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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)
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Background This study aims to estimate general and racial-ethnic specific cumulative probability of developing dependence among nicotine, alcohol, cannabis or cocaine users, and to identify predictors of transition to substance dependence. Methods Analyses were done for the subsample of lifetime nicotine (n=15,918), alcohol (n=28,907), cannabis (n=7,389) or cocaine (n=2,259) users who participated in the first and second wave of the National Epidemiological Survey on Alcohol and Related Conditions (NESARC). Discrete-time survival analyses were implemented to estimate the cumulative probability of transitioning from use to dependence and to identify predictors of transition to dependence. Results The cumulative probability estimate of transition to dependence was 67.5% for nicotine users, 22.7% for alcohol users, 20.9% for cocaine users, and 8.9% for cannabis users. Half of the cases of dependence on nicotine, alcohol, cannabis and cocaine were observed approximately 27, 13, 5 and 4 years after use onset, respectively. Significant racial-ethnic differences were observed in the probability of transition to dependence across the four substances. Several predictors of dependence were common across the four substances assessed. Conclusions Transition from use to dependence was highest for nicotine users, followed by cocaine, alcohol and cannabis users. Transition to cannabis or cocaine dependence occurred faster than transition to nicotine or alcohol dependence. The existence of common predictors of transition dependence across substances suggests that shared mechanisms are involved. The increased risk of transition to dependence among individuals from minorities or those with psychiatric or dependence comorbidity highlights the importance of promoting outreach and treatment of these populations.
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Cites
Kessler, R. C. (1997) · Archives of General Psychiatry · doi:10.1001/archpsyc.1997.01830160031005 · Cited by 2,085
Kendler, K. S., Prescott, C. A., Myers, J., & Neale, M. C. (2003) · Archives of General Psychiatry · doi:10.1001/archpsyc.60.9.929 · Cited by 1,868
Kessler, R. C., Nelson, C. B., McGonagle, K. A., Edlund, M. J., Frank, R. G., & Leaf, P. J. (1996) · American Journal of Orthopsychiatry · doi:10.1037/h0080151 · Cited by 1,378 · cited 2×
“Psychiatric comorbidity predicted transition to dependence, as previously reported (Breslau et al., 2004; Glantz et al., 2008; Kessler, 2004; Kessler et al., 1996; Zimmermann et al., 2003).”
MethodWagner, F. (2002) · Neuropsychopharmacology · doi:10.1016/s0893-133x(01)00367-0 · Cited by 739
Grant, B. F., Hasin, D. S., Stinson, F. S., Dawson, D. A., Chou, S. P., Ruan, W. J., & Pickering, R. P. (2004) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.v65n0711 · Cited by 724
Self-citationGrant, B. F., Stinson, F. S., Dawson, D. A., Chou, S. P., Ruan, W. J., & Pickering, R. P. (2004) · Archives of General Psychiatry · doi:10.1001/archpsyc.61.4.361 · Cited by 644
Self-citationGrant, B. F., Hasin, D. S., Blanco, C., Stinson, F. S., Chou, S. P., Goldstein, R. B., Dawson, D. A., Smith, S., Saha, T. D., & Huang, B. (2005) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.v66n1102 · Cited by 601
Self-citationThe epidemiology of dual diagnosis
Kessler, R. C. (2004) · Biological Psychiatry · doi:10.1016/j.biopsych.2004.06.034 · Cited by 588 · cited 1×
“N IH -PA Author M anuscript N IH -PA Author M anuscript N IH -PA Author M anuscript Psychiatric comorbidity predicted transition to dependence, as previously reported (Breslau et al., 2004; Glantz et al., 2008; Kessler, 2004; Kessler et al., 1996; Zimmermann et al., 2003).”
MethodRuan, W. J., Goldstein, R. B., Chou, S. P., Smith, S. M., Saha, T. D., Pickering, R. P., Dawson, D. A., Huang, B., Stinson, F. S., & Grant, B. F. (2008) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2007.06.001 · Cited by 557
Self-citationGrant, B. F., Stinson, F. S., Hasin, D. S., Dawson, D. A., Chou, S. P., Ruan, W. J., & Huang, B. (2005) · The Journal of Clinical Psychiatry · doi:10.4088/jcp.v66n1001 · Cited by 479 · cited 1×
“AUDADIS-IV methods to diagnose these disorders are described in detail elsewhere (Grant et al., 2005a; Grant et al., 2005b; Grant et al., 2005c; Hasin et al., 2005a; Stinson et al., 2007).”
MethodSelf-citation
Cited by
Adverse health effects of marijuana use.
Volkow, N. D., Baler, R. D., Compton, W. M., & Weiss, S. R. B. (2014) · New England Journal of Medicine · doi:10.1056/nejmra1402309 · Cited by 2,774
Sex and gender differences in substance use disorders
McHugh, R. K., Votaw, V. R., Sugarman, D. E., & Greenfield, S. F. (2018) · Clinical Psychology Review · doi:10.1016/j.cpr.2017.10.012 · Cited by 1,076
The pharmacokinetics and the pharmacodynamics of cannabinoids
Lucas, C. J., Galettis, P., & Schneider, J. (2018) · British Journal of Clinical Pharmacology · doi:10.1111/bcp.13710 · Cited by 724
Compton, W. M., Han, B., Jones, C. M., Blanco, C., & Hughes, A. (2016) · The Lancet Psychiatry · doi:10.1016/s2215-0366(16)30208-5 · Cited by 377
Self-citationLeung, J., Chan, G. C. K., Hides, L., & Hall, W. D. (2020) · Addictive Behaviors · doi:10.1016/j.addbeh.2020.106479 · Cited by 358
Time to connect: bringing social context into addiction neuroscience
Heilig, M., Epstein, D. H., Nader, M. A., & Shaham, Y. (2016) · Nature Reviews Neuroscience · doi:10.1038/nrn.2016.67 · Cited by 298
Khan, S. S., Secades-Villa, R., Okuda, M., Wang, S., Pérez-Fuentes, G., Kerridge, B. T., & Blanco, C. (2013) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2012.10.015 · Cited by 293
Self-citationA multistep general theory of transition to addiction
Piazza, P. V., & Deroche-Gamonet, V. (2013) · Psychopharmacology · doi:10.1007/s00213-013-3224-4 · Cited by 227
Onaemo, V. N., Fawehinmi, T. O., & D'Arcy, C. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.12.043 · Cited by 152
Burggren, A. C., Shirazi, A., Ginder, N., & London, E. D. (2019) · The American Journal of Drug and Alcohol Abuse · doi:10.1080/00952990.2019.1634086 · Cited by 144
Gonzalez, R., Schuster, R. M., Mermelstein, R. J., Vassileva, J., Martin, E. M., & Diviak, K. R. (2012) · Journal of Clinical and Experimental Neuropsychology · doi:10.1080/13803395.2012.703642 · Cited by 137
Spanagel, R. (2020) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2020.22.3/rspanagel · Cited by 127
Marel, C., Sunderland, M., Mills, K. L., Slade, T., Teesson, M., & Chapman, C. (2019) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2018.10.010 · Cited by 114
Towards a comprehensive developmental model of cannabis use disorders
Blanco, C., Rafful, C., Wall, M. M., Ridenour, T. A., Wang, S., & Kendler, K. S. (2014) · Addiction · doi:10.1111/add.12382 · Cited by 114
Self-citationStress modulates illness-course of substance use disorders: a translational review
Lijffijt, M., Hu, K., & Swann, A. C. (2014) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2014.00083 · Cited by 103
Otten, R., Mun, C. J., Shaw, D. S., Wilson, M. N., & Dishion, T. J. (2019) · Addiction · doi:10.1111/add.14452 · Cited by 69
Lichenstein, S. D., Manco, N., Cope, L. M., Egbo, L., Garrison, K. A., Hardee, J., Hillmer, A. T., Reeder, K., Stern, E. F., Worhunsky, P., et al. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-021-01226-9 · Cited by 63
Aligning the ICD-11 classification of disorders due to substance use with global service needs
Poznyak, V., Reed, G. M., & Medina-Mora, M. E. (2018) · Epidemiology and Psychiatric Sciences · doi:10.1017/s2045796017000622 · Cited by 62
Blanco, C., Flórez‐Salamanca, L., Secades‐Villa, R., Wang, S., & Hasin, D. S. (2018) · The American Journal on Addictions · doi:10.1111/ajad.12764 · Cited by 61
Self-citationBlanco, C., Iza, M., Schwartz, R. P., Rafful, C., Wang, S., & Olfson, M. (2013) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2012.12.013 · Cited by 61
Self-citationTowards a comprehensive developmental model of pathological gambling
Blanco, C., Hanania, J., Petry, N. M., Wall, M. M., Wang, S., Jin, C. J., & Kendler, K. S. (2015) · Addiction · doi:10.1111/add.12946 · Cited by 57
Self-citationBlanco, C., Okuda, M., Wang, S., Liu, S.-M., & Olfson, M. (2014) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2014.1206 · Cited by 49
Self-citationAlcohol, cannabis, and other drug use: Engagement and outcome in PTSD treatment
Bedard-Gilligan, M., Garcia, N., Zoellner, L. A., & Feeny, N. C. (2018) · Psychology of Addictive Behaviors · doi:10.1037/adb0000355 · Cited by 48
Prevalence & correlates of tobacco use among adolescents in Kerala, India
Jaisoorya, T. S., Beena, K. V., Beena, M., Jose, D. C., Ellangovan, K., Thennarasu, K., & Benegal, V. (2016) · Indian Journal of Medical Research · doi:10.4103/ijmr.ijmr_1873_14 · Cited by 47
Blanco, C., Rafful, C., Wall, M. M., Jin, C. J., Kerridge, B., & Schwartz, R. P. (2013) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2013.07.011 · Cited by 40
Self-citationToward a comprehensive developmental model of smoking initiation and nicotine dependence
García-Rodríguez, O., Blanco, C., Wall, M. M., Wang, S., Jin, C. J., & Kendler, K. S. (2014) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2014.09.002 · Cited by 28
Self-citationBaek, J. H., Cha, B., Moon, E., Ha, T. H., Chang, J. S., Kim, J. H., Choi, J. E., Kang, B. J., Hong, K. S., & Ha, K. (2014) · Journal of Affective Disorders · doi:10.1016/j.jad.2014.05.027 · Cited by 19
The metabotropic glutamate receptor 5 as a biomarker for psychiatric disorders
(2023) · International Review of Neurobiology · doi:10.1016/bs.irn.2022.10.007 · Cited by 8
Lourmière, G., Lacroix, A., Girard, M., & Nubukpo, P. (2022) · American Journal of Clinical Hypnosis · doi:10.1080/00029157.2021.1877105 · Cited by 2
Metadata
- Authors
- Lopez-Quintero, C., Cobos, J. P. D. L., Hasin, D. S., Okuda, M., Wang, S., Grant, B. F., & Blanco, C.
- Venue
- Drug and Alcohol Dependence
- Publisher
- Elsevier BV
- Published
- 2011-05
- Volume
- 115
- Issue
- 1-2
- Pages
- 120-130
- ISSN
- 0376-8716 (ISSN-L)
- OpenAlex
- W2079140185
- Cited by
- 704
- References
- 19
- FWCI
- 8.18
- Type
- journal article
- Language
- en
- Open access
- green
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