This paper presents estimates of the number of people who will need treatment for illicit drug abuse problems for the years 2000 through 2020.
The methodology employs logistic regression models, with treatment need as a dependent variable, using data from lifetime marijuana users included in the National Household Survey on Drug Abuse.
Age at first use of marijuana was found to be the most important predictor in these models.
Other variables included in the models were age, gender, and race/ethnicity.
By generating estimates under alternative assumptions about future rates of initiation, it was projected that if current rates of initiation continue, treatment need will increase by 57% by 2020, and that the need for treatment will remain high even if initiation rates decrease dramatically, because of the aging baby boom cohort.
Mots-clés Pascal : Toxicomanie, Estimation statistique, Besoin, Traitement, Sevrage toxique, Antécédent, Age apparition, Consommation, Marihuana, Etats Unis, Amérique du Nord, Amérique, Homme
Mots-clés Pascal anglais : Drug addiction, Statistical estimation, Need, Treatment, Detoxification, Antecedent, Age of onset, Consumption, Marihuana, United States, North America, America, Human
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Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 99-0343511
Code Inist : 002B18C05A. Création : 14/12/1999.