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. 2012 Sep;42(9):1925-35.
doi: 10.1017/S0033291711002790. Epub 2011 Dec 13.

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

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

W E Copeland et al. Psychol Med. 2012 Sep.

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.

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Conflict of interest statement

No other authors have any biomedical financial interests.

Figures

Figure 1
Figure 1
Three-month prevalence rates for a) alcohol abuse or dependence and b) at least weekly alcohol use. Assessment schedule and participation rates are available from table 1.
Figure 1
Figure 1
Three-month prevalence rates for a) alcohol abuse or dependence and b) at least weekly alcohol use. Assessment schedule and participation rates are available from table 1.
Figure 2
Figure 2
Comparison of males and females rates of persistence and desistance for protective factors. Graphs compare rates for (a) 2 or more years of post-secondary education, (b) marriage, and (c) parenthood. All interaction terms were statistically significant (post-secondary education: p=0.03; marriage: not able to be estimated due to no cases of persistence in married females; parenthood: p=0.04). Post-secondary education was protective for males (OR=0.2, 95%CI 0.0, 0.9; p=0.05) but not for females (OR=3.6, 95%CI 0.5, 27.1; p=0.20). Marriage increase risk for persistence in males (OR=12.3, 95%CI 2.1, 71.5; p=0.005) but was protective in female (odds ratio could not be estimated as no female persisters were married). Despite a significant interaction term, parenthood was not associated with persister/desister status for females (OR=0.2, 95%CI 0.0, 1.4; p=.09) or males (OR=2.7, 95%CI 0.5, 15.5; p=.25). * Indicates significant group difference.
Figure 2
Figure 2
Comparison of males and females rates of persistence and desistance for protective factors. Graphs compare rates for (a) 2 or more years of post-secondary education, (b) marriage, and (c) parenthood. All interaction terms were statistically significant (post-secondary education: p=0.03; marriage: not able to be estimated due to no cases of persistence in married females; parenthood: p=0.04). Post-secondary education was protective for males (OR=0.2, 95%CI 0.0, 0.9; p=0.05) but not for females (OR=3.6, 95%CI 0.5, 27.1; p=0.20). Marriage increase risk for persistence in males (OR=12.3, 95%CI 2.1, 71.5; p=0.005) but was protective in female (odds ratio could not be estimated as no female persisters were married). Despite a significant interaction term, parenthood was not associated with persister/desister status for females (OR=0.2, 95%CI 0.0, 1.4; p=.09) or males (OR=2.7, 95%CI 0.5, 15.5; p=.25). * Indicates significant group difference.
Figure 2
Figure 2
Comparison of males and females rates of persistence and desistance for protective factors. Graphs compare rates for (a) 2 or more years of post-secondary education, (b) marriage, and (c) parenthood. All interaction terms were statistically significant (post-secondary education: p=0.03; marriage: not able to be estimated due to no cases of persistence in married females; parenthood: p=0.04). Post-secondary education was protective for males (OR=0.2, 95%CI 0.0, 0.9; p=0.05) but not for females (OR=3.6, 95%CI 0.5, 27.1; p=0.20). Marriage increase risk for persistence in males (OR=12.3, 95%CI 2.1, 71.5; p=0.005) but was protective in female (odds ratio could not be estimated as no female persisters were married). Despite a significant interaction term, parenthood was not associated with persister/desister status for females (OR=0.2, 95%CI 0.0, 1.4; p=.09) or males (OR=2.7, 95%CI 0.5, 15.5; p=.25). * Indicates significant group difference.
Figure 3
Figure 3
Association between cumulative scale of late adolescent risk factors and 3-month mid 20s alcohol disorder rates. Controlling for sex and race/ethnicity, the number of late adolescent risk factors significantly predicted young adult persistence status (OR=8.4, 95%CI 4.5, 15.7; p<.0001).

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