BACKGROUND: Etiologic research on complex disorders including alcohol dependence requires informative phenotypes. Information is lost when categorical variables represent inherently dimensional conditions. We investigated the validity of DSM-IV alcohol dependence as a dimensional phenotype by examining evidence for linearity and thresholds in associations with validating variables. METHOD: Current drinkers in the National Longitudinal Alcohol Epidemiologic Survey (NLAES) (n=18352) and National Epidemiologic Survey of Alcohol and Related Conditions (NESARC) (n=20836) were analyzed. Validating variables included family alcoholism, early-onset drinking, and alcohol treatment. Logistic or Poisson regression modeled the relationships between the validating variables and dependence in categorical, dimensional or hybrid forms, with severity defined as number of current DSM-IV alcohol-dependence criteria. Wald tests assessed differences between models. RESULTS: No evidence was found for boundaries between categories. Instead, the association of alcohol dependence with the validating variables generally increased in linear fashion as the number of alcohol-dependence criteria increased. For NLAES models of family alcoholism, early-onset drinking and treatment, the lines had zero intercepts, with slopes of 0.18, 0.27, 0.70, respectively. For NESARC models of family history and early-onset drinking, the zero intercept lines had slopes of 0.20, 0.33, and 0.77, respectively. Wald tests indicated that models representing alcohol dependence as a dimensional linear predictor best described the association between dependence criteria and the validating variables. CONCLUSIONS: The sample sizes allowed strong tests. Diagnoses are necessary for clinical decision-making, but a dimensional alcohol-dependence indicator should provide more information for research purposes.
BACKGROUND: Etiologic research on complex disorders including alcohol dependence requires informative phenotypes. Information is lost when categorical variables represent inherently dimensional conditions. We investigated the validity of DSM-IV alcohol dependence as a dimensional phenotype by examining evidence for linearity and thresholds in associations with validating variables. METHOD: Current drinkers in the National Longitudinal Alcohol Epidemiologic Survey (NLAES) (n=18352) and National Epidemiologic Survey of Alcohol and Related Conditions (NESARC) (n=20836) were analyzed. Validating variables included family alcoholism, early-onset drinking, and alcohol treatment. Logistic or Poisson regression modeled the relationships between the validating variables and dependence in categorical, dimensional or hybrid forms, with severity defined as number of current DSM-IV alcohol-dependence criteria. Wald tests assessed differences between models. RESULTS: No evidence was found for boundaries between categories. Instead, the association of alcohol dependence with the validating variables generally increased in linear fashion as the number of alcohol-dependence criteria increased. For NLAES models of family alcoholism, early-onset drinking and treatment, the lines had zero intercepts, with slopes of 0.18, 0.27, 0.70, respectively. For NESARC models of family history and early-onset drinking, the zero intercept lines had slopes of 0.20, 0.33, and 0.77, respectively. Wald tests indicated that models representing alcohol dependence as a dimensional linear predictor best described the association between dependence criteria and the validating variables. CONCLUSIONS: The sample sizes allowed strong tests. Diagnoses are necessary for clinical decision-making, but a dimensional alcohol-dependence indicator should provide more information for research purposes.
Authors: Karl G Hill; J David Hawkins; Jennifer A Bailey; Richard F Catalano; Robert D Abbott; Valerie B Shapiro Journal: Drug Alcohol Depend Date: 2010-03-17 Impact factor: 4.492
Authors: Risë B Goldstein; S Patricia Chou; Sharon M Smith; Jeesun Jung; Haitao Zhang; Tulshi D Saha; Roger P Pickering; W June Ruan; Boji Huang; Bridget F Grant Journal: J Stud Alcohol Drugs Date: 2015-05 Impact factor: 2.582
Authors: Richard Sherva; John P Rice; Rosalind J Neuman; Nanette Rochberg; Nancy L Saccone; Laura J Bierut Journal: Alcohol Clin Exp Res Date: 2009-03-06 Impact factor: 3.455