Table 2.
Multiple linear regression relating independent variables (x1–x7) to five models with dependent variables (y1–y5)
| Dependent variables |
|||||
|---|---|---|---|---|---|
| Independent variables | y1. Total cholesterol (mmol/l) | y2. LDL cholesterol (mmol/l) | y3. log10triglyceride (mmol/l) | y4. HDL cholesterol (mmol/l) | y5. Rf |
| x1. log10AER (mg/day) | 0.128 (<0.001) | 0.110 (<0.001) | 0.179 (<0.001) | −0.063 (0.024) | −0.185 (<0.001) |
| x2. HbA1c (%) | 0.106 (<0.001) | 0.109 (<0.001) | 0.125 (<0.001) | −0.047 (0.130) | −0.082 (<0.001) |
| x3. BMI (kg/m2) | 0.192 (<0.001) | 0.213 (<0.001) | 0.238 (<0.001) | −0.155 (<0.001) | −0.055 (0.054) |
| x4. CCr (ml/s · 1.73 m−2) | −0.101 (<0.001) | −0.097 (<0.001) | −0.075 (0.008) | −0.014 (0.615) | −0.015 (0.608) |
| x5. Intervention (0 = 1°, 1 = 2°) | 0.030 (0.301) | 0.048 (0.096) | 0.033 (0.239) | −0.058 (0.034) | 0.015 (0.614) |
| x6. Sex (0 = female, 1 = male) | −0.054 (0.063) | 0.050 (0.084) | 0.101 (<0.001) | −0.365 (<0.001) | −0.191 (<0.001) |
| x7. Group (0 = intensive, 1 = standard) | 0.046 (0.164) | 0.032 (0.331) | 0.028 (0.378) | 0.024 (0.443) | −0.032 (0.322) |
| Model multiple r | 0.285 | 0.292 | 0.357 | 0.421 | 0.312 |
Data for independent variables are the β-coefficients normalized by dividing by SD to allow for direct comparison of the strength of the independent variables (P value). Data for the model multiple r are for each dependent variable and represent how well the multiple linear model accounts for the effect of the set of independent variables on each dependent variable (equation form: y1–5 = β0 + β1x1 + β2x2 + β3x3 + β4x4 + β5x5 + β6x6+ β7x7, where β0 is the y-intercept of the regression line).