We examined the variance inflation factors for each model to ensure that the degree of multi-collinearity was low. We further incorporated spatial dependence in multilevel logistic regressions to account for potential between-neighborhood correlations. We first constructed the rate of inpatient stays involved with OUD per 1000 population, the rate of inpatient stays involved with opioid overdose per 1000 population, and the rate of observation stays involved with OUD per 1000 population, at the zip code level. We then calculated spatially lagged rates of hospital stays related to opioids using GEODA . In multilevel logistic regressions, the correspondent spatially lagged variable was added as a zip code level covariate.Table 2 reports multilevel logistic regression results for inpatient stay records. Patients living in neighborhoods with one more recreational marijuana dispensaries per square mile were more likely to be diagnosed with OUD in inpatient stays. Living in neighborhoods with increased density of medical marijuana dispensaries or DATA-2000 waivered providers was not associated with being diagnosed with OUD or opioid overdose in inpatient stays. Regarding patient-level covariates: females were less likely to have OUD related inpatient stays than males; individuals aged 21-34 had the highest odds of OUD related inpatient stays, while individuals aged 50-64 had the highest odds of inpatient stays related to opioid overdose, across age groups; non-Hispanic white had the highest odds of OUD related inpatient stays, while non-Hispanic white and black had the highest odds of inpatient stays related to opioid overdose, across race and ethnic groups; individuals with Medicaid had the highest odds of OUD related inpatient stays,growing cannabis while individuals with Medicare had the highest odds of inpatient stays related to opioid overdose, among individuals with different health insurance.
Table 3 reports multilevel logistic regression results for observation stay records. The density of medical marijuana dispensaries, recreational marijuana dispensaries, or DATA-2000 waivered providers was not associated with OUD-related observation stays. Regarding patient-level covariates: individuals aged 21-34 had the highest odds of OUD related observation stays, across age groups; other non-Hispanic minority had the highest odds of OUD related observation stays, across race and ethnic groups; individuals with Medicaid had the highest odds of OUD related observation stays, among individuals with different health insurance. Appendix Tables present sensitivity analysis results. As shown in Appendix Table 1, the density of marijuana dispensaries or DATA-2000 waivered providers was not associated with OUD-related hospital stays. As shown in Appendix Table 2, living in neighborhoods with 1+ recreational dispensary was associated with higher odds of being diagnosed with OUD in inpatient stays, while living in neighborhoods with 1+ medical dispensary was associated with lower odds of being diagnosed with OUD in observation stays. As shown in Appendix Table 3: compared to patients living in neighborhoods without any recreational marijuana dispensaries, patients living in neighborhoods with one recreational marijuana dispensaries were more likely to be diagnosed with OUD in inpatient stays, while patients living in neighborhoods with one medical marijuana dispensary were less likely to be diagnosed with OUD in observation stays compared to those living in neighborhoods without any medical marijuana dispensaries. This study is the first attempt to explore the associations of the neighborhood availability of marijuana dispensaries and DATA-2000 waivered providers with opioid-related health outcomes.
Utilizing the unique policy environment in Washington, we were able to ascertain the differential associations of recreational marijuana and medical marijuana dispensaries. The findings suggested that the availability of recreational marijuana dispensaries in a neighborhood was associated with a higher likelihood of inpatient stays related to OUD. No associations were detected between the availability of medical marijuana dispensaries or DATA-2000 waivered providers and opioid-related hospital stays. This study suggested that neighborhood availability of recreational marijuana dispensaries was associated with increased opioid-related hospital stays, yet the availability of medical marijuana dispensaries was not. On the one hand, marijuana use for recreational purpose may lead to increased opioid use , which may explain our findings for recreational marijuana dispensaries and previous studies which reported elevated opioid use and misuse among marijuana users . On the other hand, because of the therapeutic effects of marijuana on pain , patients with pain may use marijuana as a complement or substitute for medical purposes . This may explain why the availability of medical marijuana dispensaries was not associated with increased opioid-related hospital stays. However, our neighborhood-level evidence cannot directly support this assumption at the individual level. Findings of our main analysis for medical marijuana dispensaries were consistent with a recent individual-level prospective cohort study in Australia but did not support previous state-level investigations . Future empirical evaluations are warranted to substantiate the correlations between marijuana and opioid and the individual pattern of drug use.
The null associations between availability of DATA-2000 waivered providers and opioidrelated hospital stays do not necessarily indicate a null impact of increased DATA-2000 waivered provider supply on OUD outcomes. DATA-2000 waivered providers may respond to the aggravated opioid epidemic by increasing the supply of OUD treatments. A recent study demonstrated that states with higher opioid overdose had higher rates of growth in the supply of DATA-2000 waivered providers . The observed cross sectional associations may, therefore, reflect the combined effects of the demand-supply relationship and the true impact of increased treatment capacities on opioid-related outcomes. Also, buprenorphine treatment utilization can also be affected by demand-side factors, such as health insurance coverage and patients’ awareness . Future research should utilize longitudinal data to separate the demand-supply factor from the true impact. The study has limitations. First,cannabis growing the study examined cross-sectional associations instead of causality. Although we controlled for a rich set of patient and neighborhood characteristics, it is likely that some unobserved heterogeneities influenced the estimation of the associations. Second, OUD related to opioids could not be differentiated from that related to illicit opioids in ICD-10-CM diagnosis codes. To ensure consistency of definitions, we, therefore, did not differentiate opioid overdose related to prescription opioids and illicit opioids. Third, the CHARS data had several limitations. Emergency department records were not available in CHARS. Also, no unique identifiers were provided to identify multiple hospital stays of a unique patient, but such cases should be rare in a relatively short time frame . Fourth, the directories obtained from SAMHSA may not cover all DATA-2000 waivered providers. Also, we did not control for other resources for treating OUD, such as opioid treatment programs providing methadone, because few neighborhoods had these programs. Fifth, we can only evaluate the impact of the availability of marijuana dispensaries and DATA-2000 waivered providers, rather than the exposure to marijuana and access to OUD treatment. Moreover, the classification of dispensaries does not ensure exclusive supply to users using marijuana for recreational or medical purpose, especially during the study period when dispensaries were insufficiently regulated in Washington. Lastly, the first half year of 2016 is a transition period with rapid changes in the policy and neighborhood environments related to marijuana and opioid in Washington. We recognized that the number and classification of marijuana dispensaries and the supply of DATA-2000 waivered providers might not remain constant throughout the entire 6-month study period. The study findings may not be generalizable to Washington after July 2016 when all medical marijuana dispensaries were forced to shut down or transform to recreational marijuana dispensaries or to other states where policy contexts were different.
Marijuana is the most commonly used illicit drug worldwide, with the majority of US states having legalized it for either recreational and/or medicinal use within the past decade. In the wake of these rapid social and legal changes, epidemiological research reveals that past-year cannabis use disorder rates have increased in the general population and have also more than doubled in the past decade among military veterans. Among individuals with CUD , rates of comorbid mood disorders are higher relative to those without CUD. Comorbidity between mood disorders and SUDs including CUD is particularly common in veterans, particularly post deployment, calling for more research investigating potential mechanisms to explain this comorbidity.marijuana problems in general populations and among veterans. Affective-motivational theory emphasizes the central role of negative affect in motivating drug use, including marijuana use specifically . Recent cross-sectional data suggest that marijuana users who experience MDD are more likely to have CUD than marijuana users without MDD. Cross-sectional between-subject and prospective within-subject empirical research in support of this theory suggests that greater intensity of negative affect associated with MDD leads to increased marijuana use to in order to cope with negative emotions. Yet, coping-oriented use of substances has also been shown to worsen affective symptoms of depression and to increase substance misuse. Evidence for the directionality of the association between MDD and CUD is mixed. Some longitudinal studies have provided evidence that cannabis use predicted increased symptoms of depression; whereas depressive symptoms did not predict increased cannabis use. However, this directionality was only found among adolescent girls in one study, limiting generalizability. One meta-analysis of longitudinal studies found that heavy cannabis use may be associated with increased depressive symptoms, but did not explore the opposite direction . In contrast, large epidemiological studies have also revealed MDD was prospectively associated with CUD and contributed to its etiology. Additional longitudinal work has suggested a bidirectional relationship between depressive symptoms and cannabis use from adolescence to young adulthood across five years of assessment in men.Impulsive personality traits have long been a hallmark characteristic for substance misuse and substance use disorders in general. Certain facets of impulsivity, such as delay discounting, have been associated with greater marijuana use and marijuana dependence. Composite scores of attentional, motor, and non-planning impulsivity have also been associated with marijuana problems. Importantly, the UPPS-P Impulsive Behaviors Scale classifies impulsivity as multi-faceted construct, in which certain traits are uniquely related to specific risky behaviors. Each of these five impulsivity-like traits have been found to be associated with marijuana use and related consequences.Impulsive personality traits may partially explain the association between MDD and marijuana use and problems. Specifically, negative urgency , one facet of impulsivity characterized by rash action when experiencing emotional distress, may be of particular relevance to this comorbidity. When considering all facets of the UPPS-P model, NU and lack of perseverance specifically have been shown to relate to symptoms of MDD. NU has also been associated with marijuana use and problems in general populations. Relatedly, NU has been associated with alcohol use problems, particularly among those with higher levels of MDD. Thus, marijuana users with MDD may be more likely to act without thinking when upset or distressed. This in turn may lead to heavier use and a greater number of negative consequences related to marijuana use.In order to clarify the mechanisms linking MDD and problematic marijuana use, this study sought to examine whether NU would uniquely explain the relationship between MDD and marijuana use and problems. Two specific questions are examined: 1) The extent to which higher NU accounts for the relationship between MDD and marijuana use and problems; and 2) Whether this effect is unique to NU, or if other impulsive personality traits also partially account for the relationship between MDD and marijuana use and problems.Data were drawn from a larger prospective study examining marijuana use and affective disorders in returning Operation Enduring Freedom, Operation Iraqi Freedom, and Operation New Dawn veterans who were deployed post 9/11/2001 and who used marijuana at least once in his/her lifetime. Participants were recruited from a VHA facility in the Northeast US by utilizing the VHA OEF/OIF/OND Roster, an accruing database of combat veterans who have recently returned from military service in Iraq and Afghanistan and enrolled in VHA . Veterans were screened for eligibility by telephone and were invited for a baseline visit, at which time they signed informed consent and completed a battery of interview and self-report assessments . The study was approved by the university and local VHA Institutional Review Boards. Participants were compensated $50 upon completion of the study session. The original sample included 361 participants, from which four subjects were removed for missing data, resulting in a final N = 357.Descriptive statistics and bivariate correlations were first examined. Next, hypothesized mediational models were examined. MDD was specified as the predictor, or independent variable; marijuana use and problems were specified as the outcomes, and impulsivity measures were specified as the mediators of interest.