Predictors of driving outcomes including both crash involvement and driving cessation in a prospective study of Japanese older drivers

Kosuge, Ritsu; Okamura, Kazuko; Kihira, Makoto; Nakano, Yukako; Fujita, Goro

doi:10.1016/j.aap.2017.05.019

Cited by 20 publications

(10 citation statements)

References 51 publications

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“…This result is consistent with a previous study showing that cognitive impairment was a strong predictor of DC [ 34 ]. In this study, cognitive function was evaluated by the MMSE-DS score, but several studies have reported that evaluation by the MMSE score has limitations for predicting DC [ 12 , 46 ]. Kosuge and colleagues suggested that a reduction in cognitive processing speed is the strongest predictor of DC rather than the MMSE score [ 12 ].…”

Section: Discussionmentioning

confidence: 99%

“…In this study, cognitive function was evaluated by the MMSE-DS score, but several studies have reported that evaluation by the MMSE score has limitations for predicting DC [ 12 , 46 ]. Kosuge and colleagues suggested that a reduction in cognitive processing speed is the strongest predictor of DC rather than the MMSE score [ 12 ]. Another study reported that flanker task scores, selective attention, and inhibitory ability are stronger DC predictors than the MMSE score [ 46 ].…”

Section: Discussionmentioning

confidence: 99%

“…According to statistics, approximately 80% of males and 50% of females aged 70 and over will be licensed holders in 2030 in the UK [ 11 ]. The increasing number of older drivers as well as age-related functional change and disease have contributed to the increasing incidence of car accidents among the elderly population [ 4 , 12 ]. In Korea, there were a total of 10,155 car accidents involving older drivers in 2008, but this number increased to 30,012 in 2018 [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

“…Because of the risk of car accidents caused by older adults, most countries have established strict systems to screen older adults’ ability to drive. In Japan, drivers aged 70 and older have to be screened for cognitive function and take a driving lesson and driving test before renewing their driver’s licenses [ 12 ]. In Korea, it is recommended that drivers aged 65 and older take an optional lesson on safe driving, while for drivers aged 75 and older, the lesson is mandatory.…”

Section: Introductionmentioning

confidence: 99%

“…Other studies reported that older drivers drove more safely than younger drivers, and another study indicated that older drivers with medical conditions relevant to driving were safer drivers than younger drivers with medical conditions relevant to driving [ 19 , 20 ]. However, some studies reported a higher rate of accidents among older drivers than among drivers from other age groups [ 10 , 12 ]. Therefore, we need to consider the reasonable criteria that will prohibit high risk driving besides age, because driving restrictions due to advanced age that do not consider alternative transportation methods could restrict the mobility of older adults.…”

Section: Introductionmentioning

confidence: 99%

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The Predictors of Driving Cessation among Older Drivers in Korea

Moon

2020

IJERPH

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Background: As the elderly population and the number of older drivers grow, public safety concerns about traffic accidents involving older drivers are increasing. Approaches to reduce traffic accidents involving older drivers without limiting their mobility are needed. This study aimed to investigate the driving cessation (DC) rate among older Korean adults and predictors of DC based on the comprehensive mobility framework. Method: In this cross-sectional study, data from 2970 to 10,062 older adults over 65 years old from the 2017 National Survey of Elderly People were analyzed in April 2020. Multivariate logistic regression analyses were conducted to identify the predictors of DC. Results: Residential area, an environmental factor, was a strong predictor of DC (Odds Ratio (OR) 2.21, 95% Confidential Interval (CI) 1.86–2.62). Older drivers living in an area with a metro system were 2.21 more likely to stop driving than those living in an area without a metro system. Other demographic, financial, psychosocial, physical, and cognitive variables also predicted DC. Conclusion: Environmental factors were strong predictors of older adults’ DC. Therefore, political and environmental support, such as the provision of accessible public transportation, is essential to increase the DC rate among older adults to increase public safety without decreasing their mobility.

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