Men in Community Correction Programs and Their Female Primary Sex Partners: Latent Class Analysis to Identify the Relationship of Clusters of Drug Use and Sexual Behaviors and HIV Risks
- 7 Downloads
Existing research indicates that justice-involved individuals use a variety of different drugs and polysubstance use is common. Research shows that different typologies of drug users, such as polydrug users versus users of a single drug, have differing types of individual-, structural-, and neighborhood-level risk characteristics. However, little research has been conducted on how different typologies of drug use are associated with HIV risks among individuals in community corrections and their intimate sex partners. This paper examines the different types of drug use typologies among men in community correction programs and their female primary sex partners. We used latent class analysis to identify typologies of drug use among men in community correction programs in New York City and among their female primary sex partners. We also examined the associations between drug use typologies with sexual and drug use behaviors that increase the risk of HIV acquisition. The final analysis included a total of 1167 participants (822 male participants and 345 of their female primary sex partners). Latent class analyses identified three identical typologies of drug use for both men and their female primary sex partners: (1) polydrug use, (2) mild polydrug users with severe alcohol and marijuana use, and (3) alcohol and marijuana users. Men and women who were classified as polydrug users and mild polydrug users, compared to those who were classified as alcohol and marijuana users, tended to be older and non-Hispanic Caucasians. Polydrug users and mild polydrug users were also more likely to have risky sex partners and higher rates of criminal justice involvement. There is a need to provide HIV and drug use treatment and linkage to service and care for men in community correction programs, especially polydrug users. Community correction programs could be the venue to provide better access by reaching out to this high HIV risk key population with increased rates of drug use and multiple sex partners.
KeywordsDrug use Criminal justice HIV Sexual risk behaviors
The authors appreciate the assistance of the Center for Court Innovation and the New York City Department of Probation for supporting the implementation of this study, and want to particularly thank the men and women who participated in this study.
This study was funded by the National Institute of Drug Abuse (grant R01DA033168). Dr. Davis is supported by the National Institute of Mental Health (T32 grant MH019139 and P30 grant MH043520) and Mr. Marotta is supported by the National Institute of Drug Abuse (T32 grant DA037801).
- 1.Kaeble D, Glaze L, Bureau of Justice Statistics. Correctional Populations in the United States, 2015. In. Washington, D.C.: U.S. Department of Justice; 2016.Google Scholar
- 2.Kaeble D, Bonczar T, Bureau of Justice Statistics. Probation and Parole in the United States, 2015. Washington, D.C.: U.S. Department of Justice; 2017.Google Scholar
- 3.Califano Jr, JA. Behind bars: Substance abuse and America's prison population. New York, NY: National Center on Addiction and Substance Abuse at Columbia University (CASA), January 1998. Available online at http://www.casacolumbia.org/Absolutenm/articlefiles/5745.pdf. Accessed 15 Sept 1999.
- 15.Zhang Z. Drug and alcohol use and related matters among arrestees, 2003. Washington, DC: National Institute of Justice; 2003.Google Scholar
- 16.Arrestee Drug Abuse Monitoring. 2000 arrestee drug abuse monitoring: annual report. Washington, DC: National Institute of Justice; 2003.Google Scholar
- 30.Callaghan R, Brands B, Taylor L, et al. The clinical characteristics of adolescents reporting methamphetamine as their primary drug of choice: an examination of youth admitted to inpatient substance-abuse treatment in northern British Columbia, Canada, 2001–2005. J Adolesc Health. 2007;40:286–9.CrossRefPubMedGoogle Scholar
- 32.Muthén B. Latent variable analysis. The Sage handbook of quantitative methodology for the social sciences. Thousands oaks: SAGE; 2004. p. 345–368.Google Scholar
- 34.Muthén B. Statistical and substantive checking in growth mixture modeling: comment on Bauer and Curran (2003). Washington DC: American Psychological Association; 2003.Google Scholar
- 35.Muthén L, Muthén B. Mplus. The comprehensive modelling program for applied researchers: user’s guide. Los Angeles: Muthén & Muthén; 2015. p. 5.Google Scholar
- 37.New York State Corrections and Community Supervision. Under custody report: profile of under custody population as of January 1, 2016. Albany, NY; Department of Corrections and Community Supervision; 2016.Google Scholar
- 40.White K, Holman M. Marijuana prohibition in California: racial prejudice and selective arrests. Race, Gender Class. 2012;19(3/4):75–92.Google Scholar
- 41.Johnson B, Golub A, Dunlap E, Sifaneck S. An analysis of alternatives to New York City’s current marijuana arrest and detention policy. Policing: Int J Police Strat Manag. 2008;31(2):226–50.Google Scholar