Table 5.
Multiple linear regression analyses performed by backward regression.
| Model | Independent factor | β | Lower 95% interval | Upper 95% interval | P value | R 2 |
|---|---|---|---|---|---|---|
| Model 1a (SD) | 24 h SBPV | 0.024 | 0.009 | 0.038 | 0.002 | 0.159 |
| Constant | 0.662 | 0.486 | 0.838 | 0.000 | ||
|
| ||||||
| Model 2b (CV) | 24 h SBPV | 0.028 | 0.010 | 0.045 | 0.003 | 0.141 |
| Constant | 0.671 | 0.488 | 0.853 | 0.000 | ||
|
| ||||||
| Model 3c (ARV) | Daytime SBPV | 0.027 | 0.010 | 0.043 | 0.002 | 0.157 |
| Constant | 0.689 | 0.527 | 0.851 | 0.000 | ||
|
| ||||||
| Model 4d (Mix) | Daytime SBPV (ARV) | 0.027 | 0.010 | 0.043 | 0.002 | 0.157 |
| Constant | 0.689 | 0.527 | 0.851 | 0.000 | ||
aModel 1: using the SDs of blood pressure as the independent factors. bModel 2: using the coefficients of variation of blood pressure as the independent factors. cModel 3: using average real variabilities of blood pressure as the independent factors. dModel 4: backward regression using the significant independent factors from model 1 to model 3.