Activity level, performance and exposure among older drivers.
20200326 ST [electronic version only]
Staplin, L. Lococo, K.H. Gish, K.W. Stutts, J. Srinivasan, R.
Washington, D.C., U.S. Department of Transportation DOT, National Highway Traffic Safety Administration NHTSA, 2019, V + 43 p. + app.; NHTSA Report DOT HS 812 734
|Samenvatting||This project explored the relationship between the fitness of older people – operationalized through multiple measures ofphysical activity level and cognitive status – and their driving performance and exposure. A certified driver rehabilitationspecialist conducted on-road evaluations for a study sample (n=67; mean age=78.6) recruited from senior residentialcommunities in the vicinity of Chapel Hill, NC. GPS and video recorders installed in study participants’ own vehiclescollected naturalistic driving data for approximately one month. Functional status assessments included measures ofhead/neck/torso flexibility; lower limb strength, balance, and proprioception; visual search with divided attention; andexecutive function. Activity levels were gauged through the Phone-FITT questionnaire; the VO2max questionnaire andbody measurements; and a pedometer that participants wore around their ankle for a month to record active minutes perday, steps per day, gait speed, and daily distance. Because of their complementary nature, the physical activity measureswere combined into a single, continuous scale ranging from 1 (lowest level of physical activity) to 100 (highest level ofactivity), termed the Unified Physical Activity Index (UPAI). Subsequent correlations between UPAI scores and roadtest scores (operational, tactical, strategic, and total) showed that, while higher physical activity levels generally wereassociated with better road test performance, in all cases relationships were very weak, accounting for less than 3% ofthe variance in the performance evaluations. Similarly, UPAI scores failed to account for more than 1.5% of the variancein multiple measures of trip frequency, distance, or time, or of scanning behavior as characterized by frequency of sideglances and over-the-shoulder checks. Correlations between functional status measures and performance and exposurealso were very weak; the strongest (inverse) relationships, accounting for about 5% of variance, were between head/neck- flexibility and shoulder checks per minute and between trails B score and minutes of driving per day. Logistic regressionfound that Trails B and Snellgrove Maze Test scores significantly predicted pass/fail outcomes on the road test, and amultiple regression model relating trails B (and other variables) to driving minutes per day indicated that the trails Brelationship was statistically significant. (Author/publisher)|
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