Role of Health Sector in Road Traffic Injuries Prevention: A Public Health Approach.
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SUBMITTER: Azami-Aghdash S
PROVIDER: S-EPMC8631116 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundsThis study aims to estimate and compare the parameters of some univariate and bivariate count models to identify the factors affecting the number of mortality and the number of injured in road accidents.MethodsThe accident data used in this study are related to Kermanshah province in march2020 to march2021. Accidents areas were divided into 125 areas based on density characteristics. In a one-year period, 3090 accidents happened on the suburban roads of Kermanshah province, which resulted in 398 deaths and 4805 injuries. Accident information, including longitude and latitude of accident location, type of accident (fatal and injury), number of deaths, number of injuries, accident type, the reason of the accident, and the kind of accident were all included as population-level variables in the regression models. We investigated four frequently used bivariate count regression models for accident data in the literature.ResultsIn bivariate analysis, except for the DNM model, there is a reasonable decrease in the AIC measures of the saturated model compared to the reduced model for the other three models. For the injury models, MSE is lowest, respectively for DIBP (137.87), BNB (289.46), BP (412.36) and DNM (3640.89) models. These results are also established for death models. But, in univariate analysis, only injury models almost present reasonable results.ConclusionsOur findings show that the IDBP model is better suitable for evaluating accident datasets than other models. Motorcycle accidents, pedestrian accidents, left turn deviance, and dangerous speeding were all significant variables in the IDBP death model, and these parameters were linked to accident mortality.
| S-EPMC9290223 | biostudies-literature
Project description:Background: As the world is busy addressing COVID-19, road traffic injuries, another major cause of death is continuously killing people on the roads. In Nepal, there were frequent media reports of occurrences of road crashes, injuries, and deaths despite nationwide lockdown. This paper aims to describe the situation of road traffic crashes and casualties during the period of complete lockdown. Methods: This study used secondary data from two sources: Nepal Police and media reports between 24 March and 14 June 2020 (because the government lifted the nationwide lockdown from 15 June 2020). Available details of crashes, deaths, and injuries for this period were extracted from media reports and the summary data that was obtained from the Police. We have included data from both sources in the results. Results: Nepal Police recorded 1,801 incidents of road crashes during the 82 days of the COVID-19 lockdown with 256 deaths (on average 3.1 deaths daily) and 1,824 injuries (on average 22.2 injuries daily). Motorcycles comprised over 21% of all vehicles involved in crashes. Ambulances and other vehicles for essential services were also found to be involved in crashes. Speeding itself was the cause for almost a quarter of the incidents during the lockdown. Conclusions: Although a reduction in the number of road crashes and related injuries and fatalities was observed, this reduction was not as substantial as anticipated during the heavy restrictions on vehicular movement imposed during the lockdown. Media reports were mainly found to be reporting the crashes where deaths occurred, but police records also included nonfatal injuries. The incidence of crashes in this period shows that it is important to work for road safety to save lives from road traffic crashes in Nepal.
| S-EPMC7818237 | biostudies-literature
Project description:BackgroundBoth road safety campaigns and epidemiological research into social differences in road traffic injury risk often assume that road traffic injuries occur close to home. While previous work has examined distance from home to site of collision for child pedestrians in local areas, less is known about the geographic distribution of road traffic injuries from other modes. This study explores the distribution of the distance between home residence and collision site (crash distance) by mode of transport, geographic area, and social characteristics in England.MethodsUsing 10 years of road casualty data collected by the police, we examined the distribution of crash distance by age, sex, injury severity, area deprivation, urban/rural status, year, day of week, and, in London only, ethnic group.Results54% of pedestrians, 39% of cyclists, 17% of powered two-wheeler riders and 16% of car occupants were injured within 1 km of home. 82% of pedestrians, 83% of cyclists, 54% of powered two-wheeler and 53% of car occupants were injured within 5 km of home. We found some social and geographic differences in crash distance: for all transport modes injuries tended to occur closer to home in more deprived or urban areas; younger and older pedestrians and cyclists were also injured closer to home. Crash distance appears to have increased over time for pedestrian, cyclist and car occupant injuries, but has decreased over time for powered two-wheeler injuries.ConclusionsInjuries from all travel modes tend to occur quite close to home, supporting assumptions made in epidemiological and road safety education literature. However, the trend for increasing crash distance and the social differences identified may have methodological implications for future epidemiological studies on social differences in injury risk.
| S-EPMC3680192 | biostudies-literature
Project description:This study investigates the important role of attendant factors, such as road traffic victims' access to trauma centres, the robustness of health infrastructure, and the responsiveness of police and emergency services in the incidence of Road Traffic Injuries (RTI) during the pandemic-induced COVID-19 lockdowns. The differential effects of the first and second waves of the pandemic concerning perceived health risk and legal restrictions provide us with a natural experiment that helps us differentiate between the impact of attendant factors and the standard relationship between mobility and Road Traffic Injuries. The authors use the auto-regressive recurrent neural network method on two population levels-Tamil Nadu (TN), a predominantly rural state, and Chennai, the most significant metropolitan city of the state, to draw causal inference through counterfactual predictions on daily counts of road traffic deaths and Road Traffic Injuries. During the first wave of the pandemic, which was less severe than the second wave, the traffic flow was correlated to Road Traffic Death/Road Traffic Injury. In the second wave's partial and post lockdown phases, an unprecedented fall of over 70% in Road Traffic Injury-Grievous as against Road Traffic Injury-Minor was recorded. Attendant factors, such as the ability of the victim to approach relief centres, the capability of health and other allied infrastructures, transportation and medical treatment of road traffic crash victims, and minimal access to other emergency services, including police, assumed greater significance than overall traffic flow in the incidence of Road Traffic Injury in the more severe second wave. These findings highlight the significant role these attendant factors play in producing the discrepancy between the actual road traffic incident rate and the officially registered rate. Thus, our study enables practitioners to observe the mobility-adjusted actual incidence rate devoid of factors related to reporting and registration of accidents.
| S-EPMC9122230 | biostudies-literature
Project description:ObjectivesTo conduct a community survey to estimate the degree to which road traffic injuries (RTIs) are under reported and to compare the characteristics of RTI reported to the police to those not reported.DesignA cross-sectional population-based study.SettingKandy district, Sri Lanka.ParticipantsRTIs and deaths during the preceding 12 months were identified through a community-based cross-sectional survey with a sample size of 3080 households. A stratified multistage cluster sampling with population proportion to size was used. 'Events reported' to the police were cross checked against events in the police records of the given or adjacent police stations, and either were 'Events found' or 'Not found'. 'Under reported' included those 'Not reported' and those reported but 'Not found' in the police dataset.ResultsInformation about 11 724 persons were obtained from 3080 households, identifying 149 persons who suffered an RTI. Of these, 57% were 'Events reported', and of these 43.6% (n=65) were 'Events found' in police records (95% CI, 36.0 to 51.6). There were 42 events 'Not reported' to police while an additional 7 were 'Not found' in the police records of the given police station. Although they were claimed to have been reported to the police, 33% (95% CI 25.8 to 40.7) were 'Under reported'. There were significant differences in age (p=0.02), family income (p<0.001), road user type (p=0.001), injury severity (p<0.001) and injury category (p=0.01) between 'Events found' in the police records and 'Under reported' events.ConclusionsIn the Kandy district, 33% of RTIs were 'under reported'. These findings could be used as evidence for policy planning to prevent RTIs, and highlights the need for a nation-wide community-based survey to determine the true rates of RTI for a better understanding of the reasons for under reporting.
| S-EPMC3822300 | biostudies-literature
Project description:ObjectiveCorrelation analysis and multiple linear regression analysis were conducted to estimate the influence of meteorological factors on road traffic injuries stratified by severity. Crash rate was defined as mean monthly road traffic accidents per 1,000 vectors.DesignEcological time-series study.SettingMacao traffic accident registry database between January 1st, 2001 and November 31st, 2016.ParticipantsIn total, 393,176 traffic accidents and 72,501 cases of road traffic injuries (RTIs) were enrolled; patients' severity was divided into mild injury, required hospitalisation, and death.ExposureVariation of monthly meteorological factors.Main outcome measureWeather-condition-related road traffic accidents, injuries, and deaths.ResultsWindy weather significantly correlated with increased number of traffic accidents among all transport vectors (r = .375 to .637; p < 0.001). Multiple linear regression showed temperature (B = 0.704; p < 0.05) and humidity (B = - 0.537; p < 0.001) were independent factors for mild injury. The role of windy weather was relatively more obvious among patients with severe injuries (B = 0.304; p < 0.001) or those who died (B = 0.015; p < 0.001). A longer duration of sunshine was also associated to RTI-related deaths (B = 0.015; p < 0.001). In total, 13.4% of RTIs were attributable to meteorological factors and may be preventable.ConclusionThe World Health Organization stated that RTIs are a major but neglected public health challenge. This study demonstrates meteorological factors have significant effects on any degree of RTIs. The results may not be generalized to other climates or populations while the findings may have implications in both preventing injuries and to announce safety precautions regarding trauma and motor vehicle collisions to the general public by public agencies.
| S-EPMC6376939 | biostudies-literature
Project description:ObjectivesEvery day, an average of 3,400 deaths and tens of millions of injuries occur as a result of traffic accidents. This study aims to model and validate road traffic injury (RTI) times series, specifically considering gender.Study designTime trend studies of monthly road traffic injuries (RTI) in Iran from March 2005 to February 2016, as well as those of males and females from March 2009 to February 2016 were performed.MethodsThe seasonal auto-regressive integrated moving average method (SARIMA) was employed to predict RTI time series. The final model was selected from various SARIMA models based on the Akaike information criterion (AIC) and the Bayesian information criterion (BIC). To examine whether the residuals were white noise, the Ljung-Box (LB) test and residuals plots were used for un-correlation, and the zero mean and stationarity, respectively. Additionally, smoothing methods were utilized to validate the SARIMA models for fitting and out-of-range prediction of the time series models under study. The sample auto-correlation function (ACF) and the partial autocorrelation function (PACF) with 20 lags were employed to determine the order of models and to ascertain if the residuals of the model were uncorrelated.ResultsBased on the obtained results, SARIMA (2,1,0)(0,1,1)12, SARIMA (0,1,1)(0,1,1)12, SARIMA (1,1,1)(0,0,1)12, and SARIMA (2,0,0)(1,0,0)12 were chosen for the time series including incidence rates of total road traffic injuries (IRTI), IRTI of males, females, and males-to-females, respectively. The AIC values were -87.57, 413.38, -732.91, and -85.32, respectively. The LB test for the residuals of the time series models of (0.539) IRTI, (0.3) IRTI of males, (0.23) females, and (0.237) males-to-females indicated that residuals were uncorrelated. Furthermore, prediction values for the next 24 months (2016 to 2018) showed no decline in the incidence rate of male and female traffic injuries. Results of the predictions using exponential smoothing methods indicated out-of-range prediction validity of the SARIMA models.ConclusionThis study exemplified the high efficiency of SARIMA models in predicting road traffic injuries (RTIs). Based on observations, the IRTI mean in Iran was 35.57 in 2016. The predicted values of the IRTI for 2016-2018 by the SARIMA model showed no decreasing trend. During the studied period, the observed values of IRTI for males were two to three times the female values. Thus, prediction of RTI can provide a useful tool for traffic safety policymaking by simulating interrupted time series when applying new traffic enforcement interventions and regulations in the future. Additionally, IRTI analysis of males and females showed that men had a non-increasing trend but higher incidence of traffic injuries, whereas the IRTI for women revealed an increasing trend from 2009 to 2012 with a lower incidence of injuries. This growth could be attributed to the impact of increased outdoor activities of women and the increased number of issued driving licenses in the period of 2009-2012.
| S-EPMC6508924 | biostudies-literature
Project description:Background: Despite governmental interventions, the Gulf Cooperation Council (GCC) region continues to experience higher road traffic crash and fatality rates relative to Western nations. This trend suggests a potential disconnect between Road Traffic Injuries (RTI) research and the mitigation measures put in place. Method: Here, we present an in-depth bibliometric analysis to obtain a comprehensive understanding of RTI research in the GCC region. The Web of Science database was used to search and retrieve the relevant articles during the period of 1981-2019. Results: The volume of RTI research increased from 2015-2019, suggesting an increased focus on traffic safety in the GCC region. Saudi Arabia had the highest RTI research productivity level (126 publications); Bahrain had the lowest (7 publications). Inconsistent with its low publication volume, Hammad Medical Corps of Qatar had the highest citation impact score of 16.33. Global collaboration for RTI research was highest between Saudi Arabia and the United States. The most prevalent publication journal for the region was Accident Analysis and Prevention. The most common keywords were " road traffic accidents" and " road traffic injuries"; terms such as " mobile phones", " pedestrian safety", " pedestrians", and " distracted driving" were least common. In the five most productive GCC nations with respect to RTI research (Saudi Arabia, United Arab Emirates, Qatar, Kuwait, and Oman), researchers tended to publish works related to road traffic safety in traffic safety-oriented journals. Conclusions: The quantity and quality of RTI publications in GCC is insufficient to meet the increasing related public health and economic burden in the region. The trends among publication volumes, citations, and impact were inconsistent. There is a lack of research collaboration among the institutions. Most of the research related to RTI is being conducted by researchers with a medical background. Research focusing on pedestrians, cyclists and road user behavior is also inadequate.
| S-EPMC7542249 | biostudies-literature
Project description:To estimate the potential years of life lost by road traffic injuries three years after the beginning of the Decade of Action for Traffic Safety.We analyzed the data of the Sistema de Informações sobre Mortalidade (SIM - Mortality Information System) related to road traffic injuries, in 2013. We estimated the crude and standardized mortality rates for Brazil and geographic regions. We calculated, for the Country, the proportional mortality according to age groups, education level, race/skin color, and type or quality of the victim while user of the public highway. We estimated the potential years of life lost according to sex.The mortality rate in 2013 was of 21.0 deaths per 100,000 inhabitants for the Country. The Midwest region presented the highest rate (29.9 deaths per 100,000 inhabitants). Most of the deaths by road traffic injuries took place with males (34.9 deaths per 100,000 males). More than half of the people who have died because of road traffic injuries were of black race/skin color, young adults (24.2%), individuals with low schooling (24.0%), and motorcyclists (28.5%). The mortality rate in the triennium 2011-2013 decreased 4.1%, but increased among motorcyclists. Across the Country, more than a million of potential years of life were lost, in 2013, because of road traffic injuries, especially in the age group of 20 to 29 years.The impact of the high mortality rate is of over a million of potential years of life lost by road traffic injuries, especially among adults in productive age (early mortality), in only one year, representing extreme social cost arising from a cause of death that could be prevented. Despite the reduction of mortality by road traffic injuries from 2011 to 2013, the mortality rates increased among motorcyclists.Estimar os anos potenciais de vida perdidos por acidente de transporte terrestre após três anos do início da Década de Ação pela Segurança no Trânsito.Foram analisados os dados do Sistema de Informações sobre Mortalidade correspondentes aos acidentes de transporte terrestre, em 2013. Foram calculadas as taxas de mortalidade bruta e padronizada para o Brasil e regiões geográficas. Foi calculada, para o País, a mortalidade proporcional segundo faixas etárias, escolaridade, raça/cor da pele e tipo ou qualidade da vítima enquanto usuária da via pública. Foram estimados os anos potenciais de vida perdidos segundo sexo.A taxa de mortalidade, em 2013, foi de 21,0 óbitos por 100 mil habitantes para o País. A região Centro-Oeste apresentou a taxa mais elevada (29,9 óbitos por 100 mil habitantes). A maioria dos óbitos por acidentes de transporte terrestre foi observada no sexo masculino (34,9 óbitos por 100 mil homens). Mais da metade das pessoas que faleceram em decorrência de acidentes de transporte terrestre eram da raça/cor da pele negra, adultos jovens (24,2%), indivíduos com baixa escolaridade (24,0%) e motociclistas (28,5%). A taxa de mortalidade, no triênio 2011 a 2013, apresentou redução de 4,1%, mas aumentou entre os motociclistas. Em todo o País, mais de um milhão de anos potenciais de vida foram perdidos, em 2013, devido aos acidentes de transporte terrestre, especialmente na faixa etária de 20 a 29 anos.O impacto da alta taxa de mortalidade é de mais de um milhão de anos potenciais de vida perdidos por acidentes de transporte terrestre, principalmente entre adultos em idade produtiva (mortalidade precoce), em apenas um ano, representando extremo custo social decorrente de uma causa de óbito que poderia ser prevenida. Apesar da redução da mortalidade por acidentes de transporte terrestre de 2011 a 2013, as taxas de mortalidade aumentaram entre os motociclistas.
| S-EPMC5068963 | biostudies-literature
Project description:ObjectiveRoad traffic injuries (RTIs) are recognized as one of the most important causes of morbidity and mortality throughout the world, especially in developing countries. Human behavior is reportedly one of the critical factors in the occurrence of such injuries. The purpose of this study is to evaluate the correlation of abnormal driving behaviors with the frequency and severity of RTIs among drivers in Hamadan, west of Iran.MethodsThe present cross-sectional study was conducted on 800 people driving, who were selected by multistage cluster sampling technique. Data were collected using a three-part self-administered questionnaire including demographic, social and driving characteristics; the Manchester driver behavior questionnaire (DBQ); as well as information on a history of the occurrence of the injuries caused by the crashes and the severity of them. Data were statistically analyzed using numerical indices, linear regression analysis, Pearson correlation, ordinal logistic regression model and multinomial logistic regression.ResultsThe highest and lowest mean percentages of abnormal driving behavior were related to unintentional violations (19.13) and Lapses (16.44), respectively. "Changing radio stations and listening to music while driving", "overtaking a driver who drives slowly", and "unintentionally exceeding the speed limit" were the three highest behaviors associated with road traffic injuries, with the mean and standard deviation of (1.93 ± 1.4), (1.90±1.4), (1.58±1.3), respectively. Age, gender, educational level, driving experience and driving hours during the day were significantly associated with DBQ dimensions and severity of road traffic injuries.ConclusionsThe results of this study showed that socio-demographic characteristics were significantly correlated with driving behavior. In addition, driving behaviors were correlated with traffic crashes and the resulting injuries. The findings of this study can be utilized to develop driving behavior interventions among the drivers.
| S-EPMC7486081 | biostudies-literature