killing the pain: prescription drug abuse and other risky behaviors in rural appalachia jennifer r....
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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
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Annual numbers (in millions) of new nonmedical users of pain relievers aged 12 and older
Source: National Household Survey on Drug Abuse 1970-2000
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Past Year Illicit Drug Dependence or Abuse
Source: National Survey on Drug Use and Health 2002
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Percent increase in number of treatment admissions for narcotic painkillers: 1997 – 2002
Source: Treatment Episode Data Set 1997 - 2002
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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
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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).
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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)
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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
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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
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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 townParticipants recruited via Respondent
Driven Sampling (RDS)24- and 30-month follow-up ongoing
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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)CocaineHeroinMethamphetamine
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Outcomes
HIV, HCV, HSV-2 prevalence and incidence (i.e., seroconversion)
HIV risk behaviorsunprotected sexsharing syringes and other injection-related
paraphernalia
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Data Collection Procedures
Interviewer-administered questionnaireComputer-assisted personal interview
(CAPI) via tablet PCSerologic testing (with pre- and post-test
counseling)HIV (with confirmatory testing)HCVHSV-2
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Baseline Data -Participant Characteristics N=503
n %
Male 286 56.7
Age, median (IQR) 31 (26 ,38)
Caucasian 474 94.2
Employed Full-Time 173 34.4
Lifetime Injection Drug Use 394 78.3
Prevalent HIV 0 0
Prevalent HCV 220 43.7
Prevalent HSV-2 58 11.5
Incident HCV 36 12.7
Incident HSV-2 50 11.2
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Baseline Data – Drug Use
Lifetime Past 30 Days
Alcohol 499 99.2 276 54.9
Methadone (illicit) 476 94.6 306 60.8
Heroin 176 35.0 22 4.4
OxyContin 477 94.8 351 69.8
Oxycodone 482 95.8 364 72.4
Hydrocodone 488 97.0 408 81.3
Benzodiazepines 480 95.5 429 85.3
Methamphetamine 219 43.5 17 3.4
Cocaine 472 93.8 113 22.5
Marijuana 491 97.6 308 61.2
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Baseline Data – Age of Onset
Alcohol
Marijuana
Age 14
Benzodiazepines
Hydrocodone
Age 18
Cocaine
Oxycodone
Age 20Crack
Age 21
OxyContin
Heroin
Methadone
Age 23
IDU
Age 22
Methamphetamine
Age 24
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Drugs Initiated Injection With (n=394 Lifetime IDUs)
n %
OxyContin 190 48.2
Other Rx opiates 53 13.4
TOTAL ALL Rx opiates 243 61.7
Methamphetamine 4 1.0
Cocaine 117 29.7
Heroin 19 4.8
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Baseline Data – IDU Drugs (n=394 Lifetime IDUs)
n %
Rx Opiates 348 88.3
Rx Stimulants 27 6.8
Rx Benzodiazepines 23 5.8
Methamphetamine 39 9.9
Cocaine 271 68.8
Heroin 95 24.1
Speedball (cocaine/OxyContin) 60 15.2
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Baseline Data -Sex Risk
n %
Male Sex Partners, median (IQR) 9 (5, 17.5)
Female Sex Partners, median (IQR) 20 (10, 45)
Sexual Orientation
Heterosexual 459 91.2
Homosexual 9 1.8
Bisexual 34 6.8
Sex Encounters w/o Condom (30 days) 14 (4, 30)
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Baseline Data – Drug Risk
n %
Sharing Syringes (past 6 mo) N=288 92 31.9
Sharing Cottons, Cookers, Water (6 mo) N=288
137 47.6
Daily Injection N=288 102 35.4
Sharing Straws (6 mo) N=503 407 88.9
Overdose (Lifetime) N=503 146 29.0
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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)
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Drug Network
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by
Drug Network by HCV Status
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Results from Ongoing or Published Studies from SNAP
Transition to InjectionHCV PrevalenceMethadone UseOverdose
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Initiation to Injection
48.2% of participants initiated injection with OxyContin®
Young and Havens, Addiction, 2012
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Initiation to Injection
Young and Havens, Addiction, 2012
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Initiation to Injection
Young and Havens, Addiction, 2012
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Hepatitis C
Overall prevalence is 44.1% (54.5% among IDUs)
Incidence is about 10 cases/100 PYIndependent 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
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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
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Overdose
28% experienced 1 or more ODs58% witnessed 1 or more ODsIndividual 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
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Acknowledgements
NIH/NIDA (R01-DA024598)Dr. Carl Leukefeld (BSC), Dr. Carrie
Oser (Sociology) and Dr. Rick Crosby (Health Behavior)
Center on Drug and Alcohol ResearchDepartment of Behavioral Science