Individual differences in legal and illicit cannabis purchasing behaviour in British Columbia, Canada: Findings from a 2021 cross-sectional survey.

BACKGROUND: Despite thousands of licensed cannabis retail stores operating across Canada, there remains a significant illicit cannabis market. Some cannabis users continue to buy cannabis from dealers, illicit stores, and/or illicit online retailers. METHODS: Data are from the 2021 British Columbia Cannabis Use Survey. Respondents (n = 8473) were 19 years or older, lived in British Columbia at the time of the survey, and reported using cannabis in the past 12 months. RESULTS: Buying cannabis from all types of illicit sources was more common among younger cannabis users, those who use cannabis more frequently and started using cannabis before the age of 17 (vs. 19 or older), and among those who co-use cannabis with other drugs. Specifically, buying cannabis from a dealer was more common among men, those with lower educational attainment, and those who seek the lowest prices when buying cannabis. In contrast, those using cannabis for medical (vs. non-medical) purposes were more likely to report getting cannabis from illicit retail stores, while buying cannabis from illicit websites was more common among people who use edible cannabis products. CONCLUSION: Consistent with other studies, younger and more frequent cannabis users were more likely to report buying cannabis from illicit sources. However, these findings suggest there is significant heterogeneity among those who buy cannabis from different types of illicit sources, which should be carefully considered when developing policies and strategies aimed at encouraging consumers to transition to legal sources.

Evolving Disparities in Cannabis Use Among Youth by Demographics and Tobacco and Alcohol Use in the U.S.: 2013-2021.

INTRODUCTION: This study investigated the prevalence of past 30-day cannabis use among U.S. youth by cigarette use, alcohol use, demographics, and state-of-residence cannabis legal status in 2021 and examined whether changes in cannabis use prevalence were modified by these factors from 2013 to 2021. METHODS: Data were drawn from the 24 states that collected cannabis use data participating in the Youth Risk Behavior Surveillance System from 2013 to 2021. Logistic regression analyses estimated past 30-day cannabis prevalence in 2021 and produced AORs by current cigarette, alcohol, and state-of-residence cannabis legal status. The same method was used with year as the exposure, adjusting for sex, race, and ethnicity, to assess trends in prevalence from 2013 to 2021. RESULTS: In 2021, cannabis use was more common among female youth (16.75% vs 13.83% [AOR=1.26, 95% CI=1.16, 1.37]) and non-Hispanic Black and Hispanic youth than among non-Hispanic White youth (17.19%, 16.14% vs 14.60% [AOR=1.25, 95% CI=1.12, 1.39 and AOR=1.16, 95% CI=1.04, 1.29, respectively]). Cannabis use was much more common among youth who reported any past 30-day cigarette or alcohol use (44.90% vs 6.48% [AOR=11.80, 95% CI=10.57, 13.18]). Declines in cannabis use were observed independent of state-level cannabis law from 2013 to 2021, and cannabis use prevalence did not differ significantly by state-of-residence cannabis legal status among the 24 participating states in 2021. CONCLUSIONS: Public health officials should carefully consider the potential impact of expanding commercialization of cannabis as a wellness product on youth cannabis use, especially with regard to minoritized populations and co-use with tobacco and alcohol. National and state-level public health education on cannabis use and youth-oriented prevention of cannabis uptake are long overdue.

High on Hookah: Smoking Marijuana from a Hookah among Adults in the United States, Population Assessment of Tobacco and Health Study, 2015-2019.

Background: This study aimed to examine the trend and factors associated with smoking marijuana from a hookah device among US adults. Methods: Data were drawn from the Population Assessment of Tobacco and Health (PATH) Study, an ongoing nationally representative, longitudinal cohort study of the US population. Adult respondents who self-reported ever smoking marijuana from a hookah at Wave 5 (2018-19, N = 34,279 US adults) were included in the multivariable analysis. Trend analysis also was conducted using National Cancer Institute JoinPoint software from 2015 to 2019. Results: In 2018-19, an estimated 23.6 million (9.7%) US adults reported ever smoking marijuana from a hookah. Trend analysis showed the increasing prevalence of using marijuana from a hookah device from Wave 3 (8.9%) to Wave 5 (9.7%; time trend p = .007). Adults aged 25-44 years old (vs. 18-24; 13%, vs. 9%), whites (vs. Black; 11% vs. 9%), and lesbian, gay, or bisexual (LGB vs. straight; 17% vs. 9%) were more likely to report ever smoking marijuana from a hookah (ps < .05). Former and current users (vs. never users) of e-cigarettes (19% and 25% vs. 5%), cigarettes (11% and 21% vs. 2%), cigars (17% and 27% vs. 3%), and pipes (21% and 33% vs. 7%) and past 30-day blunt users (vs. non-users; 39% vs. 9%) were more likely to ever smoke marijuana from a hookah (ps < .05). Pregnant women (vs. non-pregnant; 12.8% vs. 8.6%; p = 0.03) were more likely to smoke marijuana from a hookah. Conclusions: Smoking marijuana from a hookah device is prevalent among young adults in the US, especially among vulnerable populations, and has increased significantly from 2015-2019.

Using Young Adult Language to Describe the Effects of Simultaneous Alcohol and Marijuana Use: Implications for Assessment.

Introduction: Prevalence of alcohol and marijuana use is highest in young adulthood and an increasing number of young adults report simultaneous alcohol and marijuana (SAM) use, which is consistently linked with numerous negative consequences. To better understand reasons for engaging in SAM use and to refine measurement of subjective effects of SAM use, this study aimed to identify (1) how young adults describe subjective experiences during a SAM use occasion and (2) how language describing subjective effects changes as a function of level of alcohol and marijuana use. Methods: Using Amazon's Mechanical Turk (MTurk), 323 participants (53.6% women, 68.4% White, M age = 23.0 years) who reported past-month heavy episodic drinking and past-month SAM use were asked to list words to describe how they feel when using only alcohol, only marijuana, and various combinations of alcohol and marijuana. Results: SAM use language varied as a function of age and substance use behavior but was not associated with sex or race. Large differences in the terms used to describe subjective effects were observed when comparing different combinations of alcohol and marijuana use; most notably the term "cross-faded" appeared primarily when engaging at the heaviest combinations of alcohol and marijuana. Conclusion: Young adults have a wide range of vocabulary for describing subjective effects of SAM use, and subjective effects vary as a function of the level of each substance used. Future research should consider integrating such contemporary language when measuring subjective effects of SAM use.

Sociodemographic Characteristics Associated With and Prevalence and Frequency of Cannabis Use Among Adults in the US.

Importance: Cannabis use has increased, but there are few studies on frequent and daily cannabis use among US adults. Individuals who engage in higher frequency use may suffer more health consequences. Objective: To examine frequency of cannabis use and associated factors among US adults. Design, Setting, and Participants: This survey study included data from 21 US states and 2 US territories reported in the Behavioral Risk Factor Surveillance System surveys from 2016 to 2019. Cross-sectional data on US adults ages 18 years and older were used to estimate demographic, socioeconomic, and behavioral risk factors for cannabis use, taking into account the survey strata and sampling weights for the 4 years of combined data. Using a multivariable ordinal logistic analysis, the association of demographic, socioeconomic status, and behavioral risk factors with past month cannabis frequency were examined. Exposures: Sociodemographic characteristic, ie, age, gender, race and ethnicity, educational attainment, employment status, and annual household income. Main Outcomes and Measures: Ordinal categorization of number of days of cannabis use in the past 30 days in terms of nonuse, infrequent use (1-5 days), frequent use (6-29 days), and daily use. Results: Among the 387 179 respondents, 58 009 (27.9%) were ages 18 to 34 years, 186 923 (50.3%) were ages 35 to 64 years, and 142 225 (21.8%) were age 65 years or older (mean [SD] age, 48.3 [0.1] years). The sample included 28 345 (9.8%) Black, 36 697 (22.6%) Hispanic, and 292 210 (57.3%) White respondents. Smoking was the most common form of cannabis use. The frequency of cannabis use varied significantly by age, gender, race, marital status, education, and employment. Higher frequency cannabis use was associated with younger age (ages 18-34 years: adjusted odds ratio [aOR],4.12; 95% CI, 3.63-4.68; ages 35-64 years: aOR,2.22; 95% CI, 1.98-2.49), Black (aOR, 1.46; 95% CI, 1.33-1.71) and Native American (aOR, 1.25; 95% CI, 1.04-1.52) race, and less educational attainment (high school or less: aOR,1.09; 95% CI, 1.02-1.17; some college: aOR,1.27; 95% CI, 1.19-1.35). Being married (aOR, 0.54; 95% CI, 0.51-0.58) or identifying as Asian (aOR, 0.60; 95% CI, 0.51-0.71) or Hispanic (aOR, 0.71; 95% CI, 0.65-0.77) was associated with lower-frequency cannabis use after accounting for other baseline factors. Conclusions and Relevance: This nationally based study found that higher-frequency cannabis use is more common among young and racial minority populations, as well as respondents with low socioeconomic status. Given the known and emerging negative health effects of cannabis use, more attention may need to be paid to high-frequency use among underserved populations in the form of screening, risk stratification, and treatment.

Assessment of Nicotine and Cannabis Vaping and Respiratory Symptoms in Young Adults.

Importance: Rates of e-cigarette use (ie, nicotine vaping) and cannabis vaping continue to increase among youth and young adults. However, the association of nicotine and cannabis vaping with independent respiratory health outcomes has not been well studied. Objective: To investigate associations of nicotine and cannabis vaping with bronchitic symptoms, wheeze, and shortness of breath. Design, Setting, and Participants: Cross-sectional survey data on self-reported lifetime, 6-month, and 30-day vaping from 2553 young adults recruited from high schools in Southern California were collected from June 2018 to October 2019. Of these participants, 94% provided data for shortness of breath and wheeze, and 86% provided data for chronic bronchitis. Main Outcomes and Measures: Self-reported nicotine and cannabis vaping were measured on a Likert-type scale using the following responses: (1) never used, (2) lifetime but no past 6-month use, (3) past 6-month use but no use in the past 30 days, (4) use on 1 or 2 of the past 30 days, and (5) use on 3 or more of the past 30 days. Three respiratory health outcomes were assessed separately on the basis of self-reported symptoms: bronchitic symptoms in the previous 12 months (ie, daily cough for 3 months in a row, congestion or phlegm other than with a cold, and/or bronchitis), wheeze in the previous 12 months, and shortness of breath when hurrying on level ground or walking up a slight hill. Results: Of 2553 participants in the analytic sample (mean [SD] age, 19.3 [0.79] years; 1477 [57.9%] female individuals), 1095 of 2553 young adults (42.9%) reported vaping nicotine and 939 of 2553 (38.4%) reported vaping cannabis. Compared with those who never vaped cannabis, individuals who vaped cannabis in their lifetime but not in the past 60 months (204 of 2553 [8.4%]; adjusted odds ratio [aOR], 1.83 [95% CI, 1.08-3.10]), in the past 6 months but not in the last 30 days (490 of 2443 [20.1%]; aOR, 1.58 [95% CI, 1.02-2.46]), 1-2 days in the past 30 days (90 of 2443 [3.7%]; aOR, 2.83 [95% CI, 1.46-5.50]), and 3 or more days in the past 30 days (155 of 2443 [6.3%]; aOR, 2.14 [95% CI, 1.16-3.92]) had significantly higher odds of chronic bronchitic symptoms after adjusting for nicotine vaping, cigarette smoking, cannabis smoking, and sociodemographic characteristics. Cannabis vaping 3 or more times in the last 30 days was also associated with increased odds of wheeze (aOR, 2.27 [95% CI, 1.17-4.37]). Associations of cannabis vaping with shortness of breath and nicotine vaping with any respiratory health outcome were not statistically significant in fully adjusted models. Conclusions and Relevance: Findings of this cross-sectional study suggest that cannabis vaping is associated with increased risk of bronchitic symptoms and wheeze in young adults. Further research is needed to understand the temporality of the association and the mechanisms underlying the difference between nicotine and cannabis vaping in the risk of bronchitic symptoms and wheeze.

Co-occurrence across time and space of drug- and cannabinoid- exposure and adverse mental health outcomes in the National Survey of Drug Use and Health: combined geotemporospatial and causal inference analysis.

BACKGROUND: Whilst many studies have linked increased drug and cannabis exposure to adverse mental health (MH) outcomes their effects on whole populations and geotemporospatial relationships are not well understood. METHODS: Ecological cohort study of National Survey of Drug Use and Health (NSDUH) geographically-linked substate-shapefiles 2010-2012 and 2014-2016 supplemented by five-year US American Community Survey. Drugs: cigarettes, alcohol abuse, last-month cannabis use and last-year cocaine use. MH: any mental illness, major depressive illness, serious mental illness and suicidal thinking. DATA ANALYSIS: two-stage, geotemporospatial, robust generalized linear regression and causal inference methods in R. RESULTS: 410,138 NSDUH respondents. Average response rate 76.7%. When drug and sociodemographic variables were combined in geospatial models significant terms including tobacco, alcohol, cannabis exposure and various ethnicities remained in final models for all four major mental health outcomes. Interactive terms including cannabis were related to any mental illness (ß-estimate = 1.97 (95%C.I. 1.56-2.37), P <  2.2 × 10- 16), major depressive episode (ß-estimate = 2.03 (1.54-2.52), P = 3.6 × 10- 16), serious mental illness (SMI, ß-estimate = 2.04 (1.48-2.60), P = 1.0 × 10- 12), suicidal ideation (ß-estimate = 1.99 (1.52-2.47), P <  2.2 × 10- 16) and in each case cannabis alone was significantly associated (from ß-estimate = - 3.43 (- 4.46 - -2.42), P = 3.4 × 10- 11) with adverse MH outcomes on complex interactive regression surfaces. Geospatial modelling showed a monotonic upward trajectory of SMI which doubled (3.62 to 7.06%) as cannabis use increased. Extrapolated to whole populations cannabis decriminalization (4.26%, (4.18, 4.34%)), Prevalence Ratio (PR) = 1.035(1.034-1.036), attributable fraction in the exposed (AFE) = 3.28%(3.18-3.37%), P < 10- 300) and legalization (4.75% (4.65, 4.84%), PR = 1.155 (1.153-1.158), AFE = 12.91% (12.72-13.10%), P < 10- 300) were associated with increased SMI vs. illegal status (4.26, (4.18-4.33%)). CONCLUSIONS: Data show all four indices of mental ill-health track cannabis exposure across space and time and are robust to multivariable adjustment for ethnicity, socioeconomics and other drug use. MH deteriorated with cannabis legalization. Cannabis use-MH data are consistent with causal relationships in the forward direction and include dose-response and temporal-sequential relationships. Together with similar international reports and numerous mechanistic studies preventative action to reduce cannabis use is indicated.

Trajectories of Nicotine and Cannabis Vaping and Polyuse From Adolescence to Young Adulthood.

Importance: Little is known about cannabis vaping trajectories across adolescence and young adulthood or the co-occurrence with nicotine vaping. Objective: To evaluate nicotine vaping and cannabis vaping trajectories from late adolescence to young adulthood (≥18 years of age) and the extent of polysubstance vaping. Design, Setting, and Participants: In this prospective cohort study, 5 surveys (including information on substance vaped) were completed at 10 high schools in the Los Angeles, California, metro area. Students were surveyed at 6-month intervals from fall of 11th grade (October to December 2015; wave 5) through spring of 12th grade (March to June 2017; wave 8) and again approximately 1 to 2 years after high school (October 2018 to October 2019; wave 9). Exposures: Past 30-day nicotine and cannabis vaping frequency across 5 waves. Main Outcomes and Measures: Self-reported frequency of nicotine vaping and cannabis vaping within the past 30 days across 5 time points from late adolescence to young adulthood. Trajectories were measured with these past 30-day use frequencies at each wave. Parallel growth mixture modeling estimated conditional probabilities of polysubstance vaping. Results: The analytic sample included 3322 participants with at least 1 time point of data (mean [SD] age, 16.50 [0.42] years at baseline; 1777 [53.5%] female; 1573 [47.4%] Hispanic or Latino). Growth mixture modeling identified the 5-trajectory model as optimal for both nicotine vaping and cannabis vaping. Trajectories for nicotine and cannabis vaping were similar (nonusers: 2246 [67.6%] nicotine, 2157 [64.9%] cannabis; infrequent users: 566 [17.0%] nicotine, 608 [18.3%] cannabis; moderate users: 167 [5.0%] nicotine, 233 [7.0%] cannabis; young adult-onset frequent users: 213 [6.4%] nicotine, 190 [5.7%] cannabis; adolescent-onset escalating frequent users: 131 [3.9%] nicotine, 134 [4.0%] cannabis). Males had greater odds of belonging to the adolescent-onset escalating frequent users nicotine (adjusted odds ratio, 2.88; 95% CI, 1.58-5.23; P < .01) and cannabis (adjusted odds ratio, 1.95; 95% CI,1.03-3.66; P < .05) vaping trajectories compared with nonusers. Polysubstance vaping was common, with those in trajectories reflecting more frequent nicotine vaping (adolescent-onset escalating frequent users and young adult-onset frequent users) having a high probability of membership (85% and 93%, respectively) in a cannabis-use trajectory. Conclusions and Relevance: In this cohort study, the prevalence and type of nicotine vaping and cannabis vaping developmental trajectories from late adolescence to young adulthood were similar. Polysubstance vaping was common from late adolescence to young adulthood, particularly among those reporting more frequent vaping use. The findings suggest that public health policy and clinical interventions should address polysubstance vaping in both adolescence and young adulthood.

Mental Distress in the United States at the Beginning of the COVID-19 Pandemic.

Objectives. To assess the impact of the COVID-19 pandemic on mental distress in US adults.Methods. Participants were 5065 adults from the Understanding America Study, a probability-based Internet panel representative of the US adult population. The main exposure was survey completion date (March 10-16, 2020). The outcome was mental distress measured via the 4-item version of the Patient Health Questionnaire.Results. Among states with 50 or more COVID-19 cases as of March 10, each additional day was significantly associated with an 11% increase in the odds of moving up a category of distress (odds ratio = 1.11; 95% confidence interval = 1.01, 1.21; P = .02). Perceptions about the likelihood of getting infected, death from the virus, and steps taken to avoid infecting others were associated with increased mental distress in the model that included all states. Individuals with higher consumption of alcohol or cannabis or with history of depressive symptoms were at significantly higher risk for mental distress.Conclusions. These data suggest that as the COVID-19 pandemic continues, mental distress may continue to increase and should be regularly monitored. Specific populations are at high risk for mental distress, particularly those with preexisting depressive symptoms.

Use of tobacco, alcohol and cannabis in late adolescence: roles of family living arrangement and socioeconomic group.

BACKGROUND: France has one of the highest levels in Europe for early use of legal and illegal psychoactive substances. We investigate in this country disparities in adolescent problematic substance use by family living arrangement and parental socioeconomic group. METHODS: The data used were from the 2017 nationally-representative ESCAPAD survey, conducted among 17-year-olds in metropolitan France (N = 39,115 with 97% response rate). Prevalence ratios (PR) were estimated using modified Poisson regression. RESULTS: Adolescents living in non-intact families (44%) reported daily smoking, binge drinking and regular cannabis use (respectively ≥3 episodes and ≥ 10 uses in the last 30 days) much more frequently than those living in intact families (for example, the PR estimates for father single parent families were respectively 1.69 (1.55-1.84), 1.29 (1.14-1.45) and 2.31 (1.95-2.74)). Socioeconomic differences across types of families did little to explain the differential use. Distinctive socioeconomic patterns were found: a classical gradient for smoking (PR = 1.34 (1.22-1.47) for the most disadvantaged group relative to the most privileged); an inverse association for binge drinking (PR = 0.72 (0.64-0.81) for the most disadvantaged relative to the most privileged), and no significant variation for cannabis use. CONCLUSION: Our findings shed light on the consistency of the excess use of adolescents from non-intact families and on the substance-specific nature of the association with parental socioeconomic group. Preventive approaches at the population level should be complemented by more targeted strategies.

Adolescent Cannabis Use and Perceived Social Norm Trends Pre- and Post-Implementation of Washington State's Liberalized Recreational Cannabis Policy: Healthy Youth Survey, 2008-2018.

This study examined trends in adolescent perceptions of social norms pertaining to adolescent cannabis use, in relation to past 30-day adolescent cannabis use, and was interpreted in light of Washington State's liberalized recreational cannabis policy (LRCP: 2012). Data come from Washington's Healthy Youth Survey (HYS), collected during even-numbered years between 2008 and 2018, with methods-stabilized surveys of school-attending youths in grades 8, 10, and 12. This study used an aggregate state census sample of n = 325,723. Year-specific social norms and cannabis use proportions were estimated, stratified by grade. Regression analyses assessed associations between social norms and recent cannabis use. The proportion of recent adolescent cannabis use during the initial years post-LRCP in Washington State remained relatively stable or trended downward slightly; however, 2018 data may indicate a slight upward trend for 10th and 8th graders. Cannabis use by a close friend consistently paralleled adolescent cannabis use trends. The proportion of youth reporting parental acceptance of, and overall community acceptance of, adolescent cannabis use trended slightly upward in 2014 (post-LRCP implementation) but, since, has remained stable or declined slightly. Adolescent self-acceptance of youth cannabis use increased steadily for high school students between 2008 and 2014, edged downward in 2016, and then trended back upward for 8th and 10th graders in 2018. Perceived parental acceptance remained statistically associated with adolescent cannabis use across grades and years, with the strength of associations edging up. Ongoing monitoring of substance use and related risk factor trends will be needed to understand the impacts of LRCPs.

Evaluation of Availability of Survey Data About Cannabis Use.

Importance: In response to increasing public support for cannabis legalization, understanding associations of state and federal policy changes related to cannabis legalization with patterns of cannabis use is important. A challenge for public health monitoring and research is significant variation in data availability related to cannabis use behaviors and perceptions across and within states and over time, including the availability of prelegalization vs postlegalization data. Objective: To review data available on cannabis use and related behaviors over time in Massachusetts and the US. Design, Setting, and Participants: This case series examined state and national surveys on public health and related behaviors and outcomes to review availability of cannabis-related data for Massachusetts for 8 key indicators over time. Additionally, the Behavioral Risk Factor Surveillance System (BRFSS) and Youth Risk Behavior Surveillance System for all states were reviewed. The analysis was conducted between February 1, 2019, and March 18, 2020. Exposures: Surveys that enable state-level estimation of cannabis use and related behaviors. Main Outcomes and Measures: Eight key indicators related to cannabis use behaviors and perceptions: lifetime cannabis use, age of initiation, frequency of use, location of use, method of use, source of cannabis, perceptions of cannabis, and reason for use (ie, medical vs nonmedical). Results: There were 7 surveys that monitored cannabis use and related behaviors in Massachusetts for adolescents and adults. No surveys monitored all 8 indicators of interest, and availability over time was limited. In the most recent BRFSS, 24 states asked cannabis-related questions, meaning BRFSS data on cannabis use was lacking for more than half of the US adult population. In the Youth Risk Behavior Surveillance System, 36 states asked standard cannabis questions; most other states had at least 1 question related to cannabis use and frequency. Conclusions and Relevance: These findings of limitations of existing surveys, and particularly the lack of national questions in the BRFSS and Youth Risk Behavior Surveillance System, suggest that available data have substantial limitations for monitoring cannabis use. As cannabis policy changes continue, there is a need to remain focused on the availability of high-quality data sources that allow for critical public health research.

Association Between the Use of Cannabis and Physical Violence in Youths: A Meta-Analytical Investigation.

OBJECTIVE: The aim of this meta-analysis was to investigate the extent to which cannabis use among youths is associated with the risk of perpetrating physical violence. METHODS: Searches were conducted in PubMed, PsycINFO, Web of Science, and Google Scholar for articles published from the inception of each database to July 2019. All studies that examined both cannabis use and the perpetration of physical violence in a sample of youths and young adults <30 years old were included. The meta-analysis was performed with a random-effects model. Risk of publication bias was assessed with Egger's test. Guidelines from the Meta-Analysis of Observational Studies in Epidemiology were followed. RESULTS: After screening 11,348 potential studies, 30 study arms were included, yielding a total of 296,815 adolescents and young adults. The odds ratio for the pooled studies was 2.11 (95% CI=1.64, 2.72). The pooled odds ratios were 2.15 (95% CI=1.58, 2.94) and 2.02 (95% CI=1.26, 3.23) for the cross-sectional and longitudinal studies, respectively. Preliminary evidence suggests that the risk of violence was higher for persistent heavy users (odds ratio=2.81, 95% CI=1.68, 4.74) compared with past-year users (odds ratio=2.05, 95% CI=1.5, 2.8) and lifetime users (odds ratio=1.94, 95% CI=1.29, 2.93). The odds ratio for unadjusted studies was 2.62 (95% CI=1.89, 3.62), and for studies using odds ratios adjusted for potential confounding factors, 2.01 (95% CI=1.57, 2.56). CONCLUSIONS: These results demonstrate a moderate association between cannabis use and physical violence, which remained significant regardless of study design and adjustment for confounding factors (i.e., socioeconomic factors, other substance use). Cannabis use in this population is a risk factor for violence.

At-risk drinking and current cannabis use among medical students: a multivariable analysis of the role of personality traits

Objective: To explore the role of personality traits in at-risk drinking and current cannabis use among medical students. Methods: This cross-sectional study evaluated 707 medical students from two universities. Multiple logistic regression models for at-risk drinking and current cannabis use were constructed including sociodemographic, psychiatric, and personality variables. Results: At-risk drinking and current cannabis use were reported by 19.3% and 14.9% of participants, respectively. Models including Big Five measures showed associations of at-risk drinking with higher extraversion (p < 0.00001, adjusted odds ratio [AOR] = 1.9) and lower conscientiousness (p = 0.00001, AOR = 0.5); cannabis use was also associated with lower conscientiousness (p = 0.003, AOR = 0.6), besides higher openness to experience (p = 0.002, AOR = 1.9). Models including measures of the Behavioral Inhibition and Activation Systems scales (BIS/BAS) showed associations of at-risk drinking with lower BIS (p = 0.002, AOR = 0.9) and higher BAS fun-seeking (p = 0.0005, AOR = 1.2); cannabis use was also associated with higher BAS fun-seeking (p = 0.008, AOR = 1.2). Personality variables had modest effects on model fit. Conclusion: Specific personality traits were independently associated with at-risk drinking and current cannabis use, albeit with modest effect sizes.

Development of a Cannabis Assessment Tool (CAT-1) to measure current and lifetime marijuana use among older Veterans.

OBJECTIVE: To develop a tool to assess current (past 30 days) and lifetime marijuana use in older Veterans. SETTING: US Veteran's Affairs Healthcare System. PARTICIPANTS: 704 older Veterans were screened, 339 completed the initial survey, 100 completed the follow-up. PRIMARY OUTCOME MEASURE: Pearson's correlation coefficient to assess strength of association between initial and follow-up survey on measures of current and lifetime marijuana use. RESULTS: Both a 'gram-month' measure of marijuana smoked in the past 30 days (r=0.83) and a frequency-based measure assessing total number of times smoked in the past 30 days were reliable (r=0.89). Both a simple categorical measure of lifetime use (agreement=85%) and a continuous measure of lifetime use (r=0.82) were reliable. CONCLUSIONS: The Cannabis Assessment Tool offers a reliable assessment of past 30 days and lifetime assessments of smoking cannabis in older adults.

Estimation of the proportion of population cannabis consumption in Australia that is accounted for by daily users using Monte Carlo Simulation.

AIM: To estimate the proportion of cannabis consumed in Australia by daily cannabis users. DESIGN: Monte Carlo simulation using parameters estimated from nationally representative and repeated cross-sectional household surveys in 2007, 2010, 2013 and 2016. SETTING: Australia PARTICIPANTS: Adult samples (mean age = 49.9; 55% females) from four National Drug Strategy Household Surveys (n = 92 243). MEASUREMENT: Frequency of cannabis use (daily/weekly/about once a month/every few months/once or twice a year). The weighted estimated prevalence of users in each of these frequency levels was multiplied by population size to estimate the total number of users. Quantity of cannabis use was measured as number of joints consumed. The consumption of those who reported using bongs was converted into joints based on the bong to joint ratio estimated from the survey data. We estimated the proportion of cannabis consumed by daily users by Monte Carlo simulation using parameters estimated from the household surveys. We conducted 10 000 simulation trials, and in each trial we [1] simulated the number of users at each consumption level (stratum) based on estimated prevalence and population size[2], for each simulated individual, we simulated the number of days of cannabis use in a year based on frequency data[3], for each consumption day, we simulated the quantity consumed [4] and lastly we calculated the total joints consumed at each consumption level and estimated the proportion of joints consumed by daily users out of the total consumption. FINDINGS: The prevalence of past-year cannabis use increased from 8.9% [95% confidence interval (CI) = 8.5-9.4] in 2007 to 10.5% (95% CI = 10.0-11.1) in 2016, 16% of whom were daily users. Between 2007 and 2016, daily users accounted for between 81.6 and 85.7% of all cannabis consumed. Weekly users accounted for an additional 12.1-15.9%. CONCLUSION: Between 2007 and 2016, only one in six Australian cannabis users were daily users, but they accounted for more than 80% of the estimated cannabis consumed in Australia.

At-risk drinking and current cannabis use among medical students: a multivariable analysis of the role of personality traits.

OBJECTIVE: To explore the role of personality traits in at-risk drinking and current cannabis use among medical students. METHODS: This cross-sectional study evaluated 707 medical students from two universities. Multiple logistic regression models for at-risk drinking and current cannabis use were constructed including sociodemographic, psychiatric, and personality variables. RESULTS: At-risk drinking and current cannabis use were reported by 19.3% and 14.9% of participants, respectively. Models including Big Five measures showed associations of at-risk drinking with higher extraversion (p < 0.00001, adjusted odds ratio [AOR] = 1.9) and lower conscientiousness (p = 0.00001, AOR = 0.5); cannabis use was also associated with lower conscientiousness (p = 0.003, AOR = 0.6), besides higher openness to experience (p = 0.002, AOR = 1.9). Models including measures of the Behavioral Inhibition and Activation Systems scales (BIS/BAS) showed associations of at-risk drinking with lower BIS (p = 0.002, AOR = 0.9) and higher BAS fun-seeking (p = 0.0005, AOR = 1.2); cannabis use was also associated with higher BAS fun-seeking (p = 0.008, AOR = 1.2). Personality variables had modest effects on model fit. CONCLUSION: Specific personality traits were independently associated with at-risk drinking and current cannabis use, albeit with modest effect sizes.

Role of Alcohol and Drug Detection by Regular Urine Sample Testing in pre-transplant evaluation for Alcohol Liver Disease. / Papel de la detección regular de sustancias en orina en pacientes en valoración pre-transplante hepático por hepatopatía alcohólica.

Alcohol Liver Disease (ALD) is one of the most prevalent conditions leading to liver transplantation for end-stage liver disease. There is lacking evidence of regular urine screening testing (RUST) impact on survival or liver transplantation of ALD patients. The aims of this study were to compare the sensitivity of RUST, to assess its impact on survival and liver transplantation, and to evaluate factors associated with adherence to RUST. We performed a single-centered retrospective study (N = 84) with ALD candidates for liver transplantation. Demographic, biochemical and clinical variables were recorded at baseline. Adherence to RUST was evaluated during follow-up. The sensitivity of both RUST and self-reports were calculated for all drugs. Multivariable logistic and survival regression analyses were performed to explore associated factors and the impact of adherence to RUST, and positive results on survival. RUST had high sensitivity for identifying active drinkers (76.9%), smokers (78.9%) and cannabis users (83.3%). High adherence to RUST was inversely associated with mortality during follow-up. Presence of personality disorders negatively impacted (OR 0.29, CI 95% 0.08-0.97) adherence to RUST. Both RUST and self-reports should be carried out in this setting. Professionals involved in liver transplantation programs must promote adherence to RUST, primarily in patients with personality disorders.

La enfermedad hepática alcohólica (EHA) es una de las causas más frecuentes de trasplante hepático en enfermedad hepática terminal. No hay evidencia de impacto de la detección regular de sustancias en orina (DRSO) sobre la supervivencia de los pacientes con EHA. Los objetivos de este estudio fueron comparar la sensibilidad de la DRSO, evaluar su impacto en la supervivencia y en el trasplante de hígado, y evaluar el impacto de la adherencia a la DRSO. Realizamos un estudio retrospectivo (N = 84) con candidatos para trasplante de hígado por EHA. Registramos las variables demográficas, bioquímicas y clínicas al inicio del estudio. Evaluamos la adherencia a la DRSO durante el seguimiento. Calculamos la sensibilidad tanto de la DRSO como de las declaraciones de los pacientes para todas las sustancias. Realizamos análisis multivariables (regresión logística) y de supervivencia para explorar los factores asociados y el impacto de la adherencia a la DRSO, y de los resultados positivos en la DRSO sobre la supervivencia. La DRSO tuvo una alta sensibilidad para identificar bebedores activos (76,9%), fumadores (78,9%) y consumidores de cannabis (83,3%). Alta adherencia a la DRSO tuvo una asociación inversa con mortalidad durante el seguimiento. La presencia de trastornos de la personalidad tuvo un impacto negativo (RM ,29, IC 95% ,08-,97) sobre la adherencia a la DRSO. Tanto la DRSO como las declaraciones deben llevarse a cabo en este perfil de pacientes. Los profesionales que participan en programas de trasplante hepático deben promover el cumplimiento de la DRSO, principalmente en pacientes con trastornos de la personalidad.

Socio-demographic predictors of well-being in United Kingdom adolescents, and the impact of well-being on a range of health-related outcomes.

The deleterious impact of low mental well-being, and higher levels psychological symptoms (collectively well-being), on concurrent and prospective health outcomes has elsewhere been demonstrated. Further, variables such as conurbation and deprivation have been found to be related to mental and physical heath. This study used data from a longitudinal study to examine which demographic predicted well-being scores, and how scores on these constructs were related to six health-related outcomes. Participants were adolescents (N = 4,956; Male = 2376[48%]), from 72 High Schools in Northern Ireland. Three waves of data were gathered on mental well-being, psychological symptoms, subjective life expectancy (living to age 35 and age 75 years), self-rated health, frequency of physical exercise, and lifetime use of cigarettes and cannabis. Results showed that both well-being scores were significantly associated with gender cross-sectionally, but demographic variables did not predict changes in well-being longitudinally. Both well-being measures were significantly associated with health outcomes cross-sectionally, with mental well-being (over time) predicting life subjective life expectancy, self-rated health, and addictive behaviors, while psychological symptoms (over time) predicted the former two, but not addictive behaviors. Overall, the relationship between mental well-being, psychological symptoms, and the health outcomes assessed, was small in terms of effect size.