Skip to main content
NCBI home page
Journal of Studies on Alcohol and Drugs logoLink to Journal of Studies on Alcohol and Drugs
. 2021 Feb 15;82(1):93–102. doi: 10.15288/jsad.2021.82.93

Key Subgroup Differences in Age-Related Change From 18 to 55 in Alcohol and Marijuana Use: U.S. National Data

Megan E Patrick a,*, Deborah D Kloska a, Christopher J Mehus b, Yvonne Terry-McElrath a, Patrick M O’Malley a, John E Schulenberg a,c
PMCID: PMC7901262  PMID: 33573727

Abstract

Objective:

This study examined age-related change in alcohol use, marijuana use, and the association between the two, from ages 18 to 55, in a national longitudinal sample.

Method:

Data were from national Monitoring the Future study participants (N = 11,888) who were high school seniors in 1976–1980 and were eligible to respond to the age 55 survey in 2013–2017. Time-varying effect modeling was used to model past-30-day prevalence and associations between alcohol and marijuana across ages 18–55, overall and by sex, race/ethnicity, and college attendance.

Results:

Marijuana prevalence peaked at age 18 and was lowest in the late 40s; alcohol prevalence peaked at age 22 and was lowest in the early 40s. Associations between alcohol and marijuana use were strongest at age 18. Significant differences were observed by sex, race/ethnicity, and college attendance (e.g., women’s use was lower and decreased faster in the late 30s than men’s; White respondents’ alcohol and marijuana use were higher and peaked before Black respondents’; compared with non-attenders, college attenders’ use was higher for alcohol but lower for marijuana). The alcohol and marijuana use association was strongest at ages 18–20 for most subgroups, except Black respondents, for whom the association was strongest at age 30.

Conclusions:

Longitudinal data showed patterns of alcohol and marijuana use across adulthood. Such patterns highlight sociodemographic risk factors across the life span, ages that should be targeted for clinician awareness and intervention efforts, and populations at particular risk of harm from alcohol and marijuana co-use during adulthood. (J. Stud. Alcohol Drugs, 82, 93–102, 2021)

CHARTING THE NORMATIVE developmental course of alcohol and marijuana use across the life span is key for etiologic purposes and provides essential data for treatment and health service planning and provision. Both U.S. cross-sectional and longitudinal studies have shown that alcohol and marijuana use generally peak during the early 20s (Chassin et al., 2004; Dawson et al., 2015; Haberstick et al., 2014; Jackson et al., 2008; Juon et al., 2011; Karlamangla et al., 2006; Patrick et al., 2019a; Terry-McElrath & Patrick, 2018; Terry-McElrath et al., 2017). After the 20s, the likelihoods of using alcohol and marijuana tend to decrease (Karlamangla et al., 2006; Kerr et al., 2018; Substance Abuse and Mental Health Services Administration, 2019; Terry-McElrath et al., 2017), but the developmental course through mid-adulthood has not been well studied.

A small literature has examined mid-adulthood use changes. For example, based on cross-sectional data from U.S. national studies using discrete age categories: (a) frequency and quantity of alcohol decreased from the 20s to early 30s, rose slightly through the early 50s, and then lowered again (Chan et al., 2007); and (b) marijuana prevalence decreased between ages 18 and 50, with the strongest change occurring during the 20s (Kerr et al., 2018). Longitudinal research examining marijuana use between ages 18 and 50, using the same U.S. data as the current study, found that the majority of users were members of latent classes that ceased high probabilities of use in their 20s (Terry-McElrath et al., 2017). A needed next step in this research area is modeling continuous age-related change in alcohol and marijuana use from late adolescence through mid-adulthood.

Age-related change in degree of association between alcohol and marijuana use

Health risks associated with alcohol (Hingson et al., 2002, 2005) and marijuana use (Volkow et al., 2014) may be compounded for those using both substances during the same period (i.e., concurrent use). Among college freshmen, moderate drinkers who also used marijuana (vs. moderate drinkers who did not use marijuana) were more likely to report blackouts, driving under the influence, and drinking more than intended (Haas et al., 2015). Marijuana use has been associated with later alcohol use disorder onset and persistence (Weinberger et al., 2016). The majority of adolescent and young adult marijuana users report alcohol use (Pape et al., 2009; Patton et al., 2007; Terry-McElrath & Patrick, 2018), and concurrent use among adult alcohol users was 14% in the combined 2005/2010 National Alcohol Surveys (Subbaraman & Kerr, 2015). Rates of change in alcohol and marijuana use from late adolescence through mid-young adulthood have shown strong concordance (Jackson et al., 2008), but the degree to which alcohol and marijuana use are correlated at given ages from late adolescence to midlife is not known.

Sex, race/ethnicity, and college differences in age-related change

Men typically demonstrate higher alcohol and marijuana prevalence and frequency than women, although such sex differences have narrowed across historical time (Johnston et al., 2020; Schulenberg et al., 2020). Men are overrepresented among heavy users of marijuana (Caldeira et al., 2012; Nelson et al., 2015; Terry-McElrath et al., 2017) and alcohol (Nelson et al., 2015) and are at higher risk for alcohol and marijuana use disorders (Haberstick et al., 2014; Schulenberg et al., 2016). Concurrent alcohol and marijuana use was higher among men in 2000, but by 2005/2010, sex differences were not significant (Midanik et al., 2007; Subbaraman & Kerr, 2015). In longitudinal research from ages 12 to 34, men exhibited higher rates of change over time in alcohol and marijuana use than women (Chen & Jacobson, 2012); research of ages 18 to 30 found that peak binge drinking age occurred significantly later for men than for women (Patrick et al., 2019a). Research examining alcohol use from age 50 onward found that men were more likely to be among the minority of individuals whose alcohol use increased with age (Platt et al., 2010). Additional research examining sex differences in age-related alcohol and marijuana use change through midlife is needed.

Differential age-related changes in alcohol and marijuana use also are evident by race/ethnicity in the United States. During older adolescence, heavy drinking has been found to be significantly lower among Black than White youth, as has been marijuana use until recent years (Miech et al., 2019). Muthén and Muthén (2000) found that heavy drinking was significantly lower among Black than White individuals at age 18, but not by age 32. Chen and Jacobsen (2012) documented a higher rate of change between ages 12 and 34 in both alcohol and marijuana use for White versus Black individuals. Differences in age-related changes in alcohol and marijuana prevalence and/or association through mid-adulthood by race/ethnicity have not been examined.

Higher educational achievement has shown mixed associations with age-related change in alcohol and marijuana use. College attendance was associated with greater change in high-risk drinking across the transition into young adulthood (Patrick et al., 2016); alcohol abstinence from age 50 onward was negatively associated with years of education (Platt et al., 2010). However, having less than a high school education was associated with increased binge drinking during the mid-50s (Karlamangla et al., 2006) and membership in increasing alcohol use trajectories from age 50 onward (Bobo & Greek, 2011). The likelihood that adult alcohol users also used marijuana may be higher among those with less than a high school education (Midanik et al., 2007). Additional research is needed examining associations between college attendance and substance use from late adolescence through mid-adulthood.

Current study

This study addresses two specific research questions using national U.S. longitudinal data from ages 18 to 55: (a) How does modeled age-related change in past-30-day alcohol and marijuana prevalence vary by sex, race/ethnicity, and college attendance and (b) how does the modeled age-related association between alcohol use and marijuana use vary by sex, race/ethnicity, and college attendance?

Method

Sample

This study used longitudinal panel data from the Monitoring the Future (MTF) study (Schulenberg et al., 2020). Since 1976, MTF has surveyed annual nationally representative samples of high school seniors (modal age [hereafter referred to simply as “age”] 18) in the contiguous United States (Miech et al., 2019). About 2,450 respondents were selected yearly for longitudinal follow-up, randomized to begin 1 or 2 years after high school (i.e., ages 19 or 20; Schulenberg et al., 2020). Using mailed questionnaires, respondents were surveyed biennially up to six times between ages 19 and 30, and every 5 years from ages 35 to 55, totaling up to 12 data collection waves from 12th grade through age 55.

The analytic sample included 11,888 respondents who were high school seniors in 1976–1980, were eligible to respond to the age 55 survey during 2013–2017, and provided data for at least one wave. The unweighted sample was 50.1% female, 81.7% White, 11.0% Black, 7.3% other race/ethnicity. (The other group was combined because of sample size and included Hispanic [2.6%], American Indian [1.4%], Asian American [0.8%], and “other” race/ethnicity [2.6%].) Mean number of waves per participant was 10.2 (SD = 2.6); 73.5% provided data for six or more waves. At age 55, 50.6% (n = 6,017) responded. Depending on the sociodemographic subgroup, 90,348 to 96,823 data points were available for estimating coefficient functions. A University of Michigan Institutional Review Board approved the study.

Measures

Substance use.

At each wave, respondents reported past-30-day alcohol and marijuana use separately by answering, “On how many occasions (if any) have you used . . . during the last 30 days?” Data were coded into dichotomies indicating any use in the last 30 days (1) versus none (0).

Covariates.

Sex (female, male) and race/ethnicity (White, Black, other) were assessed at age 18. College attendance was a dichotomy indicating if respondents attended at least some college (full- or part-time) at any time from age 19 to 30. Age in years was based on wave and ranged from 18 to 55.

Analysis

Time-varying effect modeling was used to model continuous change from ages 18 to 55. The analytic approach examines associations over continuous time without parametric form assumptions (e.g., linear, quadratic, etc.); the only assumption is that coefficients change over time in a smooth way (Lanza et al., 2014; Tan et al., 2012). All analyses were conducted using SAS version 9.4 (SAS Institute Inc., Cary, NC), using the logistic option in the %WeightedTVEM macro (v2.6; Dziak et al., 2017, available for download at https://aimlab.psu.edu/tvem). The macro allows for inclusion of MTF age-specific attrition weights (calculated based on extensive information available from 12th grade measures). Using data from the 12 data collection waves, coefficient functions were estimated as a series of splines, incorporating data from neighboring time points; estimates for ages between the data collection points were interpolated based on surrounding data points. Analyses reported here used the macro default of 100 time points (in this case, continuous age) for plotting the estimated coefficient functions and their confidence bands (Li et al., 2017). Because of the large number of estimates across age, results are presented using figures showing point estimates and confidence intervals across age. Estimates for key sociodemographic subgroups were obtained by using “domain” and “which” statements allowing for differing functional forms within each subgroup. Model fit was based on pseudo likelihood information criteria (pseudo-Akaike information criterion, pseudo-Bayesian information criterion).

For modeling past-30-day alcohol and marijuana prevalence change, log-odds were converted to prevalence estimates for ease of presentation and discussion. Figures with 95% point-wise confidence intervals (CIs) present prevalence estimates across age; subgroup differences are significant when confidence intervals do not overlap. For modeling change in the extent to which alcohol use was associated with marijuana use likelihood, results are presented as odds ratios (ORs) and 95% point-wise confidence intervals. Interaction terms were used to test for subgroup differences; significant subgroup differences are indicated at ages in which interaction term confidence intervals did not include 1.0. If interactions were significant, subgroup-specific models were estimated and presented in figures showing subgroup-specific associations. For models examining racial/ethnic differences, three subgroups were included (White [referent], Black, and other). However, because of the high levels of heterogeneity reflected in the “other” category, only results for White and Black respondents are presented and discussed.

Results

Alcohol use

Figure 1a shows that overall 30-day alcohol prevalence increased from 71.5% (95% CI [70.6%, 72.5%]) at age 18 to an age 22 peak of 79.3% [78.5%, 80.1%] and then declined through age 42 to 64.0% [62.9%, 65.1%], where it remained stable through age 55 at 65.5% [64.1%, 66.8%].

Figure 1.

Figure 1.

Open in a new tab

Modeled prevalence of any past-30-day alcohol use among U.S. respondents ages 18–55: overall, by sex, by race/ethnicity, and by college attendance (12th-grade cohorts 1976–1980 combined). Notes: Estimates obtained from time-varying effect models. Dashed lines indicate 95% confidence intervals. Ns are unweighted. Overall: 95,886 data points from 11,177 individuals. By sex: Women: 51,114 data points from 5,621 individuals; men: 44,755 data points from 5,553 individuals. By race/ethnicity: White individuals: 81,885 data points from 9,214 individuals; Black individuals: 7,277 data points from 1,062 individuals. By college attendance: College attenders between ages 19 and 30: 45,399 data points from 4,461 individuals; non-college attenders between ages 19 and 30: 49,568 data points from 5,806 individuals.

Alcohol prevalence was significantly higher among men than women at all ages examined (Figure 1b), although sex differences decreased somewhat beginning at age 45. Among men, alcohol prevalence increased from 77.1% [76.2%, 77.9%] at age 18 to an age 23 peak of 84.4% [83.8%, 85.0%]; prevalence then declined steadily through age 47 to 68.9% [67.8%, 70.0%], after which there was a slight increase through age 55 to 70.0% [68.7%, 71.3%]. Among women, alcohol prevalence increased from 65.4% [64.3%, 66.4%] at age 18 to an age 22 peak of 74.3% [73.3%, 75.2%]. Prevalence for women declined thereafter at a faster pace than for men through age 39 to 58.2% [57.1%, 59.3%], and then increased slightly through age 52 to 61.1% [60.2%, 62.7%], where it remained steady through age 55.

Alcohol prevalence was significantly higher among White than Black respondents at all ages examined (Figure 1c). Among White respondents, prevalence increased from 77.3% [76.5%, 78.2%] at age 18 to a peak at age 21 of 82.1% [81.4%, 82.8%], followed by a gradual decline through age 41 to 67.2% [66.1%, 68.2%] and then relative stability through age 55 (68.5% [67.2%, 69.8%]). Among Black respondents, prevalence increased more steeply than among White respondents from 51.1% [50.0%, 52.3%] at age 18 to an age 23 peak of 68.7% [67.7%, 69.8%], followed by a steeper decrease than Whites through age 48 to 45.0% [43.7%, 46.2%] and then relative stability through age 55 to 46.2% [44.7%, 47.7%].

Regarding college attendance (Figure 1d), alcohol prevalence increased for both college attenders and non-attenders from ages 18 to 19 with no significant differences between the two groups. From ages 20 to 55, college attendance was associated with higher prevalence. Prevalence peaked for college attenders at age 22 at 83.1% [82.4%, 83.7%], declined through age 40 to 69.4% [68.4%, 70.3%], and then leveled off through age 55 to 71.6% [70.3%, 72.8%]. Prevalence for non-attenders peaked earlier at age 21 at 76.3% [75.5%, 77.2%], declined through age 50 to 58.5% [57.3%, 59.8%], and remained stable thereafter (ending at 59.2% [57.7%, 60.7%] at age 55).

Marijuana use

Overall 30-day marijuana prevalence peaked at 38.5% [37.5%, 39.5%] at age 18 (Figure 2a). This peak was followed by a decline through age 40 to 8.2% [7.7%, 8.8%] and another slower decline through age 47 to 7.4% [6.8%, 8.0%]; a very slight increase followed through age 55 to 8.1% [7.5%, 9.0%].

Figure 2.

Figure 2.

Open in a new tab

Modeled prevalence of any past-30-day marijuana use among U.S. respondents ages 18–55: overall, by sex, by race/ethnicity, and by college attendance (12th-grade cohorts 1976–1980 combined). Notes: Estimates obtained from time-varying effect models. Dashed lines indicate 95% confidence intervals. Ns are unweighted. Overall: 96,823 data points from 11,449 individuals. By sex: Women: 51,675 data points from 5,777 individuals; men: 45,130 data points from 5,670 individuals. By race/ethnicity: White individuals: 82,344 data points from 9,340 individuals; Black individuals: 7,627 data points from 1,170 individuals. By college attendance: College attenders between ages 19 and 30: 45,731 data points from 4,526 individuals; non-college attenders between ages 19 and 30: 50,139 data points from 5,982 individuals.

Men showed significantly higher marijuana prevalence than women at all ages examined (Figure 2b). For men, peak prevalence at age 18 was 44.5% [43.4%, 45.5%], followed by a decline through age 48 to 10.0% [9.2%, 10.7%], where it remained steady through age 55 (10.6% [9.7%, 11.6%]). For women, peak prevalence at age 18 was 32.0% [31.2%, 32.8%] followed by a steady decline through age 46 to 4.9% [4.6%, 5.4%]; prevalence then increased slightly through age 55 to 5.9% [5.3%, 6.5%].

White individuals reported significantly higher marijuana prevalence than Black individuals at ages 18–19 and 29–44 (Figure 2c). Peak prevalence for White respondents was 39.8% [38.8%, 40.8%] at age 18 and for Black respondents was 35.7% [34.9%, 36.6%] at age 20. Lowest prevalence levels were 7.6% [7.0%, 8.2%] for Whites at age 48 and 5.9% [5.5%, 6.4%] for Blacks at age 45. Prevalence levels from ages 29 to 44 were significantly lower for Black than White individuals but otherwise converged.

Marijuana prevalence from ages 18 to 55 was significantly higher for college non-attenders than attenders (Figure 2d). Peak prevalence for non-attenders was observed at age 18 at 41.5% [40.4%, 42.5%]; prevalence decreased through age 48 to 8.7% [8.0%, 9.4%] and then increased slightly through age 55 to 9.3% [8.5%, 10.2%]. Peak prevalence for college attenders was observed at age 20 at 33.6% [32.7%, 34.4%]; prevalence then declined through age 46 to 6.1% [5.6%, 6.5%] and then increased slightly through age 55 to 7.0% [6.4%, 7.7%].

Alcohol and marijuana use associations

The likelihood of reporting past-30-day marijuana use was significantly higher among those reporting past-30-day alcohol use at all ages examined, but the degree of association varied markedly across age (Figure 3a). The association was strongest at ages 18–19 with an OR of 11.5 [10.1, 13.1], but then weakened considerably through age 35 to OR 4.5 [3.8, 5.4], and continued to weaken somewhat through age 55 to OR 2.3 [1.8, 3.0]. Interaction models indicated significant differences based on sex, race/ethnicity, and college attendance.

Figure 3.

Figure 3.

Open in a new tab

Modeled age-varying associations between past-30-day alcohol use and the odds of past-30-day marijuana use among U.S. respondents ages 18–55: overall, by sex, by race/ethnicity, and by college attendance. Notes: Estimates obtained from time-varying effect models. Dashed lines indicate 95% confidence intervals. Ns are unweighted. Overall: 94,648 data points from 10,955 individuals. By sex: Women: 50,528 data points from 5,534 individuals; men: 44,104 data points from 5,419 individuals. By race/ethnicity: White individuals: 80,974 data points from 9,081 individuals; Black individuals: 7,084 data points from 1,014 individuals. By college attendance: College attenders between ages 19 and 30: 44,959 data points from 4,397 individuals; non-college attenders between ages 19 and 30: 48,798 data points from 5,676 individuals.

The likelihood of marijuana use among alcohol users was significantly stronger for men than women at ages 19–24 and 42–50 (Figure 3b). From ages 19 to 24, association strength for women was decreasing from an age 18 peak; in contrast, men did not reach peak association strength until age 20. At age 20, the OR for marijuana use among alcohol users was 13.3 [11.7, 15.3] for men compared with 7.7 [6.8, 8.8] for women. From ages 42 to 50, association strength was decreasing for women but evidencing an inverted U-shaped increase for men. For example, at age 45, the OR for men was 3.7 [3.0, 4.6] compared with 2.2 [1.7, 2.7] for women.

The likelihood of marijuana use among alcohol users was significantly lower among Black than White respondents at ages 18–20 (Figure 3c), when association strength decreased from the age 18 peak association strength for White individuals but increased for Black individuals. The likelihood of marijuana use based on alcohol use was significantly higher among Black than White respondents at ages 25–41, when association strength decreased among White individuals but rose to peak association strength at age 30 among Black individuals. At age 30, the OR for Black individuals was 14.7 [12.5, 17.3] versus 5.2 [4.5, 6.2] for White individuals.

The likelihood of marijuana use among alcohol users was higher for college attenders than non-attenders at ages 18–19 and 24–41 (Figure 3d). During ages 18–19, association strength was decreasing from an age 18 peak for college attenders but slightly increasing to an age 20 peak for non-attenders. From ages 24 to 41, association strength was decreasing for both subgroups. At age 30, the OR for 30-day marijuana use among 30-day alcohol users was 9.2 [7.8, 10.9] for college attenders compared with 5.3 [4.5, 6.3] for non-attenders.

Discussion

Alcohol and marijuana use research has focused most frequently on adolescence and young adulthood; the present study extends this research into mid-adulthood by modeling key socioeconomic subgroup differences in age-related change from 18 to 55 in alcohol and marijuana prevalence and the likelihood of marijuana use based on alcohol use. Significant differences by sex, race/ethnicity, and college attendance were observed in (a) highest subgroup prevalence across age, (b) ages of peak prevalence, (c) ages of prevalence stabilization during the 40s and indications of increasing prevalence during the 50s, and (d) ages of peak strength in marijuana use likelihood based on alcohol use.

Our findings regarding sex, race/ethnicity, and college attendance differences in overall alcohol and marijuana prevalence support some prior studies while contrasting with others. Prior research indicated higher alcohol use among men than women (Johnston et al., 2019; Schulenberg et al., 2020), whereas findings regarding sex differences in marijuana use have been mixed (Bachman et al., 1997, 2002; Midanik et al., 2007; Subbaraman & Kerr, 2015). In the current study, men reported higher alcohol and marijuana prevalence than women from ages 18 to 55. Prior research found lower alcohol use among Black than White older adolescents (Muthén & Muthén, 2000); by the early 30s, alcohol use was similar between the two groups, whereas Black individuals reported higher marijuana use (Chen & Jacobson, 2012; Muthén & Muthén, 2000). The current study found consistently higher alcohol and marijuana prevalence among White compared with Black individuals. Regarding education, college has been associated with steeper increases and decreases in heavy drinking during the 20s (Patrick et al., 2016) and moderate marijuana use during the 20s that decreases thereafter (Terry-McElrath et al., 2017). Results from the current study show that those with at least some college education had higher alcohol prevalence from ages 19 to 55, but lower marijuana prevalence across ages 18–55. Targeted prevention and intervention efforts should start from an understanding that male (vs. female) and White (vs. Black) individuals are at greater risk for alcohol and marijuana use from adolescence through mid-adulthood. In addition, college attenders are at greater risk for alcohol use throughout adulthood, and non-attenders are at greater risk for marijuana use from adolescence through adulthood. Drug use intervention programs for young adults who do not attend college are needed.

The current study’s findings on peak prevalence age both supported and added new information to previous research. Consistent with previous research (Schulenberg et al., 2020), overall marijuana prevalence peaked in late adolescence (age 18), whereas overall alcohol prevalence peaked during early young adulthood (age 22). Prior research indicated that peak binge drinking prevalence occurred earlier among women than men (Patrick et al., 2019a); these results were supported by the current study. In fact, this study found sex differences in peak alcohol prevalence age (women before men), and differences in peak alcohol and marijuana prevalence age by race/ethnicity (White before Black individuals) and education (non-college before college individuals). Across sociodemographic subgroups, the age range was 18–20 for peak marijuana prevalence and 21–23 for peak alcohol prevalence. Differences in age at peak prevalence may be particularly important for marijuana. The peak age of 18 (for the population overall, men, women, White individuals, and non-college attenders) would suggest that primary prevention efforts occur during high school. However, the peak age of 20 for both Black individuals and for college students indicates a need for targeted prevention efforts during early young adulthood.

Prior cross-sectional research indicated that alcohol prevalence declined through the 30s, stabilized in the 40s, and rose slightly around age 50, whereas marijuana prevalence declined throughout these ages (Chan et al., 2007; Kerr et al., 2018). The current study found a meaningful degree of variation in ages characterized by declining prevalence. The alcohol use decline continued longer for men than women (through ages 47 vs. 39, respectively), for Black than White individuals (48 vs. 41), and for those without versus with a college education (50 vs. 40). The decline in marijuana prevalence across subgroups was generally longer for men than women (48 vs. 46), White than Black respondents (48 vs. 45), and those without versus with college education (48 vs. 46). Some evidence of increased prevalence of use during mid-adulthood was observed for alcohol (men and women) and marijuana (women, as well as both those with and without college education). The slight rise in use during the 50s—particularly for marijuana—may represent recent period effects seen in other studies, rather than age effects (Kerr et al., 2018). Both clinician awareness of and interventions targeting the likelihood of increasing alcohol and/or marijuana use during mid-adulthood are needed.

Health risks associated with alcohol and marijuana use (Hingson et al., 2002, 2005; Volkow et al., 2014) may be compounded as a result of concurrent or simultaneous use. The majority of concurrent alcohol and marijuana users use simultaneously (Patrick et al., 2019b), and simultaneous use has been associated with increased risk of mental and physical health problems, unsafe driving, and substance use dependence (Patrick et al., 2019b; Terry-McElrath et al., 2014). These increased risks result from the additive effects of simultaneous use (Belgrave et al., 1979; Chesher et al., 1976; Kelly et al., 2004; Lamers & Ramaekers, 2001; Ramaekers et al., 2000; Robbe, 1998). The current study’s findings indicate that overall, the strength of association between marijuana and alcohol decreased notably from ages 18 to 19 through the mid-30s and then continued a lower rate of decrease through age 55. Only among men was there any increase in the strength of association after age 30. Alcohol and marijuana were most correlated at ages 18–20 for all subgroups except Black individuals, among whom the correlation was strongest at age 30. The markedly later age of peak association among Black individuals is consistent with prior evidence that the percentage of alcohol users who also report marijuana use is greater among Black than White adults (Midanik et al., 2007; Subbaraman & Kerr, 2015). It is important to note that the association between current alcohol and marijuana use is likely reciprocal, although it was modeled as current marijuana use conditional on current alcohol use.

Strengths and limitations

These findings are subject to limitations. The sample was drawn from 12th-grade students; results may not generalize to those who drop out before 12th grade, as alcohol and marijuana use are higher among those who drop out (Bachman et al., 2008; Tice et al., 2017). The present study concerns age-related change among five cohorts (1976–1980) of high school seniors followed through age 55; some observed age-related change likely reflects period effects. Future longitudinal research including more recent cohorts could determine the generalizability of our age-related findings. Additional considerations including relationship status, employment status, and mental health should be examined in future research. Other limitations include self-reported data and attrition (although attrition weights were used). These limitations notwithstanding, the current analysis utilized a time-varying effect model and data from a national sample of U.S. 12th-grade students followed through mid-adulthood to model age-related change in alcohol prevalence, marijuana prevalence, and associations between these two substances to help better inform targeted prevention and intervention efforts.

Conclusions

The overall pattern of adult alcohol and marijuana use was peak prevalence at age 18 (for marijuana use) and age 22 (for alcohol use), and lowest prevalence of use in the 40s followed by slight increases in use during the 50s. Alcohol and marijuana use were correlated across adulthood, but especially so among younger adults in general, with a particularly strong association between alcohol use and marijuana use for Black adults around age 30. Sociodemographic characteristics are indicators of increased risk. Namely, male (vs. female) and White (vs. Black) individuals are at greater risk for alcohol use and marijuana use from adolescence through mid-adulthood. College attenders are at greater risk for alcohol use and non-attenders are at greater risk for marijuana use across adulthood. Prevention programs during high school are important to address the fact that the peak prevalence in marijuana use is generally age 18, although later for college attenders and Black individuals. Interventions focused on alcohol and marijuana are needed across young and middle adulthood.

Footnotes

This research was supported by awards from the National Institute on Drug Abuse (R01DA037902 to Megan Patrick for manuscript preparation; R01DA001411 to Richard Miech and R01DA016575 to John Schulenberg for data collection and manuscript preparation) and the National Institute on Alcohol Abuse and Alcoholism R01AA026861 (to Katherine Keyes & Justin Jager). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

References

  1. Bachman J. G., O’Malley P. M., Schulenberg J. E., Johnston L. D., Bryant A. L., Merline A. C. The decline of substance use in young adulthood: Changes in social activities, roles, and beliefs. Mahwah, NJ: Lawrence Erlbaum Associates; 2002. [Google Scholar]
  2. Bachman J. G., O’Malley P. M., Schulenberg J. E., Johnston L. D., Freedman-Doan P., Messersmith E. E. The education–drug use connection: How successes and failures in school relate to adolescent smoking, drinking, drug use, and delinquency. Mahwah, NJ: Lawrence Erlbaum Associates/Taylor & Francis; 2008. [Google Scholar]
  3. Bachman J. G., Wadsworth K. N., O’Malley P. M., Johnston L. D., Schulenberg J. E. Smoking, drinking, and drug use in young adulthood: The impacts of new freedoms and new responsibilities. Mahwah, NJ: Lawrence Erlbaum Associates; 1997. [Google Scholar]
  4. Belgrave B. E., Bird K. D., Chesher G. B., Jackson D. M., Lubbe K. E., Starmer G. A., Teo R. K. The effect of (−) trans-delta9-tetra-hydrocannabinol, alone and in combination with ethanol, on human performance. Psychopharmacology. 1979;62:53–60. doi: 10.1007/BF00426035. doi:10.1007/BF00426035. [DOI] [PubMed] [Google Scholar]
  5. Bobo J. K., Greek A. A. Increasing and decreasing alcohol use trajectories among older women in the U.S. across a 10-year interval. International Journal of Environmental Research and Public Health. 2011;8:3263–3276. doi: 10.3390/ijerph8083263. doi:10.3390/ijerph8083263. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Caldeira K. M., O’Grady K. E., Vincent K. B., Arria A. M. Marijuana use trajectories during the post-college transition: Health outcomes in young adulthood. Drug and Alcohol Dependence. 2012;125:267–275. doi: 10.1016/j.drugalcdep.2012.02.022. doi:10.1016/j.drugalcdep.2012.02.022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Chan K. K., Neighbors C., Gilson M., Larimer M. E., Marlatt G. A. Epidemiological trends in drinking by age and gender: Providing normative feedback to adults. Addictive Behaviors. 2007;32:967–976. doi: 10.1016/j.addbeh.2006.07.003. doi:10.1016/j.addbeh.2006.07.003. [DOI] [PubMed] [Google Scholar]
  8. Chassin L., Flora D. B., King K. M. Trajectories of alcohol and drug use and dependence from adolescence to adulthood: The effects of familial alcoholism and personality. Journal of Abnormal Psychology. 2004;113:483–498. doi: 10.1037/0021-843X.113.4.483. doi:10.1037/0021-843X.113.4.483. [DOI] [PubMed] [Google Scholar]
  9. Chen P., Jacobson K. C. Developmental trajectories of substance use from early adolescence to young adulthood: Gender and racial/ethnic differences. Journal of Adolescent Health. 2012;50:154–163. doi: 10.1016/j.jadohealth.2011.05.013. doi:10.1016/j.jadohealth.2011.05.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Chesher G. B., Franks H. M., Hensley V. R., Hensley W. J., Jackson D. M., Starmer G. A., Teo R. K. The interaction of ethanol and delta9-tetrahydrocannabinol in man: Effects on perceptual, cognitive and motor functions. Medical Journal of Australia. 1976;2:159–163. [PubMed] [Google Scholar]
  11. Dawson D. A., Goldstein R. B., Saha T. D., Grant B. F. Changes in alcohol consumption: United States, 2001-2002 to 2012-2013. Drug and Alcohol Dependence. 2015;148:56–61. doi: 10.1016/j.drugalcdep.2014.12.016. doi:10.1016/j.drugalcdep.2014.12.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Dziak J. J., Li R., Wagner A. T. Weighted TVEM SAS Macro Users’ Guide (Version 2.6) 2017 Retrieved from https://www.cpc.unc.edu/projects/addhealth/publications/7007.
  13. Haas A. L., Wickham R., Macia K., Shields M., Macher R., Schulte T. Identifying classes of conjoint alcohol and marijuana use in entering freshmen. Psychology of Addictive Behaviors. 2015;29:620–626. doi: 10.1037/adb0000089. doi:10.1037/adb0000089. [DOI] [PubMed] [Google Scholar]
  14. Haberstick B. C., Young S. E., Zeiger J. S., Lessem J. M., Hewitt J. K., Hopfer C. J. Prevalence and correlates of alcohol and cannabis use disorders in the United States: Results from the National Longitudinal Study of Adolescent Health. Drug and Alcohol Dependence. 2014;136:158–161. doi: 10.1016/j.drugalcdep.2013.11.022. doi:10.1016/j.drugalcdep.2013.11.022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Hingson R., Heeren T., Winter M., Wechsler H. Magnitude of alcohol-related mortality and morbidity among U.S. college students ages 18-24: Changes from 1998 to 2001. Annual Review of Public Health. 2005;26:259–279. doi: 10.1146/annurev.publhealth.26.021304.144652. doi:10.1146/annurev.publhealth.26.021304.144652. [DOI] [PubMed] [Google Scholar]
  16. Hingson R. W., Heeren T., Zakocs R. C., Kopstein A., Wechsler H. Magnitude of alcohol-related mortality and morbidity among U.S. college students ages 18–24. Journal of Studies on Alcohol. 2002;63:136–144. doi: 10.15288/jsa.2002.63.136. doi:10.15288/jsa.2002.63.136. [DOI] [PubMed] [Google Scholar]
  17. Jackson K. M., Sher K. J., Schulenberg J. E. Conjoint developmental trajectories of young adult substance use. Alcoholism: Clinical and Experimental Research. 2008;32:723–737. doi: 10.1111/j.1530-0277.2008.00643.x. doi:10.1111/j.1530-0277.2008.00643.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Johnston L. D., Schulenberg J. E., O’Malley P. M., Bachman J. G., Miech R. A., Patrick M. E. Demographic subgroup trends among young adults in the use of various licit and illicit drugs, 1988-2019 (Monitoring the Future Occasional Paper No. 95) 2020 [Google Scholar]
  19. Juon H.-S., Fothergill K. E., Green K. M., Doherty E. E., Ensminger M. E. Antecedents and consequences of marijuana use trajectories over the life course in an African American population. Drug and Alcohol Dependence. 2011;118:216–223. doi: 10.1016/j.drugalcdep.2011.03.027. doi:10.1016/j.drugalcdep.2011.03.027. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Karlamangla A., Zhou K., Reuben D., Greendale G., Moore A. Longitudinal trajectories of heavy drinking in adults in the United States of America. Addiction. 2006;101:91–99. doi: 10.1111/j.1360-0443.2005.01299.x. doi:10.1111/j.1360-0443.2005.01299.x. [DOI] [PubMed] [Google Scholar]
  21. Kelly E., Drake S., Ross J. A review of drug use and driving: Epidemiology, impairment and risk perceptions. Drug and Alcohol Review. 2004;23:319–344. doi: 10.1080/09595230412331289482. doi:10.1080/09595230412331289482. [DOI] [PubMed] [Google Scholar]
  22. Kerr W. C., Lui C., Ye Y. Trends and age, period and cohort effects for marijuana use prevalence in the 1984-2015 US National Alcohol Surveys. Addiction. 2018;113:473–481. doi: 10.1111/add.14031. doi:10.1111/add.14031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Lamers C., Ramaekers J. Visual search and urban city driving under the influence of marijuana and alcohol. Human Psychopharmacology. 2001;16:393–401. doi: 10.1002/hup.307. doi:10.1002/hup.307. [DOI] [PubMed] [Google Scholar]
  24. Lanza S. T., Vasilenko S. A., Liu X., Li R., Piper M. E. Advancing the understanding of craving during smoking cessation attempts: A demonstration of the time-varying effect model. Nicotine & Tobacco Research. 2014;16(Supplement 2):S127–S134. doi: 10.1093/ntr/ntt128. doi:10.1093/ntr/ntt128. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Li R., Dziak J. J., Tan X., Huang L., Wagner A. T., Yang J. TVEM (Time-vArying Effect Modeling) SAS Macro Users’Guide Version 3.1.1. 2017. Retrieved from https://www.methodology.psu.edu/files/2019/03/TVEM_3.1.1-1fxcco8.pdf. [Google Scholar]
  26. Midanik L. T., Tam T. W., Weisner C. Concurrent and simultaneous drug and alcohol use: Results of the 2000 National Alcohol Survey. Drug and Alcohol Dependence. 2007;90:72–80. doi: 10.1016/j.drugalcdep.2007.02.024. doi:10.1016/j.drugalcdep.2007.02.024. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Miech R., Johnston L. D., O’Malley P. M., Bachman J. G., Schulenberg J. E., Patrick M. E. Monitoring the Future national survey results on drug use, 1975–2018: Volume I, Secondary school students. 2019. Retrieved from http://www.monitoringthefuture.org/pubs/monographs/mtf-vol1_2019.pdf. [Google Scholar]
  28. Muthén B. O., Muthén L. K. The development of heavy drinking and alcohol-related problems from ages 18 to 37 in a U.S. national sample. Journal of Studies on Alcohol. 2000;61:290–300. doi: 10.15288/jsa.2000.61.290. doi:10.15288/jsa.2000.61.290. [DOI] [PubMed] [Google Scholar]
  29. Nelson S. E., Van Ryzin M. J., Dishion T. J. Alcohol, marijuana, and tobacco use trajectories from age 12 to 24 years: Demographic correlates and young adult substance use problems. Development and Psychopathology. 2015;27:253–277. doi: 10.1017/S0954579414000650. doi:10.1017/S0954579414000650. [DOI] [PubMed] [Google Scholar]
  30. Pape H., Rossow I., Storvoll E. E. Under double influence: Assessment of simultaneous alcohol and cannabis use in general youth populations. Drug and Alcohol Dependence. 2009;101:69–73. doi: 10.1016/j.drugalcdep.2008.11.002. doi:10.1016/j.drugalcdep.2008.11.002. [DOI] [PubMed] [Google Scholar]
  31. Patrick M. E., Terry-McElrath Y. M., Kloska D. D., Schulenberg J. E. High-intensity drinking among young adults in the United States: Prevalence, frequency, and developmental change. Alcoholism: Clinical and Experimental Research. 2016;40:1905–1912. doi: 10.1111/acer.13164. doi:10.1111/acer.13164. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Patrick M. E., Terry-McElrath Y. M., Lanza S. T., Jager J., Schulenberg J. E., O’Malley P. M. Shifting age of peak binge drinking prevalence: Historical changes in normative trajectories among young adults aged 18 to 30. Alcoholism: Clinical and Experimental Research. 2019a;43:287–298. doi: 10.1111/acer.13933. doi:10.1111/acer.13933. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Patrick M. E., Terry-McElrath Y. M., Lee C. M., Schulenberg J. E. Simultaneous alcohol and marijuana use among underage young adults in the United States. Addictive Behaviors. 2019b;88:77–81. doi: 10.1016/j.addbeh.2018.08.015. doi:10.1016/j.addbeh.2018.08.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Patton G. C., Coffey C., Lynskey M. T., Reid S., Hemphill S., Carlin J. B., Hall W. Trajectories of adolescent alcohol and cannabis use into young adulthood. Addiction. 2007;102:607–615. doi: 10.1111/j.1360-0443.2006.01728.x. doi:10.1111/j.1360-0443.2006.01728.x. [DOI] [PubMed] [Google Scholar]
  35. Platt A., Sloan F. A., Costanzo P. Alcohol-consumption trajectories and associated characteristics among adults older than age 50. Journal of Studies on Alcohol and Drugs. 2010;71:169–179. doi: 10.15288/jsad.2010.71.169. doi:10.15288/jsad.2010.71.169. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Ramaekers J., Robbe H., O’Hanlon J. Marijuana, alcohol and actual driving performance. Human Psychopharmacology. 2000;15:551–558. doi: 10.1002/1099-1077(200010)15:7<551::AID-HUP236>3.0.CO;2-P. doi:10.1002/1099-1077(200010)15:7<551::AID-HUP236>3.0.CO;2-P. [DOI] [PubMed] [Google Scholar]
  37. Robbe H. Marijuana’s impairing effects on driving are moderate when taken alone but severe when combined with alcohol. Human Psychopharmacology. 1998;13:S70–S78. doi:10.1002/(SICI)1099-1077(1998110)13:2+<S70::AID-HUP50>3.0.CO;2-R. [Google Scholar]
  38. Schulenberg J. E., Johnston L. D., O’Malley P. M., Bachman J. G., Miech R. A., Patrick M. E. Monitoring the Future national survey results on drug use, 1975–2019: Volume II. College students and adults ages. 2020:19–60. [Google Scholar]
  39. Schulenberg J. E., Patrick M. E., Kloska D. D., Maslowsky J., Maggs J. L., O’Malley P. M. Substance use disorder in early midlife: A national prospective study on health and well-being correlates and long-term predictors. Substance Abuse: Research and Treatment. 2016;9(Supplement 1):41–57. doi: 10.4137/SART.S31437. doi:10.4137/SART.S31437. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Subbaraman M. S., Kerr W. C. Simultaneous versus concurrent use of alcohol and cannabis in the National Alcohol Survey. Alcoholism: Clinical and Experimental Research. 2015;39:872–879. doi: 10.1111/acer.12698. doi:10.1111/acer.12698. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Substance Abuse and Mental Health Services Administration. Key substance use and mental health indicators in the United States: Results from the 2018 National Survey on Drug Use and Health. (HHS Publication No. PEP19-5068, NSDUH Series H-54) 2019 Retrieved from https://www.samhsa.gov/data/ [Google Scholar]
  42. Tan X., Shiyko M. P., Li R., Li Y., Dierker L. A time-varying effect model for intensive longitudinal data. Psychological Methods. 2012;17:61–77. doi: 10.1037/a0025814. doi:10.1037/a0025814. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Terry-McElrath Y. M., O’Malley P. M., Johnston L. D., Bray B. C., Patrick M. E., Schulenberg J. E. Longitudinal patterns of marijuana use across ages 18-50 in a US national sample: A descriptive examination of predictors and health correlates of repeated measures latent class membership. Drug and Alcohol Dependence. 2017;171:70–83. doi: 10.1016/j.drugalcdep.2016.11.021. doi:10.1016/j.drugalcdep.2016.11.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Terry-McElrath Y. M., Patrick M. E. Simultaneous alcohol and marijuana use among young adult drinkers: Age-specific changes in prevalence from 1977 to 2016. Alcoholism: Clinical and Experimental Research. 2018;42:2224–2233. doi: 10.1111/acer.13879. doi:10.1111/acer.13879. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Tice P., Lipari R. N., Van Horn S. L. Substance use among 12th grade aged youths by dropout status. CBHSQ Report. 2017, August 15 Retrieved from https://www.samhsa.gov/data/sites/default/files/report_3196/ShortReport-3196.html. [PubMed] [Google Scholar]
  46. Volkow N. D., Baler R. D., Compton W. M., Weiss S. R. B. Adverse health effects of marijuana use. The New England Journal of Medicine. 2014;370:2219–2227. doi: 10.1056/NEJMra1402309. doi:10.1056/NEJMra1402309. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Weinberger A. H., Platt J., Goodwin R. D. Is cannabis use associated with an increased risk of onset and persistence of alcohol use disorders? A three-year prospective study among adults in the United States. Drug and Alcohol Dependence. 2016;161:363–367. doi: 10.1016/j.drugalcdep.2016.01.014. doi:10.1016/j.drugalcdep.2016.01.014. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Journal of Studies on Alcohol and Drugs are provided here courtesy of Rutgers University. Center of Alcohol Studies

RESOURCES