ABSTRACT
Background and Aim: Diabetes is one of the chronic diseases with no curative treatment; also, it is the most common cause of amputation, blindness and chronic renal failure and the most important risk factor of heart diseases. Logistic regression is one of the statistical analysis models for predicting that can be used to find out the relationship between dependent and predictor independent variables and control of the confounding variables. The aim of this study was to determine the rate of effective variables on diabetes and estimation of the logistic regression model for predicting
Methods: 5357 persons in Kerman city, Iran, were enrolled. Diabetes considered as the response variable and weight, height, body mass index [BMI], waist circumference, hip circumference, waist-to-hip ratio [WHR], age, gender, occupation, education, drugs, drug abuse, activities, systolic and diastolic blood pressure, and levels of total cholesterol, the high-density lipoprotein [HDL], the low-density lipoprotein [LDL], and triglycerides were considered as independent variables in the model. Measures of sensitivity, specificity, accuracy, Kappa measure of agreement and ROC [receiver operating characteristic] curve was applied for determining the power of test
Results: The Sensitivity, specificity, accuracy rate, Kappa measure of agreement and area under the ROC curve for the model were 0.764, 0.725, 0.731, 0.312 and 0.822, respectively. The following variables were significant according to their impact and their importance, respectively: WHR [beta = 2.66, OR=14.32], anti-hypertensive drug [beta =1.279, OR= 3.59], sex [beta =0.707, OR= 2.028], level of education, walking and cycling [beta = 0.136, OR= 1.146], waist circumference [beta =0.12, OR= 1.127], weight [beta = 0.112, OR= 1.118], BMI [beta = 0.053, OR= 1.054], systolic blood pressure [beta =0.052, OR= 1.054], age [beta =0.046, OR= 1.047], diastolic blood pressure [beta =0.043, OR= 1.044], total cholesterol [beta = 0.003, OR= 1.003], triglycerides [beta =0.01, OR= 1.011], LDL [beta = 0.001, OR= 1.001], hip circumference [beta = - 0.025, OR= 1.025], height [beta = -0.071, OR= 0.932], HDL [beta = -0.078, OR= 0.925], an intense 10-minute work activities [beta = -0.507, OR=0.602]
Conclusion: According to the criteria of accuracy and power of prediction, and considering ROC curve value [0.822] which could perform test accuracy as well for the diagnosis of diabetes, the logistic regression model was an appropriate model for the prediction of diabetes in this study
ABSTRACT
Traffic and problems around it is one of the important problems of industrial countries the prevention of which can develop the country and determine the health people's. Cycle drivers are considered as high risk drivers of the roads for sustaining most loss. While putting on helmet can decrease roads deaths and injuries up to 20%-45%, WHO statistics reports the suffering of 25% of traffic victims from head injuries. This is a descriptive study conducted on 210 cycle drivers of Yazd city.The subjects were selected by cluster sampling method in 5 sections of the city. The data were collected by a questionnaire and were then analyzed by SPSS software. Different tests were used to analyze the data. The results indicate that most of the cycle drivers [37.6%] was at the age group of 17-20.Those who enjoyed a driving certificate was 48.6% while 51.4% lacked it. Of them 43.3% used a helmet while 56.7% did not. Also 58.9% of the drivers intended to use a helmet in future. The mean grade score of the attitude of the drivers in the age group under 17 was 55.28 +/- 4.57 and their practice stood at 1 +/- .57. Also the mean grade score of the attitude of the age group 17-20 was 55.08 +/- 6.77 while that for their practice score came to 1.54 +/- .74. The results indicate that using helmet by cycle drivers can have an appropriate effect on their health. It is also shown that using helmet by these drivers is rather low so calling for a need to draw attention of the authorities to the idea