169 Risk of road traffic crash, medical factors and behavioural adaptations in elderly drivers. (1st September 2016)

• Record Type: Journal Article
• Authors: Luxcey, Audrey; Lagarde, Emmanuel; Lafont, Sylviane; Zins, Marie; Contrand, Benjamin; Orriols, Ludivine
• Is Part Of: Injury prevention. Volume 22(2016)Supplement 2
• Page Start: A62
• Page End: A62
• Publication Date: 2016-09-01
• Subjects: elderly drivers -- crash -- medical factors -- adaptations; Children's accidents -- Prevention -- Periodicals; Accidents -- Prevention -- Periodicals; 617.1
• DOI: 10.1136/injuryprev-2016-042156.169
• Languages: English
• ISSNs: 1353-8047

Abstract

Abstract : Background: If at first glance the question of medical factors in road safety seems to boil down to the list of diseases and medications consistent or incompatible with driving, the problem is much more complex because many factors come into play: mobility, loss of autonomy, perceptions of disabilities and behavioural adaptations to them. Regarding the increase of elderly drivers on the road, the aim of this project is to identify medical conditions, incapacities and medicine consumption associated with a risk of road traffic crash and to describe key parameters of the interaction between medical conditions, medical consumption and driving behaviours in this population. Methods: Gazel is a cohort of 20 000 retirees of the French national electricity and gas companies (EDF-GDF) followed since 1989 and originally included men aged 40–50 years and women aged 35–50 years. This cohort has been followed up by means of yearly self-administered questionnaires. This annual questionnaire includes questions about sociodemographic characteristics, health, diseases, lifestyle, difficulties of everyday life, psychosocial and psychological data and road traffic crashes. A driving behaviour and road safety questionnaire was administered in 2001, 2004 and 2007. In 2015, questions about mobility, health and incapacities were added and this questionnaire was administered by internet. Besides the classical statistical methods for the descriptive phase, models suitable for longitudinal data will be used. Results: The number of participants was 14, 226 in 2001, 11, 706 in 2004, 11, 551 in 2007 and 5, 402 in 2015. First results show that when participants get older, they drive more carefully and their perception of their crash risk decreases. Other analyses are in progress. Conclusions: The interactions of the three components: medical conditions, drug consumption and driving behaviours need to be understood to design effective preventive policies and proper screening of drivers unfit to drive.