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Cited by 114Substance Abuse Treatment and OutcomesCannabis and Cannabinoid ResearchGambling Behavior and Treatments

Towards a comprehensive developmental model of cannabis use disorders

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Blanco, Carlos, Rafful, Claudia, Wall, Melanie M., Ridenour, Ty A., Wang, Shuai, Kendler, Kenneth S.·2014·Addiction
DOI 10.1111/add.12382PMC PMC3956073
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Abstract

Aims: To develop a comprehensive risk‐factor model of cannabis use disorders (CUD) based on K endler's development model for major depression. Design: Risk factors were divided into five developmental tiers based on K endler's model of depression (childhood, early adolescence, late adolescence, adulthood, past year). Hierarchical logistic regression models were used to examine the independent contribution of each risk factor. Separate models were built to predict the lifetime risk of cannabis use and the risk of CUD among those with a history of lifetime risk of cannabis use. Setting: Data were drawn from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) in the U nited S tates. Participants: Participants consisted of wave 2 of the NESARC (n = 34 653). Measurements: Odds ratios (OR), Adjusted OR (AOR) and confidence intervals (95% CI) were used to determine the risk factors in each tier and with multiple models. Findings: After mutually adjusting for the effect of other risk factors, lifetime history of drug use disorder (AOR = 4.78, 95% CI = 1.53–14.91), past year alcohol use disorders (AOR = 6.55, 95% CI = 2.54–16.89) and independent (AOR = 1.57, 95% CI = 1.15–2.14) and dependent (AOR = 1.25, 95% CI = 1.01–1.55) stressful life events predicted lifetime cannabis use. Impulsivity (AOR = 2.18, 95% CI = 1.34–3.53), past year alcohol use disorders (AOR = 4.09, 95% CI = 2.29–7.31), greater number of Axis I disorders (AOR = 1.56, 95% CI = 1.01–2.40) and social deviance (AOR = 1.19, 95% CI = 1.08–1.32) independently increased the risk of the development of CUD, whereas religious service attendance (AOR = 0.50, 95% CI = 0.30–0.85) decreased this risk. In both models, the effect of earlier development tiers was mediated by more proximal ones. There were few gender differences in both models. Conclusions: A modification of K endler's risk factor model for major depression which stratifies risk factors into five groups (childhood, early adolescence, late adolescence, adulthood, past year) provides a useful foundation for a comprehensive developmental model of cannabis use and cannabis use disorders.

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  • Substance use and SUDs are multidetermined, with different risk factors playing varying roles at different life stages, from the prenatal period and childhood to early and late adulthood.

    “Substance use and SUDs are multidetermined, with the differ ent risk factors playing varying roles at different life stages, from the prenatal period and childhood to early and late adulthood 78,79,164 .”

    From Substance use disorders: a comprehensive update of classification, epidemiology, neurobiology, clinical aspects, treatment and prevention (2023) · cites this paper as [78]

    The Methods (Measures; page unavailable) group risk factors from childhood through adulthood and the past year, and the Discussion (page unavailable) describes cannabis use disorders as multifactorial, with earlier factors often mediated by later ones. The paper studies cannabis use and cannabis use disorders, not substance use and SUDs generally; its developmental tiers do not include the prenatal period or distinguish late adulthood. (LLM, conf=0.88)

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  • Biological risk for SUDs emerges early in life, changes at various life stages, and is differentially influenced by social factors and experiences during those life stages and transitions.

    “Biological risk for SUDs emerges early in life, changes at vari ous life stages, and is differentially influenced by social factors and experiences during those different life stages and transi tions 78 .”

    From Substance use disorders: a comprehensive update of classification, epidemiology, neurobiology, clinical aspects, treatment and prevention (2023) · cites this paper as [78]

    The Methods (Measures; page not provided) place family history of substance use disorders alongside social experiences in childhood and organize risk factors across five developmental stages. The Discussion (page not provided) says earlier and later factors jointly contribute to cannabis use disorder risk. It does not establish that biological risk itself changes over life or is altered by social experiences, and its analysis concerns cannabis use disorder rather than SUDs generally. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 47

  1. [1]SAMSA Results from the 2010 National Survey on Drug Use and Health: Summary of National Findings 2011 Rockville, MD Substance Abuse and Mental Health Services Administration 30199189
  2. [2]Houston JE Murphy J Adamson G Stringer M Shevlin M Childhood sexual abuse, early cannabis use, and psychosis: testing an interaction model based on the National Comorbidity Survey Schizophr Bull 2008 34 3 580 585 18024467 PMC2632429
  3. [3]Duncan AE Sartor CE Scherrer JF Grant J Heath AC Nelson EC The association between cannabis abuse and dependence and childhood physical and sexual abuse: evidence from an offspring of twins design Addiction 2008 103 6 990 997 18482422 PMC2653098
  4. [4]Reingle JM Staras SAS Jennings WG Branchini J Maldonado-Molina MM The relationship between marijuana use and intimate partner violence in a nationally representative, longitudinal sample Journal of Interpersonal Violence 2011 PMC3782298 22080574
  5. [5]Compton WM Conway KP Stinson FS Colliver JD Grant BF Prevalence, correlates, and comorbidity of DSM-IV antisocial personality syndromes and alcohol and specific drug use disorders in the United States: results from the national epidemiologic survey on alcohol and related conditions J Clin Psychiatry 2005 66 677 685 15960559
  6. [6]Behrendt S Wittchen HU Höfler M Lieb R Beesdo K Transitions from first substance use to substance use disorders in adolescence: Is early onset associated with a rapid escalation? Drug Alcohol Depend 2009 99 68 78 18768267
  7. [7]Behrendt S Beesdo-Baum K Höfler M Perkonigg A Bühringer G Lieb R The relevance of age at first alcohol and nicotine use for initiation of cannabis use and progression to cannabis use disorders Drug Alcohol Depend 2012 123 1–3 48 56 22071122
  8. [8]Lopez-Quintero C Cobos JP Hasin DS Okuda M Wang S Grant BF Probability and predictors of transition from first use to dependence on nicotine, alcohol, cannabis, and cocaine: Results of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) Drug Alcohol Depend 2011 115 1–2 120 130 21145178 PMC3069146
  9. [9]Chamorro J Bernardi S Potenza MN Grant JD Marsh R Wang S Impulsivity in the general population: a national study J Psychiatr Res 2012 46 8 994 1001 22626529 PMC3564492
  10. [10]Moeller FG Barratt ES Dougherty DM Schmitz JM Swann AC Psychiatric aspects of impulsivity Am J Psychiatry 2001 158 11 1783 1793 11691682
  11. [11]Lynskey MT Heath A Nelson E Bucholz K Madden P Slutske W Genetic and environmental contributions to cannabis dependence in a national young adult twin sample Psychol Med 2002 32 02 195 207 11871371
  12. [12]Agrawal A Lynskey MT The genetic epidemiology of cannabis use, abuse and dependence Addiction 2006 101 6 801 812 16696624
  13. [13]Clark DB Winters KC Measuring risks and outcomes in substance use disorders prevention research J Consult Clin Psyschol 2002 70 6 1207 12472298
  14. [14]Pérez-Fuentes G Olfson M Villegas L Morcillo C Wang S Blanco C Prevalence and correlates of child sexual abuse: a national study Compr Psychiatry 2013 54 16 27 22854279 PMC3518746
  15. [15]Sugaya L Hasin DS Olfson M Lin KH Grant B Blanco C Child physical abuse and adult mental health: a national study J Trauma Stress 2012 25 4 384 392 22806701 PMC3805363
  16. [16]Douglas KR Chan G Gelernter J Arias AJ Anton RF Weiss RD Adverse childhood events as risk factors for substance dependence: partial mediation by mood and anxiety disorders Addict Behav 2010 35 1 7 13 19720467 PMC2763992
  17. [17]Nathan PE The addictive personality is the behavior of the addict J Consult Clin Psyschol 1988 56 2 183 188 3286702
  18. [18]Tarter RE Kirisci L Mezzich A Cornelius JR Pajer K Vanyukov M Neurobehavioral disinhibition in childhood predicts early age at onset of substance use disorder Am J Psychiatry 2003 160 6 1078 1085 12777265
  19. [19]Mezzich AC Tarter RE Feske U Kirisci L McNamee RL Day BS Assessment of risk for substance use disorder consequent to consumption of illegal drugs: Psychometric validation of the neurobehavior disinhibition trait Psychol Addict Behav 2007 21 4 508 515 18072833
  20. [20]Grant BF Stinson FS Dawson DA Chou SP Dufour MC Compton W Prevalence and co-occurrence of substance use disorders and independent mood and anxiety disorders: Results from the National Epidemiologic Survey on Alcohol and Related Conditions Arch Gen Psychiatry 2004 61 8 807 816 15289279
  21. [21]Grant B Comorbidity between DSM-IV drug use disorders and major depression: results of a National Survey of Adults Journal of Substance Abuse 1995 7 4 481 497 8838629
  22. [22]Dawson DA Goldstein RB Chou SP Ruan WJ Grant BF Age at first drink and the first incidence of adult-onset DSM-IV alcohol use disorders Alcohol Clin Exp Res 2008 32 12 2149 2160 18828796 PMC2760820
  23. [23]King KM Chassin L A prospective study of the effects of age of initiation of alcohol and drug use on young adult substance dependence J Stud Alcohol 2007 68 2 256 265 17286344
  24. [24]Nwakeze PC Magura S Rosenblum A Joseph H Homelessness, substance misuse, and access to public entitlements in a soup kitchen population Substance Use & Misuse 2003 38 3–6 645 668 12747400
  25. [25]Haber PS Demirkol A Lange K Murnion B Management of injecting drug users admitted to hospital The Lancet 2009 374 9697 1284 1293 19819393
  26. [26]Kendler KS Gardner CO Prescott CA Religion, psychopathology, and substance use and abuse: a multimeasure, genetic-epidemiologic study Am J Psychiatry 1997 154 3 322 329 9054778
  27. [27]Kendler KS Liu XQ Gardner CO McCullough ME Larson D Prescott CA Dimensions of religiosity and their relationship to lifetime psychiatric and substance use disorders Am J Psychiatry 2003 160 3 496 503 12611831
  28. [28]Heiman GA Ogburn E Gorroochurn P Keyes KM Hasin D Evidence for a two-stage model of dependence using the NESARC and its implications for genetic association studies Drug Alcohol Depend 2008 92 1 258 266 17933473 PMC2266584
  29. [29]Grant BF Stinson FS Dawson DA Chou SP Ruan W Pickering RP Co-occurrence of 12-month alcohol and drug use disorders and personality disorders in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions Arch Gen Psychiatry 2004 61 4 361 368 15066894
  30. [30]Grant BF Goldstein RB Chou SP Huang B Stinson FS Dawson DA Sociodemographic and psychopathologic predictors of first incidence of DSM-IV substance use, mood and anxiety disorders: results from the Wave 2 National Epidemiologic Survey on Alcohol and Related Conditions Mol Psychiatry 2009 14 11 1051 1066 18427559 PMC2766434
  31. [31]Grant BF Harford TC Dawson DA Chou PS Pickering RP The Alcohol Use Disorder and Associated Disabilities Interview Schedule (AUDADIS): reliability of alcohol and drug modules in a general population sample Drug Alcohol Depend 1995 39 1 37 44 7587973
  32. [32]Grant BF Dawson DA Stinson FS Chou PS Kay W Pickering R The Alcohol Use Disorder and Associated Disabilities Interview Schedule-IV (AUDADIS-IV): reliability of alcohol consumption, tobacco use, family history of depression and psychiatric diagnostic modules in a general population sample Drug Alcohol Depend 2003 71 1 7 16 12821201
  33. [34]Hosmer D Lemeshow S Applied logistic regression 2000 2nd ed. New York John Wiley & Sons
  34. [35]Harrell FE Jr Lee KL Califf RM Pryor DB Rosati RA Regression modelling strategies for improved prognostic prediction Statistics in Medicine 1984 3 2 143 152 6463451
  35. [37]van den Bree M Pickworth WB Risk factors predicting changes in marijuana involvement in teenagers Arch Gen Psychiatry 2005 62 3 311 319 15753244
  36. [40]Kendler KS Gardner CO Prescott CA Toward a comprehensive developmental model for major depression in women Am J Psychiatry 2002 159 7 1133 1145 12091191
  37. [41]Kendler KS Gardner CO Prescott CA Toward a comprehensive developmental model for alcohol use disorders in men Twin Research and Human Genetics 2011 14 1 1 15 21314251 PMC3081886
  38. [42]Nelson EC Heath AC Madden PAF Cooper ML Dinwiddie SH Bucholz KK Association between self-reported childhood sexual abuse and adverse psychosocial outcomes: results from a twin study Arch Gen Psychiatry 2002 59 2 139 145 11825135
  39. [43]Dube SR Anda RF Whitfield CL Brown DW Felitti VJ Dong M Long-term consequences of childhood sexual abuse by gender of victim Am J Prev Med 2005 28 5 430 438 15894146
  40. [44]Pfiffner LJ McBurnett K Rathouz PJ Father absence and familial antisocial characteristics Journal of Abnormal Child Psychology 2001 29 5 357 367 11695539
  41. [45]Wilens TE The nature of the relationship between Attention-Deficit/Hyperactivity Disorder and substance use J Clin Psychiatry 2007 68 supp 11 4 8 18307375
  42. [46]Ridenour TA Meyer-Chilenski S Reid EE Developmental momentum toward substance dependence: Natural histories and pliability of risk factors in youth experiencing chronic stress Drug Alcohol Depend 2012 123 S87 S98 22257754 PMC3342426
  43. [49]Green JG McLaughlin KA Berglund PA Gruber MJ Sampson NA Zaslavsky AM Childhood adversities and adult psychiatric disorders in the national comorbidity survey replication I: associations with first onset of DSM-IV disorders Arch Gen Psychiatry 2010 67 2 113 123 20124111 PMC2822662
  44. [50]Nunes E Levin FR Treatment of depression in patients with alcohol or other drug dependence: a meta-analysis JAMA 2004 291 1887–1896 15100209
  45. [51]Hatzenbuehler ML Keyes KM Narrow WE Grant BF Hasin DS Racial/ethnic disparities in service utilization for individuals with co-occurring mental health and substance use disorders in the general population J Clin Psychiatry 2008 69 7 1112 1121 18517286 PMC2745048
  46. [52]Watkins KE Kung FY Paddock S A national survey of care for persons with co-occurring mental and substance use disorders Psychiat Serv 2001 52 1062 1068 11474052
  47. [53]Blanco C Myers J Kendler KS Gambling, disordered gambling and their association with major depression and substance use: a web-based cohort and twin-sibling study Psychol Med 2012 42 497 508 21835089 PMC4431979

Cited by

Sorted by citations

Authors
Blanco, C., Rafful, C., Wall, M. M., Ridenour, T. A., Wang, S., & Kendler, K. S.
Affiliations
  • New York State Psychiatric Institute (US)
  • University of Pittsburgh (US)
  • Virginia Commonwealth University (US)
Corresponding author
Blanco, Carlos
ORCID
Venue
Addiction
Publisher
Wiley
Published
2013-11-21
Volume
109
Issue
2
Pages
284-294
ISSN
  • 0965-2140 (ISSN-L)
  • 1360-0443
DOI
10.1111/add.12382
PMC
PMC3956073
OpenAlex
W1547499636
Cited by
114
References
5
Citations by year
2026: 4 · 2025: 4 · 2024: 8 · 2023: 3 · 2022: 3 · 2021: 4 · 2020: 50 · 2019: 6 · 2018: 11 · 2017: 5 · 2016: 4 · 2015: 8 · 2014: 4
FWCI
3.89
Type
journal article
Language
en
Open access
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
  • Addiction (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institutes of Health
  • National Institute on Drug Abuse (DA019606, R01DA023973, P50DA005605, DA023200, R01DA019606, DA023973, K02DA023200)
Topics
  • Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
  • Health Sciences › Medicine › Pharmacology › Cannabis and Cannabinoid Research
  • Social Sciences › Psychology › Clinical Psychology › Gambling Behavior and Treatments
Keywords
cannabis use disorder, risk factors, developmental model, lifetime cannabis use, alcoholism, life events, impulsivity, social deviance, religious service attendance, Axis I disorders, gender differences, mediation, NESARC, adolescence, adulthood, childhood
MeSH terms
Adolescent, Adult, Aged, Marijuana Abuse, Humans, Human Development, Life Change Events, Middle Aged, Models, Psychological, Religion, Risk Factors, United States, Risk Assessment, Alcohol-Related Disorders, Young Adult

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