Zhifang Li, Jihong Shi, Yang Wang, Shasha An, Xin Du, Zhe Huang, Chenrui Zhu, Yongzhi Wang, Jie Tao, Shuohua Chen, Shouling Wu
Zhonghua Xin Xue Guan Bing Za Zhi. 2015 Aug;43(8):737-42.
To investigate the distribution and major influencing factors of annual systolic blood pressure variability from a large population cohort.
In this prospective cohort study, data from Kailuan Group employees who attended all 4 physical examinations ( taken in June 2006 to October 2007, June 2008 to October 2009, June 2010 to October 2011, June 2012 to October 2013, respectively) were analyzed (32 959 males and 10 401 females, mean age: (48.2 ± 11.5) years old). Systolic blood pressure variability was defined as the standard deviation (SSD) and the coefficient of variation (SCV) of systolic blood pressure of 4 physical examinations. Multivariate linear regression analysis was used to determine the related influencing factors of SSD and SCV.
(1) The mean of SSD and SCV for this cohort was 10.91 mmHg (1 mmHg = 0.133 kPa) and 8.34%, respectively. SSD and SCV increased in male and female with increasing age (both P < 0.001). (2) Multiple linear regression analysis showed that systolic blood pressure (β = 0.225, P < 0.001), age (β = 0.163, P < 0.001), fasting blood glucose (β = 0.038, P < 0.001), the use of anti-hypertensive drugs (β = 0.038, P < 0.001), sex (β = 0.038, P < 0.001), smoking (β = 0.025, P < 0.001), alcohol drinking (P = -0.022, P < 0.001), physical exercise (β = -0.018, P = 0.001), high-sensitivity c-reactive protein (β = 0.016, P = 0.001) body mass index (β = -0.011, P = 0.018) were related to SSD. Age (β = 0.139, P < 0.001), sex (β = 0.055, P < 0.001), systolic blood pressure (β = 0.047, P < 0.001), fasting blood glucose (P = 0.033, P < 0.001), drinking (β = -0.030, P < 0.001), body mass index (β = -0.026, P < 0.001), the use of anti- hypertensive drugs (β = 0.026, P < 0.001), smoking (β = 0.024, P < 0.001), physical exercise (β = -0.015, P = 0. 001), high-sensitivity c-reactive protein (β = 0. 014, P = 0. 001) were related to SCV.
SSD and SCV increase with increasing age. Systolic blood pressure, age, fasting blood glucose, the use of anti-hypertensive drugs, sex, smoking, drinking, physical exercise, high-sensitivity c-reactive protein, body mass index are major influencing factors for SSD. Age, sex, systolic blood pressure, fasting blood glucose, alcohol drinking, body mass index, the use of anti-hypertensive drugs, smoking, physical exercise, high-sensitivity c-reactive protein are major influencing factors for SCV.
从一大群队列人群中调查年度收缩压变异性的分布及主要影响因素。
在这项前瞻性队列研究中，分析了开滦集团参加了全部4次体检（分别于2006年6月至2007年10月、2008年6月至2009年10月、2010年6月至2011年10月、2012年6月至2013年10月进行）的员工数据（男性32959名，女性10401名，平均年龄：(48.2±11.5)岁）。收缩压变异性定义为4次体检收缩压的标准差（SSD）和变异系数（SCV）。采用多元线性回归分析确定SSD和SCV的相关影响因素。
(1) 该队列的SSD和SCV均值分别为10.91 mmHg（1 mmHg = 0.133 kPa）和8.34%。SSD和SCV在男性和女性中均随年龄增加而升高（均P < 0.001）。(2) 多元线性回归分析显示，收缩压（β = 0.225，P < 0.001）、年龄（β = 0.163，P < 0.001）、空腹血糖（β = 0.038, P < 0.001）、使用降压药物（β = 0.038, P < 0.001）、性别（β = 0.038, P < 0.001）、吸烟（β = 0.025, P < 0.001）、饮酒（P = -0.022, P < 0.001）、体育锻炼（β = -0.018, P = 0.001）、高敏C反应蛋白（β = 0.016, P = 0.001）、体重指数（β = -0.011, P = 0.018）与SSD相关。年龄（β = 0.139, P < 0.001）、性别（β = 0.055, P < 0.001）、收缩压（β = 0.047, P < 0.001）、空腹血糖（P = 0.033, P < 0.001）、饮酒（β = -0.030, P < 0.001）、体重指数（β = -0.026, P < 0.001）、使用降压药物（β = 0.026, P < 0.001）、吸烟（β = 0,024, P < 0.001）、体育锻炼（β = -0.015, P = 0.001）、高敏C反应蛋白（β = 0.014, P = 0.001）与SCV相关。
SSD和SCV随年龄增加而升高。收缩压、年龄、空腹血糖、使用降压药物、性别、吸烟、饮酒、体育锻炼、高敏C反应蛋白、体重指数是SSD的主要影响因素。年龄、性别、收缩压、空腹血糖、饮酒、体重指数、使用降压药物、吸烟、体育锻炼、高敏C反应蛋白是SCV的主要影响因素。
