Mathematical models assuming selective recruitment fitted to data for driver mortality and seat belt use in Japan

Abstract

Previous research has indicated that unbelted drivers are at higher risk of involvement in fatal crashes than belted drivers, suggesting selective recruitment that high-risk drivers are unlikely to become belt users. However, how the risk of involvement in fatal crashes among unbelted drivers varies according to the level of seat belt use among general drivers has yet to be clearly quantified. We, therefore, developed mathematical models describing the risk of fatal crashes in relation to seat belt use among the general public, and explored how these models fitted to changes in driver mortality and changes in observed seat belt use using Japanese data. Mortality data between 1979 and 1994 were obtained from vital statistics, and mortality data in the daytime and nighttime between 1980 and 2001 and belt use data between 1979 and 2001 were obtained from the National Police Agency. Regardless of the data set analyzed, exponential models, assuming that high-risk drivers would gradually become belt users in order of increasing risk as seat belt use among general motorists reached high levels, showed the best fit. Our models provide an insight into behavioral changes among high-risk drivers and support the selective recruitment hypothesis.