Establishment Of Forecasting Models Of Burden Of Fatal Road Traffic Injuries And Its Application In China

Objective:To project targeted forecasting models of burden of fatal road traffic injuries and use the models to predict the trends of burden of fatal road traffic injuries in China from2015to2030, providing a reference for the proposed forward-looking interventions.Methods:Collect road traffic injury deaths for different countries and different gender of all age groups by querying the World Health Organization mortality database, and gather dates of GDP per capita, urbanization, motorization and education by visiting the World Bank, the WHO, the United Nations Population Division and other agencies websites. Project logarithmic models of road traffic injury mortality for different genders and different age groups by GDP per capita, urbanization, motorization and education and repeat the WHO model only using GDP per capita, education and time, comparing the advantages and disadvantages of the two models by coefficient of determination. Enter the predictive values of independent variables into the models to predict the future trends of burden of fatal road traffic injuries from2015to2030in China.Results:1.2626data records were collected from153countries/regions, male and female each accounting for50%and time spaning from1965to2010,1965to1989,1990to1999,2000to2005,2006to2010attributable to4.8%,23.5%,31.7%and40.0%respectively.2. The fitting models of road traffic injury mortality built on GDP per capita, motorization, urbanization and education were statistically significant (P＜0.001), and the coefficients of determination for male of0-4,5-14,15-24,25-34,35-44,45-54,55-64,65age and over groups were22.7%,31.1%,51.8%,52.3%,44.9%,41.8%,40.1%,25.5%, respectively, the coefficients for each groups in women22.9%,32.6%,51.1%,49.3%,41.3%,35.9%,30.7%,20.1%, respectively;The WHO models built on the GDP per capita, education and time variables were statistically significant (P＜0.001), and the coefficients of determination for male groups were14.9%,22.0%,31.5%,33.1%,30.7%,28.5%,27.7%,17.8%, and for female each groups14.1%,20.6%,30.4%,31.8%,26.7%,24.3%,17.3%,8.8%, respectively.3. The road traffic injury mortality for2015,2020,2025and2030were13.7/100000,13.4/100000,12.8/100000,11.8/100000, with a slowly decreasing trend. The number of deaths due to fatal road traffic injury in2015,2020,2025and2030were190.565,189.358,183.051,169.033thousand respectively, with a declining trend. Years of Life Lost caused by fatal road traffic injuries in China for2015,2020,2025and2030were6918,6634,6189,5513thousands years respectively, with a gradual downward trend. However the years of life lost of55and over age group in2015,2020,2025and2030were680,737,821,839thousands years respectively, with a rising trend.Conclusion:1. The prediction models of road traffic injury mortality by GDP per capita, motorization, urbanization and education are better than the WHO models only by GDP per capita, education and time variable. These reflect the national variation of fatal road traffic injuries to a certain degree and can be used to forecast burden of fatal road traffic injuries.2. Road traffic injury mortality and the number of deaths and years of life lost due to fatal road traffic injuries were a gradual downward trend from2015to2030in China. However, the number of deaths and Years of Life Lost caused by fatal road traffic injuries of aged55and over groups were a rising trend from2015to2030. Figures:6, Tables:22, References:58.