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Traffic accidents are a major and crucial problem worldwide. The development of a traffic accident simulation system applied by using a geographic information system and multiple logistic regression with dustering can provide drivers with safe routes as well as guidelines for assessing the risk points of accidents in each sub district. This research is based on case-control study design. The data were collectedbyusingtwo types of questionnaires: a questionnaire for 35 community leaders and a questionnaire for 580 community residents based on the distance at which main routes pass through the sub district area. The data were analysed through multiple logistic regression with dustering, and the standardized coefficient of the selected variables was then added to the equation as a weight in the traffic accident simulation system. The results of the study indicated that 11 variables affected traffic accidents. These factors were evaluated in order to predict traffic accidents (Pseudo R square=0.5 906). Standardized coefficient of variables was applied in a geographic information system to simulate traffic accidents on roads. This study was distinctive for its analysis, which examined the clusters of variables that were the sub district-level data, including surroundings and road conditions at the riskiest location in each sub district. The data were analysed based on their quality as sub district data clusters. The analysis results were then applied as the weight of variables used in the G IS to obtain the values appropriate to the data clusters' quality for the GIS to properly simulate traffic accidents in each area. [ABSTRACT FROM AUTHOR]

Abstract Background Information on the distribution of Metabolic syndrome (MetS) and its combinations by urban/rural areas in lower-middle income countries has been limited. It is not clear how the various combinations of MetS components varied by urban/rural population and if particular combinations of MetS are more common. This study aimed to estimate the prevalence of MetS and combinations of MetS components according to sex and urban/rural areas from a nationally representative sample of Thai adults. Methods Data from the fourth National Health Examination Survey of 19,256 Thai adults aged 20 years and over were analyzed. MetS was defined using the harmonized criteria of six international expert groups with Asian-specific cut-point for waist circumference. Results The prevalence of MetS was 23.2% among adults aged ≥ 20 years (19.5% in men and 26.8% in women). Among men, the prevalence of MetS in urban was higher than those in rural areas (23.1% vs 17.9%, P < 0.05), but among women, the prevalence was higher in rural areas (27.9% vs 24.5%, P < 0.05). Overall, an individual component of low high density lipoprotein (HDL) and hypertriglyceridemia were more common in rural areas, while obesity, high blood pressure and hyperglycemia were more common in urban areas. The most common combination of MetS components in men was the clustering of low HDL, hypertriglyceridemia, and high blood pressure (urban: 3.4% vs. rural: 3.9%, adjusted OR 0.9, 95%CI 0.7, 1.1). Among women, the most common combination was the clustering of obesity, low HDL, and hypertriglyceridemia (urban: 3.9% vs rural: 5.9%, adjusted OR 0.8, 95%CI 0.6, 0.9), followed by the clustering of these three components with high blood pressure (urban: 3.1% vs. rural 4.5%, adjusted OR 0.8, 95%CI 0.7, 0.9). Conclusion Metabolic syndrome affects both urban and rural population with different pattern of MetS combinations. Dyslipidemia and obesity were the most common components among women in rural areas, hence, interventions to prevent and control these factors should be strengthened.