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. Author manuscript; available in PMC: 2022 Mar 24.
Published in final edited form as: Subst Abus. 2021 Mar 24;42(4):873–879. doi: 10.1080/08897077.2021.1890675

Alcohol trajectories and subsequent risk for opioid misuse in a cohort of urban adolescents

Johannes Thrul a,b,c, Beth A Reboussin d, Jill A Rabinowitz a, Brion S Maher a, Nicholas S Ialongo a
PMCID: PMC8460686  NIHMSID: NIHMS1689530  PMID: 33759726

Abstract

Background:

The opioid epidemic is a public health emergency in the US. Alcohol is the most widely used addictive substance among all age groups; however, the contribution of different alcohol use trajectories throughout adolescence and young adulthood to the development of opioid misuse in young adulthood among urban minority youth has not been investigated.

Methods:

Data are from a study of 580 youth (85% African American, 67% low SES) residing in Baltimore City followed from ages 6–26. Alcohol trajectories were identified between ages 14 and 26 using group-based trajectory modeling. Opioid misuse was defined as using opioid painkillers without a prescription or using heroin between ages 19 and 26. Opioid misuse outcomes were also investigated separately. Logistic regression examined associations of alcohol trajectories with opioid misuse in young adulthood adjusting for socio-demographics, early use of tobacco and cannabis, neighborhood, and peer factors.

Results:

Six alcohol use trajectories were identified: Young adult increasing (21.4%), adult increasing (19.1%), abstaining (19.1%), experimenting (15.3%), adolescent increasing (14.8%), and adolescent limited (10.2%). In models fully adjusted for covariates, relative to the abstaining trajectory, the adolescent increasing trajectory was associated with an elevated risk of opioid misuse (aOR = 3.3, 95%CI = 1.4, 7.8) and prescription opioid misuse (aOR = 3.9, 95%CI = 1.4, 10.8) in young adulthood.

Conclusions:

Escalating alcohol use in adolescence and young adulthood is associated with an elevated risk of opioid misuse in young adulthood in a cohort of predominantly African American and socio-economically disadvantaged young people. Tailored interventions should target high levels of alcohol use during these developmental periods to reduce risk for opioid misuse among disadvantaged youth.

Keywords: Cohort study, African-American, alcohol, opioids

Introduction

Opioid use and overdoses in the US have increased in recent years.1 While the initial wave of the epidemic was characterized by widespread use of prescription opioids in rural areas,2,3 the recent increase in overdose deaths due to heroin has been especially pronounced among African Americans,4 a fact that is frequently overlooked as the public attention focuses on the impact of the opioid epidemic on suburban, white, middle-class individuals.5 Indeed, youth living in urban areas are at increased risk for heroin and injection drug use.6 Given the significant public health burden associated with opioid use, there is a considerable need to determine risk factors and pathways related to opioid misuse among African American adolescents and young adults in order to inform public health officials and policy makers.

Alcohol is one of the most commonly used addictive substances in the US, with 70% of people ages 18 or older reporting past-year use and 55% reporting past month use.7 Moreover 19% of adolescents and young adults between 12 and 20 years old report past month underage drinking.7 Prescription opioids are frequently co-used with alcohol especially among young people,8,9 and the same has been documented for risky single occasion or binge drinking.10 A previous study using the nationally representative Monitoring the Future data of high school students found that prescription opioids were frequently co-ingested with alcohol, second only to co-ingestion with cannabis.11 While these studies point to an association between opioid and alcohol use among young people, they have relied on cross-sectional data, which limit the ability to draw conclusions about the time course of substance use. To the best of our knowledge, the question of whether different alcohol use trajectories throughout adolescence and young adulthood are associated with opioid misuse in young adulthood has not been investigated in the scientific literature to date.

Average drinking trajectories during adolescence and young adulthood often involve drinking that begins during adolescence, peaks during emerging adulthood, and declines during the mid-20s.12 There is, however, likely a substantial amount of variability in alcohol use over time besides this commonly observed trajectory of use. Trajectory modeling is one approach that has been used to identify multiple patterns of alcohol use through which individuals initiate, progress, and desist in their drinking.13 Studies that have examined trajectories of alcohol use have generally observed patterns of no/low use, adolescent limited use, late adolescent increasing use, and chronic, early use.14–16

Alcohol use among African Americans is of particular public health concern since existing research has demonstrated that they experience more alcohol-related problems than Whites, even after accounting for differences in drinking behavior.17 However, few studies of drinking trajectories focus on African Americans. In a previous study, we identified 6 different alcohol use trajectories throughout adolescence and young adulthood among urban minority youth and investigated associations between trajectory groups and risk factors at the family, peer-group, and neighborhood level.18 Given that opioid use is increasing in urban centers in the US,6 studies on potential associations between alcohol use trajectories and opioid use behaviors can potentially inform public health measures aimed at combatting opioid use and misuse among young people.

In light of limitations of the existing literature, the current study aimed to investigate alcohol use through adolescence and young adulthood as a risk factor for opioid misuse in young adulthood among a cohort of mostly African American participants from Baltimore, MD in the US. Moreover, the study modeled alcohol use trajectories, while also controlling for early use of tobacco and cannabis.

Methods

Sample

Data came from a randomized trial conducted by the Baltimore Prevention Research Center at the Johns Hopkins Bloomberg School of Public Health. A total of 799 children and families entering 1st grade in nine Baltimore City public elementary schools in 1993 were recruited to participate in two school-based, preventive interventions targeting early learning and aggressive and disruptive behavior. Students were randomly assigned to one of two intervention or control classrooms (nine schools, three classrooms per school). Interventions were provided during the 1st-grade year. The sample of 799 children was predominantly African American (85%), 46% were male, and the mean age at entrance into first grade was 6.2 years (SD = 0.37). About 2/3 of children were receiving free or reduced-price meals; a proxy for low socioeconomic status. Annual structured interviews were conducted from 6th grade through age 26 using an audio-computer assisted interview.

The analytical sample for the current analysis included 580 youth with a completed substance use assessment in 8th grade and at least one completed young adult assessment. The sample was 87% African American, 54% male, 65% were in a first-grade intervention classroom, and 71% received free or reduced-price meals. Youth excluded from the analysis due to missing data were more likely to be White (21% vs 13%, p < 0.001). There were no differences between the analytic sample and youth excluded from the analysis in terms of gender, intervention status, or receipt of free or reduced-price meals.

Measures

Substance use was assessed annually from grade 8 (approximately age 14) through age 26, using an audio-computer assisted interview to increase accurate reporting of sensitive behavior. The substance use questions were drawn from the Monitoring the Future Study.19

Alcohol use

Past year frequency of alcohol use (0 = none, 1 = once, 2 = twice, 3 = 3–4 times, 4 = 5–9 times, 5 = 10–19 times, 6 = 20–39 times, 7 = 40 or more times) was used to identify trajectories from 8th grade (approximately age 14) to age 26.

Opioid misuse

Data on opioid misuse were collected beginning at age 19. Opioid misuse included use of heroin and the misuse of prescription opioids (e.g., morphine, oxycodone, hydrocodone, hydromorphone, etc.). Participants who reported misusing any of these substances in the past year at any of the assessments between ages 19 and 26 were coded as positive for opioid misuse.

Early use of tobacco and cannabis

Data on tobacco and cannabis use were collected annually beginning at age 14. We created variables to reflect early use of tobacco and cannabis, defined as use of these substances before the age 15, which were included as covariates.

Neighborhood disorder

Perceptions of neighborhood disorder were assessed in 8th grade using 10 items from the Neighborhood Environment Scale.20 This scale contains items that assess neighborhood safety, violent crime, as well as drug use and sales. Items are rated on a 4-point Likert scale (1 = not at all true to 4 = very true) and summed to create a total score.

Neighborhood violence

Exposure to neighborhood violence was measured in 8th grade using the Children’s Report of Exposure to Violence.21 This measure assesses self-reported exposure to violence and victimization and covers topics such as being beaten up, robbed or mugged, stabbed or shot, witnessing someone else experience one of these events, or witnessing a murder. Responses were categorized into one binary indicator for any vs. no exposure to violence.

Deviant peer affiliation

We used a subset of items from the youth self-report scale22 to measure deviant peer affiliation in grades 6–8. Youths indicate how many of their friends (1 = none to 5 = all of them) have engaged in antisocial behavior, such as hitting or threatening someone, stealing, and damaging others’ property, and how many of their friends have used cannabis. This scale was the sum of seven items with higher scores indicating more deviant peer affiliation.

Socio-demographics and intervention status

The school district provided information on students’ gender and race. School records and parent reports indicating each student’s free and reduced-price meal status were collapsed into a dichotomous variable of free or reduced-price meals versus self-paid meals at any time during high school. This variable served as an indicator of student socioeconomic status. Intervention status was coded 1 for youth in a 1st grade intervention classroom and 0 otherwise.

Statistical analyses

Group-based trajectory modeling was used to identify patterns of past-year drinking frequency from age 14 to 26.13 Models used a zero-inflated Poisson distribution to account for the large number of youth that did not drink. Linear and quadratic terms for each trajectory group were included and compared. A range of different models including one to seven trajectory groups were considered. The best model was selected based on a combination of the Bayesian information criteria (BIC), entropy, group interpretability, and having reasonably large groups. Trajectory models were constructed using PROC TRAJ in SAS version 9.4. Maximum likelihood estimation was used to estimate model parameters. Participants were assigned to the drinking trajectory group with the highest probability of membership. Rates of opioid misuse overall, as well as prescription opioid misuse and heroin use separately, were examined for each alcohol trajectory group. A logistic regression model was fit to estimate the strength of the association between alcohol trajectory group membership and opioid misuse in young adulthood before and after adjustment for potentially confounding effects. We adjusted for potential confounding effects of gender, race, intervention group, receipt of free or reduced-price meals, neighborhood disorder, violence exposure, affiliation with deviant peers, as well as early use of tobacco and cannabis. Separate models were fit for opioid misuse, prescription opioid misuse, and heroin use. Odds ratios and 95% confidence intervals are presented.

Results

The BIC increased with the addition of each trajectory group, but the rate of improvement declined and reached an elbow at six groups (1 class = –13,486, 2 class = –11,362, 3 class = –10,689, 4 class = –10,307, 5 class = –10,123, 6 class = –9,992, 7 class = –9,914). Detailed fit indices are presented in Supplemental Table S1. The six group model had excellent classification accuracy (entropy = 0.93) and is presented in Figure 1. This model is consistent with the six group model identified in Reboussin et al.18 on a subset of the same cohort. The largest group reported a rapid increase in drinking at age 18 or early in young adulthood (group 1; young adult increasing, prevalence 21.4%). The second group reported very little drinking until after the legal drinking age of 21 at which point drinking frequency increased steadily until age 26 (group 2; adult increasing, prevalence 19.1%). The third group reported little to no drinking between ages 14 and 26 (group 3; abstaining, prevalence 19.1%). The fourth group began drinking in adolescence but very infrequently, declining to little to no drinking by age 26 (group 4; experimenting; prevalence 15.3%). The fifth group initiated drinking in adolescence and rapidly increases to more frequent drinking (group 5; adolescent increasing; prevalence 14.8%). The sixth group initiated drinking in adolescence but declined in drinking at age 18 (group 6; adolescent limited; prevalence 10.2%).

Figure 1.

Figure 1.

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Alcohol trajectories ages 14–26 (alcohol frequency y-axis legend: 0 = none, 1 = once, 2 = twice, 3 = 3–4 times, 4 = 5–9 times, 5 = 10–19 times, 6 = 20–39 times, 7 = 40 or more times).

Overall, 14.7% of our sample misused opioids in young adulthood. Specifically, 12.1% misused prescription opioids and 4.7% used heroin. As shown in Figure 2, the adolescent increasing alcohol trajectory group had the highest rates of opioid misuse (24.4%) and prescription opioid misuse (19.8%) followed by the adolescent limited group (22.0%, and 17.0%, respectively). The adolescent limited group had slightly higher rates of heroin use than the adolescent increasing group (10.2% vs 8.1%). The experimenting group had the next highest rates for all three opioid misuse outcomes (15.7%, 10.1%, 6.7%). Adult increasing (12.1%, 12.1%) and young adult increasing (11.7%, 11.7%) groups had similar rates of opioid and prescription opioid misuse but the adult increasing group had higher rates of heroin use (3.6% vs 0.8%). The lowest rates of opioid misuse were observed among the abstaining group (8.1%, 5.4%, 2.7%).

Figure 2.

Figure 2.

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Rates of opioid misuse between ages 19 and 26 by alcohol trajectory group.

Additional information on characteristics of the different trajectory groups is displayed in Table 1. There were significant between-group differences with regard to violence exposure, deviant peer affiliations, neighborhood disorder, early tobacco use, and cannabis use. Especially high rates and scores on these covariates were observed in the adolescent limited group, followed by the experimenting and adolescent increasing groups.

Table 1.

Individual, peer and neighborhood factors by alcohol trajectory group.

Characteristic Overall
N = 580		 Abstaining
N = 111		 Adult
Increasing
N = 111		 Young Adult Increasing
N = 124		 Experimenting
N = 89		 Adolescent
Limited
N = 59		 Adolescent
Increasing
N = 86		 p-Value
Male gender (N, %) 314 (54.1) 66 (59.5) 55 (50.0) 56 (45.2) 51 (57.3) 40 (67.8) 46 (53.5) 0.051
Nonwhite race (N, %) 505 (87.1) 97 (87.4) 101 (91.0) 109 (87.9) 81 (91.0) 49 (83.1) 68 (79.1) 0.128
Free/Reduced price lunch (N, %) 411 (70.9) 82 (73.9) 74 (66.7) 88 (71.0) 69 (77.5) 43 (72.9) 55 (64.0) 0.363
Intervention group(N, %) 378 (65.2) 71 (64.0) 57 (66.3) 76 (61.3) 60 (67.4) 36 (61.0) 57 (66.3) 0.722
Violence exposure (N, %) 334 (57.6) 54 (48.6) 55 (64.0) 61 (49.2) 57 (64.0) 48 (81.4) 55 (64.0) <0.001
Deviant peer affiliation (M, SD) 1.56 (0.64) 1.47 (0.59) 1.47 (0.55) 1.44 (0.47) 1.62 (0.68) 1.95 (0.87) 1.65 (0.70) <0.001
Neighborhood disorder (M, SD) 1.73 (0.64) 1.73 (0.62) 1.64 (0.59) 1.63 (0.60) 1.75 (0.67) 1.99 (0.66) 1.77 (0.67) 0.007
Early tobacco use (N, %) 195 (33.6) 24 (21.6) 19 (17.1) 32 (25.8) 41 (46.1) 37 (62.7) 42 (48.8) <0.001
Early cannabis use (N, %) 105 (18.1) 9 (8.1) 11 (9.9) 12 (9.7) 32 (36.0) 22 (37.3) 19 (22.1) <0.001
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Bold values represent statistical significance.

In unadjusted logistic regression models (Table 2), adolescent limited and adolescent increasing alcohol trajectory groups were significantly associated with an increased risk of opioid misuse in young adulthood relative to the abstaining group (OR = 3.2, 95%CI = 1.3, 8.0 and OR = 3.7 95%CI = 1.6. 8.5, respectively). In fully adjusted models, only the adolescent increasing alcohol trajectory retained a statistically significant association with opioid misuse, compared to the abstaining group (aOR = 3.3, 95%CI = 1.4, 7.8). Significant covariates associated with opioid misuse were male gender (aOR = 1.7, 95%CI = 1.0, 2.9) and nonwhite race (aOR = 0.5, 95%CI = 0.2, 0.9). A similar pattern was observed for prescription opioid misuse, specifically. Both adolescent limited and adolescent increasing alcohol use trajectory groups were significantly associated with an increased risk of prescription opioid misuse in young adulthood relative to the abstaining group (OR = 3.6, 95%CI = 1.2, 10.4 and OR = 4.3, 95%CI = 1.6, 11.5, respectively). In fully adjusted models, only the adolescent increasing alcohol trajectory group retained a statistically significant association with prescription opioid misuse, compared to the abstaining group (aOR = 3.9, 95%CI = 1.4, 10.8). The only significant covariate associated with prescription opioid misuse was race (aOR = 0.4, 95%CI = 0.2, 0.9), with African Americans being less likely to have reported opioid misuse. The only significant covariate associated with heroin use was male gender (aOR = 4.4, 95%CI = 1.5, 13.4).

Table 2.

Associations between alcohol trajectory groups and opioid misuse in young adulthood (age 19–26).

Alcohol trajectory Opioids
 Prescription opioids
 Heroin
Unadjusted OR
(95% CI)		 Adjusted OR
(95% CI)		 Unadjusted OR
(95% CI)		 Adjusted OR
(95% CI)		 Unadjusted OR
(95% CI)		 Adjusted
OR (95% CI)
Abstaining 1.0 1.0 1.0 1.0 1.0 1.0
Adult increasing 1.5 (0.6, 3.7) 1.7 (0.7, 4.2) 2.3 (0.8, 6.3) 2.5 (0.9, 7.1) 1.3 (0.3, 6.2) 1.6 (0.3, 7.4)
Young adult increasing 1.6 (0.6, 3.7) 1.7 (0.7, 4.1) 2.4 (0.9, 6.4) 2.6 (0.9, 7.0) 0.3 (0.03, 2.8) 0.4 (0.04, 3.6)
Experimenting 2.1 (0.9, 5.1) 1.8 (0.7, 4.6) 2.0 (0.7, 5.8) 1.8 (0.6, 5.3) 2.6 (0.6, 10.7) 2.2 (0.5, 9.4)
Adolescent limited 3.2* (1.3, 8.0) 2.4 (0.9, 6.3) 3.6* (1.2, 10.4) 2.9 (0.95, 8.9) 4.1 (0.98, 16.9) 2.4 (0.5, 10.8)
Adolescent increasing 3.7** (1.6, 8.5) 3.3** (1.4, 7.8) 4.3** (1.6, 11.5) 3.9** (1.4, 10.8) 3.1 (0.8, 12.7) 2.6 (0.6, 11.0)
Male gender 1.7* (1.0, 2.9) 1.3 (0.8, 2.2) 4.4** (1.5, 13.4)
Nonwhite race 0.5* (0.2, 0.9) 0.4* (0.2, 0.9) 0.4 (0.2, 1.2)
Free/Reduced price lunch 1.2 (0.7, 2.0) 1.3 (0.7, 2.4) 0.8 (0.3, 2.0)
Intervention group 1.0 (0.6, 1.6) 1.0 (0.6, 1.6) 0.8 (0.4, 2.0)
Violence exposure 1.1 (0.6, 1.8) 1.1 (0.6, 2.0) 0.9 (0.4, 2.4)
Deviant peer affiliation 0.9 (0.6, 1.3) 0.8 (0.5, 1.3) 1.2 (0.7, 2.1)
Neighborhood disorder 1.1 (0.8, 1.7) 1.2 (0.8, 1.8) 1.0 (0.5, 2.0)
Early tobacco use 1.2 (0.7, 2.2) 1.0 (0.5, 1.9) 1.4 (0.6, 3.8)
Early cannabis use 1.7 (0.9, 3.3) 1.8 (0.9, 3.6) 1.9 (0.7, 5.1)
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Note:

*

p < 0.05;

**

p < 0.01.

Bold values represent statistical significance.

Discussion

The current study aimed to investigate associations between alcohol use trajectories through adolescence and young adulthood and opioid misuse in young adulthood among a cohort of mostly African American participants from Baltimore, MD in the US. Rather than investigating cross-sectional associations between opioid and alcohol use among young people,8–11 or treating changes in drinking behavior as one overarching trajectory over time,12 our study used group-based trajectory modeling to identify subgroups of alcohol use trajectories that may be associated with differential risk for misusing opioids. We identified 6 alcohol use trajectory groups including young adult increasing (21.4%), adult increasing (19.1%), abstaining (19.1%), experimenting (15.3%), adolescent increasing (14.8%), and adolescent limited (10.2%). Compared to the abstaining group, the adolescent increasing trajectory group, which demonstrated an alcohol use pattern of early escalation starting at age 14 and high use throughout adolescence and young adulthood, had a significantly increased risk for opioid misuse, in general, and prescription opioid misuse, specifically, in young adulthood, in models fully adjusted for sociodemographics, peer and neighborhood risk factors, as well as early use of tobacco and cannabis.

Compared to the alcohol abstaining group, the adolescent increasing trajectory group had a greater than 3-fold risk of misusing opioids in young adulthood in fully adjusted models. A potential reason for this association may be that frequent exposure to alcohol throughout adolescence can disrupt neuroplasticity during this developmentally sensitive time period.23 Moreover, children and adolescents growing up in disadvantaged urban environments may already be at a higher risk for executive dysfunction and elevated stress reactivity,24 which can be additional risk factors for the development of substance use disorder.25 Our findings are consistent with previous studies that found frequent co-use of opioids with alcohol8,9 and binge drinking10 among young people. These results also indicate that escalating early alcohol use is a risk factor for opioid misuse over and above the early use of other substances, including tobacco and cannabis. While existing studies have demonstrated that cannabis use may increase the risk of developing prescription opioid misuse and opioid use disorder26 as well as other subsequent substance use disorders,27 our findings suggest that early and frequent alcohol use may be independent risk factors as well. Future studies investigating risk factors for opioid misuse should thus pay attention to alcohol use.

The concept of “maturing out” of problematic drinking has been investigated extensively in the existing literature, which may explain why the experimenting and adolescent limited trajectories were not associated with opioid misuse in young adulthood. Major changes in the lives of young people, including college enrollment, full-time employment, marriage, or parenting, can redirect a trajectory of problematic drinking behavior to one of less frequent, heavy alcohol use.28 In impoverished communities with fewer job opportunities, later marriage, and earlier parenting, it is important to understand what other factors may redirect trajectories as well as identify malleable factors early in the life course that prevents early initiation. This seems especially relevant for the adolescent increasing group that demonstrated the highest alcohol use as well as greatest risk for opioid misuse in the current study.

While the adolescent limited alcohol use trajectory group had a significantly increased risk for opioid misuse compared to the abstaining group in unadjusted models, this significance was attenuated in fully adjusted models including sociodemographics, neighborhood and peer-group risk factors, and early use of tobacco and cannabis. In fully adjusted models, the only significant covariates associated with opioid misuse were gender and race, and the only significant covariate for prescription opioid misuse was race. These results indicate that young men were at increased risk for opioid misuse, whereas compared to Whites, African Americans were consistently at lower risk for opioid misuse and prescription opioid misuse specifically in our sample. This is consistent with nationally representative trends data in the US over the past 40 years that has demonstrated higher risk of prescription opioid misuse among white adolescents, potentially due to underprescribing of opioid pain medication to African Americans.29

Group differences in risk for opioid misuse were mainly driven by prescription opioids and no significant between-group differences were observed for heroin use, in both unadjusted and adjusted models. However, it should be noted that observed odds ratios for heroin use for the adolescent limited and adolescent increasing trajectory groups were similar to those for prescription opioids. The wide confidence intervals suggest that due to a lower prevalence of heroin use, these analyses may have been underpowered. While we did not observe significant between group differences in heroin use, it should still be noted that heroin use in this sample was substantial. For example, 10.2% of the adolescent limited trajectory group and 8.1% of the adolescent increasing group reported heroin use in young adulthood, which is orders of magnitude greater than heroin use prevalence of 0.5% in the general population of young adults 18–25 years old.7

Limitations

This study has several limitations. While our sample is representative of urban students entering public schools in Baltimore in the 1990s, findings may not generalize to other samples or populations. Further, substance use behaviors were assessed using participant self-report without a more objective measure of use and may, thus, be subject to bias. Our study followed up participants through young adulthood and future research is needed to investigate whether trajectories throughout adolescence and young adulthood increase risk for opioid misuse later in adulthood. Also, previous research has demonstrated that the timing of assessments can impact latent class estimates30 and, thus, our decision to model alcohol use trajectories over adolescence and young adulthood may have impacted the unique trajectories identified in the current work. Moreover, we modeled our opioid misuse outcome as any opioid misuse in the past year at any of the assessments between ages 19 and 26 to maximize power and address issues of skewed data. A low prevalence of opioid misuse in any given year prevented us from modeling opioid misuse outcomes with more complex longitudinal analyses. An important strength of this study is the large cohort of low-income, urban, primarily African American youth. This is one of the few studies that follow low-income African Americans from childhood to young adulthood and includes extensive measures of substance use, individual-level and social risk factors, as well as assessments of the urban neighborhoods where they live.

Conclusions

This study showed that a trajectory of escalating alcohol use in adolescence and young adulthood is associated with an elevated risk of opioid misuse in young adulthood in a cohort of mostly African American and socio-economically disadvantaged young people. Findings suggest that prevention and early intervention related to early initiation and sustained increase in drinking over the course of adolescence is needed. Such interventions include structural measures that limit and enforce the availability of alcohol for underage drinkers and brief interventions that include personalized normative feedback and provide drinking reduction strategies.31,32 Future research could then be conducted to test whether such efforts may also have downstream effects on future opioid misuse.

Supplementary Material

Supplement table

Funding

The work was supported by the National Institute on Drug Abuse [NIDA; R01 DA044184 02S1]. The funding organization had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Footnotes

Disclosure statement

No potential conflict of interest was reported by the author(s).

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