Historical Trends in Cannabis Use among U.S. Adults Aged 19-55, 2013-2021.

OBJECTIVE: The current study used U.S. national data to examine trends in cannabis use from 2013-2021, focusing on changes in cannabis prevalence during young and middle adulthood, and whether trends differed by sociodemographic characteristics. METHOD: Data from 2013-2021 from 21,133 respondents aged 19-30 and 29,898 aged 35-55 in the national Monitoring the Future panel study (followed since they were in 12th grade in 1976-2020) were used to model historical trends in cannabis prevalence (any 12-month use, any 30-day use, and near-daily use [20+ occasions in the past 30 days]). RESULTS: Prevalence of 12-month, 30-day, and near-daily cannabis use significantly increased from 2013-2021 for both young and middle adults. Trends for all three behaviors indicated either consistent linear increases or two-slope increases where the slope estimate was larger in more recent years. Historical increases in 12-month and 30-day use were similar for young and middle adulthood; the historical increase in near-daily use among middle adults had some evidence for a possible pandemic-related deviation. Historical trends did not differ by race/ethnicity or college degree. Trends for 12-month and 30-day use differed by sex, with females increasing more than males over time, especially during middle adulthood. CONCLUSIONS: Significant increases in the prevalence of cannabis use have occurred over the past decade for young and middle adults across sociodemographic groups, with some indication that near-daily use increased among middle adults at the onset of the pandemic. Although males continue to have higher prevalence than females, the gap has narrowed with greater increases in cannabis use among women.

Trends in coping reasons for marijuana use among U.S. adolescents from 2016 to 2022.

OBJECTIVE: This study examines historical trends in coping reasons for marijuana use among adolescents (1976-2022) and explores sociodemographic variations in recent years (2016-2022). METHOD: Data from U.S. national samples of 12th grade adolescents in the Monitoring the Future (MTF) study were used to examine long-term trends (1976-2022, N = 43,237) and recent differences by sociodemographic characteristics (2016-2022, N = 3,816). Measures included marijuana use, coping reasons for use, and sociodemographic characteristics. RESULTS: The most prevalent coping reason across time was "relax," endorsed by 52.9% of past 12-month users. Coping reasons mostly exhibited significant increases over time. Sociodemographic factors were associated with coping reasons. Females had higher odds of using marijuana to escape problems and get through the day (vs. males). Black respondents were more likely to use marijuana to get through the day, and Hispanic respondents were more likely to use to relax (vs. White respondents). Those with lower (vs. higher) parental education were more likely to use due to anger/frustration and to escape problems. Adolescents who used marijuana frequently (vs. less often) had higher odds of endorsing all coping reasons. There was no robust evidence of interactions between sociodemographic characteristics and year. CONCLUSIONS: Results indicate a consistent increase in coping reasons for adolescent marijuana use over time, with variations based on sociodemographic characteristics. The findings highlight the importance of understanding subpopulations of adolescents who have higher risk of coping-related marijuana use.

Alcohol Use Disorder Symptoms Reported during Midlife: Results from the Monitoring the Future Study among US Adults at Modal Ages 50, 55, and 60.

BACKGROUND: The extent to which adolescent substance use is associated with alcohol use disorder (AUD) symptoms in midlife is not yet fully explored. METHODS: Longitudinal data from the national Monitoring the Future study was used. The sample included 11,830 12th graders (1976-1987) who were surveyed again at modal ages 50 (37.8%), 55 (46.3%), or 60 (15.8%) in 2008-2019. Approximately 48.7% were male; 81.5% identified as non-Hispanic White. Weighted logistic and multinomial logistic regressions were used to examine associations between past 30-day use of cigarettes, marijuana, and alcohol at age 18, sociodemographics, and a midlife AUD symptom outcome (coded as non-drinking, drinking without AUD [endorsed ≤1 criterion], or AUD symptoms [endorsed 2+ criteria]). RESULTS: Prevalence of midlife AUD symptoms was 27.1%. Higher relative risk of reporting AUD symptoms (vs. drinking without AUD) was associated with age 18 substance use (any cigarette use [vs. no use], any marijuana use [vs. no use], binge drinking [vs. both no use and drinking at less than binge levels]), being male (vs. female), being non-Hispanic White (vs. non-Hispanic Black), and having a 4-year college degree. Higher relative risk of reporting non-drinking (vs. drinking without AUD) was associated with no 30-day alcohol use at age 18, being non-Hispanic Black or non-Hispanic other (vs. non-Hispanic White), and not having a 4-year college degree. CONCLUSIONS: Findings suggest substance use at age 18 has meaningful associations with midlife AUD symptoms. Dissemination of prevention and intervention efforts in adolescence and early adulthood may be important for reducing hazardous midlife drinking.

Age- and Sex-Varying Associations Between Depressive Symptoms and Substance Use from Modal Ages 35 to 55 in a National Sample of U.S. Adults.

It is important to examine normative age-related change in substance use risk factors across the lifespan, with research focusing on middle adulthood particularly needed. The current study examined time-varying associations between depressive symptoms and alcohol, cigarette, and marijuana use from modal ages 35 to 55 in a national sample of US adults, overall and by sex. Data were obtained from 11,147 individuals in the longitudinal Monitoring the Future study. Participants were in 12th grade (modal age 18) in 1976-1982 and (for the data reported in this study) were surveyed again at modal ages 35 (in 1993-1999), 40, 45, 50, and 55 (in 2013-2019). Weighted time-varying effect modeling was used to examine age-related change in associations among depressive symptoms, any and heavy use of cigarettes, alcohol, and marijuana. Across midlife, greater depressive symptoms were associated with decreased odds of any alcohol use during the 40 s and 50 s, but with increased odds of binge drinking from ages 35-40, and-at most ages-any and pack + cigarette use and any and frequent marijuana use. The association between depressive symptoms and substance use was generally similar for men and women. Results highlight the increased risk for binge drinking, smoking, and marijuana with higher levels of depressive symptoms and underscore the importance of screening and interventions for depressive symptoms and substance use in midlife.

Alcohol use contexts (social settings, drinking games/specials, and locations) as predictors of high-intensity drinking on a given day among U.S. young adults.

BACKGROUND: This study examined whether variability in young adult drinking social settings, drinking games/drink price specials, and locations differentiated daily high-intensity drinking (HID) likelihood; whether contexts varied by legal drinking age and college status (attending a 4-year college full-time); and whether legal drinking age and college status moderated drinking context/intensity associations. METHODS: Participants (n = 818 people, 46.3% female) were part of the Young Adult Daily Life Study in 2019 to 2022. They were originally selected because they were past 30-day drinkers from the 2018 U.S. national probability Monitoring the Future 12th grade sample and because they reported one or more days of alcohol use during 14-day data collection bursts across the following 4 years (n = 5080 drinking days). Weighted multilevel modeling was used to estimate drinking context/intensity associations. Drinking intensity was defined as moderate (females 1 to 3, males 1 to 4 drinks), binge (4 to 7, 5 to 9 drinks), or HID (8+, 10+ drinks). Models controlled for other within-person (weekend, historical time period) and between-person (sex and race/ethnicity) covariates. RESULTS: Contexts differentiating HID and binge drinking days included drinking with large groups, strangers, pregaming, drinking games, and more drinking locations. Legal drinking age was associated with lower odds of free drinks but greater odds of drinking at bars/restaurants. College status was associated with lower odds of drinking alone or free drinks, but greater odds of drinking with friends, large groups, pregaming, drinking games, discounted price drinks, and at bars/restaurants, parties, and more drinking locations. Legal drinking age and college status moderated some context-intensity associations. CONCLUSIONS: Social settings, pregaming, drinking games, and drinking at more locations were associated with increased risk of HID on a given day. Legal drinking age and college status were associated with specific drinking contexts and moderated some context/intensity associations. Incorporating the contexts associated with HID into interventions may help to reduce HID and related consequences in young adults.

Patterns and predictors of high-intensity drinking and implications for intervention.

Efforts to intervene with subgroups at particularly high risk for alcohol use require information on factors that differentiate drinking intensity levels. This article summarizes existing research and provides new findings on sociodemographics and risk factors that differentiate high-intensity drinking (HID) to provide context for developing and delivering interventions for the highest-risk drinkers. Cross-sectional data were obtained in 2019 from participants who reported past 30-day alcohol use in 2018 as part of the nationally representative 12th grade Monitoring the Future study. Among past 2-week drinkers in 2019 (N = 601; modal age 19; 57.0% male; 67.4% non-Hispanic White), bivariate associations between drinking intensity (moderate drinking [1-4 drinks for women/1-5 drinks for men], binge-only drinking [4-7/5-9 drinks], and HID [8+/10+ drinks]) and a range of sociodemographic characteristics, risk factors, and alcohol-related consequences were examined. Results showed binge-drinking norms, social and enhancement drinking motives, nicotine vaping, and use of limiting/stopping drinking and manner of drinking protective behavioral strategies differentiated all drinking intensity levels, lending support to HID and binge-only drinking having an overlapping risk profile. However, there were also risk factors uniquely associated with HID, including sex, college attendance, employment, HID norms, use of serious harm reduction protective behavioral strategies, family history of drinking problems, any cigarette or drug use other than marijuana, and depression symptoms. Therefore, risk factors differentiate young adult drinking intensity. These results can inform efforts to adapt interventions for young adults who report HID. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Comparison of a web-push vs. mailed survey protocol in the Monitoring the Future panel study among adults ages 35 to 60.

Introduction: Updating the mode of data collection may affect response rates or survey results. The ongoing, national Monitoring the Future (MTF) panel study has traditionally used mailed paper surveys. In 2018, MTF experimented with a web-push data collection design for young adults ages 19-30, concluding that the web-push design improved response rates and did not change substance use estimates after controlling for sociodemographic characteristics (Patrick et al., 2021). The current study sought to replicate the web-push experiment with MTF adults ages 35 to 60 in 2020. Methods: In 2020, the MTF panel study included an experiment to test a web-push protocol for respondents ages 35 to 60 (N = 14,379). Participants were randomized to the web-push (i.e., a web survey invitation, with paper surveys available for non-respondents) or traditional MTF (i.e., mailed paper surveys) data collection condition. Results: Results indicated no significant difference in overall response rate for the web-push vs. standard MTF conditions in this age group. Differences in reported estimates of past 30-day substance use prevalence by condition were not significant after adjusting for sociodemographic characteristics. In multivariable models, participants in the web-push condition were less likely to respond via web (than paper) if they were Black, smoked cigarettes in the past 30 days, were unmarried, or did not have a college degree. Conclusions: Overall, the move to the web-push design had minimal impact on response rates and substance use prevalence estimates for this age group. However, in the web-push condition, sociodemographic differences were associated with mode of response.

Solitary alcohol use in adolescence predicts alcohol problems in adulthood: A 17-year longitudinal study in a large national sample of US high school students.

BACKGROUND: Identifying risk factors for alcohol use disorder (AUD) is important for public health. The social context of drinking-such as drinking alone-may be an independent and robust early risk marker for AUD symptoms later in life. We evaluated whether solitary alcohol use in adolescence (age 18) and young adulthood (age 23/24) was concurrently associated with binge drinking and prospectively predicted age 35 AUD symptoms, and whether associations differed by sex. METHODS: Longitudinal data were from the Monitoring the Future study. Surveys were completed by adolescents in 12th grade at age 18 (1976-2002), young adults at age 23/24 (1981-2008), and adults at age 35 (1993-2019). Analyses included past 12-month alcohol users (n = 4464 for adolescent models; n = 4561 for young adult models). Multivariable regression analyses tested whether adolescent and young adult solitary alcohol use was associated concurrently with binge drinking frequency and prospectively with age 35 AUD symptoms. RESULTS: Solitary alcohol use in adolescence and young adulthood was associated (a) concurrently with binge drinking and (b) prospectively with increased risk of age 35 AUD symptoms (even after controlling for earlier binge drinking, alcohol use frequency, and sociodemographic covariates). Adolescent solitary alcohol use was associated with age 35 AUD symptoms particularly among females; no interaction was observed between sex and young adult solitary alcohol use in predicting age 35 AUD symptoms. CONCLUSIONS: Adolescent and young adult solitary alcohol use was associated with increased adult AUD symptoms above and beyond other risk factors; adolescent female solitary alcohol users were especially at risk.

An empirical evaluation of alternative approaches to adjusting for attrition when analyzing longitudinal survey data on young adults' substance use trajectories.

OBJECTIVES: Longitudinal survey data allow for the estimation of developmental trajectories of substance use from adolescence to young adulthood, but these estimates may be subject to attrition bias. Moreover, there is a lack of consensus regarding the most effective statistical methodology to adjust for sample selection and attrition bias when estimating these trajectories. Our objective is to develop specific recommendations regarding adjustment approaches for attrition in longitudinal surveys in practice. METHODS: Analyzing data from the national U.S. Monitoring the Future panel study following four cohorts of individuals from modal ages 18 to 29/30, we systematically compare alternative approaches to analyzing longitudinal data with a wide range of substance use outcomes, and examine the sensitivity of inferences regarding substance use prevalence and trajectories as a function of college attendance to the approach used. RESULTS: Our results show that analyzing all available observations in each wave, while simultaneously accounting for the correlations among repeated observations, sample selection, and attrition, is the most effective approach. The adjustment effects are pronounced in wave-specific descriptive estimates but generally modest in covariate-adjusted trajectory modeling. CONCLUSIONS: The adjustments can refine the precision, and, to some extent, the implications of our findings regarding young adult substance use trajectories.

Characteristics and reasons for use associated with solitary alcohol and marijuana use among U.S. 12th Grade Students, 2015-2021.

BACKGROUND: Little is known regarding what sociodemographic characteristics and reasons for use are associated with adolescent solitary alcohol and marijuana use. METHODS: Data from 7845 12th grade students participating in the nationally-representative Monitoring the Future study from 2015 to 2021 were used to examine cross-sectional associations between sociodemographics, heavy drinking/marijuana use, reasons for use, and past 12-month solitary alcohol or marijuana use among past 12-month users. Historical trends and possible differences related to the COVID-19 pandemic also were examined. RESULTS: Solitary use prevalence increased from 2015 to 2021 with no evidence of significant COVID-19 deviations. In 2021, solitary alcohol use was reported by 32.1% (SE 3.01) and solitary marijuana use by 55.8% (4.72) of those reporting past 12-month use. Common and substance-specific sociodemographic risk factors were observed. Binge drinking was associated with solitary alcohol use; frequent marijuana use was associated with solitary marijuana use. Reasons for use related to coping with negative affect were associated with solitary use. Compulsive use reasons were more strongly associated with solitary alcohol than marijuana use. Drinking to have a good time with friends was negatively associated with solitary alcohol use but this association was not seen for solitary marijuana use. CONCLUSIONS: The percentage of adolescents who use alcohol or marijuana when they were alone has increased among those who report using each substance. Associations between solitary use and (a) higher levels of consumption and (b) coping with negative affect highlight the importance of solitary use as a risk indicator.

Alcohol use and the COVID-19 pandemic: Historical trends in drinking, contexts, and reasons for use among U.S. adults.

OBJECTIVE: The current study used U.S. national data to examine drinking trends prior to and during the COVID-19 pandemic in 2020, focusing on changes in U.S. young- and middle-adult alcohol prevalence, frequency, and drinking contexts and reasons, and whether they differed by age and college status. METHODS: Data from 2015 to 2020 from 16,987 young adults (ages 19-30) and 23,584 middle adults (ages 35-55) in the national Monitoring the Future study were used to model historical trends and potential 2020 shifts (data collection April 1 to November 30, 2020) in prevalence (30-day, daily, binge drinking) and frequency (30-day, binge drinking). For young adults, data on drinking contexts and negative affect reasons for drinking were examined. Moderation by age and college status was also tested. RESULTS: 2020 was associated with (1) downward deviation in 30-day (young and middle adults) and binge drinking (young adults) prevalence; (2) upward deviation in daily drinking prevalence (middle adults); (3) among drinkers, upward deviation in frequency of 30-day (young and middle adults) and binge drinking (young adults); and (4) changes in drinking contexts and reasons among drinkers. Among college students, in particular, 2020 was associated with a downward deviation from expected historical trends in drinking prevalence. Upward deviations in daily prevalence and both binge and 30-day drinking frequency were stronger at ages 25-30 (vs. 19-24) and 35-45 (vs. 50-55). CONCLUSIONS: Among U.S. young and middle adults, deviations from expected historical trends in population alcohol use that occurred during the pandemic included decreases in alcohol use prevalence, increases in alcohol use frequency, and increases in the use of alcohol to relax/relieve tension and because of boredom. These shifts were likely due, in part, to drinking while alone and at home-which increased during the pandemic.

Self-reported perceived negative consequences of marijuana use among U.S. young adult users, 2008-2019.

PURPOSE: This study estimated self-reported perceived negative marijuana use consequences among a national sample of U.S. young adults, examining consequence prevalence differences by use frequency, college attendance, living situation, employment, sex, and race/ethnicity; and use frequency/sociodemographic characteristic interactions. METHODS: A subsample of 1,212 respondents from the 2004-2018 class cohorts of 12th grade students participating in the nationally-representative Monitoring the Future study was surveyed up to two times from modal ages 19 through 22 (in 2008-2019). Respondents self-reported negative consequences related to their own past 12-month marijuana use. Bivariate and multivariable models examined subgroup differences in consequence prevalence. RESULTS: Approximately 60% of those using frequently (20+ use occasions in the past 30 days) and 35% of those using non-frequently reported negative consequences. Among all young adult marijuana users, 31.1% reported emotional/physical consequences, 12.9% performance/financial consequences, and 12.3% relational consequences. Use frequency was positively associated with consequence likelihood, excluding regret and unsafe driving. Among college students, frequent use was more strongly associated with any and performance/financial consequences. Controlling for use frequency, men reported more performance/financial consequences; relational consequences were higher among Hispanic (vs. White) respondents, and those living with parents, employed full-time, and not attending 4-year colleges. CONCLUSION: Young adults using marijuana reported a wide range of negative use consequences; likelihood of most consequences increased with higher use frequency. Perceived consequences varied by college attendance, living situation, employment, sex, and race/ethnicity. Efforts to reduce negative marijuana consequences may be strengthened by recognizing and addressing the different types of negative consequences users perceive.

Social Role, Behavior, and Belief Changes Associated With Driving After Using Marijuana Among U.S. Young Adults, and Comparisons With Driving After 5+ Drinking.

OBJECTIVE: This study examined past-2-week driving after marijuana use (DMU) and driving after having five or more drinks (D5D) during young adulthood, specifically focusing on associations between within-person change in social roles (living situation, marriage, parenthood, education, employment) and mediators (perceived risk, evenings out, and religiosity) from modal ages 19 to 30. METHOD: Multilevel analyses were conducted using survey data collected from 2013 to 2019 from 1,873 adults (1,060 women; total number of data collection waves = 7,037) participating in the longitudinal Monitoring the Future study. RESULTS: Change across waves from not being married to married was associated with lower DMU likelihood at any particular wave both directly and via mediation through wave-level change in evenings out. Change in employment (not employed to employed full time) was associated with higher D5D likelihood at any particular wave both directly and via mediation through change in evenings out. Wave-level change in other social roles was indirectly associated with DMU/D5D likelihood via wave-level change in evenings out. CONCLUSIONS: Change in all social roles examined was associated with change in evenings out, which appears to be a primary, proximal predictor of young adult DMU/D5D. Improved understanding of how socialization change is associated with driving after substance use may strengthen efforts to reduce the harms associated with such driving behaviors.

Consideration of an upper-bound continuous maximum drinks measure for adolescent binge and high-intensity drinking prevalence.

BACKGROUND: The degree to which binge and high-intensity drinking prevalence estimates vary from fixed threshold frequency and continuous maximum drinks measures is unknown. The current study compared prevalence estimates for adolescent binge and high-intensity drinking (5+ drinks, 10+ drinks, respectively) and sex-specific thresholds using fixed threshold frequency and continuous maximum drinks measures. METHODS: Data were obtained from 7911 respondents participating in the 2018 and 2019 nationally representative Monitoring the Future 12th-grade surveys. Comparisons of frequency prevalence (e.g., any occasions of 5+ drinking using the frequency measure) versus maximum drinks prevalence (e.g., reporting 5 or more drinks using the maximum number of drinks measure) were made using all respondents and then separately within males and females. RESULTS: Among the sample overall and within sex, binge drinking estimates from the 5+ frequency prevalence and 5+ maximum drinks prevalence measures evidenced overlapping confidence intervals (estimates were slightly higher for frequency prevalence); similar results were observed for high-intensity drinking 10+ frequency prevalence and 10+ maximum drinks prevalence. For example, among the sample overall, 5+ frequency prevalence was 11.4% [95% CI 10.3, 12.6]; 5+ maximum drinks prevalence was 10.7% [9.6, 11.8]; 10+ frequency prevalence was 5.1% [4.4, 5.8]; and 10+ maximum drinks prevalence was 4.1% [3.5, 4.7]. Using sex-specific thresholds (i.e., 4+ drinks for females and 5+ drinks for males), binge frequency and maximum drinks levels also had overlapping confidence intervals. Binge drinking prevalence estimates for females were approximately 1.5 times higher using sex-specific (4+) versus universal (5+) thresholds. CONCLUSIONS: In this nationally representative sample of 12th-grade students, prevalence levels for 5+ and 10+ drinking did not differ significantly when using frequency versus maximum drinks measures. Among females, binge drinking prevalence was higher using sex-specific versus universal thresholds. Both the frequency and maximum drinks measures provided comparable estimates of binge and high-intensity drinking prevalence among older adolescents.

Drinking Intensity at Age 29/30 as a Predictor of Alcohol Use Disorder Symptoms at Age 35 in a National Sample.

OBJECTIVE: The purpose of this longitudinal study was to identify associations of drinking intensity at age 29/30 with symptoms of alcohol use disorder (AUD) at age 35. METHOD: Analyses used national longitudinal data from 1,253 individuals (53.5% female) participating in the Monitoring the Future study. Age 29/30 data were collected from 2005 to 2013; age 35 data were collected from 2010 to 2018. Multivariable models regressed age 35 past-5-year AUD symptoms (vs. nondisordered drinking/abstinence) on age 29/30 past-2-week drinking intensity (no/low [0-4] drinking, binge [5-9] drinking, high-intensity [10+] drinking), with key covariates being controlled for. RESULTS: At age 35, 32.6% (SE = 1.50) of respondents reported AUD symptoms. AUD symptoms at age 35 were reported by 77.5% (SE = 4.79) of participants who reported age 29/30 high-intensity drinking and 60.6% (SE = 3.95) of participants who reported age 29/30 binge drinking. Age 35 past-5-year abstinence was reported by almost no respondents reporting age 29/30 binge drinking or high-intensity drinking. AUD symptoms at age 35 were significantly more likely for those who reported binge (adjusted multivariable odds ratio [AOR] = 5.61, 95% CI [3.79, 8.30], p < .001) or high-intensity (AOR = 12.26, 95% CI [6.70, 22.41], p < .001) drinking versus no/low drinking at age 29/30. The likelihood of having AUD symptoms was significantly higher for high-intensity than for binge drinkers (AOR = 2.18, 95% CI [1.14, 4.19], p = .019). CONCLUSIONS: Nearly 80% of those young adults who reported engaging in high-intensity drinking (10+ drinks in a row) at age 29/30 later reported AUD symptoms at age 35. High-intensity drinking appears to be a strong prospective marker of risk for AUD symptoms among adults in the United States.

Drinking Motives and Drinking Consequences across Days: Differences and Similarities between Moderate, Binge, and High-Intensity Drinking.

BACKGROUND: The current study examined the extent to which within-person variation in drinking motives differentiates moderate, binge, and high-intensity drinking; and independent associations of motives and drinking intensity with alcohol use consequences in a sample of young adult drinkers from across the United States. METHODS: Participants were past 30-day drinkers in the U.S. nationally representative Monitoring the Future 12th grade sample in 2018, who also reported alcohol use during a 14-day data collection burst 1 year later (N = 484 people, mean age 19.3 [SD 0.40], 43% female; N = 1042 drinking days) as part of the Young Adult Daily Life Study in 2019. Weighted multilevel modeling estimated within- and between-person associations of drinking motives, drinking intensity (i.e., moderate [women 1-3, men 1-4 drinks], binge [women 4-7, men 5-9 drinks], and high-intensity drinking [women 8+, men 10+ drinks]), and number of positive and negative alcohol consequences. RESULTS: On days participants reported greater enhancement and social motives, they were more likely to engage in high-intensity (vs. binge) drinking and binge (vs. moderate) drinking and experience more positive alcohol consequences. On days participants reported greater enhancement and coping motives, they experienced more negative alcohol consequences. Binge (vs. moderate) drinking on a given day was associated with more positive and negative alcohol consequences; high-intensity (vs. binge) drinking on a given day was associated with more negative alcohol consequences that day. Moderation analyses indicated that social motives were associated with high-intensity (vs. binge) drinking only among college students. CONCLUSIONS: Stronger drinking motives on a given day were associated with drinking intensity (enhancement and social motives) and negative consequences (enhancement and coping). High-intensity (vs. binge or moderate) drinking was associated with more negative consequences but not more positive consequences. These results underscore that high-intensity drinking and consequences vary across days and time-varying, occasion-specific risks such as current motivational context are appropriate targets for intervention.

Diversion of Medical Marijuana to Unintended Users Among U.S. Adults Age 35 and 55, 2013-2018.

OBJECTIVE: This study estimated the percentage of age 35 and 55 adults reporting using medical marijuana intended for someone else (diverted use) and compared demographics and health status of such users with respondents reporting recommended use (i.e., individuals with a medical marijuana recommendation for their own health conditions) and to respondents using marijuana not intended for medical use (nonmedical marijuana [NMM] use). METHOD: Cross-sectional analyses were conducted using complex sample survey data collected from 2013 to 2018 from 12,138 adults (6,998 women) at modal ages 35 or 55 participating in the U.S. national Monitoring the Future study. RESULTS: Diverted use was reported by 72.9% [95% CI, 66.4, 79.4] and 64.3% [56.0, 72.7] of age 35 and 55 past-12-month medical marijuana users, respectively. Age 35 diverted users were more likely than recommended users to not work full time and have no postsecondary education. Age 55 recommended users were more likely than NMM users to be retired. Age 35 diverted users were less likely than recommended users to report poor physical health (odds ratio [OR] = 0.40 [0.17, 0.94]). Age 55 diverted users were less likely than recommended users to report three or more poor health conditions (OR = 0.22 [0.09, 0.55]) and any qualifying conditions (OR = 0.21 [0.08, 0.58]). Prevalence of these conditions was similar between diverted and NMM users. CONCLUSIONS: Results indicated a substantial degree of nonmedical (i.e., recreational) marijuana use. Diverted and NMM users reported generally similar levels of health conditions, whereas diverted users had fewer indicators of poor health than recommended users.

Changes in the Order of Cigarette and Marijuana Initiation and Associations with Cigarette Use, Nicotine Vaping, and Marijuana Use: U.S. 12th Grade Students, 2000-2019.

This study (a) examined changes in marijuana and cigarette initiation sequencing and (b) considered implications of such changes for prevention efforts by examining associations between initiation sequencing and current adolescent substance use. Analyses used 2000-2019 cross-sectional data from the national Monitoring the Future (MTF) study (78,252 U.S. 12th grade students). Models examined trends in six distinct patterns of initiation order, and multivariable associations between order of initiation and 30-day cigarette and marijuana use prevalence, cigarette and marijuana use frequency among users, and nicotine and marijuana vaping prevalence. While the percentage of students initiating neither cigarettes nor marijuana increased, increases also were observed in marijuana-only initiation (the fastest-growing pattern) and initiation of marijuana before cigarettes; these increases were accompanied by a significant decrease in cigarette-only initiation. Cigarette use prevalence and frequency were highest among students initiating cigarettes before marijuana; marijuana use prevalence and frequency were highest among students initiating marijuana before cigarettes. Cigarette and marijuana prevalence, as well as marijuana frequency, were lowest among students initiating only a single substance. Nicotine vaping was less prevalent among students initiating a single substance versus both substances, but no significant differences were observed in nicotine vaping prevalence between those initiating only cigarettes versus only marijuana. Implications of these findings for prevention efforts are discussed in the frameworks of both the common liability model and route of administration model.

The growing transition from lifetime marijuana use to frequent use among 12th grade students: U.S. National data from 1976 to 2019.

BACKGROUND: More United States adolescents now report high-frequency marijuana use than similar use levels of alcohol or tobacco. Increased high-frequency use raises questions such as (a) is frequent use likelihood growing among adolescents who experiment with use? (b) Is such change observed equally across sex and racial/ethnic subgroups? (c) Have sociodemographic and other covariate associations with frequent use changed over time? METHODS: Data were obtained from 649,505 12th grade students participating in the cross-sectional, nationally-representative Monitoring the Future study from 1976 to 2019. Historical trends were modeled for any and frequent (20+ occasions) past 30-day marijuana use among all students and lifetime users, and lifetime user sex and racial/ethnic subgroups. Multivariable logistic regression estimates from 1989 to 1993 (lowest prevalence years) versus 2015-2019 (most recent years) were compared to examine covariate association changes with frequent use. RESULTS: Among all students, recent linear trends in any and frequent marijuana use were not significantly different from zero (0.023 [SE 0.156] and 0.036 [0.073], respectively); frequent use among lifetime users increased (0.233 [0.107], p = 0.048). Among lifetime users, the increase was stronger for male than female students, and for minority versus White students. Significant association changes with race/ethnicity, parental education, and perceived risk were observed. CONCLUSIONS: The proportion of adolescent lifetime marijuana users reporting current frequent marijuana use increased, and is now at near-record levels. Increases were particularly strong among males and minority students. There appears to be an increasing likelihood that adolescents who experiment with marijuana use may progress to frequent use.