Prevalence and Determinants of Metabolic Syndrome among Women in Chinese Rural Areas

BACKGROUND AND AIMS: Metabolic syndrome (MS) is prevalent in recent years but few data is reported in the rural areas in China. The aim of this study was to examine MS prevalence and its risk factors among women in rural China. METHODS AND RESULTS: The Nantong Metabolic Syndrome Study (NMSS), a population based cross-sectional study, was conducted during 2007-2008 in Nantong, China. In person interviews, blood glucose and lipid measurements were completed for 13,505 female participants aged 18-74 years. The International Diabetes Federation (IDF), the US Third Report of the National Cholesterol Education Program, the Adult Treatment Panel (ATPIII) and modified ATPIII for Asian population has determined three criteria of MS. These criteria for MS were used and compared in this study. The prevalence of MS was 22.0%, 16.9% and 23.3% according to IDF, ATPIII and ATPIII-modified criteria, respectively. Levels of agreement of these criteria for MS were above 0.75. We found that vigorous-intensity of occupational physical activity was associated with a low prevalence of MS with OR of 0.76 (95% confidence interval (CI): 0.63-0.91). Rice wine drinkers (alcohol >12.8 g/day) had about 34% low risks of developing MS with OR of 0.66 (95% CI: 0.48-0.91), compared with non-drinkers. Odds ratio of MS was 1.81 (95% CI: 1.15-2.84) in women who smoked more than 20 pack-years, compared to non-smokers. Odds ratio of MS was 1.56 (95% CI: 1.25-1.95) in women who had familial history of diseases, including hypertension, diabetes and stroke, compared to women without familial history of those diseases. CONCLUSION: MS is highly prevalent among women in rural China. Both physical activity and rice wine consumption play a protective role, while family history and smoking are risk factors in MS development. Educational programs should be established for promoting healthy lifestyles and appropriate interventions in rural China

Canonical correlation analysis for determination of relationships between different length measurements and body weights of common cuttlefish (Sepia officinalis)

In this study, canonical correlation analysis was applied to estimate relationships between length characters mantle length (cm), upper hood length (cm), lower hood length (cm), cuttle bone line zone length (cm), cuttle bone free zone length (cm) and weights characters body weight (g), stomach weight (g), stomach wall weight (g), digestive gland weight (g) of 697 cuttlefish (Sepia officinalis) populations caught from iskenderun bay from 2006-2007, Eastern Mediterranean region, Turkey. The first 3 of the estimated canonical correlation coefficients between the pairs of canonical variables were found significant (0.949, 0.358, 0.294 and p<0.01). The results obtained from canonical correlation analysis indicated that mantle length had largest contribution for the explanatory capacity of canonical variables estimated from length characters of 697 cuttlefish (Sepia officinalis) when compared with other length characters while body weight had largest contribution for the explanatory capacity of canonical variables estimated from weight characters when compared with other weight characters. The results of this study showed that mantle lenght should be used with the aim of estimating weight per Sepia officinalis individuals in common cuttlefish genotypes. © Medwell Journals, 2012

Estimating soil temperature using neighboring station data via multi-nonlinear regression and artificial neural network models

PubMedID: 22322408The aim of this study is to estimate the soil temperatures of a target station using only the soil temperatures of neighboring stations without any consideration of the other variables or parameters related to soil properties. For this aim, the soil temperatures were measured at depths of 5, 10, 20, 50, and 100 cm below the earth surface at eight measuring stations in Turkey. Firstly, the multiple nonlinear regression analysis was performed with the "Enter" method to determine the relationship between the values of target station and neighboring stations. Then, the stepwise regression analysis was applied to determine the best independent variables. Finally, an artificial neural network (ANN) model was developed to estimate the soil temperature of a target station. According to the derived results for the training data set, the mean absolute percentage error and correlation coefficient ranged from 1.45% to 3.11% and from 0.9979 to 0.9986, respectively, while corresponding ranges of 1.685-3.65% and 0.9988-0.9991, respectively, were obtained based on the testing data set. The obtained results show that the developed ANN model provides a simple and accurate prediction to determine the soil temperature. In addition, the missing data at the target station could be determined within a high degree of accuracy. © 2012 Springer Science+Business Media B.V

A comparative study of least squares method and least absolute deviation method for parameters estimation in length-weight relationship for white grouper (Ephinephelus aeneus)

In fisheries science, by means of linear regression models, length-weight relationships are often estimated to determine weight and biomass when only length measurements are taken from fish. Least Squares method (LS) is commonly used to determinate the relationship between weight and length for fish, when the error term, ei, is assumed to be normally distributed. If it can be observed to degenerate the structure of data in the y-direction, LS method is not completely perform to estimate the regression parameters. And than LS method explains minimum levels to the total variation of the model. In this situation, one of the linear regression methods often recommended as robust or outlier-resistant alternatives to LS is Least Absolute Deviation (LAD). The aim of this study is to investigate for comparing the least squares method and the LAD method by means of drawing conclusions and to determine the model which is optimal for displaying the relationship between length and weight for Ephinephelus aeneus in the presence of outliers. Mean square error and R 2 are used to evaluate estimator performance. © 2006 Asian Network for Scientific Information

Width/length-weight and width-length relationships for 8 crab species from the North-eastern Mediterranean coast of Turkey

In this study, relationships between width/length-weight and width-length by sex and combine were estimated 1133 individuals belonging to 8 species from 5 families in the North-eastern Mediterranean coast of Turkey. Regression coefficient between the regression of W-CL, W-CW and CL-CW for female, male and both were found very high (p&lt;0.001) and the median value of b W-CL were 3.135, 3.132 and 3.081; W-CW were 3.135, 3.132 and 3.081, respectively. The r2 values ranged from 0.91-0.99. © Medwell Journals, 2009

Use of factor analysis scores in multiple regression model for estimation of body weight from some body measurements in lizardfish

The aim of the study is to find out, the utility function of factor analysis scores in multiple linear regression model that were used to estimate body weight with respect to some body measurements (total length, standard length, fork length, head length, body depth, body circuit, body height) measured from Lizardfish in Iskenderun Bay. The results of the factor analysis showed that 3 factor with eigenvalues greater than 1 can be selected as explanatory variables and used to estimate body weight of Lizardfish in multiple linear regression model. The factors accounted for 98.4% of total variation in the body weight. © Medwell Journals, 2009

A comparative study of estimation methods for parameters in multiple linear regression model

This paper investigated least squares method, non-parametric method and robust regression methods to predict the parameters of multiple regression models. To evaluate these methods, measurements of body weight, total length and fork length of fishes collected from Serranus cabrilla were used. In these regression models, body weight was dependent variable whereas total length and fork length were independent variables. The results show that non-parametric regression method, general additive model, has minimum R2 value and least median squares has maximum R2 value, 0.334 and 0.855, respectively. © GSP, India

Development of a Bacillus subtilis-Based Rotavirus Vaccine ▿

Bacillus subtilis vaccine strains engineered to express either group A bovine or murine rotavirus VP6 were tested in adult mice for their ability to induce immune responses and provide protection against rotavirus challenge. Mice were inoculated intranasally with spores or vegetative cells of the recombinant strains of B. subtilis. To enhance mucosal immunity, whole cholera toxin (CT) or a mutant form (R192G) of Escherichia coli heat-labile toxin (mLT) were included as adjuvants. To evaluate vaccine efficacy, the immunized mice were challenged orally with EDIM EW murine rotavirus and monitored daily for 7 days for virus shedding in feces. Mice immunized with either VP6 spore or VP6 vegetative cell vaccines raised serum anti-VP6 IgG enzyme-linked immunosorbent assay (ELISA) titers, whereas only the VP6 spore vaccines generated fecal anti-VP6 IgA ELISA titers. Mice in groups that were immunized with VP6 spore vaccines plus CT or mLT showed significant reductions in virus shedding, whereas the groups of mice immunized with VP6 vegetative cell vaccines showed no difference in virus shedding compared with mice immunized with control spores or cells. These results demonstrate that intranasal inoculation with B. subtilis spore-based rotavirus vaccines is effective in generating protective immunity against rotavirus challenge in mice