Sae Takada1, Viola Nyakato2, Akihiro Nishi3, A James O'Malley4, Bernard Kakuhikire2, Jessica M Perkins5, David R Bangsberg6, Nicholas A Christakis7, Alexander C Tsai8. 1. National Clinician Scholars Program UCLA, Division of General Internal Medicine and Health Services Research, Department of Medicine, Los Angeles, CA, USA; VA HSR&D Center for the Study of Healthcare Innovation, Implementation & Policy, Los Angeles, CA, USA. Electronic address: stakada@mednet.ucla.edu. 2. Mbarara University of Science & Technology, Mbarara, Uganda. 3. Department of Epidemiology, Fielding School of Public Health, UCLA, Los Angeles, CA, USA. 4. The Dartmouth Institute, The Department of Biomedical Data Science, Geisel School of Medicine, USA. 5. Department of Human and Organizational Development Peabody College, Vanderbilt University, PMB 90, 230 Appleton Place, Nashville, TN, 37203, USA; Vanderbilt Institute of Global Health, Vanderbilt University Medical Center, Nashville, TN, USA. 6. Oregon Health & Science University-Portland State University School of Public Health, Portland, OR, USA. 7. Department of Sociology, Yale Institute for Network Science, P.O. Box 208263, New Haven, CT, 06520-8263, USA. 8. Mbarara University of Science & Technology, Mbarara, Uganda; Harvard Medical School, Boston, MA, USA; Chester M. Pierce, MD Division of Global Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
Abstract
RATIONALE: HIV-related stigma profoundly affects the physical and social wellbeing of people living with HIV, as well as the community's engagement with testing, treatment, and prevention. Based on theories of stigma elaborating how it arises from the relationships between the stigmatized and the stigmatizer as well as within the general community, we hypothesized that social networks can shape HIV-related stigma. OBJECTIVE: To estimate social network correlates of HIV-related stigma. METHODS: During 2011-2012, we collected complete social network data from a community of 1669 adults ("egos") in Mbarara, Uganda using six culturally-adapted name generators to elicit different types of social ties ("alters"). We measured HIV-related stigma using the 9-item AIDS-Related Stigma Scale. HIV serostatus was based on self-report. We fitted linear regression models that account for network autocorrelation to estimate the association between egos' HIV-related stigma, alters' HIV-related stigma and alters' self-reported HIV serostatus, while adjusting for egos' HIV serostatus, network centrality, village size, perceived HIV prevalence, and sociodemographic characteristics. RESULTS: The average AIDS-Related Stigma Score was 0.79 (Standard Deviation = 0.50). In the population 116 (7%) egos reported being HIV-positive, and 757 (46%) reported an HIV-positive alter. In the multivariable model, we found that egos' own HIV-related stigma was positively correlated with their alters' average stigma score (b=0.53; 95% confidence interval [CI] 0.42-0.63) and negatively correlated with having one or more HIV-positive alters (b=-0.05; 95% CI -0.10 to -0.003). CONCLUSION: Stigma-reduction interventions should be targeted not only at the level of the individual but also at the level of the network. Directed and meaningful contact with people living with HIV may also reduce HIV-related stigma. Published by Elsevier Ltd.
RATIONALE: HIV-related stigma profoundly affects the physical and social wellbeing of people living with HIV, as well as the community's engagement with testing, treatment, and prevention. Based on theories of stigma elaborating how it arises from the relationships between the stigmatized and the stigmatizer as well as within the general community, we hypothesized that social networks can shape HIV-related stigma. OBJECTIVE: To estimate social network correlates of HIV-related stigma. METHODS: During 2011-2012, we collected complete social network data from a community of 1669 adults ("egos") in Mbarara, Uganda using six culturally-adapted name generators to elicit different types of social ties ("alters"). We measured HIV-related stigma using the 9-item AIDS-Related Stigma Scale. HIV serostatus was based on self-report. We fitted linear regression models that account for network autocorrelation to estimate the association between egos' HIV-related stigma, alters' HIV-related stigma and alters' self-reported HIV serostatus, while adjusting for egos' HIV serostatus, network centrality, village size, perceived HIV prevalence, and sociodemographic characteristics. RESULTS: The average AIDS-Related Stigma Score was 0.79 (Standard Deviation = 0.50). In the population 116 (7%) egos reported being HIV-positive, and 757 (46%) reported an HIV-positive alter. In the multivariable model, we found that egos' own HIV-related stigma was positively correlated with their alters' average stigma score (b=0.53; 95% confidence interval [CI] 0.42-0.63) and negatively correlated with having one or more HIV-positive alters (b=-0.05; 95% CI -0.10 to -0.003). CONCLUSION:Stigma-reduction interventions should be targeted not only at the level of the individual but also at the level of the network. Directed and meaningful contact with people living with HIV may also reduce HIV-related stigma. Published by Elsevier Ltd.
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