Measured as elapsed time from first use to dependence syndrome onset, the estimated "induction interval" for cocaine is thought to be short relative to the cannabis interval, but little is known about risk of becoming dependent during first months after onset of use. Virtually all published estimates for this facet of drug dependence epidemiology are from life histories elicited years after first use. To improve estimation, we turn to new month-wise data from nationally representative samples of newly incident drug users identified via probability sampling and confidential computer-assisted self-interviews for the United States National Surveys on Drug Use and Health, 2004-2013. Standardized modules assessed first and most recent use, and dependence syndromes, for each drug subtype. A four-parameter Hill function depicts the drug dependence transition for subgroups defined by units of elapsed time from first to most recent use, with an expectation of greater cocaine dependence transitions for cocaine versus cannabis. This study's novel estimates for cocaine users one month after first use show 2-4% with cocaine dependence; 12-17% are dependent when use has persisted. Corresponding cannabis estimates are 0-1% after one month, but 10-23% when use persists. Duration or persistence of cannabis smoking beyond an initial interval of a few months of use seems to be a signal of noteworthy risk for, or co-occurrence of, rapid-onset cannabis dependence, not too distant from cocaine estimates, when we sort newly incident users into subgroups defined by elapsed time from first to most recent use.
Digital Object Identifier (DOI)
This work was supported by a National Institutes of Health National Institute on Drug Abuse T32 research training program grant award (T32DA021129) for OAV’s postdoctoral fellowship, by JCA’s NIDA Senior Scientist and Mentorship Award (K05DA015799), and by the Michigan State University.
Vsevolozhskaya, Olga A. and Anthony, James C., "Estimated Probability of Becoming a Case of Drug Dependence in Relation to Duration of Drug-Taking Experience: A Functional Analysis Approach" (2016). Biostatistics Faculty Publications. 24.
Available for download on Thursday, June 29, 2017