Characterizing profiles of polysubstance use among high school students in Baltimore, Maryland: A latent class analysis

Trajectories of polysubstance use: Are past-year internalizing and externalizing problems associated with trajectories of polysubstance use over time?

OBJECTIVE

Polysubstance use among adults has been a public health concern in the U.S. and is associated with adverse consequences. This study aimed to identify the longitudinal trajectory of polysubstance use and test whether internalizing and externalizing problems predict it.

METHODS

Data of adults aged 18 and older (N = 15076) were extracted from the Waves 1-5 Population Assessment of Tobacco and Health Study (2013-2019). Group-Based Trajectory Modeling was performed to identify the trajectory of polysubstance use. Examined substances included use of cigarettes, e-cigarettes, excessive alcohol, cannabis, painkillers, and cocaine in past 30 days from all waves. Weighted multinomial logistic regressions were conducted to investigate the associations between internalizing and externalizing problems and the trajectory of polysubstance use, controlling for demographic variables.

RESULTS

Five trajectory groups were identified: (1) No to minimal polysubstance use risk (45.6 %); (2) Polysubstance use-low risk (10.7 %); (3) Cigarette-leading polysubstance use-high risk (23.5 %); (4) Cigarette-cannabis co-leading polysubstance use-high risk (12.3 %); and (5) Cannabis-leading polysubstance use-high risk (7.8 %). Compared with Group 1, higher internalizing problems predicted the membership of Group 3 [Relative risk ratio (RRR) range: 1.07-1.17] and Group 4 (RRR range: 1.04-1.21). Compared with Group 1, higher externalizing problems predicted the membership of Group 5 (RRR range: 1.01-1.10).

CONCLUSIONS

Prevention efforts should consider internalizing problems and associated trajectories of high-risk polysubstance use (e.g., cigarette-leading and cigarette-cannabis co-leading) as well as externalizing problems and associated trajectories of high-risk polysubstance use (e.g., cannabis-leading), when designing interventions to prevent polysubstance use.

Polysubstance Use among Maryland High School Students: Variations across County-Level School Districts

BACKGROUND

Polysubstance use is a highly prevalent public health issue, particularly among adolescents, and decisions on prevention programming and policies are often made at the local level. While there is a growing literature examining patterns of polysubstance use among adolescents, little is known about differences in those patterns across geographic regions.

METHODS

Using a large, representative sample of high school students from the state of Maryland (n = 41,091) from the 2018 Maryland Youth Risk Behavior Survey, we conducted a latent class analysis (LCA) of adolescent substance use along nine binary indicators, including past 30-day combustible tobacco, e-cigarette, alcohol, and cannabis use, as well as lifetime use of prescription opioids, cocaine, heroin, methamphetamine, and injection drug use. Measurement invariance across counties was examined using the Multiple Indicators and Multiple Causes (MIMIC) procedure.

RESULTS

The results of the LCA show three classes of adolescent substance use for the total sample: (1) low substance use, (2) commonly used substances (i.e., e-cigarette, alcohol, and cannabis use), and (3) polysubstance use. The results from the MIMIC procedure demonstrated geographic differences in students' endorsement of specific indicators and their class membership.

CONCLUSIONS

These differences demonstrate the need for an examination of local trends in adolescent polysubstance use to inform multi-tiered prevention programming and policy.

E-cigarettes may serve as a gateway to conventional cigarettes and other addictive drugs

Electronic cigarettes (e-cigarettes) are devices that allow the user to inhale nicotine in a vapor, and are primarily marketed as a means of quitting smoking and a less harmful replacement for traditional cigarette smoking. However, further research is needed to determine if vaping nicotine via e-cigarettes can be effective. Conversely, nicotine has been considered a gateway drug to alcohol and other addictive drugs and e-cigarettes containing nicotine may have the same effects. Previous reports have shown that e-cigarette use may open the gate for the use of other drugs including conventional cigarettes, cannabis, opioids, etc. The increasing prevalence of e-cigarettes, particularly among youth and adolescents in the last decade have led to an increase in the dual use of e-cigarettes with alcohol, cannabis, and other illicit drug use like heroin and 3-4-methylenedioxymethamphetamine (MDMA). The advent of e-cigarettes as a device to self-administer addictive agents such as cocaine and synthetic cathinones may bring about additional adverse health effects associated with their concurrent use. This review aims to briefly describe e-cigarettes and their different generations, and their co-use with other addictive drugs as well as the use of the device as a tool to self-administer addictive drugs, such as cocaine, etc.

The latent class structure of substance use in US adults 50 years and older

OBJECTIVE

Substance use rates have increased in adults 50 years and older, and substance use in this population is associated with significant consequences. Given that little is known about their underlying substance use patterns, the objective was to identify latent classes of adults 50 years and older by past-year substance use, past-month substance use, and past-year substance use disorder (SUD) diagnosis.

METHODS

The National Survey on Drug Use and Health is an annual nationwide cross-sectional U.S. survey. Participants were 35,229 civilian, non-institutionalized U.S. residents, 50 years and older. Past-year and past-month alcohol, tobacco, marijuana, heroin, cocaine, methamphetamine use, and opioid, stimulant, and tranquilizer/sedative prescription drug misuse (PDM) were captured, as was past-year DSM-IV SUD from these substances. Correlates included mental health, physical health, and healthcare utilization variables.

RESULTS

Latent class analysis indicated four past-year or past-month substance use subgroups (Alcohol-Only, Alcohol-Tobacco-Marijuana, Cocaine-Polydrug, PDM-Polydrug), with SUD prevalence rising from 3.2% to 17.3%, 68.8%, and 78.5% by past-year subgroup; similarly, rates of past-year suicidal ideation increased from 2.1%, to 4.8%, 12.0%, and 20.4% by past-year subgroup. For SUD, there were three subgroups (Low Nicotine Dependence [ND], High Alcohol Use Disorder, Multiple SUDs). Over 90% of adults were in a low-risk subgroup (i.e., Alcohol-Only and Low ND), but members of Cocaine-Polydrug, PDM-Polydrug, or Multiple SUDs latent classes had high rates of mental and physical health concerns.

CONCLUSIONS

Most adults 50 and older have lower risk profiles, but those engaged in PDM or cocaine use are heavily substance-involved and need screening and likely multi-disciplinary intervention.

Association of E-cigarettes with adolescent alcohol use and binge drinking-drunkenness: A systematic review and meta-analysis

Background: E-cigarette (ECIG) use has increased substantially in the past decade. Co-use of alcohol and ECIGS may have serious consequences in adolescents. Objectives: To evaluate the association of e-cigarettes (ECIGs) with alcohol use in adolescents. Methods: Searched databases included PubMed, EMBASE, CINAHL, PsycINFO, Web of Science, and gray literature. Studies were included if they contained a non-E-cigarette group (NON-ECIG), an ECIG group, detailed rates of alcohol use, binge drinking, or drunkenness and included adolescents. Two independent reviewers extracted data using MOOSE guidelines. Evidence quality across studies was assessed using Cochrane GRADE methodology. Summary effects of ECIG vs. NON-ECIG use on any alcohol use and a composite of binge drinking/drunkenness were calculated using a random-effects model. Results: 28 of 3768 initially identified studies were included: 25 cross-sectional, 3 cohort studies, N = 458,357 total subjects (49.6% females). Pooling of data showed that ECIG users had a higher risk for any alcohol use compared to NON-ECIG users (Odds Ratio/OR 6.62, 95% confidence interval/CI 5.67-7.72) and a higher rate of binge drinking/drunkenness compared to NON-ECIG users (OR 6.73, 95% CI 4.5 - 10.07). The subset of high school ECIG users had higher rates of alcohol use (OR 8.17, 95% CI 5.95-11.2) and binge drinking/drunkenness (OR 7.98, 95% CI 5.98-10.63) compared to NON-ECIG users. Conclusion: ECIG users had a higher risk of alcohol use and binge drinking/drunkenness compared to NON-ECIG users. Our findings indicate that interventions to reduce ECIG use should be coupled with measures to reduce alcohol use in adolescents.Abbreviations: ECIG: e-cigarettes; NON-ECIG: non e-cigarettes.

Adolescent Anabolic-Androgenic Steroid Use in Association with Other Drug Use, Injection Drug Use, and Team Sport Participation

Introduction

The majority of epidemiologic research on adolescent non-medical anabolic-androgenic steroid (AAS) use was conducted in the 1990s and early 2000s, indicating a need to update evidence for the modern era. We aim to understand the prevalence of AAS use among US adolescents and assess associations between AAS use, sports participation, other drug use, and injection drug use (IDU).

Methods

Using data from the 2017 National Youth Risk Behavior Survey, we estimated the prevalence of AAS use and tested for associations between AAS use, sports participation, and drug use, overall and by sex.

Results

The prevalence of AAS use was 2.98%. The prevalence among boys (3.46%) was higher than among girls (2.41%). AAS use was high among youth with lifetime heroin use (64.41%) and IDU (64.42%). There was no association between AAS and team sport participation (p=0.61).

Conclusions

Our results indicate that adolescent AAS use is an aspect of polysubstance use rather than a substance used solely for performance enhancement in sports. Research with adolescents should be mindful of the overlap of heroin and AAS use among youth with IDU.