Table 3.
Association of baseline and rate of increase in eGFR (mL/min/1.73 m2) and UACR (mg/g) with LVMI (g/m2) (n = 539) from multiple regression analysis
| Variables | Model 1 |
Model 2 |
Model 3 |
Model 4 |
Model 5 |
Model 6 |
||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| β-Coefficient (95% CI) | P Value | β-Coefficient (95% CI) | P Value | β-Coefficient (95% CI) | P Value | β-Coefficient (95% CI) | P Value | β-Coefficient (95% CI) | P Value | β-Coefficient (95% CI) | P Value | |
| Baseline eGFR | −0.21 (−0.30, −0.12) | <.001 | −0.18 (−0.28, −0.09) | <.001 | −0.07 (−0.19, 0.05) | .23 | −0.11 (−0.23, 0.01) | .06 | −0.08 (−0.19, 0.04) | .18 | −0.11 (−0.23, 0.00) | .06 |
| Baseline UACR | 2.87 (1.55, 4.18) | <.001 | 2.51 (1.20, 3.82) | <.001 | 2.08 (0.72, 3.45) | .003 | 2.00 (0.68, 3.32) | .003 | 2.31 (0.92, 3.72) | .001 | 2.26 (0.87, 3.65) | .002 |
| Gender (female) | −1.35 (−5.03, 2.34) | .47 | −1.02 (−4.57, 2.54) | .57 | −0.93 (−4.49, 2.63) | .61 | −1.23 (−4.78, 2.33) | .50 | ||||
| Waist circumference | 0.16 (0.02, 0.30) | .027 | 0.18 (0.05, 0.32) | .009 | 0.18 (0.04, 0.31) | .01 | 0.18 (0.04, 0.32) | .01 | ||||
| Baseline SBP | 0.16 (0.06, 0.27) | .003 | 0.30 (0.18, 0.41) | <.001 | 0.29 (0.18, 0.40) | <.001 | 0.29 (0.18, 0.40) | <.001 | ||||
| SBP change∗ | 0.26 (0.16, 0.35) | <.001 | 0.24 (0.14, 0.34) | <.001 | 0.25 (0.15, 0.35) | <.001 | ||||||
| Rate of decline in eGFR† | −1.15 (−2.03, −0.28) | .010 | −1.05 (−1.94, −0.17) | .02 | ||||||||
| Rate of increase in UACR‡ | .03 | .04 | ||||||||||
| <0.14 (Ref) | 1.00 | 1.00 | ||||||||||
| 0.14–1.07 | 2.56 (−1.07, 6.19) | .17 | 2.65 (−0.97, 6.27) | .15 | ||||||||
| ≥1.07 | 4.61 (1.18, 8.05) | .009 | 4.19 (0.75, 7.63) | .02 | ||||||||
ACEI, angiotensin-converting enzyme inhibitor; ARB, angiotensin II receptor blocker; CCB, calcium channel blocker; CI, confidence interval; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; HDL, high-density lipoprotein; LDL, low-density lipoprotein; LVMI, left ventricular mass index; SBP, systolic blood pressure; UACR, urine albumin-to-creatinine ratio.
Model 1: Baseline eGFR, baseline UACR (model 1 for each variable).
Model 2: Baseline eGFR + baseline UACR.
Model 3: Variables in model 2 + age, gender, education, waist circumference, diabetes, heart disease, SBP, DBP, smoking, LDL, HDL, triglyceride, ACEI or ARB use, CCB use, β-blocker use, diuretics use, and intervention group.
Model 4: Variables in model 3 + SBP change, DBP change, and rate of decline in eGFR.
Model 5: Variables in model 3 + SBP change, DBP change, and rate of increase in UACR.
Model 6: Variables in model 3 + SBP change, DBP change, rate of increase in UACR, and rate of decline in eGFR.
All models accounted for clustering effect by household as a random effect.
In addition to kidney function biomarkers and gender, variables with P value < .05 in model 6 were reported in the table.
Change in SBP was calculated using SBP at year 7 minus baseline SBP.
Rate of decline in eGFR = (eGFR at year 7 − eGFR at baseline)/duration of follow-up (in y).
Rate of increase in UACR = (UACR at year 7 − UACR at baseline)/duration of follow-up (in y).