中文摘要：

目的探讨脂质聚集指数（L AP）与女性高尿酸血症的关系。方法本研究为横断面研究。共纳入2006年3-9月重庆市珞璜社区成年女性174例,均为体检人群。测量所有研究对象的身高、体重、腰围（WC）、血压、尿酸（UA）、血糖、胰岛素、血脂,计算体重指数（BMI）,胰岛素抵抗指数（HOMA-IR）和L AP。根据尿酸水平分为正常组及高尿酸症组,采用独立样本的t检验进行比较。根据LAP水平四分位水平分为4组,组间比较采用单因素方差分析。采用Pearson相关分析和多元线性逐步回归分析研究UA和其他变量之间的关系。采用logistic回归分析LAP最高四分位数研究对象高尿酸血症发生风险的比值比（OR）。采用ROC曲线分析各指标对高尿酸血症的预测能力。结果与尿酸正常者相比,高尿酸血症者年龄、WC、TG、空腹胰岛素（FINS）、HOMA-IR和LAP明显增高（P〈0.05）。根据研究对象LAP水平四分位数分组进行比较,年龄、WC、BMI、收缩压（SBP）、舒张压（DBP）、甘油三酯（TG）、总胆固醇（TC）、低密度脂蛋白胆固醇（LDL-C）、空腹血糖（FPG）、餐后2h血糖（2h-PPG）、FINS、HOMA-IR和UA随LAP增高明显增高（P〈0.05）,而高密度脂蛋白胆固醇（HDL-C）明显降低（P〈0.05）。Pearson相关性分析显示,UA与年龄、WC、BMI、SBP、DBP、TG、TC、LDL-C、FPG、2h-PPG及L AP呈正相关（P〈0.05）,与HDL-C呈负相关（P〈0.05）。以UA为因变量的多因素分析结果显示,LAP、SBP和HDL-C进入筛选模型（LAP：标准回归系数=0.306,P=0.010;SBP：标准回归系数=0.189,P〈0.001;HDL-C：标准回归系数=–0.185,P=0.014）。Logistic回归分析结果显示,研究对象LAP在上四分位（LAP≥20.2）者比LAP在下四分位者（LAP〈20.2）发生高尿酸血症的风险增加2.02倍（OR=2.02,95%CI 0.305.91,P=0.045）。ROC曲线分析显示,LAP曲线下面积（0.86±0.06,95%CI 0.750.98）。结论在成年女性中LAP

英文摘要：

Objective To explore the relationship between lipid accumulation index （LAI） and hyperuricemia in females. Methods One hundred and seventy-four adult females were included in the cross-sectional study from Mar. to Sep. 2006 through a simple random sampling from a group of population subjected to routine physical examination in the Luohuang Community of Chongqing municipality. The anthropometric measurements, blood pressure （BP）, uric acid （UA）, lipid profile, glucose and insulin levels were measured. Lipid accumulation product （LAP）, body mass index （BMI） and the homeostasis model assessment of insulin resistance （HOMA-IR） were calculated. Subjects were divided into normal group and hyperuricemia group based on their UA levels, and an independent-samples t test was performed for comparison between the two groups; one-factor analysis of variance was performed for multiple comparisons. The Student-Newman-Keuls test was performed for homogeneity of variance. The relationship between UA and other variables was analyzed by Pearson correlation analysis and multiple linear stepwise regression analysis. Logistic regression analysis was used to determine the odds ratio of hyperuricemia in the highest quartile of LAP level. The analysis of the areas under the receiver operating characteristic （ROC） curves was performed to identify the predictive ability of relevantvariables to hyperuricemia. Results Compared with normal group, the age, waist circumference （WC）, triglyceride （TG）, fasting insulin （FINS）, HOMA-IR and LAP were higher in hyperuricemia group （P〈0.05）. The age, and levels ofWC, BMI, systolic blood pressure （SBP）, diastolic blood pressure （DBP）, TG, total cholesterol （TC）, low-density lipoprotein cholesterol （LDL-C）, fasting glucose （FPG）, 2-hour postprandial glucose （2h-PPG）, FINS, HOMA-IR and UA were higher as LAP increased （P〈0.05）, whereas the level of high-density lipoprotein cholesterol （HDL-C） lowered as LAP increased （P〈0.