Statistical analysis and visualization

Stata/SE 16.1 software (StataCorp LP, College Station, TX, United States) was used to analyze the statistical data. Statistics were considered significant when p-value <0.05. All study variables were subjected to descriptive statistics analysis, which was provided as frequency (%) for categorical data and mean ± standard deviation (SD) or median for nonnormal quantitative data. One-way analysis of variance (ANOVA) statistic and post hoc analysis using the Scheffe test with p-value <0.05 were utilized if the distribution of the quantitative data, such as age and laboratory results, was normal. The Kruskal-Wallis test and post hoc Mann–Whitney U test with p-value <0.017 were used if the data distribution was not normal.

The following Spearman’s correlation coefficient was analyzed; (1) anthropometric measurements, including BMI and waist circumference (2) physical examination; blood pressure and (3) blood tests; FBS, HbA1C, TC, TG, LDL-C, HDL-C, AST, ALT, and hs-CRP. Correlation heat map visualization was performed using the ggplot2 R package. A p-value <0.05 was considered statistically significant and was labeled in the figure. In addition, the phylogenetic heat tree was visualized using the metacoder R package.