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Predicting persistent alcohol problems: a prospective analysis from the Great Smoky Mountain Study

Published online by Cambridge University Press:  13 December 2011

W. E. Copeland*
Affiliation:
Duke University Medical Center, Durham, NC, USA
A. Angold
Affiliation:
Duke University Medical Center, Durham, NC, USA
L. Shanahan
Affiliation:
University of North Carolina, Greensboro, NC, USA
J. Dreyfuss
Affiliation:
North Carolina State University, Raleigh, NC, USA
I. Dlamini
Affiliation:
Regeneron Pharmaceuticals, Tarrytown, NY, USA
E. J. Costello
Affiliation:
Duke University Medical Center, Durham, NC, USA
*
*Address for correspondence: W. E. Copeland, Ph.D., Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Box 3454, Durham NC 27710, USA. (Email: [email protected])

Abstract

Background

Rates of alcohol disorders peak in late adolescence and decrease substantially into the mid-20s. Our aim was to identify risk factors that predict alcohol problems that persist into the mid-20s.

Method

Data are from the prospective, population-based Great Smoky Mountains Study (GSMS; n=1420), which followed children through late adolescence and into young adulthood. Alcohol persisters were defined as subjects with an alcohol disorder (abuse or dependence) in late adolescence (ages 19 and 21 years) that continued to meet criteria for an alcohol disorder at the mid-20s assessment.

Results

The 3-month prevalence of having an alcohol disorder (abuse or dependence) decreased markedly from late adolescence into the mid-20s. A third of late adolescents with an alcohol disorder continued to meet criteria for an alcohol disorder in young adulthood (37 of 144 who met criteria in late adolescence). Risk factors for persister status included multiple alcohol abuse criteria during late adolescence but no alcohol dependence criteria. Risk factors for persister status also included associated features of alcohol dependence such as craving alcohol and drinking to unconsciousness. Persister status was also associated with depression, cannabis dependence and illicit substance use, but not with other psychiatric disorders. More than 90% of late adolescents with three or more of the risk factors identified met criteria for a young adult alcohol disorder.

Conclusions

Symptoms of alcohol abuse, not dependence, best predict long-term persistence of alcohol problems. The set of risk factors identified may be a useful screen for selective and indicated prevention efforts.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2011

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References

Angold, A, Costello, EJ (1995). A test-retest reliability study of child-reported psychiatric symptoms and diagnoses using the Child and Adolescent Psychiatric Assessment (CAPA-C). Psychological Medicine 25, 755762.CrossRefGoogle ScholarPubMed
Angold, A, Costello, EJ (2000). The Child and Adolescent Psychiatric Assessment (CAPA). Journal of the American Academy of Child and Adolescent Psychiatry 39, 3948.CrossRefGoogle ScholarPubMed
Angold, A, Cox, A, Prendergast, M, Rutter, M, Simonoff, E, Costello, EJ, Ascher, BH (1999). The Young Adult Psychiatric Assessment (YAPA). Duke University Medical Center: Durham, NC.Google Scholar
Ascher, BH, Farmer, EMZ, Burns, BJ, Angold, A (1996). The Child and Adolescent Services Assessment (CASA): description and psychometrics. Journal of Emotional and Behavioral Disorders 4, 1220.CrossRefGoogle Scholar
Babor, TF, Hofmann, M, Delboca, FK, Hesselbrock, V, Meyer, RE, Dolinsky, ZS, Rounsaville, B (1992). Types of alcoholics, I: Evidence of an empirically derived typology based on indicators of vulnerability and severity. Archives of General Psychiatry 49, 599608.CrossRefGoogle ScholarPubMed
Bachman, JG, O'Malley, PM, Sscheulenberg, JE, Johnston, LD, Bryant, AL, Merline, AC (2002). The Decline of Substance Use in Young Adulthood: Changes in Social Activities, Roles and Beliefs. Erlbaum: Mahwah, NJ.Google Scholar
Casey, BJ, Giedd, JN, Thomas, KM (2000). Structural and functional brain development and its relation to cognitive development. Biological Psychology 5, 241257.CrossRefGoogle Scholar
Chen, K, Kandel, DB (1995). The natural history of drug use from adolescence to the mid-thirties in a general population sample. American Journal of Public Health 85, 4147.CrossRefGoogle Scholar
Chen, K, Kandel, DB (1998). Predictors of cessation of marijuana use: an event history analysis. Drug and Alcohol Dependence 50, 109121.CrossRefGoogle ScholarPubMed
Cloninger, CR (1988). Etiologic factors in substance abuse: an adoption study perspective. NIDA Research Monograph 89, 5272.Google ScholarPubMed
Costello, EJ, Angold, A, Burns, B, Stangl, D, Tweed, D, Erkanli, A, Worthman, C (1996). The Great Smoky Mountains Study of Youth: goals, designs, methods, and the prevalence of DSM-III-R disorders. Archives of General Psychiatry 53, 11291136.CrossRefGoogle ScholarPubMed
Costello, EJ, Copeland, W, Cowell, A, Keeler, G (2007). Service costs of caring for adolescents with mental illness in a rural community, 1993–2000. American Journal of Psychiatry 164, 3642.CrossRefGoogle Scholar
Costello, EJ, Mustillo, S, Erkanli, A, Keeler, G, Angold, A (2003). Prevalence and development of psychiatric disorders in childhood and adolescence. Archives of General Psychiatry 60, 837844.CrossRefGoogle ScholarPubMed
Dawson, DA, Goldstein, RB, Grant, BF (2007). Rates and correlates of relapse among individuals in remission from DSM-IV alcohol dependence: a 3-year follow-up. Alcoholism: Clinical and Experimental Research 31, 20362045.CrossRefGoogle ScholarPubMed
Dawson, DA, Grant, BF, Stinson, FS, Zhou, Y (2005). Effectiveness of the derived Alcohol Use Disorders Identification Test (AUDIT-C) in screening for alcohol use disorders and risk drinking in the US general population. Alcoholism: Clinical and Experimental Research 29, 844854.CrossRefGoogle ScholarPubMed
De Bruijn, C, van den Brink, W, De Graaf, R, Vollebergh, WAM (2006). The three year course of alcohol use disorders in the general population: DSM-IV, ICD-10 and the Craving Withdrawal Model. Addiction 101, 385392.CrossRefGoogle ScholarPubMed
Delucchi, KL, Matzger, H, Weisner, C (2008). Alcohol in emerging adulthood: 7-year study of problem and dependent drinkers. Addictive Behaviors 33, 134142.CrossRefGoogle ScholarPubMed
Farrington, DP (1983). Offending from 10 to 25 years of age. In Prospective Studies of Crime and Delinquency (ed. Vandusen, K. T. and Mednick, S. A.), pp. 1738. Kluwer-Nijhoff: Boston, MA.CrossRefGoogle Scholar
Grant, BF, Dawson, DA, Stinson, FS, Chou, SP, Dufouf, MC, Pickering, RP (2004). The 12-month prevalence and trends in DSM-IV alcohol abuse and dependence: United States, 1991–1992 and 2001–2002. Drug and Alcohol Dependence 74, 223234.CrossRefGoogle ScholarPubMed
Grant, BF, Stinson, FS, Harford, T (2001). The 5-year course of alcohol abuse among young adults. Journal of Substance Abuse 13, 229238.CrossRefGoogle ScholarPubMed
Guo, J, Collins, LM, Hill, KG, Hawkins, JD (2000). Developmental pathways to alcohol abuse and dependence in young adulthood. Journal of Studies on Alcohol 61, 799808.CrossRefGoogle ScholarPubMed
Harford, TC, Grant, BF, Yi, HY, Chen, CM (2005). Patterns of DSM-IV alcohol abuse and dependence criteria among adolescents and adults: results from the 2001 National Household Survey on Drug Abuse. Alcoholism, Clinical and Experimental Research 29, 810828.CrossRefGoogle ScholarPubMed
Harrington, DM, McBride, RS (1970). Traffic violations by type, age, sex, and marital status. Accident Analysis and Prevention 2, 6779.CrossRefGoogle Scholar
Hasin, D, Grant, B, Endicott, J (1990). The natural history of alcohol abuse: implications for definitions of alcohol use disorders. American Journal of Psychiatry 147, 15371541.Google ScholarPubMed
Hasin, DS, Stinson, FS, Ogburn, E, Grant, BF (2007). Prevalence, correlates, disability, and comorbidity of DSM-IV alcohol abuse and dependence in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Archives of General Psychiatry 64, 830842.CrossRefGoogle ScholarPubMed
Hasin, DS, Van Rossem, R, McCloud, S, Endicott, J (1997). Differentiating DSM-IV alcohol dependence and abuse by course: community heavy drinkers. Journal of Substance Abuse 9, 127135.CrossRefGoogle ScholarPubMed
Hawkins, JD, Catalano, RF, Miller, JY (1992). Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: implications for substance abuse prevention. Psychological Bulletin 112, 64–105.CrossRefGoogle ScholarPubMed
Jackson, KM, O'Neill, SE, Sher, KJ (2006). Characterizing alcohol dependence: transitions during young and middle adulthood. Experimental and Clinical Psychopharmacology 14, 228244.CrossRefGoogle ScholarPubMed
Kandel, DB, Raveis, VH (1989). Cessation of illicit drug use in young adulthood. Archives of General Psychiatry 46, 109116.CrossRefGoogle ScholarPubMed
Kaplow, JB, Curran, PJ, Angold, A, Costello, EJ (2001). The prospective relation between dimensions of anxiety and the initiation of adolescent alcohol use. Journal of Clinical Child Psychology 30, 316326.CrossRefGoogle ScholarPubMed
Kosterman, R, Hawkins, J, Guo, J, Catalano, R, Abbott, R (2000). The dynamics of alcohol and marijuana initiation: patterns and predictors of first use in adolescence. American Journal of Public Health 90, 360366.Google ScholarPubMed
Kraemer, HC (1992). Evaluating Medical Tests: Objective and Quantitative Guidelines. Sage Publications: Thousand Oaks, CA.Google Scholar
Littlefield, A, Sher, K, Wood, P (2009). Is ‘maturing out’ of problematic alcohol involvement related to personality change? Journal of Abnormal Psychology 118, 360374.CrossRefGoogle ScholarPubMed
Littlefield, AK, Sher, KJ, Wood, PK (2010). A personality-based description of maturing out of alcohol problems: extension with a five-factor model and robustness to modeling challenges. Addictive Behaviors 35, 948954.CrossRefGoogle ScholarPubMed
Maggs, JL, Schulenberg, JE (2004/2005). Trajectories of alcohol use during the transition to adulthood. Alcohol Research and Health 28, 195201.Google Scholar
Martin, A, Srihari, V (2006). Geometrically evident: framing studies using the Graphic Appraisal Tool for Epidemiology (GATE). Journal of the American Academy of Child and Adolescent Psychiatry 45, 15211526.CrossRefGoogle ScholarPubMed
Nakao, K, Treas, J (1992). The 1989 Socioeconomic Index of Occupations: Construction from the 1989 Occupational Prestige Scores. GSS Methodological Report No. 74. National Opinion Research Center: Chicago, IL.Google Scholar
Pagan, JL, Rose, RJ, Viken, RJ, Pulkkinen, L, Kaprio, J, Dick, DM (2006). Genetic and environmental influences on stages of alcohol use across adolescence and into young adulthood. Behavior Genetics 36, 483497.CrossRefGoogle ScholarPubMed
Pirkola, SP, Poikolainen, K, Lonnqvist, JK (2006). Currently active and remitted alcohol dependence in a nationwide adult general population – results from the Finnish Health 2000 study. Alcohol and Alcoholism 41, 315320.CrossRefGoogle Scholar
Rumpf, HJ, Bischof, G, Hapke, U, Meyer, C, John, U (2000). Studies on natural recovery from alcohol dependence: sample selection bias by media solicitation? Addiction 95, 765775.CrossRefGoogle ScholarPubMed
Saha, TD, Chou, SP, Grant, BF (2006). Toward an alcohol use disorder continuum using item response theory: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Psychological Medicine 36, 931941.CrossRefGoogle ScholarPubMed
Sampson, R, Laub, J (2003). Life-course desisters? Trajectories of crime among delinquent boys followed to age 70. Criminology 41, 555592.CrossRefGoogle Scholar
Schuckit, MA, Smith, TL, Landi, NA (2000). The 5-year clinical course of high-functioning men with DSM-IV alcohol abuse or dependence. American Journal of Psychiatry 157, 20282035.CrossRefGoogle ScholarPubMed
Smart, R (2007). Natural recovery or recovery without treatment from alcohol and drug problems as seen from survey data. In Promoting Self-Change from Addictive Behaviors (ed. Klingemann, H. and Sobell, L. C.), pp. 5972. Springer: New York.CrossRefGoogle Scholar
Staff, J, Schulenberg, JE, Maslowsky, J, Bachman, JG, O'Malley, PM, Maggs, JL, Johnston, LD (2010). Substance use changes and social role transitions: proximal developmental effects on ongoing trajectories from late adolescence through early adulthood. Development and Psychopathology 22, 917932.CrossRefGoogle ScholarPubMed
Tarter, RE (2002). Etiology of adolescent substance abuse: a developmental perspective. American Journal on Addictions 11, 171191.CrossRefGoogle ScholarPubMed
Thompson, PM, Giedd, JN, Woods, RP, Macdonald, D, Evans, AC, Toga, AW (2000). Growth patterns in the developing brain detected by using continuum mechanical tensor maps. Nature 404, 190193.CrossRefGoogle ScholarPubMed
Webb, JA, Baer, PE, McLaughlin, RJ, McKelvey, RS, Caid, CD (1991). Risk factors and their relation to initiation of alcohol use among early adolescents. Journal of the American Academy of Child and Adolescent Psychiatry 30, 563568.CrossRefGoogle ScholarPubMed
Yamaguchi, K, Kandel, DB (1985). On the resolution of role incompatibility: a life event history analysis of family roles and marijuana use. American Journal of Sociology 90, 12841325.CrossRefGoogle Scholar
Zucker, RA (2008). Anticipating problem alcohol use developmentally from childhood into middle adulthood: what have we learned? Addiction 103, 100108.CrossRefGoogle ScholarPubMed
Zucker, RA, Fitzgerald, HE, Moses, HD (1995). Emergence of alcohol problems and the several alcoholisms: a developmental perspective on etiologic theory and life course trajectory. In Developmental Psychopathology. Volume 2. Risk, Disorder, and Adaptation (ed. Cicchetti, D. and Cohen, D. J.), pp. 677711. John Wiley & Sons, Inc.: New York, NY.Google Scholar