title: Alcohol-impaired driving: average quantity consumed and frequency of drinking do matter.
abstract: OBJECTIVE
  The objective of this article is to estimate and validate a logistic model of alcohol-impaired driving using previously ignored alcohol consumption behaviors, other risky behaviors, and demographic characteristics as independent variables.
  
  
  METHODS
  The determinants of impaired driving are estimated using the US Centers for Disease Control and Prevention's (CDC) Behavioral Risk Factor Surveillance System (BRFSS) surveys. Variables used in a logistic model to explain alcohol-impaired driving are not only standard sociodemographic variables and bingeing but also frequency of drinking and average quantity consumed, as well as other risky behaviors. We use interactions to understand how being female and being young affect impaired driving. Having estimated our model using the 1997 survey, we validated our model using the BRFSS data for 1999.
  
  
  RESULTS
  Drinking 9 or more times in the past month doubled the odds of impaired driving. The greater average consumption of alcohol per session, the greater the odds of driving impaired, especially for persons in the highest quartile of alcohol consumed. Bingeing has the greatest effect on impaired driving. Seat belt use is the one risky behavior found to be related to such driving. Sociodemographic effects are consistent with earlier research. Being young (18-30) interacts with two of the alcohol consumption variables and being a woman interacts with always wearing a seat belt. Our model was robust in the validation analysis.
  
  
  CONCLUSIONS
  All 3 dimensions of drinking behavior are important determinants of alcohol-impaired driving, including frequency and average quantity consumed. Including these factors in regressions improves the estimates of the effects of all variables.
authors.affiliation: School of Social Work, University of Michigan, Ann Arbor, Michigan 48105, USA. birdz@umich.edu
authors.forename: William C
authors.initials: WC
authors.lastname: Birdsall
authors.forename: Beth Glover
authors.initials: BG
authors.lastname: Reed
authors.forename: Syeda S
authors.initials: SS
authors.lastname: Huq
authors.forename: Laura
authors.initials: L
authors.lastname: Wheeler
authors.forename: Sarah
authors.initials: S
authors.lastname: Rush
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000428:Alcohol Drinking / Q000453:epidemiology / Q000523:psychology*; D000435:Alcoholic Intoxication / Q000453:epidemiology*; D001334:Automobile Driving / Q000523:psychology / Q000706:statistics & numerical data*; D040343:Behavioral Risk Factor Surveillance System; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D008960:Models, Psychological; D012309:Risk-Taking; D012622:Seat Belts / Q000706:statistics & numerical data; D017678:Sex Distribution; D014481:United States / Q000453:epidemiology; D055815:Young Adult