Statistical analysis
All statistical analyses were performed using IBM SPSS 22.0 for Windows. Kolmogrov-Smirnov and Shapiro Wilk tests were used for evaluating whether the observations are from the normal distribution. In describing the features of data, number of cases (n) and their proportions (%) for categorical variables, median and range for non-normally distributed continous variables and mean and standard deviation for normally distributed continous variables were calculated. Pearson chi-square or Fisher Exact test was used to compare NoDM and NIDDM groups according to categorical variables. The Mann-Whitney U test or two sample t-test were used to compare NoDM and NIDDM groups for continous data obtained from basic features of patients such as age, weight and height. According to the other continous variables, these two tests were also used for the comparison of NoDM and NIDDM groups at each time point. Additionally, the longitudinal data sets in this study were analyzed by a linear regression model with Generalized Estimating Equations (GEE) method which can be applied for normally or non-normally distributed measurements of same patients over time. In GEE analyses, working correlation matrix was assumed to be unstructured. The results of GEE method are corresponding to overall comparison of two groups over all four time points. A p-value<0.05 for two-sided tests was considered statistically significant.