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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.

We determined the prevalence of obesity in Thai adults aged 20 and over in 2009 and examined trends of body mass index (BMI) between 1991 and 2009. Data from Thai National Health Examination Survey for 19,181 adults in 2009 and 64,480 adults between 1991 and 2004 were used to calculate age-adjusted mean and prevalence. Logistic regression was used to examine the association of obesity with education level. In 2009, age-adjusted prevalence of obesity classes I (BMI 25-29.9 kg/m(2)) and II (BMI ≥30 kg/m(2)) in Thai adults aged ≥20 years were 26.0% and 9.0%, respectively. Compared with primary education, the odds of obesity class I were highest in men with university education. For women, the odds of obesity classes I and II were highest in those with primary education. BMI significantly increased from 21.6 kg/m(2) in men and 22.8 kg/m(2) in women in 1991 to 23.3 kg/m(2) and 24.4 kg/m(2) in 2009, respectively. The average BMI increases per decade were highest in men with secondary education (1.0 kg/m(2), P < 0.001) and in women with primary education with the same rate. There were increasing trends in BMI with slight variation by SES groups in Thai men and women during 1991-2009.

Objective: To estimate daily intake of sodium and examine the relation of socio-demographic factors with sodium intake exceeding the recommendations., Material and Method: Data from the Thai National Health Examination Survey IV (NHES IV) conducted during 2008-2009 were used. The 24-hour-dietary-recall data were available for a subsample of 10% of the total participants. All food and beverage data were analyzed for amount of total daily sodium intake for each person. In statistical analyses, descriptive statistics were employed to describe participants' characteristics, quantities of dietary sodium and percentages of participants noncompliant with daily sodium intake recommendations. Logistic regression was used to examine socio-demographic determinants of sodium intake exceeding the recommendations., Results: 2,969 participants participated in this study. Sodium intake varied by socio-demographics. Percentages of participants non-compliant with sodium intake recommendations ranged from 75.3 (> or = 1,500 mg) to 52.0 (> or = 2,400 mg) for those aged < 16 years and from 86.3 (> or = 1,500 mg) to 67.6 (2,400 mg) for those aged > or = 16 years. In the younger group, age and region were key determinants of consuming sodium exceeding all recommendations. Having family income between 5,000 and < 10,000 baht/month was significantly associated with sodium intake exceeding recommendation targets. In the older group, being female and increasing age reduced a risk of non-compliance with some recommendations; oppositely, region and residential area participants lived significantly, increased non-compliant risk., Conclusion: Most participants consumed dietary sodium exceeding current recommendations. Effective programs to reduce sodium intake in Thais are critical.

Objective: To determine the changes in prevalence, awareness, treatment and control of hypertension and their metabolic risk factors in Thai population between 2004 and 2009., Methods: The Thai National Health Examination Survey (NHES) in 2004 and 2009 data were used. Blood pressure and anthropometric measurements were performed. Prevalence, awareness, treatment and control of hypertension of Thai population aged at least 15 years were calculated. Analyses were weighted to the probability of sampling., Results: The prevalence of hypertension in 2004 and 2009 were relatively stable at approximately 21.0%. There was improvement in awareness of hypertension, from 18.2% for men and 33.0% for women in 2004 to 39.5 and 59.4% in 2009, respectively. The high blood pressure control rates improved from 4.8 to 14.4% for men and from 10.8 to 27.2% for women, respectively (all P < 0.05). The improvement in awareness, treatment and control of hypertension was also observed in individuals with diabetes, obesity and hypercholesterolemia. However, among hypertensive individuals, there were increases in proportions of obesity (BMI ≥ 25 kg/m(2)) between two surveys: from 39.1 to 47.5% in men and from 54.6 to 62.9% in women, respectively (all P < 0.05)., Conclusion: Despite improvement in awareness and control of hypertension in Thai population, a large proportion of hypertensive individuals remained suboptimally controlled. Strengthening measures to control high blood pressure and metabolic risk factors, especially obesity and hypercholesterolemia, in individuals with hypertension are needed.