Factors Influencing Road Accidents in Oman.

Road traffic accidents (RTAs) are increasingly being recognized as a growing public health problem in Arabian Gulf countries including Sultanate of Oman. The discovery of oil around the middle of the last century has led to changes in many aspects of life in Oman, not least in regard to the amount of vehicles on the roads. Whilst affluence may advance a country in terms of technology, infrastructure and economic stability, it is not necessarily the case that general patterns of behavior will adapt at the same speed. This is one of the reasons suggested for the high number of incidents involving aggressive driving behavior and driving offenses. The study of such incidents, and their relation to traffic accidents, has become a major concern of researchers over several years. This study will investigate the factors that may influence RTAs in Oman based on the 2008 Oman World Health Survey (MHO, 2012). Careless driving is generally identified as one of the most important factors in RTAs over the period of study, accounting for a big percentage of all incidents, while excessive speed is among the most common cause. The result has been a large increase in the number of road traffic accidents with casualties and fatalities creating a serious public health problem. This problem drastically needs targeted research in order to identify methods of reducing accidents and fatalities. Particularly, knowing socio-economic factors has immense importance in reducing accidents and fatalities through controlling the factors to their best. This study will undertake to determine the factors that are associated with the road accident by implementing suitable statistical models including the multilevel logistic regression model to Oman National Health Survey data conducted by the Ministry of Health of the Sultanate of Oman. Since the survey is based on a multistage stratified sampling the nested sources of variability should be considered in modelling to find the actual effects of the factors. Therefore multilevel logistic regression modelling would be the best choice to take the variability due to place of living (urban or rural) and regions (districts) into account and thereby to determine if a more accurate urban and rural categorization would reveal different findings.The objectives of the present study are categorized in two ways: firstly, to measure the prevalence of road accidents across demographic and socioeconomic descriptors and secondly to determine the significant factors associated with RTAs, in particular to examine whether urban residence as described above (i.e. living in the town or city) and whether different region?s residence (i.e. living in different district) are independently associated with RTA, adjusting for other factors and demographic factors.