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Killing the Pain:  Prescription Drug Abuse and Other Risky Behaviors in Rural Appalachia

Killing the Pain:  Prescription Drug Abuse and Other Risky Behaviors in Rural Appalachia. Jennifer R. Havens, PhD, MPH Department of Behavioral Science Center on Drug and Alcohol Research University of Kentucky College of Medicine.

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Killing the Pain:  Prescription Drug Abuse and Other Risky Behaviors in Rural Appalachia

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  1. Killing the Pain: Prescription Drug Abuse and Other Risky Behaviorsin Rural Appalachia Jennifer R. Havens, PhD, MPH Department of Behavioral Science Center on Drug and Alcohol Research University of Kentucky College of Medicine

  2. Annual numbers (in millions) of new nonmedical users of pain relievers aged 12 and older Source: National Household Survey on Drug Abuse 1970-2000

  3. Past Year Illicit Drug Dependence or Abuse Source: National Survey on Drug Use and Health 2002

  4. Percent increase in number of treatment admissions for narcotic painkillers: 1997 – 2002 Source: Treatment Episode Data Set 1997 - 2002

  5. BackgroundRural Substance Abuse • Differing trends – rates of prescription drug opiate use and methamphetamine higher than urban areas (Havens et al., Am J Drug Alc Abuse, 2007; Havens et al., Am J Drug Alc Abuse, 2009) • Differing drugs of abuse may be due to lack of availability of drugs such as heroin in rural areas

  6. Injection Drug Use among Rural Drug Users • Previous research: IDU rare among rural drug users in Appalachian Kentucky (Leukefeld et al., Substance Use and Misuse, 1997) • Recent research suggested a much higher prevalence of IDU among Appalachian drug users (>40%) (Havens et al., Drug and Alcohol Dependence, 2007).

  7. IDU among Appalachian Drug Users • Majority of rural IDUs reported injecting OxyContin® and other prescription drugs NOT designed for injection • Fewer than 10% had ever injected heroin and/or cocaine • Self-reported hepatitis C infection significantly higher among the IDUs versus non-IDUs (p<0.001) (Havens et al., Drug and Alcohol Dependence, 2007)

  8. Social Networks and HIV Risk among Rural Drug Users • Overall goal of the study is to determine the prevalence and incidence of HIV, hepatitis C and herpes simplex-2 virus as well as to examine both individual and social network-related risk factors for HIV and other infectious diseases among rural drug users

  9. Specific Aims • To determine prevalence and incidence of HIV, hepatitis C (HCV) and herpes simplex-2 virus (HSV-2) among rural IDUs and non-IDUs • Characterize risk for HIV and other infectious diseases among rural injection and non-injection drug users in the context of both individual-level and network-level risk

  10. Participants • 500 rural out-of-treatment injection and non-injection drug users recruited and followed at 6-, 12-, and 18-months post-baseline • Storefront location in rural town • Participants recruited via Respondent Driven Sampling (RDS) • 24- and 30-month follow-up ongoing

  11. Eligibility Criteria • Age 18+ • English-speaking • IDU (initial seeds) • Use of at least 1 of the following drugs in prior 6 mo: • Rx Opiates (illicit use) • Cocaine • Heroin • Methamphetamine

  12. Outcomes • HIV, HCV, HSV-2 prevalence and incidence (i.e., seroconversion) • HIV risk behaviors • unprotected sex • sharing syringes and other injection-related paraphernalia

  13. Data Collection Procedures • Interviewer-administered questionnaire • Computer-assisted personal interview (CAPI) via tablet PC • Serologic testing (with pre- and post-test counseling) • HIV (with confirmatory testing) • HCV • HSV-2

  14. Baseline Data -Participant Characteristics N=503

  15. Baseline Data – Drug Use

  16. Baseline Data – Age of Onset • Alcohol • Marijuana • Age 14 • Benzodiazepines • Hydrocodone • Age 18 • Crack • Age 21 • IDU • Age 22 • Methamphetamine • Age 24 • Cocaine • Oxycodone • Age 20 • OxyContin • Heroin • Methadone • Age 23

  17. Drugs Initiated Injection With (n=394 Lifetime IDUs)

  18. Baseline Data – IDU Drugs (n=394 Lifetime IDUs)

  19. Baseline Data -Sex Risk

  20. Baseline Data – Drug Risk

  21. Baseline Data – Social Networks • Support Network Members, median (IQR) • 2 (1, 3) • Drug Network Members, median (IQR) • 4 (2, 9) • Sex Network Members, median (IQR) • 2 (1, 5)

  22. Drug Network

  23. by Drug Network by HCV Status

  24. Results from Ongoing or Published Studies from SNAP • Transition to Injection • HCV Prevalence • Methadone Use • Overdose

  25. Initiation to Injection • 48.2% of participants initiated injection with OxyContin® Young and Havens, Addiction, 2012

  26. Initiation to Injection Young and Havens, Addiction, 2012

  27. Initiation to Injection Young and Havens, Addiction, 2012

  28. Hepatitis C • Overall prevalence is 44.1% (54.5% among IDUs) • Incidence is about 10 cases/100 PY • Independent associations with HCV: • Syringe sharing (aOR: 2.04, 95% CI: 1.20, 3.45) • Years IDU (aOR: 1.04, 95% CI: 1.01, 1.07) • Injecting Rx opiates (aOR: 2.37, 95% CI: 1.21, 4.63) • Injecting Cocaine (aOR: 2.24, 95% CI: 1.41, 3.54) Havens et al., American Journal of Public Health, 2013

  29. Methadone Use • 94.6% of cohort report lifetime illicit methadone use • Methadone NOT diverted from treatment programs • Factors associated with high frequency methadone use: older age, less exposure to drug tx, not having Rx for physical problem, not using OxyContin concurrently, fewer lifetime arrests and experiencing recent drug problems Hall, Leukefeld and Havens, under review, 2013

  30. Overdose • 28% experienced 1 or more ODs • 58% witnessed 1 or more ODs • Individual factors associated with OD: ever in drug tx, injection of Rx opiates, PTSD, ASPD • Network factors associated with OD: having additional support network members Havens et al., Drug and Alcohol Dependence, 2011

  31. Acknowledgements • NIH/NIDA (R01-DA024598) • Dr. Carl Leukefeld (BSC), Dr. Carrie Oser (Sociology) and Dr. Rick Crosby (Health Behavior) • Center on Drug and Alcohol Research • Department of Behavioral Science

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