E C Long1, H Ohlsson2, J Sundquist2,3, K Sundquist2,3, K S Kendler4,5,6. 1. Edna Bennett Pierce Prevention Research Center, Pennsylvania State University, 314 Biobehavioral Health Building, University Park, PA 16802, USA. 2. Center for Primary Health Care Research, Clinical Research Center, Lund University, Box 50332, 202 13 Malmö, Sweden. 3. Department of Family Medicine and Community Health, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl., New York, NY 10029, USA. 4. Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 800 E. Leigh St., Biotech One, Suite 100, Richmond, VA 23219, USA. 5. Department of Psychiatry, Virginia Commonwealth University, 1200 East Broad St., P.O. Box 980710, Richmond, VA 23298, USA. 6. Department of Human and Molecular Genetics, Virginia Commonwealth University, 1101 East Marshall St., Box 980033, Richmond, VA 23298, USA.
Abstract
AIMS: The aims of the present study are to identify alcohol use disorder (AUD) classes among a population-based Swedish sample, determine if these classes differ by variables known to be associated with AUD and determine whether some AUD classes have stronger genetic influences than others. METHODS: A latent class analysis (LCA), based on types of registrations, was conducted on Swedish individuals with an AUD registration born between 1960 and 1990 (N = 184,770). These classes were then validated using demographics; patterns of comorbidity with drug abuse, psychiatric disorders and criminal behavior; and neighborhood-level factors, i.e. peer AUD and neighborhood deprivation. The degree of genetic and environmental influence was also investigated. RESULTS: The best-fit LCA had four classes: (a) outpatient/prescription, characterized by a mix of outpatient medical and prescription registrations, (b) low-frequency inpatient, characterized entirely by inpatient medical registrations, with the majority of individuals having one AUD registration, (c) high-frequency mixed, characterized by a mix of all four registration types, with the majority having four or more registrations and (d) crime, characterized almost entirely by criminal registrations. The highest heritability for both males and females was found for Class 3 (61% and 65%, respectively) and the lowest for Class 1 (20% for both), with shared environmental influences accounting for 10% or less of the variance in all Classes. CONCLUSIONS: Using comprehensive, nationwide registry data, we showed evidence for four distinct, meaningful classes of AUD with varying degrees of heritability.
AIMS: The aims of the present study are to identify alcohol use disorder (AUD) classes among a population-based Swedish sample, determine if these classes differ by variables known to be associated with AUD and determine whether some AUD classes have stronger genetic influences than others. METHODS: A latent class analysis (LCA), based on types of registrations, was conducted on Swedish individuals with an AUD registration born between 1960 and 1990 (N = 184,770). These classes were then validated using demographics; patterns of comorbidity with drug abuse, psychiatric disorders and criminal behavior; and neighborhood-level factors, i.e. peer AUD and neighborhood deprivation. The degree of genetic and environmental influence was also investigated. RESULTS: The best-fit LCA had four classes: (a) outpatient/prescription, characterized by a mix of outpatient medical and prescription registrations, (b) low-frequency inpatient, characterized entirely by inpatient medical registrations, with the majority of individuals having one AUD registration, (c) high-frequency mixed, characterized by a mix of all four registration types, with the majority having four or more registrations and (d) crime, characterized almost entirely by criminal registrations. The highest heritability for both males and females was found for Class 3 (61% and 65%, respectively) and the lowest for Class 1 (20% for both), with shared environmental influences accounting for 10% or less of the variance in all Classes. CONCLUSIONS: Using comprehensive, nationwide registry data, we showed evidence for four distinct, meaningful classes of AUD with varying degrees of heritability.
Authors: Nicole D Sintov; Kenneth S Kendler; Kelly C Young-Wolff; Dermot Walsh; Diana G Patterson; Carol A Prescott Journal: Drug Alcohol Depend Date: 2010-03-01 Impact factor: 4.492
Authors: Danielle M Dick; Arpana Agrawal; Jen C Wang; Anthony Hinrichs; Sarah Bertelsen; Kathleen K Bucholz; Marc Schuckit; John Kramer; John Nurnberger; Jay Tischfield; Howard J Edenberg; Alison Goate; Laura J Bierut Journal: Addiction Date: 2007-07 Impact factor: 6.526
Authors: Katherine J Karriker-Jaffe; Sara L Lönn; Won K Cook; Kenneth S Kendler; Kristina Sundquist Journal: Health Place Date: 2018-01-12 Impact factor: 4.078