Parents' knowledge and socio-demographic determinants toward child's restraint system use.

BACKGROUND: Lack of protection or improper protection, is one of the most important reasons of child passenger's death and injury in traffic crashes. Based on what we see on the roads, Iranian children are unrestrained inside the car. The aim of this study was to investigate children restrained system (CRS) use rate, its socio-demographic determinants and parents' knowledge toward CRS use among Iranian parents. METHODS: Using multi-stage cluster sampling and direct in filed method of observation, the behavior of 700 children in cars was observed in the current cross-sectional study. Socio-demographic determinants and parents' knowledge, toward using the CRS were evaluated using questionnaires. The study was performed from July to August 2019 in Tabriz city, northwestern Iran. RESULTS: The rate of child safety seat (CSS) use was 15.1% CI 95%:(12.5%,18.0%), and the rate of booster use was 0.6%; CI 95%:(4.3%,8.0%). The majority of parents [e.g. 64.3%; CI 95%: (60.7%,67.9%)], had low knowledge about the use of CRS. The most important reasons for not using CRS was lack of laws and policies [e.g. 59.7%; CI 95%:(12.5%,18.0%)], lack of knowledge [e.g.59.6%; CI 95%:(57.9%, 63.3%)] and the high cost of CRS [e.g. 57.6%; CI 95%:(53.81%,61.2%)]. The most important predictors of not using CRS were the child's age, parental knowledge, and the socioeconomic status of the household (p < 0.05). CONCLUSIONS: Most children did not have CRS. The parents with higher education and those with higher socioeconomic status had higher rate of CRS use. Based on the low rate of CRS use and poor parental knowledge about it, education of parents toward boosters use and benefits of using CRS, enforcing mandatory laws and ploicies for CRS use in Iran, and allocation of government subsidies to low-income families for purchasing CRS are suggeted as essential strategies to increase CRS use.

Applying count time series to assess 13-year pedestrian mortality trend caused by traffic accidents in East-Azerbaijan province, Iran.

In populated cities, pedestrian mortality is higher compared to other traffic mortalities. The current study aimed to describe the trend of pedestrian mortality in the East-Azerbaijan (Northwest of Iran) province from 2006 to 2019 and find the factors that affect the mortality number. Pedestrian mortality data from March 2006 to March 2019 was obtained from the Legal Medicine Organization database of Iran. Generalized Linear Auto Regressive Moving Average (GLARMA) models were used to assess the trend, and affecting factors of pedestrian mortality. According to the traffic accident data from 21 March 2006 until 20 March 2019 in East-Azerbaijan 24.11% of mortalities are related to pedestrians. Pedestrian mortality had a decreasing seasonal trend during 2006-2019. The result of the GLARMA model showed that age >65, being non-educated, cases with head trauma death cause, pre-hospital death, accident inside the city, vehicle type and self-employed jobs had a direct relation to pedestrian's mortality.

Hidden patterns among the fatally injured pedestrians in an Iranian population: application of categorical principal component analysis (CATPCA).

BACKGROUND: Identifying hidden patterns and relationships among the features of the Fatal Pedestrian Road Traffic Injuries (FPRTI) can be effective in reducing pedestrian fatalities. This study is thus aimed to detect the patterns among the fatally injured pedestrians due to FPRTI in East Azerbaijan province, Iran. METHODS: This descriptive-analytic research was carried out based on the data of all 1782 FPRTI that occurred in East Azerbaijan, Iran from 2010 to 2019 collected by the forensic organization. Categorical Principal Component Analysis (CATPCA) was performed to recognize hidden patterns in the data by extracting principal components from the set of 13 features of FPRTI. The importance of each component was assessed by using the variance accounted for (VAF) index. RESULTS: The optimum number of components to fit the CATPCA model was six which explained 71.09% of the total variation. The first and most important component with VAF = 22.04% contained the demographic and socioeconomic characteristics of the killed pedestrians. The second-ranked component with VAF = 12.96% was related to the injury type. The third component with VAF = 10.56% was the severity of the injury. The fourth component with VAF = 9.07% was somehow related to the knowledge and observance of the traffic rules. The fifth component with VAF = 8.63% was about the quality of medical relief and finally, the sixth component with VAF = 7.82% dealt with environmental conditions. CONCLUSION: CATPCA revealed hidden patterns among the fatally injured pedestrians in the form of six components. The revealed patterns showed that some interactions between correlated features led to a higher mortality rate.

Predictors of fatal outcomes in pedestrian accidents in Tabriz Metropolis of Iran: Application of PLS-DA method.

Objectives: Road traffic deaths in walking pedestrians are a global public health problem. Considering that in Iran pedestrians have a high proportion of deaths caused by traffic accidents, the objective of the present study was to investigate mortality rate and related factors of fatal injury in pedestrian crashes in Tabriz Metropolis of Iran as the largest and most populous city of the northwest of Iran.Methods: The design of this study is case-control based on police and Forensic Medicine Organization data. All registered fatal pedestrian crashes in Tabriz Metropolis from 2014 to 2015 (146 cases) were included in the study as the case group. Also, 292 pedestrians (the ratio of cases to controls was 1:2) with non-fatal crashes were considered as the control group. Due to high dimensional data and multicollinearity issue, Partial least squares discriminant analysis (PLS-DA) was used for data analysis. Importance of the variables was determined by the VIP (Variable Importance in the Projection) index. Performance of the model was assessed by using training and test set validation method. The area under the ROC curve (AUC) and classification error rates were calculated for the test set. R software version 3.5.1 (mixOmcs packages) was used for data analysis.Results: According to the results of PLS-DA, the most important variables related to fatal outcome in pedestrian crashes with VIP > 1 were: pedestrian age (positive effect), type of vehicle (light machinery with a negative effect), kind of vehicle plate (private plate with a negative effect), season of accident occurrence (winter season with a positive effect), type of driver's licenses (Class A with a positive effect), pedestrian gender (male with a positive effect) and Fault of Pedestrian (At-fault with a positive effect). The overall accuracy for the fitted model and AUC were 0.77 and 0.79, respectively.Conclusions: The results show that predictors of a fatal outcome in pedestrian accidents in Tabriz can be attributed to the pedestrian characteristics (which notably account for differences in vulnerability in case of an accident), the car and driver features, and weather (which may all notably influence the amount of energy involved in the collision, through the car mass, speed, and conditions delaying the braking response or reducing the braking effectiveness). Regarding the statistical method, the PLS-DA is a powerful method which can be used to analyze high dimension data with multicollinearity issue.