Schepis, Ty S. PhD,; Hakes, Jahn K. PhD
The nonmedical use of prescription medications (NUPM) is a significant public health concern, as NUPM-related substance use treatment utilization, emergency department visits, and overdose have all increased in the past 10 years (Manchikanti, 2006; Substance Abuse and Mental Health Services Administration, 2009; 2010). The NUPM is also associated with significant psychosocial consequences, including poorer academic performance, unemployment, and problematic levels of other substance use (Goodwin and Hasin, 2002; McCabe et al., 2006; Schepis and Krishnan-Sarin, 2008). Nonetheless, the medications in question have important therapeutic properties in treating psychiatric conditions (eg, sedatives or tranquilizers) and clinically significant pain (eg, opioids). Thus, prescribing clinicians are faced with the difficult balancing act of limiting the potential for the NUPM while appropriately treating the conditions for which these medications are indicated.
To make informed clinical decisions about best prescribing practices, it is important to establish the prospective consequences resulting from the NUPM. Prospective studies that could illuminate such downstream sequelae, however, are lacking. Recent evidence, building on cross-sectional work indicating a consistent relationship between the NUPM and psychopathology (eg, Huang et al., 2006; Wu et al., 2008), indicates that the NUPM and psychopathology may each influence the course of the other (Martins et al., 2009; Schepis and Hakes, 2011; Schepis and McCabe, 2012).
Both Martins et al. (2009) and Schepis and Hakes (2011) found evidence of dynamic interactions between the NUPM and psychopathology, using data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Martins et al. (2009) used cross-sectional data from wave 1 of the NESARC to examine opioid NUPM. The results indicated that preexisting psychopathology increased likelihood of opioid NUPM and, more strongly, substance dependence from opioid NUPM; conversely, this work found that preexisting opioid NUPM increased the likelihood of psychopathology, with the greatest increases in those with opioid-related dependence.
In the second study, Schepis and Hakes (2011) found that lifetime and past-year NUPM increased the risk for the incidence of depressive disorders, bipolar disorders, anxiety disorders, and non-NUPM substance use disorders (SUDs) in those with no psychiatric history at wave 1. Similarly, lifetime and past-year NUPM predicted incidence of bipolar disorders, anxiety disorders, alcohol use disorders (AUDs), and non-NUPM SUDs in those with history of a different psychiatric disorder. Finally, lifetime and past-year NUPM predicted AUD and recurrence of non-NUPM SUD during the follow-up (Schepis and Hakes, 2011). Finally, work by Schepis and McCabe (2012) found evidence that earlier age of major depressive disorder (MDD) onset was consistently associated with a greater likelihood of lifetime and more recent NUPM. In contrast, earlier age of NUPM onset was only associated with increased MDD likelihood in those with the NUPM initiation before MDD onset. Earlier age of MDD onset was a correlate of the NUPM regardless of whether the NUPM or MDD was experienced first. In all 3 studies (Martins et al., 2009; Schepis and Hakes, 2011; Schepis and McCabe, 2012), the evidence indicated that the NUPM might precipitate the incidence and recurrence of psychopathology, perhaps through neurobiological alterations to stress-related systems secondary to significant engagement in the NUPM (Brady and Sinha, 2005).
That said, previous work only examined the NUPM as a dichotomous risk factor. In other words, those with no lifetime NUPM were compared with those with any history, or in the case of Schepis and Hakes (2011), those with no past-year NUPM were compared with those with any past-year NUPM. Such analyses are important in establishing the presence of a risk factor, but they cannot evaluate whether that risk factor operates in a unitary fashion or whether increases in the NUPM frequency and severity are associated with incremental increases in psychopathology risk in a dose-related fashion. Such an evaluation could reveal which groups of nonmedical users are most vulnerable to the effects of the NUPM on psychopathology and, thus, in need of particular focus from prevention efforts.
AIMS AND SCOPE
This work aims to follow-up on our previous work establishing the NUPM as a prospective risk factor for psychopathology (Schepis and Hakes, 2011) and the work of Martins et al. (2009) by examining relationships between past-year opioid and pooled tranquilizer/sedative NUPM frequency and psychopathology. Because of small cell sizes, analyses of amphetamines were not performed, and the tranquilizer (eg, benzodiazepine) and sedative medications were pooled; pooling of tranquilizer and sedative medications was also done because of the similar pharmacological properties of the medications and overlap between these medication classes in motives for the NUPM (Boyd et al., 2006; Hertz and Knight, 2006). Also, analyses of incidence in those with no psychiatric history were not performed because of insufficient power to examine medication class-specific effects. Fewer than 10 individuals developed a new incidence or recurrence from at least 1 disorder group, which would have been likely to produce results with unstable parameter estimates and an increased likelihood of spurious results.
We hypothesized that increasing past-year NUPM frequency would increase the risk for incidence of psychopathology at wave 2 in a dose-related fashion in those with a history of a different disorder at wave 1. In addition, we hypothesized that recurrence risk for anxiety, AUD, and non-NUPM SUD would increase in a dose-related fashion with increasing past-year and maximum NUPM frequency. We hypothesized that no dose-related effects would be found for depressive or bipolar disorders because our previous work (Schepis and Hakes, 2011) did not find evidence that the NUPM precipitated recurrent episodes of these disorders.
The NESARC is a longitudinal, nationally representative survey funded by the National Institute on Alcohol Abuse and Alcoholism. The survey targets the noninstitutionalized adult population of the United States, with data weighting to create nationally representative data and adjust for selection procedures, nonresponse, and the need to oversample young adults. The NESARC has completed 2 waves of data collection, with wave 1 occurring in 2001 and 2002 and wave 2 occurring in 2004 and 2005; this investigation uses data from both waves. In both waves, participants are asked all sensitive questions (including those on nonmedical prescription use) using computer-assisted personal interviewing methods. Questions are read to the participant, who wears headphones, and the field interviewer remains out of view of the computer. The US Census Bureau and the US Office of Management and Budget approved the NESARC protocol, and the Texas State University institutional review board exempted this work from oversight. More comprehensive accounts of the NESARC are available elsewhere (Grant, Kaplan, et al., 2003; Grant and Kaplan, 2005).
At wave 1 of the NESARC, 43,093 individuals participated, with 39,959 eligible to participate in wave 2, and 34,653 consented to participate in wave 2. The wave 1 response rate was 81.2%, and the wave 2 response rate was 86.7%, with a total response rate 70.2% across waves. The weighted sample is 52% female, 71% Caucasian, 12% Hispanic/Latino, and 11% African American; 13% of the sample was younger than 25 years.
Measures (NESARC Wave Providing Data in Parentheses)
Nonmedical Use (Wave 1)
Participants are asked the following dichotomous (yes/no) question to assess the use of a variety of illicit drugs and medications in a nonmedical fashion, including opioids and tranquilizers/sedatives: “Now I'd like to ask you about your experiences with medicines and other kinds of drugs that you may have used ON YOUR OWN–-that is, either WITHOUT a doctor's prescription (PAUSE); in GREATER amounts, MORE OFTEN, or LONGER than prescribed (PAUSE); or for a reason other than a doctor said you should use them. People use these medicines and drugs ON THEIR OWN to feel more alert, to relax or quiet their nerves, to feel better, to enjoy themselves, or to get high or just to see how they would work.” As noted previously, this is read to the participant by the computer administering the survey, using computer-assisted personal interview methods.
Past-Year NUPM Frequency (Wave 1)
In the NESARC, the NUPM frequency data are split categorically as follows: no use, once a year, 2 times a year, 3 to 6 times a year, 7 to 11 times a year, once a month, 2 to 3 times a month, 1 to 2 times a week, 3 to 4 times a week, nearly every day, and every day. For these analyses, data are categorized as follows: not in the past year, up to 3 times per month (monthly or less), and once or more per week (weekly/daily). This coding arrangement was chosen because it resulted in roughly even cell sizes for the 2 NUPM groups for both opioid and tranquilizer/sedative users. Those who endorsed “unknown” (<0.08% per variable) were excluded. For the pooled tranquilizer/sedative use group, the highest frequency of nonmedical use was selected from the 2 classes of medication.
Axis I Diagnosis (Waves 1 and 2)
The NESARC assesses psychiatric disorders through the use of the National Institute on Alcohol Abuse and Alcoholism's Alcohol Use Disorder and Associated Disabilities Interview Schedule-IV, which appears to have good reliability and validity (Grant, Dawson, et al., 2003). Here, psychiatric outcomes included AUDs, non-NUPM SUDs, depressive disorders (MDD or dysthymia), bipolar disorders (bipolar I or II), and anxiety disorders (panic disorder with and without agoraphobia, social phobia, specific phobia, or generalized anxiety disorder). The NUPM-related SUD diagnoses were excluded from the SUD category for consistency with previous work upon which this study is based (Schepis and Hakes, 2011).
Axis II Diagnosis (Wave 1)
Seven axis II personality disorder (PD) diagnoses assessed at wave I were included in models as an dichotomous control variable (ie, lifetime presence or absence); these are antisocial, avoidant, dependent, obsessive-compulsive, paranoid, schizoid, and histrionic PD.
Sociodemographic Control Variables (Wave 1)
Age (18–25; 26–35; 36–50; ≥51 years), sex (male/female), race/ethnicity (white, African American, Asian American, Native American/Alaskan Native, Hawaiian Native/Pacific Islander, Hispanic), marital status (6 categories: married, living as if married, widowed, divorced, separated, and never married), education level (did not complete high school, completed high school, some postsecondary education, 4-year degree, some graduate school, and graduate degree), household income (5 groupings: under $40,000, between $40,000 and $69,999, between $70,000 and $99,999, between $100,000 and $149,000, ≥$150,000), employment/full-time student status (employed [0/1]; student [0/1]), and region of residence (Northeast, Midwest, South, and West) were used as sociodemographic control variables.
First, participants with no history of psychopathology (N = 17,167) were not used in analyses, as the numbers of those with a NUPM use history in the past year who developed psychopathology during the follow-up period were too small for stable parameter estimates; these numbers were always less than 15 participants with a history of the NUPM who later developed a disorder from a given category (eg, depressive). After excluding these participants, the remaining sample of 17,486 participants with a history of psychopathology were divided into 4 groups, with each participant in 2 of these groups. These individuals were split twice, on the basis of past-year opioid or tranquilizer/sedative use status: (1) past-year opioid users, (2) non–past-year opioid users, (3) past-year tranquilizer/sedative users, (4) non–past-year tranquilizer/sedative users. Please note that participants included in these analyses were in one of the first 2 groups based on past-year opioid use status and one of the second groups based on past-year tranquilizer/sedative use status. The sociodemographic characteristics of the participant groups are outlined in Table 1.
Analyses employed design-based multivariate logistic regression. Analyses were conducted to examine the effects of past-year NUPM frequency with 2 sets of outcomes: first, on the development of new diagnoses by wave 2 among those with a history of another psychiatric illness at wave 1; and second, on the recurrence of psychopathology at wave 2 among those with a history of a disorder but without a current episode at wave 1. In all cases, the monthly or less often frequency group served as the reference group. Analyses were first performed for opioid nonmedical use and then for tranquilizer/sedative nonmedical use. Please note that although anxiety disorders were pooled for the purposes of reporting of results, coding of recurrence or incidence was done with each disorder separated individually. In other words, an individual with a diagnosis of generalized anxiety at time 1 who developed a diagnosis of social phobia by time 2 would be coded as having an incidence of a new anxiety disorder, not a recurrence.
Results are reported as adjusted odds ratios (AORs) with 95% confidence intervals, after controlling for the sociodemographic variables listed earlier and wave 1 PD status. For the recurrence analyses, the presence of other comorbid axis I disorders were also controlled for; this was not done for the incidence analyses in those with a psychiatric history, because all such individuals necessarily had comorbidity. Also, data were weighted, clustered on primary sampling units, and stratified appropriately. Fischer's scoring algorithm was employed to iteratively estimate regression parameters, and Taylor Series approximation, with adjusted degrees of freedom, was employed to estimate variance. Models were included only if they evidenced adequate fit and had a significant omnibus regression χ2 value. All analyses were performed in SAS, version 9.2 (Cary, NC), using PROC SURVEYLOGISTIC.
Incidence of Psychopathology in Those With a Psychiatric History: Opioids
Please note that all outcome statistics, including 95% confidence intervals for AOR, are listed in Table 2. In non–past-year users, incidence of AUD, SUD, and bipolar disorder were less likely (AUD: P < 0.0001, OR = 0.53; SUD: P < 0.0001, OR = 0.35; bipolar: P = 0.0003, OR = 0.74) than in monthly or less often users. In contrast, depressive disorders were more likely (P = 0.013, OR = 1.49) to occur in nonusers. Finally, weekly/daily users were more likely to have a new depressive (P = 0.029, OR = 1.95), bipolar (P < 0.0001, OR = 2.12), or anxiety disorder (P = 0.0003, OR = 1.72) than monthly or less often users during follow-up.
Incidence of Psychopathology in Those With a Psychiatric History: Tranquilizers/Sedatives
Only 3 sets of results were significant in tranquilizer/sedative users. Nonusers had lower risk for the incidence of SUD and depressive and anxiety disorders than monthly or less often users (SUD: P < 0.0001, OR = 0.58; bipolar: P = 0.03, OR = 0.74; anxiety: P = 0.008, OR = 0.80). Also, those in the weekly/daily group were more likely to have onset of a new anxiety disorder (P < 0.0001, OR = 2.27) than monthly or less often users.
Recurrence of Psychopathology: Opioids
All data on recurrence are listed in Table 3. Nonusers were significantly different than monthly or less often users on every psychopathology outcome. Nonusers were at lower risk for recurrence of AUD (P < 0.0001, OR = 0.40), SUD (P < 0.0001, OR = 0.47), and bipolar disorders (P = 0.03, OR = 0.66); nonusers were unexpectedly at higher risk for both anxiety (P < 0.0001, OR = 1.66) and depressive (P < 0.0001, OR = 1.93) disorders than monthly or less often users. Weekly/daily users were also at higher risk for recurrent depressive (P < 0.0001, OR = 2.88) and anxiety (P = 0.023, AOR = 1.60) disorders than monthly or less often users.
Recurrence of Psychopathology: Tranquilizers/Sedatives
Recurrence of AUD and SUD was less likely in non–past-year users (AUD: P < 0.0001, AOR = 0.45; SUD: P < 0.0001, AOR = 0.38) than in monthly or less often users. Conversely, depressive (P = 0.013, AOR = 1.66) and bipolar (P < 0.0001, AOR = 2.79) disorders were more likely to recur in those with weekly/daily use.
Several significant differences were found across the analyses between monthly or less often nonmedical users and either weekly/daily users or non–past-year users. That said, results did not generally indicate a clear dose-related pattern, as would be indicated if non–past-year users were at lowest and weekly/daily users at highest risk. Given the lower base rates of the NUPM, lower power could have influenced the results, but the most valid interpretation is that these findings argue against the precipitation hypothesis for opioid or tranquilizer/sedative nonmedical use, particularly as concerns AUD and SUD.
Instead, this work highlights differences in how opioid or tranquilizer/sedative NUPM influences the incidence and course of AUD and SUD versus the mood and anxiety disorders. Risk for AUD or SUD recurrence was higher in those with any opioid or tranquilizer/sedative NUPM, with less risk in non–past-year users; no differences were found within nonmedical users. In contrast, compared with monthly or less often use, incidence of depressive, bipolar, and anxiety disorders was often more likely in those with weekly/daily use, with 8 of the 12 possible cases evidencing increased risk for a mood or anxiety disorder with weekly or daily opioid or tranquilizer/sedative NUPM. Finally, the risk for the recurrence of depressive and anxiety disorders are higher for non–past-year opioid users, whereas bipolar incidence and recurrence was generally less likely.
The risk for AUD or SUD recurrence imparted by any level of opioid or tranquilizer/sedative NUPM may simply result from the fact that problematic users of alcohol and other substances are more likely to engage in the NUPM (eg, Blazer and Wu, 2009; McCabe et al., 2006). In other words, heavy alcohol and other substance users tend to use multiple substances, so the risk imparted by the NUPM may simply signify the influence of a shared, higher-order risk factor (eg, impulsivity; Hall et al., 2010). In contrast, bipolar and anxiety disorder (and to a much lesser extent, depressive disorder) risk was most often increased only in weekly or daily nonmedical users. This may signal some degree of precipitation, as only frequent use prompts development of recurrence of those forms of psychopathology. That said, the lack of consistent findings of decreased risk in non–past-year users does not strongly support a precipitation hypothesis. These equivocal findings need further evaluation.
Finally, the protective effects of infrequent use in nonmedical opioid users for depressive and anxiety disorder recurrence may point to a curvilinear relationship between opioid NUPM and depressive or anxiety recurrence. Longitudinal work in adolescents (Shedler and Block, 1990) and cross-sectional work in young adults (Caldwell et al., 2002) indicates that “experimenters” with alcohol have lower levels of anxiety and depressive symptoms than nonusers and higher levels of constraint and inhibition than regular users. Although the analogy from the previous work with alcohol to this work with opioid nonmedical use is imperfect, our findings may point to the illusion of a direct relationship between the NUPM and depressive or anxiety disorders caused by a third factor or set of factors such as externalizing psychopathology (McGue, Iacono, Legrand, and Elkins, 2001; McGue, Iacono, Legrand, Malone, et al., 2001), impulsivity (Hall et al., 2010), or internalizing symptoms (Shand et al., 2011).
Seven limitations of this work should be noted. First, SUD resulting only from the NUPM was excluded, placing those individuals in the group with no psychopathology. This was consistent with the previous work upon which this investigation was based (Schepis and Hakes, 2011). Second, most of the NESARC respondents were older than the median age of psychopathology onset (Andrade et al., 2003; Bonnewyn et al., 2007). This was likely to influence the 19% incidence rate for examined disorders over the 3-year follow-up in those with the NUPM at baseline; this in turn is lower than the 46.4% lifetime incidence rate from a similar group of disorders. Thus, although these results are generalizable to the US population at the time of the survey, they are likely to have missed the period of psychopathology incidence for many individuals. This was unavoidable, given the NESARC design.
Third, because the NESARC codes methamphetamine use with stimulant NUPM, we excluded a small proportion of these participants from analyses by including them in the group with no psychopathology, if they did not have other diagnoses than SUD from stimulant NUPM. Fourth, because of small cell sizes for many substances, we combined drug use disorders from different classes in computing incidence or recurrence. Thus, it is possible that an individual had a history of a disorder at time 1 from one substance with a new disorder at time 2 from a new substance. This would be counted as a recurrence, not an incidence. Given the small samples affected, we believe this was a minor limitation. Fifth, the NESARC does not code whether individuals also use medications appropriately (or “medically”) in addition to nonmedically. Some evidence indicates subtle differences between nonmedical-only users and those who use medications medically and nonmedically (eg, McCabe et al., 2012), and future research should examine the effect of this distinction on the psychopathology–NUPM relationship. Sixth, the use of self-report data could lead to inaccurate reporting, particularly in cases where the data was retrospective. Finally, although the response rate of the NESARC is excellent and statistical methods corrected for nonresponse, bias could have resulted from selective dropout.
Although the precipitation hypothesis was not clearly supported in this investigation, some degree of support for precipitation was found for the mood and anxiety disorders. More definitive are the findings about vulnerable groups of nonmedical users. Any level of opioid or tranquilizer/sedative NUPM increases risk for episodes of AUD and SUD, whereas risk for mood and anxiety disorders is only increased at a level of weekly or more frequent opioid or tranquilizer/sedative NUPM. Patients with problematic substance use histories need to be screened for opioid or tranquilizer/sedative NUPM and counseled about its potential harms, particularly as they apply to AUD and SUD. For those with histories of mood or anxiety disorders, screening may be best aimed at more frequent nonmedical users. Also, frequent nonmedical users may benefit from education about the risk for the development of depressive, bipolar, or anxiety disorders. Although the precipitation hypothesis was generally not supported, more research is needed to clarify the nature of the relationship between NUPM and psychopathology, as such work could significantly limit the morbidity and mortality associated with each.
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benzodiazepines; etiology; nonmedical prescription use; opioid; psychopathology