The American Civil Liberties Union report data from the NSDUH and Uniform Crime Reporting Data showing that Black males were no more likely to report marijuana use, but 4-times more likely to be incarcerated for marijuana possession compared to their non-Hispanic White male counterparts . Epidemiologic data have shown a linear increase in cigarette and marijuana co-use in Whites, Blacks/ African-Americans, and Hispanics with the fastest rate of increase among Blacks/ African-Americans . Among Blacks/ African-Americans, it is possible that statewide legalization of medical marijuana could help to reduce marijuana-related incarcerations, and at the same time, influence the rate of couse. We are cognizant of the many layers that add to the complexities around the issue of marijuana legalization that are well beyond the scope of our study. We recommend future research will assess potential and actual benefits/ costs of marijuana legalization to society at large, and in states where marijuana is legal, identify issues that can be addressed with specific regulatory measures . Study limitations include the cross sectional nature of these analyses which limits our ability to infer causality. Interpretation of our findings is limited to cigarette smokers which is distinct from those who reported other tobacco products . We were unable to examine statewide legalization of medical marijuana by the number of years the policy went into effect using the NSDUH to account for time lags from adoption to full implementation. The NSDUH public dataset only provides a binary categorization of states that were legal vs. illegal that lumps states that just passed the law with long-term legalization states limits our ability to detect long-term effects and may have attenuated our findings. Further study is needed to examine the effect of combusted vs. non-combusted marijuana use on nicotine given increasing prevalence of edible and aerosolized delivery of marijuana with vaporizers . At present, the NSDUH does not ask respondents to indicate whether use was combusted and/ or non-combusted and we recommend that future surveys collect information on marijuana modality to elucidate the relationship between various forms of marijuana intake and nicotine and/ or THC dependence. Data on combusted vs. non-combusted THC intake can also help to identify if there might be differences in health effects across marijuana use modality. In addition, the present study did not examine population density which might be a potential covariate for marijuana use.
Strengths of the study were use of a large national dataset representative of the U.S. population and internal validity of nicotine dependence comparisons across age categories using the same dataset,indoor cannabis grow system which eliminates methodological variations from one study to another. Medical marijuana legalization was positively associated with cigarette and marijuana couse and co-users were at greater risk for nicotine dependence. Long-term longitudinal data across age groups are needed to elucidate these results. In the meantime, it is recommended that stakeholders in tobacco control participate in policy discussions involving marijuana legalization including regulatory measures to prevent further co-use and develop novel cessation treatments to help co-users who may have a harder time with quitting. Substance use disorders, hazardous drinking and mental illness all peak in prevalence in early adulthood, yet few young adults receive appropriate services. For example, the 2011 National Household Survey on Drug Use and Health found that the 1-year prevalence of illicit drug or alcohol abuse or dependence increased from 7 % among 12–17 year olds to 19 % for 18–25 year olds, decreasing to 6 % for individuals over 25. The same report found that adults ages 18–25 had higher rates of mental illness and were less likely to receive treatment in the prior year than older adults. Alcohol use can adversely impact symptom severity and treatment of co-occurring mental illness. Reduced response to antidepressants and increased risk of side effects have been reported with even moderate levels of alcohol use. In the STAR*D depression treatment cohort, individuals with major depressive disorder and co-occurring substance use disorders had earlier onset of depression, greater severity and functional impairment, and higher rates of suicide attempts and completed suicide. Similarly, while many individuals with anxiety disorders use alcohol for short-term symptom relief, drinking can ultimately make anxiety more severe. These associations highlight the need to assess alcohol and drug use patterns among young adults with mental health problems, in order to understand potential symptom exacerbation and medication interaction risks. Assessment could also help to identify which individuals may benefit from psychiatry-based brief interventions to reduce harmful drinking patterns, and who should be referred to specialty care addiction treatment. Apart from the potential value of brief interventions, screening provides benchmark medical record data at intake to help providers track potential changes in drinking over time. Some studies suggest that screening alone could help to reduce drinking. In the clinician’s guide to identifying and treating drinking problems in health care settings, the National Institutes on Alcohol Abuse and Alcoholism recommends asking how many times in the past year individuals have had 5 or more drinks for men and 4 or more for women. In 2009 Smith et al., reported a sensitivity of 88 % and specificity 67 % of this cutoff in detecting a current in a primary care setting. Using the Alcohol Use Disorders Identification Test as reference, Massey et al. reported 96 % sensitivity and 82 % specificity of screening question to detect harmful drinking in an alert non-psychotic consult-liaison population.
In the present study we used a similar cutoff drawn from electronic health record intake data in a psychiatry clinic setting to examine prevalence and correlates of hazardous drinking in young adults. The same cutoff was used for both sexes as this was the information available from the data, which was based on a graduated frequency measure that did not adjust quantities based on sex. Although young adults are at high risk for alcohol related problems, studies evaluating drinking patterns and their association with clinical characteristics are lacking. This study evaluated self-reported alcohol use patterns and the association between prior-year hazardous drinking and potentially relevant patient characteristics, including gender, age, clinician-assigned psychiatric diagnosis, and other substance use in a sample of young adults presenting for initial mental health treatment. We hypothesized that prior-year hazardous drinking would be associated with an AUD diagnosis, with other common psychiatric diagnoses, in particular, anxiety and depression, and with other types of substance use prevalent in this population such as tobacco and marijuana.Study participants were adults ages 18–25 seeking psychiatric services in an outpatient clinic in a university medical center. This clinic provides a range of assessment and treatment services, including medication management and individual and group psychotherapy. The clinic has no formal services for patients primarily seeking alcohol or drug treatment. Individuals seeking such services are pre-screened by telephone by clinic staff and referred to local specialty care programs. The sample included all individuals who presented to the clinic for initial evaluation between September 14th, 2005 and June 29th, 2011, were between the ages of 18 and 25 at intake, and completed routine computerized questionnaires, including a self-administered Electronic Health Inventory, Beck Depression InventoryII and a clinical interview. Other than age range and intake dates, there were no exclusion criteria. The EHI was completed on private computers in the clinic waiting area. It included questions about demographic characteristics, current and past medical history, and patterns of substance use for alcohol, cannabis and tobacco. For each substance, participants were asked if they had ever used that substance during their lifetime. Positive responses prompted questions on duration and frequently of use. Providers received a printed copy of the EHI questionnaire results for use in evaluation of new patients at intake. The University of California, San Francisco Committee on Human Research approved the study, including the examination of de-identified records of patients who had an initial clinic visit during the study time period. Participants who endorsed any lifetime alcohol or cannabis/marijuana use were asked the timing of most recent use prior to intake. Alcohol use questions included usual quantity consumed per occasion , frequency of use in the past 30 days and number of days in the past year when 1–2, 3–4, 5–7, and ≥8 drinks were consumed on one occasion.
Combining the responses of any consumption of 5–7 or ≥8 drinks consumed on one occasion in the past year, hazardous drinking was defined for this analysis as any past-year consumption of 5 or more drinks on one occasion, consistent with the definition used by the NHIS during the same time period. While NIAAA currently recommends a different cut-off for hazardous drinking in men and women , data were not available to assess this distinction.By chart review, we obtained all assigned Diagnostic and Statistical Manual of Mental Disorder, Fourth Edition Text Revision diagnoses listed on each participants’ standardized initial intake evaluation form, as assigned and documented by the clinician. Blinded to responses on the EHI, a study research assistant reviewed and coded all listed diagnoses. We coded only definite diagnoses, excluding “rule out” diagnoses.We coded drug use disorder positive if abuse or dependence was diagnosed for the following drugs: amphetamine, cannabis, opiates, methamphetamine, mushrooms, benzodiazepines, cocaine, stimulants, or if poly substance abuse was diagnosed. Given the young age of the sample, disorders in remission would still be temporally relatively recent. Therefore,cannabis grow setup no distinction was made between diagnoses in remission or active. We coded alcohol use disorder positive if alcohol abuse or dependence was diagnosed. Likewise, no distinction was made between diagnoses in remission or still active. We coded depressive disorder positive if major depressive disorder, dysthymia, or depression not otherwise specified was diagnosed. Similarly, we coded an anxiety disorder if anxiety disorder NOS, generalized anxiety disorder, social anxiety disorder, panic disorder, specific phobia, post-traumatic stress disorder or obsessive compulsive disorder was diagnosed. We coded bipolar disorder positive if bipolar affective disorder type I, II or NOS was diagnosed. We coded psychotic disorder positive if schizophrenia, schizo affective disorder, delusional disorder or psychosis NOS was diagnosed. We coded attention deficit hyperactivity disorder positive if ADHD or ADHD NOS was diagnosed. We coded eating disorder positive if anorexia, bulimia or eating disorder NOS was diagnosed.We linked self-reported demographic and substance use data from the EHI to diagnostic data from the chart review to create a single dataset for analysis. We compared differences in alcohol use rates between men and women using the χ2 test, and differences in BDI-II score and mean quantity of alcohol consumed between women and men using t tests. Similarly, using χ2 tests for categorical variables and t tests for continuous variable, rates of alcohol, tobacco and marijuana use, as well as rates of specific psychiatric diagnoses at intake were examined by prior-year hazardous drinking. Underage alcohol use was also examined . Given that participants could be assigned several diagnoses at intake, individual diagnoses were not included in regression models . Instead, we assessed diagnostic burden as indicated by the number of diagnoses assigned at intake. We used a single logistic regression model to test the association between number of psychiatric diagnoses, any lifetime use of tobacco and cannabis, age, race/ethnicity and gender as potential predictors of participants reporting any hazardous drinking in the prior year. We used STATA version 13 for all analyses.Overall, rates and frequency of alcohol, tobacco and marijuana use were significantly greater in those who endorsed hazardous drinking in the prior 12 months compared to those who didn’t . Rates of AUDs were four times greater among those who endorsed hazardous drinking in the prior 12 months, compared to those who didn’t . Rate of psychotic disorders among those who endorsed prior 12-month hazardous drinking were less frequent compared to those who denied hazardous drinking in the prior 12 months. There were no significant differences in the rates of other psychiatric disorders among those who did and those who did not endorse hazardous drinking in the prior 12 months.The single model included number of diagnoses at intake, age, gender, race, and any lifetime marijuana or tobacco use. Variables positively associated with prior-year hazardous drinking included lifetime marijuana use , lifetime tobacco use and older age .