Journal of Epidemiology
Online ISSN : 1349-9092
Print ISSN : 0917-5040
ISSN-L : 0917-5040

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Reduced Road Injuries While Commuting Due to Heavy Snowfall and Ensuing Modal Shifts Among Junior High School Students in Japan
Haruhiko InadaJun TomioMasao IchikawaShinji Nakahara
著者情報
ジャーナル オープンアクセス 早期公開

論文ID: JE20200504

この記事には本公開記事があります。
2版: 2021/06/22
1版: 2021/02/13
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Background: Modal shifts in transport may reduce overall road injuries. Cyclist junior high school students are at a high risk of road injuries while commuting in Japan, and injuries among junior high school students could be reduced if the cyclists switch to other transport modes.

Methods: We estimated the change in the incidence of road deaths and serious injuries while commuting in months with heavy snowfall, when cyclists are likely to switch to other transport modes. Using police data on the monthly number of road injuries while commuting among junior high school students in Japan between 2004 and 2013 and corresponding population statistics and snowfall data, we calculated the monthly injury rate (number of deaths and serious injuries divided by population) at the prefecture level. We conducted Poisson regression analysis to estimate the change in the rate in months with a snowfall of ≥100 cm, compared to months without snowfall.

Results: A total of 3,164 deaths and serious injuries occurred during 2004 to 2013. The injury rate among cyclists was almost zero in months with a snowfall of ≥100 cm. That among cyclists and pedestrians in these months was reduced by 68% (95% confidence interval, 43–82%).

Conclusions: In months with heavy snowfall, road injuries while commuting were reduced due to the near-elimination of cycling injuries among junior high school students in Japan. Switching from cycling to other transport modes would reduce overall road injuries among this population, and inducing modal shifts can be an important tool for road safety.

著者関連情報
© 2021 Haruhiko Inada et al. This is an open access article distributed under the terms of Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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