| Background:With the economic developed and the improvement in the level of social well-off as well as diet changes,the prevalence of hyperuricemia and dyslipidemia increased year by year.Increased serum uric acid and dyslipidemia are strongly associated with hypertension,diabetes,cardiovasculardisease(CVD)and mortality.This project was supported by International Society of Nephrology(ISN).This cross-sectional study was conducted in Wanzhai Town,Zhuhai City,a prominent commercial city in Southern China.To improve the explore the association of serum uric acid and lipid ratios with insulin resistance,CRP and CKD.We also explored the risk factors for hyperuricemia.To improve the understanding of hyperuricemia and dyslipidemia,developing preventive and therapeutic approaches to hyperuricemia and dyslipidemia,Finally can reduce the economic burden of patients.Objective1.To investigate prevalence of hyperuricemia and its comorbidities in a Southern Chinese population.We also explored the risk factors for hyperuricemia.2.To explore the relationship between serum uric acid with insulin resistance in men,premenopausal women and postmenopausal women.3.To explore the relationship between serum uric acid with CRP in men,premenopausal women and postmenopausal women.4.To examine the association of serum lipids,lipid ratios with Chronic Kidney Disease in a Chinese population.5.To explore the association of lipid ratios and triglyceride with insulin resistance in a Chinese population.We also provide the clinical utility of lipid ratios to identify men and women with IR.Methods1.Community Prevalence of Hyperuricemia and its Comorbidities1.1 This cross-sectional study was conducted in Wanzhai Town,Zhuhai City,a prominent commercial city in Southern China.There ere six communities in Wanzhai Town and three of them were randomly selected for this survey.This survey was conducted between June and October in 2012.All adult residents(aged 18 years or older)living in the three communities were invited to participate in the survey.Participants were recruited by mail and home visit.1834 residents voluntarily participated in the survey.The study was approved by The Ethics Committee of The Third Affiliated Hospital of Southern Medical University in Guangzhou.All community residents gave their written informed consent.We have described this cross-sectional study in our previous paper.Data were collected in the local community clinic,health stations or during home interview.Demorgraphic(age and gender),personal health history(hypertension,diabetes stroke,and coronary artery disease)and details about lifestyle(smoking status,alcohol intake and physical activity)were obtained by questionnaire.Anthropometric indexes were collected in the community clinic and measured according to the recommendation by the World Health Organization.Finally,we collected the history of taking medications which may increase or reduce serum uric levels.These medications included diuretics,uricosurics,vitamin C,aspirin and alloprinol.All blood specimens were collected after an overnight fast of at least 10 hours in local community clinic.First morning urine samples were collected.Women who were actively menstruating were excluded from the urine test.Urinary creatinine,serum creatinine,fasting glucose,serum total cholesterol,serum triglyceride,serum high density lipoprotein cholesterol urinary albumin,high sensitivity C-reactive protein(CRP)and serum insulin was measured.1.2 Definitions1.2.1 Hyperuricemia was defined as serum uric acid? 416.4umol/l(7mg/ldl)in men or? 356.9umol/l(6mg/ldl)in women.1.2.2 Estimated glomerular filtration rate(eGFR)was calculated as 175 ×(Scr)-1.234 ×(Age)-0.179 ×(if female,×0.79).Urinary albumin to creatinine ratio(ACR)(mg/g)was calculated as the ratio of urinary albumin to urinary creatitine.CKD was defined as eGFR less than 60 ml/min/1.73m2 and/or ACR ?30mg/g.1.2.3 Metabolism syndrome(MetS)was defined as having at least three of the following five criteria:abdominal obesity(WC ? 90cm in men or ? 80cm in women),elevated triglyceride levels(? 50 mg/dl),low high density lipoprotein cholesterol levels(<40mg/dl in men,or<50mg/dl in women),an elevated blood pressure(?130/85 mmHg)and an elevated fasting glucose level(?110 mg/dl or 6.1 mmol/l).1.2.4 Hypertension was defined as a self-reported history of hypertension and/or a systolic blood pressure ?140 mm Hg and/or a diastolic blood pressure ?90 mm Hg.1.2.5 Diabetes mellitus was defined as a self-reported history of diabetes or fasting serum glucose ?7.0 mmol/l.1.2.6 Insulin resistance was defined as exceeding the 75%percentile of HOMA-IR in normal glucose tolerance subjects.Insulin Resistance(IR)was defined as HOMA-IR>2.691.2.7 Dyslipidemia is defined by the presence of at least one of the following:serum total TC level ?5.18 mmol/L,TG level ? 1.7 mmol/L,LDL-C level ? 3.37 mmol/L,and HDL-C-cholesterol level<1.04 mmol/L,and/or having received treatment for dyslipidemia during the previous 2 weeks.1.2.8 Women at postmenopausal status in our present study were older than 49 years and others at premenopausal status were almost y yonger than 49 years,which was consistent with an epidemiological survey in Guangdong province(Zhuhai is one of cities in Guangdong province),the average of natural menuopause is 48.9 years in women from the urban areas.1.3 Statistical Analysis1.3.1 Data were analyzed using Stata(version 11).Continuous variables were shown as mean ± standard deviation if they had normal distribution.Median and interquartile range were used to show skewed distributed continuous variables.The categorical variables were presented as absolute and relative(%)values or proportion.A two-tailed p value<0.05 was considered significant.All participants were divided into three subgroups:men,premenopausal and postmenopausal women.The baseline characteristics within the three subgroups were examined using the chi-squared test for categorical variables and oneway factor analysis of variance or Wilcoxon rank-sum test for continuous variables.The Bonferroni method was used for multi-comparsion.1.3.2 Logistic regression models were used to explore the potential risk factors for hyperuricemia.The first model was unadjusted.According to previous studies,hypertension,alcohol consumption,metabolic syndrome and obesity attribute to increase risk of gout.Age,alcohol consumption,components of metabolic syndrome and CKD were added into adjusted model.2.Association of Uric Acid with Insulin Resistance in Men,Premenopausal Women and Postmenopausal Women2.1 We used the data from a population-based,cross-sectional survey conducted in Wanzhai Town,Zhuhai City.1834 subjects were included.2.2 Statistical Analysis2.2.1 Data were analyzed using STATA(version 11,Stata Press,College Station,TX,USA).Mean ±standard deviation(SD)was reported for numerical variable.Proportions were reported for categorical variables.All statistical tests were 2-sided,and p<0.05 was considered statistically significant.All participants were divided into three subgroups:men,premenopausal and postmenopausal women.SUA levels were divided into quartiles.Baseline characteristics of four quartiles subjects were examined in the three subgroups.The continuous variables were analyzed by Wilcoxon rank-sum test and the categorical variables were analyzed by the chi-squared test or Fisher's exact test.2.2.2 The association between SUA and IR:Logistic regression models were used to examine whether UA is associated IR in men,premenopausal and postmenopausal women.SUA was divided into quartiles and used as an independent variable.Model one was adjusted for lifestyle factors(current smoking,alcohol use,physical inactivity),age,sex,comorbidities(history of coronary heart disease,history of stroke),education status and BMI were included.To examine whether hypertension and diabetes are in the pathway between SUA and RI,hypertension and diabetes were included in the next model.The lowest quartile group was a reference category.Logistic regression analyses were conducted separately in men,premenopausal and postmenopausal women.3.Association of Uric Acid with C-Reactive Protein in Men,Premenopausal Women and Postmenopausal Women3.1 We used the data from a population-based,cross-sectional survey conducted in Wanzhai Town,Zhuhai City.1834 subjects were included.3.2 Statistical Analysis3.2.1 Data were analyzed using STATA(version 11,Stata Press,College Station,TX,USA).All participants were divided into three subgroups:men,premenopausal and postmenopausal women.SUA levels were divided into quartiles.p<0.05 was considered statistically significant.3.2 2 The association between SUA and CRP:Logistic regression models were used to examine whether UA is associated IR in men,premenopausal and postmenopausal women.SUA was divided into quartiles and used as an independent variable.Model one was adjusted for lifestyle factors(current smoking,alcohol use,physical inactivity),age,sex,comorbidities(history of coronary heart disease,history of stroke),education status and BMI were included.To examine whether hypertension and diabetes are in the pathway between SUA and CRP,hypertension and diabetes were included in the next model.The lowest quartile group was a reference category.Logistic regression analyses were conducted separately in men,premenopausal and postmenopausal women.4.Serum Lipid Profiles,Lipid Ratios and Chronic Kidney Disease in a Chinese Population4.1 We used the data from a population-based,cross-sectional survey conducted in Wanzhai Town,Zhuhai City.1834 subjects were included.4.2 Statistical Analysis4.2.1 All statistical analyses were conducted using Stata(version 11).Statistical significance was set at P value<0.05.We used mean ± standard deviation to describe continuous variables with a normal distribution and medians and interquartile ranges for skewed distributed variables.Frequencies and percentages were used to indicate categorical variables.Clinical characteristics of the study population were listed.We also compared the characteristics of male and female subjects.Student's T test or rank-sum test were used for continuous variables and the chi-squared test for categorical variables.4.2.2 In order to examine the associations of serum lipids,lipid ratios with CKD,logistic regression models were used for estimating the odds ratios(OR)and 95%confidence interval(CI).In the current study,the associations of serum lipids,and lipid ratios with CKD were explored in male and female subjects,respectively.The models were adjusted for socio-demographic status(age and educational attainment),comorbidities(history of hypertension,history of diabetes,and history of coronary heart disease and history of stroke),lifestyle factors(current smoking,current alcohol use,physical inactivity),systolic blood pressure(SBP),diastolic blood pressure(DBP),serum fasting glucose and waist circumference.4.2.3 We also used multivariate regression models to examine the correlations of serum lipids and lipid ratios with eGFR or ACR in each gender,respectively.In the regression models,eGFR or logarithmically transformed ACR was used as a dependent variable,respectively.Multivariate regression models were also adjusted for variables which were used in the logistic regression models.All logistic regression analyses and multivariate regression models were conducted separately in male and female subjects.All variables with a skewed distribution were logarithmically transformed before being analyzed.5.Association between Lipid Ratios and Insulin Resistance in a Chinese Popula Population5.1 We used the data from a population-based,cross-sectional survey conducted in Wanzhai Town,Zhuhai City.614 men and 1055 women without diabetes were included.5.2 Statistical Analysis5.2.1 All statistical analyses were performed using Stata(version 11).In the present study,all statistical analyses were run in men and women separately.Descriptive statistics for continuous variables were presented as mean ± standard deviation if variables were normally distributed or as median and interquartile range if variables were skewed distributed.Frequencies and percentages were used to express categorical variables.A p-value of<0.05 was considered significance.In the present study,we divided both men and women into two different BMI categories:a normal-weight subgroup and an overweight/obese subgroup.Clinical characteristics of subjects in different BMI categories were presented and compared using Student t test or rank-sum test for continuous variables and the chi-squared test or Fisher's exact test for categorical variables.5.2.2 To explore whether lipid ratios and TG are associated with IR in Chinese individuals,logistic regression models were used and odds ratios(ORs)and 95%confidence interval(CI)were calculated.Lipid ratios and TG were used as an independent variable,respectively.In the adjusted models,potential confounders were added.These confounders included socio-demographic status(age and educational attainment),lifestyle factors(current smoking,current alcohol use,and physical inactivity),waist circumference,systolic blood pressure and diastolic blood pressure.The prior study indicated waist circumference is associated with IR even in normal-weight individuals,so waist circumference was also added as a covariate.5.2.3 We used HOMA-IR as a continuous variable to examine the correlations of HOMA-IR with the lipid ratios and TG.The models were adjusted for age,educational attainment,current smoking,current alcohol use,physical inactivity,waist circumference,systolic blood pressure and diastolic blood pressure.All variables with a skewed distribution including HOMA-IR,TG,the TG/HDL-C ratio,the TC/HDL-C ratio and the LDL-C/HDL-C ratio were logarithmically transformed in the regression models.5.2.4 Accurate estimates of the area under the receiver operating characteristic(AUROC)curve analysis was conducted by using the TG/HDL-C ratio,the TC/HDL-C ratio,the LDL-C/HDL-C ratio,and TG as continuous variables in the logistic regression models.The AUROC of waist circumference is assigned as a standard AUROC.The AUROCs were also adjusted for covariates used in the logistic models.We also used another anthropometric index,BMI,as a continuous variable in the logistic regression models to examine whether BMI is a better predictor of IR than waist circumference and the lipid ratios.Youden's index was calculated as(specificity + sensitivity-1)and used to select the optimal cut-offs for each lipid ratio and TG.Results:1.Community Prevalence of Hyperuricemia and its Comorbidities1.1 1834 participants with mean age 52.8 ± 14.5 years were included in the current study.Among them,679 were men(37.02%)and 1155(62.98%)were women.Among 1155 women,498 women were defined as premenopausal status and 657 women were classified as postmenopausal status.There was no signifiant difference in the mean age between men and women.Men had higher serum uric acid levels than women(P<0.001).Postmenopausal women had significant higher serum uric acid levels than premenopausal women(P<0.001).There were significant differences in history of hypertension,diabetes,coronary heart disease,and alcohol consumption among three subgroups.Premenopausal women had lower systolic blood pressure and diastolic blood pressure than postmenopausal women and men(P<0.001).Postmenopausal women had higher systolic blood pressure than men(P<0.001),but there was no significant difference in diastolic blood pressure between men and postmenopausal women.1.2 Prevalence of hyperuricemia and its comorbidities:The prevalence of hyperuricemia in men,premenopausal women and postmenopausal women were 42.71%(290),15.06%(75),and 34.25%,respectively.Men had a higher prevalence of hyperuricemia than both premenopausal and postmenopausal women(P<0.001).Menopausal status affected the prevalence of hyperuricemia in women,and postmenopausal women had a higher prevalence of hyperuricemia than premenopausal women(P<0.05).Hyperuricemia often coexisted with metabolic syndrome,hypertension,CKD,central obesity,insulin resistance or elevated triglyceride levels in three subgroups.There were significant differences in the prevalence of metabolic syndrome,hypertension,diabetes,central obesity,insulin resistance,elevated triglyceride levels and low high density lipoprotein cholesterol levels in subjects with hyperuricemia among three subgroups.1.3 Risk factors for hyperuricemia in men and women:In adjusted model,age was associated with hyperuricemia in women but not in men.CKD was associated with hyperuricemia in both women and men.Among components of metabolic syndrome,waist circumference and elevated serum triglyceride were associated with hyperuricemia in both women and men.But elevated blood pressure was only significantly associated with hyperuricemia in women.2.Association of Uric Acid with Insulin Resistance in Men,Premenopausal Women and Postmenopausal Women2.1 We included 1,834 participants with mean age 52.8 ± 14.5years in our study.Among them,679(37.02%)were men and 1,155(62.98%)were women.Sex-specific SUA quartiles were used as follows:Q1:<345?mol/L,Q2:345?<400?mol/L,Q3:400?<468?mol/L,Q4:? 468 ?mol/L in males;Q1:<248pmol/L,Q2:248?<288?mol/L,Q3:288?<328?mol/L,Q4:? 328 ?mol/L in premenopausal women;and Q1:<281?mol/L,Q2:281?<330?mol/L,Q3:330?<380?mol/L,Q4:? 380?mol/L in postmenopausal women.In men,premenopausal and postmenopausal women subgroups,subjects with the higher quartile SUA had a higher BMI,a larger waist circumference,higher systolic blood pressure,higher diastolic blood pressure.And,subjects with the higher quartile SUA also had higher serum creatinine levels,higher CRP levels,higher triglyceride levels and lower eGFR.These differences were significant(p<0.05).2.2 After adjustment for age,comorbidities(history of coronary heart disease,history of stroke),lifestyle factors(current smoking,alcohol use,physical inactivity),education status BMI hypertension and diabetes,SUA was not independently associated with an increased risk for insulin resistance in men.2.3 After adjustment for age,comorbidities(history of coronary heart disease,history of stroke),lifestyle factors(current smoking,alcohol use,physical inactivity),education status BMI hypertension and diabetes,women with higher quartiles of SUA had an increased risk for insulin resistance comparing to women with the lowest quartile SUA in both premenopausal and postmenopausal women,.(RR 3.28,95%CI 1.48,7.25,P=0.003;RR 3.71,95%CI 2.07,6.66,P<0.001,respectively).In the postmenopausal women cohort,the third quartile SUA had a 102%increased risk for insulin resistance(RR 2.02,95%CI 1.13,3.63,P=0.02,comparing the highest to the lowest quartile).3.Association of Uric Acid with C-Reactive Protein in Men,Premenopausal Women and Postmenopausal Women3.1 After adjustment for age,comorbidities(history of coronary heart disease,history of stroke),lifestyle factors(current smoking,alcohol use,physical inactivity),education status BMI hypertension and diabetes,SUA was independently associated with an increased risk for CRP in men.The highest quartile SUA had a 78%increased risk for CRP((RR 1.78,95%CI 1.03,3.08,P=0.04,comparing the highest to the lowest quartile).3.2 After adjustment for age,comorbidities(history of coronary heart disease,history of stroke),lifestyle factors(current smoking,alcohol use,physical inactivity),education status BMI hypertension and diabetes,In the postmenopausal women cohort,the highest quartile SUA had a 162%increased risk for CRP((RR 2.62,95%CI 1.42,4.82,P=0.002,comparing the highest to the lowest quartile).SUA was not independently associated with an increased risk for CRP in premenopausal women.4.Serum Lipid Profiles,Lipid Ratios and Chronic Kidney Disease in a Chinese Population4.1 Clinical Characteristics of Study Population:A total of 1834 subjects(the mean age was52.8 ± 14.5years)were included in the analysis.Among 1834 subjects,only 235(12.81%)subjects had CKD.Men had a significantly larger waist circumference,a higher SBP and a higher DBP than women.Women had a higher level of eGFR than men,but there was no significant difference on prevalence of CKD between men and women.In the past three months,no subjects used contrast agents or antibiotics.The proportions of current smokers and current alcohol use were significantly higher in men.Men had a higher TG/HDL-C ratio,a higher TC/HDL-C ratio and a higher LDL-C/HDL-C ratio than women,and all of these differences were significant(P<0.05).Men also had higher serum TGs and lower HDL-Cs than women.4.2 Association of Serum Lipids,Lipid Ratios with CKD in Male and Female Subjects:In unadjusted models,TC,logarithm-transformed(log)TG,and log TG/HDL-C ratio were significantly associated with CKD in male subjects.After adjusted for age,educational attainment,comorbidities,lifestyle factors,blood pressure,fasting glucose and waist circumference,only log TG was associated with CKD.The odds ratio(every SD increment)was 1.39(95%CI 1.03-1.87,P =0.03).In the unadjusted model,TC,log TG,log LDL-C/HDL-C ratio,log TG/HDL-C ratio and log LDL-C/HDL-C ratio were associated with the risk of incident CKD in female subjects.However,further adjusted for potential confounders,none of the serum lipids and lipid ratios was associated with CKD.4.3 Correlation of eGFR or ACR with Serum Lipids and Lipid Ratios:Correlations of eGFR/ACR with serum lipids and lipid ratios in each gender were shown in Table 3.In the adjusted models,log TG and log TG/HDL-C were negatively correlated with eGFR in male subjects(P<0.05).In female subjects,serum TC,log TG,log TG/HDL-C ratio and log TC/HDL-C ratio were negatively correlated with eGFR(P<0.05).All of serum lipid profiles and lipid related ratio were not correlated with ACR.5.Association between Lipid Ratios and Insulin Resistance in a Chinese Population5.1 Clinical characteristics of three subgroups in different CRP categories:In both men and women,overweight/obese subjects had a larger waist circumference and higher levels of lipid ratios than normal-weight subjects.Compared with the normal-weight subjects,overweight/obese subjects had significantly higher levels of lipid ratios and TG.Overweight/obese subjects also had higher blood pressures and higher levels of fasting glucose,and the differences were significant.5.2 VAssociations of lipid ratios and TG with IR defined by HOMA-IR in different BMI categories:In normal-weight men,none of lipid ratios nor serum TG was associated with IR in the adjusted models.In overweight/obese men,the TG/HDL-C ratio,the TC/HDL-C ratio and TG were significant associated with IR,and the associations were independent of waist circumference and other potential confounders.In normal-weight women,all of lipid ratios and TG were significantly associated with IR and the associations were independent of other confounders.In overweight/obese women,the TG/HDL-C ratio,the TC/HDL-C ratio,and TG were associated with IR.When HOMA-IR was used as a continuous variable in the adjusted regression models,TG,the TG/HDL-C ratio and the TC/HDL-C ratio were significantly association with HOMA-IR in both the normal-weight or overweight/obese men and women(P<0.05).The LDL-C/HDL-C ratio was only associated with HOMA-IR in normal-weight women.5.3 Comparison of AUROCs for potential markers of IR in different BMI categories by sex:In logistic regression models,waist circumference was associated with IR in normal-weight men.The AUROC for waist circumference was 0.71(95%CI 0.61-0.81).In overweight/obese men,the AUROC curve analyses showed that the TG/HDL ratio,the TC/HDL-C ratio and serum TG were acceptable predictors for IR defined by HOMA-IR(the AUROC>0.7).In normal-weight women,waist circumference,the TG/HDL-C ratio,the TC/HDL-C ratio,the LDL-C/HDL-C ratio and TG were suitable predictors for IR.Among four variables,the TG/HDL-C ratio and TG were better predictors for IR than waist circumference and the TC/HDL-C ratio.The TG/HDL-C ratio and TG had significantly higher AUROCs than waist circumference(P<0.05).In overweight/obese women,TG and the TG/HDL-C ratio were acceptable predictors for IR(the AUROC>0.70).The AUROCs for waist circumference and the LDL-C/HDL-C ratio were significantly lower(0.6<AUROC<0.7).BMI was also a suitable predictor for IR in men and normal-weight women(the AUROC>0.7),but it was not better than waist circumference,TG and the TG/HDL-C ratio.5.4 Optimal cut-offs for lipid ratios and TG in male and female subjects:The optimal cut-offs for lipid ratios and TG are listed in table-4.The cut-offs for TG/HDL-C ratio were 1.51 in men and 0.84 in women.The cut-offs for TG were 1.78 in men and 1.49 in women,respectively.In men,the optimal cut-off for TC/HDL-C ratio was 3.80.In women,the optimal cut-off for TC/HDL-C ratio was 3.82.The cut-offs for waist circumference were 87 cm in men and 81 cm in women.Men and women had different cut-offs for BMI(25.15 kg/m2 in men and 23.44 kg/m2 in women).Conclusions1.Hyperuricemia is common and men have a higher prevalence of hyperuricemia than women.Postmenopausal women have a higher prevalence than premenopausal women.Metabolic syndrome,hypertension,CKD,central obesity,insulin resistance or elevated triglyceride levels are common comorbidities of hyperuricemia.CKD,waist circumference and elevated serum triglyceride are associated with hyperuricemia.But age and elevated blood pressure are only significantly associated with hyperuricemia in women.2.SUA was not independently associated with an increased risk for insulin resistance in men.SUA was associated with presence of insulin resistance in premenopausal women and postmenopausal women.The risk for insulin resistance was higher in postmenopausal women than premenopausal women.3.SUA was not independently associated with CRP premenopausal women.SUA was associated with presence of CRP in men and postmenopausal women.4.Among serum lipids profiles and lipid ratios,only serum TG is a suitable predictor for CKD in men and the association is independent of other potential confounders.In women,none of the serum lipids and lipid ratios can be used as a predictor for CKD.Log TG and log TG/HDL-C are negatively correlated with eGFR in both genders.In men,LDL-C and log LDL-C/HDL-C ratio are correlated with ACR.In female subjects,no serum lipid or lipid ratio is correlated with ACR.5.The TG/HDL-C,the TC/HDL-C and TG are associated with IR in overweight/obese men,normal-weight and overweight/obese women.The LDL-C/HDL-C is only associated with IR in normal-weight women.The TG/HDL-C and TG might be used as surrogate markers for assessing IR. |
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