Predictors of Automobile Crashes and Moving Violations among Elderly Drivers

  1. Richard A. Marottoli, MD, MPH;
  2. Leo M. Cooney, MD;
  3. D. Raye Wagner, MA, MS;
  4. John Doucette, MPhil; and
  5. Mary E. Tinetti, MD
  1. From West Haven Veterans Affairs Medical Center and Yale University School of Medicine, New Haven, Connecticut. Requests for Reprints: Richard A. Marottoli, MD, MPH, Yale University School of Medicine, Department of Internal Medicine, 333 Cedar Street, P.O. Box 208025, New Haven, CT 06520-8025. Grant Support: In part by grant AG 07449 from the National Institute on Aging. Dr. Marottoli is a recipient of a Veterans Administration Health Services Research and Career Development award.

    Abstract

    Objective: To identify the factors associated with automobile crashes, moving violations, and being stopped by police in a cohort of elderly drivers.

    Design: Prospective cohort study.

    Setting: Urban community.

    Participants: All 283 persons who drove between 1990 and 1991, selected from a representative cohort of community-living persons aged 72 years and older in New Haven, Connecticut.

    Measurements: Data on independent variables in five domains (demographic, health, psychosocial, activity, and physical performance) were collected in structured interviews before events occurred. The outcome measure was the self-report of involvement in automobile crashes, moving violations, or being stopped by police in a 1-year period.

    Results: Of the 283 drivers, 13% reported a crash, a moving violation, or being stopped by police in 1 year. The baseline factors associated with the occurrence of adverse events in multivariable analysis (with adjustment for driving frequency and housing type) were the following: poor design copying on the Mini-Mental State Examination (relative risk, 2.7; 95% CI, 1.5 to 5.0), fewer blocks walked (relative risk, 2.3; CI, 1.3 to 4.0), and more foot abnormalities (relative risk, 1.9; CI, 1.1 to 3.3). These risk factors were combined for assessment of their ability to predict the occurrence of adverse driving events. If no factors were present, 6% of drivers had events; if 1 factor was present, 12% had events; if 2 factors were present, 26% had events; and if 3 factors were present, 47% had events.

    Conclusions: In this urban population, several simple clinical measures correlated with the risk for adverse driving events.

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