Drug use Discrimination Predicts Formation of High-Risk Social Networks: Examining Social Pathways of Discrimination

Abstract

Experiences of discrimination, or social marginalization and ostracism, may lead to the formation of social networks characterized by inequality. For example, those who experience discrimination may be more likely to develop drug use and sexual partnerships with others who are at increased risk for HIV compared to those without experiences of discrimination. This is critical as engaging in risk behaviors with others who are more likely to be HIV positive can increase one’s risk of HIV. We used log-binomial regression models to examine the relationship between drug use, racial and incarceration discrimination with changes in the composition of one’s risk network among 502 persons who use drugs. We examined both absolute and proportional changes with respect to sex partners, drug use partners, and injecting partners, after accounting for individual risk behaviors. At baseline, participants were predominately male (70%), black or Latino (91%), un-married (85%), and used crack (64%). Among those followed-up (67%), having experienced discrimination due to drug use was significantly related to increases in the absolute number of sex networks and drug networks over time. No types of discrimination were related to changes in the proportion of high-risk network members. Discrimination may increase one’s risk of HIV acquisition by leading them to preferentially form risk relationships with higher-risk individuals, thereby perpetuating racial and ethnic inequities in HIV. Future social network studies and behavioral interventions should consider whether social discrimination plays a role in HIV transmission.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2

References

  1. 1.

    Laumann EO, Youm Y. Racial/ethnic group differences in the prevalence of sexually transmitted diseases in the United States: a network explanation. Sex Transm Dis. 1999;26(5):250–61.

    CAS  Article  PubMed  Google Scholar 

  2. 2.

    Raymond HF, McFarland W. Racial mixing and HIV risk among men who have sex with men. AIDS Behav. 2009;13(4):630–7.

    Article  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Bingham TA, Harawa NT, Johnson DF, Secura GM, MacKellar DA, Valleroy LA. The effect of partner characteristics on HIV infection among African American men who have sex with men in the Young Men’s Survey, Los Angeles, 1999–2000. AIDS Educ Prev. 2003;15(1 Suppl A):39–52.

    Article  PubMed  Google Scholar 

  4. 4.

    Harawa NT, Greenland S, Bingham TA, et al. Associations of race/ethnicity with hiv prevalence and HIV-related behaviors among young men who have sex with men in 7 urban centers in the United States. J Acquir Immune Defic Syndr. 2004;35(5):526–36.

    Article  PubMed  Google Scholar 

  5. 5.

    Latkin CA, Kuramoto SJ, Davey-Rothwell MA, Tobin KE. Social norms, social networks, and HIV risk behavior among injection drug users. AIDS Behav. 2009;14(5):1159–68.

    Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Friedman SR, Aral S. Social networks, risk-potential networks, health, and disease. J Urban Health. 2001;78(3):411–8.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Latkin CA, Forman V, Knowlton A, Sherman S. Norms, social networks, and HIV-related risk behaviors among urban disadvantaged drug users. Soc Sci Med. 2003;56(3):465–76.

    Article  PubMed  Google Scholar 

  8. 8.

    Latkin CA, Hua W, Forman VL. The relationship between social network characteristics and exchanging sex for drugs or money among drug users in Baltimore, MD, USA. Int J STD AIDS. 2003;14(11):770–5.

    CAS  Article  PubMed  Google Scholar 

  9. 9.

    Mustanski B, Birkett M, Kuhns LM, Latkin CA, Muth SQ. The role of geographic and network factors in racial disparities in HIV among young men who have sex with men: an egocentric network study. AIDS Behav. 2015;19(6):1037–47.

    Article  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Sullivan PS, Rosenberg ES, Sanchez TH, et al. Explaining racial disparities in HIV incidence in black and white men who have sex with men in Atlanta, GA: a prospective observational cohort study. Ann Epidemiol. 2015;25(6):445–54.

    Article  PubMed  PubMed Central  Google Scholar 

  11. 11.

    McPherson M, Smith-Lovin L, Cook JM. Birds of a feather: homophily in social networks. Annu Rev Sociol. 2001;27:415–44.

    Article  Google Scholar 

  12. 12.

    Sharmeen F, Arentze T, Timmermans H. Predicting the evolution of social networks with life cycle events. Transportation (Amst). 2015;42(5):733–51.

    Article  PubMed  PubMed Central  Google Scholar 

  13. 13.

    DiMaggio P, Garip F. How network externalities can exacerbate intergroup inequality. Am J Sociol. 2011;116(6):1887–933.

    Article  Google Scholar 

  14. 14.

    Kadushin C. Social networks and inequality: how facebook contributes to economic (and other) inequality. 2012. https://www.psychologytoday.com/blog/understanding-social-networks/201203/social-networks-and-inequality.

  15. 15.

    Kreek MJ. Extreme marginalization: addiction and other mental health disorders, stigma, and imprisonment. Ann N Y Acad Sci. 2011;1231:65–72.

    Article  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Jones C. Levels of racism: a theoretic framework and a gardener’s tale. Am J Public Health. 2000;90(8):1212–5.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Ahmed AT, Mohammed SA, Williams DR. Racial discrimination & health: pathways & evidence. Indian J Med Res. 2007;126(4):318–27.

    PubMed  Google Scholar 

  18. 18.

    Williams DR, Neighbors HW, Jackson JS. Racial/ethnic discrimination and health: findings from community studies. Am J Public Health. 2003;93(2):200–8.

    Article  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Hallfors DD, Iritani BJ, Miller WC, Bauer DJ. Sexual and drug behavior patterns and HIV and STD racial disparities: the need for new directions. Am J Public Health. 2007;97:125–32.

    Article  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Jones CP. Levels of racism: a theoretic framework and a gardener’s tale. Am J Public Health. 2000;90(8):1212–5.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Link BG, Phelan JC. Conceptualizing stigma. Annu Rev Sociol. 2001;27:363–85.

    Article  Google Scholar 

  22. 22.

    Brondolo E, Brady Ver Halen N, Pencille M, Beatty D, Contrada RJ. Coping with racism: a selective review of the literature and a theoretical and methodological critique. J Behav Med. 2009;32(1):64–88.

    Article  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Rhodes T, Singer M, Bourgois P, Friedman SR, Strathdee SA. The social structural production of HIV risk among injecting drug users. Soc Sci Med. 2005;61(5):1026–44.

    Article  PubMed  Google Scholar 

  24. 24.

    Crawford ND, Ford C, Galea S, Latkin C, Jones KC, Fuller CM. The relationship between perceived discrimination and high-risk social ties among illicit drug users in New York City, 2006–2009. AIDS Behav. 2013;17:419–26.

    Article  PubMed  Google Scholar 

  25. 25.

    Eng PM, Rimm EB, Fitzmaurice G, Kawachi I. Social ties and change in social ties in relation to subsequent total and cause-specific mortality and coronary heart disease incidence in men. Am J Epidemiol. 2002;155(8):700–9.

    Article  PubMed  Google Scholar 

  26. 26.

    Cornwell B, Laumann EO. The health benefits of network growth: new evidence from a national survey of older adults. Soc Sci Med. 2015;125:94–106.

    Article  PubMed  Google Scholar 

  27. 27.

    de la Haye K, Green HD Jr, Pollard MS, Kennedy DP, Tucker JS. Befriending risky peers: factors driving adolescents’ selection of friends with similar marijuana use. J Youth Adolesc. 2015;44(10):1914–28.

    Article  PubMed  Google Scholar 

  28. 28.

    Dingle GA, Stark C, Cruwys T, Best D. Breaking good: breaking ties with social groups may be good for recovery from substance misuse. Br J Soc Psychol. 2015;54(2):236–54.

    Article  PubMed  Google Scholar 

  29. 29.

    Stuber J, Galea S, Ahern J, Blaney S, Fuller C. The association between multiple domains of discrimination and self-assessed health: a multilevel analysis of Latinos and blacks in four low-income New York city neighborhoods. Health Serv Res. 2003;38(6 Pt 2):1735–59.

    Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Young M, Stuber J, Ahern J, Galea S. Interpersonal discrimination and the health of illicit drug users. Am J Drug Alcohol Abus. 2005;31(3):371–91.

    Article  Google Scholar 

  31. 31.

    Rudolph AE, Crawford ND, Latkin C, et al. Subpopulations of illicit drug users reached by targeted street outreach and respondent-driven sampling strategies: implications for research and public health practice. Ann Epidemiol. 2011;21:280–9.

    Article  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Rudolph AE, Crawford ND, Latkin C, et al. Individual, study, and neighborhood level characteristics associated with peer recruitment of young illicit drug users in New York city: optimizing respondent driven sampling. Soc Sci Med. 2011;73:1097–104.

    Article  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Rudolph AE, Young AM, Lewis CF. Assessing the geographic coverage and spatial clustering of illicit drug users recruited through respondent-driven sampling in New York city. J Urban Health. 2015;92(2):352–78.

    Article  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Ford CL, Airhihenbuwa CO. The public health critical race methodology: praxis for antiracism research. Soc Sci Med. 2010;71(8):1390–8.

    Article  PubMed  Google Scholar 

  35. 35.

    Ford CL, Airhihenbuwa CO. Critical race theory, race equity, and public health: toward antiracism praxis. Am J Public Health. 2010;100(Suppl 1):S30–5.

    Article  PubMed  PubMed Central  Google Scholar 

  36. 36.

    Ford CL, Miller WC, Smurzynski M, Leone PA. Key components of a theory-guided HIV prevention outreach model: pre-outreach preparation, community assessment, and a network of key informants. AIDS Educ Prev. 2007;19(2):173–86.

    Article  PubMed  Google Scholar 

  37. 37.

    Rudolph AE, Latkin C, Crawford ND, Jones KC, Fuller CM. Does respondent driven sampling alter the social network composition and health-seeking behaviors of illicit drug users followed prospectively? PLoS ONE. 2011;6(5):e19615.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Anthony JC, Vlahov D, Celentano D, Menon AS, Margolick J, Cohn S. Self-report interview data for a study of HIV-1 infection among intravenous drug users: description of methods and preliminary evidence on validity. J Drug Issues. 1991;21(4):739–57.

    Article  Google Scholar 

  39. 39.

    Vlahov D, Anthony JC, Celentano D, Solomon L, Chowdhury N. Trends of HIV-1 risk reduction among initiates into intravenous drug use 1982–1987. Am J Drug Alcohol Abus. 1991;17(1):39–48.

    CAS  Article  Google Scholar 

  40. 40.

    Lee L, McKenna M, Sharpe T. HIV diagnoses among injection-drug users in states with HIV surveillance–25 states, 1994–2000. MMWR Morb Mortal Wkly Rep. 2003;52(27):634–6.

    Google Scholar 

  41. 41.

    Ahern J, Stuber J, Galea S. Stigma, discrimination and the health of illicit drug users. Drug Alcohol Depend. 2007;88(2–3):188–96.

    Article  PubMed  Google Scholar 

  42. 42.

    Robins LN, Wing J, Wittchen HU, et al. The composite international diagnostic interview. An epidemiologic instrument suitable for use in conjunction with different diagnostic systems and in different cultures. Arch Gen Psychiatry. 1988;45(12):1069–77.

    CAS  Article  PubMed  Google Scholar 

  43. 43.

    Rudolph AE, Crawford ND, Latkin C, et al. Subpopulations of illicit drug users reached by targeted street outreach and respondent-driven sampling strategies: implications for research and public health practice. Ann Epidemiol. 2011;21(4):280–9.

    Article  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Christakis NA, Fowler JH. The spread of obesity in a large social network over 32 years. N Engl J Med. 2007;357(4):370–9.

    CAS  Article  PubMed  Google Scholar 

  45. 45.

    Christakis NA, Fowler JH. The collective dynamics of smoking in a large social network. N Engl J Med. 2008;358(21):2249–58.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Fowler JH, Christakis NA. Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham heart study. BMJ. 2008;337:a2338.

    Article  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Knowlton A, Hua W, Latkin C. Social support among HIV positive injection drug users: implications to integrated intervention for HIV positives. AIDS Behav. 2004;8(4):357–63.

    Article  PubMed  Google Scholar 

  48. 48.

    Ford CL, Daniel M, Earp JA, Kaufman JS, Golin CE, Miller WC. Perceived everyday racism, residential segregation, and HIV testing among patients at a sexually transmitted disease clinic. Am J Public Health. 2009;99(Suppl 1):S137–43.

    Article  PubMed  PubMed Central  Google Scholar 

  49. 49.

    Rothenberg R. Maintenance of endemicity in urban environments: a hypothesis linking risk, network structure and geography. Sex Transm Infect. 2007;83(1):10–5.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Rothenberg R, Muth SQ, Malone S, Potterat JJ, Woodhouse DE. Social and geographic distance in HIV risk. Sex Transm Dis. 2005;32(8):506–12.

    Article  PubMed  Google Scholar 

  51. 51.

    Crawford ND, Borrell L, Ford C, Galea S, Latkin C, Link B, Fuller C. Neighborhood differences in the relationship between discrimination and high-risk social networks among illicit drug users. J Commun Health. 2013;38(2):328–37.

  52. 52.

    Friedman SR, Neaigus A, Des Jarlais DC, et al. Social intervention against AIDS among injecting drug users. Br J Addict. 1992;87(3):393–404.

    CAS  Article  PubMed  Google Scholar 

Download references

Funding

This study was funded by the National Institute on Drug Abuse (R01 DA 019964-01). The authors also thank the Robert Wood Johnson Foundation Health & Society Scholars program for its financial support. We would also like to acknowledge the support of the HIV/AIDS Substance Use Training and Trauma Program. Finally, the authors would like to thank the START staff and participants for their invaluable contributions.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Natalie D. Crawford.

Ethics declarations

Conflict of interest

There are no conflicts of interest to disclose.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional review board of the New York Academy of Medicine and Columbia University Medical Center.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

Appendix 1: The relationship between experiences of discrimination and changes in the absolute number of risk network members over 6, 12 and 18 months among PWUD, NYC 2006–2009

Appendix 1: The relationship between experiences of discrimination and changes in the absolute number of risk network members over 6, 12 and 18 months among PWUD, NYC 2006–2009

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Crawford, N.D., Ford, C., Rudolph, A. et al. Drug use Discrimination Predicts Formation of High-Risk Social Networks: Examining Social Pathways of Discrimination. AIDS Behav 21, 2659–2669 (2017). https://doi.org/10.1007/s10461-016-1639-8

Download citation

Keywords

  • HIV
  • Social networks
  • Discrimination
  • Substance use
  • Racial/ethnic inequities