OBJECTIVE: The aim of this study was to understand the variation in response to alcohol use by identifying classes of alcohol users based on alcohol-dependence symptoms and to compare these classes across demographic characteristics, abuse symptoms, and treatment usage. METHOD: Data from combined 2002-2005 National Survey on Drug Use and Health identified 110,742 past-year alcohol users, age 18 years or older. Latent class analysis defined classes based on observed clustering of alcohol-dependence symptoms based on criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV). Chi-square statistics were used to test differences in sociodemographic and alcohol-abuse characteristics across classes. Multivariable latent class regressions were used to compare treatment usage across classes. RESULTS: The four-class model had the best overall fit and identified classes that differed quantitatively and qualitatively, with 2.3% of the users in the most-severe class and 83.8% in the least-severe/ not-affected class. These classes differed in a number of demographic characteristics and alcohol-abuse symptoms. All individuals in the most severe class met DSM-IV criteria for alcohol dependence; 80% of this class had alcohol-abuse symptoms. Twenty-six percent of the moderate and 50% of the moderate-high class met dependence criteria. Approximately 19% of the most-severe class and less than 5% of the moderate and moderate-high class received treatment for alcohol in the past year. CONCLUSIONS: This study demonstrates that meeting dependence criteria only partially captures variations in responses to severity of alcohol problems. Although individuals in the most-severe class were more likely to perceive need and receive treatment, the percentage of individuals receiving treatment was low.
OBJECTIVE: The aim of this study was to understand the variation in response to alcohol use by identifying classes of alcohol users based on alcohol-dependence symptoms and to compare these classes across demographic characteristics, abuse symptoms, and treatment usage. METHOD: Data from combined 2002-2005 National Survey on Drug Use and Health identified 110,742 past-year alcohol users, age 18 years or older. Latent class analysis defined classes based on observed clustering of alcohol-dependence symptoms based on criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV). Chi-square statistics were used to test differences in sociodemographic and alcohol-abuse characteristics across classes. Multivariable latent class regressions were used to compare treatment usage across classes. RESULTS: The four-class model had the best overall fit and identified classes that differed quantitatively and qualitatively, with 2.3% of the users in the most-severe class and 83.8% in the least-severe/ not-affected class. These classes differed in a number of demographic characteristics and alcohol-abuse symptoms. All individuals in the most severe class met DSM-IV criteria for alcohol dependence; 80% of this class had alcohol-abuse symptoms. Twenty-six percent of the moderate and 50% of the moderate-high class met dependence criteria. Approximately 19% of the most-severe class and less than 5% of the moderate and moderate-high class received treatment for alcohol in the past year. CONCLUSIONS: This study demonstrates that meeting dependence criteria only partially captures variations in responses to severity of alcohol problems. Although individuals in the most-severe class were more likely to perceive need and receive treatment, the percentage of individuals receiving treatment was low.
Authors: K K Bucholz; A C Heath; T Reich; V M Hesselbrock; J R Kramer; J I Nurnberger; M A Schuckit Journal: Alcohol Clin Exp Res Date: 1996-11 Impact factor: 3.455
Authors: Leah Wetherill; Manav Kapoor; Arpana Agrawal; Kathleen Bucholz; Daniel Koller; Sarah E Bertelsen; Nhung Le; Jen-Chyong Wang; Laura Almasy; Victor Hesselbrock; John Kramer; John I Nurnberger; Marc Schuckit; Jay A Tischfield; Xiaoling Xuei; Bernice Porjesz; Howard J Edenberg; Alison M Goate; Tatiana Foroud Journal: Alcohol Clin Exp Res Date: 2013-09-09 Impact factor: 3.455
Authors: João Mauricio Castaldelli-Maia; Camila M Silveira; Erica R Siu; Yuan-Pang Wang; Igor A Milhorança; Clóvis Alexandrino-Silva; Guilherme Borges; Maria C Viana; Arthur G Andrade; Laura H Andrade; Silvia S Martins Journal: Drug Alcohol Depend Date: 2014-01-03 Impact factor: 4.492
Authors: Lareina N La Flair; Catherine P Bradshaw; Carla L Storr; Kerry M Green; Anika A H Alvanzo; Rosa M Crum Journal: J Stud Alcohol Drugs Date: 2012-05 Impact factor: 2.582
Authors: Lareina N La Flair; Beth A Reboussin; Carla L Storr; Elizabeth Letourneau; Kerry M Green; Ramin Mojtabai; Lauren R Pacek; Anika A H Alvanzo; Bernadette Cullen; Rosa M Crum Journal: Drug Alcohol Depend Date: 2013-04-29 Impact factor: 4.492