Key result
A multiple linear regression model using height, age, and blood pressure accurately assessed pulse wave velocity in women over 45, with no significant difference from tested values (p=0.423).
Cross-Sectional (n=164)
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A multiple linear regression model based on height, age, and blood pressure can accurately estimate pulse wave velocity in adult females over 45.
The purpose of present study is to build a multiple linear regression model using biomechanical theory to assess the relationship of pulse wave velocity (PWV) with blood pressure, height and age. By testing the PWV, blood pressure, height, weight of 164 female adults aged above 45 and existing data, the author constructed a multiple linear regression equation. Through comparing the practical test PWV values with the estimate values from regression model, the result showed that there was no significant difference between the model assessment and practical test values (t=0.833, p=.423>.05). Therefore, the regression model is fit for assessing PWV value by height, age, systolic and diastolic pressure.
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Long Jia (2014) reported a cross-sectional. Height, age, systolic and diastolic pressure was evaluated on Difference between practical test PWV values and estimate values from regression model (p=0.423). A multiple linear regression model using height, age, and blood pressure accurately assessed pulse wave velocity in women over 45, with no significant difference from tested values (p=0.423).
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