No abstract

National Health and Medical Research Council and the Australian Government.

Aims Failure to complete high school predicts substantial economic and social disadvantage in adult life. The aim was to determine the longitudinal association of mid-adolescent polydrug use and high school non-completion, relative to other drug use profiles. Design A longitudinal analysis of the relationship between polydrug use in three cohorts at Grade 9 (age 14–15) and school non-completion (reported post high school). Setting A State-representative sample of students across Victoria, Australia. Participants 2287 secondary school students from 152 high schools. The retention rate was 85%. Measurements The primary outcome was noncompletion of Grade 12 (assessed at age 19–23 years). At Grade 9, predictors included 30 day use of eight drugs, school commitment, academic failure, and peer drug use. Other controls included socioeconomic status, family relationship quality, depressive symptoms, gender, age, and cohort. Findings Three distinct classes of drug use were identified - no drug use (31.7%), mainly alcohol use (61.8%), and polydrug use (6.5%). Polydrug users were characterised by high rates of alcohol, tobacco, and cannabis use. In the full model, mainly alcohol users and polydrug users were less likely to complete school than nondrug users [OR = 1.54 (95% CIs 1.17–2.03), and OR = 2.51 (95% CIs 1.45–4.33), respectively, ps < .001]. These effects were independent of school commitment, academic failure, peer drug use, and other controls. Conclusions Mid-adolescent polydrug use in Australia predicts subsequent school non-completion after accounting for a range of potential confounding factors. Adolescents who mainly consume alcohol are also at elevated risk of school non-completion.

Background and Aims Studies have consistently found a longitudinal association between e‐cigarette use (vaping) and cigarette smoking. Many have interpreted such association as causal. This systematic review and meta‐analysis evaluated the plausibility of a causal interpretation by (1) estimating the effect of adolescent vaping on smoking initiation, adjusted for study quality characteristics, (2) evaluating the sufficiency of adjustment for confounding based on the social development model (SDM) and the social ecological model (SEM) and E‐value analyses and (3) investigating sample attrition and publication bias. Methods Systematic review and meta‐analysis of longitudinal studies that examined the association between e‐cigarette use at baseline and smoking at follow‐up. Participants were non‐smokers aged < 18 at baseline. Results Meta‐analysis of 11 studies showed a significant longitudinal association between vaping and smoking [adjusted odds ratio (aOR) = 2.93, 95% confidence interval (CI) = 2.22, 3.87]. Studies with sample sizes < 1000 had a significantly higher odds ratio (OR = 6.68, 95% CI = 3.63, 12.31) than studies with sample sizes > 1000 (OR = 2.49, 95% CI = 1.97, 3.15). Overall, the attrition rate was very high (median = 30%). All but one study reported results from complete sample analysis, despite those dropping out having higher risk profiles. Only two studies comprehensively adjusted for confounding. The median E‐value was 2.90, indicating that the estimates were not robust against unmeasured confounding. Conclusions There is a longitudinal association between adolescent vaping and smoking initiation; however, the evidence is limited by publication bias, high sample attrition and inadequate adjustment for potential confounders.

Background: Alcohol use and illicit drug use peak during young adulthood (around 18–29 years of age), but comparatively little is known about polydrug use in nationally representative samples of young adults. Drawing on a nationally representative cross-sectional survey (Australian National Drug Strategy Household Survey), this study examines polydrug use patterns and associated psychosocial risk factors among young adults (n = 3,333; age 19–29).Method: The use of a broad range of licit and illicit drugs were examined, including alcohol, tobacco, cannabis, cocaine, hallucinogens, ecstasy, ketamine, GHB, inhalants, steroids, barbiturates, meth/amphetamines, heroin, methadone/buprenorphine, other opiates, painkillers, and tranquilizers/sleeping pills. Latent class analysis was employed to identify patterns of polydrug use.Results: Polydrug use in this sample was best described using a 5-class solution. The majority of young adults predominantly used alcohol only (52.3%), alcohol and tobacco (34.18%). The other classes were cannabis, ecstasy, and licit drug use (9.4%), cannabis, amphetamine derivative, and licit drug use (2.8%), and sedative and alcohol use (1.3%). Young adult males with low education and/or high income were most at risk of polydrug use.Conclusion: Almost half of young adults reported polydrug use, highlighting the importance of post-high school screening for key risk factors and polydrug use profiles, and the delivery of early intervention strategies targeting illicit drugs.

Participants who reported a lifetime diagnosis of depression (OR=1.15, p=0.003), anxiety (OR=1.72, p<0.001), and a larger number of substance use (OR=1.29, p<0.001) were more likely to use BHO than only using high potency herbal cannabis. BHO users also reported stronger negative effects and less positive effects when using BHO than high potency herbal cannabis (p<0.001) CONCLUSION: Mental health problems and other illicit drug use were associated with use of BHO. BHO was reported to have stronger negative and weaker positive effects than high potency herbal cannabis.

The results point to the importance of monitoring and responding to comparatively minor shifts in the proportion of peers who use alcohol, particularly among very young adolescents.

Introduction and Aims