Paediatric, pedestrian road traffic injuries in the city of Mashhad in north-eastern Iran 2015-2019: a data note.
Ontology highlight
ABSTRACT:
SUBMITTER: Tabari P
PROVIDER: S-EPMC7395334 | biostudies-literature | 2020 Jul
REPOSITORIES: biostudies-literature
Publications
Paediatric, pedestrian road traffic injuries in the city of Mashhad in north-eastern Iran 2015-2019: a data note.
Tabari Parinaz P Shabanikiya Hamidreza H Bagheri Nasser N Bergquist Robert R Hashtarkhani Soheil S Kiani Fatemeh F Mohammadi Alireza A Kiani Behzad B
BMC research notes 20200731 1
<h4>Objectives</h4>The leading factors of paediatric, pedestrian road traffic injuries (PPRTIs) are associated with the characteristics of immediate environment. Spatial analysis of data related to PPRTIs could provide useful knowledge for public health specialists to prevent and decrease the number of accidents. Therefore, we aim to release the datasets which have been used to conduct a multiple-scale spatial analysis of PPRTIs in the city of Mashhad, Iran, between 2015-2019.<h4>Data descriptio ...[more]
Similar Datasets
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: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:Child pedestrian road traffic injuries (RTIs) are an important cause of death and disability in poorer nations, however RTI prevention strategies in those countries largely draw upon studies conducted in wealthier countries. This research investigated personal and environmental risk factors for child pedestrian RTIs relevant to an urban, developing world setting.This is a case control study of personal and environmental risk factors for child pedestrian RTIs in San Juan de Miraflores, Lima, Perú. The analysis of personal risk factors included 100 cases of serious pedestrian RTIs and 200 age and gender matched controls. Demographic, socioeconomic, and injury data were collected. The environmental risk factor study evaluated vehicle and pedestrian movement and infrastructure at the sites in which 40 of the above case RTIs occurred and 80 control sites.After adjustment, factors associated with increased risk of child pedestrian RTIs included high vehicle volume (OR 7.88, 95%CI 1.97-31.52), absent lane demarcations (OR 6.59, 95% CI 1.65-26.26), high vehicle speed (OR 5.35, 95%CI 1.55-18.54), high street vendor density (OR 1.25, 95%CI 1.01-1.55), and more children living in the home (OR 1.25, 95%CI 1.00-1.56). Protective factors included more hours/day spent in school (OR 0.52, 95%CI 0.33-0.82) and years of family residence in the same home (OR 0.97, 95%CI 0.95-0.99).Reducing traffic volumes and speeds, limiting the number of street vendors on a given stretch of road, and improving lane demarcation should be evaluated as components of child pedestrian RTI interventions in poorer countries.
| S-EPMC2528934 | biostudies-literature
Project description: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.
| S-EPMC10125984 | biostudies-literature
Project description: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.
| S-EPMC5112526 | biostudies-literature
Project description:BACKGROUND:Road traffic law enforcement was implemented on 1st April 2011 (the first intervention) and traffic ticket fines have been increased on 1st March 2016 (the second intervention) in Iran. The aim of the current study was to evaluate the effects of the law enforcement on reduction in the incidence rate of road traffic fatality (IRRTF), the incidence rate of road traffic injuries (IRRTI) and the incidence rate of rural road traffic offenses (IRRRTO) in Iran. METHODS:Interrupted time series analysis was conducted to evaluate the impact of law enforcement and increased traffic tickets fines. Monthly data of fatality on urban, rural and local rural roads, injuries with respect to gender and traffic offenses namely speeding, illegal overtaking and tailgating were investigated separately for the period 2009-2016. RESULTS:Results showed a reduction in the incidence rate of total road traffic fatality (IRTRTF), the incidence rate of rural road traffic fatality (IRRRTF) and the incidence rate of urban road traffic fatality (IRURTF) by -21.44% (-39.3 to -3.59, 95% CI), -21.25% (-31.32 to -11.88, 95% CI) and -26.75% (-37.49 to -16, 95% CI) through the first intervention which resulted in 0.383, 0.255 and 0.222 decline in casualties per 100 000 population, respectively. Conversely, no reduction was found in the incidence rate of local rural road traffic fatality (IRLRRTF) and the IRRTI. Second intervention was found to only affect the IRURTF with -26.75% (-37.49 to -16, 95% CI) which led to 0.222 casualties per 100 000 population. In addition, a reduction effect was observed on the incidence rate of illegal overtaking (IRIO) and the incidence rate of speeding (IRS) with -42.8% (-57.39 to -28.22, 95% CI) and -10.54% (-21.05 to -0.03, 95% CI which implied a decrease of 415.85 and 1003.8 in monthly traffic offenses per 100 000 vehicles), respectively. CONCLUSION:Time series analysis suggests a decline in IRTRTF, IRRRTF, and IRURTF caused by the first intervention. However, the second intervention found to be only effective in IRURTF, IRIO, and IRS with the implication that future initiatives should be focused on modifying the implementation of the traffic interventions.
| S-EPMC7164613 | biostudies-literature
Project description:BackgroundRoad-Traffic-Injuries (RTIs) are predicted to rise up to the fifth leading cause of worldwide death by 2030 and Iran has the third highest RTIs mortality among higher-middle income countries. Although the high mortality of RTI in Iran is a warning, it provides the opportunity to indirectly assess the implemented RTI-related regulations' effectiveness via high-resolution relevant statistics and, hence, Iran could serve as a guide for countries with similar context. In order to do so, we utilized this study to report the time and spatial trends of RTIs-related mortality in different age and sex groups and road user classes in Iran.MethodsBased on the national death-registration-system (DRS), cemeteries data, and the demographic characteristics, and after addressing incompleteness, we estimated mortality rates using spatiotemporal and Gaussian process regression models. We assessed Pearson seatbelt and helmet use and RTIs-attributable Age-Standardized-Morality-Rate (ASMR) associations. We also predicted RTIs-death-numbers, 2012-2020, by fitting a Generalized Additive Model to assess the status of achieving relevant sustainable development goal (SDG), namely reducing the number of RTIs-related deaths by half.ResultsOverall RTIs-attributable death and ASMR at the national level increased from 12.64 [95% UI, 9.52-16.86] to 29.1 [22.76-37.14] per 100,000 people in the time period of 1990-2015. The trend consisted of an increasing segment in 1990-2003 followed by a decreasing part till 2015. The highest percentage of death belonged to the three-or-more-wheels motorized vehicles. Pedestrian injuries percentage increased significantly and the highest mortality rate occurred in 85 years and older individuals. Low prevalence of seatbelt and helmet use were observed in provinces with higher than the median ASMR due to the relevant cause of each. RTIs-attributable death number is expected to reduce by 15.99% till 2020 which is lower than the established SDG goal.ConclusionsDespite the observed substantial moderation in the RTI-ASMR, Iran is till among the leading countries in terms of the highest mortality rates in the world. The enforced regulations including speed limitations (particularly for elder pedestrians) and mandatory use of seatbelt and helmet (for young adult and male drivers) had a considerable effect on ASMR, nevertheless, the RTI burden reduction needs to be sustained and enhanced.
| S-EPMC8459502 | 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:(1) Background: Pedestrian injuries (PIs) represent a significant proportion of road traffic injuries. Our aim was to investigate the incidence and mortality of PIs in different age groups and sociodemographic index (SDI) categories between 1990 and 2017. (2) Method: Estimates of age-standardized incidence and mortality along with trends of PIs by SDI levels were obtained from the Global Burden of Disease from 1990 to 2017. We also forecasted the trends across all the SDI categories until 2040 using the Statistical Package for the Social Sciences (SPSS Statistics for Windows, version 23.0, Chicago, IL, USA) time series expert modeler. (3) Results: Globally, the incidence of PIs increased by 3.31% (-9.94 to 16.56) in 2017 compared to 1990. Men have higher incidence of PIs than women. Forecasted incidence was 132.02 (127.37 to 136.66) per 100,000 population in 2020, 101.52 (65.99 to 137.05) in 2030, and reduced further to 71.02 (10.62 to 152.65) by 2040. Globally across all SDI categories, there was a decreasing trend in mortality due to PIs with the global estimated percentage reduction of 37.12% (-45.19 to -29.04). (4) Conclusions: The results show that PIs are still a burden for all SDI categories despite some variation. Although incidence and mortality are expected to decrease globally, some SDI categories and specific vulnerable age groups may require particular attention. Further studies addressing incidence and mortality patterns in vulnerable SDI categories are needed.
| S-EPMC7143775 | 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