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Comparative Study
. 2012 Oct 21:12:887.
doi: 10.1186/1471-2458-12-887.

Comparing the impact of socio-demographic factors associated with traffic injury among older road users and the general population in Japan

Affiliations
Comparative Study

Comparing the impact of socio-demographic factors associated with traffic injury among older road users and the general population in Japan

Takashi Nagata et al. BMC Public Health. .

Abstract

Background: The increasing number of older road users represents a public health issue because older individuals are more susceptible to traffic injury and mortality than the general population. This study investigated the association between socio-demographic factors and traffic injury and traffic mortality for the general population and among older road users in Japan.

Methods: An ecological study was conducted using national data in Japan. Multivariate regression methods were applied to investigate the association of traffic injury and traffic mortality for the general population and among older road users with significant demographic, economic, road traffic, and medical/cultural factors.

Results: Income per capita, total road length, and alcohol consumption per person were significantly associated with traffic injury and traffic mortality both for the general population and among older road users in Japan. Income per capita and alcohol consumption per person were negatively associated with traffic mortality for both groups. Meanwhile, for both groups, income per capita was positively associated with traffic injury, while total road length and alcohol consumption per person were negatively associated with traffic injury.

Conclusions: The effects of socio-demographic factors on traffic injury and traffic mortality in Japan were similar for both the general population and older road users. The study results suggest that injury preventive measures designed for the general population will be beneficial also for older road users in Japan.

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Figures

Figure 1
Figure 1
The associations of variables with high correlation of estimations

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