Sakai JT, Stallings MC, Mikulich-Gilbertson SK, Corley RP, Young SE, Hopfer CJ, Crowley TJ. Mate similarity for substance dependence and antisocial personality disorder symptoms among parents of patients and controls.
Drug Alcohol Depend 2004;
75:165-75. [PMID:
15276222 DOI:
10.1016/j.drugalcdep.2004.01.015]
[Citation(s) in RCA: 24] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2003] [Revised: 01/19/2004] [Accepted: 01/29/2004] [Indexed: 11/20/2022]
Abstract
UNLABELLED
Substance dependence (SD) and antisocial personality disorder (ASPD) are highly comorbid and aggregate in families. Mating assortment may be an important process contributing to this familial aggregation.
HYPOTHESIS
Symptom counts of substance dependence, antisocial personality disorder, and retrospectively assessed conduct disorder (CD) will be correlated significantly among parents of youth in treatment for substance use and conduct problems and, separately, among parents of community controls.
METHODS
We examined SD, ASPD, and CD among 151 pairs of parents of adolescents in treatment for substance use and conduct problems, and in 206 pairs of parents of control subjects.
RESULTS
For average dependence symptoms (ADS) (the sum of across-drug substance dependence symptoms divided by the number of substance categories meeting minimum threshold use) mother-father correlations were 0.40 for patients and 0.28 for controls. Mother--father correlations for ASPD symptom count were 0.33 for patients and 0.26 for controls and for CD symptom count were 0.31 for patients (all P < 0.01) and 0.10 for controls (P = 0.14).
CONCLUSIONS
Spousal correlations for ADS and ASPD, suggest substantial non-random mating. Results support gender differences in homogamy for SD. Behavior genetic studies of these disorders need to account for assortment to avoid biases in estimates of genetic and environmental effects.
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