Screening Of The Metabolic Syndrome And Prediction Of Cardiovascular Diseases In Kazakh Of Xinjiang

Objectives(1)This research aims to investigate the prevalence of and risk factors of Metabolic Syndrome(MetS)in Kazakh by four widely used criteria(NCEP-ATP?\CDS\IDF\JIS)in order to realize the prevalence situation.It contributes to explore the pathogenesis and prevention measures of MetS.In addition.It also provides reference to selected appropriate indicators for screening of MetS.(2)The lipid accumulation product(LAP),visceral adiposity index(VAI),body adiposity index(BAI),waist-to-height ratio(WHtR),were explored to screen MetS.Compared with the traditional screening index such as: waistline,waist-to-hip ratio and BMI,we identify the most appropriate screening index of MetS for Kazakhs.And these efficient and appropriate screening indexes combination would be explored to screen MetS in Kazakh.(3)The exploratory factor analysis would be used to extract the primary factors of MetS,which could establish the prediction model of cardiovascular(CVD)incidence.The risk of CVD in Kazakh would be estimated by the above model.Then we will classify the risky grades of CVD.Finally the high-risky groups of CVD were identified.The above results would provide basic data for primary prevention of CVD in Kazakh.In addition,our study would provide a new idea to predict the incidence of CVD in the community population.Methods(1)Multistage cluster sampling was employed to choose participants.Four criteria(NCEP-ATP ?\IDF\CDS\JIS)were employed to measure the prevalence of MetS and components in Kazakh.The distribution components of MetS were analyzed by permutation and combination.Non-conditional logistic regression analysis was performed to identify the association between MetS and social demographic characteristics,family history of disease,dietary factors,smoking and drinking,uric acid,Alanine transaminase(ALT),Aspartate aminotransferase(AST).(2)Non-conditional logistic regression analysis was applied to analyze the correlations between MetS and the obesity measurement indexes.The screening test was used to evaluate the validity,reliability,yield of obesity measurement indexes in screening MetS.The receiver operating characteristic curves(ROC)was used to compare the values of obesity measurement indexes in screening MetS.Double-combined-test was used to explore the best combination to screen MetS in Kazakh.The yield of double-combined-test was calculated based on Bayes theorems.(3)EFA was employed to extract the primary factors of MetS stratified by gender.Bartlett spherical test and KMO test were used to analyze the applicable conditions of EFA.We explained the meaning of primary factors by factor loading.The Cox proportional risk model was used to establish the risk prediction model of CVD based on the primary factors of MetS,age,smoking and CVD family history.Omnibus tests of model coefficients were applied to fitting degree of the model.The ROC was used to evaluate the prediction results.We draw the risk-matrix of CVD by this prediction model of CVD.Results(1)Based on the four widely used criteria of MetS,the age-standard prevalence of MetS were 18.90%(NCEP-ATPIII),22.84%(CDS),27.13%(IDF)and 32.16%(JIS),respectively.The prevalenc of MetS increased along with the age.The prevalence of MetS components in descending order were obesity(61.92%),high blood pressure(48.18%),low HDL-C(38.21%),high TG(23.04%),high blood glucose(24.23%).The most common form of three components of MetS was obesity+low HDL-C+high blood pressure(12.69%).Multivariate analysis showed that the major influential factors of MetS in Kazakh were dietary factors,low intake of vegetables(OR=1.74,95%CI:1.31-2.31),high intake of red meat(OR=1.24,95%CI:1.02-1.50),Moderate intake of fresh milk(OR=0.60,95%CI: 0.47-0.77).Hyperuricemia(OR=1.64,95% CI:1.45-1.87),ALT elevated(OR=1.80,95%CI:1.46-2.21),and AST elevated(OR=1.69,95%CI:1.36-2.10)were risk factors.(2)The levels of obesity measurement indexes for patients of MetS were higher than non –MetS population.The strongest association was observed between the MetS and LAP: man(OR=46.60,95%CI:31.98-67.89),woman(OR=47.74,95%CI:33.62-67.81);VAI:man(OR=23.93,95%CI: 17.63-32.49),woman(OR=19.61,95%CI: 14.22-27.06)?the level of Q4 compared Q1.The results of screening test showed that the area under the ROC curve(ROC-area)of LAP was the largest one in screening MetS during man,ROC-area of man(AUC=0.843,95%CI:0.828-0.859)and ROC-area of woman(AUC=0.819,95%CI: 0.805-0.833).The second largest weas VAL,ROC-area of man(AUC=0.760,95%CI:0.787-0.822)and ROC-area of woman(AUC=0.780,95%CI:0.764-0.795).The optimal cutoff points of screening MetS by LAP was 35.58 for man,31.51 for woman.The optimal cutoff points of screening MetS by VAI was 1.67 for man,2.04 for woman.The results of validity evaluation show that the Youden index of LAP was the largest and the second was VAI.The sensitivity of waistline was the highest(man:88.65%,woman:85.10%).The specificity of LAP was the highest in man(82.00%),and VAI in woman(80.32%).The results of reliability evaluation show that the ageement rate and Kappa value of LAP were highest in man(79.25%,0.54),but VAI in woman(74.93%,0.42).Youden index of combined-test between VAI and WHR in man was the highest(0.87),and sensitivity(95.20%),specificity(91.53%),positive prediction value(84.00%),Youden index of combined-test between VAI and waistline were the highest in woman and sensitivity(94.32%),specificity(91.35%),positive prediction value(85.76%).(3)The incidence density of CVD in patients of MetS was 20.89 per one thousand people,which was higher than non-MetS(13.28 per one thousand people).The hazard ratio of CVD was 1.53(95%CI:1.17-1.99)for total population,for man 1.75(95%CI: 1.11-2.76),for woman 1.43(95%CI:1.04-1.98),respectively.The hazard ratio of CVD for man elevated from(HR=4.55,95%CI:1.06-19.60)for one component of MetS to(HR=7.27,95%CI:1.63-32.52)for ?4 components of MetS(HR=2.76,95%CI: 1.20-6.36).The hazard ratio of CVD for woman elevated from(HR=1.78,95%CI:0.81-3.89)for one component of MetS to(HR=2.76,95%CI:1.20-6.36)for ?4 components of MetS(HR=2.76,95%CI:1.20-6.36).The strongest association was observed between the CVD and MetS components for man was obestity(HR=2.17,95%CI:1.31-3.60),and high blood pressure(HR=2.38,95%CI:1.71-3.31).The results of factor analysis show that the primary factors were obesity factor(contribution rate:man: 32.10%,woman:30.39%),obesity and serum lipid factor(contribution rate: man:13.70%,woman:14.90%),cholesterol factor(contribution rate: man:10.44%,woman:12.86%),blood pressure factor(contribution rate: man:8.76%,woman:8.75%),and Serum liver enzyme factor(contribution rate: man:8.04%,woman:7.24%).The prediction model of CVD in man including obesity factor,cholesterol factor,age and coronary heart disease family history.The prediction model of CVD in woman including cholesterol factor,blood pressure factor,age,and smoking.The efficiency evaluation of prediction mode show the AUC was 0.751(95%CI:0.695-0.808)for man,AUC=0.754(95%CI:0.717-0.792)for woman.We draw the risk-matrix of CVD in the patients of MetS in man and woman.The hazard ratio of CVD can be divided into five grades,blue for normal(0-0.1),yellow for light risk danger(0.1-0.2),orange for moderate danger(0.2-0.3),red for high danger(0.4-0.5),deep red,extremely high danger(0.5-0.6).Conclusions(1)The prevalence of MetS in Kazakh was higher than that of national average level of China.Less consumption of vegetables and much intake of red meat were the main risk factors of MetS,while moderate intake of fresh milk was a protective factor of MetS in them.The MetS is typically characterized by the abdominal obestiy in Kazakh.(2)The screening value of LAP and VAI were higher than waistline and BMI.The double-screening-test of VAI and WHR was the best in validity,reliability,yield for man,and VAI and waistline for woman.(3)The primary factors of MetS in Kasakhs were obesity factor,obesity and serum lipid factor,blood pressure factor,cholesterol factor,Serum liver enzyme factor.The prediction power of prediction model of cardiovascular(CVD)incidence was effective,which could identify high-risk groups of CVD.