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.