• Louisa Degenhardt, Wai Tat Chiu, Nancy Sampson, Ronald C Kessler, and James C Anthony.
• Department of Epidemiology, Michigan State University, B601 West Fee Hall, East Lansing, MI 48824, USA. l.degenhardt@unsw.edu.au
• Drug Alcohol Depend. 2007 Oct 8; 90 (2-3): 210-23.

BackgroundIn 1994, epidemiological patterns of extra-medical drug use in the United States were estimated from the National Comorbidity Survey. This paper describes such patterns based upon more recent data from the National Comorbidity Survey Replication (NCS-R).MethodsThe NCS-R was a nationally representative face-to-face household survey of 9282 English-speaking respondents, aging 18 years and older, conducted in 2001-2003 using a fully structured diagnostic interview, the WHO Composite International Diagnostic Interview (CIDI) Version 3.0.ResultsThe estimated cumulative incidence of alcohol use in the NCS-R was 92%; tobacco, 74%; extra-medical use of other psychoactive drugs, 45%; cannabis, 43% and cocaine, 16%. Statistically robust associations existed between all types of drug use and age, sex, income, employment, education, marital status, geography, religious affiliation and religiosity. Very robust birth cohort differences were observed for cocaine, cannabis, and other extra-medical drug use, but not for alcohol or tobacco. Trends in the estimated cumulative incidence of drug use among young people across time suggested clear periods of fluctuating risk.ConclusionsThese epidemiological patterns of alcohol, tobacco, and other extra-medical drug use in the United States in the early 21st century provide an update of NCS estimates from roughly 10 years ago, and are consistent with contemporaneous epidemiological studies. New findings on religion and religiosity, and exploratory data on time trends, represent progress in both concepts and methodology for such research. These estimates lead to no firm causal inferences, but contribute to a descriptive epidemiological foundation for future research on drug use and dependence across recent decades, birth cohorts, and population subgroups.

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