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目的利用主成分回归分析法探讨尿酸水平与体检和血生化指标的相关性。方法采用分层整群随机抽样方法,被调查者均接受问卷调查,测量身高、体重、血压、腰围(WC),检测尿酸(UA)、空腹血糖(FPG),血红蛋白(Hb)、甘油三脂(TC)、总胆固醇(TG)、高密度脂蛋白胆固醇(HDL-c),低密度脂蛋白胆固醇(LDL-c)。结果高尿酸组与尿酸正常组比较,各项指标差异有统计学意义(P<0.01);主成分回归分析年龄、血红蛋白、空腹血糖、甘油三脂、BMI、腰围、收缩压与血尿酸值成正相关,HDL与血尿酸值成负相关。结论主成分回归分析能较好解决尿酸相关指标的多重共线性,尿酸与糖尿病、肥胖、高血压、血脂异常密切相关。
Objective To explore the correlation between uric acid level and physical examination and blood biochemical indexes by principal component regression analysis. Methods The stratified cluster random sampling method was adopted. The respondents were surveyed by questionnaire to measure the height, weight, blood pressure, waist circumference (WC), uric acid (UA), fasting blood glucose (FPG), hemoglobin (TC), total cholesterol (TG), high density lipoprotein cholesterol (HDL-c) and low density lipoprotein cholesterol (LDL-c). Results There was significant difference in all the indexes between hyperuricemia group and normal uric acid group (P <0.01). The principal components regression analysis included age, hemoglobin, fasting blood glucose, triglyceride, BMI, waist circumference, systolic blood pressure and serum uric acid Related, HDL and serum uric acid value is negatively correlated. Conclusion The principal component regression analysis can better solve the multi-collinearity of uric acid related indicators, uric acid and diabetes, obesity, hypertension, dyslipidemia are closely related.