 | The 131st Annual Meeting (November 15-19, 2003) of APHA |
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| The 131st Annual Meeting (November 15-19, 2003) of APHA |
Chiung M. Chen, MA, Alcohol Epidemiologic Data System, CSR Incorporated, 2107 Wilson Blvd., Suite 1000, Arlington, VA 22201, Hsiao-ye Yi, PhD, Alcohol Epidemiologic Data System, CSR, Incorporated, 2107 Wilson Blvd., Suite 1000, Arlington, VA 22201, 703-312-5220, hyi@csrincorporated.com, J. Quinn Schroeder, MS, Alcohol Epidemiologic Data System, CSR Incorporated, 2107 Wilson Ave. Suite 1000, Arlington, VA 22201, and Mary C. Dufour, MD, MPH, National Institute on Alcohol Abuse and Alcoholism, NIH, Willco Building, Suite 514, 6000 Executive Boulevard, Bethesda, MD 20892-7003.
Demographic characteristics, such as age, sex, race, and education are known to be associated with drinking and driving behavior. They are also known to be associated with drinking patterns. As drinking patterns are found to affect drinking and driving behavior, some researchers have suggested that drinking patterns may be intervening variables between demographic characteristics and the risk behavior of drinking and driving. This hypothesis, however, has rarely been directly tested. Using path analysis, the current study tests this hypothesis by examining the direct effects of demographic variables and their indirect effects via drinking patterns on the behavior of drinking and driving.
Data were drawn from the National Survey of Drinking and Driving Attitudes and Behavior, 1999. The drinking pattern measures were constructed based on a stochastic model of drinking patterns developed by Gruenewald and colleagues.
The path models show that the direct effects of sex, age, marital status, and education not only remain significant but also tend to predominate over the indirect effects. This suggests that these demographic characteristics themselves affect drinking and driving behavior directly rather than via variations in drinking patterns. For some categories in education and age group, the direct effects and their pertinent indirect effects had opposite signs, indicating that the demographic effects are enhanced by drinking patterns among some subgroups but reduced among others. This study will contribute to better understanding the mechanism by which demographic variables affect drinking and driving behavior, and, thus benefit the prevention efforts by identifying and targeting high risk groups.
Learning Objectives:
Presenting author's disclosure statement:
I do not have any significant financial interest/arrangement or affiliation with any organization/institution whose products or services are being discussed in this session.