Intercorrelation of Alcohol and Other Drug Use Disorders among a National Sample of Drivers

Michael Scherer, Sarah Canham, Robert B. Voas, C. Debra Furr-Holden

Research output: Contribution to journalArticlepeer-review


This study examined the relationship between alcohol, marijuana, cocaine, and painkiller use disorders in a sample of drivers. We studied nighttime drivers aged 16 to 87 (n = 4,277) from the 2007 National Roadside Survey who reported substance use behaviors and provided breath tests for alcohol. Logistic regression analyses assessed the relationships between (1) substance (i.e., alcohol/marijuana/cocaine/pain killer) use disorders; (2) demographic characteristics; and (3) BAC levels. Overall, 13.2% of participants met criteria for marijuana use disorder, 7% met criteria for cocaine use disorder, and 15.4% met criteria for extra-medicinal painkiller use disorder. When self-report data were analyzed, three reciprocal associations emerged: (1) marijuana use disorders and alcohol use disorders were correlated; (2) marijuana use disorders and cocaine use disorders were correlated; and (3) cocaine use disorders and painkiller use disorders were correlated. BAC data revealed that marijuana and cocaine use disorders were both associated with positive BAC levels, but only cocaine use disorders were associated with BAC levels over the legal limit. Results suggest significant poly-substance use disorders in a sample of nighttime drivers, with variations by demographic characteristics. The individual and public health consequences of multiple substance use disorders among drivers are significant.

Original languageEnglish (US)
Pages (from-to)143-150
Number of pages8
JournalJournal of Psychoactive Drugs
Issue number2
StatePublished - Mar 15 2018


  • Alcohol
  • cocaine
  • marijuana
  • painkillers
  • substance use disorder

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • General Psychology


Dive into the research topics of 'Intercorrelation of Alcohol and Other Drug Use Disorders among a National Sample of Drivers'. Together they form a unique fingerprint.

Cite this