Effectiveness of implementing the criminal administrative punishment law of drunk driving in China: An interrupted time series analysis, 2004-2017

Trends in injury-related mortality among residents of Jiangsu Province from 2012 to 2021: an age-period-cohort analysis

Objective

We investigated the temporal trends and examined age-, period-, and cohort-specific effects of injury-related deaths among residents in Jiangsu to provide evidence for future injury prevention.

Methods

This study included 406,936 injury deaths from the Jiangsu provincial population death registration system. The average annual percent change (AAPC) in age-standardized mortality rates (ASMRs) was analyzed using joinpoint regression. Age-period-cohort models were generated to explore the effects of age, period, and birth cohort effects on mortality risk.

Results

ASMRs for all injuries (AAPC = -2.3%), road traffic accidents (AAPC = -5.3%), suicide (AAPC = -3.8%), and drowning (AAPC = -3.9%) showed a downward trend during 2012-2021(all p < 0.05), while unintentional falls showed an upward trend (AAPC = 5.1%, p < 0.05). From 2012 to 2021, the age-standardized mortality rates (ASMRs) for four primary types of injuries consistently exhibited higher among males compared to females, with rural regions displaying higher ASMRs than urban areas. Trends in ASMRs for road traffic accidents, drowning, and unintentional falls by sex and urban/rural areas were consistent with overall trends. Significant age, cohort, and period effects were identified in the trends of injury-related deaths for both sexes in Jiangsu. The age effect showed that the highest age effect for injury-related deaths was for the ages of 85 years and above, except for suicide, which was for the ages 80-84 years. Between 2012 and 2021, the period effect on road traffic accidents declined, while that on accidental falls increased. Initially, the period effect on suicide decreased but then rose, peaking in 2012 with a Relative Risk (RR) of 1.11 (95% CI: 1.04-1.19). Similarly, the period effect on drowning initially declined before rising, with the highest effect observed in 2013, at an RR of 1.12 (95% CI: 1.07-1.19). The highest cohort effects for road traffic accidents were observed in the 1957-1961 group, for accidental falls in the 1952-1956 group, and for both drowning and suicide in the 1927-1931 group.

Conclusion

The mortality rate of unintentional falls has been increasing. Older adults are at high risk for the four leading injuries. The improvements in mortality rates can be attributed to advancements in education, urbanization, and the promulgation and implementation of laws and policies.

How do drunk-driving events escalate into drunk-driving crashes? An empirical analysis of Beijing from a spatiotemporal perspective

Drunk-driving events often escalate into drunk-driving crashes, however, the contributing factors of this progression remain elusive. To mitigate the likelihood of crashes stemming from drunk-driving events, this paper introduces the notion of 'the severity of drunk-driving event' and examines the complex relationship between the severity and its contributing factors, considering spatiotemporal heterogeneity. The study utilizes a Geographically and Temporally Weighted Binary Logistic Regression (GTWBLR) model to conduct spatiotemporal analysis based on police-reported drunk-driving events in Beijing, China. The results show that most factors passed the non-stationary test, indicating their effects on the severity of drunk-driving event vary significantly across different spatial and temporal domains. Notably, during non-workday, drunk-driving events in northeast of Beijing are more likely to escalate into crashes. Furthermore, severe weather during winter in the northwest of Beijing is associated with high risk of drunk-driving crashes. Based on these insights, the authorities can strengthen drunk-driving checks in the northeast region of Beijing, particularly during non-workdays. And it is crucial to promptly clear accumulated snow on the roads during severe winter weather to improve road safety. These insights and recommendations are highly valuable for reducing the risk of drunk-driving crashes.

Impact of the revised Unified Federal Traffic Law on crash casualties in Abu Dhabi Emirate: Interrupted time series analysis

In recent years, different developing countries have shown growing interest in enacting road safety policies. However, research on their effectiveness in reducing crashes, injuries, and deaths is limited. This study evaluated the impact of traffic safety measures introduced in the revised Unified Federal Traffic Law in the Emirates of Abu Dhabi (AD) and the United Arab Emirates (UAE) on crash and casualty reductions. In particular, it examines the 2009 enactment of the black-point system. To the best of our knowledge, this is the first study to consider this topic in a desert or UAE context. Box-Tiao intervention analysis was used to examine monthly AD police data from January 2007 to December 2013. The analysis utilized a dynamic programming approach to test for structural changes in the AD casualty data and empirically confirm the presence and exact location of breakpoints (intervention time). The interrupted time-series analysis results indicated a significant drop in casualty rates post-intervention. Since the intervention, the AD has witnessed a slow downward trend in the crash casualty rate. These findings confirm the effectiveness of the implemented safety measures. They provide quality information to authorities regarding implementing and adopting life-saving interventions and road safety management.

Revision of the driver behavior questionnaire for Chinese drivers' aberrant driving behaviors using naturalistic driving data

The Manchester Driver Behavior Questionnaire (DBQ) is a widely used self-reported measure of aberrant driving behaviors. It provides a standardized way of evaluating drivers' safety awareness and motivation, but the effectiveness of the DBQ's application in different regions can be influenced by culture, social norms, and time period. Several studies have adjusted DBQ items to reflect driver behavior native to particular regions or times, but few have used objective measurements to make proper adjustments. A naturalistic driving study (NDS) provides vehicle kinematic data and in-vehicle videos that objectively capture actual driving behaviors. The gender, age, and driving experience characteristics of aberrant driving behaviors were analyzed, and, based on comparisons between the DBQ self-reported driving behaviors and those observed in the Shanghai, China, NDS, the existing items from the Manchester DBQ were subsequently adjusted. Sixty-two types of real-world aberrant driving behaviors were extracted from 490 valid crash and near crash events observed in the Shanghai NDS. Aberrant driving behavior rates were calculated for individual characteristics (gender, age, and driving experience), and factor rates were calculated based on the three DBQ factor types of violation, error, and lapse. Results revealed that (a) male drivers, drivers in their thirties, and those with three to five years of driving experience demonstrated higher rates of aberrant driving behaviors; and (b) there were weak correlations between observed NDS factor rates and self-reported DBQ scores, and only slight differences among drivers divided by factor rate level (e.g., high violation rate). The questionnaire calibrated for Chinese drivers includes 23 items. Five of the original 24 DBQ items were modified, eight were left unchanged, eleven were deleted, and ten field-observed combined behaviors were added. In addition to the importance of adjusting the DBQ for today's Chinese drivers, this study provides a method for objectively modifying DBQ items in the future in accord with observed driving behaviors in an NDS.

Characteristics, likelihood and challenges of road traffic injuries in China before COVID-19 and in the postpandemic era

Through a review of previous studies, this paper analysed the epidemiological characteristics and attempts to determine the various trends of road traffic injuries (RTIs) in China before and after the coronavirus disease 2019 (COVID-19). This paper proposed effective measures and suggestions for responding to RTIs in China. Moreover, this paper aimed to provide some references for studies on RTIs in the future. According to a reference review, 50 articles related to RTIs were published and viewed in the China National Knowledge Infrastructure (CNKI), Wanfang database, Weipu (VIP) database and PubMed/MEDLINE database. Articles were selected according to the exclusion and inclusion criteria and then classified and summarized. Regarding cases, RTIs in China were highest in summer, autumn, and in rural areas and lowest in February. Men, elderly individuals and people living in rural areas were more susceptible to RTIs. In addition, thanks to effective and proactive policies and measures, the number of RTIs and casualties in China has substantially decreased, while there has been a growing number of traffic accidents along with the increase in nonmotor vehicles. However, it is worth noting that the number of RTIs obviously fell during the COVID-19 pandemic due to traffic lockdown orders and home quarantine policies. Nevertheless, accidents related to electric bicycles increased unsteadily because of the reduction in public transportation use at the same time. The factors that cause RTIs in China can be divided into four aspects: human behaviours, road conditions, vehicles and the environment. As a result, measures responding to RTIs should be accordingly proposed. Moreover, the road traffic safety situation in developing countries was more severe than that in developed countries. RTIs in China showed a downward trend attributed to road safety laws and various policies, and the downward trend was more significant during the COVID-19 pandemic owing to traffic lockdowns and home quarantine measures. It is urgent and necessary to promote road traffic safety, reduce injuries, and minimize the burden of injuries in developing countries.

A Random-Parameter Negative Binomial Model for Assessing Freeway Crash Frequency by Injury Severity: Daytime versus Nighttime

This study explored the effects of contributing factors on crash frequency, by injury severity of all, daytime, and nighttime crashes that occurred on freeways. With three injury severity outcomes classified as light injury, minor injury, and severe injury, the effects of the explanatory variables affecting the crash frequency were examined in terms of the crash, traffic, speed, geometric, and sight characteristics. Regarding the model estimations, the lowest AIC and BIC values (2263.87 and 2379.22, respectively) showed the superiority of the random-parameter multivariate negative binomial (RPMNB) model in terms of the goodness-of-fit measure. Additionally, the RPMNB model indicated the highest R2 (0.25) and predictive accuracy, along with a significantly positive α parameter. Moreover, transferability tests were conducted to confirm the rationality of separating the daytime and nighttime crashes. Based on the RPMNB models, several explanatory variables were observed to exhibit relatively stable effects whereas other variables presented obvious variations. This study can be of certain value in guiding highway design and policies and developing effective safety countermeasures.

Alcohol-impaired motorcyclists versus car drivers: A comparison of crash involvement and legal consequence from adjudication data

INTRODUCTION

Driving under the influence (DUI) increases the probability of motor-vehicle collisions, especially for motorcycles with less protections. This study aimed to identify commonalities and differences between criminally DUI offenses (i.e., with a blood alcohol concentration (BAC) of 80 mg/dL or higher) committed by motorcyclists and car drivers.

METHODS

A total of 10,457 motorcycle DUIs and 8,402 car DUIs were compared using a series of logistic regression models, using data extracted from the documents of adjudication decisions by the courts of Jiangsu, China.

RESULTS

The results revealed that offenders from the high-BAC group (i.e., 200 mg/dL or higher) accounted for more than 20% of the total DUI offenses, and were more likely to be involved in a crash and punished with a longer detention. Motorcyclists had a higher likelihood of crash involvement, and were also more likely to be responsible for single-vehicle crashes associated with higher odds of injury sustained, compared to alcohol-impaired car drivers. In the verdict, motorcycle offenders were more likely to receive a less severe penalty.

CONCLUSIONS

Interventions are clearly required to focus on reducing in the high-BAC group of offenders. For alcohol-impaired motorcyclists, their risks of crash and injury against BAC climb more steeply than the risks for car drivers. The factors including frequent occurrences, uncertainty of detection, and short-term sentences may weaken the deterrence effect of the criminalization of motorcycle DUI. Practical Applications: The traffic-related adjudication data support traffic safety analysis. Strategies such as combating motorcycle violations (e.g., unlicensed operators or driving unsafe vehicles), undertaking education and awareness campaigns, are expected for DUI prevention.

Effects of stricter drunk-driving laws on alcohol-related road traffic death, injury, and crash rates in South Korea: A synthetic counterfactual approach using Bayesian structural time-series models

In December 2018, new drunk-driving laws were enacted in Korea to impose stricter penalties and standards for driving under the influence of alcohol. This study aimed to estimate the effects of stricter drunk-driving laws on alcohol-related road traffic death, injury, and crash rates in Korea. Using police-reported traffic accident data and registered vehicle data from 2013 to 2020, monthly road traffic outcome rates were calculated: the response series involved alcohol-related rates and the non-equivalent control series involved total and non-alcohol-related rates. Based on a controlled interrupted time-series design using Bayesian structural time-series models, effects of the laws on alcohol-related road traffic outcome rates were evaluated. After implementation of these laws, the alcohol-related road traffic crash rate decreased by 14.3% (95% credible interval [CrI] -26.8% to -1.9%), alcohol-related road traffic injury rate by 17.6% (95% CrI -31.6% to -3.8%), and alcohol-related minor road traffic injury rate by 20.2% (95% CrI -32.4% to -7.7%). Alcohol-related road traffic death and severe injury rates also decreased more than the declining trends in the pre-period, but reduced non-significantly by 15.0% (95% CrI -47.2% to 17.3%) and 9.9% (95% CrI -33.9% to 14.5%), respectively. The mixed effectiveness of Korea's new drunk-driving laws on alcohol-related road traffic outcomes suggests that additional strategies are necessary to consistently and effectively reduce alcohol-related road traffic outcomes. More research is needed on ways to enhance the effectiveness of drunk-driving laws.

Studies of the effectiveness of transport sector interventions in low- and middle-income countries: An evidence and gap map

BACKGROUND

There are great disparities in the quantity and quality of infrastructure. European countries such as Denmark, Germany, Switzerland, and the UK have close to 200 km of road per 100 km², and the Netherlands over 300 km per 100 km². By contrast, Kenya and Indonesia have <30, Laos and Morocco <20, Tanzania and Bolivia <10, and Mauritania only 1 km per 100 km². As these figures show, there is a significant backlog of transport infrastructure investment in both rural and urban areas, especially in sub-Saharan Africa. This situation is often exacerbated by weak governance and an inadequate regulatory framework with poor enforcement which lead to high costs and defective construction.The wellbeing of many poor people is constrained by lack of transport, which is called "transport poverty". Lucas et al. suggest that up to 90% of the world's population are transport poor when defined as meeting at least one of the following criteria: (1) lack of available suitable transport, (2) lack of transport to necessary destinations, (3) cost of necessary transport puts household below the income poverty line, (4) excessive travel time, or (5) unsafe or unhealthy travel conditions.

OBJECTIVES

The aim of this evidence and gap map (EGM) is to identify, map, and describe existing evidence from studies reporting the quantitative effects of transport sector interventions related to all means of transport (roads, rail, trams and monorail, ports, shipping, and inland waterways, and air transport).

METHODS

The intervention framework of this EGM reframes Berg et al's three categories (infrastructure, prices, and regulations) broadly as infrastructure, incentives, and institutions as subcategories for each intervention category which are each mode of transport (road, rail trams and monorail, ports, shipping, and inlands waterways, and air transport). This EGM identifies the area where intervention studies have been conducted as well as the current gaps in the evidence base.This EGM includes ongoing and completed impact evaluations and systematic reviews (SRs) of the effectiveness of transport sector interventions. This is a map of effectiveness studies (impact evaluations). The impact evaluations include experimental designs, nonexperimental designs, and regression designs. We have not included the before versus after studies and qualitative studies in this map. The search strategies included both academic and grey literature search on organisational websites, bibliographic searches and hand search of journals.An EGM is a table or matrix which provides a visual presentation of the evidence in a particular sector or a subsector. The map is presented as a matrix in which rows are intervention categories (e.g., roads) and subcategories (e.g., infrastructure) and the column outcome domains (e.g., environment) and subcategories as (e.g., air quality). Each cell contains studies of the corresponding intervention for the relevant outcome, with links to the available studies. Included studies were coded according to the intervention and outcomes assessed and additional filters as region, population, and study design. Critical appraisal of included SR was done using A Measurement Tool to Assess Systematic Reviews (AMSTAR -2) rating scale.

SELECTION CRITERIA

The search included both academic and grey literature available online. We included impact evaluations and SRs that assessed the effectiveness of transport sector interventions in low- and middle-income countries.

RESULTS

This EGM on the transport sector includes 466 studies from low- and middle-income countries, of which 34 are SRs and 432 impact evaluations. There are many studies of the effects of roads intervention in all three subcategories-infrastructure, incentives, and institutions, with the most studies in the infrastructure subcategories. There are no or fewer studies on the interventions category ports, shipping, and waterways and for civil aviation (Air Transport).In the outcomes, the evidence is most concentrated on transport infrastructure, services, and use, with the greatest concentration of evidence on transport time and cost (193 studies) and transport modality (160 studies). There is also a concentration of evidence on economic development and health and education outcomes. There are 139 studies on economic development, 90 studies on household income and poverty, and 101 studies on health outcomes.The major gaps in evidence are from all sectors except roads in the intervention. And there is a lack of evidence on outcome categories such as cultural heritage and cultural diversity and very little evidence on displacement (three studies), noise pollution (four studies), and transport equity (2). There is a moderate amount of evidence on infrastructure quantity (32 studies), location, land use and prices (49 studies), market access (29 studies), access to education facilities (23 studies), air quality (50 studies), and cost analysis including ex post CBA (21 studies).The evidence is mostly from East Asia and the Pacific Region (223 studies (40%), then the evidence is from the sub-Saharan Africa (108 studies), South Asia (96 studies), Latin America & Caribbean (79 studies). The least evidence is from Middle East & North Africa (30 studies) and Europe & Central Asia (20 studies). The most used study design is other regression design in all regions, with largest number from East Asia and Pacific (274). There is total 33 completed SRs identified and one ongoing, around 85% of the SR are rated low confidence, and 12% rated as medium confidence. Only one review was rated as high confidence. This EGM contains the available evidence in English.

CONCLUSION

This map shows the available evidence and gaps on the effectiveness of transport sector intervention in low- and middle-income countries. The evidence is highly concentrated on the outcome of transport infrastructure (especially roads), service, and use (351 studies). It is also concentrated in a specific region-East Asia and Pacific (223 studies)-and more urban populations (261 studies). Sectors with great development potential, such as waterways, are under-examined reflecting also under-investment.The available evidence can guide the policymakers, and government-related to transport sector intervention and its effects on many outcomes across sectors. There is a need to conduct experimental studies and quality SRs in this area. Environment, gender equity, culture, and education in low- and middle-income countries are under-researched areas in the transport sector.

Analysis and prediction of intersection traffic violations using automated enforcement system data

The automated enforcement system (AES) is an effective way of supplementing traditional traffic enforcement, and the traffic violation data from AES can also be effectively used for safety research. In this study, traffic violation data were used to analyze the influencing factors associated with traffic violations and to predict the probability of violations at intersections. The potential factors influencing violations include 24 independent factors related to time, space, traffic and weather. Results from a logistic model showed that the midday period, weekends, residential districts, collector roads, congested traffic conditions, high traffic flow, lower wind speed and low temperature would increase the probability of traffic violations. The probability of violations was predicted by the random forest algorithm, which was proven to be the best traffic violation prediction model among logistic regression, Gaussian naive Bayes, and support vector machine. Moreover, the proximity weighted synthetic oversampling technique (ProWSyn) method was applied to reduce the impact of the imbalance ratio (IR) and improve the model's prediction performance. The receiver operating characteristics (ROC) curves and Precision-Recall (PR) curves illustrated that the random forest algorithm using oversampling data had the best classifier prediction performance than undersampling data. The area under curve (AUC) and out-of-bag (OOB) error with IR = 1 reached 0.914 and 0.0787, which showed the better performance of the random forest algorithm using ProWSyn in dealing with imbalanced traffic violation data.

Time-varying effect of drunk driving regulations on road traffic mortality in Guangzhou, China: an interrupted time-series analysis

Background

China has introduced a series of stricter policies to criminalize drunk driving and increase penalties since May 2011. However, there is no previous study examining the time-varying impacts of drunk driving regulations on road traffic fatalities based on daily data.

Methods

We collected 6536 individual data of road traffic deaths (RTDs) in Guangzhou from 2008 to 2018. The quasi-Poisson regression models with an inclusion of the intervention variable and the interaction of intervention variable and a function of time were used to quantify the time-varying effects of these regulations.

Results

During the 11-year study period, the number of population and motor vehicles showed a steady upward trend. However, the population- and motor vehicles- standardized RTDs rose steadily before May 2011, the criminalizing drunk driving intervention was implemented and gradually declined after that. The new drunk driving intervention were associated with an average risk reduction of RTDs (ER = -9.01, 95% eCI: − 10.05% to − 7.62%) during the 7.7 years after May 2011. On average, 75.82 (95% eCI, 54.06 to 92.04) RTDs per 1 million population annually were prevented due to the drunk driving intervention.

Conclusion

These findings would provide important implications for the development of integrated intervention measures in China and other countries attempting to reduce traffic fatalities by stricter regulations on drunk driving.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11958-4.

Revised road traffic safety law and years of life lost due to traffic deaths in China, 2002-2019

Legal intervention is a powerful tool to reduce road traffic injuries (RTIs). China amended the Road Traffic Safety Law in 2011, but the impact of amended law on traffic crash deaths is still unknown. In this study, we conducted an interrupted time series analysis and examined years of life lost (YLLs) per 100,000 population as the assessment indicator to evaluate the association of road traffic safety law and traffic crash mortality. Annual YLLs data due to traffic deaths from 2002 to 2019 in China were obtained from the Global Burden of Disease (GBD) 2019. After implementation of the revised law, the average level of total YLLs per 100,000 population due to traffic deaths decreased from 1133.14 to 848.87, and the slope of annual YLLs per 100,000 population decreased by 30.11 (95% CI: 22.46, 37.75), indicating a steeper downward trend. The revised traffic law was associated with YLLs reduction due to traffic deaths for males, females, all age groups, pedestrians, motor vehicle users, and other road users, as well as traffic deaths attributed to alcohol use and tobacco use. These findings suggested that the revised Road Traffic Safety Law improved road safety by decreasing YLLs due to traffic deaths in China. However, the burden of RTIs is still heavy and efforts to further improve traffic laws and the adoption of other interventions are urgently needed.

Road injury burden in Mexico 1990 to 2019: Secondary data analysis from the Global Burden of Disease Study

Road injuries have been a major cause of premature mortality and disability in Mexico. The objective of this paper is to report the findings from the Global Burden of Disease study (GBD-2019) on road injuries in Mexico at a national and subnational scale from 1990 to 2019, and to assess the association between road injury burden and the socio-demographic index. Following the 2019 Global Burden of Disease study road injury mortality, premature mortality, the years lived with disability and disability-adjusted life-years (DALYs) are reported. While the number of deaths from road injuries increased between 1990 and 2019, the age-standardized mortality rates declined. Pedestrian road injuries and motor vehicle road injuries accounted for 8 of every 10 deaths from road injury in 2019. Road injury mortality and DALY rates decreased nationally, but stagnated since 2011. The road injury burden was higher for men in all age groups. Pedestrian and motor vehicle road injuries caused the highest DALY rate in both males and females. There was no significant association between the SDI and the road injury age-standardized DALY rates. This study presents a comprehensive report of road injury burden of disease in Mexico. Mexico continues to have an incomplete, fragmented and poorly enforced legislative framework, with a large diversity between its 32 states. Thus, an integrated legislative and juridical effort is needed to continue reducing the road injury disease burden, which is tailored for specific age groups, vulnerable road users and high-burden areas.