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Objective: Cannabis use disorder diagnoses are increasing among U.S. adults and are more prevalent among people with comorbid psychiatric disorders. Recent changes in cannabis laws, increasing cannabis availability, and higher-potency cannabis may have placed people with cannabis use and psychiatric disorders at disproportionately increasing risk for cannabis use disorder. The authors used Veterans Health Administration (VHA) data to examine whether trends in cannabis use disorder prevalence among VHA patients differ by whether they have psychiatric disorders., Methods: VHA electronic health records from 2005 to 2019 (N range, 4,332,165-5,657,277) were used to identify overall and age-group-specific (<35, 35-64, and ≥65 years) trends in prevalence of cannabis use disorder diagnoses among patients with depressive, anxiety, posttraumatic stress, bipolar, or psychotic spectrum disorders and to compare these to corresponding trends among patients without any of these disorders. Given transitions in ICD coding, differences in trends were tested within two periods: 2005-2014 (ICD-9-CM) and 2016-2019 (ICD-10-CM)., Results: Greater increases in prevalence of cannabis use disorder diagnoses were observed among patients with psychiatric disorders compared to those without (difference in prevalence change, 2005-2014: 1.91%, 95% CI=1.87-1.96; 2016-2019: 0.34%, 95% CI=0.29-0.38). Disproportionate increases in cannabis use disorder prevalence among patients with psychiatric disorders were greatest among those under age 35 between 2005 and 2014, and among those age 65 or older between 2016 and 2019. Among patients with psychiatric disorders, the greatest increases in cannabis use disorder prevalences were observed among those with bipolar and psychotic spectrum disorders., Conclusions: The findings highlight disproportionately increasing disparities in risk of cannabis use disorder among VHA patients with common psychiatric disorders. Greater public health and clinical efforts are needed to monitor, prevent, and treat cannabis use disorder in this population., Competing Interests: Dr. Saxon receives royalties from UpToDate. Dr. Hasin has received support from Syneos Health.The other authors report no financial relationships with commercial interests.

Background: Cannabis use disorder is associated with considerable comorbidity and impairment in functioning, and prevalence is increasing among adults with chronic pain. We aimed to assess the effect of introduction of medical cannabis laws (MCL) and recreational cannabis laws (RCL) on the increase in cannabis use disorder among patients in the US Veterans Health Administration (VHA)., Methods: Data from patients with one or more primary care, emergency, or mental health visit to the VHA in 2005-19 were analysed using 15 repeated cross-sectional VHA electronic health record datasets (ie, one dataset per year). Patients in hospice or palliative care were excluded. Patients were stratified as having chronic pain or not using an American Pain Society taxonomy of painful medical conditions. We used staggered-adoption difference-in-difference analyses to estimate the role of MCL and RCL enactment in the increases in prevalence of diagnosed cannabis use disorder and associations with presence of chronic pain, accounting for the year that state laws were enacted. We did this by fitting a linear binomial regression model stratified by pain, with time-varying cannabis law status, fixed effects for state, categorical year, time-varying state-level sociodemographic covariates, and patient covariates (age group [18-34 years, 35-64 years, and 65-75 years], sex, and race and ethnicity)., Findings: Between 2005 and 2019, 3 234 382-4 579 994 patients were included per year. Among patients without pain in 2005, 5·1% were female, mean age was 58·3 (SD 12·6) years, and 75·7%, 15·6%, and 3·6% were White, Black, and Hispanic or Latino, respectively. In 2019, 9·3% were female, mean age was 56·7 (SD 15·2) years, and 68·1%, 18·2%, and 6·5% were White, Black, and Hispanic or Latino, respectively. Among patients with pain in 2005, 7·1% were female, mean age was 57·2 (SD 11·4) years, and 74·0%, 17·8%, and 3·9% were White, Black, and Hispanic or Latino, respectively. In 2019, 12·4% were female, mean age was 57·2 (SD 13·8) years, and 65·3%, 21·9%, and 7·0% were White, Black, and Hispanic or Latino, respectively. Among patients with chronic pain, enacting MCL led to a 0·135% (95% CI 0·118-0·153) absolute increase in cannabis use disorder prevalence, with 8·4% of the total increase in MCL-enacting states attributable to MCL. Enacting RCL led to a 0·188% (0·160-0·217) absolute increase in cannabis use disorder prevalence, with 11·5% of the total increase in RCL-enacting states attributable to RCL. In patients without chronic pain, enacting MCL and RCL led to smaller absolute increases in cannabis use disorder prevalence (MCL: 0·037% [0·027-0·048], 5·7% attributable to MCL; RCL: 0·042% [0·023-0·060], 6·0% attributable to RCL). Overall, associations of MCL and RCL with cannabis use disorder were greater in patients with chronic pain than in patients without chronic pain., Interpretation: Increasing cannabis use disorder prevalence among patients with chronic pain following state legalisation is a public health concern, especially among older age groups. Given cannabis commercialisation and widespread public beliefs about its efficacy, clinical monitoring of cannabis use and discussion of the risk of cannabis use disorder among patients with chronic pain is warranted., Funding: NIDA grant R01DA048860, New York State Psychiatric Institute, and the VA Centers of Excellence in Substance Addiction Treatment and Education., Competing Interests: Declaration of interests DSH receives support from Syneos Health for an unrelated project. JLG reports consulting fees from Hoffman-La Roche, a patent pending (use of glecaprevir and pibrentasvir for the treatment of post-traumatic stress disorder), and participation on a data safety monitoring board or advisory board for National Institute of Mental Health (using machine learning to optimise user engagement and clinical response to digital mental health interventions). SSM serves on the Board of Directors for the College on Problems of Drug Dependence. AJS has received consulting fees from Indivior, travel support from Alkermes, research support from MedicaSafe, and royalties from UpTo-Date. KMK has served as an expert witness in litigation. All other authors declare no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Abstract: In the United States, cannabis is increasingly used to manage chronic pain. Veterans Health Administration (VHA) patients are disproportionately affected by pain and may use cannabis for symptom management. Because cannabis use increases the risk of cannabis use disorders (CUDs), we examined time trends in CUD among VHA patients with and without chronic pain, and whether these trends differed by age. From VHA electronic health records from 2005 to 2019 (∼4.3-5.6 million patients yearly), we extracted diagnoses of CUD and chronic pain conditions ( International Classification of Diseases [ ICD ]- 9-CM , 2005-2014; ICD-10-CM , 2016-2019). Differential trends in CUD prevalence overall and age-stratified (<35, 35-64, or ≥65) were assessed by any chronic pain and number of pain conditions (0, 1, or ≥2). From 2005 to 2014, the prevalence of CUD among patients with any chronic pain increased significantly more (1.11%-2.56%) than those without pain (0.70%-1.26%). Cannabis use disorder prevalence increased significantly more among patients with chronic pain across all age groups and was highest among those with ≥2 pain conditions. From 2016 to 2019, CUD prevalence among patients age ≥65 with chronic pain increased significantly more (0.63%-1.01%) than those without chronic pain (0.28%-0.47%) and was highest among those with ≥2 pain conditions. Over time, CUD prevalence has increased more among VHA patients with chronic pain than other VHA patients, with the highest increase among those age ≥65. Clinicians should monitor symptoms of CUD among VHA patients and others with chronic pain who use cannabis, and consider noncannabis therapies, particularly because the effectiveness of cannabis for chronic pain management remains inconclusive., (Copyright © 2023 International Association for the Study of Pain.)

Importance: Cannabis use disorder (CUD) is increasing among US adults. Few national studies have addressed the role of medical cannabis laws (MCLs) and recreational cannabis laws (RCLs) in these increases, particularly in patient populations with high rates of CUD risk factors., Objective: To quantify the role of MCL and RCL enactment in the increases in diagnosed CUD prevalence among Veterans Health Administration (VHA) patients from 2005 to 2019., Design, Setting, and Participants: Staggered-adoption difference-in-difference analyses were used to estimate the role of MCL and RCL in the increases in prevalence of CUD diagnoses, fitting a linear binomial regression model with fixed effects for state, categorical year, time-varying cannabis law status, state-level sociodemographic covariates, and patient age group, sex, and race and ethnicity. Patients aged 18 to 75 years with 1 or more VHA primary care, emergency department, or mental health visit and no hospice/palliative care within a given calendar year were included. Time-varying yearly state control covariates were state/year rates from American Community Survey data: percentage male, Black, Hispanic, White, 18 years or older, unemployed, income below poverty threshold, and yearly median household income. Analysis took place between February to December 2022., Main Outcomes and Measures: As preplanned, International Classification of Diseases, Clinical Modification, ninth and tenth revisions, CUD diagnoses from electronic health records were analyzed., Results: The number of individuals analyzed ranged from 3 234 382 in 2005 to 4 579 994 in 2019. Patients were largely male (94.1% in 2005 and 89.0% in 2019) and White (75.0% in 2005 and 66.6% in 2019), with a mean (SD) age of 57.0 [14.4] years. From 2005 to 2019, adjusted CUD prevalences increased from 1.38% to 2.25% in states with no cannabis laws (no CLs), 1.38% to 2.54% in MCL-only enacting states, and 1.39% to 2.56% in RCL-enacting states. Difference-in-difference results indicated that MCL-only enactment was associated with a 0.05% (0.05-0.06) absolute increase in CUD prevalence, ie, that 4.7% of the total increase in CUD prevalence in MCL-only enacting states could be attributed to MCLs, while RCL enactment was associated with a 1.12% (95% CI, 0.10-0.13) absolute increase in CUD prevalence, ie, that 9.8% of the total increase in CUD prevalence in RCL-enacting states could be attributed to RCLs. The role of RCL in the increases in CUD prevalence was greatest in patients aged 65 to 75 years, with an absolute increase of 0.15% (95% CI, 0.13-0.17) in CUD prevalence associated with RCLs, ie, 18.6% of the total increase in CUD prevalence in that age group., Conclusions and Relevance: In this study of VHA patients, MCL and RCL enactment played a significant role in the overall increases in CUD prevalence, particularly in older patients. However, consistent with general population studies, effect sizes were relatively small, suggesting that cumulatively, laws affected cannabis attitudes diffusely across the country or that other factors played a larger role in the overall increases in adult CUD. Results underscore the need to screen for cannabis use and CUD and to treat CUD when it is present.

Objective: In the United States, adult cannabis use has increased over time, but less information is available on time trends in cannabis use disorder. The authors used Veterans Health Administration (VHA) data to examine change over time in cannabis use disorder diagnoses among veterans, an important population subgroup, and whether such trends differ by age group (&lt;35 years, 35-64 years, ≥65 years), sex, or race/ethnicity., Methods: VHA electronic health records from 2005 to 2019 (range of Ns per year, 4,403,027-5,797,240) were used to identify the percentage of VHA patients seen each year with a cannabis use disorder diagnosis (ICD-9-CM, January 1, 2005-September 30, 2015; ICD-10-CM, October 1, 2015-December 31, 2019). Trends in cannabis use disorder diagnoses were examined by age and by race/ethnicity and sex within age groups. Given the transition in ICD coding, differences in trends were tested within two periods: 2005-2014 (ICD-9-CM) and 2016-2019 (ICD-10-CM)., Results: In 2005, the percentages of VHA patients diagnosed with cannabis use disorder in the &lt;35, 35-64, and ≥65 year age groups were 1.70%, 1.59%, and 0.03%, respectively; by 2019, the percentages had increased to 4.84%, 2.86%, and 0.74%, respectively. Although the prevalence of cannabis use disorder was consistently higher among males than females, between 2016 and 2019, the prevalence increased more among females than males in the &lt;35 year group. Black patients had a consistently higher prevalence of cannabis use disorder than other racial/ethnic groups, and increases were greater among Black than White patients in the &lt;35 year group in both periods., Conclusions: Since 2005, diagnoses of cannabis use disorder have increased substantially among VHA patients, as they have in the general population and other patient populations. Possible explanations warranting investigation include decreasing perception of risk, changing laws, increasing cannabis potency, stressors related to growing socioeconomic inequality, and use of cannabis to self-treat pain. Clinicians and the public should be educated about the increases in cannabis use disorder in general in the United States, including among patients treated at the VHA.

Objective: The authors sought to determine the association of cannabis indicators with self-reported psychotic disorders in the U.S. general population., Methods: Participants were from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; 2001-2002; N=43,093) and NESARC-III (2012-2013; N=36,309). Logistic regression was used to estimate standardized prevalences of past-year self-reported psychotic disorders within each survey and to evaluate the association of past-year self-reported psychotic disorders with indicators of nonmedical cannabis use (any use; frequent use [at least three times/week], daily/near-daily use, and DSM-IV cannabis use disorder) compared with those with no past-year nonmedical cannabis use. Whether the strength of associations differed between surveys was indicated by difference-in-difference tests (between-survey contrasts) and ratios of odds ratios between surveys., Results: Self-reported psychotic disorders were significantly more prevalent among participants with any nonmedical cannabis use than those without (2001-2002: 1.65% compared with 0.27%; 2012-2013: 1.89% compared with 0.68%). In 2001-2002, self-reported psychotic disorders were unrelated to either frequent use or daily/near-daily use. However, in 2012 - 2013, compared with nonusers, self-reported psychotic disorders were more common among participants with frequent use and those with daily/near-daily nonmedical cannabis use (2012-2013: 2.79% and 2.52%, respectively, compared with 0.68% among nonusers). Self-reported psychotic disorders were significantly more prevalent among participants with cannabis use disorder than nonusers in both surveys (2001-2002: 2.55% compared with 0.27%; 2012 - 2013: 3.38% compared with 0.68%). The strength of these associations did not change over time., Conclusions: Data from the U.S. general population, especially more recent data, suggest associations between self-reported psychotic disorder and frequent nonmedical cannabis use and cannabis use disorder. Clinicians and policy makers should consider these relationships when monitoring patients and formulating programs.

Background: In clinical trials of pharmacotherapy for substance use, abstinence is the primary endpoint accepted by regulatory agencies. However, this endpoint could be overly restrictive, impeding efforts to identify effective medications for cocaine use disorder. To examine non-abstinent gradations in cocaine use as potential indicators of improvement, we investigated the relationship of frequency of cocaine use to clinical correlates in national survey data., Methods: Lifetime cocaine users (n = 2501) were interviewed in the National Epidemiological Survey on Alcohol and Related Conditions (NESARC) in 2001-2002 and re-interviewed in 2004-2005. Adjusted odds ratios (aORs) indicated associations between heaviest frequency of cocaine use and use of other substances, DSM-IV substance use disorders, psychiatric disorders, and change between 2001-2002 and 2004-2005. The reference category for all aORs was non-users., Results: Greater lifetime cocaine use frequency was associated with lifetime cocaine, alcohol, and cannabis dependence (aOR for a linear trend = 2.80, 1.22, 1.22, respectively) and past-year cocaine, alcohol, and cannabis dependence (aOR = 1.78, 1.13, 1.16, respectively). Greater lifetime cocaine use frequency was associated with past-year depressive, panic, and generalized anxiety disorders (aOR = 1.07, 1.09, 1.12, respectively). Among cocaine users in 2001-2002, compared to the reference group using less than monthly, use ≥1x/week and use 1-3 times a month was associated with cocaine use disorder in 2004-2005 (aOR = 2.13 and aOR = 1.67, respectively)., Conclusion: Gradations in risk for dependence on cocaine, other substances and psychiatric disorders by frequency of cocaine use indicates a promising direction for more sensitive outcome measures of treatment effects on cocaine outcomes than binary indicators (e.g., any use vs. none). Study results add to findings suggesting that non-abstinent measures might be useful indicators of treatment efficacy in clinical trials., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Marijuana use may increase schizophrenia risk, and this effect may be genetically moderated. We investigated how hypothetical genetic test results indicating the presence or absence of heightened schizophrenia risk in reaction to marijuana use would affect attitudes toward marijuana use. In two experiments, participants were randomized to hypothetical scenarios in which genetic testing showed the presence or absence of a predisposition for marijuana use to increase their schizophrenia risk, or to a control condition with no mention of genetic testing. Experiment 1 used a sample of 801 U.S. young adults recruited via Amazon.com's Mechanical Turk platform. Experiment 2 replicated the same procedures with a nationally representative sample of 800 U.S. adults aged 18-30. In Experiment 1, those in the predisposition condition, compared to the control condition, rated the likelihood and importance of their avoiding marijuana as significantly higher, whereas those in the no-predisposition condition rated both as significantly lower. In experiment 2, these findings were largely replicated for the predisposition condition but not the no-predisposition condition, and prior marijuana use was a significant moderator, with the effects of the predisposition condition confined to participants who reported having used marijuana. If these results are predictive of responses to actual genetic testing, they suggest that genetic test results indicating that marijuana use will increase one's schizophrenia risk may incentivize abstinence, especially for those with prior marijuana use. Future research could further investigate whether genetic test results indicating the absence of such a predisposition might disincentivize abstinence from marijuana use., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Objective: Given changes in U.S. marijuana laws, attitudes, and use patterns, individuals with pain may be an emerging group at risk for nonmedical cannabis use and cannabis use disorder. The authors examined differences in the prevalence of nonmedical cannabis use and cannabis use disorder among U.S. adults with and without pain, as well as whether these differences widened over time., Methods: Data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC, 2001-2002; N=43,093) and NESARC-III (2012-2013; N=36,309) were analyzed using logistic regression. Risk differences of past-year nonmedical cannabis use, frequent (at least three times a week) nonmedical use, and DSM-IV cannabis use disorder were estimated for groups with and without moderate to severe pain, and these risk differences were tested for change over time., Results: Any nonmedical cannabis use was more prevalent in respondents with than without pain (2001-2002: 5.15% compared with 3.74%; 2012-2013: 12.42% compared with 9.02%), a risk difference significantly greater in the 2012-2013 data than in the 2001-2002 data. The prevalence of frequent nonmedical cannabis use did not differ by pain status in the 2001-2002 survey, but was significantly more prevalent in those with than without pain in the 2012-2013 survey (5.03% compared with 3.45%). Cannabis use disorder was more prevalent in respondents with than without pain (2001-2002: 1.77% compared with 1.35%; 2012-2013: 4.18% compared with 2.74%), a significantly greater risk difference in the data from 2012-2013 than from 2001-2002., Conclusions: The results suggest that adults with pain are a group increasingly vulnerable to adverse cannabis use outcomes, warranting clinical and public health attention to this risk. Psychiatrists and other health care providers treating patients with pain should monitor such patients for signs and symptoms of cannabis use disorder.

Importance: Little is known about changes in marijuana use and cannabis use disorder (CUD) after recreational marijuana legalization (RML)., Objectives: To examine the associations between RML enactment and changes in marijuana use, frequent use, and CUD in the United States from 2008 to 2016., Design, Setting, and Participants: This survey study used repeated cross-sectional survey data from the National Survey on Drug Use and Health (2008-2016) conducted in the United States among participants in the age groups of 12 to 17, 18 to 25, and 26 years or older., Interventions: Multilevel logistic regression models were fit to obtain estimates of before-vs-after changes in marijuana use among respondents in states enacting RML compared to changes in other states., Main Outcomes and Measures: Self-reported past-month marijuana use, past-month frequent marijuana use, past-month frequent use among past-month users, past-year CUD, and past-year CUD among past-year users., Results: The study included 505 796 respondents consisting of 51.51% females and 77.24% participants 26 years or older. Among the total, 65.43% were white, 11.90% black, 15.36% Hispanic, and 7.31% of other race/ethnicity. Among respondents aged 12 to 17 years, past-year CUD increased from 2.18% to 2.72% after RML enactment, a 25% higher increase than that for the same age group in states that did not enact RML (odds ratio [OR], 1.25; 95% CI, 1.01-1.55). Among past-year marijuana users in this age group, CUD increased from 22.80% to 27.20% (OR, 1.27; 95% CI, 1.01-1.59). Unmeasured confounders would need to be more prevalent in RML states and increase the risk of cannabis use by 1.08 to 1.11 times to explain observed results, indicating results that are sensitive to omitted variables. No associations were found among the respondents aged 18 to 25 years. Among respondents 26 years or older, past-month marijuana use after RML enactment increased from 5.65% to 7.10% (OR, 1.28; 95% CI, 1.16-1.40), past-month frequent use from 2.13% to 2.62% (OR, 1.24; 95% CI, 1.08-1.41), and past-year CUD from 0.90% to 1.23% (OR, 1.36; 95% CI, 1.08-1.71); these results were more robust to unmeasured confounding. Among marijuana users in this age group, past-month frequent marijuana use and past-year CUD did not increase after RML enactment., Conclusions and Relevance: This study's findings suggest that although marijuana legalization advanced social justice goals, the small post-RML increase in risk for CUD among respondents aged 12 to 17 years and increased frequent use and CUD among adults 26 years or older in this study are a potential public health concern. To undertake prevention efforts, further studies are warranted to assess how these increases occur and to identify subpopulations that may be especially vulnerable.

Background: The prevalence of cigarette smoking is nearly three times higher among persons who use cannabis and have cannabis use disorders (CUDs), relative to those who do not. The current study examined cigarette quit ratios from 2002 to 2016 among US adults with and without cannabis use and CUDs., Methods: The current study analysed US adults aged 18 years and older from the National Survey on Drug Use and Health, an annual cross-sectional study. Quit ratios (ie, proportion of former smokers among ever-smokers) were calculated annually from 2002 to 2016. Time trends in quit ratios by cannabis use/CUDs were tested using logistic regression., Results: In 2016, the quit ratios for people with any cannabis use (23%) and CUDs (15%) were less than half the quit ratios of those without cannabis use and CUDs (51% and 48%, respectively). After controlling for demographics and substance use disorders, the quit ratio did not change from 2002 to 2016 among persons with CUD, though it non-linearly increased among persons with cannabis use, without cannabis use and without CUDs. Quit ratios increased more rapidly among those who reported past-month cannabis use compared with those without past-month cannabis use., Conclusions: Cigarette smoking quit ratios remain dramatically lower among people who use cannabis and have CUDs and quit ratios did not change significantly from 2002 to 2016 among those with CUDs. Public health and clinical attention are needed to increase quit ratios and reduce harmful cigarette smoking consequences for persons with cannabis use and CUDs., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: Mental health and substance use problems are associated with smoking relapse among former smokers. Yet, little is known about the prevalence of mental health and substance use among former smokers in the U.S. In addition, it is unknown whether the prevalence of these conditions has changed over time as former U.S. smokers have grown to outnumber current U.S. smokers. This study, which was conducted in 2018 and 2019, examined the prevalence and trends over time in depression (2005-2016), marijuana use (2002-2016), and alcohol use problems (2002-2016) among former U.S. smokers., Methods: The National Survey on Drug Use and Health is an annual, nationally representative, cross-sectional study. Data from U.S. individuals who were aged ≥18 years in 2002-2016 were included. Former smokers were defined as having smoked ≥100 lifetime cigarettes and no past-year cigarettes., Results: From 2005 to 2016, the prevalence of major depression increased from 4.88% to 6.04% (AOR=1.01, 95% CI=1.00, 1.03, p=0.04). From 2002 to 2016, past-year marijuana use rose from 5.35% to 10.09% (AOR=1.08, 95% CI=1.07, 1.09, p<0.001) among former smokers. Past-month binge alcohol use also increased from 17.22% to 22.33% (AOR=1.03, 95% CI=1.02, 1.04, p<0.001), although the prevalence of past-year alcohol abuse or dependence did not change., Conclusions: Depression and substance use, which are factors associated with increased risk for cigarette use relapse, appear to be increasing over time among former U.S. smokers. Increased awareness of these trends may be important for clinical and public health efforts to direct attention to conditions potentially threatening sustained abstinence among former smokers., (Copyright © 2019 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Background: Cannabis use is on the rise in the United States (US) and is disproportionately common among cigarette smokers. Cannabis use disorder (CUD) occurs among a small subset of cannabis users and may impact cigarette use. The objective of this study was to estimate trends in the prevalence of CUD among daily, non-daily, former, and never cigarette smokers from 2002 to 2016., Methods: Data were drawn from cross-sectional, nationally representative samples of individuals ages 12 and older in the US that were collected annually. The prevalence of past 12-month CUD was estimated each year from 2002 to 2016 among daily, non-daily, former, and never cigarette smokers (total analytic N = 837,326)., Results: Overall, the prevalence of CUD decreased from 2002 to 2016. Yet, trends differed by cigarette smoking status. Adjusting for demographics, the prevalence of CUD increased significantly among non-daily smokers (aOR = 1.02; 95% CI = 1.01-1.03) from 2002 to 2016 and did not change among daily, former, or never smokers. CUD was significantly more common among non-daily (4.32%) and daily cigarette smokers (2.92%) compared with former (0.99%) and never smokers (1.11%) in 2016. Approximately one in five (18.11%-22.87%) youth ages 12-17 who smoke cigarettes met criteria for CUD in 2016, compared with approximately 2% of non-smoking youth., Conclusions: Despite downward trends in CUD observed at the general population level, the prevalence of CUD significantly increased among non-daily cigarette smokers from 2002 to 2016. In the US, CUD remains significantly higher among cigarette smokers relative to non-cigarette smokers., (Copyright © 2018. Published by Elsevier B.V.)

Background: National trends in adolescent's marijuana risk perceptions are traditionally used as a predictor of concurrent and future trends in adolescent marijuana use. We test the validity of this practice during a time of rapid marijuana policy change., Methods: Two repeated cross-sectional U.S. nationally-representative surveys of 8th, 10th, and 12th-graders: Monitoring the Future (MTF) (1991-2015; N = 1,181,692) and National Survey on Drug Use and Health (NSDUH) (2002-2014; N = 113,317). We examined trends in the year-to-year prevalence of perceiving no risk of harm in using marijuana regularly, and prevalence of regular marijuana use within the previous month. A piecewise linear regression model tested for a change in the relationship between trends. Similar analyses examined any past-month use and controlled for demographic characteristics., Results: Among MTF 12th-graders, the prevalence of regular marijuana use and risk perceptions changed similarly between 1991 and 2006 but diverged sharply afterward. The prevalence of regular marijuana use increased by ∼1 percentage point to 6.03% by 2015. In contrast, the proportion of 12th-graders that perceived marijuana as posing no risk increased over 11 percentage points to 21.39%. A similar divergence was found among NSDUH 12th-graders and other grades, for any past month marijuana use, and when controlling demographic characteristics., Conclusions: An increase in adolescent marijuana use has not accompanied recent rapid decreases in marijuana risk perceptions. Policy makers may consider broader prevention strategies in addition to targeting marijuana risk perceptions. Further monitoring of predictors of marijuana use trends is needed as states legalize recreational marijuana use., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Objective: The authors sought to determine whether cannabis use is associated with a change in the risk of incident nonmedical prescription opioid use and opioid use disorder at 3-year follow-up., Method: The authors used logistic regression models to assess prospective associations between cannabis use at wave 1 (2001-2002) and nonmedical prescription opioid use and prescription opioid use disorder at wave 2 (2004-2005) of the National Epidemiologic Survey on Alcohol and Related Conditions. Corresponding analyses were performed among adults with moderate or more severe pain and with nonmedical opioid use at wave 1. Cannabis and prescription opioid use were measured with a structured interview (the Alcohol Use Disorder and Associated Disabilities Interview Schedule-DSM-IV version). Other covariates included age, sex, race/ethnicity, anxiety or mood disorders, family history of drug, alcohol, and behavioral problems, and, in opioid use disorder analyses, nonmedical opioid use., Results: In logistic regression models, cannabis use at wave 1 was associated with increased incident nonmedical prescription opioid use (odds ratio=5.78, 95% CI=4.23-7.90) and opioid use disorder (odds ratio=7.76, 95% CI=4.95-12.16) at wave 2. These associations remained significant after adjustment for background characteristics (nonmedical opioid use: adjusted odds ratio=2.62, 95% CI=1.86-3.69; opioid use disorder: adjusted odds ratio=2.18, 95% CI=1.14-4.14). Among adults with pain at wave 1, cannabis use was also associated with increased incident nonmedical opioid use (adjusted odds ratio=2.99, 95% CI=1.63-5.47) at wave 2; it was also associated with increased incident prescription opioid use disorder, although the association fell short of significance (adjusted odds ratio=2.14, 95% CI=0.95-4.83). Among adults with nonmedical opioid use at wave 1, cannabis use was also associated with an increase in nonmedical opioid use (adjusted odds ratio=3.13, 95% CI=1.19-8.23)., Conclusions: Cannabis use appears to increase rather than decrease the risk of developing nonmedical prescription opioid use and opioid use disorder.

Importance: Over the last 25 years, illicit cannabis use and cannabis use disorders have increased among US adults, and 28 states have passed medical marijuana laws (MML). Little is known about MML and adult illicit cannabis use or cannabis use disorders considered over time., Objective: To present national data on state MML and degree of change in the prevalence of cannabis use and disorders., Design, Participants, and Setting: Differences in the degree of change between those living in MML states and other states were examined using 3 cross-sectional US adult surveys: the National Longitudinal Alcohol Epidemiologic Survey (NLAES; 1991-1992), the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; 2001-2002), and the National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III; 2012-2013). Early-MML states passed MML between NLAES and NESARC ("earlier period"). Late-MML states passed MML between NESARC and NESARC-III ("later period")., Main Outcomes and Measures: Past-year illicit cannabis use and DSM-IV cannabis use disorder., Results: Overall, from 1991-1992 to 2012-2013, illicit cannabis use increased significantly more in states that passed MML than in other states (1.4-percentage point more; SE, 0.5; P = .004), as did cannabis use disorders (0.7-percentage point more; SE, 0.3; P = .03). In the earlier period, illicit cannabis use and disorders decreased similarly in non-MML states and in California (where prevalence was much higher to start with). In contrast, in remaining early-MML states, the prevalence of use and disorders increased. Remaining early-MML and non-MML states differed significantly for use (by 2.5 percentage points; SE, 0.9; P = .004) and disorder (1.1 percentage points; SE, 0.5; P = .02). In the later period, illicit use increased by the following percentage points: never-MML states, 3.5 (SE, 0.5); California, 5.3 (SE, 1.0); Colorado, 7.0 (SE, 1.6); other early-MML states, 2.6 (SE, 0.9); and late-MML states, 5.1 (SE, 0.8). Compared with never-MML states, increases in use were significantly greater in late-MML states (1.6-percentage point more; SE, 0.6; P = .01), California (1.8-percentage point more; SE, 0.9; P = .04), and Colorado (3.5-percentage point more; SE, 1.5; P = .03). Increases in cannabis use disorder, which was less prevalent, were smaller but followed similar patterns descriptively, with change greater than never-MML states in California (1.0-percentage point more; SE, 0.5; P = .06) and Colorado (1.6-percentage point more; SE, 0.8; P = .04)., Conclusions and Relevance: Medical marijuana laws appear to have contributed to increased prevalence of illicit cannabis use and cannabis use disorders. State-specific policy changes may also have played a role. While medical marijuana may help some, cannabis-related health consequences associated with changes in state marijuana laws should receive consideration by health care professionals and the public.

Aim: Concurrently with increasingly permissive attitudes towards marijuana use and its legalization, the prevalence of marijuana use has increased in recent years in the U.S. Substance use is generally more prevalent in men than women, although for alcohol, the gender gap is narrowing. However, information is lacking on whether time trends in marijuana use differ by gender, or whether socioeconomic status in the context of the Great Recession may affect these changes., Methods: Using repeated cross-sectional data from the National Survey on Drug Use and Health (2002-2014), we examined changes over time in prevalence of past-year marijuana use by gender, and whether gender differences varied across income levels. After empirically determining a change point in use in 2007, we used logistic regression to test interaction terms including time, gender, and income level., Results: Prevalence of marijuana use increased for both men (+4.0%) and women (+2.7%) from 2002 to 2014, with all of the increase occurring from 2007 to 2014. Increases were greater for men, leading to a widening of the gender gap over time (p<0.001). This divergence occurred primarily due to increased prevalence among men in the lowest income level (+6.2%) from 2007 to 2014., Conclusion: Our findings are consistent with other studies documenting increased substance use during times of economic insecurity, especially among men. Corresponding with the Great Recession and lower employment rate beginning in 2007, low-income men showed the greatest increases in marijuana use during this period, leading to a widening of the gender gap in prevalence of marijuana use over time., (Copyright © 2016. Published by Elsevier Ireland Ltd.)

Importance: With rising rates of marijuana use in the general population and an increasing number of states legalizing recreational marijuana use and authorizing medical marijuana programs, there are renewed clinical and policy concerns regarding the mental health effects of cannabis use., Objective: To examine prospective associations between cannabis use and risk of mental health and substance use disorders in the general adult population., Design, Setting, and Participants: A nationally representative sample of US adults aged 18 years or older was interviewed 3 years apart in the National Epidemiologic Survey on Alcohol and Related Conditions (wave 1, 2001-2002; wave 2, 2004-2005). The primary analyses were limited to 34 653 respondents who were interviewed in both waves. Data analysis was conducted from March 15 to November 30, 2015., Main Outcomes and Measures: We used multiple regression and propensity score matching to estimate the strength of independent associations between cannabis use at wave 1 and incident and prevalent psychiatric disorders at wave 2. Psychiatric disorders were measured with a structured interview (Alcohol Use Disorder and Associated Disabilities Interview Schedule-DSM-IV). In both analyses, the same set of wave 1 confounders was used, including sociodemographic characteristics, family history of substance use disorder, disturbed family environment, childhood parental loss, low self-esteem, social deviance, education, recent trauma, past and present psychiatric disorders, and respondent's history of divorce., Results: In the multiple regression analysis of 34 653 respondents (14 564 male [47.9% weighted]; mean [SD] age, 45.1 [17.3] years), cannabis use in wave 1 (2001-2002), which was reported by 1279 respondents, was significantly associated with substance use disorders in wave 2 (2004-2005) (any substance use disorder: odds ratio [OR], 6.2; 95% CI, 4.1-9.4; any alcohol use disorder: OR, 2.7; 95% CI, 1.9-3.8; any cannabis use disorder: OR, 9.5; 95% CI, 6.4-14.1; any other drug use disorder: OR, 2.6; 95% CI, 1.6-4.4; and nicotine dependence: OR, 1.7; 95% CI, 1.2-2.4), but not any mood disorder (OR, 1.1; 95% CI, 0.8-1.4) or anxiety disorder (OR, 0.9; 95% CI, 0.7-1.1). The same general pattern of results was observed in the multiple regression analyses of wave 2 prevalent psychiatric disorders and in the propensity score-matched analysis of incident and prevalent psychiatric disorders., Conclusions and Relevance: Within the general population, cannabis use is associated with an increased risk for several substance use disorders. Physicians and policy makers should take these associations of cannabis use under careful consideration.

Aims: To develop a comprehensive risk-factor model of cannabis use disorders (CUD) based on Kendler's development model for major depression., Design: Risk factors were divided into five developmental tiers based on Kendler's model of depression (childhood, early adolescence, late adolescence, adulthood, past year). Hierarchical logistic regression models were used to examine the independent contribution of each risk factor. Separate models were built to predict the lifetime risk of cannabis use and the risk of CUD among those with a history of lifetime risk of cannabis use., Setting: Data were drawn from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) in the United States., Participants: Participants consisted of wave 2 of the NESARC (n = 34 653)., Measurements: Odds ratios (OR), Adjusted OR (AOR) and confidence intervals (95% CI) were used to determine the risk factors in each tier and with multiple models., Findings: After mutually adjusting for the effect of other risk factors, lifetime history of drug use disorder (AOR = 4.78, 95% CI = 1.53-14.91), past year alcohol use disorders (AOR = 6.55, 95% CI = 2.54-16.89) and independent (AOR = 1.57, 95% CI = 1.15-2.14) and dependent (AOR = 1.25, 95% CI = 1.01-1.55) stressful life events predicted lifetime cannabis use. Impulsivity (AOR = 2.18, 95% CI = 1.34-3.53), past year alcohol use disorders (AOR = 4.09, 95% CI = 2.29-7.31), greater number of Axis I disorders (AOR = 1.56, 95% CI = 1.01-2.40) and social deviance (AOR = 1.19, 95% CI = 1.08-1.32) independently increased the risk of the development of CUD, whereas religious service attendance (AOR = 0.50, 95% CI = 0.30-0.85) decreased this risk. In both models, the effect of earlier development tiers was mediated by more proximal ones. There were few gender differences in both models., Conclusions: A modification of Kendler's risk factor model for major depression which stratifies risk factors into five groups (childhood, early adolescence, late adolescence, adulthood, past year) provides a useful foundation for a comprehensive developmental model of cannabis use and cannabis use disorders., (© 2013 Society for the Study of Addiction.)

Background: A number of changes have been proposed and investigated in the criteria for substance use disorders in DSM-5. However, although clinical utility of DSM-5 is a high priority, relatively little of the empirical evidence supporting the changes was obtained from samples of substance abuse patients., Methods: Proposed changes were examined in 663 patients in treatment for substance use disorders, evaluated by experienced clinicians using the Psychiatric Research Interview for Substance and Mental Disorders (PRISM). Factor and item response theory analysis was used to investigate the dimensionality and psychometric properties of alcohol, cannabis, cocaine and heroin abuse and dependence criteria, and craving., Results: The seven dependence criteria, three of the abuse criteria (hazardous use; social/interpersonal problems related to use; neglect of roles to use), and craving form a unidimensional latent trait for alcohol, cannabis, cocaine and heroin. Craving did not add significantly to the total information offered by the dependence criteria, but adding the three abuse criteria and craving together did significantly increase total information for the criteria sets associated with alcohol, cannabis and heroin., Conclusion: Among adult patients in treatment for substance disorders, the alcohol, cannabis, cocaine and heroin criteria for dependence, abuse (with the exception of legal problems), and craving measure a single underlying dimension. Results support the proposal to combine abuse and dependence into a single diagnosis in the DSM-5, omitting legal problems. Mixed support was provided for the addition of craving as a new criterion, warranting future studies of this important construct in substance use disorders., (Copyright © 2011. Published by Elsevier Ireland Ltd.)