论文部分内容阅读
目的探讨广州市中老年人群收缩压(systolic blood pressure,SBP)、舒张压(diastolic bloodpressure,DBP)与血尿酸(uric acid,UA)、血尿素氮(blood urea nitrogen,BUN)浓度的相关性及两组指标间典型相关特征。方法采集广州市中老年人群242例的血标本检测血UA、BUN浓度等,应用柱式水银血压计测量上臂血压3次,取平均血压值。各研究指标间相关性采用Pearson相关分析,应用多元相关分析进一步分析SBP、DBP与血UA、BUN浓度两组指标间的典型相关性,应用逐步回归分析估计因变量为SBP、DBP,解释变量为UA、BUN的回归系数和标准回归系数。结果Pearson相关分析显示广州市中老年人群242例的SBP与血UA浓度呈正相关(r=0.16023,P=0.0126);SBP与血BUN浓度呈正相关(r=0.16424,P=0.0105);DBP与血UA浓度呈正相关(r=0.16562,P=0.0099);DBP与血BUN浓度呈正相关(r=0.13506,P=0.0358)。本组SBP、DBP与血清UA、BUN浓度两组指标间的典型相关系数R_(1,Can)=0.233302,呈低度正相关性,具有统计学意义(F=3.44,P=0.0088)。其标准典型变量V_1主要受SBP的影响(V_1=0.6392×SBP’+0.4649×DBP’),标准典型变量W_1受UA和BUN的影响程度相当(W_1=0.6990×UA’+0.6430×BUN’),逐步回归分析结果显示SBP和DBP皆与UA和BUN有正向回归关系。结论广州市中老年人血清UA、BUN浓度越高的个体其SBP可能越高;血清UA、BUN浓度组合作为预测心血管病的指标可能更有意义。
Objective To investigate the relationship between systolic blood pressure (SBP), diastolic blood pressure (DBP) and uric acid (UA) and blood urea nitrogen (BUN) concentration in middle-aged and elderly people in Guangzhou. Typical correlation between two sets of indicators. Methods Blood samples of 242 middle-aged and old people in Guangzhou were collected to measure blood UA and BUN concentration. Upper arm blood pressure was measured 3 times with a bar-type mercury sphygmomanometer and average blood pressure was taken. Pearson correlation analysis was used to analyze the correlation between the indexes. The multivariate correlation analysis was used to further analyze the typical correlation between SBP, DBP and blood UA and BUN concentrations. The stepwise regression analysis was used to estimate the dependent variables SBP and DBP. The explanatory variables were UA, BUN regression coefficients and standard regression coefficients. Results Pearson correlation analysis showed that there was a positive correlation between SBP and blood UA in 242 middle-aged and elderly people in Guangzhou (r = 0.16023, P = 0.0126), SBP was positively correlated with blood BUN (r = 0.16424, P = 0.0105) UA had a positive correlation (r = 0.16562, P = 0.0099). There was a positive correlation between DBP and blood BUN (r = 0.13506, P = 0.0358). The typical correlation coefficient R_ (1, Can) = 0.233302 between the two groups of SBP, DBP and serum UA, BUN concentrations was a low positive correlation with statistical significance (F = 3.44, P = 0.0088). The standard typical variable V_1 is mainly affected by SBP (V_1 = 0.6392 × SBP ’+ 0.4649 × DBP’). The standard typical variable W_1 is affected by UA and BUN (W_1 = 0.6990 × UA ’+ 0.6430 × BUN’ Stepwise regression analysis showed that both SBP and DBP had a positive regression relationship with UA and BUN. Conclusion The serum SBP of UA and BUN in middle-aged and elderly people in Guangzhou may have higher SBP. The combination of serum UA and BUN may be more meaningful as a predictor of cardiovascular disease.