Abstract
Background/Objectives
Marijuana is the most commonly used illicit substance, yet among the least studied in medication development research. Cocaine-dependent individuals frequently also use marijuana; however, little is known about the effect of this combined use on treatment presentation.
Methods
Marijuana use was assessed in 1183 individuals seeking outpatient treatment for cocaine dependence. Based on past 30 days of use, the sample was divided into three groups: (1) patients reporting no recent marijuana use (n = 634); (2) occasional use (n = 403); (3) and frequent concurrent marijuana use (n = 146). Differences on baseline measures of substance use, addiction severity (ASI), psychopathology, and sociodemographic characteristics were examined as a function of level of marijuana use.
Results
Frequent marijuana users were more likely to be female, Caucasian, and younger than other groups. Cocaine-dependent patients with frequent marijuana use also used more cocaine and alcohol, and reported more medical, legal, and psychiatric problems, including antisocial personality disorder.
Conclusion and Scientific Significance
Cocaine-dependent patients with frequent marijuana use present for treatment with more severe impairment. Accounting for this heterogeneity among participants may improve treatment outcome.
Keywords: Clinical treatment trial, cocaine dependence, dual substance abuse, marijuana
INTRODUCTION
Marijuana is the most commonly used illicit substance in the general population and among cocaine users (1–4). Rates of use among clinical samples of cocaine dependent patients range from 59 to 89%, with prevalence of cannabis dependence estimated at 18 to 53% (4–8). Marijuana use is highly salient in the context of substance dependence not only because of its prevalence but also because of its unpredictable effects when used in combination with other drugs (9).
The pervasive and devastating effects of cocaine dependence are well documented. More recently, the serious consequences of chronic marijuana use have been established. On its own, frequent marijuana use can lead to interpersonal difficulties, decreased motivation, cognitive impairment, respiratory and cardiovascular disease, and an increased risk of use of other substances (1, 10–13). Exactly how the effects of marijuana interact with the negative health and psychosocial effects of chronic cocaine use is unclear; however, there is evidence suggesting an exacerbation of consequences when using both drugs together (14, 15). For example, Budney et al. found that among 186 cocaine-dependent individuals, marijuana use at intake was associated with more frequent cocaine and alcohol use, increased depressive symptoms, and health-related consequences (16).
Human studies of the interaction of cocaine and marijuana have shown that combining the two drugs increases absorption of cocaine, and raises heart rate and blood pressure (17, 18). In a laboratory study by Lukas and colleagues, when subjects were administered marijuana prior to cocaine, latency to cocaine effects was significantly reduced, and duration of the positive or “good” effects of cocaine was increased, while the duration of dysphoric or “bad” effects was decreased (19). Thus, cocaine-marijuana users may engage in heavier or more frequent drug use in order to seek these desired behavioral and subjective effects.
In general, polydrug use is associated with poorer treatment outcome than single drug use (20), but results of studies specifically examining the impact of concurrent marijuana use on cocaine treatment outcome are mixed. Two studies reported adverse effects of continued marijuana use on risk of cocaine use or relapse (6, 21), while two other studies found a positive association between concurrent marijuana use and treatment retention (5, 22). Others have failed to find an association between marijuana use and treatment outcome of cocaine dependence (16, 23). Marijuana use and dependence, while not exclusionary in most cocaine clinical trials, may introduce an important source of population heterogeneity. Thus, initial research is needed to understand the potentially important differences among groups of cocaine users with and without concurrent marijuana use.
The present study focused on concurrent use of marijuana and its relation to the clinical profile of cocaine dependent individuals, including sociodemographics, substance use, and psychosocial variables. The extent to which cocaine dependent individuals used marijuana was expected to be related to the severity of their clinical presentation, with more frequent marijuana users showing the greatest impairment.
METHODS
Participants and Procedures
Participants were consecutive admissions to behavioral and pharmacological treatment studies for cocaine dependence conducted at the Treatment Research Clinic (TRC) in Houston, Texas.
Subjects were cocaine-dependent, English-speaking, between the ages of 18 and 60, able to participate in 12 weeks of outpatient treatment, and competent to give informed consent. Individuals were excluded if they met diagnostic criteria for current DSM-IV substance dependence (except nicotine, cannabis and cocaine) or Axis I disorders, used psychotropic medications, or experienced unstable or serious medical illnesses. All participants signed an informed consent form that was reviewed and approved by the Committee for the Protection of Human Subjects of The University of Texas—Houston, Health Science Center. Subjects took part in a two-week intake evaluation process to determine study eligibility, which included a physical examination, laboratory work-up, and a structured clinical interview for DSM-IV diagnoses.
The total sample of 1183 subjects had a mean age of 39 years (SD = 6.96) and a mean education level of 12.72 years (SD = 2.08). Most were African American (64.7%), male (82%), and unemployed (53%). Reported use of cocaine in the 30 days prior to treatment was 13.42 days (SD = 8.87). The majority of subjects (85.5%) reported smoking cocaine as their primary route of administration, and 64% previously participated in drug abuse treatment.
Measures
Sociodemographics and Substance Use
Author-constructed forms were used to collect sociodemographic and drug history information. The drug history interview included items assessing recent quantity/frequency, duration of use, route of administration, longest sustained abstinence, past quit attempts, and desire to quit for all classes of psychoactive drugs. The Addiction Severity Index (ASI) (24) was used to assess severity of problems in the following areas: medical, employment, drug, alcohol, legal, family/social, and psychiatric. Interviewers underwent standard ASI training procedures and received ongoing supervision. ASI composite severity scores were calculated.
Diagnosis
Current and past diagnostic information was obtained using the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (38) per the Structured Clinical Interview for DSM-IV [SCID (39)]. All Axis I modules and the three Axis II modules for antisocial, borderline, and dependent personality disorder were administered. SCID assessments were conducted by master’s and doctoral level clinicians who were trained by experienced interviewers using standardized training videotapes from Biometrics Research, New York. As recommended, a series of practice interviews was performed to enhance interrater reliability before beginning interviews with study participants. Provisional SCID-based diagnoses were confirmed by the study psychologist or psychiatrist.
Marijuana Use
Ninety-five percent of subjects in this cocaine-dependent sample reported ever having used marijuana. Approximately half of the subjects (n = 549, 46.4%) reported current use, defined as any marijuana use during the past 30 days. Within the current users, inspection of the distribution of days of use supported a further division between “occasional users” (n = 403, 34.1%) and “frequent users” (n = 146, 12.3%). Based on natural breaks in the distribution, subjects using marijuana 1 to 9 days over the past 30 days were categorized as occasional users and reported a mean ± SD of 2.57 ± 2.01 days of use. Subjects using marijuana 10 or more days over the past 30 days (M = 20.75 ± 7.57 days) were categorized as frequent users. This classification system demonstrated convergent validity with intake urine screen results. Percentage of marijuana positive screens was 76.7% in frequent users, 23.1% in occasional users, and 1.1% in the non-using group. Additionally, frequent users were more likely to meet current marijuana dependence criteria (20.5% relative to 3% in occasional users).
Data Analysis
Differences across levels of marijuana use were assessed with contingency tables and χ2-testing for categorical variables and analyses of variances (ANOVA) for continuous variables. Tukey tests were used to control for Type I error in post hoc pairwise comparisons. Conversely, examining the prediction of marijuana group status by salient baseline variables employed logistic regression.
RESULTS
Comparison of Sociodemographic and Addiction Severity Characteristics
Table 1 presents the sociodemographic characteristics across levels of concurrent marijuana use. Gender differences indicated a higher proportion of women than men in the frequent using group only. For race, group differences indicated a higher proportion of Caucasians than African-Americans or Hispanics in the frequent using group. Age differences were found as well, with the frequent using group younger than the occasional and non-using groups. The frequent using group had higher ASI severity scores on the alcohol, drug, psychiatric, and legal scales compared to occasional and non-users. In contrast, the frequent using group had lower severity scores on the employment subscale. They were more likely to be employed than the occasional and non-users.
TABLE 1.
Comparison of sociodemographic and addiction severity characteristics
| None | Occasional | Frequent | |||||
|---|---|---|---|---|---|---|---|
| (N = 634) | (N = 403) | (N = 146) | F/X 2 | p-value | OR1 | 95% CI | |
| Sociodemographic | |||||||
| Age (mean ± SD) | 39.7 ± 6.5a | 39.1 ± 7.4a | 35.7 ± 7.1b | 20.0 | ≤.0001 | .94 | .92, .97 |
| Education (mean ± SD) | 12.7 ± 2.1 | 12.8 ± 2.1 | 12.5 ± 1.7 | 1.2 | .31 | ||
| Female (%) | 16.9a | 17.1a | 27.4b | 9.3 | .009 | 1.83 | 1.17, 2,86 |
| Married (%) | 24.1 | 22.1 | 21.9 | .7 | .70 | ||
| White (%) | 24.9a | 27.0a | 44.5b | 25.7 | .001 | 1.55 | 1.17, 2.05 |
| Employed (%) | 23.0 | 24.6 | 33.6 | 7.1 | .029 | 1.55 | 1.03, 2.34 |
| ASI Composites (mean ± SD) | |||||||
| Medical | .07 ± .20 | .08 ± .20 | .12 ± .27 | 2.67 | .07 | ||
| Employment | .66 ± .24a | .63 ± .30a | .59 ± .24b | 4.81 | .008 | .38 | .19, .73 |
| Legal | .04 ± .55a | .04 ± .10a | .07 ± .14b | 3.37 | .034 | 6.82 | 1.86, 25.07 |
| Alcohol | .19 ± .13a | .20 ± .14a | .25 ± .13b | 12.6 | ≤.0001 | 4.03 | 1.15, 14.13 |
| Drug | .22 ± .07a | .24 ± .07b | .33 ± .07c | 133.3 | ≤.0001 | N/A2 | |
| Family/Social | .18 ± .21 | .19 ± .21 | .18 ± .22 | .31 | .73 | ||
| Psychiatric | .10 ± .16a | .10 ± .15a | .14 ± .18b | 4.32 | .014 | 4.73 | 1.56, 14.35 |
Group means sharing a common letter are not significantly different (p <.05).
Odds of membership in frequent versus occasional using groups was computed by binary logistic regression.
Calculation of this variable included ASI item used to define marijuana group.
Comparison of Substance Use Characteristics
Table 2 presents the substance use characteristics across level of concurrent marijuana use. Compared to non-users and occasional users, those in the frequent using group reported more recent days using cocaine and alcohol. Frequent users reported an earlier age of first use of cocaine than occasional users and reported more intranasal use of cocaine than occasional users. Among users of marijuana, frequent users were more likely to perceive marijuana as a problem but rated their desire to quit using marijuana lower than occasional users.
TABLE 2.
Comparison of substance use characteristics
| None | Occasional | Frequent | |||||
|---|---|---|---|---|---|---|---|
| (N = 634) | (N = 403) | (N = 146) | F/X 2 | p-value | OR1 | 95% CI | |
| Drug use, days in past 30 (M ± SD) | |||||||
| Cocaine | 12.5 ± 8.8a | 13.8 ± 8.7a | 16.6 ± 8.9b | 13.5 | ≤.0001 | 1.04 | 1.03, 1.06 |
| Alcohol | 8.0 ± 8.9a | 10.0 ± 9.3b | 12.9 ± 10.2c | 18.26 | ≤.0001 | 1.04 | 1.03, 1.06 |
| Lifetime drug use, years (M ± SD) | |||||||
| Cocaine | 10.8 ± 6.0 | 10.8 ± 6.1 | 10.7 ± 9.1 | .03 | .97 | ||
| Alcohol | 15.2 ± 10.0 | 16.2 ± 10.2 | 14.1 ± 8.5 | 2.79 | .062 | ||
| Marijuana | 6.8 ± 7.6a | 13.4 ± 9.1b | 16.8 ± 7.7c | 132.5 | ≤.0001 | 1.09 | 1.07, 1.11 |
| Route of cocaine administration | |||||||
| Nasal (%) | 9.4a | 11.8a | 17.4b | 7.3 | .026 | .55 | .33, .89 |
| Age of First Use | |||||||
| Cocaine | 26.9 ± 7.7a | 26.5 ± 7.7a | 24.2 ± 7.4b | 6.8 | .001 | .96 | .93,.98 |
| Alcohol | 19.3 ± 6.7a | 18.1 ± 6.2b | 18.1 ± 6.3b | 5.1 | .007 | ||
| Marijuana | 16.8 ± 4.5 | 17.4 ± 5.3 | 17.5 ± 4.5 | 2.11 | .12 | ||
| Desire to Quit (1–10) | |||||||
| Cocaine | 9.6 ± 1.1 | 9.5 ± 1.4 | 9.5 ± 1.3 | 2.5 | .08 | ||
| Alcohol | 4.4 ± 3.6 | 4.5 ± 3.5 | 4.4 ± 3.5 | .004 | .99 | ||
| Marijuana | 4.11 ± 3.7a | 4.7 ± 3.9a | 2.8 ± 3.0b | 13.1 | ≤.0001 | .86 | .81, .91 |
| Marijuana as problem (%) | 14.7a | 22.4b | 27.1b | 14.4 | .001 |
Group means sharing a common letter are not significantly different (p < .05).
Odds of membership in frequent versus occasional using groups was computed by binary logistic regression.
Comparison of Diagnostic Characteristics
By study protocol, eligible subjects met DSM-IV criteria for cocaine dependence and did not meet criteria for current dependence on alcohol, sedatives, opioids, or hallucinogens. Frequent marijuana users were more likely to have current and lifetime cannabis use disorders. As shown in Table 3 no differences were found on lifetime diagnoses of alcohol abuse or dependence. The proportion of subjects meeting criteria for lifetime abuse of hallucinogens and opioids was highest among the frequent using group. Of the Axis II disorders assessed, differences were found for the diagnosis of Antisocial Personality Disorder (ASPD) with the frequent using group more likely to meet criteria for this disorder compared to occasional users. Occasional users met ASPD criteria more often than non-users.
TABLE 3.
Comparison of diagnostic characteristics
| None | Occasional | Frequent | |||||
|---|---|---|---|---|---|---|---|
| (N = 634) | (N = 403) | (N = 146) | F/X2 | p-value | OR1 | 95% CI | |
| Alcohol Abuse (%) | |||||||
| Lifetime | 35.0 | 36.8 | 34.5 | .40 | .82 | ||
| Current | 7.3 | 9.0 | 12.4 | 4.2 | .12 | ||
| Alcohol Dependence (%) | |||||||
| Lifetime | 21 | 22.9 | 20.5 | .63 | .73 | ||
| Marijuana Abuse (%) | |||||||
| Lifetime | 26.2a | 37.7b | 37.0b | 17.3 | ≤.0001 | ||
| Current | .5a | 3.2b | 19.2c | 116.3 | ≤.0001 | 7.10 | 3.56, 14.15 |
| Marijuana Dependence (%) | |||||||
| Lifetime | 14.2a | 15.7a | 26.0b | 12.3 | .002 | 1.89 | 1.20, 2.98 |
| Current | .2a | 3.0b | 20.5c | 141.5 | ≤.0001 | 4.64 | 2.61, 8.24 |
| Lifetime Substance Abuse (%) | |||||||
| Sedative | 8.7 | 7.3 | 13.7 | 5.6 | .06 | ||
| Opioid | 3.8a | 5.0a | 9.6b | 8.5 | .014 | 2.02 | .99, 4.10 |
| Hallucinogen | 5.8a | 8.8a | 15.1b | 14.3 | .001 | 1.85 | 1.05, 3.27 |
| SI Mood Disorder (%) | 6.2 | 7.2 | 7.5 | .52 | .77 | ||
| Borderline PD (%) | 2.2 | 4.0 | 3.5 | 2.9 | .24 | ||
| Antisocial PD (%) | 7.6a | 12.3b | 20.8c | 22.5 | ≤.0001 | 1.87 | 1.14, 3.10 |
| BDI (M ± SD) | 15.1 ± 10.0 | 15.6 ± 9.7 | 16.5 ± 10.7 | 1.05 | .35 |
Group means sharing a common letter are not significantly different (p <.05).
Odds of membership in frequent versus occasional using groups was computed by binary logistic regression.
DISCUSSION
The large percentage (46.4%) of concurrent marijuana users in this sample of treatment-seeking cocaine dependent sample is consistent with previous reports (16, 25, 26). Overall, findings support our hypothesis that frequent concurrent marijuana users present with a distinct clinical profile. In most comparisons, between-group effects were driven by greater differences between frequent users and the other groups. Key points from this study are summarized below.
Concurrent marijuana is associated with problem severity in cocaine-dependent patients, a finding that is consistent with other studies documenting the negative consequences of using cocaine in combination with other drugs, including alcohol (27, 28) and opioids (29, 30). We found that frequent users of marijuana showed a pattern of greater impairment, exemplified by more severe ASI scores and heavier patterns of drug use. These individuals present for treatment with heavier recent use of marijuana, cocaine, and alcohol. Level of marijuana use is positively related to length of time using cocaine (earlier onset) and likelihood of meeting lifetime abuse or dependence criteria for other substances. In this sample, frequent marijuana users were also more likely to meet criteria for ASPD compared to less frequent marijuana using patients. Together, these results, along with those reported previously suggest increased risk of psychopathology among cocaine dependent patients with a higher frequency of marijuana use (16, 31).
Marijuana was more likely to be perceived as a problem in the frequent using group; however, this group rated their desire to quit using marijuana as lower than less frequent users. Compared to cocaine, marijuana tends to be associated with more ambivalence about quitting and lower readiness to quit (25, 32, 33). Levin et al. (33) further explored this difference in motivation and found that marijuana-dependent patients may want to change, but are not experiencing as severely negative consequences as cocaine-dependent individuals.
Gender differences found here are consistent with SAMHSA data showing that a higher percentage of women cite marijuana as a secondary drug of abuse (2). In epidemiological and treatment studies of marijuana as a primary drug of abuse, men have been overrepresented (3, 34–36). Based on our results indicating that cocaine-dependent females versus males were more likely to be frequent users of marijuana, additional research targeting dual-drug-using women is needed.
One of the strengths of this study is that findings are based on data collected from a large and well-defined sample of treatment-seeking cocaine dependent individuals. Grouping marijuana users according to frequency of use provided new information about how the level of concurrent use impacts clinical presentation. The lack of reliable differences between non-users and occasional users suggests that the clinically important feature is not whether (or not) cocaine patients use marijuana concurrently, but rather the extent to which they use marijuana. Further research on the temporal and functional relationship between cocaine and marijuana use, especially in the frequent using subgroup, is warranted. Additionally, we recommend that future studies employ a more fine-grained measurement of marijuana use to include amount in addition to frequency of use.
While the present study advances our knowledge about marijuana use in the population of cocaine dependent individuals, outcome data are not yet available to assess whether differences found at baseline are meaningful predictors of outcome. Also, we recognize that a considerable number of tests were conducted at an α = .05 probability of committing a Type I error. Significant findings reported provide a starting point for generating hypotheses.
Multiple substance use is common in cocaine patients and allowing for concurrent use of other drugs has been recommended to increase feasibility and generalizability of results (37). However, the present findings strongly suggest that concurrent marijuana use should not go ignored or unmonitored in cocaine clinical trials. Future studies should assess differences in presenting clinical characteristics of marijuana-using cocaine dependent patients and consider the impact of these differences in evaluation of treatment outcomes.
ACKNOWLEDGMENTS
This study was funded by grants from the National Institute on Drug Abuse (P50-DA9262).
Footnotes
Declaration of Interest The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the article.
Contributor Information
Jan A. Lindsay, Department of Psychiatry and Behavioral Sciences, University of Texas, Houston, Texas, USA
Angela L. Stotts, Department of Family and Community Medicine, University of Texas, Houston, Texas, USA
Charles E. Green, Center for Clinical Research and Evidence-Based Medicine, University of Texas, Houston, Texas, USA
David V. Herin, Department of Psychiatry, University of Minnesota, Minneapolis, Minnesota, USA
Joy M. Schmitz, Department of Psychiatry and Behavioral Sciences, University of Texas, Houston, Texas, USA
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