boards at the Y.R. Gaitonde Centre for AIDS Research and Education and the Johns Hopkins University School of Medicine.
RDS process measures have been previously reported[21]. Excluding RDS seeds, 11,721 PWID were recruited (Figure.S1). This analysis was restricted to participants who had a laboratory-confirmed HIV infection, self-reported a prior HIV-positive diagnosis, and were eligible for ART at the time of the survey. ART eligibility was defined as a lifetime history of ART use or indication for ART at the time of the survey based on concurrent national guidelines (CD4+ count<350 cells/mm3)[22]. Of 2517 participants with HIV, 1117 had a prior HIV-positive diagnosis, of which 993 were ART-eligible. Twenty-two participants were additionally excluded due to missing data on key variables, yielding an analytic sample of 971 (Table.S1).
Exposures
The survey included six Likert-scale items that measured enacted drug use stigma from various sources (i.e., healthcare workers, family, and non-specific sources) and five Likert-scale items that measured internalized drug use stigma (see Table.S2 for full items)[18,20]. Psychometric properties of these subscales in the overall study sample have been previously described[18]. In this subsample, confirmatory factor analysis suggested a 2-factor model acceptably fit the data (Table.S3); both the enacted (α=0.87) and internalized stigma (α=0.92) subscales had high internal consistency. Mean scores were calculated for each subscale, with higher scores reflecting greater stigma (range=0–3). Given there are no standard score cutpoints, scores were dichotomized a priori as none vs. any (0 vs. >0) for enacted stigma and at the population-level overall median score (≤median vs. >median) for internalized stigma[18].
Outcomes
The primary outcome was HIV viral suppression (HIV-1 RNA<150 copies/mL). Self-reported ART use in the past 30 days was examined as a secondary outcome.
Statistical analysis
A composite weight of RDS-II weights and the relative city population size of PWID was used to calculate summary statistics with data from all cities combined[23,24].
The association of each stigma measure with each outcome was examined using separate multilevel logistic regression models that incorporated a city-level random-intercept and sample size-scaled RDS-II weights as sampling weights. Adjusted odds ratios (aOR) and corresponding 95% confidence intervals (CI) were estimated from a multivariable model that included adjustment for covariates that are established determinants of viral suppression and hypothesized to be associated with drug use stigma: age (continuous), gender, northeast region, educational attainment, unstable housing, incarceration in the past 6 months, alcohol use/dependence (AUDIT), and IDU frequency in the past 6 months (none, yes-less than daily, yes-daily). While IDU frequency can be considered a potential confounder or mediator, we included adjustment for it given it is a strong predictor of viral suppression in this study population and there was no temporality in variable measurement[25]. As a secondary analysis, each enacted stigma item was separately modeled given they reflect different sources of stigma.
Subgroup analyses were conducted stratified by age group (<35 and ≥35 years). It was hypothesized that age may modify the association of internalized stigma with viral suppression given that age is often a determinant of HIV outcomes[25,26], and older PWID have a longer exposure to drug use stigma, including prior to drug use initiation.
Sensitivity analyses were also conducted among participants who self-reported ever seeing a doctor for HIV care as well as among participants who self-reported ever using ART. Unweighted analyses were conducted to test the sensitivity of results to the RDS-II estimator and to visually depict the probability of viral suppression by continuous internalized stigma scores using random-effects generalized additive models.
Of note, all reported sample sizes are unweighted and all other estimates are weighted, unless specified otherwise.
Results
In the analytic population (n=971), the median age was 36 years (IQR=29–42) and the median duration of IDU was 13 years (IQR=8–20) (Table.1). IDU duration was positively correlated with age (Pearson’s r=0.75), but was not correlated with enacted stigma scores (r=−0.02) or internalized stigma scores (r=−0.06). The distribution of enacted stigma scores were right-skewed with a median of 0.0 (IQR=0.0–0.3); 34.8% (n=458) reported any enacted stigma. The median internalized stigma score was 1.6 (IQR=0.8–2.4). The prevalence of past 30-day ART use and HIV viral suppression was 65.1% (n=610) and 56.1% (n=541), respectively.
Table 1.
Characteristics of the study population overall and by enacted and internalized stigma score (n=971).
| Characteristic | No. of Participants (%) a | ||||
|---|---|---|---|---|---|
| Overall | Enacted stigma | Internalized stigma | |||
| None [0] | Any [> 0] | ≤ 1.6 | > 1.6 | ||
| Overall sample size, N | 971 | 513 | 458 | 467 | 504 |
| Median age (IQR), years | 36 (29–42) | 36 (29–42) | 35 (30–42) | 37 (30–43) | 35 (28–41) |
| Gender | |||||
| Male | 829 (76.8) | 423 (72.4) | 406 (84.9) | 389 (69.0) | 440 (85.5) |
| Female | 142 (23.2) | 90 (27.6) | 52 (15.1) | 78 (31.0) | 64 (14.5) |
| Transgender | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 0 (0.0) |
| Northeast region | |||||
| No | 396 (39.6) | 175 (32.4) | 221 (53.0) | 136 (22.7) | 260 (58.7) |
| Yes | 575 (60.4) | 338 (67.6) | 237 (47.0) | 331 (77.3) | 244 (41.3) |
| Educational attainment | |||||
| Primary or less | 251 (32.7) | 116 (29.6) | 135 (38.4) | 100 (29.9) | 151 (35.8) |
| Secondary | 455 (46.6) | 237 (47.1) | 218 (45.7) | 219 (50.1) | 236 (42.7) |
| High school or more | 265 (20.7) | 160 (23.3) | 105 (15.9) | 148 (20.0) | 117 (21.5) |
| Housing instability | |||||
| Stable housing | 922 (94.8) | 498 (97.1) | 424 (90.6) | 448 (95.3) | 474 (94.4) |
| Homeless or living in a slum | 49 (5.2) | 15 (2.9) | 34 (9.4) | 19 (4.7) | 30 (5.6) |
| Incarcerated in the past 6 months | |||||
| No | 892 (94.7) | 485 (96.4) | 407 (91.5) | 437 (95.9) | 455 (93.3) |
| Yes | 79 (5.3) | 28 (3.6) | 51 (8.5) | 30 (4.1) | 49 (6.7) |
| Alcohol use (AUDIT) | |||||
| None/mild | 737 (83.6) | 452 (92.9) | 285 (66.2) | 385 (87.3) | 352 (79.4) |
| Harmful/hazardous | 120 (8.7) | 33 (4.0) | 87 (17.7) | 45 (7.0) | 75 (10.7) |
| Dependence | 114 (7.6) | 28 (3.1) | 86 (16.1) | 37 (5.6) | 77 (9.9) |
| Injection drug use in the past 6 months | |||||
| None | 369 (55.2) | 269 (69.6) | 100 (28.1) | 219 (66.4) | 150 (42.5) |
| Less than daily | 197 (16.6) | 89 (12.4) | 108 (24.5) | 75 (11.2) | 122 (22.7) |
| Daily | 405 (28.2) | 155 (18.0) | 250 (47.4) | 173 (22.4) | 232 (34.8) |
| Median duration of IDU (IQR), years b | 13 (8–20) | 13 (8–21) | 13 (8–19) | 13 (8–21) | 13 (8–19) |
| Lifetime history of receiving HIV care | |||||
| No | 176 (14.9) | 71 (9.6) | 105 (24.8) | 88 (12.4) | 88 (17.7) |
| Yes | 795 (85.1) | 442 (90.4) | 353 (75.2) | 379 (87.6) | 416 (82.3) |
| Lifetime history of ART use | |||||
| No | 289 (28.0) | 132 (21.8) | 157 (39.7) | 122 (21.2) | 167 (35.8) |
| Yes | 682 (72.0) | 381 (78.2) | 301 (60.3) | 345 (78.8) | 337 (64.2) |
Note: Greater stigma scores reflect a greater degree of stigma reported.
Unless specified otherwise, data are unweighted sample sizes and corresponding weighted column percentages (%) estimated using a composite weight that accounts for the RDS-II weight and relative city population size of PWID derived from state-level data.
9 participants were missing data on duration of injection drug use.
Abbreviations: ART, antiretroviral therapy; IDU, injection drug use; IQR, interquartile range
Participants reporting any enacted stigma (vs. none) had one-fourth the adjusted odds of ART use (aOR=0.26;[95%CI=0.15–0.44]) and half the adjusted odds of viral suppression (aOR=0.49;[95%CI=0.31–0.78]) (Table.2). While the healthcare-related enacted stigma items were not associated with viral suppression, having previously received any threat of physical harm from a non-specific source was associated with viral suppression (aOR=0.45;[95%CI=0.32–0.62]) (Table.S4).
Table 2.
Association of drug use stigma with antiretroviral therapy use and HIV viral suppression overall and stratified by age group (n=971).
| Drug use stigma | N | Outcome: Antiretroviral therapy use in the past 30 days |
Outcome: HIV viral suppression (<150 copies/mL) |
||||
|---|---|---|---|---|---|---|---|
| No. (%) a | OR (95% CI) b | aOR (95% CI) b,c | No. (%) a | OR (95% CI) b | aOR (95% CI) b,c | ||
| Overall | |||||||
| Enacted stigma | |||||||
| None (0) | 513 | 358 (74.8) | Ref. | Ref. | 321 (63.7) | Ref. | Ref. |
| Any (>0) | 458 | 252 (46.8) | 0.28 (0.19, 0.42) | 0.26 (0.15, 0.44) | 220 (41.7) | 0.47 (0.31, 0.71) | 0.49 (0.31, 0.78) |
| Internalized stigma | |||||||
| ≤ 1.6 | 467 | 320 (75.8) | Ref. | Ref. | 290 (60.8) | Ref. | Ref. |
| > 1.6 | 504 | 290 (52.9) | 0.65 (0.38, 1.12) | 0.67 (0.38, 1.18) | 251 (50.7) | 0.61 (0.37, 0.996) | 0.68 (0.39, 1.17) |
| Age < 35 years | |||||||
| Enacted stigma | |||||||
| None (0) | 197 | 101 (59.9) | Ref. | Ref. | 78 (46.3) | Ref. | Ref. |
| Any (>0) | 201 | 73 (30.4) | 0.35 (0.16, 0.77) | 0.35 (0.11, 1.11) | 64 (32.5) | 1.04 (0.48, 2.28) | 0.98 (0.41, 2.35) |
| Internalized stigma | |||||||
| ≤ 1.6 | 178 | 88 (63.6) | Ref. | Ref. | 70 (42.6) | Ref. | Ref. |
| > 1.6 | 220 | 86 (35.0) | 0.74 (0.31, 1.72) | 0.82 (0.45, 1.51) | 72 (40.1) | 0.99 (0.43, 2.25) | 1.22 (0.57, 2.60) |
| Age ≥ 35 years | |||||||
| Enacted stigma | |||||||
| None (0) | 316 | 257 (86.7) | Ref. | Ref. | 243 (77.7) | Ref. | Ref. |
| Any (>0) | 257 | 179 (61.0) | 0.26 (0.14, 0.50) | 0.25 (0.13, 0.45) | 156 (49.6) | 0.28 (0.14, 0.58) | 0.33 (0.18, 0.64) |
| Internalized stigma | |||||||
| ≤ 1.6 | 289 | 232 (84.9) | Ref. | Ref. | 220 (74.5) | Ref. | Ref. |
| > 1.6 | 284 | 204 (69.3) | 0.59 (0.34, 1.04) | 0.58 (0.32, 1.07) | 179 (60.3) | 0.44 (0.27, 0.73) | 0.51 (0.27, 0.97) |
Note: Greater stigma scores reflect a greater degree of stigma reported.
Data are unweighted sample sizes and corresponding weighted row percentages (%) estimated using a composite weight that accounts for the RDS-II weight and relative city population size of PWID derived from state-level data.
Separately for each stigma domain and outcome, odds ratios (OR) and corresponding 95% confidence intervals (CI) were estimated from a logistic regression model with a random-intercept for each city and scaled RDS-II weights.
The multivariable model included adjustment for age, gender, northeast region, educational attainment, unstable housing, incarceration in the past 6 months, alcohol use/dependence, and IDU frequency in the past 6 months.
High levels of internalized stigma (>1.6 vs. ≤1.6) were associated with 0.61 (95%CI=0.37–0.996) lower crude odds of viral suppression, but this association was attenuated in multivariable analysis (aOR=0.68;[95%CI=0.39–1.17]).
Any enacted stigma was associated with lower adjusted odds of viral suppression among participants aged ≥35 years (aOR=0.33;[95%CI=0.18–0.64]) but not among those aged <35 years (aOR=0.98;[95%CI=0.41–2.35]). Similarly, high levels of internalized stigma were associated with lower adjusted odds of viral suppression among participants aged ≥35 years (aOR=0.51;[95%CI=0.27–0.97]) but not among those aged <35 years (aOR=1.22;[95%CI=0.57–2.60]).
The direction of each association was generally the same in sensitivity analyses (Tables.S5–S6;Figure.S2).
Discussion
In a multi-city, community-based sample of PWID who were previously diagnosed with HIV and indicated for ART use, enacted drug use stigma was associated with reduced likelihood of ART use and HIV viral suppression. Additionally, higher internalized drug use stigma was associated with reduced likelihood of viral suppression among those aged ≥35 years. Drug use stigma may partially explain the suboptimal levels of viral suppression among PWID with HIV in India, with potential moderation by age.
This study includes data from 12 Indian cities with heterogenous HIV and drug use epidemic contexts, and the study findings are consistent with qualitative studies among PWID with HIV in India, which suggest drug use stigma is a barrier to accessing and adhering to ART[14,17]. In contrast, a study among PWID with HIV in Saint-Petersburg, Russia found no association of perceived drug use stigma with self-reported ART initiation[27]. The conflicting results between studies could be due to differential sociostructural and cultural contexts[10], as well as differences in stigma and outcome measurement. Comparable data on stigmas and viral suppression among PWID with HIV are limited; however, in other key populations, there have been mixed results regarding associations between stigmas and viral suppression[28–30].
This study is limited by its cross-sectional design, which precluded causal effect estimation and mediation analysis. Drawing from existing stigma frameworks[31–34], the observed associations may be partly mediated by drug use practices[18,35,36], depression and mental distress[10,37–39], social isolation (self-isolation and social rejection)[40,41], healthcare avoidance[42,43], and ultimately low ART use and adherence. Longitudinal studies are needed to quantify the health-related impacts and mediating mechanisms of drug use, HIV, and other intersecting stigmas among PWID.
Given the pervasiveness of drug use stigma, multilevel stigma reduction interventions are likely needed to effectively reduce it. While enacted drug use stigma from healthcare settings was not associated with viral suppression, this may be because greater engagement in health services leads to more opportunity for experiencing stigma[44]. Stigma reduction interventions in healthcare settings are important[45], as any reports of enacted stigma in healthcare settings are unacceptable and can contribute to internalized and anticipated stigma among PWID communities[42,44]. The strong association between receiving threats of physical harm from non-specific sources and viral suppression underscores the need for broader socio-structural stigma reduction interventions outside healthcare settings as well.
There was also a high burden of internalized drug use stigma, which was associated with viral suppression among older PWID but not among younger PWID. In addition to older PWID having had greater exposure to drug use stigma across their lifespan, it is possible that older PWID have poorer social support systems to buffer stigma effects[46]. It is also plausible that younger PWID have a lower perceived need for ART, presumably due to a shorter time since HIV diagnosis. Interventions that help PWID address different aspects of drug use stigma may help improve HIV outcomes.
In summary, drug use stigma may be a barrier to achieving the final pillar of the UNAIDS 2030 “95–95-95” targets among PWID[4]. Programmatic efforts should consider prioritizing drug use stigma reduction to maximize the effectiveness of treatment as prevention and alleviate inequities among PWID.
Supplementary Material
Acknowledgements
We sincerely thank the National AIDS Control Organization (NACO), India, and all of our partner non-governmental organizations across India. We are also very grateful to the study participants, without whom this work would not have been possible.
Source of Funding:
This work was supported by the National Institutes of Health (NIH) (grant numbers K24DA035684, R01DA032059, R01DA041034, DP2DA040244, T32AI102623, and F31DA054849) and the Johns Hopkins University Center for AIDS Research, an NIH funded program (1P30AI094189), which is supported by the following NIH Co-Funding and Participating Institutes and Centers: NIAID, NCI, NICHD, NHLBI, NIDA, NIA, NIGMS, NIDDK, NIMHD. Additional support was also received from the Elton John AIDS Foundation. The funders of the study had no role in study design, data collection, data analysis, data interpretation, writing of the report, or the decision to submit for publication; thus, the content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the funding organizations.
Conflicts of interest:
SHM reports personal fees from Gilead Sciences, outside the submitted work. SSS reports receiving grants, personal fees, and non-financial support from Gilead Sciences, and grants and non-financial support from Abbott Laboratories, outside the submitted work. All other authors declare no competing interests.
Footnotes
Previous Presentation: This work was presented in part at the AIDS 2020: 23rd International AIDS Conference, 6–10 July 2020, Virtual.
Data availability
The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.
References
- 1.Cohen MS, Chen YQ, McCauley M, Gamble T, Hosseinipour MC, Kumarasamy N, et al. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med 2011; 365:493–505. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Lundgren JD, Babiker AG, Gordin F, Emery S, Grund B, Sharma S, et al. Initiation of Antiretroviral Therapy in Early Asymptomatic HIV Infection. N Engl J Med 2015; 373:795–807. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Havlir D, Lockman S, Ayles H, Larmarange J, Chamie G, Gaolathe T, et al. What do the Universal Test and Treat trials tell us about the path to HIV epidemic control? J Int AIDS Soc 2020; 23:e25455. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.UNAIDS. Understanding Fast-Track Targets. Accelerating action to end the AIDS epidemic by 2030. Geneva, Switz Jt United Nations Program HIV/AIDS 2015. [Google Scholar]
- 5.Risher K, Mayer KH, Beyrer C. HIV treatment cascade in MSM, people who inject drugs, and sex workers. Curr. Opin. HIV AIDS. 2015. doi: 10.1097/COH.0000000000000200 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Mehta SH, Lucas GM, Solomon S, Srikrishnan AK, McFall AM, Dhingra N, et al. HIV care continuum among men who have sex with men and persons who inject drugs in India: barriers to successful engagement. Clin Infect Dis 2015; 61:1732–1741. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Nyblade L, Mingkwan P, Stockton MA. Stigma reduction: an essential ingredient to ending AIDS by 2030. lancet HIV 2021; 8:e106–e113. [DOI] [PubMed] [Google Scholar]
- 8.Csete J, Kamarulzaman A, Kazatchkine M, Altice F, Balicki M, Buxton J, et al. Public health and international drug policy. Lancet (London, England) 2016; 387:1427–1480. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.DeBeck K, Cheng T, Montaner JS, Beyrer C, Elliott R, Sherman S, et al. HIV and the criminalisation of drug use among people who inject drugs: a systematic review. Lancet HIV 2017; 4:e357–e374. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Burke SE, Calabrese SK, Dovidio JF, Levina OS, Uusküla A, Niccolai LM, et al. A tale of two cities: stigma and health outcomes among people with HIV who inject drugs in St. Petersburg, Russia and Kohtla-Järve, Estonia. Soc Sci Med 2015; 130:154–161. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Calabrese SK, Burke SE, Dovidio JF, Levina OS, Uusküla A, Niccolai LM, et al. Internalized HIV and Drug Stigmas: Interacting Forces Threatening Health Status and Health Service Utilization Among People with HIV Who Inject Drugs in St. Petersburg, Russia. AIDS Behav 2016; 20:85–97. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Vetrova MV, Cheng DM, Bendiks S, Gnatienko N, Lloyd-Travaglini C, Jiang W, et al. HIV and Substance Use Stigma, Intersectional Stigma and Healthcare Among HIV-Positive PWID in Russia. AIDS Behav 2021; 25:2815–2826. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Sabin LL, Desilva MB, Hamer DH, Keyi X, Yue Y, Wen F, et al. Barriers to adherence to antiretroviral medications among patients living with HIV in southern China: a qualitative study. AIDS Care 2008; 20:1242–1250. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Chakrapani V, Velayudham J, Shunmugam M, Newman PA, Dubrow R. Barriers to antiretroviral treatment access for injecting drug users living with HIV in Chennai, South India. AIDS Care 2014; 26:835–841. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Kiriazova T, Lunze K, Raj A, Bushara N, Blokhina E, Krupitsky E, et al. “It is easier for me to shoot up”: stigma, abandonment, and why HIV-positive drug users in Russia fail to link to HIV care. AIDS Care 2017; 29:559–563. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Davis A, McCrimmon T, Dasgupta A, Gilbert L, Terlikbayeva A, Hunt T, et al. Individual, social, and structural factors affecting antiretroviral therapy adherence among HIV-positive people who inject drugs in Kazakhstan. Int J Drug Policy 2018; 62:43–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Kumar S, Gupte HA, Isaakidis P, Mishra JK, Munjattu JF. “They don’t like us….”: Barriers to antiretroviral and opioid substitution therapy among homeless HIV positive people who inject drugs in Delhi: A mixed method study. PLoS One 2018; 13:e0203262. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Patel EU, Solomon SS, Lucas GM, McFall AM, Tomori C, Srikrishnan AK, et al. Drug use stigma and its association with active hepatitis C virus infection and injection drug use behaviors among community-based people who inject drugs in India. Int J Drug Policy 2021; 96:103354. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Patel EU, Solomon SS, Lucas GM, McFall AM, Srikrishnan AK, Kumar MS, et al. Temporal change in population-level prevalence of detectable HIV viraemia and its association with HIV incidence in key populations in India: a serial cross-sectional study. lancet HIV 2021; 8:e544–e553. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Solomon SS, Lucas GM, Celentano DD, McFall AM, Ogburn E, Moulton LH, et al. Design of the Indian NCA study (Indian national collaboration on AIDS): a cluster randomized trial to evaluate the effectiveness of integrated care centers to improve HIV outcomes among men who have sex with men and persons who inject drugs in India. BMC Health Serv Res 2016; 16:652. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Solomon SS, Solomon S, McFall AM, Srikrishnan AK, Anand S, Verma V, et al. Integrated HIV testing, prevention, and treatment intervention for key populations in India: a cluster-randomised trial. Lancet HIV 2019; 6:e283–e296. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.National AIDS Control Organization. National Guidelines for HIV Testing. New Delhi, India: ; 2015. http://www.naco.gov.in/sites/default/files/National_Guidelines_for_HIV_Testing_21Apr2016.pdf
- 23.Volz E, Heckathorn D. Probability based estimation theory for respondent driven sampling. J Off Stat 2008. [Google Scholar]
- 24.National Institute of Medical Statistics and National AIDS Control Organization (NACO). Technical Report: India HIV Estimates. 2010.
- 25.Prabhu S, McFall AM, Mehta SH, Srikrishnan AK, Kumar MS, Anand S, et al. Psychosocial Barriers to Viral Suppression in a Community-based Sample of Human Immunodeficiency Virus-infected Men Who Have Sex With Men and People Who Inject Drugs in India. Clin Infect Dis 2020; 70:304–313. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.McFall AM, Mehta SH, Srikrishnan AK, Lucas GM, Vasudevan CK, Celentano DD, et al. Getting to 90: linkage to HIV care among men who have sex with men and people who inject drugs in India. AIDS Care 2016; 28:1230–1239. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Vetrova M, Lodi S, Rateau L, Patts G, Blokhina E, Palatkin V, et al. Stigma and ART initiation among people with HIV and a lifetime history of illicit drug use in Saint-Petersburg, Russia-A prospective cohort analysis. Int J Drug Policy 2022; 102:103600. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Lyons CE, Olawore O, Turpin G, Coly K, Ketende S, Liestman B, et al. Intersectional stigmas and HIV-related outcomes among a cohort of key populations enrolled in stigma mitigation interventions in Senegal. AIDS 2020; 34 Suppl 1:S63–S71. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Yam EA, Pulerwitz J, Almonte D, García F, Del Valle A, Colom A, et al. Stigma among key populations living with HIV in the Dominican Republic: experiences of people of Haitian descent, MSM, and female sex workers. AIDS 2020; 34 Suppl 1:S43–S51. [DOI] [PubMed] [Google Scholar]
- 30.Geibel S, Gottert A, Friedland BA, Jeremiah K, McClair TL, Mallouris C, et al. Internalized stigma among people living with HIV: assessing the Internalized AIDS-Related Stigma Scale in four countries. AIDS 2020; 34 Suppl 1:S33–S41. [DOI] [PubMed] [Google Scholar]
- 31.Hatzenbuehler ML, Phelan JC, Link BG. Stigma as a fundamental cause of population health inequalities. Am J Public Health 2013; 103:813–821. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Earnshaw VA, Chaudoir SR. From conceptualizing to measuring HIV stigma: a review of HIV stigma mechanism measures. AIDS Behav 2009; 13:1160–1177. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Stangl AL, Earnshaw VA, Logie CH, van Brakel W, C Simbayi L, Barré I, et al. The Health Stigma and Discrimination Framework: a global, crosscutting framework to inform research, intervention development, and policy on health-related stigmas. BMC Med. 2019; 17:31. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Earnshaw VA. Stigma and substance use disorders: A clinical, research, and advocacy agenda. Am Psychol 2020; 75:1300–1311. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Cama E, Brener L, Wilson H, von Hippel C. Internalized Stigma Among People Who Inject Drugs. Subst Use Misuse 2016; 51:1664–1668. [DOI] [PubMed] [Google Scholar]
- 36.von Hippel C, Brener L, Horwitz R. Implicit and explicit internalized stigma: Relationship with risky behaviors, psychosocial functioning and healthcare access among people who inject drugs. Addict Behav 2018; 76:305–311. [DOI] [PubMed] [Google Scholar]
- 37.Thanh DC, Moland KM, Fylkesnes K. Persisting stigma reduces the utilisation of HIV-related care and support services in Viet Nam. BMC Health Serv Res 2012; 12:428. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Couto E Cruz C, Salom CL, Dietze P, Burns L, Alati R. The association between experiencing discrimination and physical and mental health among people who inject drugs. Int J Drug Policy 2019; 65:24–30. [DOI] [PubMed] [Google Scholar]
- 39.Li L, Lin C, Feng N, Nguyen DB, Cao W, Le AT, et al. Stigma Related to HIV and Drug Use: Layers, Types, and Relations to Mental Health. AIDS Behav 2020; 24:2347–2354. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Salter ML, Go VF, Le Minh N, Gregowski A, Ha TV, Rudolph A, et al. Influence of Perceived Secondary Stigma and Family on the Response to HIV Infection Among Injection Drug Users in Vietnam. AIDS Educ Prev Off Publ Int Soc AIDS Educ 2010; 22:558–570. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Spooner C, Saktiawati AMI, Lazuardi E, Worth H, Subronto YW, Padmawati RS. Impacts of stigma on HIV risk for women who inject drugs in Java: A qualitative study. Int J Drug Policy 2015; 26:1244–1250. [DOI] [PubMed] [Google Scholar]
- 42.Biancarelli DL, Biello KB, Childs E, Drainoni M, Salhaney P, Edeza A, et al. Strategies used by people who inject drugs to avoid stigma in healthcare settings. Drug Alcohol Depend 2019; 198:80–86. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Heath AJ, Kerr T, Ti L, Kaplan K, Suwannawong P, Wood E, et al. Healthcare avoidance by people who inject drugs in Bangkok, Thailand. J Public Health (Oxf) 2016; 38:e301–e308. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Djordjevic F, Ryan K, Gunn J, Brener L, O’Keefe D, Draper B, et al. Health service utilization and experiences of stigma amongst people who inject drugs in Melbourne, Australia. J Viral Hepat 2021; 28:1738–1743. [DOI] [PubMed] [Google Scholar]
- 45.Nyblade L, Stockton MA, Giger K, Bond V, Ekstrand ML, Lean RM, et al. Stigma in health facilities: why it matters and how we can change it. BMC Med. 2019; 17:25. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Crystal S, Akincigil A, Sambamoorthi U, Wenger N, Fleishman JA, Zingmond DS, et al. The diverse older HIV-positive population: a national profile of economic circumstances, social support, and quality of life. J Acquir Immune Defic Syndr 2003; 33 Suppl 2:S76–83. [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.