The Investigation of Relationship between Socio Economic Status and the Outcomes of Deaths and severity Injury in Road Traffic Crashes Patients

 Road traffic crashes and its deaths and injuries are one of the main public health problems in all over the world especially in Low and Middle Income Countries (LMICs). Road traffic crashes resulting in deaths, physical and psychological problems, and economic costs which have damages on families and communities. The number of road traffic deaths was exceeded from 1.3 million in 2016. Most of the road traffic injuries are belong to low and middle-income countries of the world. Road traffic injury is the eight leading causes of deaths for all ages, while it is largely neglected. 
There are several effective factors in road traffic crashes. The socio-economic status is known as important factors related to health status, although its influence is not fully understood on different aspects of health. People who live in low socioeconomic status suffer from the disease and injuries two times more than others. The results of the studies show that fatal and non-fatal injuries have an inverse relationship with socio-economic status. The socio-economic status is known as important factors related to health status. People who live in low socioeconomic status suffer from the disease and injuries two times more than others. The results of the studies show that fatal and non-fatal injuries have an inverse relationship with SES. However, there is a lack of enough information about the effects of socioeconomic status on road traffic crashes and its related outcomes. 
The incidence rate of road traffic injuries and its related deaths have a relationship with socio-economic status. In the international level, these incidences vary between the High-income countries and Low and Middle-income countries. Moreover, the incidences of road traffic injuries and deaths vary between the different socio-economic groups in each country.
The socio-economic status is known as the main predictor factor in different aspects of health. The importance of socio-economic status will increase in regarding this point which the outcomes of road traffic crashes are sometimes irreversible. However, the effect of socioeconomic status on the many aspects of health is not fully understood. Identifying the socio-economic status factors related to the outcomes of road traffic crashes can provide a good opportunity for policy makers and managers to use preventive interventions in high-risk groups.  This study used an analytical cross-sectional design. The studied sample was people who injured because of road traffic crashes and referred to Pour-Sina hospital in the city of Rasht. Rasht is the central city of Guilan province. Guilan province is located in the north of Iran and the rate of road traffic crashes is high in this province. The collection of data has been done by two researchers. The data collection questioner trained in order to meet the quality assurance and prevention the information bias. The using questionnaires consisted of two parts. The first part was a checklist to collecting the demographic information including the; age, gender, a marital status which obtained from hospital records. Moreover, collecting the crash information such as; the location of the injury, the type of injury, the severity of injury (based on Injury Severity Score), the clinical outcome of the patient which were extracted from hospital records. The second part of the instrument was related to socio-economic issues. For this purpose, the standardized questionnaire was used which the validity and reliability of that were confirmed in the previous study. In the cases that the injured people had died or were unable to interview due to the severity of the injuries, the interview was conducted with one of the close relatives (father, mother, brother or sister) and after obtaining informed consent.
In order to determine the socio-economic status factors (that are a combination of variables), the principal components analysis was used. Principal component analysis simplifies the data and reduces the number of variables. To extracted the factor/factors from the variables, the Varimax rotation method was used. The Varimax rotation is used if factors are assumed to be uncorrelated which is known as orthogonal rotation. In this study, the Eigenvalue greater than 1 was chosen. After determining the factor, the variables that were present in each factor were identified.
To obtain the main socio-economic status factors the method of principal component analysis was used. To assess the interest of the implementation of the principal component analysis on a data, Bartlett’s sphericity test and the KMO index were used. The main SES factors were determined and in order to assess the relationship between these factors and death and severity of injuries related to road traffic crashes, the logistic regression with the Backward-LR method was used. The analysis was adjusted on the variable of age and sex of patients. For the severity of the injury, the ISS scale was grouped (ISS> 15, ISS = <15) and it is considered as the dependent variable in the Logistic Regression model. The ISS scale above 15 is considered to be a severe injury All analyses were performed using the SPSS software version 20. The significance level of the tests in this study was considered 0.05.  In this study, 300 traumatic patients were recruited. From all, 234 patients (78%) were male. The mean age of injured patients was 34.25 years old (19.07). The ISS scale was grouped (ISS> 15, ISS = <15). the ISS scale above 15 is considered to be a severe injury. The severe injury (ISS > 15) was observed among 245 (81.7%) patients. 
Bartlett’s sphericity test and the KMO index showed that there is a good correlation between the studied variables and the using of principal component analysis is feasible. The p-value for the Bartlett test is significant and the KMO index is more than 0.5. Some socio-economic status factors had a relationship with the outcomes of death and the severity of the injury of patients. There were three factors which affect the outcome of road traffic crashes. The first factor includes the following variables; household cost, the education level of an injured person, and the education level of the mother. The second factor includes the variables of; job, owning the mobile and motorcyclist. The third factor includes the variables of; income and fathers job. The results of logistic regression analysis showed that factor 3 (family income and father's job) had a significant relationship with the outcome of traumatic death. For this factor, the odds ratios of 0.45 (CI 95%; 0.042- 0.83) for deaths and 0.65 (CI 95%; 0.45- 0.90) for the severity of injuries was obtained. The highest SES had the lowest deaths and injuries. 
There was a relationship between economic factors and the severity of the trauma, the economic-social third factor including variables; family income and father's occupation were identified as an effective factor in the severity of trauma. The odds ratio for the third factor (household income and father's occupation) was 0.68 (95% confidence interval: 0.452-0.908).  The results of this study showed that social economic factors affect both the deaths and the severity of injuries. The results of this study showed that the third factor (family income and father's job) had a significant relationship with traumatic death. In other words, the mortality rate of road traffic crashes is high among families with a low level of socio-economic status. Considering the high rates of deaths and severe injuries caused by traffic accidents in Iran compared to other countries, it is necessary economic and social factors will be considered as effective factors on deaths and injuries in road traffic policy-making and planning.