Identifying Which Place Characteristics are Associated with the Odds of Recent HIV Testing in a Large Sample of People Who Inject Drugs in 19 US Metropolitan Areas


This exploratory analysis investigates relationships of place characteristics to HIV testing among people who inject drugs (PWID). We used CDC’s 2012 National HIV Behavioral Surveillance (NHBS) data among PWID from 19 US metropolitan statistical areas (MSAs); we restricted the analytic sample to PWID self-reporting being HIV negative (N = 7477). Administrative data were analyzed to describe the 1. Sociodemographic Composition; 2. Economic disadvantage; 3. Healthcare Service/Law enforcement; and 4. HIV burden of the ZIP codes, counties, and MSAs where PWID lived. Multilevel models tested associations of place characteristics with HIV testing. Fifty-eight percent of PWID reported past-year testing. MSA-level per capita correctional expenditures were positively associated with recent HIV testing among black PWID, but not white PWID. Higher MSA-level household income and imbalanced sex ratios (more women than men) in the MSA were associated with higher odds of testing. HIV screening for PWID is suboptimal (58%) and needs improvement. Identifying place characteristics associated with testing among PWID can strengthen service allocation and interventions in areas of need to increase access to HIV testing.

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  1. 1.

    The isolation index measures the extent to which minority members are exposed only to one another, and was calculated per Massey and Denton [32]. The isolation index varies from 0 (no isolation) to 100 (complete isolation).


  1. 1.

    National Minority AIDS Council. African Americans, health disparities, and HIV/AIDS: recommendations for confronting the epidemic in Black America. Washington, DC: National Minority AIDS Council; 2006.

  2. 2.

    National Institute on Drug Abuse of the National Institutes of Health. NIH Health Disparities Strategic Plan, Fiscal Years 2009–2013. National Institute on Drug Abuse. Bethesda, MD: NIH; 2009.

  3. 3.

    National Center for HIV/AIDS VH, STD, and TB Prevention at the Centers for Disease Control and Prevention within the U.S. Department of Health and Human Services. Strategic plan: the division of HIV/AIDS prevention 2011 through 2015. Atlanta, GA: CDC; 2011.

  4. 4.

    Centers for Disease Control and Prevention. Revised recommendations for HIV testing of adults, adolescents, and pregnant women in health-care settings. MMWR Recomm Rep. 2006;55:1–17.

  5. 5.

    Davis CS, Burris S, Kraut-Becher J, Lynch KG, Metzger D. Effects of an intensive street-level police intervention on syringe exchange program use in Philadelphia, PA. Am J Public Health. 2005;95:233–6.

  6. 6.

    Heimer R, Grau L, Curtin E, Khoshnood K, Singer M. Assessment of HIV testing of urban injection drug users: implications for expansion of HIV testing and prevention efforts. Am J Public Health. 2007;97:110–6.

  7. 7.

    Riess TH, Kim C, Downing M. Motives for HIV testing among drug users: an analysis of gender differences. AIDS Educ Prev. 2001;13:509–23.

  8. 8.

    Spielberg F, Branson BM, Goldbaum GM, Lockhart D, Kurth A, Celum CL, et al. Overcoming barriers to HIV testing: preferences for new strategies among clients of a needle exchange, a sexually transmitted disease clinic, and sex venues for men who have sex with men. J Acquir Immune Defic Syndr. 2003;32:318–27.

  9. 9.

    Bowles KE, Clark HA, Tai E, Sullivan PS, Song B, Tsang J, et al. Implementing rapid HIV testing in outreach and community settings: results from an advancing HIV prevention demonstration project conducted in seven U.S. cities. Public Health Rep. 2008;123(Suppl 3):78–85.

  10. 10.

    Rhodes T. The ‘risk environment’: a framework for understanding and reducing drug-related harm. Int J Drug Policy. 2002;13:85–94. ISSN 0955-3959.

  11. 11.

    Rhodes T. Risk environments and drug harms: a social science for harm reduction approach. Int J Drug Policy. 2009;20:193–201.

  12. 12.

    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;61:1026–44.

  13. 13.

    Rhodes T, Wagner K, Strathdee SA, Shannon K, Davidson P, Bourgois P. Structural violence and structural vulnerability within the risk environment: theoretical and methodological perspectives for a social epidemiology of HIV risk among injection drug users and sex workers. In: O’Campo P, Dunn JR, editors. Rethinking social epidemiology: Towards a science of change. New York: Springer; 2012. pp. 205–30.

  14. 14.

    Strathdee SA, Hallett TB, Bobrova N, Rhodes T, Booth R, et al. HIV and risk environment for injecting drug users: the past, present, and future. Lancet. 2010;376:268–84.

  15. 15.

    Cooper HLF, Linton S, Kelley ME, Ross Z, Wolfe ME, Chen YT, et al. Racialized risk environments in a large sample of people who inject drugs in the United States. Int J Drug Policy. 2015;27:43–55.

  16. 16.

    Cooper HL, Linton S, Kelley ME, Ross Z, Wolfe ME, Chen YT, et al. Risk environments, race/ethnicity, and HIV status in a large sample of people who inject drugs in the United States. PLoS ONE. 2016;11:e0150410.

  17. 17.

    Cooper HLF, Bossak B, Tempalski B, Friedman SR, Des Jarlais DC. Geographic approaches to quantifying the risk environment: drug-related law enforcement and access to syringe exchange programmes. Int J Drug Policy. 2009;20:217–26.

  18. 18.

    Cooper HLF, Bossak B, Tempalski B, Friedman SR, Des Jarlais DC. Temporal trends in spatial access to pharmacies that sell over-the-counter syringes in New York City health districts: relationship to local racial/ethnic composition and need. J Urban Health. 2009;8:929–45.

  19. 19.

    Friedman SR, Cooper HLF, Tempalski B, Keem M, Friedman R, Flom PL, et al. Relationships of deterrence and law enforcement to drug-related harms among drug injectors in U.S.A. metropolitan areas. AIDS. 2006;20:93–9.

  20. 20.

    Friedman SR, Tempalski B, Brady J, Friedman JJ, Cooper HLF, Flom PL, et al. Predictors of the degree of drug treatment coverage for injection drug users in 94 metropolitan areas in the United States. Int J Drug Policy. 2007;18:475–85.

  21. 21.

    Friedman SR, Tempalski B, Brady JE, West BS, Pouget ER, Williams LD, et al. Income inequality, drug-related arrests, and the health of people who inject drugs: reflections on seventeen years of research. Int J Drug Policy. 2016;32:11–6.

  22. 22.

    Tempalski B, Flom PL, Friedman SR, Des Jarlais DC, Friedman JJ, McKnight C, et al. Social and political factors predicting the presence of syringe exchange programs in 96 Metropolitan areas in the United States. Am J Public Health. 2007;97:437–47.

  23. 23.

    Tempalski B, Cooper H, Friedman SR, Des Jarlais DC, Brady J. Correlates of syringe coverage for heroin injection in 35 large metropolitan areas in the US in which heroin is the dominant injected drug. Int J Drug Policy. 2008;S19:S47–58.

  24. 24.

    Cooper HLF, Des Jarlais DC, Tempalski B, Bossak B, Ross Z, Friedman SR. Drug-related arrest rates and spatial access to syringe exchange programs in New York City health districts: combined effects on the risk of injection-related infections among injectors. Health Place. 2012;18:218–28.

  25. 25.

    Cooper HL, West B, Linton S, Hunter-Jones J, Zlotorzynska M, Stall R, et al. Contextual predictors of injection drug use among black adolescents and adults in US metropolitan areas, 1993–2007. Am J Public Health. 2016;106:517–26.

  26. 26.

    Linton SL, Cooper HL, Kelley ME, Karnes CC, Ross Z, Wolfe ME, et al. Associations of place characteristics with HIV and HCV risk behaviors among racial/ethnic groups of people who inject drugs in the United States. Am J Epidemiol. 2016;26:619–30.

  27. 27.

    Cooper H, Friedman S, Tempalski B, Friedman R, Keem M. Racial/Ethnic disparities in injection drug use in 94 U.S. metropolitan statistical areas in 1998. Am J Epidemiol. 2005;15:326–34.

  28. 28.

    Linton SL, Cooper HLF, Kelley ME, Karnes CC, Ross Z, Wolfe ME, et al. HIV infection among people who inject drugs in the United States: geographically explained variance across racial and ethnic groups. Am J Public Health. 2015;105:2457–65.

  29. 29.

    Centers for Disease Control and Prevention. National HIV Behavioral Surveillance. Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Viral Hepatitis, Sexual Transmitted Diseases and Tuberculosis Prevention. 2017. Accessed June 2017.

  30. 30.

    Broz D, Wejnert C, Pham HT, DiNenno E, Heffelfinger JD, Cribbin M, et al. HIV infection and risk, prevention, and testing behaviors among injecting drug users—National HIV Behavioral Surveillance System, 20 U.S. cities, 2009. MMWR. Surveillance Summaries. 2014;63:1–51.

  31. 31.

    Lansky AA, Abdul-Quader S, et al. Developing an HIV behavioral surveillance system for injecting drug users: the National HIV Behavioral Surveillance System. Public Health Rep. 2007;122(Suppl 1):48–55.

  32. 32.

    Massey D, Denton N. American Apartheid: segregation and the making of the underclass. Cambridge, Massachusetts: Harvard University Press; 1993.

  33. 33.

    Henkel D. Unemployment and substance use: a review of the literature 1990–2010. Curr Drug Abuse Rev. 2011;4:4–27.

  34. 34.

    Tempalski B, Pouget ER, Cleland CM, Brady JE, Cooper HLF, Hall HI, et al. Trends in the population prevalence of people who inject drugs in US metropolitan areas 1992–2007. PLoS ONE. 2013;8:e64789.

  35. 35.

    Kemp PA, Neale J. Employability and problem drug users. Crit Soc Policy. 2005;25:28–46.

  36. 36.

    Salganicoff A, Cubanski J, Ranji U, Neuman T. Health coverage and expenses: impact on older women’s economic well-being. J Women Polit Policy. 2009;30:222–47.

  37. 37.

    Link BG, Phelan JC. Fundamental sources of health inequalities. In: Policy challenges in modern health care. Piscataway, NJ: Rutgers University Press; 2005.

  38. 38.

    Arnold M, Hsu L, Pipkin S, McFarland W, Rutherford GW. Race, place and AIDS: the role of socioeconomic context on racial disparities in treatment and survival in San Francisco. Soc Sci Med. 2009;69:121–8.

  39. 39.

    Cunningham WE, Hays RD, Duan N, Andersen RM, Nakazono TT, Bozzette SA, Shapiro MF. The effect of socioeconomic status on the survival of people receiving care for HIV infection in the United States. J Health Care Poor Underserv. 2005;16:655–76.

  40. 40.

    Joy R, Druyts EF, Brandson EK, Lima VD, Rustad CA, Zhang W, Wood E, Montaner JSG, Hogg RS. Impact of neighborhood-level socioeconomic status on disease progression in a universal health care setting. J Acquir Immune Defic Syndr. 2008;47:500–5.

  41. 41.

    Nikolopoulos GK, Fotiou A, Kanavou E, et al. National income inequality and declining GDP growth rates are associated with increases in HIV diagnoses among people who inject drugs in Europe: a panel data analysis. PLoS ONE. 2015;10:e0122367.

  42. 42.

    Friedman SR, Rossi D, Braine N. Theorizing, “Big Events” as a potential risk environment for drug use, drug-related harm and HIV epidemic outbreaks. Int J Drug Policy. 2009;20:283–91.

  43. 43.

    Kotranski L, Semaan S, Lauby J, Halbert J, Feighan K. Correlates of HIV seropositivity and HIV testing among out-of-treatment drug users. Am J Drug Alcohol Abuse. 1998;24:377–93.

  44. 44.

    Setia MS, Quesnel-Vallee A, Curtis S, Lynch J. Assessing the role of individual and neighbourhood characteristics in HIV testing: evidence from a population based survey. Open AIDS J. 2009;3:46–54.

  45. 45.

    Blankenship KM, Smoyer AB, Bray SJ, Mattocks K. Black-white disparities in HIV/AIDS: the role of drug policy and the corrections system. J Health Care Poor Underserv. 2005;16:140–56.

  46. 46.

    West HC, Sabol WJ, Greenman SJ, Li S. Prisoners in 2009. U.S. Department of Justice, Bureau of Justice Statistics. Washington, DC. December 2010, NCJ 231675. Revised 10.27.2011. Accessed 29 Nov 2016.

  47. 47.

    Maruschak LM, Berzofsky M, Unangst J, Carson EA, Bronson J. Medical Problems of State and Federal Prisoners and Jail Inmates, 2011–12. U.S. Department of Justice, Bureau of Justice Statistics. Washington, DC. February 2015, NCJ 248491. Accessed 1 Dec 2016.

  48. 48.

    Thomas JC, Torrone E. Incarceration as forced migration: effects on selected community health outcomes. Am J Public Health. 2006;96:1762–5.

  49. 49.

    Seth P, Figueroa A, Wang G, Reid L, Belcher L. HIV testing, HIV positivity, and linkage and referral services in correctional facilities in the United States, 2009–2013. Sex Transm Dis. 2015;42:643–9.

  50. 50.

    Zack B. Correctional health and the HIV stages of care. J Correct Health Care. 2013;19:229–30.

  51. 51.

    Milloy MJ, Montaner JSG, Wood E. Incarceration of people living with HIV/AIDS: implications for treatment-as-prevention. Curr HIV/AIDS Rep. 2014;11:308–16.

  52. 52.

    Dwyer M, Fish DG, Gallucci AV, Walker SJ. HIV Care in Correctional Settings. In: Guide for HIV/AIDS clinical care—2014 Edition. Rockville, MD: U.S. Department of Health and Human Services; 2014.

  53. 53.

    Green TC, Pouget ER, Harrington M, Taxman FS, Rhodes AG, OʼConnell D, et al. Limiting options: sex ratios, incarceration rates, and sexual risk behavior among people on probation and parole. Sex Transm Dis. 2012;39:424–30.

  54. 54.

    Pouget ER, Kershaw TS, Niccolai LM, Ickovics JR, Blankenship KM. Associations of sex ratios and male incarceration rates with multiple opposite-sex partners: potential social determinants of HIV/STI transmission. Public Health Rep. 2010;S125:S70–80.

  55. 55.

    Newsome V, Airhihenbuwa CO. Gender ratio imbalance effects on HIV risk behaviors in African American women. Health Promot Pract. 2013;14:459–63.

  56. 56.

    Paivinen H, Bade S. Voice: challenging the stigma of addiction; a nursing perspective. Int J Drug Policy. 2008;19:214–9.

  57. 57.

    Denning P. Rethinking the treatment of dual disorders. In: Marlatt A, editor. Harm reduction: pragmatic strategies for managing high risk behaviors. 2d ed. New York: Guilford Press; 2012.

  58. 58.

    Denning P. Harm reduction therapy with families and friends of people with drug problems. J Clin Psychol. 2010;66:164–74.

  59. 59.

    Little J, Franskoviak P. We’re glad you came: harm reduction therapy in community settings. J Clin Psychol. 2010;66:175–88.

  60. 60.

    Marlatt GA, Larimer ME, Witkiewitz K, editors. Harm reduction: pragmatic strategies for managing high risk behaviors. New York: Guilford; 2012.

  61. 61.

    Springer E. Effective AIDS prevention with active drug users: the harm reduction model. J Subst Abuse Treat. 1991;4:141–57.

  62. 62.

    Shrestha RK, Sansom SL, Kimbrough L, Hutchinson AB, Daltry D, et al. Cost-effectiveness of using social networks to identify undiagnosed HIV infection among minority populations. J Public Health Manag Pract. 2010;16:457–64.

  63. 63.

    World Health Organization. Service delivery approaches to HIV testing and counselling (HTC): a strategic policy framework. 2012. Accessed 27 July 2017.

  64. 64.

    Bungay V, Kolar K, Thindal S, Remple VP, Johnston CL, et al. Community-based HIV and STI prevention in women working in indoor sex markets. Health Promot. 2013;14:247–55.

  65. 65.

    Stein R, Green K, Bell K, Toledo CA, Uhl G, et al. Provision of HIV counseling and testing services at five community-based organizations among young men of color who have sex with men. AIDS Behav. 2011;15:743–50.

  66. 66.

    Shrestha RK, Clark HA, Sansom SL, Song B, Buckendahl H, et al. Cost-effectiveness of finding new HIV diagnoses using rapid HIV testing in community-based organizations. Public Health Rep. 2008;123(Suppl 3):94–100.

  67. 67.

    Schwartlander B, Stover J, Hallett T, Atun R, Avila C, et al. Towards an improved investment approach for an effective response to HIV/AIDS. Lancet. 2011;377:2031–41.

  68. 68.

    Suthar AB, Ford N, Bachanas PJ, Wong VJ, Rajan JS, Saltzman AK, et al. Towards universal voluntary HIV testing and counselling: a systematic review and meta-analysis of community-based approaches. PLoS Med. 2013;10:e1001496.

  69. 69.

    Tempalski B, McQuie H. Drugscapes and the role of place and space in IDU-related HIV risk environments. Invit Comment Int J Drug Policy. 2009;20:4–13.

  70. 70.

    Cooper HLF, Tempalski B. Integrating place into research on drug use, drug users’ health, and drug policy. Special issue on place matters: drug users’ health and health policy. Guest Ed Int J Drug Policy. 2014;5:333–652.

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This research was supported by two Grants from the National Institutes of Health: “Place Characteristics & Disparities in HIV in IDUS: A Multilevel Analysis of NHBS” (DA035101; Cooper, PI) and, “Metropolitan Trajectories of HIV Epidemics and Responses in US Key Populations” (DA037568; Cooper, Friedman, & Stall, PIs). It was also supported by the Centers and Disease Control and Prevention, and the National HIV Behavioral Surveillance System Study Group: Atlanta, GA: Jennifer Taussig, Shacara Johnson, Jeff Todd; Baltimore, MD: Colin Flynn, Danielle German; Boston, MA: Debbie Isenberg, Maura Driscoll, Elizabeth Hurwitz; Chicago, IL: Nikhil Prachand, Nanette Benbow; Dallas, TX: Sharon Melville, Richard Yeager, Jim Dyer, Alicia Novoa; Denver, CO: Mark Thrun, Alia Al-Tayyib; Detroit, MI: Emily Higgins, Eve Mokotoff, Vivian Griffin; Houston, TX: Aaron Sayegh, Jan Risser, Hafeez Rehman; Los Angeles, CA: Trista Bingham, Ekow Kwa Sey; Miami, FL: Lisa Metsch, David Forrest, Dano Beck, Gabriel Cardenas; Nassau-Suffolk, NY: Chris Nemeth, Lou Smith, Carol-Ann Watson; New Orleans, LA: William T. Robinson, DeAnn Gruber, Narquis Barak; New York City, NY: Alan Neaigus, Samuel Jenness, Travis Wendel, Camila Gelpi-Acosta, Holly Hagan; Newark, NJ: Henry Godette, Barbara Bolden, Sally D’Errico; Philadelphia, PA: Kathleen A. Brady, Althea Kirkland, Mark Shpaner; San Diego, CA: Vanessa Miguelino-Keasling, Al Velasco; San Francisco, CA: H. Fisher Raymond; San Juan, PR: Sandra Miranda De Leo´n, Yadira Rolo´n-Colo´n; Seattle, WA: Maria Courogen, Hanne Thiede, Richard Burt; St Louis, MO: Michael Herbert, Yelena Friedberg, Dale Wrigley, Jacob Fisher; Washington, DC: Marie Sansone, Tiffany West-Ojo, Manya Magnus, Irene Kuo; Behavioral Surveillance Team. We also thank the men and women who participated in NHBS and the staff at all NHBS sites.

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Correspondence to Barbara Tempalski.

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Conflict of interest

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

Ethical Approval

Each author has contributed to the conception and design of the work, the acquisition of data or the analysis of the data in a manner substantial enough to take public responsibility for it. In addition, each author believes that the paper represents valid work and has reviewed the final version of the manuscript and approves it for publication. The findings in this paper have not been published and are not being considered elsewhere for publication.


Emory University’s Institutional Review Board (IRB) approved this study’s protocols; each NHBS site’s IRB approved the NHBS protocol. CDC reviewed and approved the protocol as non-engaged research.

Additional information

National HIV Behavioral Surveillance Study Group author names are listed in Acknowledgements.


Appendix 1

See Table 7.

Table 7 Results of three geographic-scale specific, multivariable multilevel models regressing the odds of past-year HIV testing on individual race/ethnicity and place-based covariates in a sample of self-reported HIV-negative people who inject drugs (PWID; N = 7477), drawn from the 2012 National HIV Behavioral Surveillance. Hierarchical generalized linear models were applied to account for place-based clustering

Appendix 2: Characteristics Among Self-Reported HIV-Negative PWID (N = 7477), Drawn from the 2012 Centers for Disease Control and Prevention’s National HIV Behavioral Surveillance

Description of the Places Where PWID Lived

Sociodemographic composition characteristics: On average, PWID lived in ZIP codes where 26.7% (SD = 23.4) of PWID are white, 38.9% (SD = 31.7) black and 24.8% (SD = 23.9) Latino. MSA-level average black residential isolation index was 44.8% (SD = 20.6) and the average Latino isolation index was 37.3% (SD = 16.8) (Appendix A).

Economic disadvantage characteristics: The mean ZIP code poverty rate for PWID was 28.4% (SD = 11.4); in comparison, the mean county-level poverty rate was 18.8% (SD = 5.2), and the mean MSA-level poverty rate 14.4% (SD = 4.3). On average PWID lived in ZIP codes with a median household income of $40,909.00, in counties where the median income was $54,817.00, and in MSAs where the median income was $66,668.00.

Healthcare Service/Law Enforcement intervention characteristics: In this sample, the mean ZIP code distance (i.e., 3 mile radius) for spatial access to substance use disorder treatment facilities was 1.8 (SD = 2.2). On our dichotomous measures of spatial access to other health services for PWID, we found that 77.4% of PWID lived in ZIP codes where spatial access to HIV testing sites > 0 (i.e., there was ≥ 1 testing site within 3 miles of the ZIP’s centroid), 63% had some spatial access to an MTP, and 48.8% had some spatial access to an SSP.

On average, PWID lived in counties where 22.0% (SD = 8.7) of residents were without health insurance, and where 16.9% (SD = 21.1) of residents lived in medically underserved areas. On average, PWID were located in counties where arrest rates for hard drug possession were 3.6 per 1000 population (SD = 3.1), and in MSAs where arrest rates were 2.8 per 1000 population (SD = 1.4).

On average, PWID lived in MSAs that spent $333.60 per capita on police (SD = 95.1), $97.60 per capita on corrections (SD = 44.7), and $163.60 per capita on health care (SD = 170.0).

HIV burden characteristics: On average, PWID lived in MSAs where annual AIDS-related mortality rates among PWID were 1.37 per 1000 PWID (SD = 1.8) and where annual AIDS diagnoses among PWID were 0.89 per 1000 PWID (SD = 0.9).

See Table 8.

Table 8 Characteristics among self-reported HIV-negative PWID (N = 7477), drawn from the 2012 Centers for Disease Control and Prevention’s National HIV Behavioral Surveillance

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Tempalski, B., Cooper, H.L.F., Kelley, M.E. et al. Identifying Which Place Characteristics are Associated with the Odds of Recent HIV Testing in a Large Sample of People Who Inject Drugs in 19 US Metropolitan Areas. AIDS Behav 23, 318–335 (2019) doi:10.1007/s10461-018-2217-z

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  • Place characteristics
  • HIV testing
  • People who inject drugs
  • National HIV Behavioral Surveillance
  • US metropolitan statistical areas