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A latent class analysis of drug abuse in a national Swedish sample

Published online by Cambridge University Press:  01 February 2013

K. S. Kendler*
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA Department of Psychiatry, Virginia Commonwealth University, Richmond VA, USA Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
H. Ohlsson
Affiliation:
Center for Primary Health Care Research, Lund University, Malmö, Sweden
K. Sundquist
Affiliation:
Center for Primary Health Care Research, Lund University, Malmö, Sweden Stanford Prevention Research Center, Stanford University School of Medicine, Stanford, CA, USA
J. Sundquist
Affiliation:
Center for Primary Health Care Research, Lund University, Malmö, Sweden Stanford Prevention Research Center, Stanford University School of Medicine, Stanford, CA, USA
*
*Address for correspondence: K. S. Kendler, M.D., Virginia Institute for Psychiatric and Behavioral Genetics of VCU, Box 980126, Richmond, VA 23298-0126, USA. (Email: [email protected])

Abstract

Background

Drug abuse (DA) is a clinically heterogeneous syndrome. Using medical, legal, death and pharmacy records covering the entire population of Sweden, could we uncover meaningful subtypes of DA?

Method

We performed a latent class analysis (LCA) on all individuals in Sweden born 1950–1993 who were registered with DA or its consequences (n=192 501) and then validated these classes using demographics, patterns of co-morbidity with alcohol use disorder (AUD), non-DA crime and psychiatric illness, and the pattern of aggregation and co-aggregation in sibling pairs.

Results

The best-fit LCA had six classes: (1) low-frequency pure criminal, (2) high-frequency medical criminal, (3) low-frequency pure medical, (4) high-frequency medical, (5) prescription and (6) death. Each class had a distinct pattern of demographic features and co-morbidity and aggregated within sibling pairs with at least moderate specificity. For example, class 2 was characterized by early age at registration, low educational attainment, high male preponderance, high rates of AUDs, strong resemblance within sibling pairs [odds ratio (OR) 12.6] and crime and the highest risk for DA in siblings (20.0%). By contrast, class 5 had a female preponderance, late age at registration, low rates of crime and AUDs, high rates of psychiatric illness, high familiality within sibling pairs (OR 14.7) but the lowest observed risk for DA in siblings (8.9%).

Conclusions

DA as assessed by public records is a heterogeneous syndrome. Familial factors contribute substantially to this heterogeneity. Advances in our understanding of etiological processes leading to DA will be aided by a consideration of this heterogeneity.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2013 

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