Association Between Recreational Marijuana Legalization in the United States and Changes in Marijuana Use and Cannabis Use Disorder From 2008 to 2016 | Adolescent Medicine | JAMA Psychiatry | JAMA Network
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Table 1.  Demographic Characteristics, Self-reported Substance Use, and State Marijuana Legalization Among Study Participants, National Survey on Drug Use and Health, 2008-2016
Demographic Characteristics, Self-reported Substance Use, and State Marijuana Legalization Among Study Participants, National Survey on Drug Use and Health, 2008-2016
Table 2.  Past-Month Marijuana Use, Frequent Marijuana Use, and CUD in the Past 12 Months Among 495 796 Respondents Before vs After RML Enactment From 2008 to 2016a
Past-Month Marijuana Use, Frequent Marijuana Use, and CUD in the Past 12 Months Among 495 796 Respondents Before vs After RML Enactment From 2008 to 2016a
Table 3.  Past-Month Frequent Marijuana Use Among Users and Past-Year CUD Among Users Before vs After RML Enactment From 2008 to 2016a
Past-Month Frequent Marijuana Use Among Users and Past-Year CUD Among Users Before vs After RML Enactment From 2008 to 2016a
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    2 Comments for this article
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    An Obvious Outcome?
    Raymond Small, MD, MPH | Physicianet Consulting Group, LTD
    Is anyone actually surprised by the findings of this study/survey? The conclusions seem rather obvious to my way of thinking. Make a once illicit substance readily available for purchase and void of prior criminality--with its consequences--and more and more people are going to use and/or abuse it, invariably magnifying negative aspects of usage; warranting public health concerns. Consider stats purporting that the rates of opioid abuse and the morbidity and mortality from overdosage have decreased notably in states that have legalized recreational cannabis. Is this not a net positive; a lesser of two evils in favor of THC legalization? Calculation of a "risk versus benefit" ratio should be utilized in this still controversial and polarizing subject as much as it is in more mainstream medicine and public health agencies.
    CONFLICT OF INTEREST: None Reported
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    Prohibition and consumption
    Silver Damsen, PhD | University of Illinois, Urbana-Champaign
    I'm surprised, but then not that there is little thought about the fact that the 17-12 year-old group can't purchase legal marijuana in the first place. Thus, making marijuana more readily available through legal channels for those over 21 shouldn't impact those under 18. Teens purchased their marijuana illegally before adult legalization and are still purchasing it illegally after adult legalization. The cost of legal marijuana also tends to be significantly higher than those purchased through illegal means. So, it would not seem at all likely that adults are purchasing legal marijuana that they are then re-selling illegally to teens.

    This statistic alone should challenge the hypothesis that making a drug legal increases the chances that it will be abused. The increase is also so small as to be questionable as statistically significant in the first place.

    Thus, it makes more sense to at least consider other variables as contributing to the increase in over-consumption (that is if we assume the change is even statistically significant). If one looks at the history of prohibition, the pattern is that the more a drug is prohibited, the more dangerous its consumption tends to be. Thus, an overall increase in prohibition advertising and Just Say No campaigns are also likely contributers, as would be stress in society. To understand the last aspect Bruce Alexander's Rat Park experiments would be required reading.

    I hate to have to point this out to professional researchers, and that I do shows the pathetic state of research on drug consumption, but far too much research, including this piece here, does not look at the social history of drug consumption that prior to prohibition about 100 years ago that opioids, coca (the original form of cocaine), and marijuana were safely consumed for thousands of years. Thus, a more useful study would be what was going on around a hundred years ago that worked to create prohibition and how has prohibition impacted consumption?

    That these researchers seem entirely unfamiliar with the the data that says that prohibition increases dangerous consumption but doesn't decrease overall use. This is because the normal Supply and Demand model that justifies prohibition doesn't apply to drugs because the Demand for drugs is inelastic. Thus, while in normal conditions if the price for a commodity is increased, the Demand will go down, but this doesn't hold for drugs. Rather, if the cost is increased it just means that those that purchase the drug will suffer more to acquire it. Curiously, overall and once society has stabilized after making a formally illegal drug legal again, not only dangerous consumption but overall consumption tends to go down. However, true enough it would not be realistic to expect it to stop entirely.

    Also, relevant would be to compare this increase (which again I'm not seeing as that statistically significant) to what has been reported as the increase in alcohol over-use after the end of prohibition. For a time, consumption of alcohol showed signs of over-consumption, but this stabilized over time.

    But most relevant of all is that prohibition doesn't work. We have a hundred years of it failing to show that it doesn't work. And this study seems badly constructed from the outset simply by including those that can't purchase legal marijuana and not even attempting to discuss or define that for teens drugs will be illegal even if all prohibition ends for adults. However, it does point out that prohibition itself doesn't keep someone from getting a drug they want.
    CONFLICT OF INTEREST: None Reported
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    Original Investigation
    November 13, 2019

    Association Between Recreational Marijuana Legalization in the United States and Changes in Marijuana Use and Cannabis Use Disorder From 2008 to 2016

    Author Affiliations
    • 1Division of Epidemiology, Department of Population Health, New York University School of Medicine, New York
    • 2Violence Prevention Research Program, Department of Emergency Medicine, University of California, Davis, Sacramento
    • 3Department of Biostatistics, Columbia University Mailman School of Public Health, New York, New York
    • 4Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
    • 5Division of Translational Epidemiology, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
    • 6Division of Translational Epidemiology, New York State Psychiatric Institute, New York
    JAMA Psychiatry. 2020;77(2):165-171. doi:10.1001/jamapsychiatry.2019.3254
    Key Points

    Question  How did marijuana use and cannabis use disorder change during 2008 to 2016 after the legalization of recreational marijuana in the United States?

    Findings  In this multilevel, difference-in-difference survey study with 505 796 respondents comparing marijuana use before and after the legalization of recreational marijuana in the United States, the proportion of respondents aged 12 to 17 years reporting cannabis use disorder increased from 2.18% to 2.72%, while the proportion of respondents 26 years or older reporting frequent marijuana use increased from 2.13% to 2.62% and those with cannabis use disorder, from 0.90% to 1.23%.

    Meaning  This study’s findings suggest that possible increases in the risk for cannabis use disorder among adolescent users and increases in frequent use and cannabis use disorder among adults after legalization of recreational marijuana use may raise public health concerns and warrant ongoing study.

    Abstract

    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.

    Introduction

    Marijuana is one of the world’s most widely used psychoactive substances. Approximately 183 million people, or 3.8% of the world’s population, used marijuana in 2015.1 Although occasional marijuana use is not associated with substantial problems, long-term, heavy use is linked to psychological and physical health concerns,2-4 lower educational attainment,5 decline in social class, unemployment,6,7 and motor vehicle crashes.8,9

    In the United States, 33 states and the District of Columbia have enacted medical marijuana legalization (MML), and 11 states and the District of Columbia have enacted recreational marijuana legalization (RML). Reducing racial/ethnic inequalities in marijuana-related arrests and convictions has been a key aim of legalization. At the same time, questions have arisen about the impact of legalization on marijuana use.10 Prior studies did not find any association between MML and adolescent marijuana use11; however, they did find increases in adult past-month use and cannabis use disorder (CUD) after MML.12-19 Findings on MML may not apply to RML,20 because RML could have a broader impact through changes in pricing,21 access, acceptability,22,23 and advertising.

    Little is known about the association of RML with marijuana use and how it differs from that of MML with marijuana use. In school-based samples, one study found increased past-month adolescent use in Washington but not in Colorado after RML.24 Another study found increases in use among college students in Washington,25 while a third study found decreased marijuana use among adolescents.26 At the national level, the association of RML with marijuana use, frequent use, and CUD across age groups remains unknown. Furthermore, whether RML leads to an expansion of the pool of new marijuana users or increases problematic use among existing marijuana users is unclear.

    In this study, we addressed these gaps by comparing past-month marijuana use, frequent marijuana use, and CUD before and after RML enactment among adolescents, young adults, and adults, using data from 2008 to 2016. To distinguish the association of RML enactment with new marijuana users from that with problematic use among existing users, we examined changes in frequent marijuana use and CUD among the overall sample as well as among users. States that did not enact RML, regardless of whether they had enacted MML, were included in the analyses to control for nationwide trends in marijuana use.

    Methods
    Data

    The National Survey on Drug Use and Health (NSDUH) collects data on more than 17 500 adolescents (aged 12-17 years), 17 500 young adults (aged 18-25 years), and 18 800 adults (aged ≥26 years) on a yearly basis.27 The NSDUH uses a 50-state design and has an independent multistage area probability sample for each state, which produces state-representative estimates. Up to 2013, equal sample sizes (33%) were collected for all the age groups. Since 2014, adults 26 years or older were oversampled (25% for youth aged 12-17 years, 25% for young adults aged 18-25 years, and 50% for adults aged ≥26 years) to more accurately estimate drug use among the aging, drug-using population. This sample redesign did not change the prevalence estimates of outcome variables or the precision of the estimates between states that did and did not enact RML equally.

    In-person audio, computer-assisted self-interviews were conducted by professional field interviewers; response rates ranged from 55% to 75%,28 depending on the year.29,30 Oral informed consent was obtained from study participants for screening and interviewing. This survey study was approved by the institutional review board at the Columbia University Mailman School of Public Health, New York, New York.

    Measures

    Our primary exposure variable was the state-level enactment of RML in Colorado, Washington, Alaska, and Oregon. The date that marijuana was legalized for recreational use was determined by a review of publicly available state policies31 used in previous work on MML17,20,24,32-34 and updated in 2017. Recreational marijuana legalization was enacted in Colorado and Washington in November 2012, in Alaska in February 2015, and in Oregon in October 2015. A 3-level variable was created for each state by year, coded as 0 (never enacted RML), 1 (before RML enactment), and 2 (after RML enactment). States were coded as “after RML enactment” if they enacted the law between January 1 and June 30; if they enacted the law between July 1 and December 31, they were coded as “before RML enactment” for that year and “after RML enactment” in the following years. States that enacted RML after our study period (ie, after July 1, 2016) were coded as “before RML enactment.” Findings were unchanged when states that enacted RML after our study period were recoded as “never enacted RML.”

    Primary outcomes were past-month marijuana use, frequent use in the past month, past-year CUD overall, and past-month frequent use and past-year CUD among users in accordance with the time frames used in NSDUH. Frequent use was defined as 20 days or more of use in the past month. Respondents were classified as having CUD based on a structured instrument that assessed symptoms corresponding to DSM-IV criteria.35 Outcomes were examined separately by age group (12-17, 18-25, and ≥26 years) to examine the specific association between RML enactment and marijuana use in adolescence, young adulthood, and adulthood.

    State-level covariates included the state proportions of males, individuals of white race/ethnicity, those aged 10 to 24 years, and those older than 25 years without a high school education. State demographic information was obtained from the American Community Survey.36 Individual-level covariates included respondent age, sex, race/ethnicity, nativity (US-born or non–US-born), urbanicity, and total family income.

    Statistical Analysis

    Statistical analysis was performed between December 6, 2017, and March 14, 2019. In descriptive analyses, we calculated the prevalence of past-month marijuana use, past-month frequent marijuana use, and CUD for each year from 2008 to 2016, providing estimates of trends in marijuana use before any RML enactment (ie, 2008-2011) and after RML enactment (ie, 2013-2016 or 2015-2016, depending on the state of residence). We calculated the mean NSDUH-weighted, state-level prevalence estimates across 3 groups as follows: (1) states that never enacted RML or MML, (2) states that enacted MML but not RML during our study period, and (3) states that enacted RML and MML during our study period regardless of when legalization was enacted. Summaries were stratified by the following 3 age groups: 12 to 17, 18 to 25, and 26 years or older, consistent with the NSDUH sampling design. Missing data on demographic characteristics and substance use measures were imputed by NSDUH using the predictive mean neighbors procedure.37 Missing data on the outcome variables ranged from 0.5% (CUD) to 0.8% of the sample (past-month marijuana use and frequent marijuana use among past-month users). Listwise deletion was used to address missing data on the outcomes.

    We used a series of multilevel logistic regression models to obtain estimates of before-vs-after changes in marijuana outcomes associated with changes in RML enactment after controlling for contemporaneous trends in the entire country. This approach is similar to a difference-in-difference analysis but accounts for the varying years of RML enactment by state. Because NSDUH study participants were nested within states, a state-level random effect was included. Outcomes were measured at the individual level. State-level RML enactment was captured using our 3-level state variable (never enacted RML, before RML enactment, and after RML enactment) as a time-varying covariate, allowing for potential differences between states that never enacted RML and those that would eventually enact RML.

    To examine whether the associations between RML enactment and marijuana use differed by age group, we included age as a 3-level variable (12-17, 18-25, and ≥26 years) and tested its interaction with our exposure variable. All models controlled for contemporaneous trends in marijuana use between 2008 and 2016 by using a piecewise cubic spline function of year with a knot at 2011.38 In addition, all models controlled for individual- and state-level covariates to account for potential remaining differences in the NSDUH respondents and in the overall state population between RML and non-RML states. Odds ratios (ORs) and 95% CIs were calculated to estimate associations. These did not include NSDUH sampling weights because the model directly incorporated all individual-level variables related to the sampling design.39 Analyses were conducted at the 5% significance level, and the testing was 2-sided. The SAS statistical software, version 9.2 (SAS Institute Inc) was used for analyses, and figures were created in R software, version 3.6.0 (R Core Team).

    Sensitivity Analysis

    Unmeasured time-invariant state differences were accounted for in our tests for before-RML vs after-RML changes in marijuana outcomes. However, to evaluate the potential association of time-varying unmeasured confounding, we calculated E-values, a type of sensitivity analysis increasingly used in epidemiologic studies.40-42 E-values indicate the minimum strength of unmeasured confounders’ association with the exposure (eg, RML enactment) and the outcome (eg, marijuana use) that could artifactually produce the observed association and lower bound of the CI if the true association were null (eTable 2 and eTable 3 in the Supplement). Small E-values (lowest possible is a value of 1.0) suggest that unmeasured confounding may account for observed associations; larger E-values indicate results that are increasingly robust to unmeasured confounding. E-values were obtained using the EValue package in R software, version 3.6.0.

    Results

    This study included 505 796 respondents and comprised 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. Table 1 provides additional sample characteristics. eFigures 1 to 3 in the Supplement show the descriptive trends in the prevalence of past-month marijuana use, past-month frequent marijuana use, and CUD during 2008 to 2016. After 2012 (ie, the start of the post-RML period, when Washington and Colorado enacted RML), among states that enacted RML, the slopes of past-month marijuana use for respondents 26 years or older (eFigure 1 in the Supplement) and the slopes of past-month frequent marijuana use for respondents aged 18 to 25 years and 26 years or older (eFigure 2 in the Supplement) appeared steeper than the slopes among those that enacted only MML or those that did not enact either RML or MML. The slopes of CUD (eFigure 3 in the Supplement) did not appear to differ across the 3 groups.

    Table 2 and Table 3 present the primary findings for the overall population (Table 2) and for the subset of marijuana users (Table 3). Among the 12- to 17-year-old respondents, the prevalence of past-month marijuana use and past-month frequent use following state RML enactment did not change in the overall sample or among users. However, after RML enactment, past-year CUD prevalence increased slightly among all 12- to 17-year-old respondents (2.18% to 2.72%; OR, 1.25; 95% CI, 1.01-1.55). This increase was 25% higher than that for participants in the same age group in states with no RML enactment. Among the past-year users, CUD increased from 22.80% to 27.20% (OR, 1.27; 95% CI, 1.01-1.59).

    In the group aged 18 to 25 years, no difference was found after state RML enactment in past-month marijuana use, past-month frequent use, or past-year CUD in the overall sample (Table 2) or among users (Table 3).

    Among respondents aged 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) (Table 2). Furthermore, past-month frequent use increased from 2.13% to 2.62% (OR, 1.24; 95% CI, 1.08-1.41) and past-year CUD increased from 0.90% to 1.23% (OR, 1.36; 95% CI, 1.08-1.71) (Table 2). Among users, past-month frequent use and past-year CUD did not increase (Table 3).

    Variations by age (interactions; eTable 1 in the Supplement) were found for the association between RML enactment and past-month marijuana use (F = 23.48; P < .001), past-month frequent marijuana use (F = 11.17; P < .001), and past-year CUD (F = 5.19; P < .001). Although the association of RML enactment with past-month frequent use and past-year CUD among users did not vary by age, age-group variations in the overall sample, the distinctly different levels of marijuana use in the 3 age groups (eFigures 1-3 in the Supplement), and differences in consequences associated with marijuana use by age warranted presentation of all findings stratified by age.

    Sensitivity Analysis

    eTables 2 and 3 in the Supplement present E-values. Among respondents aged 12 to 17 years old, the small E-values for the observed OR and the lower limit of the 95% CI for CUD (ie, lower CI E-values of 1.11 in the overall sample and 1.08 among past-year marijuana users) indicate that associations between unmeasured confounders and RML and between unmeasured confounders and CUD may explain the observed association between RML enactment and CUD. Among respondents aged 26 years or older, the larger E-values (ie, lower CI E-values, 1.37-1.59; eTables 2 and 3 in the Supplement) reduced the concern that unobserved confounding may explain the observed associations.

    Discussion

    In the present study, RML enactment during 2012 to 2015 was followed by a small increase in adolescent CUD and by an increase in past-month marijuana use, past-month frequent marijuana use, and past-year CUD among adults 26 years or older. Cannabis use disorder among adolescents and its associated long-term adverse health, economic, and social consequences2-6,8,9,43,44 have raised concerns about unintended consequences of legalization in this age group. The increase in past-month frequent marijuana use and CUD in the adult population is also an important public health concern because both frequent use and CUD are associated with considerable comorbidity and disability.7,45,46

    This study advances our understanding of the association of changing marijuana laws with marijuana use in 2 important ways. First, it is the first national study, to our knowledge, to examine the association of legalization of recreational marijuana use at the state level with marijuana use among adolescents, young adults, and adults. Prior studies on the consequences of RML enactment focused either on only adolescents24,26,47,48 or on single states without a comparison group.47-50 None examined the association of RML enactment with CUD, which is strongly associated with adverse health consequences.2-6,8,9,43,44 Second, this study’s findings suggest that the change in marijuana use following RML enactment may differ by age group.

    Adolescents did not exhibit increases in marijuana use or frequent use after RML enactment. Prior studies did not detect any post-MML increase in adolescent marijuana use.11,17,20,33 One study did find an increase in marijuana use after RML among 8th- and 10th-grade (but not 12th-grade) students in Washington, but not in Colorado.24 Our study builds on this prior study by using state-representative samples of adolescents in and out of school, and by examining the consequences of RML enactment in 4 states over a longer time span. Our findings on use are consistent with the availability theory: because marijuana is legal only for people 21 years or older, we would expect new users to be concentrated among those for whom access increased the most (ie, adults) and not among adolescents.51

    Among adolescent marijuana users, CUD prevalence increased slightly after RML enactment. E-value analyses suggested that unmeasured time-varying confounders hypothetically more prevalent in RML states that increase the risk of cannabis use slightly (1.08-1.11 times) may explain this finding. The extent to which such confounders exist is unclear because our difference-in-difference design accounted for unmeasured time-invariant sources of confounding and also adjusted for measured time-varying individual- and state-level demographic characteristics. However, the small E-values warrant a conservative interpretation of the increase in CUD among participants aged 12 to 17 years.

    The seriousness of the long-term consequences of CUD in adolescents suggests the need for additional study when data for more years become available. A small increase in adolescent CUD, but not in frequent use among past-month users, suggests that RML enactment may affect adolescents who are particularly vulnerable owing to a history of psychiatric comorbidity, traumatic life events, or family history of substance use disorders52 or to the increased potency of marijuana products after legalization.53

    Among young adults, RML enactment did not result in changes in past-month marijuana use, past-month frequent marijuana use, or past-year CUD. Part of this finding may be related to a ceiling effect because young adulthood is the peak developmental age for risk of substance use, including marijuana54 (eFigure 1 in the Supplement), and for several years, young adults have widely and consistently perceived marijuana to be readily available.30 Furthermore, concerns about legal problems associated with accessing marijuana may be less salient during this risk-taking phase of young adulthood, before maturing into adult roles such as jobs, marriage, and child-bearing.55 Finally, as RML allows legal access to marijuana for people 21 years or older, the lack of legal access for those aged 18 to 20 years may also partly explain the absence of an association between RML enactment and marijuana use in this age group.13,17

    In contrast, among adults 26 years or older, RML enactment resulted in increased past-month marijuana use, past-month frequent use, and past-year CUD. Mechanisms including increased availability and access to marijuana, a decrease in the price of marijuana,19,21 and changes in perceptions of risk associated with marijuana use17 may explain the increase in adult use following RML enactment, while the increased potency of marijuana products available in the legal market53 could potentially contribute to the increase in CUD. Findings are consistent with increased adult use after MML in the United States; prior studies found post-MML increases in the prevalence of marijuana use and CUD among adults.13,16,17

    The present study examined the mean of the association of RML enactment with marijuana use across the first 4 states to enact RML. Prior work on MML suggests that differences in forms of marijuana access (eg, availability and density of retail outlets), types of marijuana products available, possession limits, potency, price, and taxation regulations may moderate the association of legalization with marijuana use.51,56 As more states legalize recreational marijuana use, attention to variation by types of legalization approaches warrants analysis.

    Limitations

    This study has limitations. First, the study relied on self-reported marijuana use, and the social desirability to report use may change after legalization. However, the use of audio, computer-assisted self-interviews reduces these concerns because respondents provided confidential self-reports without interacting with an interviewer.29 Second, frequency of use and CUD are only 2 of the important dimensions of marijuana use; future studies should examine additional measures, for example, frequency within days and tetrahydrocannabinol potency in marijuana products, to comprehensively examine how RML affects marijuana use. Third, this study examined short-term changes in marijuana use after RML enactment; once data become available, future studies should examine longer-term changes in marijuana use, for example, after commercialization. Fourth, NSDUH uses DSM-IV criteria to measure CUD rather than the current DSM-5 criteria. Hence, the CUD definition does not include cravings or cannabis withdrawal. Fifth, NSDUH excludes people who are homeless or residing in institutions, potentially underestimating the prevalence of marijuana use and related disorders.

    Conclusions

    We believe that this study offers a novel, major step forward in understanding the changes in marijuana use that may follow the legalization of recreational marijuana use in the United States. The study’s many strengths included large, nationally representative samples across multiple years and major age groups, a survey design that produces accurate state-level estimates, and use of comprehensive measures and advanced statistical methods. Legalization of recreational marijuana use has the potential to provide important social benefits, particularly around issues of equity in criminal justice. However, the potential for frequent use and CUD is an important public health concern that warrants ongoing study and investment in substance use prevention and treatment to prevent unintended harm.

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    Article Information

    Accepted for Publication: August 19, 2019.

    Corresponding Author: Magdalena Cerdá, DrPH, Division of Epidemiology, Department of Population Health, New York University School of Medicine, 180 Madison Ave, Fourth Floor (4-16), New York, NY 10016 (magdalena.cerda@nyumc.org).

    Published Online: November 13, 2019. doi:10.1001/jamapsychiatry.2019.3254

    Author Contributions: Drs Mauro and Martins had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Cerdá, Hasin, Wall, Martins.

    Acquisition, analysis, or interpretation of data: Cerdá, Mauro, Hamilton, Levy, Santaella-Tenorio, Wall, Keyes, Martins.

    Drafting of the manuscript: Cerdá, Mauro, Hamilton, Levy, Santaella-Tenorio, Hasin, Wall.

    Critical revision of the manuscript for important intellectual content: Cerdá, Mauro, Levy, Santaella-Tenorio, Hasin, Wall, Keyes, Martins.

    Statistical analysis: Mauro, Hamilton, Levy, Santaella-Tenorio, Hasin, Wall, Keyes.

    Obtained funding: Martins.

    Administrative, technical, or material support: Martins.

    Supervision: Cerdá, Mauro, Hasin, Martins.

    Conflict of Interest Disclosures: All authors received grant 1R01DA037866 from the National Institute on Drug Abuse (National Institutes of Health). Dr Hasin reported receiving grant R01DA048860 from the National Institute on Drug Abuse. No other disclosures were reported.

    Funding/Support: This study was funded by grant 1R01DA037866 from the National Institute on Drug Abuse (principal investigator, Dr Martins).

    Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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