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Longitudinal patterns of polysubstance use throughout adolescence: association with adult substance use and psychosocial outcomes controlling for preadolescent risk factors in a male cohort

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Abstract

Purpose

Inconsistent reports raise the question of the extent to which poor adult outcomes are associated with adolescent polysubstance use (PSU: alcohol, marijuana, other illicit drugs) above and beyond earlier risk factors.

Methods

Early adulthood substance-related and psychosocial outcomes were examined in association with age 13 to 17 developmental patterns of PSU in boys from urban, low SES neighborhoods (N = 926). Three classes obtained by latent growth modeling described low/non-users (N = 565, 61.0%), lower risk PSU (later onset, occasional use, 2 ≤ substances; N = 223, 24.1%), and higher risk PSU (earlier onset, frequent use, 3 ≥ substances; N = 138, 14.9%). Preadolescent individual, familial and social predictors of adolescent PSU patterns were used as covariates.

Results

Adolescent PSU contributed to both age-24 substance-related outcomes (frequency of alcohol, drug use, and getting drunk, risky behaviors under influence, and use-related problems) and psychosocial outcomes (no high school diploma, professional or financial strain, ASP symptoms, criminal record) over and above preadolescent risk factors. Controlling for preadolescent risk factors, adolescent PSU made a more important contribution to adult substance use outcomes (increasing the risk by about 110%) than to psychosocial outcomes (16.8% risk increase). PSU classes showed poorer adjustment for all age-24 substance use, and for various psychosocial outcomes than low/non-users. Higher risk polysubstance users also reported poorer outcomes than their lower risk peers for most substance use outcomes, and for professional or financial strain and criminal record.

Conclusion

Findings highlight the contribution of adolescent PSU in a dose–response fashion, over and above preadolescent risk factors, on both homotypic and heterotypic outcomes in early adulthood.

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Data availability

The dataset supporting the present report is not publicly available. Availability on request by qualified scientists will be considered after handing in a data request (https://grip-info.ca/acces-aux-donnees/). Formal agreement and ethical clearance to regulate data storage and use will be required. All data were anonymized in accordance with ethical guidelines.

References

  1. Han B, Compton WM, Blanco C, DuPont RL (2017) National trends in substance use and use disorders among youth. J Am Acad Child Adolesc Psychiatry 56(9):747-754.e3

    Article  PubMed  Google Scholar 

  2. Zuckermann AME, Williams GC, Battista K, Jiang Y, de Groh M, Leatherdale ST (2020) Prevalence and correlates of youth poly-substance use in the COMPASS study. Addict Behav 107:106400

    Article  PubMed  Google Scholar 

  3. Zuckermann A, Williams G, Battista K, de Groh M, Jiang Y, Leatherdale ST (2019) Trends of poly-substance use among Canadian youth. Addict Behav Rep 10:100189

    PubMed  PubMed Central  Google Scholar 

  4. Oldham M, Livingston M, Whitaker V, Callinan S, Fairbrother H, Curtis P, Meier P, Holmes J (2021) Trends in the psychosocial characteristics of 11–15-year-olds who still drink, smoke, take drugs and engage in poly-substance use in England. Drug Alcohol Rev 40:597–606

    Article  PubMed  Google Scholar 

  5. Connor JP, Gullo MJ, White A, Kelly AB (2014) Polysubstance use: diagnostic challenges, patterns of use and health. Curr Opin Psychiatry 27:269–275

    Article  PubMed  Google Scholar 

  6. Moss HB, Chen CM, Yi H (2014) Early adolescent patterns of alcohol, cigarettes, and marijuana polysubstance use and young adult substance use outcomes in a nationally representative sample. Drug Alcohol Depend 136:51–62

    Article  PubMed  Google Scholar 

  7. European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) (2009) Polydrug use: patterns and responses. Official Publications of the European Communities, Luxembourg

    Google Scholar 

  8. Tucker JS, Rodriguez A, Davis JP, Klein DJ, D’Amico EJ (2021) Simultaneous trajectories of alcohol and cannabis use from adolescence to emerging adulthood: associations with role transitions and functional outcomes. Psychol Addict Behav 35(6):628–637

    Article  PubMed  PubMed Central  Google Scholar 

  9. Lynne-Landsman SD, Bradshaw CP, Ialongo NS (2010) Testing a developmental cascade model of adolescent substance use trajectories and young adult adjustment. Dev Psychopathol 22:933–948

    Article  PubMed  PubMed Central  Google Scholar 

  10. Tucker JS, Rodriguez A, Dunbar MS et al (2019) Cannabis and tobacco use and co-use: trajectories and correlates from early adolescence to emerging adulthood. Drug Alcohol Depend 204:107499

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Merrin GJ, Leadbeater B (2018) Do classes of polysubstance use in adolescence differentiate growth in substances used in the transition to young adulthood? Subst Use Misuse 53(13):2112–2124

    Article  PubMed  Google Scholar 

  12. Schulenberg J, Maslowsky J, Patrick M, Martz M (2019) Substance use in the context of adolescent development (chapter 2). In: Zucker RA, Brown SA (eds) The Oxford handbook of adolescent substance abuse. Oxford University Press, Oxford, pp 19–36

    Google Scholar 

  13. Collins RL, Ellickson PL, Bell RM (1998) Simultaneous polydrug use among teens: prevalence and predictors. J Subst Abus 10:233–253

    Article  CAS  Google Scholar 

  14. Tomczyk S, Isensee B, Hanewinkel R (2016) Latent classes of polysubstance use among adolescents—a systematic review. Drug Alcohol Depend 160:12–29

    Article  PubMed  Google Scholar 

  15. Halladay J, Woock R, El-Khechen H, Munn C, MacKillop J, Amlung M et al (2020) Patterns of substance use among adolescents: a systematic review. Drug Alcohol Depend 160(216):108222

    Article  Google Scholar 

  16. Carbonneau R, Vitaro F, Brendgen M, Tremblay RE (2022) Alcohol, marijuana and other illicit drugs use throughout adolescence: co-occurring courses and preadolescent risk factors. Child Psychiatry Hum Dev 53:1194-1206. https://doi.org/10.1007/s10578-021-01202-w

    Article  PubMed  Google Scholar 

  17. Lamont A, Woodlief D, Malone P (2014) Predicting high-risk versus higher-risk substance use during late adolescence from early adolescent risk factors using latent class analysis. Addict Res Theory 22:78–89

    Article  PubMed  Google Scholar 

  18. Martínez-Loredo V, Fernández-Hermida JR, de La Torre-Luque A, Fernández-Artamendi S (2018) Polydrug use trajectories and differences in impulsivity among adolescents. Int J Clin Health Psychol 18(3):235–244

    Article  PubMed  PubMed Central  Google Scholar 

  19. Kaplow JB, Curran PJ, Dodge KA, Conduct Problems Prevention Research Group (2002) Child, parent, and peer predictors of early-onset substance use: a multisite longitudinal study. J Abnorm Child Psychol 30(3):199–216

    Article  PubMed  PubMed Central  Google Scholar 

  20. Jackson NJ, Isen JD, Khoddam R et al (2016) Impact of adolescent marijuana use on intelligence: results from two longitudinal twin studies. Proc Natl Acad Sci USA 113(5):E500–E508

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Meier MH, Caspi A, Danese A et al (2018) Associations between adolescent cannabis use and neuropsychological decline: a longitudinal co-twin control study. Addiction 113(2):257–265

    Article  PubMed  Google Scholar 

  22. Verweij KJ, Huizink AC, Agrawal A, Martin NG, Lynskey MT (2013) Is the relationship between early-onset cannabis use and educational attainment causal or due to common liability? Drug Alcohol Depend 133(2):580–586

    Article  PubMed  Google Scholar 

  23. Beauchaine TP, Zisner AR, Sauder CL (2017) Trait impulsivity and the externalizing spectrum. Annu Rev Clin Psychol 13:343–368

    Article  PubMed  Google Scholar 

  24. Iacono WG, Malone SM, McGue M (2008) Behavioral disinhibition and the development of early-onset addiction: common and specific influences. Annu Rev Clin Psychol 4:325–348

    Article  PubMed  Google Scholar 

  25. Patrick CJ, Foell J, Venables NC, Worthy DA (2016) Substance use disorders as externalizing outcomes. In: Beauchaine TP, Hinshaw SP (eds) The Oxford handbook of externalizing spectrum disorders. Oxford University Press, New York, pp 38–60

    Google Scholar 

  26. Chassin L, Colder CR, Hussong AM, Sher KJ (2016) Substance use and substance use disorders (chapter 19). In: Cicchetti D (ed) Development and psychopathology (vol 3) maladaptation and psychopathology. Wiley, pp 1–65

    Google Scholar 

  27. Dodge KA, Malone PS, Lansford JE, Miller S, Pettit GS, Bates JE (2009) A dynamic cascade model of the development of substance-use onset. Monogr Soc Res Child Dev 74(3):vii–119

    PubMed  Google Scholar 

  28. Fuhrmann D, Knoll LJ, Blakemore SJ (2015) Adolescence as a sensitive period of brain development. Trends Cogn Sci 19(10):558–566

    Article  PubMed  Google Scholar 

  29. Meredith L, Squeglia L (2020) The adolescent brain: predictors and consequences of substance use (Chapter 13). In: Begun AL, Murray MM (eds) The Routledge handbook of social work and addictive behaviors. Routledge, New York, pp 216–231

    Chapter  Google Scholar 

  30. Volkow ND, Michaelides M, Baler R (2019) The neuroscience of drug reward and addiction. Physiol Rev 99(4):2115–2140

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Uhl GR, Koob GF, Cable J (2019) The neurobiology of addiction. Ann N Y Acad Sci 1451(1):5–28

    Article  PubMed  PubMed Central  Google Scholar 

  32. Conrod PJ, Nikolaou K (2016) Annual research review: on the developmental neuropsychology of substance use disorders. J Child Psychol Psychiatry 57(3):371–394

    Article  PubMed  Google Scholar 

  33. Crummy EA, O’Neal TJ, Baskin BM, Ferguson SM (2020) One is not enough: understanding and modeling polysubstance use. Front Neurosci 14:569

    Article  PubMed  PubMed Central  Google Scholar 

  34. Hernández-Serrano O, Gras ME, Font-Mayolas S, Sullman MJM (2016) Types of polydrug usage. In: Preedy VR (ed) Neuropathology of drug addictions and substance misuse. Academic Press, New York, pp 839–849

    Chapter  Google Scholar 

  35. Smith JL, Mattick RP, Jamadar SD, Iredale JM (2014) Deficits in behavioural inhibition in substance abuse and addiction: a meta-analysis. Drug Alcohol Depend 145:1–33

    Article  PubMed  Google Scholar 

  36. Copeland WE, Hill SN, Shanahan L (2021) Adult psychiatric, substance, and functional outcomes of different definitions of early cannabis use. J Am Acad Child Adolesc Psychiatry (published online ahead of print Aug 17 0890–8567(21)01350–2)

  37. Meier MH (2021) Cannabis use and psychosocial functioning: evidence from prospective longitudinal studies. Curr Opin Psychol 38:19–24

    Article  PubMed  Google Scholar 

  38. Wemm SE, Sinha R (2019) Drug-induced stress responses and addiction risk and relapse. Neurobiol Stress 10:100148

    Article  PubMed  PubMed Central  Google Scholar 

  39. Guttmannova K, Kosterman R, White HR et al (2017) The association between regular marijuana use and adult mental health outcomes. Drug Alcohol Depend 179:109–116

    Article  PubMed  PubMed Central  Google Scholar 

  40. Taylor M, Collin SM, Munafò MR, MacLeod J, Hickman M, Heron J (2017) Patterns of cannabis use during adolescence and their association with harmful substance use behaviour: findings from a UK birth cohort. J Epidemiol Community Health 71(8):764–770

    Article  PubMed  Google Scholar 

  41. Scholes-Balog KE, Hemphill SA, Evans-Whipp TJ, Toumbourou JW, Patton GC (2016) Developmental trajectories of adolescent cannabis use and their relationship to young adult social and behavioural adjustment: a longitudinal study of Australian youth. Addict Behav 53:11–18

    Article  PubMed  Google Scholar 

  42. Gobbi G, Atkin T, Zytynski T et al (2019) Association of cannabis use in adolescence and risk of depression, anxiety, and suicidality in young adulthood: a systematic review and meta-analysis. JAMA Psychiat 76(4):426–434

    Article  Google Scholar 

  43. Banks DE, Hershberger AR, Pemberton T, Clifton RL, Aalsma MC, Zapolski TCB (2019) Poly-use of cannabis and other substances among juvenile-justice involved youth: variations in psychological and substance-related problems by typology. Am J Drug Alcohol Abuse 45(3):313–322

    Article  PubMed  PubMed Central  Google Scholar 

  44. Tremblay RE, Vitaro F, Nagin D, Pagani L, Séguin JR (2003) The Montreal longitudinal and experimental study: rediscovering the power of descriptions. Taking stock of delinquency: an overview of findings from contemporary longitudinal studies. Kluwer Academic/Plenum, New York

    Google Scholar 

  45. Cohen J (1988) Statistical power analysis for the behavioral sciences, 2nd edn. Erlbaum, Hillsdale

    Google Scholar 

  46. McCabe SE, Cranford JA, Morales M, Young A (2006) Simultaneous and concurrent polydrug use of alcohol and prescription drugs: prevalence, correlates, and consequences. J Stud Alcohol Drugs 67:529–537

    Article  Google Scholar 

  47. Muthén LK, Muthén BO (1998–2017) Mplus user’s guide eighth edition. Muthén & Muthén, Los Angeles

  48. Feldman B, Masyn KE, Conger R (2009) New approaches to studying problem behaviors: a comparison of methods for modeling longitudinal, categorical adolescent drinking data. Dev Psychol 45:652–676

    Article  PubMed  PubMed Central  Google Scholar 

  49. Kandauda AS, Wickrama TKL, Walker-O’Neal C, Lorenz FO (2016) Higher-order growth curves and mixture modeling with Mplus. Routledge, New-York

    Google Scholar 

  50. Kandel DB (2002) Stages and pathways of drug involvement: examining the gateway. Cambridge University Press, New-York

    Book  Google Scholar 

  51. Gray KM, Squeglia LM (2018) Research review: what have we learned about adolescent substance use? J Child Psychol Psychiatry 59(6):618–627

    Article  PubMed  Google Scholar 

  52. Tremblay RE, Vitaro F, Gagnon C, Piché C, Royer N (1991) Social behavior questionnaire: assessing adjusted as well as maladjusted behavior. Int J Behav Dev 15:227–245

    Article  Google Scholar 

  53. Rosenberg M (1965) Society and the adolescent self-image. Princeton University Press, Princeton

    Book  Google Scholar 

  54. Eysenck SBG, Easting G, Pearsons PR (1984) Age norms for impulsiveness, venturesomeness, and empathy in children. Pers Individ Dif 5:315–321

    Article  Google Scholar 

  55. Eysenck SBG, Eysenck HJ (1978) Impulsiveness and venturesomeness: their position in a dimensional system of personality description. Psychol Rep 43:1247–1255

    Article  CAS  PubMed  Google Scholar 

  56. LeBlanc M, Frechette M (1989) Male criminal activity from childhood through youth: multilevel and developmental perspective. Springer-Verlag, New York

    Book  Google Scholar 

  57. Clark LA, Watson D (1995) Constructing validity: basic issues in objective scale development. Psychol Assess 7:309–319

    Article  Google Scholar 

  58. American Psychiatric Association (2013) Diagnostic and statistical manual of mental disorders, 5th edn. American Psychiatric Publishing, Arlington

    Book  Google Scholar 

  59. Hardin JW, Hilbe JM (2018) Generalized linear models and extensions, 4th edn. Stata Press, College Station

    Google Scholar 

  60. Burnham KP, Anderson DR (2002) Model selection and multimodel inference, 2nd edn. Springer, Berlin

    Google Scholar 

  61. Mundry R, Nunn C (2009) Stepwise model fitting and statistical inference: turning noise into signal pollution. Am Nat 173:119–123

    Article  PubMed  Google Scholar 

  62. Dziak JJ, Coffman DL, Lanza ST, Li R, Jermiin LS (2020) Sensitivity and specificity of information criteria. Brief Bioinform 21(2):553–565

    Article  PubMed  Google Scholar 

  63. Steyerberg EW, Vickers AJ, Cook NR et al (2010) Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology 21(1):128–138

    Article  PubMed  PubMed Central  Google Scholar 

  64. Nagelkerke NJD (1991) A note on the general definition of the coefficient of determination. Biometrika 78(3):691–692

    Article  Google Scholar 

  65. Nagin DS (2005) Group-based modeling of development. Harvard University Press, Cambridge

    Book  Google Scholar 

  66. Clark SL, Muthen B (2009) Relating latent class analysis results to variables not included in the analysis. Available at http://www.statmodel.com/download/Relatinglca.pdf

  67. Thompson CA, Arah OA (2014) Selection bias modeling using observed data augmented with imputed record-level probabilities. Ann Epidemiol 24(10):747–753

    Article  PubMed  PubMed Central  Google Scholar 

  68. Upah R, Jacob T, Price RK (2015) Trajectories of lifetime comorbid alcohol and other drug use disorders through midlife. J Stud Alcohol Drugs 76(5):721–732

    Article  PubMed  Google Scholar 

  69. Carbonneau R, Tremblay RE (2022) Antisocial behavior prevention: toward a developmental biopsychosocial perspective (Chapter 2). In: Garofalo C, Sijtsema JJ (eds) Clinical forensic psychology: introductory perspectives on offending. Palgrave Macmillan, Springer Nature, pp 29–47

    Chapter  Google Scholar 

  70. Nelson SE, Van Ryzin MJ, Dishion TJ (2015) Alcohol, marijuana, and tobacco use trajectories from age 12 to 24 years: demographic correlates and young adult substance use problems. Dev Psychopathol 27(1):253–277

    Article  PubMed  Google Scholar 

  71. National Research Council and Institute of Medicine (2009) Preventing mental, emotional, and behavioral disorders among young people: progress and possibilities. The National Academies Press, Washington

    Google Scholar 

  72. Perry CL (2000) Preadolescent and adolescent influences on health (Chapter E). Promoting health: Intervention strategies from social and behavioral research. The National Academies Press, Washington, pp 217–253

    Google Scholar 

  73. Derringer J, Krueger RF, Iacono WG, McGue M (2010) Modeling the impact of age and sex on a dimension of poly-substance use in adolescence: a longitudinal study from 11- to 17-years-old. Drug Alcohol Depend 110(3):193–199

    Article  PubMed  PubMed Central  Google Scholar 

  74. Johnston LD, Miech RA, O’Malley PM, Bachman JG, Schulenberg JE, Patrick ME (2020) Monitoring the Future national survey results on drug use 1975–2019: overview, key findings on adolescent drug use. Institute for Social Research, University of Michigan, Ann Arbor

    Book  Google Scholar 

  75. Choi HJ, Lu Y, Schulte M, Temple JR (2018) Adolescent substance use: latent class and transition analysis. Addict Behav 77:160–165

    Article  PubMed  Google Scholar 

  76. Crane NA, Langenecker SA, Mermelstein RJ (2021) Risk factors for alcohol, marijuana, and cigarette polysubstance use during adolescence and young adulthood: a 7-year longitudinal study of youth at high risk for smoking escalation. Addict Behav 119:106944

    Article  PubMed  PubMed Central  Google Scholar 

  77. Merrin GJ, Ames ME, Sturgess C, Leadbeater BJ (2020) Disruption of transitions in high-risk substance use from adolescence to young adulthood: school, employment, and romantic relationship factors. Subst Use Misuse 55(7):1129–1137

    Article  PubMed  Google Scholar 

  78. Steinhoff A, Bechtiger L, Ribeaud D, Eisner MP, Quednow BB, Shanahan L (2022) Polysubstance use in early adulthood: patterns and developmental precursors in an urban cohort. Front Behav Neurosci 15:797473

    Article  PubMed  PubMed Central  Google Scholar 

  79. Miech RA, Johnston LD, Patrick ME, O’Malley PM, Bachman JG, Schulenberg JE (2023) Monitoring the Future National Survey Results on Drug Use, 1975–2022: Secondary School Students. Institute for Social Research, University of Michigan, Ann Arbor

    Google Scholar 

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Acknowledgements

We thank the families and the participants of the Montreal Longitudinal and Experimental Study for their collaboration to this project, and the staff of the Research Unit on Children’s Psychosocial Maladjustment for data collection and management.

Funding

We thank the Québec Ministry of Health, the Fond Québécois de la Recherche sur la Société et la Culture, Canada’s Social Science and Humanities Research Council, and the University of Montréal for financial support.

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Correspondence to Rene Carbonneau.

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All procedures contributing to this work complied with the ethical standards of the relevant national and institutional committees on human experimentation and with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. This study was approved by the University of Montreal’s Institutional Review Board.

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Informed written consent of the participants was obtained from all participants and their parents (when applicable), for each assessment wave, prior to their inclusion in the study.

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Carbonneau, R., Vitaro, F., Brendgen, M. et al. Longitudinal patterns of polysubstance use throughout adolescence: association with adult substance use and psychosocial outcomes controlling for preadolescent risk factors in a male cohort. Soc Psychiatry Psychiatr Epidemiol 58, 1469–1481 (2023). https://doi.org/10.1007/s00127-023-02454-8

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