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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
J Addict Dis. Author manuscript; available in PMC 2010 July 1.
Published in final edited form as:
J Addict Dis. 2009 July; 28(3): 232–242.
doi:  10.1080/10550880903028452
PMCID: PMC2824904
NIHMSID: NIHMS124422

Non-medical Use of Prescription Analgesics: A Three-Year National Longitudinal Study

Carol J. Boyd, Ph.D., MSN,* Christian J. Teter, PharmD, BCPP, Brady T. West, M.A., Michele Morales, Ph.D., MSW, and Sean Esteban McCabe, Ph.D., MSW

Abstract

This secondary analysis examined the non-medical use of prescription analgesics and determined its relationship to: 1) continued non-medical use and 2) substance use disorders three years later. Prospective data were collected using the Alcohol Use Disorders and Associated Disabilities Interview Schedule: DSM-IV Version (AUDADIS-DSM-IV). A nationally representative sample (n=34,653) of U.S. adults 18 years or older was interviewed at Wave 1 (2001-2002) and re-interviewed at Wave 2 (2004-2005). Multivariate logistic regression analyses indicated younger age (18 to 24 years) and non-medical use at Wave 1 was associated with higher odds of a general substance or opioid abuse/dependence disorder at Wave 2 (AOR=3.42, 95% CI = 1.45, 8.07); however, most respondents who engaged in non-medical use will cease using three years later although non-medical use is associated with higher prevalence of a future substance use disorder.

Keywords: Prescription, pain medication, Non-medical, DSM-IV, Abuse, Dependence, Opioid, Epidemiology

INTRODUCTION

In the past decade, several national surveys1,2 have demonstrated increased prevalence in the non-medical use of prescription analgesics, yet despite this acknowledged increase, relatively little is known about changes in non-medical use over time. Most of the national studies, including the National Survey of Drug Use and Health1 and Monitoring the Future2, predominantly rely on cross-sectional study designs that provide few insights into changes in drug use status such as the proportion of non-medical users who maintain or cease the behavior over time.

National cross-sectional studies indicate that annual non-medical use and abuse of, and dependence on, prescription analgesics or prescription opioids is most prevalent among individuals 18 to 24 years old.1,2 Approximately 10-25% of individuals who engaged in past-year non-medical use of prescription analgesics or prescription opioids met the criteria for abuse or dependence,3-6 and among those who retrospectively reported lifetime non-medical use of prescription analgesics, 23.8% progressed to prescription opioid abuse and 7.2% developed prescription opioid dependence during their lifetimes.7 Using retrospective data from the first wave of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), McCabe and colleagues found evidence that younger initiators of non-medical use of prescription analgesics were at greater risk for developing prescription opioid abuse or dependence.7 Drawing on a nationally representative sample of adults using Wave 1 data, McCabe et al.7 demonstrated that older age at the time of first non-medical use reduced the odds of developing any lifetime diagnosis of prescription medication abuse or dependence; however, conclusions were constrained by the biases inherent in retrospective recall data.

Few prospective studies have examined the probability of continued use of non-medical use or the probability of developing a substance use disorder after initiating non-medical use of prescription analgesics. At the time of McCabe and colleagues study,7 there was only one wave of NESARC data available. In 2008, a second wave of the NESARC became available, and the resulting NESARC database includes two waves of interviews that were conducted approximately three years apart. These prospective data provide an opportunity to assess the probability of non-medical users of prescription analgesics at Wave 1 developing prescription opioid use disorders or other substance use disorders at Wave 2.

Statement of Purpose and Research Questions

The purpose of this secondary analysis of NESARC data was to determine the prevalence of non-medical use of prescription analgesics at Wave 1 and whether this non-medical use at Wave 1 predicts continued non-medical use or substance use disorders at Wave 2. We were interested in different status groups of non-medical users: former and current users (with and without abuse and dependence diagnoses) at Wave 1 and whether non-medical use status predicted the development of prescription opioid or substance use disorders at Wave 2; we were also interested in the role a respondent's age might play in the relationship.

Research questions included: What is the association between no history of non-medical use of prescription analgesics, former non-medical use, or current non-medical use at Wave 1 and current non-medical use of prescription analgesics at Wave 2? What is the association between no history of non-medical use of prescription analgesics, former non-medical use, or current non-medical use at Wave 1 and a diagnosis of prescription opioid or other substance abuse or dependence at Wave 2? Does a younger age at Wave 1 predict prescription opioid or other substance abuse or dependence at Wave 2?

METHODS

Data for this secondary analysis comes from the 2001-2002 and 2004-2005 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). The NESARC funded by NIAAA and NIDA, uses a prospective design with a nationally representative sample; the target population for the NESARC is the non-institutionalized U.S. population of civilians ages 18 and older. NESARC data come from interviews conducted in respondents' households. The United States Census Bureau and the United States Office of Budget and Management approved the NESARC research protocol and the University of Michigan Institutional Review Board approved the current study. The authors received NIDA funding for this secondary analysis of the NESARC data. We use the term “prescription analgesics” because this is the term that is most consistent with the questions asked of respondents and thus, our term is consistent with the measure.

Sample

Stratification and clustering of the target population are incorporated in the NESARC study design. Sampling weights were computed for Wave 2 respondents to offset unequal probabilities of selection, differential non-response, and post-stratification of the population. The sample for this study included 34,653 respondents. The overall response rate at Wave 1 (2001-2002) was 81% and 86.7% at Wave 2 (2004-2005) for an overall response rate of 70.2%. Sampling weights were calculated in order to establish that the subsample of respondents re-interviewed at Wave 2 was representative of the original nationally representative sample at Wave 1; after applying the sampling weights, the sample represented a population that can be described as follows: 52% female, 71% White, 12% Hispanic, 11% African American, 4% Asian, and 2% Native American or other racial groups. Thirteen percent of the sample was 18 to 24 years of age and 87% was 25 years of age or older.

Measures

The NESARC includes questions about mood, anxiety, and alcohol and other drug use as well as assessments of substance use disorders. For many of the substance use assessment measures, validity and reliability have been established.8-15

Non-medical use of prescription analgesics was assessed for the scheduled drug class that includes analgesics with abuse potential such as Darvon®, Percodan®, Dilaudid®, Demerol® and products containing codeine (OxyContin® was added at Wave 2). Respondents were asked about non-medical use of prescription analgesics that were not prescribed to them by a doctor or used in a manner not intended by the prescribing clinician (e.g., more often than prescribed, longer than prescribed, or for a reason other than prescribed, such as to get high). In 2004-2005, three analgesics were added to the Wave 2 question, and unfortunately, two of the added medications were not opioid analgesics (Celebrex® and Vioxx®). Although with Wave 1 data, we can describe respondents (who endorse this question) as “non-medical users of prescription opioids”, for Wave 2, we must limit ourselves to the more general term, “non-medical use of prescription analgesics” since a respondent could endorse the question by using a non-steroidal anti-inflammatory medication (NSAID), never having used a scheduled pain medication (opioid). The timeframes for these questions included lifetime, since last interview and annual (past 12 months) for each drug. A more comprehensive list of specific prescription analgesics is available elsewhere.16

Substance use and prescription opioid use disorders The NESARC included the NIAAA Alcohol Use Disorder and Associated Disabilities Interview Schedule-DSM-IV Version (AUDADIS-IV), a fully structured diagnostic interview. The AUDADIS-IV contains symptom questions that operationalize DSM-IV criteria for drug and alcohol use disorders, including diagnoses for opioid abuse and dependence. Drug-specific diagnoses were made for prescription analgesics as well as for alcohol and a combination of amphetamines, cocaine, inhalants, heroin and marijuana. An AUDADIS-IV diagnosis of prescription opioid abuse required: 1) the absence of an AUDADIS-IV diagnosis of prescription opioid dependence and 2) at least one positive response to four abuse criteria. A lifetime AUDADIS-IV diagnosis of prescription opioid dependence was defined as an affirmative response to at least 3 of the 7 dependence criteria. The test-retest reliability coefficients (kappas) associated with AUDADIS-IV diagnoses of substance use disorders involving prescription medications ranged from κ = 0.69 to 0.96 and the validity of the AUDADIS-IV has been established.8-12,17-20 Drug use status variables were created for lifetime non-medical users of prescription analgesics at Wave 1 (e.g. former use, former abuse only, former dependence, past-year use, etc.). Binary outcome variables using Wave 2 data were created for abuse and dependence disorders that included marijuana, hallucinogens, cocaine, inhalants, heroin, amphetamines, analgesics, tranquilizers and sedatives.

Non-medical use of prescription analgesics status was defined according to the following categories developed from Wave 1 responses to the questions about non-medical use of prescription analgesics:

  1. Lifetime non-user of prescription analgesics.
  2. Former use: Engaged in lifetime non-medical use of prescription analgesics but reported no use in the past 12 months.
  3. Current use: Engaged in non-medical use of prescription analgesics in the past 12 months.
  4. Former abuse: Engaged in lifetime non-medical use of prescription analgesics and met lifetime abuse criteria but did not engage in non-medical use in past 12 months.
  5. Current abuse: Engaged in annual non-medical use of prescription analgesics and met abuse criteria in the past 12 months.
  6. Former dependence: Engaged in lifetime non-medical use of prescription analgesics and met lifetime dependence criteria but did not engage in non-medical use in past 12 months.
  7. Current dependence: Engaged in annual non-medical use of prescription analgesics and met dependence criteria in the past 12 months.

Data Analysis

All statistical analyses of the NESARC data performed in this paper were design-based, in that they 1) generated weighted, nationally representative estimates of finite population parameters of interest (e.g., prevalence rates) using the sampling weights assigned to the Wave 2 respondents, and 2) used the Taylor Series Linearization method to compute variance estimates for the weighted estimates that reflected sampling variance in the estimates due to the stratification and clustering (i.e., complex, multistage design) of the NESARC sample. Using methods appropriate for subpopulation analyses of complex sample survey data,21 Wave 2 prevalence rates were estimated separately for males and females, in distinct subclasses defined by age and prescription analgesic use status at Wave 1. In addition, Wave 2 prevalence rates of non-medical use of prescription analgesics, diagnoses of opioid abuse or dependence, diagnoses of any substance abuse or dependence since the Wave 1 interview were estimated for each of the seven distinct subclasses of respondents defined by Wave 1 prescription analgesic use status. Finally, multivariate logistic regression models were fitted to binary Wave 2 outcomes indicating 1) no non-medical use of prescription analgesics since the last interview, 2) any prescription opioid use disorder since the last interview, and 3) any drug abuse or dependence since the last interview. Wave 1 predictors included in each of the three models were age, sex, race, diagnosis of lifetime alcohol use disorder, diagnosis of lifetime mood disorder, diagnosis of any lifetime anxiety disorder, any lifetime illicit drug use, and any other lifetime non-medical use of prescription drugs. All study variables were computed and managed using the SAS software (Version 9.1.3), and all analyses were performed using the SUDAAN software (Version 9.0.1) for analysis of survey data, as recommended by NESARC staff.

RESULTS

Based on the NESARC data, an estimated 4.8% (SE = 0.2) of U.S. adults were lifetime non-medical users of prescription analgesics at Wave 1 (2001-2002) with an estimated mean age at onset of 25.2 years. Seventy-nine percent of males and 85% of females who engaged in past-year non-medical use of prescription analgesics at Wave 1 no longer reported past-year non-medical use at Wave 2. For males, approximately 21% of those who engaged in past-year non-medical use at Wave 1 were doing the same at Wave 2; for females, approximately 15% of those who engaged in past-year non-medical use at Wave 1 were doing the same at Wave 2 (see Tables Tables11 and and2).2). The estimated percentages of males and females who reported past-year non-medical use of prescription analgesics at Wave 1 and met the criteria for prescription opioid use disorder at Wave 2 were 8.3% and 5.9%, respectively. Any substance use disorder at Wave 2 was identified in 46.6% of males and 30.4% of females who reported past-year non-medical use of analgesics at Wave 1, versus only 14.3% of males and 5.4% of females with no lifetime non-medical use of analgesics at Wave 1.

Table 1
Males: Prevalence estimates of non-medical use of prescription pain medications and substance use disorders over time
Table 2
Females: Prevalence estimates of non-medical use of prescription pain medications and substance use disorders over time

Prevalence estimates of non-medical use of prescription analgesics and substance use disorders over time

Separate prevalence estimates for males and females were computed, allowing for the examination of bivariate associations between respondents' age group and non-medical use of prescription analgesics at Wave 1 and non-medical use and prescription opioid and substance use disorders at Wave 2 (see Tables Tables11 and and2).2). Current and former non-medical use of prescription analgesics at Wave 1 were generally associated with higher rates of prescription opioid use disorder and substance use disorder at Wave 2 for both males and females. However, the age of the respondent at Wave 1 was associated with different substance use disorder estimates at Wave 2. For instance, 18% of younger females (18 to 24 years) who reported past-year non-medical use of prescription analgesics at Wave 1 reported the same behavior at Wave 2; 3% of past-year non-medical users at Wave 1 reported a past-year prescription opioid use disorder and 38% reported any past-year substance use disorder at Wave 2. These estimates are contrasted with older females (55 years and older) where only 4% of those who engaged in past-year non-medical use of prescription analgesics at Wave 1 continued this behavior at Wave 2; further only 2% had a past-year prescription opioid use disorder and 19% had any past-year substance use disorder at Wave 2. Similar patterns held for males: 27% of younger males (18 to 24 years) who engaged in past-year non-medical use of prescription analgesics at Wave 1 also reported this behavior at Wave 2; 8% of these users developed a past-year prescription opioid use disorder and 50% developed any past-year substance use disorder at Wave 2. These estimates are contrasted with 9% of males 55 years or older who reported past-year non-medical use at Wave 1 and reported the same behavior at Wave 2; zero percent had a past-year prescription opioid use disorder at Wave 2 and only 5% were estimated to have a past-year substance abuse disorder.

We examined the associations between non-medical use of prescription analgesic status at Wave 1 and prevalence estimates for substance use disorders at Wave 2 (see Table 3). As hypothesized, those who had never engaged in non-medical use of prescription analgesics at Wave 1 had very low probabilities of subsequent non-medical use and developing substance use disorders by Wave 2. Only an estimated 2% of those who never engaged in non-medical use of prescription analgesics at Wave 1 also reported non-medical use at Wave 2 (since last interview). Further, only an estimated 0.3% and 0.2% of non-lifetime users at Wave 1 had a prescription opioid abuse or dependence diagnosis at Wave 2, respectively. However, the associations look quite different for those who reported past-year non-medical use of prescription medications at Wave 1. We hypothesized that past-year non-medical use of prescription analgesics at Wave 1 would be strongly associated with non-medical use at Wave 2, but this was not supported by the estimates: only 22.5% of past-year users (without disorders at Wave 1) were estimated to be users at Wave 2, indicating that a majority of users who had not developed disorders had stopped their non-medical use by Wave 2. For those individuals who were prescription opioid dependent at Wave 1 (n = 33), the estimated prevalence of prescription opioid dependence was 12.5% at Wave 2 while the prevalence of reporting any substance dependence was 59.8% at Wave 2.

Table 3
Prevalence estimates of non-medical use of prescription pain medications and substance use disorders since last interview

Multivariate results

Covariates measuring age, sex, race, lifetime alcohol use disorder and lifetime mood and anxiety disorders were considered as predictors of two forms of substance abuse/dependence disorders – opioid abuse/dependence and general substance abuse/dependence for the subpopulation of individuals reporting past-year non-medical use at Wave 1. When treating the referent age group as ≥ 45 years, these multivariate analyses indicated that younger age at Wave 1 (18 to 24 years) was associated with significantly higher odds of having a general substance use disorder at Wave 2 (AOR=3.42, 95% CI = 1.45, 8.07), but was not associated with prescription opioid use disorders at Wave 2 (AOR=2.12, 95% CI = 0.47, 9.64). The odds of having a disorder at Wave 2 differed for the next age group (25 to 34 years) as well (again using the referent age group as > 45 years). For instance, being in the 25 to 34 year-old group at Wave 1 was associated with significantly higher odds of having a prescription opioid use disorder at Wave 2 (AOR=5.09, 95% CI = 1.04, 24.9) but not with the odds of having a general substance abuse or dependence, The older age group at Wave 1 (35 to 44 years old) was not at higher odds of developing either substance use disorder at Wave 2 when compared to the referent group.

DISCUSSION

The purpose of this secondary analysis of data collected in Waves 1 and 2 of the NESARC was to examine the relationships between non-medical use of prescription analgesics at Wave 1 and the development of substance use disorders at Wave 2. In this study, we found that approximately 5% of the U.S. adult population was lifetime non-medical users of prescription analgesics at Wave 1, an estimate considerably lower than the NSDUH1 estimate of 12.8% for those 18 years and older in 2002. The discrepancies between the two estimates are most likely related to the use of different questions and the medications included in the questions.

In earlier work, McCabe et al.7 found that younger first-time non-medical users of prescription analgesics were at greater risk for developing prescription opioid abuse or dependence in their lifetime when compared to older counterparts. We found that the most “at risk” years for non-medical use of prescription analgesics appear to be young adulthood; the estimated mean age at onset of non-medical use of prescription analgesics was approximately 25 years in the NESARC (compared with 24 years in the 2005 NSDUH). In this two-wave secondary analysis, we used a multivariate logistic regression model and determined the odds of developing a substance abuse disorder at Wave 2 as a function of Wave 1 predictors (non-medical use status.)

Of import, 85% of females and 79% of males who engaged in past-year non-medical use of prescription analgesics at Wave 1 did not engage in past-year non-medical use at Wave 2, although 30% of females and 47% of males met criteria for any past-year substance use disorders at Wave 2. These data lend support to the argument that there are different subtypes of non-medical users of prescription analgesics22-23 and that abuse and dependence trajectories may differ by subtypes. Boyd et al.22 and McCabe et al.23 found that the type(s) of motive for non-medical use of prescription analgesics were associated with greater substance abuse problems as indicated by higher Drug Abuse Screening Test, Short Form (DAST-10) scores. Zacny and Lichtor24 suggest that national surveys should include motives for non-medical use of prescription analgesics because the relationship between motives and substance abuse problems is established. Nonetheless, the majority of those who engaged in non-medical use of prescription medications at Wave 1 stopped the behavior by Wave 2 and did not develop abuse or dependence problems.

We found few meaningful gender differences in our analyses. Males were more likely to develop a past-year substance use disorder at Wave 2, but not a prescription opioid use disorder. Females were generally more likely to develop a past-year prescription opioid use disorder at Wave 2. One exception to this pattern was that 19.6% of males between the ages of 35 and 44 who engaged in non-medical use of prescription analgesics at Wave 1 reported a prescription opioid use disorder at Wave 2. This estimate compares with 11% of their female counterparts.

Previous research has shown that non-medical use of prescription medications is most prevalent among adolescents and young adults in the United States2,16,25 and this study was no exception. Regardless of the non-medical use status, young adults between the ages of 18 and 34 years had some of the highest current rates of non-medical use of prescription analgesics at Wave 2. Our analyses indicate that relative to adults with age greater than or equal to 45 years, non-medical use of prescription analgesics in the 18 to 24 age group was associated with a three-fold risk of developing a substance use disorder within a three-year period, while non-medical use in the 25 to 34 age group was associated with five times greater odds of developing a prescription opioid use disorder. Collectively, these findings lend additional support to those who focus on younger age as a risk factor.

Our multivariate analysis provide a mixed picture, with younger adults (ages 18 to 24 years) who engaged in non-medical use of prescription analgesics having higher odds of later developing a general substance use disorder but not specifically a prescription opioid use disorder. This does not appear true for 25 to 34 year olds; this age group appears more likely to develop a prescription opioid use disorder but not a substance use disorder. In this study, when compared to older adults, 35 to 44 year olds were not at higher odds of developing either substance use disorder. Although these group differences warrant further study, our data indicate that for younger adults who engage in non-medical use of prescription analgesics, there is greater risk of developing a substance abuse problems (either general or prescription opioid use disorders) when compared to older adults.

SUMMARY

The findings from the present study extend our knowledge regarding non-medical use of prescription analgesics over time. This investigation is one of the few national and prospective studies to examine lifetime DSM-IV opioid and substance use disorders. Indeed, it cannot be overstated that the inclusion of DSM-IV criteria to assess prescription opioid use disorders in a large, two-wave national sample is a unique strength. The relatively large sample size of the NESARC allowed for the calculation of prevalence estimates for different non-medical use status. And finally, the nationally representative nature of the sample allows for generalization to the civilian non-institutionalized population, 18 years of age and older residing in the United States.

Acknowledging the aforementioned strengths of the NESARC, there are some limitations that must be acknowledged as well. The findings from the NESARC should not be generalized to populations outside of the United States. This study represents a secondary analysis and as such, not all of the questions were ideal for our purposes. Unfortunately the NESARC classifies individuals as current non-medical prescription analgesic users if they used any of a list of prescription analgesics on at least one occasion during the preceding year. This broad criterion encompasses several different behaviors and/or patterns of medication use that are associated with substantially different risk factors and thus, the NESARC fails to distinguish among the different behaviors related to nonmedical use.26 However, this limitation is shared by other national studies that include questions about nonmedical use and are funded by the NIH such as Monitoring the Future (MTF) and National Survey of Drug Use and Health (NSDUH)). Another issue with the NESARC pertains to the underestimation of the non-medical use because some of the most commonly used prescription analgesics were not listed in the Wave 1 or Wave 2 surveys (e.g., Vicodin®).1,2,7 In addition, the list of analgesics for Wave 2 was updated and included two non-steroidal analgesics with little, if any abuse potential (e.g. Celebrex®, and Vioxx®) along with the addition of OxyContin®. These additions at Wave 2 fundamentally changed the question and force researchers using Wave 2 data to constrain their interpretations and not over-reach by speaking exclusively of opioid analgesics or scheduled analgesics. And finally, the sub-samples were relatively small (with large confidence intervals) and risk groups such as the incarcerated, homeless, and transient individuals were not included in the NESARC and this may lead to underestimates of the prevalence of non-medical use of prescription analgesics.

Despite the aforementioned limitations, this secondary analysis provides new insights into the nonmedical use of prescription analgesics. The extent to which non-medical use leads to abuse and dependence has not been well established although this study lends support to the risks of nonmedical use of prescription medications. In the future, prospective studies, designed to examine the long-term risks associated with the non-medical use of prescription analgesics are needed in order to better understand the consequences associated with this form of drug abuse.

Acknowledgements

The NESARC was funded by the National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, with supplemental support from the National Institute of Drug Abuse, National Institutes of Health. The development of this manuscript was supported by research grants DA020899 and DA007267 from the National Institute on Drug Abuse, National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Drug Abuse or the National Institutes of Health.

Contributor Information

Carol J. Boyd, Institute for Research on Women and Gender, Substance Abuse Research Center, School of Nursing The University of Michigan 204 S. State Street Ann Arbor, Michigan 48109-1290.

Christian J. Teter, School of Pharmacy Northeastern University 360 Huntington Ave. Boston, MA 02115.

Brady T. West, Center for Statistical Consultation and Research The University of Michigan 3550 Rackham Building Ann Arbor, MI, USA 48109-1070.

Michele Morales, Health Promotion and Wellness Northwestern University 633 Emerson St. Evanston, IL 60208-4000.

Sean Esteban McCabe, Institute for Research on Women and Gender, Substance Abuse Research Center, The University of Michigan 204 S. State Street Ann Arbor, Michigan 48109-1290.

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