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Evaluating the effectiveness of implementing a more severe law on prevention of road traffic injury mortality in mainland China: an interrupted time series study based on national mortality surveillance


Background In China, road traffic injury (RTI) is the seventh-leading cause of death More than 1.5 million adults in China live with permanent disabilities due to road traffic accidents. In 2011, the Chinese government implemented a more severe law that increased the penalty points and fines for persons charged with drink-driving as a criminal offence.

Objectives This study evaluated the short-term and long-term effects of the drink-driving law. It also aimed to establish whether punishments of increased severity resulted in greater reductions in RTI mortality.

Methods RTI mortality data was obtained from the Disease Surveillance Points System. A two-level interrupted time series model was used to analyse daily and monthly road traffic mortality rates, accounting for the varying trends among counties.

Results The overall RTI mortality rate showed a decreasing trend from 2007 to 2015 in mainland China, especially after 2011, and similarly decreasing trends were noted among males and females and in urban and rural areas. After the Criminal Law and Road Traffic Law amendment was implemented in 2011, charging drink-driving as a criminal offence, the immediate daily RTI mortality rate reduced by 1.57% (RR=0.9843, 95% CI: 0.9444 to 1.0259), while the slope change significantly decreased by 0.04% (RR=0.9996, 95% CI: 0.9994 to 0.9997) compared with the period before the Law was revised. Stratified analysis showed that the effect size of the law was higher for males in urban and high socioeconomic circumstances (SEC) than females in rural and low and moderate SEC. Meanwhile, the increase in penalty points for dangerous driving behaviours showed no significant effects.

Conclusion Evidence was found that charging criminal responsibility for drink-driving is associated with reducing RTI deaths in China.

  • Policy
  • Public Health
  • Epidemiology
  • Time series
  • Mortality

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