Cardiovascular risk factors in Turkish immigrants with type 2 diabetes living in the Netherlands

The cross sectional study investigated the association of tobacco smoke, vitamin D status, anthropometric parameters, and kidney function in Turkish immigrants with type 2 diabetes (T2D) living in the Netherlands. Study sample included a total of 110 participants aged 30 years and older (males= 46; females= 64). Serum cotinine, a biomarker for smoke exposure, was measured with a solid-phase competitive chemiluminescent immunoassay. Serum 25-hydroxyvitamin D [25(OH)D] was determined by electrochemiluminescence immunoassay (ECLIA). Measures of obesity including: body weight, body mass index (BMI), waist circumference (WC), and hip circumference (HC) were measured. Waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) were calculated. Urine albumin was measured by immunoturbidimetric assay. Urine creatinine was determined using the Jaffe method. All statistical analyses were performed using SPSS, version 19.0 (SPSS Inc., Chicago, IL, USA). Independent samples t-test, chi-squared tests, multiple linear regression and logistic regression analysis were used. Cotinine levels were positively associated with cholesterol to HDL ratio and atherosclerosis-index. Serum 25(OH)D levels were negatively associated with diastolic blood pressure. Gender-specific associations between anthropometric measures and high sensitivity C-reactive protein (hs-CRP) levels were observed. Hs-CRP was positively associated with WC and WHR in males and WHtR in females. Microalbuminuria (MAU), as determined by albumin-to-creatinine ratio, was present in 21% of the Turkish immigrants with T2D. Participants with hypertension were 6.58 times more likely (adjusted odds ratio) to have positive MAU as compared to normotensive participants. Our findings indicate that serum cotinine, 25(OH)D, hs-CRP, and MAU may be assessed as a standard of care for T2D management in the Turkish immigrant population. Further research should be conducted following cohorts to determine the effects of these biomarkers on CVD morbidity and mortality.

Healthy Eating Index scores associated with symptoms of depression in Cuban-Americans with and without type 2 diabetes: a cross sectional study

Background Low diet quality and depression symptoms are independently associated with poor glycemic control in subjects with type 2 diabetes (T2D); however, the relationship between them is unclear. The aim of this study was to determine the association between diet quality and symptoms of depression among Cuban-Americans with and without T2D living in South Florida. Methods Subjects (n = 356) were recruited from randomly selected mailing list. Diet quality was determined using the Healthy Eating Index-2005 (HEI-05) score. Symptoms of depression were assessed using the Beck Depression Inventory (BDI). Both linear and logistic regression analyses were run to determine whether or not these two variables were related. Symptoms of depression was the dependent variable and independent variables included HEI-05, gender, age, marital status, BMI, education level, A1C, employment status, depression medication, duration of diabetes, and diabetes status. Analysis of covariance was used to test for interactions among variables. Results An interaction between diabetes status, gender and HEI-05 was found (P = 0.011). Among males with a HEI-05 score ≤ 55.6, those with T2D had a higher mean BDI score than those without T2D (11.6 vs. 6.6 respectively, P = 0.028). Among males and females with a HEI-05 score ≤ 55.6, females without T2D had a higher mean BDI score compared to males without T2D (11.0 vs. 6.6 respectively, P = 0.012) Conclusions Differences in symptoms of depression according to diabetes status and gender are found in Cuban-Americans with low diet quality.

The association of depression and perceived stress with beta cell function between African and Haitian Americans with and without type 2 diabetes

Background: Diabetes and diabetes-related complications are major causes of morbidity and mortality in the United States. Depressive symptoms and perceived stress have been identified as possible risk factors for beta cell dysfunction and diabetes. The purpose of this study was to assess associations between depression symptoms and perceived stress with beta cell function between African and Haitian Americans with and without type 2 diabetes. Participants and Methods: Informed consent and data were available for 462 participants (231 African Americans and 231 Haitian Americans) for this cross-sectional study. A demographic questionnaire developed by the Primary Investigator was used to collect information regarding age, gender, smoking, and ethnicity. Diabetes status was determined by self-report and confirmed by fasting blood glucose. Anthropometrics (weight, and height and waist circumference) and vital signs (blood pressure) were taken. Blood samples were drawn after 8 10 hours over-night fasting to measure lipid panel, fasting plasma glucose and serum insulin concentrations. The homeostatic model assessment, version 2 (HOMA2) computer model was used to calculate beta cell function. Depression was assessed using the Beck Depression Inventory-II (BDI-II) and stress levels were assessed using the Perceived Stress Scale (PSS). Results: Moderate to severe depressive symptoms were more likely for persons with diabetes (p = 0.030). There were no differences in perceived stress between ethnicity and diabetes status (p = 0.283). General linear models for participants with and without type 2 diabetes using beta cell function as the dependent variable showed no association with depressive symptoms and perceived stress; however, Haitian Americans had significantly lower beta cell function than African Americans both with and without diabetes and adjusting for age, gender, waist circumference and smoking. Further research is needed to compare these risk factors in other race/ethnic groups.

Obesity and Serum High Sensitivity C-Reactive Protein Levels Among Elderly Turkish Immigrants in the Netherlands with Type 2 Diabetes

The study examined the associations of anthropometric measures of obesity with high sensitivity C-reactive protein (hs-CRP) levels in Turkish immigrants with type 2 diabetes (T2D) living in the Netherlands. A total of 110 participants, physician-diagnosed with T2D, aged 30 years and older were recruited from multiple sources from The Hague, Netherlands. Serum hs-CRP levels were measured with immunoturbidimetric assay. Glycated hemoglobin (A1C) was determined by high-pressure liquid chromatography. Measures of obesity: body weight, body mass index (BMI), waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were determined. Statistical analysis included descriptive statistics, Pearson’s correlations and multiple linear regressions (MLR) stratified by gender. Hs-CRP was log transformed to achieve normality. Subjects with hs-CRP levels >10 mg/L (n = 17) were excluded from the analysis. Females had a higher BMI (p = 0.007), HC (p < 0.001), and WHtR (p = 0.011) as compared to males. Conversely, males had a higher weight (p = 0.007), and WHR (p < 0.001) than females. MLR showed that after controlling for covariates, log hs-CRP was positively associated with BMI (B = 0.039, SE = 0.019, β = 0.287, p < 0.05), WC (B = 0.025, SE = 0.011, β = 0.332, p < 0.05) and WHtR (B = 4.015, SE = 1.464, β = 0.376, p < 0.01) in females only. Gender-specific associations between obesity measures and hs-CRP level need to be further investigated in the Turkish immigrant population. Hs-CRP assessment may be added as a standard of care for T2D treatment within this population.

Comparison of Some Improved Estimators for Linear Regression Model under Different Conditions

Multiple linear regression model plays a key role in statistical inference and it has extensive applications in business, environmental, physical and social sciences. Multicollinearity has been a considerable problem in multiple regression analysis. When the regressor variables are multicollinear, it becomes difficult to make precise statistical inferences about the regression coefficients. There are some statistical methods that can be used, which are discussed in this thesis are ridge regression, Liu, two parameter biased and LASSO estimators. Firstly, an analytical comparison on the basis of risk was made among ridge, Liu and LASSO estimators under orthonormal regression model. I found that LASSO dominates least squares, ridge and Liu estimators over a significant portion of the parameter space for large dimension. Secondly, a simulation study was conducted to compare performance of ridge, Liu and two parameter biased estimator by their mean squared error criterion. I found that two parameter biased estimator performs better than its corresponding ridge regression estimator. Overall, Liu estimator performs better than both ridge and two parameter biased estimator.