Elsevier

Drug and Alcohol Dependence

Volume 194, 1 January 2019, Pages 121-127
Drug and Alcohol Dependence

Full length article
Longitudinal patterns of amphetamine use from adolescence to adulthood: A latent class analysis of a 20-year prospective study of Australians

https://doi.org/10.1016/j.drugalcdep.2018.08.042Get rights and content

Highlights

  • Amphetamine users commonly initiated their use by late teenage year or early 20s.

  • Amphetamine use declined substantially even among regular users after mid-20s.

  • Adolescent cannabis use was strongly associated with regular amphetamine use.

Abstract

Background

To examine the longitudinal patterns of amphetamine use over twenty years from adolescence to the mid-thirties; and identify adolescent antecedents of future problematic patterns of use.

Design

Ten-wave longitudinal study following participants from age 15 to age 35 in Victoria, Australia. Participants (N = 1755; 47% males) first enrolled in the Victoria Adolescent Health Cohort Study in 1992.

Measurements

Outcome: Self-reported frequency of amphetamine use. Predictors: Gender, depression and anxiety, peer alcohol and tobacco use; self-reported alcohol, tobacco and cannabis use, self-reported adolescent antisocial behavior.

Findings

Three different longitudinal patterns were identified: Non-user (83.7%); Occasional user (14.5%); Regular user (1.8%). Among the two user patterns, amphetamine use was commonly initiated in late teenage years or early 20s, peaked at mid-20s, and declined substantially by mid-30s. Participants who used cannabis and had smoking peers during adolescence were at significantly more likely to become an occasional or regular user (p <  .05).

Conclusion

Regular cannabis use and peer tobacco use during adolescence were the two strongest predictors of a longitudinal pattern of regular amphetamine use in the mid-30s. This suggests that prevention programs could be implemented around or before mid-adolescence and interventions to reduce amphetamine harms focus on high-risk individuals in their 20s when amphetamine use was at its peak.

Introduction

After cannabis, amphetamines are some of the most widely used illicit substances globally. In recent years, their use and associated harms have risen in some countries including Australia, China, Indonesia and Myanmar (Degenhardt et al., 2016; Lai et al., 2016; UNODC, 2013). Regular use of amphetamines, especially by injection or smoking, is strongly associated with psychoses, depression, intentional self-harm and suicide attempts (Darke et al., 2008; Marshall and Werb, 2010; Park and Haning, 2016). Amphetamines are cardiotoxic and are linked to hypertension, myocardial ischemia, arrhythmia, and infarction (Kaye et al., 2007; Yeo et al., 2007). They are also neurotoxic, and animal models suggest that their impact may be more harmful for adolescent users whose brains are undergoing rapid and extensive maturation (Buck and Siegel, 2015).

Longitudinal research on adolescent antecedents of amphetamine use among adolescents and young adult is very limited. Most research is based on cross-sectional data, with study participants derived primarily from high-risk populations such as adult drug users (e.g., Quinn et al., 2013), or street-involved young people (e.g., Uhlmann et al., 2014). Findings from these studies have limited generalizability to the broader population, and the cross-sectional studies (e.g., Chen et al., 2014) provide little information about the developmental course of amphetamine use. Studies of the correlates of amphetamine use were largely based on individuals over 20 years old, well past the age of initiation for most amphetamine users. Identification of key adolescent markers of regular use potentially provides important information for prevention and intervention programs to target high-risk adolescents at an earlier stage, reducing their risks of progressing to regular use and dependence.

In a previous report, we examined adolescent predictors of amphetamine use 10-years later in young adulthood (Degenhardt et al., 2007). This paper extends that work in two ways. First, we examine the natural history of amphetamine use with twenty years of data on the timing of initiation, escalation, and remission with a view to identifying potential windows for intervention. Given that previous studies on other substances such as alcohol and tobacco have shown distinct longitudinal patterns of use (Chan et al., 2013; Dutra et al., 2017), we expected to identify at least three subgroups, non-users, occasional and regular users, with different histories from adolescence to adulthood. Secondly, we investigate adolescent antecedents of regular and persisting adult amphetamine use, including other substance use, antisocial behaviors, depressive and anxiety symptoms, and peer substance use. These variables were chosen because they predict other substance use and can potentially be used for selective prevention and clinical screening. (Chan et al., 2017; Kelly et al., 2015, 2012)

Section snippets

Method

Between 1992 and 2014 we undertook a ten-wave cohort study of health in young people in the state of Victoria, Australia. At baseline, a representative sample of mid-secondary school adolescents was selected using a two-stage cluster sampling procedure. At stage one, 45 schools were chosen at random from a stratified frame of government, Catholic and independent schools, with a probability proportional to the number of Year 9 (age 14–15) students in the schools in each stratum. All schools

Results

Table 1 shows the prevalence of amphetamine use from wave 1 to wave 10. During adolescence (Wave 1 to Wave 6), the rate of past-year amphetamine use was less than 5%. It increased to 7.5% in Wave 7, peaked at Wave 8 (11.3%) and Wave 9 (11.2%) and declined to 6.1% in Wave 10.

Table 2 shows the fit statistics from the 2-class to the 5-class model. The AIC decreased successively from the 2-class to the 5-class model, but the decrease leveled off after the 3-class model. The SSABIC attained the

Discussion

The use of amphetamine has increased steadily in Australia over the past two decades and may have accelerated more recently (Degenhardt et al., 2016; Lai et al., 2016). These trends have prompted calls for research on the causes and life-course trajectories of amphetamine use in Australia.

In this study, we found that the majority of the population did not use amphetamine, but those who did commonly initiated use in their late teens or early 20s. A much higher proportion of regular than

Conclusion

There were three typical longitudinal patterns of amphetamine use in this Australian cohort. The majority of the sample were non-users (83.7%), followed by occasional users (14.5%) and regular users (1.8%). Users commonly initiated use in late teenage year or early 20s, and their use peaked in their mid-20s and declined by the age of 35. Prevention programs could be implemented around or before mid-adolescence and intervention programs to reduce amphetamine harms could be delivered to high-risk

Conflict of interest

No conflict declared.

Role of funding source

This work was supported by the University of Queensland Fellowship (Gary Chan). The funding body had no role in the design, analysis or interpretation of the data.

Contributors

Chan, Hall, and Patton developed the research questions and gathered background information. Butterworth, Degenhardt and Stockings contributed to the theoretical framework and actively provided feedbacks in the research directions and the development of the manuscript. Chan undertook the statistical analyses. Becker and Patton contributed to the data collection. All authors approved of the final manuscript.

References (40)

  • K.-K. Yeo et al.

    The association of methamphetamine use and cardiomyopathy in young patients

    Am. J. Med.

    (2007)
  • A. Agrawal et al.

    A twin study of early cannabis use and subsequent use and abuse/dependence of other illicit drugs

    Psychol. Med.

    (2004)
  • Australian Institute of Health and Welfare

    National Drug Strategy Household Survey Detailed Report 2013. Drug Statistics Series No. 28

    (2014)
  • Australian Institute of Health and Welfare

    National Drug Strategy Household Survey 2016: Detailed findings. Drug Statistics Series No. 31

    (2017)
  • J.M. Buck et al.

    The effects of adolescent methamphetamine exposure

    Front. Neurosci.

    (2015)
  • G.C.K. Chan et al.

    Predicting steep escalations in alcohol use over the teenage years: age-related variations in key social influences

    Addiction

    (2013)
  • S. Darke et al.

    Major physical and psychological harms of methamphetamine use

    Drug Alcohol Rev.

    (2008)
  • L. Degenhardt et al.

    The predictors and consequences of adolescent amphetamine use: findings from the Victoria Adolescent Health Cohort Study

    Addiction

    (2007)
  • L. Degenhardt et al.

    Estimating the number of regular and dependent methamphetamine users in Australia, 2002-2014

    Med. J. Aus.

    (2016)
  • L.M. Dutra et al.

    Beyond experimentation: five trajectories of cigarette smoking in a longitudinal sample of youth

    PLoS One

    (2017)
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