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Correlation Between Serum Uric Acid Level and Central Body Fat Distribution in Patients with Type 2 Diabetes

机译:2型糖尿病患者血清尿酸水平和中枢脂肪分布的相关性

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Background: The aim of this study was to investigate the correlation between serum uric acid level and central body fat distribution in patients with type 2 diabetes (T2DM). Methods: A total of 867 patients with T2DM were enrolled. Measurements of central fat distribution were obtained by dual energy X-ray absorptiometry. Patients were stratified into three groups according to their levels of serum uric acid (SUA). Multiple linear regression analysis was used to determine the association between SUA and central body fat distribution. Logistic regression analysis was used to estimate the risk factors for hyperuricemia (HUA). Mediation analysis was applied to assess the overall, direct, and indirect mediators of SUA levels. Results: Multiple linear regression analysis showed that SUA levels were significantly positively correlated with waist circumference (WC), body mass index (BMI), visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), Android fat mass, Gynoid fat mass, fasting c-peptide (F-CP), and area under the curve of C-peptide (P 0.05 for all). VAT [odds ratio (OR), 2.367; 95% confidence interval (CI), 1.078– 5.197; P 0.001)], WC (OR, 1.041; 95% CI, 1.011– 1.072; P 0.001), high-density lipoprotein (OR, 0.274; 95% CI, 0.104– 0.727; P 0.001), and estimated glomerular filtration rate (OR, 0.966; 95% CI, 0.959– 0.973; P 0.001) were found to be independent risk factors for T2DM patients with HUA. After mediation analysis, BMI and central obesity were found to have different partial effects on the association between SUA and F-CP (P 0.001). Conclusion: In patients with T2DM, HUA was positively correlated with F-CP and central body fat distribution, especially VAT. These results suggest that central obesity may play a role in the positive correlation between HUA and insulin resistance (IR).
机译:背景:本研究的目的是探讨患有2型糖尿病(T2DM)患者血清尿酸水平和中央体脂肪分布的相关性。方法:共注册了867例T2DM患者。通过双能X射线吸收术获得中枢脂肪分布的测量。根据其血清尿酸(SUA)的水平,患者分为三组。使用多元线性回归分析来确定SUA和中央体脂肪分布之间的关联。逻辑回归分析用于估计高尿血症(华)的风险因素。应用中介分析评估SUA水平的整体,直接和间接介质。结果:多元线性回归分析表明,SUA水平与腰围(WC),体重指数(BMI),内脏脂肪组织(VAT),皮下脂肪组织(SAT),Android脂肪质量,龈脂肪脂肪量显着呈正相关禁食C-肽(F-CP),以及C-肽曲线下的面积(全部为P <0.05)。增值税[赔率比(或),2.367; 95%置信区间(CI),1.078- 5.197; P <0.001),WC(或1.041; 95%CI,1.011- 1.072; P <0.001),高密度脂蛋白(或0.274; 95%CI,0.104- 0.727; P <0.001)和估计肾小球过滤速率(或0.966; 95%CI,0.959-0.973; P <0.001)是HUA的T2DM患者的独立风险因素。中调解分析后,发现BMI和中央肥胖对SUA和F-CP之间的关联产生不同的部分效果(P <0.001)。结论:在T2DM患者中,华河与F-CP和中央体脂肪分布呈正相关,尤其是增值税。这些结果表明中央肥胖可能在华和胰岛素抵抗(IR)之间的正相关作用。

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