Association between Selenium in Soil and Diabetes in Chinese Residents Aged 35–74 Years:Results from the 2010 National Survey of Chronic Diseases and Behavioral Risk Factors Surveillance

Objective To explore the association between soil selenium levels and the risk of diabetes in Chinese adults aged 35–74 years.Methods Data for this study were derived from the China Chronic Diseases and Behavioral Risk Factors Surveillance 2010 survey.Selenium concentrations in soil were obtained from the Atlas of Soil Environmental Background Values in China.A two-level binary logistic regression model was used to determine the association between soil selenium concentrations and the risk of diabetes,with participants nested within districts/counties.Results A total of 69,332 participants aged 35–74 years,from 158 districts/counties were included in the analysis.Concentrations of selenium in soil varied greatly across the 158 districts/counties,with a median concentration of 0.219 mg/kg(IQR:0.185–0.248).The results showed that both Quartile 1(0.119–0.185 mg/kg)and Quartile 4(0.249–0.344 mg/kg)groups were positively associated with diabetes compared to a soil selenium concentration of 0.186–0.219 mg/kg(Quartile 2),crude odds ratios(ORs)(95%CI)were 1.227(1.003–1.502)and 1.280(1.048–1.563).The P values were 0.045 and 0.013,for Quartile 1 and Quartile 4 groups,respectively.After adjusting for all confounding factors of interest,the Quartile 1 group became non-significant,and the Quartile 4 group had an adjusted OR(95%CI)of 1.203(1.018–1.421)relative to the reference group(Quartile 2),the P values was 0.030.No significant results were seen for the Quartile 3 group(0.220–0.248 mg/kg)compared to the reference group.Conclusion Excessive selenium concentrations in soil could increase the risk of diabetes among Chinese adults aged 35–74 years.

Diabetes Mellitus Type 2 Prevalence, Risk Factors and Complications in the Region of Kardzhali, Bulgaria

The present study was conducted within the CINDI program and covers 1,600 individuals, divided into four age groups. The aim of this study is to investigate the key biomedical and lifestyle factors for the development of type 2 diabetes as well as the cardiovascular diabetes complications in the population aged 25-64 from Kardzhali region, Bulgaria. The results of the study show the existence of behavioral and biological risk factors of health, as well as family history in the studied individuals who suffer from diabetes. The connection between diabetes and certain cardiovascular diseases such as ischemic heart disease, myocardial infarction and cardiovascular disease is confirmed. This requires the development and implementation of intervention activities among the population of Kardzhali, aimed at reducing the level of diabetes risk factors, early identification of risk groups and timely treatment of the diseased.

Constructing Statistical Intervals for Small Area Estimates Based on Generalized Linear Mixed Model in Health Surveys

Generalized Linear Mixed Model (GLMM) has been widely used in small area estimation for health indicators. Bayesian estimation is usually used to construct statistical intervals, however, its computational intensity is a big challenge for large complex surveys. Frequentist approaches, such as bootstrapping, and Monte Carlo (MC) simulation, are also applied but not evaluated in terms of the interval magnitude, width, and the computational time consumed. The 2013 Florida Behavioral Risk Factor Surveillance System data was used as a case study. County-level estimated prevalence of three health-related outcomes was obtained through a GLMM;and their 95% confidence intervals (CIs) were generated from bootstrapping and MC simulation. The intervals were compared to 95% credential intervals through a hierarchial Bayesian model. The results showed that 95% CIs for county-level estimates of each outcome by using MC simulation were similar to the 95% credible intervals generated by Bayesian estimation and were the most computationally efficient. It could be a viable option for constructing statistical intervals for small area estimation in public health practice.

Sedentary lifestyle among adults in Jordan,2007

Objective:Sedentary lifestyle is a major risk factor for physical and mental problems,such as cardiovascular,musculoskeletal diseases,and psychological stress.About 60% of the world’s population is not sufficiently physically active in leisure time or during work and social activities.This study aimed to determine the prevalence of inactive Jordanian adults and describe their demo-graphic and behavioral characteristics.Methods:The study used data from the behavioral risk factors surveillance survey conducted in Jordan in 2007.The sample size was 3654.Respondents who were physically inactive for more than 240 min daily(sleep time not included)were considered to have a sedentary lifestyle.Data were analyzed with the program SPSS.Results:The prevalence of a sedentary lifestyle was 82.8%(2965 respondents),with a mean sedentary time of 587 min(95%confidence interval 581-594 min).Among the physically inactive adults,52.6% were men,one third of them aged 35-44 years.Sedentary lifestyle was reported by 30% of those with a secondary level of education or above.Of those with a sedentary lifestyle,37.6% were housewives and 37.5% were employees;66% of them were overweight and obese.Of the physically inactive people,2.5%had a history of heart failure and 1.3%had a history of cer-ebrovascular accidents;57.2% of them tried to engage more in physical activity and almost three quarters of them were interested in improving their dietary habits.Conclusion:Most Jordanian adults have a sedentary lifestyle,which emphasizes that there is a public health problem.Many of them are attempting to lead a healthier lifestyle.Therefore,there is an urgent need to launch an applicable national plan that enables people to practice a healthier lifestyle.

Clinical Significance of REM Sleep Behavior Disorders and Other Non-motor Symptoms of Parkinsonism

Rapid eye movement sleep behavior disorder （RBD） is one of the most common non-motor symptoms of parkinsonism, and it may serve as a prodromal marker of neurodegenerative disease. The mechanism underlying RBD is unclear. Several prospective studies have reported that specific non-motor symptoms predict a conversion risk of developing a neurodegenerative disease, including olfactory dysfunction, abnormal color vision, autonomic dysfunction, excessive daytime sleepiness, depression, and cognitive impairment. Parkinson＇s disease （PD） with RBD exhibits clinical heterogeneity with respect to motor and non-motor symptoms compared with PD without RBD. In this review, we describe the main clinical and pathogenic features of RBD, focusing on its association with other non-motor symptoms of parkinsonism.