CAJ | 학술논문

目的构建针对致死性道路交通伤害预测模型,为预测道路交通伤害未来发展趋势提供基础.方法查询WHO死亡数据库获取不同国家道路交通伤害死亡人数资料,通过世界银行、WHO、联合国人口司等机构网站获取各国不同年份人均GDP、城市化水平、机动化水平及教育水平等资料,构建包含上述4个自变量的男女各年龄组道路交通伤害死亡率对数模型,并与WHO模型拟合优度进行比较.结果共收集2 626份数据(来自153个国家/地区;男女各半;时间1965-2010年).选用人均GDP、机动化水平、城市化水平和教育水平4个变量构建的道路交通伤害死亡率拟合模型均具有统计学意义(P＜0.001),男性0～4、5～14、15 ～24、25～34、35～44、45～54、55 ～ 64、≥65岁组模型的决定系数R2分别为22.7％、31.1％、51.8％、52.3％、44.9％、41.8％、40.1％、25.5％,女性各年龄组分别为22.9％、32.6％、51.1％、49.3％、41.3％、35.9％、30.7％、20.1％;WHO模型仅选用人均GDP、教育水平和时间变量构建不同性别、年龄组预测模型,差异均有统计学意义(P＜0.001),男性各年龄组模型决定系数R2分别为14.9％、22.0％、31.5％、33.1％、30.7％、28.5％、27.7％、17.8％;女性各年龄组模型分别为14.1％、20.6％、30.4％、31.8％、26.7％、24.3％、17.3％、8.8％.结论本研究构建的道路交通伤害预测模型优于WHO模型.
목적 구건침대치사성도로교통상해예측모형,위예측도로교통상해미래발전추세제공기출.방법 사순WHO사망수거고획취불동국가도로교통상해사망인수자료,통과세계은행、WHO、연합국인구사등궤구망참획취각국불동년빈인균GDP、성시화수평、궤동화수평급교육수평등자료,구건포함상술4개자변량적남녀각년령조도로교통상해사망솔대수모형,병여WHO모형의합우도진행비교.결과 공수집2 626빈수거(래자153개국가/지구;남녀각반;시간1965-2010년).선용인균GDP、궤동화수평、성시화수평화교육수평4개변량구건적도로교통상해사망솔의합모형균구유통계학의의(P＜0.001),남성0～4、5～14、15 ～24、25～34、35～44、45～54、55 ～ 64、≥65세조모형적결정계수R2분별위22.7％、31.1％、51.8％、52.3％、44.9％、41.8％、40.1％、25.5％,녀성각년령조분별위22.9％、32.6％、51.1％、49.3％、41.3％、35.9％、30.7％、20.1％;WHO모형부선용인균GDP、교육수평화시간변량구건불동성별、년령조예측모형,차이균유통계학의의(P＜0.001),남성각년령조모형결정계수R2분별위14.9％、22.0％、31.5％、33.1％、30.7％、28.5％、27.7％、17.8％;녀성각년령조모형분별위14.1％、20.6％、30.4％、31.8％、26.7％、24.3％、17.3％、8.8％.결론 본연구구건적도로교통상해예측모형우우WHO모형.
Objective To develop the forecasting models for fatal road traffic injuries and to provide evidence for predicting the future trends on road traffic injuries.Methods Data on the mortality of road traffic injury including factors as gender and age in different countries,were obtained from the World Health Organization Mortality Database.Other information on GDP per capita,urbanization,motorization and education were collected from online resources of World Bank,WHO,the United Nations Population Division and other agencies.We fitted logarithmic models of road traffic injury mortality by gender and age group,including predictors of GDP per capita,urbanization,motorization and education.Sex-and age-specific forecasting models developed by WHO that including GDP per capita,education and time etc.were also fitted.Coefficient of determination (R2) was used to compare the performance between our modes and WHO models.Results 2 626 sets of data were collected from 153 countries/regions for both genders,between 1965 and 2010.The forecasting models of road traffic injury mortality based on GDP per capita,motorization,urbanization and education appeared to be statistically significant (P＜0.001),and the coefficients of determination for males at the age groups of 0-4,5-14,15-24,25-34,35-44,45-54,55-64,65+ were 22.7％,31.1％,51.8％,52.3 ％,44.9％,41.8％,40.1％,25.5％,respectively while the coefficients for these age groups in women were 22.9％,32.6％,51.1％,49.3％,41.3％,35.9％,30.7％,20.1％,respectively.The WHO models that were based on the GDP per capita,education and time variables were statistically significant (P＜0.001) and the coefficients of determination were 14.9％,22.0％,31.5％,33.1％,30.7％,28.5％,27.7％ and 17.8％ for males,but 14.1％,20.6％,30.4％,31.8％,26.7％,24.3％,17.3％ and 8.8％ for females,respectively.Conclusion The forecasting models that we developed seemed to be better than those developed by WHO.