Pathways between nonmedical opioid use/dependence and psychiatric disorders: Results from the National Epidemiologic Survey on Alcohol and Related Conditions

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Abstract

Background

While nonmedical use of opioids and psychiatric disorders are prevalent in the population, little is known about the temporal ordering between nonmedical opioid use and dependence and psychiatric disorders.

Method

Data were gathered in a face-to-face survey of the United States conducted in the 2001–2002 (NESARC wave 1). Participants were household and group quarters residents aged 18 years and older (n = 43,093). Cox proportional hazards models with time-dependent covariates were used to investigate potential pathways between lifetime nonmedical opioid use/dependence and psychiatric disorders.

Results

Preexisting psychiatric disorders (mood disorders, major depressive disorder, bipolar I disorder, anxiety disorders, panic and generalized anxiety disorders) were associated with an increased risk of nonmedical opioid use, with hazard ratios ranging from 2.2[95% CI = 1.6–3.1] (any anxiety disorder) to 3.1[95% CI = 2.4–2.4] (bipolar I disorder). Preexisting nonmedical opioid use was associated with an increased risk of onset of psychiatric disorders, with hazard ratios ranging from 2.8[95% CI = 2.2–3.6] (generalized anxiety disorder) to 3.6[95% CI = 2.6–4.9] (bipolar I disorder), adjusted for demographics and other illegal drug use. Nonmedical use of opioids led to the development of dependence more often among individuals with preexisting psychiatric disorders, hazard ratios were particularly strong for generalized anxiety disorder (HR = 10.8, 95% CI = 4.9–23.7) and bipolar I disorder (HR = 9.7, 95% CI = 5.4–17.3). Preexisting opioid dependence resulting from nonmedical opioid use was associated with an increased risk of onset of psychiatric disorders, with hazard ratios ranging from 4.9[95% CI = 3.0–7.9] (mood disorders) to 8.5[95% CI = 4.5–16.0] (panic disorder), adjusted for demographics and alcohol and/or other illegal drug dependence.

Conclusions

Our findings support a general vulnerability to nonmedical opioid use and major psychopathologies, as well as evidence for a ‘self-medication’ model for dependence resulting from nonmedical opioid use with bipolar disorder and generalized anxiety disorder.

Introduction

Nationally representative surveys such as the 2006 National Survey on Drug Use and Health (NSDUH) estimate that 13.6% of the U.S. population aged 12 years of age or older have used an opioid for nonmedical purposes (defined as ‘use to get high, using more than prescribed, using it for indications other than those intended by the prescriber, or for other experiences, sensations, or effects beyond the boundaries of approved prescribing procedures or indications as dispensed’ – see Anthony et al., 1994) at least once in their lifetime. The prevalence of nonmedical opioid use has been on the rise over the past few years (from 5.8% in 1998 to 9.8% in 2001) (Substance Abuse and Mental Health Services Administration [SAMHSA], 2007). In addition, an estimated 2.2 million individuals used these substances nonmedically for the first time during 2006, the largest number of recent drug initiates among persons aged 12 and older, representing a substantial increase since 1990 (627,000 initiates) (SAMHSA, 2007). Clinical and epidemiological studies have shown that nonmedical opioid use is associated with several psychiatric disorders (Busto et al., 1998, Chilcoat and Breslau, 1998b, Romach et al., 1999, Reid et al., 2002, Rosenblum et al., 2003, Sullivan et al., 2005, Dowling et al., 2006, Becker et al., 2008, Tetrault et al., 2008). As such, further investigation of pathways between psychiatric disorders and use and dependence on opioids is a public health priority.

Similar to use of many legal and illegal substances, nonmedical opioid use is robustly associated with a broad range of comorbid psychiatric conditions in nationally representative samples. For example, Sullivan et al. (2005) reported that individuals with a variety of psychiatric disorders in a nationally representative sample were more likely than those without psychiatric disorders to report concurrent nonmedical opioid use, with odds ratios ranging from 4.13 [generalized anxiety disorder] to 8.46 [panic disorder]. Several reports from various NSDUH surveys indicate associations between nonmedical opioid use and psychiatric disorder symptom scales and indicators. For instance, Becker et al. (2008) report small but significant associations between nonmedical nonmedical opioid use and panic, depressive, and social phobic/agoraphobic symptoms but not manic, generalized anxiety, or post-traumatic stress symptoms in the 2002–2004 NSDUH surveys. Additionally, Tetrault et al. (2008) and Dowling et al. (2006) documented a strong association between nonmedical opioid use and likely psychiatric disorder as measured with a non-diagnostic scale in the 2002 and 2003 NSDUH surveys. Clinical and community samples generally concur with these national data across a broad range of populations and settings (Busto et al., 1998, Romach et al., 1999, Reid et al., 2002, Rosenblum et al., 2003).

Few studies have explored associations of between DSM-IV dependence resulting from nonmedical opioid use with psychiatric disorder diagnoses. Strong evidence is provided by the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) data; Huang et al. (2006) reported significant associations with every Axis-I and Axis-II disorder measured, and particularly strong relationships with other externalizing disorders such as illegal drug dependence, nicotine dependence, and antisocial personality disorder. While studies on both nonmedical opioid use and dependence have added to our understanding of psychiatric disorders related to the use of opioids, none has attempted to investigate the temporal order of the relationship of psychiatric disorders with nonmedical opioid use and dependence resulting from nonmedical opioid use.

These studies fit into a more broad well-documented area of research indicating that psychiatric disorders occur more frequently in drug using and dependent individuals than among non-drug using individuals (Kessler et al., 2003, Kessler, 2004, Kandel et al., 1997, Regier et al., 1990, Rounsaville et al., 1991, Grant and Harford, 1995, Compton et al., 2007). This established association has motivated interest on the temporal ordering of drug use and psychiatric disorders, as the temporal direction of the association has important implications for prevention and intervention work. For instance, if drug use occurs before psychiatric disorders, then drug use prevention strategies may reduce the associated psychiatric morbidity in addition to the known physical and psychological sequelae. With regard to substance use disorders in general, research has shown that median age of onset for several psychiatric disorders usually occur before the median age of onset for substance use disorders (Kessler et al., 2005). However, preexisting psychiatric disorders also signal increased risk of subsequent substance dependence (Chilcoat and Breslau, 1998a, Chilcoat and Breslau, 1998b, Breslau et al., 2003, Zimmermann et al., 2003), with particularly strong associations documented for PTSD as a risk factor for dependence on prescription drugs (e.g., stimulants, sedatives, tranquilizers, and analgesics).

Three main non-mutually exclusive models to sequentially explain these associations have been postulated. The first is the self-medication model (Conger, 1956, Lader, 1972, Markou et al., 1998), whereby psychiatric disorders cause increases in alcohol and drug use due to anxiolytic or other qualities of substances for the relief of symptoms. The self-medication model is defined by two assumptions: the first, that individuals start using a drug and become dependent on it to alleviate distress and psychiatric symptoms; the second, that there is correspondence between the neurobiological effects of the drug used and the specific symptomotology of the psychiatric disorder (Khantzian, 1997, Khantzian, 2003). The second model is the precipitational model, whereby heavy use of alcohol and drugs may trigger mood or anxiety disorders due to neuroadaptation in brain reward pathways that can lead to subsequent development of psychiatric disorders (McEwen, 2000, Brady and Sinha, 2005). Finally, behavioral genetic studies evidence some support for an underlying shared liability to both drug use/dependence and some psychiatric disorders which may have a heritable component (Kendler et al., 2003, Krueger et al., 2001, Young et al., 2000). Thus, underlying vulnerability or another third factor influencing risk for both drug use/dependence and psychiatric disorders may explain the observed association. While these three models are proposed to explain the general observed association between drug use and psychiatric disorders, specific classes of drugs may exhibit unique pathways toward specific psychiatric disorders (Bierut et al., 1998). These models are not necessarily mutually exclusive. For example, a subset of cases could be explained by self-medication, while another subset results from the precipitational model. In light of secular trends in opioid use and dependence resulting from nonmedical opioid use exhibited in the population, further understanding of the specificity of pathways across psychiatric disorder and drug class remains important to establish in the literature. As such, the goal of this study is to shed light on which model or models may shed light on the association between nonmedical opioid use and dependence and psychiatric disorders by exploring the temporal sequencing of events. The hypotheses will be tested first for nonmedical opioid use, then for dependence that has resulted from nonmedical opioid use. The study's aims are: (1) test whether preexisting mood and anxiety disorders precede the onset of nonmedical opioid use/dependence resulting from nonmedical opioid use (self-medication hypothesis); and (2) examine if preexisting nonmedical opioid use/dependence resulting from nonmedical opioid use precedes the onset of mood or anxiety disorders (precipitational model); keeping in mind that these are not mutually exclusive pathways and that temporality does not imply causality.

Section snippets

Sample and measures

Data were drawn from 2001 to 2002 wave 1 of the National Epidemiologic Survey on Alcohol and Related Conditions, a nationally representative United States survey of civilian non-institutionalized participants aged 18 and older, using a cross-sectional design and in-person interviews. Details of the sampling frame are described elsewhere (Grant et al., 2004, 2003a). The NESARC has a longitudinal component (wave 2, data collected in 2004–2005), which is not yet publicly available. The National

Demographics

There were 1815 lifetime nonmedical opioid users among 43,093 subjects in the 2001–2002 NESARC (representing 4.74% of the general population). Males were more likely to be lifetime nonmedical opioid users than females. Respondents aged 18–29 years old were more likely to be lifetime nonmedical opioid users as compared to those in older age groups (Table 1). African–American and Hispanics were less likely to be lifetime nonmedical opioid users as compared to Whites (Table 1). Respondents with an

Discussion

We found support for pathways in both directions between nonmedical opioid use and onset of psychiatric disorders. All of the psychiatric disorders tested were estimated to be three times as likely to precede nonmedical opioid use (HR ranging from 2.8 to 3.1). Nonmedical use of opioids was linked to subsequent increased risk of mood disorders (MDD and bipolar I disorders) and anxiety disorders (panic and GAD), with hazard ratios ranging from 2.8 to 3.6, even in the presence of preexisting other

Role of funding source

This study was supported by NIDA grant DA020667 (P.I.: Dr. Martins). Katherine Keyes is supported by a fellowship from the National Institute of Mental Health (T32 MH013043-36). Howard Chilcoat is supported as an employee of GlaxoSmithKline.

The NIDA had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.

Contributors

Drs. Martins and Chilcoat wrote the research questions. Dr. Martins and Ms. Zhu undertook the statistical analyses, Dr. Martins wrote the first draft of the manuscript. Drs. Martins and Storr and Ms. Keyes managed the literature searches and summaries of previous related work. All authors revised the manuscript drafts. All authors contributed to and have approved the final manuscript.

Conflict of interest

Dr. Chilcoat is currently employed by GlaxoSmithKline. All other authors declare that they have no conflicts of interest.

Acknowledgements

The data reported herein come from the 2001–2002 NESARC that was funded by the National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, with supplemental support from the National Institute on Drug Abuse, National Institutes of Health. Fieldwork was conducted by the US Bureau of the Census. Data were obtained from the NESARC public use files. We thank Dr. Wesley Eddings from Stata Technical support for assistance in dataset preparation. We thank Ms. Grace Lee, B.S.,

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