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Addiction (Abingdon, England) · 2007

A latent class analysis of illicit drug abuse/dependence: results from the National Epidemiological Survey on Alcohol and Related Conditions.

СтатьяПоддержка NIH: внешняя программаНазвание и аннотация: Перевод в очереди
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Agrawal Arpana, Lynskey Michael T, Madden Pamela A F, Bucholz Kathleen K, Heath Andrew C

Аннотация

AIMS: We examine the co-occurrence of abuse/dependence across different illicit drugs and test associations between these classes and major psychiatric disorders.

METHOD: Latent class analyses were used to characterize polysubstance abuse/dependence (AB/D) in 43 093 individuals who participated in the National Epidemiological Survey on Alcohol and Related Conditions. Multinomial logistic regression was performed to examine the association between the classes of life-time illicit drug AB/D and gender, age and race, as well as life-time Diagnostic and Statistical Manual version IV (DSM-IV) alcohol abuse/dependence, nicotine dependence, major depressive disorder, generalized anxiety disorder, panic disorder, social phobia and antisocial personality disorder.

RESULTS: Five latent classes were identified: no AB/D (class 1: 92.5%), cannabis AB/D only (class 2: 5.8%), stimulants + hallucinogen AB/D (class 3: 0.6%), prescription drug AB/D (class 4: 0.6%) and polysubstance AB/D (class 5: 0.5%). Major depressive disorder and nicotine dependence were associated most strongly with class 5. Anxiety disorders were associated strongly with the prescription drug AB/D class while alcohol AB/D and ASPD were associated with classes 2, 3, 4 and 5 when compared to the reference class (class 1).

CONCLUSIONS: Significant heterogeneity exists in this US population for polysubstance AB/D patterns with evidence for a subgroup with high rates of sedative, tranquilizer and opiate AB/D and a history of anxiety disorders, a stimulant/hallucinogens group, a high-risk group with elevated rates of all psychiatric disorders and a milder cannabis AB/D only group. Replication of such classes across other samples has significant implications, such as characterizing risk groups that may be etiologically diverse.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты