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Research Paper

Do cannabis and amphetamine use in adolescence predict adult life success: a longitudinal study

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Received 11 Jul 2021
Accepted 19 Jan 2022
Published online: 22 Feb 2022



While some studies have reported that early age of onset of cannabis and amphetamine use predicts a range of adverse outcomes, these findings are rarely adjusted for other predictors of adverse outcomes or subsequent drug use over the adult life course. These studies have not addressed the possibility that it is subsequent rather than early age of onset of drug use that may predict adult life success.


Data are from the Mater-University of Queensland Study of Pregnancy (MUSP). At 21 years, respondents self-reported their use of cannabis and amphetamines and completed the Composite International Diagnostic Interview (CIDI) on lifetime ever use of cannabis and amphetamines. At 30 years, respondents self-reported their past-year use of cannabis and amphetamines. The outcome measure is a composite measure of life success at the 30-years follow-up. Associations are adjusted for covariates at the 14-year follow-up.


Adolescent behavior problems predict drug use at 21 years, drug use and life success at 30 years. The association between early age of onset cannabis use, amphetamine use and cannabis and amphetamine use and adult life success is not statistically significant once adjusted for cannabis and amphetamine use at the 30-year follow-up. Concurrent cannabis use at the 30-year follow-up is strongly related to life success.


In a community sample, cannabis as well as cannabis and amphetamine use and/or use disorder in the adolescent period does not appear to predict life success in adulthood for those whose use has ceased prior to 30 years of age.


Despite an extensive literature documenting the adverse consequences of the use of cannabis (Volkow et al. 2014; Airagnes et al. 2019; Campeny et al. 2020) and amphetamines (Degenhardt et al. 2017; Farrell et al. 2019; McKetin et al. 2019) there remain important gaps in what is known. These gaps include that: (i) there is a need to distinguish the harms associated with the use of cannabis and amphetamines as well as determine whether there are specific harms associated with their co-use. (ii) adolescence is a period of the life course which involves substantial biological, psychological and social changes. There is a possibility that drug use during this period may be transient or may have longer-term consequences. It is presently not known which of these two possibilities is supported by the evidence. (iii) previous (often cross-sectional) studies determine harms associated with cannabis and/or amphetamines using samples derived from clinical or treatment services. Patterns of drug use in community samples are likely to involve lower levels of use than in clinical samples and be a better indicator of harms experienced by the majority of those who use cannabis and/or amphetamines. (iv) drug use in community samples is associated with a variety of life circumstances, for example, family poverty and parental marital breakdown and child aggressive/delinquent behavior. These same life circumstances also predict a range of adverse life outcomes. Analyses need to distinguish the effects of drug use from their correlated early life predictors of adverse outcomes. (v) adolescent drug use is associated with drug use in adulthood. In determining whether adolescent drug use leads to adult age adverse outcomes it is important that patterns of drug use in both the adolescent and adult stages of the life course be identified and distinguished in analyses. (vi) there are few long-term prospective studies of adolescent drug use. Such studies are needed to estimate the duration of adverse consequences associated with adolescent drug use. (vii) the majority of studies documenting the harms associated with drug use focus on specific mental and physical health, delinquency, crime and sometimes family life outcomes. There is a need to extend our understanding of the possible consequences of adolescent drug use to include more global measures of overall social and economic outcomes. Life success is one such outcome.

The present paper takes data from a long-running longitudinal study and uses self-reported cannabis and amphetamine use as well as cannabis and amphetamine use meeting the clinical criteria for a substance use disorder, retrospectively recalled at the 21 years of age data collection, to predict life success at the 30 years of age data collection, with adjustment for cannabis and amphetamine use at 30 years of age. Covariates are taken from the 14 years of age data collection and are used as controls.


There is ample evidence that some levels of cannabis use are associated with a wide range of adverse life course outcomes (Lynskey and Hall 2000; Fergusson and Boden 2008; Horwood et al. 2010; Danielsson et al. 2014; Hasin 2018; Airagnes et al. 2019; Boden et al. 2020). Early age of onset and many years of continuing cannabis use has been found to predict psychosis-related outcomes. (McGrath et al. 2010). Outcomes associated with higher levels of cannabis use span the range of factors that are arguably indicators of life success including later life course depression (Schoeler et al., 2018), aggressive and violent behavior (Schoeler et al., 2016), as well as reduced educational achievement and socioeconomic status (Lynskey and Hall 2000; Fergusson and Boden 2008; Horwood et al. 2010), poor mental health, reduced wellbeing and less satisfactory intimate relationships (Hall et al. 2016; Hasin 2018). The adverse impact of cannabis use on education in adolescence may also have a downstream effect on occupational outcomes, while adolescent cannabis use has been reported to result in poorer relationships and reduced life satisfaction in adulthood (Fergusson and Boden 2008).


The use of amphetamines is similarly associated with poor health and social outcomes, including an elevated risk of cardiovascular complications, stroke, injury, risk of HIV and hepatitis infection, sexually transmitted infections and poor mental health as well as antisocial behavior (McKetin et al. 2019; Foulds et al. 2020; McKetin et al. 2020). Relatively little is known about the level of harm associated with specific levels of amphetamine use. Further, many of the health harms attributed to the use of amphetamines may dissipate with abstinence from substance use, though some impacts may be longer-lasting. For example, although psychosis risk associated with the use of drugs is largely transient, a minority of people are at elevated risk of developing schizophrenia (Kendler et al. 2019), with consequent long-term impacts on social and occupational outcomes (Chong et al. 2016). While these examples demonstrate the plausibility of cannabis and amphetamine use having a long-lasting effect on functioning, with the exception of Fergusson and Boden (2008) and Boden et al. (2020), most studies focus on specific health behaviors and harm experienced proximate in time to the use of cannabis and amphetamines and do not capture the duration or level of drug use involved nor consider the broader extent of the likely impact of drug use on later adult functioning.

In particular, there has been a dearth of studies addressing the co-use of cannabis and amphetamines. Cannabis and amphetamines are associated with the highest number of drug arrests and both are responsible for substantial numbers of hospital admissions (AIHW 2021). Their use and co-use are of policy importance.

Life success

One measure that has the potential to capture the global impact of substance use on functioning is life success. The case for the development of the concept of life success reflects (i) the need for a multifaceted measure of life course outcomes, (ii) extent societal changes which render more traditional measures of life course outcomes such as social class and family poverty less relevant, (iii) the need for a measure of life course outcomes that may be relevant to a wide variety of study designs and research questions. Life success, as a concept, will have advantages and limitations much as do the related concepts of social class and the quality of life (see Moons et al. 2006).

Life success has been measured using objective (Craig et al. 2020) and subjective (Layard et al. 2014) indicators. Many studies of life success have focused on objective indicators such as social or occupational status and wealth (Parker and Chusmir 1992; Ullrich et al. 2008). Objective measures of life success have included employment in the highest levels of the professions or business (Holahan 2021). Subjective rankings of what is perceived to contribute to life success commonly include satisfaction with family life (Sears 1977). In the Cambridge Study of Delinquent Development, involving a selected sample of economically disadvantaged children, life success was measured using a composite of indicators taken from multiple life domains (Farrington et al. 2006).

Parker and Chusmir (1992) have moved some way toward the validation of the concept of life success using a large pool of items mentioned in the literature, with factor analysis to select a set of 42 items (and six subscales) that met the criteria for construct validity including good internal consistency, test-retest reliability, and very good convergent validity. While life success can and is measured in multiple ways, many of those measures are correlated and the selection of specific indicators is likely to be less informative than the use of a composite indicator (Farrington et al. 2006).

We examine the relationship between the use of cannabis and amphetamines in adolescence and life success at 30 years of age. To measure life success we have developed a 9-item scale which includes objective as well as subjective measures of life success along the lines suggested by Farrington et al. (2006) and Parker and Chusmir (1992). We adopt the suggestion that the adolescent period now extends to the early 20 s (Sawyer et al, 2018). We use data from a long-running birth cohort study (the Mater-University of Queensland Study of Pregnancy – MUSP) which has had six waves of data collection from the period during pregnancy to the 30-year follow-up (Najman et al. 2015). Data on cannabis and amphetamine use were available at the 21- and 30-year follow-ups. Covariates were measured at birth and the 14-year follow-up. Life success was measured at the 30-year follow-up. We examine here the extent to which cannabis and amphetamine use up to 21 years of age, predicts life success at the 30-year follow-up, adjusting for a wide range of prior life experiences and behaviors. We also adjust for concurrent cannabis and amphetamine use at the 30-year follow-up to distinguish the consequences of adolescent use of cannabis and amphetamines from those associated with concurrent use.

Research questions

  1. Do cannabis and/or amphetamine use or use disorder by 21 years of age predict life success in adulthood independently of the early life adversities that predict both illicit drug use and life success?

  2. Does adolescent cannabis and/or amphetamine use or use disorder by 21 years of age predict life success independently of cannabis and/or amphetamine use in adulthood?

Materials and methods

Beginning in early 1981 all consecutive pregnant women attending their first visit at an obstetrical service at a major (public) hospital were invited to participate in the study. This obstetrical service accounted for almost half the births in the city of Brisbane, Australia. Of the 8556 women invited to participate in the study, 8448 agreed, of whom 7223 women gave birth to a live singleton baby, defined as the MUSP study cohort. Data were obtained on the offspring immediately after the birth and at 6 months, 5, 14, 21 and 30 years. Some 2900 children provided some data at the 30-year follow-up.

While 2900 offspring provided some data at the 30-year follow-up (excluding deaths this comprises 41% of the original sample), only about 2350 offspring (numbers vary slightly due to missing data) provided useable data at the 30-year follow-up and this group comprises the study sample for the current paper.

We have previously published more extensive details of the sampling, recruitment, study design and response rates for each phase of the study (Najman et al. 2005; 2015). We have noted that loss to follow-up is selective with low income, single-parent families, families reporting high levels of adversity and mothers experiencing anxiety and depression more frequently lost to follow-up. We have addressed the issue of possible attrition bias in a number of papers using methods such as multiple imputations and inverse probability weighting as well as specific testing the likely effects of attrition comparing data on those retained and lost to follow-up (Saiepour et al. 2019). This issue is discussed in the study limitations.

At all phases of data collection ethical approval was obtained from the Human Research Ethics Committee of the University of Queensland and the Ethics Committee of the Mater Hospital. Up to the 14-years, follow-up mothers provided consent for their own participation and the participation of their child. From 14 years onwards the offspring also provided consent.

Measurement of cannabis and amphetamine use

We administered the Composite International Diagnostic Interview (CIDI) including the module detailing past use of cannabis and amphetamines at the 21-year follow-up. The CIDI is a structured clinical interview based upon DSM-IV clinical criteria for substance abuse and dependence. The CIDI includes questions providing details of the age of onset of a disorder meeting the relevant clinical criteria. The CIDI has good validity in identifying cases that meet DSM-IV criteria for diagnosed mental health disorders (Reed et al. 1998). Of 2550 respondents who completed the CIDI, 21.9% (N = 558) had ever had a cannabis use disorder and 4.1% (N = 105) had an amphetamine use disorder. The mean age of the first onset for a cannabis use disorder was 16.4 years (SD = 2.14yrs) and for an amphetamine use disorder was 17.4 years (SD = 2.19yrs). Combining these cannabis and amphetamine use disorder variables, 77.4% (N = 1972) of the sample have never had a cannabis or amphetamine use disorder, 18.5% (N = 472) report only cannabis use disorder, 0.7% (N = 19) only an amphetamine use disorder and 3.4% (N = 86) both a cannabis and amphetamine use disorder by 21 years of age.

At the 21-year follow-up, respondents were asked how often they had ever used cannabis. Some 49.8% of respondents reported ever using cannabis. Respondents were also asked if they had ever used amphetamines like speed, uppers or pep pills. Response options included using but not in the last year. Some 21.4% of respondents reported ever using amphetamines. We then created a variable combining lifetime ever cannabis and amphetamine use. Of 3748 respondents from whom data were available 48.4% (N = 1815) were categorized as never using cannabis or amphetamines, 30.2% (N = 1131) only ever using cannabis, 1.7% (N = 64) only ever using amphetamines while 19.7% (N = 738) were categorized as ever using both cannabis and amphetamines.

At the 30-year follow-up, the now young adults were asked questions about whether they had used cannabis or amphetamines in the last 12 months. Respondents were also asked if cannabis (or amphetamines) were used, for how many days and the quantity they used on those days. They were also asked the age at which they first regularly used cannabis or amphetamines. From answers to these questions, we created a composite variable of no use or lower 50% and higher 50% levels of use (the modest numbers of users at the 30-year follow-up precludes more narrowly defined subgroups of use).

Measuring life success

We selected 9 indicators of life success all taken from the 30-year follow-up. These are in 3 categories of a variable, socioeconomic level (3 variables), subjective perceptions of quality of life (3 variables) and stability and perceived quality of intimate relationships (3 variables).

To measure the socioeconomic status of respondents we have used family income, level of education and ownership of own accommodation. To measure stability and perceived quality of intimate relationships we asked questions about the past number of intimate relationships and whether the respondent currently was in an intimate relationship as well as perceived satisfaction with that relationship (three questions). To measure subjective perceptions of quality of life we have three questions concerning satisfaction and happiness with life. The 9 life success items were added together and divided by the number of life success items for which there was available data. Those in the lowest quintile of life success scores were categorized as having low life success outcomes. Using the 9 items we find a Cronbach alpha reliability coefficient of 0.76 suggesting the 9 items are measuring a consistent underlying construct (see Supplementary Table 1 for more details of items in the life success scale).

Table 1. Sociodemographic characteristics of the mother and/or child predicting life success at 30 years of age (Odds ratio, 95% CI).

Measurement of covariates

Covariates were selected on the basis that they precede the onset of illicit drug use and are all (based upon previous research) likely early-life predictors of the use of illicit drugs. Two predictors were from the time the mother was recruited to the study, namely mothers’ age and her education. For analytic purposes, these do not change over the early life course. We have extracted 8 other covariates from the data set. These are all from the 14-year follow-up. Family income, mothers’ number of changes of partner between 7 and 14 years, child ever contacts with police as well as contacts with juvenile aid or suspension from school, are all reported by the mother. At the 14-year follow-up, the adolescent was administered a short form of Raven’s Progressive Matrices and the Wide Range Achievement Test (WRAT) (to measure IQ) and the Achenbach youth self-report (YSR) to measure anxiety and depression (subscales were combined) and aggression and delinquency (subscales were combined).

Analytic strategy

First, we examine the association between the sociodemographic variables and life success (Table 1) and drug use recalled at 21 years (Table 2). Table 3 presents the association between sociodemographic covariates and drug use at the 30-year follow-up. Table 4 has details of the association between cannabis and amphetamine use and use disorder up to 21 years of age and life success at 30 years with successive adjustments for covariates and drug use at 30 years. Table 5 provides the cross-sectional data for drug use and life success at 30 years of age. We use either binomial or multinomial logistic regression to assess all associations between early life exposures and cannabis and/or amphetamines use or use disorders at the 21-year follow-up, and cannabis and amphetamine use at 21 years and life success at the 30-year follow-up.

Table 2. Sociodemographic characteristics of mother and/or child by 14 years and drug use by 21 years of age (Odds ratio, 95% CI).

Table 3. Sociodemographic characteristics of mother and/or child by 14 years and drug use at 30 years of age (Odds Ratio, 95% CI) (Reference Category is No Drug Use).

Table 4. Cannabis and amphetamine use and use disorder by 21 + years predicting life success at 30 years.

Table 5. Association between cannabis or amphetamine use and life success at 30-year follow-up (Reference category is no cannabis or amphetamine use).


The association between early life course exposures and life success is presented in Table 1. Consistent with expectations mothers’ education and family income are predictors of offspring success at 30 years of age. A number of other early life (adolescent) characteristics of the child are strong and consistent predictors of life success including YSR externalizing behavior (at age 14), child contact with police, child suspension from school and child school performance. There is a very strong pattern of associations between the child’s aggressive and/or delinquent behavior in the early adolescent period and the child’s life success when an adult.

Table 2 provides details of the association between early life course covariates and cannabis and amphetamine use by the 21-year follow-up. These include measures of adolescent behavior including YSR externalizing behavior, contact with the police, suspension from school, and poor school performance. Mothers who report more frequent partner changes over the period up to the 14-year follow-up have children who more often use cannabis and amphetamines by 21 years of age, as do children who have higher levels of externalizing behavior, contact with police/juvenile aid and problems at school. For these latter children, rates of co-use of cannabis and amphetamines appear to be very high.

Early adolescent behaviors (age 14 years) also strongly predict the use of cannabis and amphetamines at the 30-year data collection. Adolescent externalizing behavior, contact with police/juvenile aid and suspension from school predict the use of both cannabis and amphetamines at 30 years of age. In general, these associations are strong and consistent (Table 3)

The unadjusted and adjusted associations between self-reported cannabis and amphetamine use and use disorder by the 21-year follow-up and life success some nine years later are presented in Table 4. Lower life success appears to be predicted by cannabis and amphetamine use but not by the use of only cannabis or amphetamines. Cannabis use disorder by the 21-year data collection also predicts low life success. These associations are largely unaffected after adjustment for early life covariates. However, adjustment for cannabis and amphetamine use at the 30-year follow-up indicates that cannabis and amphetamine use and use disorder by 21 years no longer predicts life success at 30 years of age.

The association between cannabis use and amphetamine use at 30 years and life success at 30 years, shown in Table 5, is adjusted for earlier life course covariates as well as concurrent use of amphetamines (for cannabis) and cannabis (adjusted for amphetamine use). Most associations in Table 5 are very strong and consistent. Persons using cannabis or amphetamines at 30 years of age consistently report low life success. For cannabis use, there appears to be a dose-related relationship, with high cannabis use being associated with the highest rates of low life success. This is not apparent with the users of amphetamines with both low and high use generally having similar rates of low life success. Adjustment for concurrent cannabis use renders the association between amphetamine use at 30 years and life success no longer statistically significant.


Figure 1 presents a visual summary of the analyses and main findings. The most salient features are the extent to which age 14 evidence of adolescent behavior problems predicts cannabis and amphetamine use at age 21 years and at age 30 years, as well as predicting life success at 30 years. It is the consistency and strength of some of these associations that is notable.

Figure 1. Research model – possible causal pathways. (Respondent age at time data were obtained).

In the context of an existing body of literature which suggests that early age of onset of drug use is a strong predictor of adult health and well-being (Hasin 2018; Airagnes et al. 2019; Farrell et al. 2019; Campeny et al. 2020) our findings could be seen to provide some contrary evidence. From a policy perspective our findings that adolescent-onset of aggressive and delinquent behavior and school problems predicting a wide range of drug use and life success outcomes represents an opportunity to alter the young person’s subsequent life trajectory. From a research perspective these findings emphasize the potential for early life experiences and behaviors that may lead to misleading interpretations of any associations observed between drug use and later life outcomes.

The early age of use of cannabis and/or amphetamines, or prior cannabis and/or amphetamine use disorder does not appear to independently predict life success at the 30-year follow-up. There is a need to test this finding and consider its validity and generalizability. Three issues need to be considered in the above context. First, is it likely that early age of onset of drug use may not lead to adverse life course outcomes; second, does the type/level or pattern of drug use suggest some drugs or patterns of use are of greater concern and; third, is life success a valid or generalizable measure of the outcome?

At the 21-year follow-up, we have two measures of cannabis and amphetamine use. Those whose pattern or cannabis and amphetamine use meet the criteria for DSM-IV use disorder (dependence or abuse) identify a subgroup of users with high levels of use at a young age. We also reported last year's use of cannabis and/or amphetamines at the 30-year follow-up. In this community-based sample of users, the level of cannabis use was modest (of those who had ever used cannabis only about 25% had used at the level of multiple times in the last month), while the level of amphetamine use was even lower (13% of ever users had used multiple times a month). The numbers using cannabis or amphetamines every day are low in our sample and suggest that the longer terms harm we report for users may largely reflect what are low levels of drug use in a community sample. The lack of an association between amphetamine use and life success may simply reflect low levels of amphetamine use in a community sample.

When we consider those who have had a history of clinically diagnosed cannabis and amphetamine use disorder, we note that some 75% of those who had a cannabis use disorder had their first episode in the 15-to-18-year age range while of those who have ever had an amphetamine use disorder, over 80% were in the 17-to-19-year age range. These respondents exhibit both early ages of onset and high levels of use. Our data on cannabis and amphetamine use suggests that a large majority of those who had ever met the criteria for a drug use disorder were no longer using at clinically significant levels by 21 years of age.

We find little evidence that the early age of onset of cannabis and/or amphetamine use or use disorder predicts adult life success. This may be attributable (i) the low rate of clinically significant drug use in a community-based sample (ii) the ability to distinguish users whose use continues into adulthood (iii) a sample that has a modest proportion who exhibit continuing and persistent use of cannabis and amphetamines.

Perhaps most surprising is the finding that cannabis and amphetamine co-use does not predict adverse outcomes independently of those who are using drugs at the 30-year follow-up. Co-use or polydrug use is frequently associated with a range of adverse outcomes (Darke et al. 2014) but it is difficult to find previous studies documenting co-use of cannabis and amphetamines in a community sample.

It is also notable that there are few in this sample who only report using amphetamines with most amphetamine users also reporting they use cannabis. This is consistent with our CIDI derived data with more respondents reporting a past cannabis and amphetamine use disorder than only reporting an amphetamine use disorder. The co-use of cannabis and amphetamines is relatively common in this population-based sample suggesting the co-use of these drugs warrants greater attention.

In any event, the frequency of a past cannabis and amphetamine co-use disorder in this sample appears to be low and it is not possible to determine whether co-use involved concurrent or serial co-use. Our measure of co-use is limited in detail but does confirm the more general finding that early age of cannabis and amphetamine use, either separately or over a similar time period appears to predict few consequences for life success at 30 years of age.

Of those who had a cannabis use disorder by 21 years of age, 36% report using cannabis at the 30-year follow-up. Of those who had had a cannabis and amphetamine use disorder by 21 years, 60% report using cannabis at 30 years. Comparable comparisons for amphetamine use at 30 years are lower with about 20% of those with a drug use disorder at 21 years using amphetamines at 30 years. At 30 years, when respondents were asked the age at which they first used cannabis and amphetamines “regularly”, some 92% of cannabis users and 77% of amphetamine users reported their first regular use was at 21 years of age or less. The data seems to suggest that those using cannabis and/or amphetamines at 30 years comprise substantial numbers of those who experienced a young age of first use. It appears to be the persistence of cannabis and amphetamine use that best predicts low life success outcomes. In any event, it is not possible to determine, at the 30-year follow-up, whether drug use has contributed to low life success or whether low life success may have contributed to drug use, or indeed whether both causal sequences may occur.


In interpreting these findings, the limitations of the current study are noted. This study involves a 30-year follow-up of a sample of children recruited in 1981-4. The loss to follow-up is substantial and has been a focus of a number of our research papers (Najman et al. 2015; Saiepour et al. 2019). In many of our papers, we have used multiple imputations, inverse probability weighting or propensity analysis to adjust for selective attrition. In no instances has this adjustment altered the substance of our findings. More recently we have engaged in a series of modeling exercises testing the impact of substantial bias in attrition as well as very high rates of attrition on our findings (Saiepour et al. 2019). The modeling suggests that the observed associations are similar within the group lost to follow-up as well as the group remaining in the study. While loss to follow-up does affect population estimates, for example, we likely lose a higher proportion of respondents who are heavier users of drugs, the association between drug use and life course outcomes is likely unaffected.

The data on cannabis and amphetamine use were obtained over a decade ago and changes in both the prevalence of the use of cannabis and amphetamines as well as changes in the concentration of active ingredients need to be considered in the current context (Volkow et al. 2014; Degenhardt et al. 2017; Stuyt 2019). Population rates of cannabis and amphetamine use have not changed greatly in Australia in recent years. However, it does appear that more concentrated forms of both cannabis and amphetamine are being used and that the impact of higher concentrations of cannabis and amphetamine has implications both for the extent to which use patterns may increase but also the possibility that there may be a greater impact of newer forms of substances on life success.

The high rates of low life success for those concurrently using cannabis and amphetamines also need to be considered in a broader context. We do not have adequate data on other illicit drugs that may be being used, for example, ecstasy, opiates and even synthetic drugs. A subset of those using cannabis as well as amphetamines may also be using a range of other drugs and it may be that our findings reflect polydrug use generally rather than the specific use of cannabis and amphetamines.


Our findings suggest that the young age of onset of cannabis and amphetamine use has minimal impact on later life success for people who do not continue to use these drugs into their adulthood. However, those who do continue to use amphetamines and/or cannabis, even at moderate levels of use, into their later adulthood have significantly lower levels of life success. The major impacts of concurrent drug use on life success are substantial and involve most domains of life success. While the use of cannabis and amphetamines in a community sample of adolescents does confirm lower levels of educational achievement, most harms are concentrated in the small number of users whose use continues into their 30 s. Policies that respond to the findings of this study would firstly act to address the factors predicting the onset of drug use (early adolescent aggressive/delinquent/school-related behavior problems), secondly to discourage cannabis and amphetamine use in the late adolescent and young adult period and, thirdly, focus on support and treatment for those whose pattern of drug use continues into their 30 s.

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Disclosure statement

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

Additional information


This work was supported by the Australian Research Council; National Health and Medical Research Council.


  • AIHW. 2021. Alcohol, tobacco & other drugs in Australia. Retrieved from Canberra: [Google Scholar]
  • Airagnes G, Lemogne C, Meneton P, Plessz M, Goldberg M, Hoertel N, Roquelaure Y, Limosin F, Zins M. 2019. Alcohol, tobacco and cannabis use are associated with job loss at follow-up: findings from the CONSTANCES cohort. PLOS One. 14(9):e0222361-e0222361. [Crossref], [Web of Science ®][Google Scholar]
  • Boden JM, Dhakal B, Foulds JA, Horwood LJ. 2020. Life-course trajectories of cannabis use: a latent class analysis of a New Zealand birth cohort. Addiction. 115(2):279290. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Campeny E, López-Pelayo H, Nutt D, Blithikioti C, Oliveras C, Nuño L, Maldonado R, Florez G, Arias F, Fernández-Artamendi S, et al. 2020. The blind men and the elephant: systematic review of systematic reviews of cannabis use related health harms. Eur Neuropsychopharmacol. 33:135. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Chong HY, Teoh SL, Wu DB-C, Kotirum S, Chiou C-F, Chaiyakunapruk N. 2016. Global economic burden of schizophrenia: a systematic review. Neuropsychiatr Dis Treat. 12:357373. [PubMed], [Web of Science ®][Google Scholar]
  • Craig JM, Piquero AR, Farrington DP. 2020. Not all at-risk boys have bad outcomes: predictors of later life success. Crime and Delinquency. 66(3):392419. [Crossref], [Web of Science ®][Google Scholar]
  • Danielsson A-K, Agardh E, Hemmingsson T, Allebeck P, Falkstedt D. 2014. Cannabis use in adolescence and risk of future disability pension: a 39-year longitudinal cohort study. Drug Alcohol Depend. 143(1):239243. [Crossref], [PubMed][Google Scholar]
  • Darke S, Marel C, Mills KL, Ross J, Slade T, Burns L, Teesson M. 2014. Patterns and correlates of non-fatal heroin overdose at 11-year follow-up: findings from the Australian Treatment Outcome Study. Drug Alcohol Depend. 144:148152. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Degenhardt L, Sara G, McKetin R, Roxburgh A, Dobbins T, Farrell M, Burns L, Hall WD. 2017. Crystalline methamphetamine use and methamphetamine-related harms in Australia. Drug Alcohol Rev. 36(2):160170. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Farrell M, Martin NK, Stockings E, Bórquez A, Cepeda JA, Degenhardt L, Ali R, Tran LT, Rehm J, Torrens M. 2019. Responding to global stimulant use: challenges and opportunities. Lancet. 394(10209):16521667. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Farrington DP, Coid JW, Harnett LM, Jolliffe D, Soteriou N, Turner RE, West DJ. 2006. Criminal careers up to age 50 and life success up to age 48: New findings from the Cambridge Study in Delinquent Development. Retrieved from [Google Scholar]
  • Fergusson DM, Boden JM. 2008. Cannabis use and later life outcomes. Addiction. 103(6):969976. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Foulds JA, Boden JM, McKetin R, Newton-Howes G. 2020. Methamphetamine use and violence: findings from a longitudinal birth cohort. Drug Alcohol Depend. 207:107826107826. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Hall WD, Patton G, Stockings E, Weier M, Lynskey M, Morley KI, Degenhardt L. 2016. Why young people's substance use matters for global health. Lancet Psychiatry. 3(3):265279. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Hasin DS. 2018. US epidemiology of cannabis use and associated problems. Neuropsychopharmacology. 43(1):195212. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Holahan CK. 2021. Achievement across the life span: perspectives from the Terman Study of the Gifted. The Gifted Child Quarterly. 65(2):185195. [Crossref], [Web of Science ®][Google Scholar]
  • Horwood LJ, Fergusson DM, Hayatbakhsh MR, Najman JM, Coffey C, Patton GC, Silins E, Hutchinson DM. 2010. Cannabis use and educational achievement: findings from three Australasian cohort studies. Drug Alcohol Depend. 110(3):247253. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Kendler KS, Ohlsson H, Sundquist J, Sundquist K. 2019. Prediction of onset of substance-induced psychotic disorder and its progression to schizophrenia in a Swedish National sample. AJP. 176(9):711719. [Crossref][Google Scholar]
  • Layard R, Clark AE, Cornaglia F, Powdthavee N, Vernoit J. 2014. What predicts a successful life? A life-course model of well-being. Econ J. 124(580):F720F738. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Lynskey M, Hall W. 2000. The effects of adolescent cannabis use on educational attainment: a review. Addiction. 95(11):16211630. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • McGrath J, Welham J, Scott J, Varghese D, Degenhardt L, Hayatbakhsh MR, Alati R, Williams GM, Bor W, Najman JM. 2010. Association between cannabis use and psychosis-related outcomes using sibling pair analysis in a cohort of young adults. Arch Gen Psychiatry. 67(5):440447. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • McKetin R, Boden JM, Foulds JA, Najman JM, Ali R, Degenhardt L, Baker AL, Ross J, Farrell M, Weatherburn D. 2020. The contribution of methamphetamine use to crime: evidence from Australian longitudinal data. Drug Alcohol Depend. 216:108262108262. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • McKetin R, Leung J, Stockings E, Huo Y, Foulds J, Lappin JM, Cumming C, Arunogiri S, Young JT, Sara G. 2019. Mental health outcomes associated with of the use of amphetamines: a systematic review and meta-analysis. EClinicalMedicine. 16:8197. [Crossref], [PubMed][Google Scholar]
  • Moons P, Budts W, De Geest S. 2006. Critique on the conceptualisation of quality of life: a review and evaluation of different conceptual approaches. Int J Nurs Stud. 43(7):891901. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Najman JM, Alati R, Bor W, Clavarino A, Mamun A, McGrath JJ, McIntyre D, O'Callaghan M, Scott J, Shuttlewood G. 2015. Cohort profile update: the Mater-University of Queensland Study of Pregnancy (MUSP). Int J Epidemiol. 44(1):7878. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Najman JM, Bor W, O'Callaghan M, Williams GM, Aird R, Shuttlewood G. 2005. Cohort profile: the Mater-University of Queensland Study of Pregnancy (MUSP). Int J Epidemiol. 34(5):992997. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Parker B, Chusmir LH. 1992. Development and validation of a life-success measures scale. Psychol Rep. 70(2):627637. [Crossref], [Web of Science ®][Google Scholar]
  • Reed V, Gander F, Pfister H, Steiger A, Sonntag H, Trenkwalder C, Sonntag A, Hundt W, Wittchen H-U. 1998. To what degree does the Composite International Diagnostic Interview (CIDI) correctly identify DSM‐IV disorders? Testing validity issues in a clinical sample. Int J Method Psychiat Res. 7(3):142155. [Crossref][Google Scholar]
  • Saiepour N, Najman JM, Ware R, Baker P, Clavarino AM, Williams GM. 2019. Does attrition affect estimates of association: a longitudinal study. J Psychiatr Res. 110:127142. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Sears RR. 1977. Sources of life satisfactions of the Terman gifted men. Am Psychol. 32(2):119128. [Crossref], [PubMed], [Web of Science ®][Google Scholar]
  • Schoeler T, Monk A, Sami MB, Klamerus E, Foglia E, Brown R, Camuri G, Altamura AC, Murray R, Bhattacharyya S. 2016. Continued versus discontinued cannabis use in patients with psychosis: a systematic review and meta-analysis. Lancet Psychiat. 3:215–225. [Crossref][Google Scholar]
  • Schoeler T, Theobald D, Pingault J, Farrington D, Coid J, Bhattacharyya S. 2018. Developmental sensitivity to cannabis use patterns and risk for major depressive disorder in mid-life: Findings from 40 years follow-up. Pschol Med. 48:2169–2176. [Crossref][Google Scholar]
  • Stuyt E. 2019. The Problem with the Current High Potency THC Marijuana from the Perspective of an Addiction Psychiatrist. Missouri Medicine. 482486. [Google Scholar]
  • Sawyer SM, Azzopardi P S, Wickremarathne D, Patton GC. 2018. The age of adolescence. Lancet, Child Adolesc Health. 2:223–228. [Google Scholar]
  • Ullrich S, Farrington DP, Coid JW. 2008. Psychopathic personality traits and life-success. Personality and Individual Differences. 44(5):11621171. [Crossref], [Web of Science ®][Google Scholar]
  • Volkow ND, Baler RD, Compton WM, Weiss SR. 2014. Adverse health effects of marijuana use. N Engl J Med. 370(23):22192227. [Crossref], [PubMed], [Web of Science ®][Google Scholar]

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