Literature DB >> 25059365

[Forecast the trend of burden from fatal road traffic injuries between 2015 and 2030 in China].

Aichun Tan1, Danping Tian1, Yuanxiu Huang1, Lin Gao1, Xin Deng1, Li Li1, Qiong He1, Tianmu Chen1, Guoqing Hu1, Jing Wu2.   

Abstract

OBJECTIVE: To predict the burden caused by fatal road traffic injuries from 2015 to 2030.
METHODS: We searched the websites of United Nations Population Division,United States Department of Agriculture, World Health Organization, China Energy Research Foundation and other agencies to obtain the predictive values of gross domestic product (GDP) per capita, urbanization, motorization and education from 2015 to 2030 in China. Predicted values were then applied to log-linear models to estimate the numbers and years of life lost due to road traffic injuries from 2015 to 2030.
RESULTS: The mortality rate caused by road traffic injury decreased slightly, from 13.7/100 000 in 2015 to 11.8/100 000 in 2030. 191, 189, 183, 169 thousand persons were estimated to die from road traffic crashes in 2015, 2020, 2025 and 2030, respectively, showing a declining trend. Years of Life Lost (YLLs) caused by road traffic deaths were predicted to be 6 918, 6 634, 6 189, 5 513 thousand years in 2015, 2020, 2025 and 2030, respectively, also showing a gradual downward trend. But the YLLs displayed an increase among people at 55 years of age or older, between 2015 and 2030. Results from the sensitivity analysis showed a stable forecasting result.
CONCLUSION: Mortality, number of deaths and YLLs from road traffic crashes were predicted to decrease slightly, between 2015 and 2030 but the number of deaths and YLLs due to road traffic injuries will continue to increase from 2015 to 2030.

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Year:  2014        PMID: 25059365

Source DB:  PubMed          Journal:  Zhonghua Liu Xing Bing Xue Za Zhi        ISSN: 0254-6450


  3 in total

1.  Road traffic injuries in China from 2007 to 2016: the epidemiological characteristics, trends and influencing factors.

Authors:  Xue Wang; Huiting Yu; Chan Nie; Yanna Zhou; Haiyan Wang; Xiuquan Shi
Journal:  PeerJ       Date:  2019-08-06       Impact factor: 2.984

2.  The comparative analysis of SARIMA, Facebook Prophet, and LSTM for road traffic injury prediction in Northeast China.

Authors:  Tianyu Feng; Zhou Zheng; Jiaying Xu; Minghui Liu; Ming Li; Huanhuan Jia; Xihe Yu
Journal:  Front Public Health       Date:  2022-07-22

3.  Analysis of road traffic injuries and casualties in China: a ten-year nationwide longitudinal study.

Authors:  Miao Qi; Xiuli Hu; Xiahong Li; Xue Wang; Xiuquan Shi
Journal:  PeerJ       Date:  2022-09-15       Impact factor: 3.061

  3 in total

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