Females experiencing sexual and drug vulnerabilities are at elevated risk for HIV infection among youth who use injection drugs

J Acquir Immune Defic Syndr. 2002 Jul 1;30(3):335-41. doi: 10.1097/00126334-200207010-00010.

Abstract

Objectives: To compare sociodemographic, drug-related, and sexual risk variables between young (13-24 years of age) and older (> or =25 years of age) injection drug users (IDUs); and to determine HIV prevalence and associated risk factors for HIV infection among young IDUs.

Methods: Data were collected through the Vancouver Injection Drug Users Study (VIDUS). To date, over 1400 Vancouver area IDUs have been enrolled and observed during follow-up. Sociodemographic, drug-related, and sexual risk variables were compared between younger and older IDUs using nonparametric methods. Mantel-Haenszel and logistic regression methods were used to compare HIV-positive and HIV-negative female youth.

Results: Younger injectors (N = 232) were more likely to be female; work in the sex trade; report condom use; inject heroin daily; smoke crack cocaine daily; and need help injecting. HIV prevalence at baseline among the youth was 10%. HIV prevalence was associated with female gender; history of sexual abuse; engaging in survival sex; injecting heroin daily; injecting speedballs (a mixture of heroin and cocaine) daily; and having numerous lifetime sexual partners.

Conclusion: Our data show that HIV positivity among young IDUs is concentrated among females engaged in dual sexual and drug-related risk exposure categories. Over half the HIV-positive youth were Aboriginal (a classification used by the federal government in Canada to include native peoples of all ethnic groups). Targeted interventions that take into account sexual and drug risk for young female and Aboriginal peoples are urgently needed.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • American Indian or Alaska Native
  • Female
  • HIV Infections / etiology*
  • Humans
  • Logistic Models
  • Risk
  • Sexual Behavior*
  • Substance Abuse, Intravenous / complications*