Taxometric investigation of the latent structure of nicotine dependence: An epidemiological sample

Abstract

A considerable number of daily tobacco users do not fulfill the DSM-IV and ICD-10 diagnostic criteria for nicotine dependence (ND). This suggests that such a diagnostic boundary may be arbitrary. This paper addresses this question empirically by comparing the viability of two models, respectively hypothesizing a dimensional and a categorical latent structure of ND. An epidemiological sample of 6,926 individuals was selected from a cross-sectional probabilistic stratified sampling design. All participants having smoked in the past 30 days were included in the study. Half of this sample was used to select appropriate composite indicators of tobacco consumption. A factor analysis with oblique PROMAX rotation was used as well as the MAXCOV (Maximum Covariance) procedure to identify indicators that maximized between-class distance, and minimize within-class variance. The remaining half of the sample was submitted to a set of three mathematically independent taxometric procedures: Mean Above Minus Below A Cut (MAMBAC), MAXCOV and Maximum Eigenvalues (MAXEIG). In line with the original hypothesis, the results supported a dimensional latent structure for ND. These findings are discussed in terms of their clinical implications for the validation of adequate screening procedures and the etiology and maintenance of ND.