AIMS AND METHODS: By analyzing data from 2,861 individuals who underwent general health screening 2 years running, we have investigated the impact of changes in waist circumference (WC) and body mass index (BMI) over a 1-year period on systolic blood pressure (BPs). We termed WC, BMI, and BPs at the first visit as WC1, BMI1, and BPs1, respectively, and those at the second visit as WC2, BMI2, and BPs2, respectively. The %dWC, %dBMI, and %dBPs was defined as (WC2 - WC1)/WC1 x 100, (BMI2 - BMI1)/BMI1 x 100, and (BPs2 - BPs1)/BPs1 x 100, respectively. RESULTS: In multivariate regression analysis using age, BPs1, WC1, and %dWC as independent variables, %dWC was a significant predictor for %BPs only in men. %dBMI was a significant predictor for %BPs in both genders when age, BPs1, BMI1, and %dBMI were used as independent variables. Compared with individuals with both %dWC <0 and %dBMI <0, age-adjusted %dBPs was significantly greater in those with both %dWC <0 and %dBMI >or=0; however, it did not significantly differ in those with both %dWC >or=0 and %dBMI <0. CONCLUSION: Our data suggest that the impact of BMI change might be greater than WC change in terms of BPs change during this short period. Copyright 2009 S. Karger AG, Basel.
AIMS AND METHODS: By analyzing data from 2,861 individuals who underwent general health screening 2 years running, we have investigated the impact of changes in waist circumference (WC) and body mass index (BMI) over a 1-year period on systolic blood pressure (BPs). We termed WC, BMI, and BPs at the first visit as WC1, BMI1, and BPs1, respectively, and those at the second visit as WC2, BMI2, and BPs2, respectively. The %dWC, %dBMI, and %dBPs was defined as (WC2 - WC1)/WC1 x 100, (BMI2 - BMI1)/BMI1 x 100, and (BPs2 - BPs1)/BPs1 x 100, respectively. RESULTS: In multivariate regression analysis using age, BPs1, WC1, and %dWC as independent variables, %dWC was a significant predictor for %BPs only in men. %dBMI was a significant predictor for %BPs in both genders when age, BPs1, BMI1, and %dBMI were used as independent variables. Compared with individuals with both %dWC <0 and %dBMI <0, age-adjusted %dBPs was significantly greater in those with both %dWC <0 and %dBMI >or=0; however, it did not significantly differ in those with both %dWC >or=0 and %dBMI <0. CONCLUSION: Our data suggest that the impact of BMI change might be greater than WC change in terms of BPs change during this short period. Copyright 2009 S. Karger AG, Basel.
Authors: X Chen; H Du; J Zhang; X Chen; G Luo; X Que; N Zhang; Z Bian; Y Guo; L Li; Z Chen; X Wu Journal: J Hum Hypertens Date: 2015-02-05 Impact factor: 3.012