Analysis of 43,093 Americans identified five drug abuse patterns: no abuse (92.5%), cannabis-only (5.8%), stimulants/hallucinogens (0.6%), prescription drugs (0.6%), and polysubstance (0.5%), each with distinct psychiatric profiles.
Read this if you want to understand the different patterns of drug use problems in the US population and their psychiatric associations.
Cannabis-only abuse (5.8%) was the most common drug problem pattern, 10x more prevalent than polysubstance (0.5%)
What the researchers found
Using latent class analysis of the National Epidemiological Survey on Alcohol and Related Conditions (43,093 participants), researchers identified five distinct patterns of illicit drug abuse/dependence.
The largest class (92.5%) had no drug abuse/dependence. Cannabis abuse/dependence only was the most common drug problem (5.8%). Three smaller classes were identified: stimulants/hallucinogens (0.6%), prescription drugs including sedatives, tranquilizers, and opiates (0.6%), and polysubstance abuse/dependence (0.5%).
Each class had a distinct psychiatric profile. The polysubstance class had the strongest associations with major depression and nicotine dependence. The prescription drug class had the strongest association with anxiety disorders. All drug classes (2-5) were associated with alcohol abuse/dependence and antisocial personality disorder compared to the no-abuse class.
Why it matters
Identifying distinct patterns of drug abuse rather than treating all illicit drug use as one category allows for better-targeted prevention and treatment. The finding that cannabis-only abuse is by far the most common pattern (5.8% vs. 0.5-0.6% for other patterns) and has the mildest psychiatric profile informs risk stratification.
The numbers in context
43,093 participants. Class 1: no abuse/dependence (92.5%). Class 2: cannabis only (5.8%). Class 3: stimulants/hallucinogens (0.6%). Class 4: prescription drugs (0.6%). Class 5: polysubstance (0.5%). Polysubstance: strongest link to depression. Prescription drugs: strongest link to anxiety.
How the study worked
Latent class analysis of 43,093 participants from the National Epidemiological Survey on Alcohol and Related Conditions. Multinomial logistic regression examined associations between drug abuse classes and psychiatric disorders (DSM-IV diagnoses of depression, anxiety, panic, social phobia, antisocial personality).
What this study cannot tell us
Cross-sectional design cannot determine whether drug abuse preceded or followed psychiatric disorders. Self-reported drug use in a national survey may underestimate prevalence. The latent class solution depends on the analytic approach and sample characteristics.
How to read the evidence
Large nationally representative sample (43,093) with standardized diagnostic assessments. Strong methodology for descriptive epidemiology.
When this study was published
Published in 2007. Subsequent analyses have replicated these general patterns, though legalization may be changing the landscape.
The bigger picture
This study helped move the field away from treating "drug abuse" as a monolithic category. By showing that different drug abuse patterns have different psychiatric profiles, it supported the development of more targeted assessment and treatment approaches.
Questions still open
- Do these five classes have different treatment needs and outcomes? Is the cannabis-only class at risk of progressing to polysubstance use?
Common questions
How common is cannabis-only abuse compared to other drug problems?
Do people who only use cannabis have mental health problems?
Read the original research
A latent class analysis of illicit drug abuse/dependence: results from the National Epidemiological Survey on Alcohol and Related Conditions.
Addiction (Abingdon, England), 102(1), 94-104
Citation
Agrawal, Arpana; Lynskey, Michael T; Madden, Pamela A F; Bucholz, Kathleen K; Heath, Andrew C. (2007). A latent class analysis of illicit drug abuse/dependence: results from the National Epidemiological Survey on Alcohol and Related Conditions.. Addiction (Abingdon, England), 102(1), 94-104.
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