Estimating Drug Use Prevalence Among Arrestees Using ADAM (Arrestee Drug Abuse Monitoring) Data: An Application of a Logistic Regression Synthetic Estimation Procedure

摘要

Society continues to suffer the immense costs and consequences associated with drug use and crime. Rates of drug use among arrestees in selected sites typically runs 10 times as high as for the general population. But rates alone cannot give policymakers a magnitude of drug use prevalence among arrestees upon which to base rational policy development. Lacking complete enumeration of the arrestee population, decisions must be based on estimates. This study estimates the prevalence of drug-using arrestees in the U. S. by using available ADAM data for calendar year 2000 as a calibration sample and projecting to the national level. Prevalence estimates are presented for any illicit drug use (of 10 tested by urinalysis) and specifically for cocaine, for gender by age group by offense category subgroups. Estimation has also been done for state and county level data (California and its largest and smallest counties, Los Angeles and Alpine), for any illicit drug use. The study used a logistic regression synthetic estimation approach, in which prevalence rates in a calibration sample (ADAM) are used to estimate the equivalent rates in a target population (national, state, or county) where the prevalence rates are unknown.