title: Urban and rural differences in older drivers' failure to stop at stop signs.
abstract: Our purpose was to determine visual and cognitive predictors for older drivers' failure to stop at stop signs. 1425 drivers aged between ages 67 and 87 residing in Salisbury Maryland were enrolled in a longitudinal study of driving. At baseline, the participants were administered a battery of vision and cognition tests, and demographic and health questionnaires. Five days of driving data were collected with a Driving Monitoring System (DMS), which obtained data on stop signs encountered and failure to stop at stop signs. Driving data were also collected 1 year later (round two). The outcome, number of times a participant failed to stop at a stop sign at round two, was modeled using vision and cognitive variables as predictors. A negative binomial regression model was used to model the failure rate. Of the 1241 who returned for round two, 1167 drivers had adequate driving data for analyses and 52 did not encounter a stop sign. In the remaining 1115, 15.8% failed at least once to stop at stop signs, and 7.1% failed to stop more than once. Rural drivers had 1.7 times the likelihood of not stopping compared to urban drivers. Amongst the urban participants, the number of points missing in the bilateral visual field was significantly associated with a lower failure rate. In this cohort, older drivers residing in rural areas were less likely to stop at stop-sign intersections than those in urban areas. It is possible that rural drivers frequent areas with less traffic and better visibility, and may be more likely to take the calculated risk of not stopping. In this cohort failure to stop at stop signs was not explained by poor vision or cognition. Conversely in urban areas, those who have visual field loss appear to be more cautious at stop signs.
authors: Dana Center for Preventive Ophthalmology, Wilmer Eye Institute, Johns Hopkins University, Baltimore, MD 21287, United States. lkeay@george.org.au
authors: Lisa
authors: L
authors: Keay
authors: Srichand
authors: S
authors: Jasti
authors: Beatriz
authors: B
authors: Munoz
authors: Kathleen A
authors: KA
authors: Turano
authors: Cynthia A
authors: CA
authors: Munro
authors: Donald D
authors: DD
authors: Duncan
authors: Kevin
authors: K
authors: Baldwin
authors: Karen J
authors: KJ
authors: Bandeen-Roche
authors: Emily W
authors: EW
authors: Gower
authors: Sheila K
authors: SK
authors: West
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D001288:Attention; D001334:Automobile Driving / Q000706:statistics & numerical data*; D001336:Automobiles / Q000706:statistics & numerical data*; D003071:Cognition; D003072:Cognition Disorders; D015331:Cohort Studies; D016001:Confidence Intervals; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D010465:Perception; D011594:Psychometrics; D012044:Regression Analysis; D012307:Risk Factors; D012424:Rural Population / Q000706:statistics & numerical data*; D011795:Surveys and Questionnaires; D014505:Urban Population / Q000706:statistics & numerical data*; D014792:Visual Acuity