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. 2013 Jun 25;15(9):630–636. doi: 10.1111/jch.12155

Table 3.

Univariate and Multivariate Regression Analysis of FMD‐AUC 120 and ΔFMD

FMD‐AUC120 ΔFMD
Covariate Univariate Multivariate Univariate Multivariate
r P Value β P Value r P Value β P Value
Age −.20 .001 −.17 .014 −.09 .132 −.06 .435
Body mass index −.03 .640 −.08 .182
Office systolic blood pressure −.16 .011 .01 .921 −.07 .249 −.04 .664
Office diastolic blood pressure −.02 .570 .02 .725
Office pulse rate −.02 .805 .02 .793
Home systolic blood pressure −.23 <.001 −.27 .003 −.13 .041 −.06 .513
Home diastolic blood pressure −.06 .350 −.02 .780
Home pulse rate −.02 .802 −.01 .906
Total cholesterol .07 .282 .02 .721
Log triglyceride −.05 .432 −.02 .703
Log fasting glucose −.08 .184 .00 .984
Log hemoglobin A1c .00 .999 .05 .427

Multiple linear regression analysis was performed to determine the variables with independent significant association with flow‐mediated vasodilation (FMD) response calculated as the area under the dilation curve during 120 seconds after deflation (FMD‐AUC120). Age, sex, office and home systolic blood pressure, and variables with P<.05 in univariate analysis were included in the model (calcium channel blocker use).