A time series study on the effects of cold temperature on road traffic injuries in Seoul, Korea

Association between High Ambient Temperatures and Road Crashes in an Australian City with Temperate Climate: A Time-Series Study, 2012-2021

(1) Background: High ambient temperatures are associated with increased morbidity and mortality rates, and some evidence suggests that high temperatures increase the risk of road crashes. However, little is known regarding the burden of road crashes attributable to no-optimal high temperatures in Australia. Therefore, this study examined the effects of high temperatures on road crashes using Adelaide in South Australia as a case study. (2) Methods: Ten-year daily time-series data on road crashes (n = 64,597) and weather during the warm season (October-March) were obtained between 2012 and 2021. A quasi-Poisson distributed lag nonlinear model (DLNM) was used to quantify the cumulative effect of high temperatures over the previous five days. The associations and attributable burden at moderate and extreme temperature ranges were computed as relative risk (RR) and attributable fraction. (3) Results: There was a J-shaped association between high ambient temperature and the risk of road crashes during the warm season in Adelaide, and pronounced effects were observed for minimum temperatures. The highest risk was observed at a 1 day lag and lasting for 5 days. High temperatures were responsible for 0.79% (95% CI: 0.15-1.33%) of road crashes, with moderately high temperatures accounting for most of the burden compared with extreme temperatures (0.55% vs. 0.32%). (4) Conclusions: In the face of a warming climate, the finding draws the attention of road transport, policy, and public health planners to design preventive plans to reduce the risk of road crashes attributable to high temperatures.

Factors affecting the number of road traffic accidents in Kerman province, southeastern Iran (2015-2021)

Road traffic accidents (RTAs) are among the top causes of mortality and disability globally, particularly in developing nations like Iran. In this study, RTAs were analyzed to develop precise predictive models for predicting the frequency of accidents in the Kerman Province (southeastern Iran) using the autoregressive integrated moving average (ARIMA) and autoregressive integrated moving average with explanatory variables (ARIMAX) modeling methods. The findings demonstrate that including factors regarding humans, vehicles, and elements of nature in the time-series analysis of accident records resulted in the development of a more reliable prediction model than utilizing only aggregated accident count. The understanding of safety on the road is increased by this research, which also offers a method for forecasting that utilizes a variety of parameters relating to people, cars, and the environment. The findings of this research are likely to contribute to lowering the incidence of RTAs in Iran.

Impact of high temperature on road injury mortality in a changing climate, 1990-2019: A global analysis

BACKGROUND

Previous studies have shown that extreme heat likely increases the risk of road injuries. However, the global burden of road injuries due to high temperature and contributing factors remain unclear. This study aims to characterize the global, regional and national burden of road injuries due to high temperature from 1990 to 2019.

METHODS

Based on the Global Burden of Disease (GBD) study 2019, we obtained the numbers and age-standardized mortality rates (ASMR) and age-standardized disability-adjusted life years (DALY) rates (ASDR) of the road injury due to high temperature at global, regional, and national levels from 1990 to 2019. The world is divided into five climate zones according to the average annual temperature of each country: tropical, subtropical, warm temperate, cold temperate, and boreal. We used the generalized additive models (GAM) to model the trends of road injuries globally and by region.

RESULTS

Globally, between 1990 and 2019, the deaths of road injury attributable to high temperature increased significantly from 20,270 (95% uncertainty interval [UI], 7836 to 42,716) to 28,396 (95% UI, 13,311 to 51,178), and the DALYs increased from 1,169,309 (95% UI, 450,834 to 2,491,075) to 1,414,527 (95% UI, 658,347 to 2,543,613). But the ASMR and the ASDR slightly decreased by 8.49% and 13.16%, respectively. The burden of road injury death attributable to high temperature remained high in low SDI and tropical regions. In addition, road transport infrastructure investment per inhabitant is associated with the burden of road injuries attributable to high temperature.

CONCLUSIONS

Globally, the ASMR and ASDR for road injuries attributable to high temperature decreased from 1990 to 2019, but the absolute death and DALYs continued to increase. Thus, concerning global warming, implementation of prevention and interventions to reduce road injuries from heat exposure should be stressed globally.

High, low, and non-optimum temperatures exposure on road injuries in a changing climate: a secondary analysis based on the Global Burden of Disease Study 2019

Global warming in the twenty-first century has gradually made high temperatures a major threat to the global population. Health problems associated with extreme temperatures have become a growing public health concern worldwide. This study aimed to estimate road injuries stratified by sex, age, geographic location, and sociodemographic status attribute to high, low, and non-optimal temperatures in 21 regional and global. We used the Global Burden of Disease (GBD) Study Results Tool to examine the age-standardized death rates (ASDR) and disability-adjusted life years (DALYs) due to road injuries in 2019 by Joinpoint regression. In addition, we reported high, low, and non-optimal temperature exposures for road injuries across different groups by gender, age, region, and disease. Moreover, we examined temporal trends in the burden of road disease caused by high, low, and non-optimum temperatures from 1990 to 2019. Trend analyzes were conducted for five sociodemographic index (SDI) regions. Globally, both ASDR and DALY declined from 1990 to 2019, with average annual percent change (AAPC) values of - 1.3% and - 1.2%, respectively. In 2019, the indicators (death and DALYs) steadily declined, while SDI quintile increased in most regions. Road injuries related to death and DALYs rate attributed to high temperatures were 0.17 and 8.50, respectively, in 2019. From 1990 to 2019, DALYs for road injuries caused by low temperatures showed the most significant upward trend in most regions, especially in low-latitude countries. This study provides a comprehensive understanding of the road injury burden caused by high, low, and non-optimum temperatures, which remains high in regions with low SDI. Therefore, special attention should be paid to road injuries in poor countries or in areas with extreme temperatures.

Extreme environmental temperatures and motorcycle crashes: a time-series analysis

Extreme temperature could affect traffic crashes by influencing road safety, vehicle performance, and drivers' behavior and abilities. Studies evaluating the impacts of extreme temperatures on the risk of traffic crashes have mainly overlooked the potential role of vehicle air conditioners. The aim of this study, therefore, was to evaluate the effect of exposure to extreme cold and hot temperatures on seeking medical attention due to motorcycle crashes. The study was conducted in Iran by using medical attendance for motorcycle crashes from March 2011 to June 2017. Data on daily minimum, mean and maximum temperature (°C), relative humidity (%), wind velocity (km/h), and precipitation (mm/day) were collected. We developed semi-parametric generalized additive models following a quasi-Poisson distribution with the distributed nonlinear lag model to estimate the immediate and lagged associations (reported as relative risk [RR], and 95% confidence interval [CI]). Between March 2011 and June 2017, 36,079 medical attendances due to motorcycle road traffic crashes were recorded (15.8 ± 5.92 victims per day). In this time period, the recorded temperature ranged from -11.2 to 45.4 °C (average: 25.5 ± 11.0 °C). We found an increased risk of medical attendance for motorcycle crashes (based on maximum daily temperature) at both extremely cold (1st percentile) and hot (99th percentile) temperatures and also hot (75th percentile) temperatures, mainly during lags 0 to 3 days (e.g., RR: 1.12 [95% CI: 1.05: 1.20]; RR: 1.08 [95% CI: 1.01: 1.16]; RR: 1.20 [95% CI: 1.09: 1.32] at lag0 for extremely cold, hot, and extremely hot conditions, respectively). The risk estimates for extremely hot temperatures were larger than hot and extremely cold temperatures. We estimated that 11.01% (95% CI: 7.77:14.06) of the medical attendance for motorcycle crashes is estimated to be attributable to non-optimal temperature (using mean temperature as exposure variable). Our findings have important public health messaging, given the considerable burden associated with road traffic injury, particularly in low- and middle-income countries.

Temporal-spatial evolution analysis of severe traffic violations using three functional forms of models considering the diurnal variation of meteorology

Traffic violations and crashes are inherently associated. Analysis of traffic violation frequency is a prerequisite for improvements in crash prevention and corresponding countermeasures. One of the essential works in the field of traffic violations relates to the exploration of the correlations between a certain violation type (e.g., speeding or safety belt use) and its causal factors (e.g., demographics and road types). Till now, the effects of spatiotemporal and meteorological factors on severe traffic violations, a general term for dangerous driving behaviors, have not been fully considered. Using the dataset consisting of daily severe traffic violations and meteorological conditions during 12 months in Jiangsu Province, China, violation performance functions were developed for three violation types (total violations, driving under the influence, and speeding) based on three models (Poisson regression, zero-inflated Poisson regression, and negative binomial model). The findings indicate that the negative binomial model has a better performance for traffic violation frequency estimation. Additionally, elastic analysis for three violation types relying on the negative binomial model was conducted to present the relationships between the explanatory variables and the expected violation frequency. The effects of spatiotemporal factors have revealed that the violation situations are significantly different in varying cities and the frequency of drunk driving shows a significant time instability. It is also found that rainy days will generate a decrease in the possibility of violation occurrence. With regard to temperature, a significant negative effect is found and the decrease in temperature will bring about an increase in violation frequency. Besides, traffic violation frequency is significantly increased during holidays with comfortable weather conditions. The conclusion of this study can provide insightful suggestions for the department of traffic enforcement to adjust the patrol plans according to the specified periods (weeks, months, or holidays) and weather conditions. Special rectification actions and targeted educational activities are also advised to be put forward simultaneously.

Ambient temperatures associated with increased risk of motor vehicle crashes in New York and Chicago

Motor Vehicle Crashes (MVC) are a major cause of death and disability worldwide. Yet it remains unknown to what extent changes in cold and hot temperatures affect the MVC. Here we quantify the linkage between ambient temperature exposure and the MVC risk of the driver in four cities of the United States. After adjusting for confounding factors, we find both a cold effect and a hot effect on MVC in New York, and a cold effect on MVC in Chicago. A 1 °C decrease in mean daily temperature below a cold threshold of -4.8 °C is associated with an increase in the overall cumulative relative risk of MVC by 11.59% (95% CI: 5.17%-16.43%) over 0-28 lag days for New York. The respective risk increase is 1.58% (95% CI: 0.36%-2.79%) over 0-2 lag days for a 1 °C increase in mean daily temperature above the hot threshold of 26.1 °C for New York. There is no significant heat wave or cold spell effects except for the heat wave effect on the consecutive heat wave days 7-10 in New York. Our study provides evidence of the association between driver exposure to low or high temperatures and the MVC risk. Improved public- administration preventive measures and policymaking are needed to minimize the negative consequences of abnormal temperatures on road safety driving.

The relationship between ambient temperatures and road traffic injuries: a systematic review and meta-analysis

Traffic accidents cause considerable economic losses and injuries. Although the adverse effects of a change in ambient temperatures on human health have been widely documented, its effects on road traffic safety are still debated. This systematic review and meta-analysis was performed to synthesize available data on the association between ambient temperature and the risks of road traffic accidents (RTAs) and traffic accident injuries (TAIs). We searched 7 different databases to locate studies. The subgroup analyses were stratified by temperature type, temperature exposure, region, mean temperature, mortality, study period, statistical model, and source of injury data. This study was registered with PROSPERO under the number CRD42021264660. This is the first meta-analysis to investigate the association between ambient temperature and road traffic safety. A total of 34 high-temperature effect estimates were reported, and two additional studies reported the relationship between low temperatures and TAI risk. The meta-analysis results found a significant association between the high temperature and RTAs, and the pooled RR was 1.025 (95%CI 1.014, 1.035). The risk of TAI was also significantly associated with temperature increases. Subgroup analyses found that using daily mean temperatures, the RR value of road traffic accidents was 1.024 (95%CI 0.939, 1.116), and the RR value of road traffic injuries was 1.052 (95%CI 1.024, 1.080). Hourly temperatures significantly increased the risk of RTA, while the risk of TAI was not significantly increased by hourly temperature. The sensitivity analysis indicated that the results were stable, and no obvious publication bias was detected. The results of this systematic review and meta-analysis suggest that increases in ambient temperature are associated with an increased risk of RTAs and TAIs. These findings add to the evidence of the impact of ambient temperature on road traffic safety.

Universal thermal climate index associations with mortality, hospital admissions, and road accidents in Bavaria

When meteorological conditions deviate from the optimal range for human well-being, the risks of illness, injury, and death increase, and such impacts are feared in particular with more frequent and intense extreme weather conditions resulting from climate change. Thermal indices, such as the universal thermal climate index (UTCI), can better assess human weather-related stresses by integrating multiple weather components. This paper quantifies and compares the seasonal and spatial association of UTCI with mortality, morbidity, and road accidents in the federal state of Bavaria, Germany. Linear regression was applied to seasonally associate daily 56 million hospital admissions and 2.5 million death counts (1995-2015) as well as approximately 930,000 road accidents and 1.7 million people injured (2002-2015) with spatially interpolated same day- and lagged- (up to 14 days) average UTCI values. Additional linear regressions were performed stratifying by age, gender, region, and district. UTCI effects were clear in all three health outcomes studied: Increased UTCI resulted in immediate (1-2 days) rises in morbidity and even more strongly in mortality in summer, and lagged (up to 14 days) decreases in fall, winter, and spring. The strongest UTCI effects were found for road accidents where increasing UTCI led to immediate decreases in daily road accidents in winter but pronounced increases in all other seasons. Differences in UTCI effects were observed e.g. between in warmer north-western regions (Franconia, more districts with heat stress-related mortality, but hospital admissions for lung, heart and external reasons decreasing with summer heat stress), the touristic alpine regions in the south (immediate effect of increasing UTCI on road accidents in summer), and the colder south-eastern regions (increasing hospital admissions for lung, heart and external reasons in winter with UTCI). Districts with high percentages of elderly suffered from higher morbidity and mortality, particularly in winter. The influences of UTCI as well as the spatial and temporal patterns of this influence call for improved infrastructure planning and resource allocation in the health sector.

Association between extreme ambient temperatures and general indistinct and work-related road crashes. A nationwide study in Italy

Despite the relevance of road crashes and their impact on social and health care costs, the effects of extreme temperatures on road crashes risk have been scarcely investigated, particularly for those occurring in occupational activities. A nationwide epidemiological study was carried out to estimate the risk of general indistinct and work-related road crashes related with extreme temperatures and to identify crash and occupation parameters mostly involved. Data about road crashes, resulting in death or injury, occurring during years 2013-2015 in Italy, were collected from the National Institute of Statistics, for general indistinct road crashes, and from the compensation claim applications registered by the national workers' compensation authority, for work-related ones. Time series of hourly temperature were derived from the results provided by the meteorological model WRF applied at a national domain with 5 km resolution. To consider the different spatial-temporal characteristics of the two road crashes archives, the association with extreme temperatures was estimated by means of a case-crossover time-stratified approach using conditional logistic regression analysis, and a time-series analysis, using over-dispersed Poisson generalized linear regression model, for general indistinct and work-related datasets respectively. The analyses were controlled for other covariates and confounding variables (including precipitation). Non-linearity and lag effects were considered by using a distributed lag non-linear model. Relative risks were calculated for increment from 75th to 99th percentiles (hot) and from 25 to first percentile (cold) of temperature. Results for general indistinct crashes show a positive association with hot temperature (RR = 1.12, 95 % CI: 1.09-1.16) and a negative one for cold (RR = 0.93, 95 % CI: 0.91-0.96), while for work-related crashes a positive association was found for both hot and cold (RR = 1.06 (95 % CI: 1.01-1.11) and RR = 1.10 (95 % CI: 1.05-1.16). The use of motorcycles, the location of accident (urban vs out of town), presence of crossroads, as well as occupational factors like the use of a vehicle on duty were all found to produce higher risks of road crashes during extreme temperatures. Mitigation and prevention measures are needed to limit social and health care costs.

Short-term effects of ambient temperature and road traffic accident injuries in Dalian, Northern China: A distributed lag non-linear analysis

BACKGROUND

Although traffic accidents cause considerable economic losses and injuries to individuals, families, and communities, little is known about the impact of meteorological factors on the incidence of traffic accident injuries (TAIs). Therefore, a time-series study was conducted to explore the effect of meteorological variables on TAIs in Dalian, Northern China.

METHODS

Poisson generalized linear models (PGLM) combined with distributed lag nonlinear models (DLNM) were used to estimate the association between daily TAIs and ambient temperature in Dalian, China, 2015-2017. The injury data collected by Dalian national injury surveillance hospitals, and meteorological data were extracted and accumulated from the National Meteorological Information Center. Modified the model with variables such as pressure, humidity, precipitation, PM_2.5, SO₂, O₃, day of the week, seasonality, and time trend. In the subgroup analysis, the modification effects of gender and age were also examined.

RESULTS

Both high temperatures (RR = 1.198, 95％CI：1.017-1.411) and low temperatures (RR = 1.017, 95％CI：1.001-1.035) increased the risk of TAIs. The cumulative lag effect would last until after the 7th day. While the 40-59 years subgroup seemed to be more vulnerable in high temperature environments, those who are more than 60 years showed higher TAIs in low temperatures for both single-day and cumulative TAI risks.

CONCLUSIONS

Identifying the association between ambient temperature and traffic injuries could provide needed scientific evidence for relevant public health actions.

Association between ambient temperature and injury by intentions and mechanisms: A case-crossover design with a distributed lag nonlinear model

Although injury is a leading cause of death worldwide, the association between ambient temperature and injury has received little research attention compared to the association of temperature with mortality and morbidity from non-external causes. With current climate change and increases in weather extremes, assessing the association between temperature and injury is important for determining public health priorities. Therefore, the present study examined the association between ambient temperature and injury risk with a focus on the intentions and mechanisms of injury. Using the national emergency database, we identified a total of 703,503 injured patients who had visited emergency departments in Seoul, South Korea from 2008 to 2016. We conducted a time-stratified case-crossover study using a conditional Poisson regression model, and applied a distributed lag nonlinear model to explore possible nonlinear and delayed effects of daily mean temperature on injury risk. Injury risk was significantly associated with ambient temperature, and temperature-injury association curves markedly differed with respect to intentions and mechanisms of injury. Although unintentional injuries increased significantly at both high and low temperatures, intentional injuries - including self-harm and assault - significantly increased only at high temperatures. The mechanism-specific analyses showed that injuries caused by traffic accidents and burns significantly increased at both high and low temperatures. However, injuries caused by all other mechanisms (i.e., fall, blunt object, machinery, penetration, and poisoning) significantly increased only at high temperatures, while injury due to slipping increased at low temperatures. Our study provides evidence that ambient temperature is associated with risk of injury, and this association differs depending on the intentions and mechanisms of injury. Overall, our findings help foster a more comprehensive understanding of the association between temperature and injury that can be used to establish appropriate public health policies and targeted interventions.

Effects of hourly precipitation and temperature on road traffic casualties in Shenzhen, China (2010-2016): A time-stratified case-crossover study

BACKGROUND

Although road traffic casualty (RTC) is preventable, it remains the eighth leading cause of death globally, especially in developing countries. Previous studies suggested the association between RTC and monthly or daily weather conditions, while the acute effects of weather conditions on an hourly timescale remains unknown. This study aims to quantify hourly effects of precipitation and temperature on RTC.

METHODS

Using ambulance records on RTC during 2010-2016 for the whole population in Shenzhen, China, we conducted a time-stratified case-crossover design which can inherently control for hour of the day, day of the week, seasonality, time trends and potential time-invariant confounders. Conditional quasi-Poisson regression with distributed lag nonlinear model was used to determine the effects of hourly precipitation and temperature on RTC.

RESULTS

Light and heavy precipitation increased RTC in current and following 2 h by 8.09% (95% CI: 4.20-12.12%) and 11.62% (95% CI: 5.93-17.62%), respectively. A J-shaped temperature-RTC curve revealed that each 1 °C increment above 17 °C were associated with a 0.87% (0.52-1.22%) increase in RTC. High temperature accounted for 6.44% (95% CI: 3.95-8.91%) of all RTC, with a high fraction of 10.64% (95% CI: 4.33-15.96%) during warm season and 8.30% (95% CI: 4.26-12.66%) in traffic peak hours. Precipitation contributed to 0.68% (95% CI: 0.44-0.92%) of RTC within 3 h. The middle-aged and female suffered more from precipitation-associated RTC, and the younger suffered more from high temperature-associated RTC.

CONCLUSIONS

High temperature increased substantially hourly RTC. Precipitation was also a risk factor of RTC and the adverse effect lasted for 3 h. The findings would be helpful to guide the development of targeted intervention to accelerate progress in road traffic safety.

A Multilevel Model Approach for Investigating Individual Accident Characteristics and Neighborhood Environment Characteristics Affecting Pedestrian-Vehicle Crashes

Walking is the most basic movement of humans and the most fundamental mode of transportation. To promote walking, it is necessary to create a safe environment for pedestrians. However, pedestrian-vehicle crashes still remain relatively high in South Korea. This study employs a multilevel model to examine the differences between the lower-level individual characteristics of pedestrian crashes and the upper-level neighborhood environmental characteristics in Seoul, South Korea. The main results of this study are as follows. The individual characteristics of pedestrian-vehicle crashes are better at explaining pedestrian injury severity than built environment characteristics at the neighborhood level. Older pedestrians and drivers suffer more severe pedestrian injuries. Larger vehicles such as trucks and vans are more likely to result in a high severity of pedestrian injuries. Pedestrian injuries increase during inclement weather and at night. The severity of pedestrian injuries is lower at intersections and crosswalks without traffic signals than at crosswalks and intersections with traffic signals. Finally, school zones and silver zones, which are representative policies for pedestrian safety in South Korea, fail to play a significant role in reducing the severity of pedestrian injuries. The results of this study can guide policymakers and planners when making decisions on how to build neighborhoods that are safer for pedestrians.

Research Trends in Agenda-setting for Climate Change Adaptation Policy in the Public Health Sector in Korea

Many studies have been conducted to assess the health effects of climate change in Korea. However, there has been a lack of consideration regarding how the results of these studies can be applied to relevant policies. The current study aims to examine research trends at the agenda-setting stage and to review future ways in which health-related adaptation to climate change can be addressed within national public health policy. A systematic review of previous studies of the health effects of climate change in Korea was conducted. Many studies have evaluated the effect of ambient temperature on health. A large number of studies have examined the effects on deaths and cardio-cerebrovascular diseases, but a limitation of these studies is that it is difficult to apply their findings to climate change adaptation policy in the health sector. Many infectious disease studies were also identified, but these mainly focused on malaria. Regarding climate change-related factors other than ambient temperature, studies of the health effects of these factors (with the exception of air pollution) are limited. In Korea, it can be concluded that studies conducted as part of the agenda-setting stage are insufficient, both because studies on the health effects of climate change have not ventured beyond defining the problem and because health adaptation to climate change has not been set as an important agenda item. In the future, the sharing and development of relevant databases is necessary. In addition, the priority of agenda items should be determined as part of a government initiative.

The Impacts of Climate Change on Road Traffic Accidents in Saudi Arabia

The potential costs of road traffic accidents (RTAs) to society are immense. Yet, no study has attempted to examine the impact of climate change on RTAs in Saudi Arabia, though RTA-leading deaths are very high, and the occurrence of climatic events is very frequent. Therefore, this study aims to assess the impact of climate change on RTAs in Saudi Arabia and to recommend some climate change mitigation and adaptation policies to make roads safe for all. This study employed annual data from 13 regions of Saudi Arabia, from 2003 to 2013. The data were analyzed on the basis of panel regression models—fixed effect, random effect, and the pooled ordinary least square. The findings show that temperature, rainfall, sandstorms, and number of vehicles were statistically and significantly responsible for RTAs in Saudi Arabia in the study period. This study also found that RTAs both inside and outside cities significantly caused injuries, but only RTAs inside cities significantly caused death. Furthermore, the death from RTAs injuries was found to be statistically significant only for motor vehicle accidents. The findings will assist policymakers in taking the right courses of action to mitigate the negative impacts of climate change through understanding climate influence on RTAs.

Climate conditions and work-related fatigue among professional drivers

The possible associations between climate parameters and drivers' fatigue have not been subject to specific studies thus far. We have undertaken a study to investigate whether the particular climate parameters are related to fatigue perception by motor vehicle drivers. The study was performed from July to October. Each driver was surveyed four times: before and after workshift on a monotonous route outside the city center (MR), and on a heavy traffic route in the city center (HTR). The study was conducted among 45 city bus drivers aged 31-58 years (43.7 ± 7.9), seniority as driver 3-34 years (14.7 ± 8.6). Data on climate conditions (ambient temperature, air pressure, humidity, wind speed, precipitations) on particular study days was obtained from the Institute of Meteorology and Water Management, National Research Institute Warsaw, Poland. Fatigue was assessed using the Fatigue Assessment Questionnaire, developed at Nofer Institute of Occupational Medicine (Lodz, Poland). The total level of fatigue was significantly (p = 0.045) higher after driving on HTR than on MR. The number of symptoms was also significantly higher (p < 0.05) among drivers working on HTR. After MR, significant correlations were found between wind speed and heavy eyelid feeling, being prone to forgetting, eye strain, frequent blinking, and between ambient temperature and feeling thirsty. After HTR feeling thirsty, tiredness and difficulty in making decisions correlated with ambient temperature and feeling thirsty with wind speed. Climate conditions can modify the drivers fatigue; therefore, we should be aware of their impact on well-being.

Effects of ambient temperature on ambulance emergency call-outs in the subtropical city of Shenzhen, China

The associations between meteorological factors and mortality have been well documented worldwide, but limited evidence is available for the non-fatal health impacts of ambient temperature, particularly there are few population-based investigations on the impacts of emergency ambulance dispatches in Asia. In this study, based on 809,906 ambulance emergency call-outs (AECOs) for the total population from 2010-2016 in the subtropical city of Shenzhen, China, a Poisson regression combined with a distributed lag nonlinear model was used to simultaneously assess the nonlinear and lag effects of daily mean temperature on AECOs. Stratified analyses by age and sex were performed to identify vulnerable subpopulations. A U-shaped relationship was found between temperature and AECOs. Cold effects were delayed and persisted for 3-4 weeks, with a cumulative relative risk (RR) and 95% confidence interval (CI) of 1.23 (1.10-1.38) and 1.25 (1.16-1.35) over lag 0-28 when comparing the 1st and 5th percentile of the temperature distribution to the optimal (i.e. minimum AECOs) temperature, respectively. Hot effects were immediate and diminished quickly in 5 days, with an increase of 19% (RR = 1.19, 95%CI: 1.14-1.23) and 21% (RR = 1.21, 95%CI: 1.16-1.26) in AECOs over lag 0-5 when comparing the 95th and 99th percentile of temperature to the optimal temperature. Children and the elderly were more vulnerable to cold effects. The youth and middle-aged people suffered more from high temperature. The effects of temperature were similar between males and females. In summary, significant increases were observed in the frequency of AECOs during cold and hot days, and the weather-associated increases in AECOs are different among age groups. This information has valuable implications in ambulance demand prediction and service provision planning.

Are hospital emergency department visits due to dog bites associated with ambient temperature? A time-series study in Beijing, China

BACKGROUND

It is well documented that suboptimal ambient temperature is associated with cardiovascular and respiratory diseases. However, no study has examined the relation between temperature and dog bites.

OBJECTIVES

To study the association between ambient temperature and daily hospital emergency department visits due to dog bites (EDVDBs) in Beijing, China; and to explore whether the temperature-EDVDB association varies by sex and age.

METHODS

Daily EDVDBs were collected from a hospital appointed for dog bites in Beijing during 2012-2014. A quasi-Poisson regression with distributed lag non-linear model (DLNM) was employed to estimate the impact of temperature on daily EDVDBs. Stratified analysis was performed to examine the temperature-EDVDB association by sex and age-groups. Sensitivity analysis was performed to check the robustness of the results by adjusting other meteorological variables and air pollutants.

RESULTS

A total of 42,481 EDVDBs were collected, with daily cases ranged from 15 to 71. The association between temperature and EDVDBs was U-shaped, with extreme cold temperature showing a weaker, delayed and shorter effect on the risk of dog bites while the effect of extreme hot temperature being stronger, more immediate and lasting longer. Cold temperature had a greater impact on female whereas male was more sensitive to hot temperature. The temperature-EDVDB association was unapparent in the 15-21years group. The cold effect was only significant in the 0-14years group whereas all age-groups suffered from the similar heat effect except those aged 22-45years. Adjusting other meteorological variables and air pollutants did not change the results.

CONCLUSIONS

The impact of temperature on EDVDBs is U-shaped in Beijing, China which varies by sex and age. The temperature effect is independent from other meteorological variables and air pollutants.

Road safety and road traffic accidents in Saudi Arabia. A systematic review of existing evidence

OBJECTIVES

To identify the changing trends and crucial preventive approaches to road traffic accidents (RTAs) adopted in the Kingdom of Saudi Arabia (KSA) over the last 2.5 decades, and to analyze aspects previously overlooked.

METHODS

This systematic review was based on evidence of RTAs in KSA. All articles published during the last 25 years on road traffic accident in KSA were analyzed. This study was carried out from December 2013 to May 2014 in the Department of Family and Community Medicine, Taibah University, Al-Madinah Al-Munawwarah, KSA.

RESULTS

Road traffic accidents accounted for 83.4% of all trauma admissions in 1984-1989, and no such overall trend was studied thereafter. The most frequently injured body regions as reported in the latest studies were head and neck, followed by upper and lower extremities, which was found to be opposite to that of the studies reported earlier. Hospital data showed an 8% non-significant increase in road accident mortalities in contrast to police records of a 27% significant reduction during the years 2005-2010. Excessive speeding was the most common cause reported in all recent and past studies.

CONCLUSION

Disparity was common in the type of reporting of RTAs, outcome measures, and possible causes over a period of 2.5 decade. All research exclusively looked into the drivers' faults. A sentinel surveillance of road crashes should be kept in place in the secondary and tertiary care hospitals for all regions of KSA.

The association between meteorological factors and road traffic injuries: a case analysis from Shantou city, China

Few studies examined the associations of meteorological factors with road traffic injuries (RTIs). The purpose of the present study was to quantify the contributions of meteorological factors to RTI cases treated at a tertiary level hospital in Shantou city, China. A time-series diagram was employed to illustrate the time trends and seasonal variation of RTIs, and correlation analysis and multiple linear regression analysis were conducted to investigate the relationships between meteorological parameters and RTIs. RTIs followed a seasonal pattern as more cases occurred during summer and winter months. RTIs are positively correlated with temperature and sunshine duration, while negatively associated with wind speed. Temperature, sunshine hour and wind speed were included in the final linear model with regression coefficients of 0.65 (t = 2.36, P = 0.019), 2.23 (t = 2.72, P = 0.007) and -27.66 (t = -5.67, P < 0.001), respectively, accounting for 19.93% of the total variation of RTI cases. The findings can help us better understand the associations between meteorological factors and RTIs, and with potential contributions to the development and implementation of regional level evidence-based weather-responsive traffic management system in the future.

Prediction of vehicle crashes by drivers' characteristics and past traffic violations in Korea using a zero-inflated negative binomial model

AIMS

Traffic safety is a significant public health challenge, and vehicle crashes account for the majority of injuries. This study aims to identify whether drivers' characteristics and past traffic violations may predict vehicle crashes in Korea.

METHODS

A total of 500,000 drivers were randomly selected from the 11.6 million driver records of the Ministry of Land, Transport and Maritime Affairs in Korea. Records of traffic crashes were obtained from the archives of the Korea Insurance Development Institute. After matching the past violation history for the period 2004-2005 with the number of crashes in year 2006, a total of 488,139 observations were used for the analysis. Zero-inflated negative binomial model was used to determine the incident risk ratio (IRR) of vehicle crashes by past violations of individual drivers. The included covariates were driver's age, gender, district of residence, vehicle choice, and driving experience.

RESULTS

Drivers violating (1) a hit-and-run or drunk driving regulation at least once and (2) a signal, central line, or speed regulation more than once had a higher risk of a vehicle crash with respective IRRs of 1.06 and 1.15. Furthermore, female gender, a younger age, fewer years of driving experience, and middle-sized vehicles were all significantly associated with a higher likelihood of vehicle crashes.

CONCLUSIONS

Drivers' demographic characteristics and past traffic violations could predict vehicle crashes in Korea. Greater resources should be assigned to the provision of traffic safety education programs for the high-risk driver groups.