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


METHODS
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.
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA 23298-0126, USA. kendler@vcu.edu
K S
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Kendler
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Ohlsson
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Sundquist
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Sundquist
D000328:Adult; D000437:Alcoholism / Q000145:classification / Q000453:epidemiology / Q000209:etiology; D015897:Comorbidity; D057237:Criminals / Q000145:classification* / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D008297:Male; D001523:Mental Disorders / Q000145:classification* / Q000453:epidemiology / Q000209:etiology; D008875:Middle Aged; D012042:Registries / Q000706:statistics & numerical data*; D012307:Risk Factors; D035781:Siblings; D019966:Substance-Related Disorders / Q000145:classification* / Q000453:epidemiology / Q000209:etiology; D013548:Sweden / Q000453:epidemiology