Table 4. Multivariate analyses for prediction of CIMT.
| Linear regression analysis | Dependent variable: carotid intima-media thickness | |||
| Independent variables | p value* | Beta (standardized) | p value# | Beta (standardized) |
| Age, years | < 0.001 | 0.494 | < 0.001 | 0.391 |
| Gender, male | < 0.001 | 0.467 | < 0.001 | 0.258 |
| Family history of CAD | 0.090 | 0.122 | ||
| Glucose (mg/dL) | 0.706 | -0.025 | ||
| Creatinine (mg/dL) | 0.353 | -0.070 | ||
| Uric acid (mg/dL) | 0.587 | -0.043 | ||
| LDL, mg/dL | 0.019 | 0.155 | 0.257 | 0.054 |
| EAT, mm | < 0.001 | 0.312 | < 0.001 | 0.441 |
| CRP (mg/dL) | 0.644 | 0.029 | ||
| Constant | 0.871 | 0.002 | ||
| Adjusted R2 | 0.554 | 0.519 |
CAD, coronary artery disease; CRP, C-reactive protein; EAT, epicardial adipose tissue thickness; HDL, high density lipoprotein; LDL, low density lipoprotein; SE, standard error.
* Linear and logistic regression analyses with enter method were used for all relevant independent variables which were included if they were significantly different in the univariate analyses. # In addition, the analysis was repeated after a pre-elimination with stepwise method for the independent variables.