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芜湖市健康体检人群慢性肾脏病流行病学调查及其相关危险因素分析

Epidemic Investigation of Chronic Kidney Disease and Related Risk Factors in Health Checkup Population in Wuhu City

【作者】 杨沿浪

【导师】 邹和群;

【作者基本信息】 南方医科大学 , 肾脏内科学, 2014, 博士

【摘要】 背景目前慢性肾脏疾病(chronic kidney disease, CKD)已经成为全球性公共卫生问题,其中终末期肾病(end stage renal disease, ESRD)接受肾脏替代治疗人数迅速增长,在13年间我国透析人数从4.17万增至32.4万人。同时CKD患者并发慢性心血管疾病(cardiovascular disease, CVD)也显著高于其他人群,CVD患病率随着CKD的进展而大幅度增加。此外贫血、高血压、钙磷代谢紊乱、肾性骨病等CKD并发症,也增加CKD患者死亡率、降低患者生存质量。以往研究显示在我国慢性肾小球疾病是CKD的首位病因,但随着近年来我国社会经济的迅速发展,人们的生活水平、饮食习惯、生活方式都发生变化,过多的高脂、高热量食物摄入及运动的减少,导致代谢综合征(高血压、高血糖、脂质代谢异常及肥胖)、高尿酸血症等代谢性疾病患病率日益升高。近年来大量研究发现代谢综合征、高尿酸血症正成为导致CKD的主要病因。代谢综合征导致肾脏损害的病理生理机制可能与胰岛素抵抗和炎症、肾脏血流动力学改变、氧化应激、以及内皮功能紊乱和交感神经系统等诸多因素影响肾脏有关。高尿酸血症通过诱导环氧化酶-2(Cyclooxygenase-2, COX-2)、巨噬细胞趋化因子-1(Monocyte Chemoattractant Protein-1, MCP-1)合成增多、肾素血管紧张素-醛固酮系统(Renin-angiotensin-aldosterone system, RAAS)激活以及一氧化氮(Nitrous Oxide, NO)合成抑制,导致肾间质炎症、纤维化,肾小球入球小动脉炎性浸润、平滑肌增生。王海燕教授领导的全国性CKD调查显示:我国大约有1.19亿多慢性肾脏病患者,具有各地区患病率不同、知晓率低的特点,并证实高血压、糖尿病和高尿酸血症等是CKD独立相关危险因素,提出需要进一步CKD患病率及危险因素的调查,提高CKD知晓率,早期防治CKD及危险因素,降低ESRD及并发疾病风险。目前不同社区开展的CKD流行病学调查不同程度存在一些缺点:被调查人员的依从性差、成本-效益比低;肾脏专科医生匮乏;横断面研究不能得出自变量和因变量之间的因果联系等。因此我们在得到EUFP7Program ISN、R&P Project和安徽省教育厅科研项目的资助下,利用芜湖皖南医学院弋矶山医院资料完整的大样本体检人群数据,研究芜湖市健康体检人群CKD的患病率,并研究代谢综合征及其不同组分、高尿酸血症对CKD的影响。对筛选出的CKD患者及高危人群加强健康教育,并提供治疗方案及预防措施,为芜湖市卫生主管部门控制和预防CKD,制定合理的公共卫生政策和有效干预手段提供参考。同时在未来我们利用体检人群资料完整、定期体检的特点,对CKD患者及高危人群建立健康档案、跟踪随访,评估CKD的进展、CKD危险因素控制情况以及各种干预措施对CKD预后的影响,并探寻危险因素和CKD之间的因果关系,肾小球滤过率(glomerular filtration rate, GFR)水平是CKD诊断、分期的重要指标,目前多根据内源性标志物血肌酐相关GFR计算公式评估肾功能。由于开发和验证GFR计算公式人群的疾病状态、种族不同,同时血肌酐参数受年龄、性别、饮食及实验室检测方法等肾外因素影响,所以GFR计算公式并不能适用于所有人群肾功能评估,采用不同的GFR计算公式可能影响对CKD患病率的评估,因此需要更多流行病研究去观察不同的GFR计算公式对不同的人群的适用性,本研究比较研究慢性肾脏病流行病学合作研究公式(Chronic Kidney Disease Epidmiology Collaboration,CKD-EPI)和中国肾脏病饮食改良公式(Chinese Modification of Diet in Renal Disease,C-MDRD)对芜湖市健康体检人群eGFR <60ml/min/173m2患病率的影响,以及两公式在不同性别、年龄中的eGFR水平的一致性。目的1.比较观察CKD-EPI和C-MDRD公式对eGFR<60ml/min/173m2患病率的影响,以及评估在不同性别、年龄中两公式计算eGFR的一致性2.调查芜湖市成人健康体检人群CKD患病率以及相关危险因素,为CKD早期预防和治疗提供参考。3.调查芜湖市中老年健康体检人群代谢综合征患病率,对比观察在中年和老年人群中代谢综合征对CKD的影响,以及代谢综合征及其不同组分对CKD的影响。4.调查芜湖市中老年健康体检人群高尿酸血症患病率,观察高尿酸血症是否是CKD独立危险因素以及高尿酸血症和高血压关系。方法1.两种GFR计算公式在芜湖市成人健康体检人群中的比较研究以及对CKD患病率及危险因素调查截取2010年1至2012年6月在皖南医学院弋矶山医院体检中心年龄≥18岁接受健康体检的40348名芜湖市城区人群。体检人群在体检前告知清晨采血前禁食12小时,体检前低油低脂饮食、禁饮酒及填写健康体检表(包括年龄、出生年月、既往史和现病史)。身高、体质量、血压指标由接受过培训的专业护士测量并人工输入电脑,血尿实验室结果通过医院LIS系统自动存储入医院计算机中心。取新鲜晨尿,采用试纸法仪器检测尿常规,显微镜下观察红细胞。采集静脉血检测血常规、血糖、总胆固醇、甘油三脂、HDL-C.LDL-C.尿素氮、肌酐和尿酸。血糖、血脂、肾功能通过全自动生化分析仪检测,血常规通过全自动血球分析仪检测。eGFR计算公式:C-MDRD=175×Scr(mg/dL)-1.234×年龄-0.179[女性×0.79];CKD-EPI公式=141×最小值(Scr/k,1)a×最大值(Scr/k,1)-1.209×0.993年龄×1.018(女性)。K=0.7(女性),0.9(男性)。α=-0.329(女性),-0.411(男性)。最大值:Scr/K的最大值or1,最小值:Scr/κ的最小值or1。CKD诊断标准:根据K/DOQI指南,GFR<60ml/min/173m2和/或尿蛋白(+~+++)2.代谢综合征、高尿酸血症和CKD关系截取上述研究中≥40岁中老年人群,共有24095名人群入选(男性14616名、女性9479名),资料采集同上。eGFR计算公式采用C-MDRD公式。MS诊断标准:2004年中华医学会糖尿病学会(CDS)诊断代谢综合征标准,至少满足下列危险因素3项或更多,①肥胖:体重指数(BMI)≥25kg/m2;②高血糖:空腹血糖≥6.1mmol/L,(或)糖负荷后血糖≥7.8mmol/L及(或)已确诊糖尿病者;③高血压:收缩压和或舒张压≥140/90mmHg已确诊为高血压者;④皿脂紊乱:空腹血甘油三酯≥1.7mmol/L及(或)空腹HDL-C (HDL-C)<0.9mmol/L(男性)、<1.0mmol/L(女性)。高尿酸血症诊断标准:男性血尿酸≥420umol/L、女性血尿酸≥360umol/L。统计学方法计量资料以均数±标准差(x±S)表示,两均数之间比较利用Student’s t-test检验,多组间计量资料采用多因素方差分析(one-way ANOVA),组间多重比较采用LSD方法。计数资料之间率比较利用χ2检验,计数资料一致性检验采用K检验:有一致性(κ=0.21-0.40)、中度一致性(κ=0.41-0.60)、高度一致性(K=0.61~0.80)、接近绝对一致(0.81-1.00)。多因素二分类logistic回归分析各独立危险因素和是否患CKD之间的关系,以优势比(OR)值和95%可信区间(95%CIs)表示。由SPSS11.5统计软件对数据进行处理。Bland-Altman分析采用Medcalc统计软件进行处理。P<0.05认为具有统计学意义。各患病率根据全国第六次人口普查年龄分布进行校正,结果(一)两种GFR计算公式在芜湖市体检人群中的比较研究1.在整个体检人群中,C-MDRD公式计算的GFR(84.56±13.02)高丁CKD-EPI(84.48±13.83)(P<0.001),两公式平均偏倚为0.074±3.83ml/min/1.73m2。 C-MDRD公式和CKD-EPI公式计算GFR时eGFR<60ml/min/1.73m2患病率分别是2.2%、3.6%,K分析显示两公式拟合度高(κ=0.708),相关性显著(r=0.729)。2.在小于60岁的人群中,C-MDRD公式和CKD-EPI公式计算GFR平均偏倚为0.57±3.38ml/min/1.73m2。C-MDRD公式计算GFR时eGFR<60ml/min/1.73m2患病率低于CKD-EPI公式(1.2%vs1.4%,P<0.001)。K分析显示两公式拟合度高(κ=0.815),相关性强(r=0.816)。3.大于60岁的人群中,C-MDRD公式和CKD-EPI公式计算GFR平均偏倚为5.65±2.77ml/min/1.73m2。 MDRD公式计算GFR时eGFR<60ml/min/1.73m2患病率低于CKD-EPI公式(11.1%vs23.0%,P<0.001)。K分析显示两公式拟合度显著降低(κ=0.590),相关性较弱(r=0.647)。(二)健康体检人群CKD的患病率及其相关危险因素研究1.健康体检人群总共有40348人(平均年龄43.25±12.73岁),其中男性24164人(43.62±12.81)、女性16213人(42.66±12.63)。CKD患病率为3.7%,经年龄标化后CKD患病率为4.5%,其中年龄标化后eGFR<60ml/min/1.73m2患病率为2.84%、蛋白尿为2.21%。男性CKD患病率高于女性(4.2%vs3.0%,P<0.001),标化后男女性CKD患病率分别为4.88%,4.07%。2.慢性疾病的患病率:芜湖市成人健康体检人群的年龄标化后肥胖患病率为4.50%、贫血为6.7%、高胆固醇血症为9.26%、高甘油三酯为24.71%、高尿酸血症为14.76%、高血糖为4.24%、高血压为19.72%以及低HDL-C为16.21%。其中男性肥胖、高血压、高血糖、高胆固醇血症、低HDL-C血症及高尿酸血症患病率高于女性(P<0.001),贫血患病率低于女性P<0.001)。3.多因素logistic回归分析:年龄>60岁人群、高尿酸血症、糖尿病、高血压、贫血、低HDL-C、高甘油三酯、肥胖等均为CKD独立危险因素。(三)代谢综合征和CKD关系的研究1.本研究的>40岁健康体检人群总人数是24095人(51.49±9.16岁),其中男性14616人(51.69±9.40岁),女性9479人(51.18±8.78岁),男女年龄间差异无统计学意义。2.年龄标化代谢综合征患病率为14.7%,其中男性代谢综合征患病率高于女性(18.19%、9.7%,P<0.01)。男性各年龄段患病率差别无统计学意义(P=0.11),女性代谢综合征患病率随着年龄而增长(P<0.01)。3.代谢综合征人群CKD患病率高于非代谢综合征人群(10.4%vs4.5%,P<0.001)。4.多因素logistic回归分析,代谢综合征人群、年龄(↑10岁)及男性是CKD独立危险因素(OR:2.29、1.89和1.20),其中在中年人群中(年龄<60岁)代谢综合征导致CKD患病风险高于老年人群(年龄≥60岁)(OR:2.72vs OR:1.72)。5.肥胖、高甘油三酯血症、低HDL-C血症、高血压及高血糖均是导致CKD风险增加的危险因素,其中高血压(OR:1.72,P<0.001)及高血糖(OR1.39,P<0.001)与CKD相关最为显著。CKD的患病率随着代谢综合征组分的增加而增加,其中1-4组分别和0组比较,经年龄、性别校正的CKD患病率OR值分别是1.45、1.34、1.42、1.39(P<0.001)。(四)高尿酸血症和CKD关系研究1.高尿酸血症粗患病率为16.0%,年龄标化后高尿酸患病率为15.59%。其中男性高尿酸血症患病率高于女性(21.6%vs7.3%,P<0.01),年龄标化后男女性高尿酸血症患病率分别为22.14%、10.10%。男女高尿酸血症患病率都随着年龄的增长而上升,其中女性在50岁以后上升显著。2.CKD患病率随着血尿酸水平的升高而升高,尿酸四分位(1-4)的CKD患病率分别是2.1%、3.4%、4.7%和11.1%;其中男性分别为2.7%、3.3%、4.1%和9.9%,女性分别是2.0%、3.5%、7.1%和25.5%。3.以血尿酸第一分位水平组为对照组进行多因素Logistic分析,第二、三、四分位水平组校正后CKD的OR值分别是:1.48(95%CI:1.16-1.90),1.51(95%CI:1.37-1.80),2.23(95%CI:2.03-2.43);校正后蛋白尿的OR值分别为:1.04(95%CI:0.71-1.52)、1.04(95%CI:0.85-1.28)、1.36(95%CI:1.17-1.57),校正后eGFR下降OR值分别是1.64(95%CI:1.17-2.47)、1.93(95%CI:1.58-2.36)和2.45(95%CI:2.15-2.79)。尿酸水平每增加1mg/dL, CKD、蛋白尿及eGFR风险增加1.61倍、1.25倍和1.94倍。4.高尿酸血症人群发生高血压风险较普通人群增加1.17倍,尿酸第四分位水平较第一分位水平高血压风险增加1.15倍(95%CI:1.10-1.21,P<0.001)。结论1.在小于60岁的芜湖健康体检人群中CKD-EPI可以代替C-MDRD公式计算GFR,而在≥60岁人群中所需要采用测量GFR作为金标准,来进一步评价CKD-EPI和C-MDRD公式的精确性和准确性。2.芜湖市健康体检人群CKD患病率水平相对较低,老年、贫血以及慢性代谢性疾病(高血压、高血糖、脂质代谢紊乱、肥胖以及高尿酸血症)是影响CKD主要危险因素。3.在芜湖中老年体检人群中,中年代谢综合征患者CKD的风险高于老年患者。高血压、高血糖、高甘油三酯、低HDL-C及肥胖是CKD的独立危险因素,其中高血糖和高血压是最为显著的危险因素。同时CKD患病率随着MS组分的增加而增加。4.芜湖市中老年健康体检人群中,高尿酸血症是CKD和高血压的独立危险因素,尿酸对肾脏损害呈水平依赖性。5.我们应该健康膳食、纠正不良的饮食习惯、合理运动及降低体重,同时卫生部门加强CKD及其高危人群的筛查,积极治疗高血压、高血糖、肥胖和脂质紊乱等慢性疾病,减少这些慢性疾病导致的心血管疾病和CKD事件的发生。

【Abstract】 Background:The chronic kidney disease (CKD) had become a leading public health problem in the world. End-stage renal disease (ESRD) receiving renal replacement therapy has been rising rapidly, for example the number of ESRD increased from41700to324000in the past13years in China. Meanwhile CKD was associated closely with cardiovascular disease (CVD) and the prevalence of CVD increased dramatically with the progress of chronic kidney disease. The complications of CKD including anemia, hypertension, calcium-phosphorus disorders, and renal bone disease also increased the mortality and reduced the quality of life for patients of CKD.Previous studies had shown that chronic glomerular disease was the first cause of CKD in China, but in recent years China had experienced rapid development of socio-economy, resulting in change of standard of living, eating habits and lifestyle with higher fat intake and less physical activities which had promoted the rising of the chronic disease such as hyperuricemia and metabolic syndrome (hypertension, diabetes, lipid abnormalities and obesity). A large number of studies had found that the metabolic syndrome, hyperuricemia were becoming the major cause of CKD. The underlying mechanisms of MS mediating pathological and pathophysiological change in the kidney included insulin resistance, inflammation, altered renal hemodynamic, oxidative stress, endothelial dysfunction, and the sympathetic nervous system (SNS). Hyperuricemia stimulated expression of cyclooxygenase (COX-2), synthesis of macrophage chemotactic factor-1(MCP-1), activation of rennin angiotensin aldosterone system (RASS) and decrease of nitric oxide (NO) syntheses, which led to inflammation and fibrosis of renal interstitial, thicken of the afferent arterioles and macrophage infiltration, increase of system and local blood pressure. A cross-sectional survey of a nationally representative sample of Chinese adults showed: the number of patients with CKD was estimated to be about119.5million, the prevalence of CKD varied greatly between geographical and the awareness rate of CKD was lower. The factors independently associated with kidney damage were hypertension, diabetes, hyperuricemia, economic status. There was an urgent need for further investigation of prevalence and risk factors of CKD, increasing the awareness rate of CKD, developing preventive and therapeutic approaches to CKD, reducing the risk of ESRD and concurrent disease.There were some disadvantages in community-based epidemic study:the respondent’s poor adherence, lower cost-benefit ratio, the lack of qualified kidney specialists, being hard to draw a causal link between independent variable and dependent variable in cross-sectional study and so on. Our study was supported by EU FP7Program, Anhui province natural science fund. Clinical data of undergoing routine checkups at the Yijishan Hospital of Wannan Medical College were analyzed in this cross-sectional study. We investigated the prevalence of and risk factors associated with CKD, the relation between CKD and MS, hyperuricemia in Wuhu, China. Aim to strengthen the education, provide the measures for preventive and therapeutic approaches to CKD, and help the hygiene department of Wuhu to make a reasonable public health policy. In the future we would follow up the high-risk population and CKD patients in order to assess the progress and control of CKD, various interventions on the CKD, and explored the causal relationship between the risk factors and CKD taking advantage of the characteristics of the regular health checkup and well-kept data-base.Estimating glomerular filtration rate (eGFR) formula was derived from regression analysis in which the level was related to the serum concentration of an endogenous filtration marker such as serum creatinine. Age, gender, diet, weight and laboratory testing method affected serum creainine concentration independently from GFR. Because the eGFR formula was from different development datasets and race, it did not apply to all people to evaluate renal function. No formula would be free of bias in the survey of the prevalence of CKD in all settings and populations, it was obligatory to compare the different eGFR equation in the epidemiological studies. In this study, we investigated the impact of the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Chinese the Modification of Diet in Renal Disease (C-MDRD) on the prevalence of CKD.Objective1. To investigate the difference in prevalence of eGFR<60ml/min/1.73m2by using C-MDRD and CKD-EPI equations respectively and assess the impact of C-MDRD and CKD-EPI eqution on the estimation of GFR in different gender and age group.2. To investigate the prevalence of chronic kidney disease (CKD) and associated risk factors in adult health checkup population in Wuhu City.3. To investigate the prevalence of MS in elderly health checkup, and the relationship between MS or its components and CKD.4. To investigate the prevalence of HUA in elderly health checkup population, evaluating whether the serum uric levelwas associated with CKD and hypertension.Methods1. Prevalence of CKD and associated risk factor inan annual health checkup population.In this cross-sectional study, data was collected from40,348residents (aged18to92years old) between January2010and June2011. Serum laboratory tests and urine dipstick/urinalysis were performed on all participates. All the participants were categorized by age into six groups according to decade (<30,30-39,40-49,50-59,60-69, and≥70years). Clinical datawas obtained from the hospital’s health checkup center. All participants underwent an overnight fasting (at least12hours, low fat, without alcohol) prior to collection of venous blood samples. Gender, birthdates, and medications were recorded. Height, weight, and blood pressure were also measured by trained nurses, and entered into the database. Dipstick testing of the first morning fresh urine was performed. A urinary protein level of1+or greater was considered abnormal. Hematuria (>=1+red blood cells) were confirmed by microscopic analysis.Three or more red blood cells observed in a high-power field (HPF) were considered abnormal.Menstruating women were not considered to have abnormal hemograms. Laboratory testing of venous blood was obtained for glucose, cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), uric acid, and creatinine levels (LH hematology analyzer). Serum creatinine was measured by ammonia iminohydrolase method. All samples were analyzed in the hospital’s clinical laboratory.eGFR was calculated by the C-MDRD equation and CKD-EPI equation as follows. C-MDRD equation which was validated for the Chinese population as follows:eGFR (ml/min/1.73m2)=175xScr (mg/dl)-1234×age (years)0.179[femalex0.79] CKD-EPI:eGFR (ml/min/1.73m2)=141×min(Scr/k,1) a×max(Scr/k,1)-1.209×0.993age×1.018(if female)。where Scr is serum creatinine, k is0.7for female and0.9for males,a is-0.329for female,-0.411for male。 min indicates the minimum of Scr/K or1, max indicates the maximum of Scr/K or1.According to the Kidney Disease Outcomes Quality Initiative (K/DOQI) classification system, an eGFR of less than60ml/min/1.73m2and/or proteinuria and/or hematuria to be indicators of CKD.2. The relationship between either metabolic syndrome orhyperuricemia and CKD Among above health checkup population, a total of24095participates of subpopulation older than40years were analyzed, including male14616and female9479, and their eGFR was calculated by the C-MDRD equationThe Chinese Diabetes Society criteria (CDS) in2004were used to define metabolic syndrome in the present study. According to the ADS criteria, participants were classified as having MS if they had three abnormalities or more for those items shown below:a) Obesity:body mass index (BMI)≥24kg/m2;b) Raised fasting glucose:overnight≥6.1mmol/L, or previously diagnosed type2diabetes;c) Hypertension:systolic blood pressure≥140mmHg, or diastolic blood pressure≥90mmHg or treatment of previously diagnosed hypertension;d) Lipid abnormality:triglyceridemia concentration≥1.7mmol/L and/or HDL-cholesterol concentration<0.9mmol/L for male or<1.0mmol/L;Hyperuricemia was defined as a serum uric acid level higher than420μmol/1in males or360μmol/1in femalesCKD was defined as an eGFR of less than60ml/min/1.73m2and/or proteinuria excluding hematuria. Statistical analysisData were presented as the mean±standard deviation for continuous variables and as proportions for categorical variables. Differences between groups wasexamined using Pearson’s chi-squared test for categorical variables and the two-tailed paired Student’s t-test for continuous data. The kappa test for agreement: kappa statistic(k)0.21-0.40is considered fair agreement,0.41-0.60moderate agreement,0.61-0.80substantial agreement and0.81-1.00near-perfect agreement. Multivariate binary logistic regression analysis was used to estimate odds ratios (ORs) by comparing CKD occurrence and associated factors. A p-value of less than0.05was considered to be statistically significant. SPSS version11.5software (SPSS Inc., Chicago, IL, USA) was used for data analysis.Result1Comparison of C-MDRD and CKD-EPI equation in health checkup in Wuhu citya) C-MDRD eGFR was higher than CKD-EPI eGFR in the whole population(84.56±13.83vs.88.48±13.83ml/min/1.73m2, P<0.001), Theaverage difference between the C-MDRD and CKD-EPI equation was0.074±3.83ml/min/1.73m2. The prevalence of eGFR<60ml/min/1.73m2was2.2%when GFR was estimated by C-MDRD equation. The prevalence was significantly lower than the prevalence calculatedby CKD-EPI equation (3.6%). However, kappa statistics showed very good agreement between the two equations(k=0.708). Results given by the two equations was highly correlated(r=0.729).b) Inter-subpopulations comparison was conducted according to sex and age. In the younger group(<60years old), Theaverage difference between the C-MDRD and CKD-EPI equations was0.57±3.38ml/min/1.73m2. The prevalence of eGFR<60ml/min/1.73m2calculated by C-MDRD equation was lower than CKD-EPI (1.2%vs.1.4%, P<0.001=. Kappa statistics showed very good agreement between the two equations (k=0.815) and highly correlated(r=0.816).c) In those aged≥60years old, theaverage difference between the eGFR calculated respectively by C-MDRD and CKD-EPI equation was5.56±2.77ml/min/1.73m2. The prevalence of eGFR<60ml/min/1.73m2by C-MDRD equationwas lower than CKD-EPI (11.1%vs.23.0%, P<0.001=and agreementthe results of the equations was fair(k=0.59) and correlated (r=0.647).2Prevalence of CKD and associated factor in the annual health checkup populationa) The mean age of all participates was43.25±12.73years old, and43.62±12.81for male,42.66±12.63for female. The crude and age-adjusted prevalence of CKD was3.7%,4.5%and the age-standardized prevalence of eGFR<60ml/min/1.73m2, proteinuria and hematuria were2.84%,2.21%,2.12%respectively. The prevalence of CKD in female was significantly higher than in male(4.2%vs3.0%, P<0.001=.b) The prevalence of other chronic disease:the age-standardized prevalence of obesity3.54%, anemia6.7%, hypercholesterolemia9.26%, hypertriglyceridemia24.71%, hyperuricemia being14.76%, diabetes being4.24%, hypertension being19.72%, Low high-density lipoprotein-C being16.21%respectively. The prevalence of obesity, hypercholesterolemia, hypertriglyceridemia, increasd low density lipoprotein cholesterol (HDL-C), hyperuricemia, diabetes in male was respectively higher than female (P<0.01), the prevalence of anemia in male was lower than female (P<0.01).c) The logistic regression analysis showed:the elderly(≥60years), hyperuricemia, diabetes, hypertension, anemia and obesity were independently associated with CKD.3Relationship between metabolic syndrome and CKD among population older than40years in the annual health checkup populationa) The number of participates aged40years or older, were24095in the study. The mean age of these participatess was51.49±9.16years old,51.69±9.40for male (60.7%) and51.18±8.78for female (39.3%).b) The prevalence and age-standardized prevalence of metabolic syndrome was14.1%and14.7%respectively. It was higher in male than in female (18.19%vs.9.7%, P<0.001), the prevalence of metabolic syndrome wasn’t different in male when grouped by age but was different in female when grouped by age.c) The prevalence of CKD was significantly higher among those compared to the their counterparts without the metabolic syndrome (10.4%vs.4.5%, P<0.001=.d) The logistic regression analysis showed:MS, age (↑10years) and male were independently associated with CKD (OR:2.29;1.89and1.20), meanwhile the OR of CKD subpopulation with younger age (<60years old) was higher than the elderly.e) Age, sex-adjusted and multivariate-adjusted logistic analysis showed the ORs for CKD ofobesity(OR:1.19,95%CI:1.06-1.35), hypertriglyceridemia(OR:1.36,95%CI:1.20-1.54), low HDL-C(OR:1.25;95%CI:1.01-1.54), hypertension(OR:1.72;95%CI:1.53-1.94), diabetes(OR:1.39;95%CI: 1.74-2.41) were risk factors of CKD. There was a significant correlation relationship between the number of metabolic syndrome components and the prevalence of CKD. The residents with1,2,3and4or5component of the MS had a1.45,1.34、1.42and1.39-fold increased odds of CKD, respectively, compared with those without any MS component.4Relation between hyperuricemia and CKDa) The crude prevalence and age-standardized prevalence of hyperuricemia was16.0%a nd15.59%respectively. The prevalence of it was21.6%in males which was significantly higher than in females(7.3%) and age-standardized prevalence of hyperuricemia for males and femaleswas22.14%,10.10%respectively, meanwhile the prevalence of it increased with the age, especial in female particular those older than50years of age in female.b) The prevalence of CKD in participates with serum uric acid levels in the first, second, third and fourth quartiles were2.1%,3.4%,4.7%and2.9%;2.7%,3.3%,4.1%and9.9%in male;2.0%,3.5%,7.1%and25.5%in female.c) Compared to the participates with a serum uric acid level at thefirst quartile, the multivariate-adjusted odds for CKD of the second, third and fourth quartiles were1.48(95%CI:1.16-1.90),1.51(95%CI:1.37-1.80),2.23(95%CI:2.03-2.43), the multivariate-adjusted odds for proteinuria being1.04(95%CI:0.71-1.52),1.04(95%CI:0.85-1.28),1.36(95%Cl:1.17-1.57) and multivariate-adjusted odds for low-eGFR being1.64(95%CI:1.17-2.47),1.93(95%Cl:1.58-2.36) respectively. When serum uric acid was analyzed a continuous variable, we observed a positive correlationwith eitherCKD, proteinuria or low-eGFR.d) The hyperuricemia was independently associated with hypertension (OR:1.17,95%Cl:1.13-1.21). Compared to the participates with serum uric acid at the first quartile, the multivariate-adjusted odds for CKD of the second, third and fourth quartiles were1.11(95%CI:1.00-1.24),1.51(95%CI:1.10-1.24),1.15,95%CI:1.10-1.21) respectively.Conclusion1. C-MDRD equation reduced the calculated prevalence of eGFR<60ml/min/1.73m2, especial in those aged≥60years old. Such discrepancies were of importance and should be confirmed and explained by additional studies using GFR measured with a reference methods.2. The prevalence of proteinuria or decreased eGFR was relatively lower in the health checkup populationover18years in Wuhu city. The age, anemia, hyperuricemia, hypertension, diabetes, lipid abnormality and obesity were all independently associated with CKD.3. In the Wuhu health checkup residents aged over40years old, metabolic syndrome was significantly associated with CKD. Hypertension, diabetes, low HDL-C, hypertriglyceridemia and obesity were independently associated with CKD, particularly diabetes and hypertension. There was linear relationship between the number of metabolic syndrome components and CKD.4. The prevalence of hyperuricemia was higher in the health checkup residents aged over40years old. Hyperuricemia was associated with increased prevalence of hypertension and CKD.5. It is suggested to be urgent to ensure health diet, proper exercise, correcting poor eating habits, weight control. It is essential for hygience departments to screen the CKD and high-risk population, controlling chronic diseases such as hypertension, diabetes, obesity and lipid disorders in order to reduce the occurrence of cardiovascular disease and CKD events.

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