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Prevalence of medical factors related to aging among older car drivers: A multicenter, prospective, descriptive study

Authors :
Hideharu Hagiya
Ryosuke Takase
Hiroyuki Honda
Yasuhiro Nakano
Yuki Otsuka
Hitomi Kataoka
Mika Uno
Keigo Ueda
Misa Takahashi
Hiroko Ogawa
Yoshihisa Hanayama
Fumio Otsuka
Publication Year :
2022
Publisher :
Research Square Platform LLC, 2022.

Abstract

Aim: An increasing number of older adults in Japan are at an increased risk of traffic accident. This study aimed to investigate the prevalence of potential underlying medical factors that increase the risk of motor vehicle accidents (MVAs) among older people. Methods: This cross-sectional observational study was conducted in 11 medical institutions in Japan using self-administered questionnaires and physical examination from January to May 2021. The background and social data, data on the use of nursing care insurance, and clinical data suggestive of polypharmacy, sarcopenia, cognitive impairment, and frailty/oral frailty were obtained. The prevalence of these factors was compared between everyday and occasional drivers. Results: Data of 127 patients were collected; their median (interquartile range) age was 73 (70–78) years. Of the total participants, 82 were men (64.6%) and 45 were women (35.4%). There were 77 everyday drivers and 50 occasional drivers. Of these, 121 (95.3%) had not applied for nursing care insurance, but the numbers of those who required help 1 and 2 were 1 (0.8%) and 3 (2.4%), respectively. Prevalence of medical factors was as follows: polypharmacy, 27.6%; sarcopenia, 8.7%; dementia, 16.4%; frailty, 15.0%; and oral frailty, 54.3%; it was not significantly different between every day and occasional drivers. Intention to return the car license was significantly higher among the occasional drivers (2.6% vs. 14.0%; odds ratio: 6.7, 95% confidence interval: 1.2–70.6, P=0.024). Conclusion: We uncovered the prevalence of medical factors that increase the risk of MVAs among older people aged ≥65 years in our community.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........2324faeebd05923237f53106d8e965c7