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ObjectiveTo investigate the association between ZJU index and the onset of nonalcoholic fatty liver disease （NAFLD） in the Uygur population and the value of ZJU index in predicting the risk of NAFLD. MethodsThe Uighur community of The 51st Regiment of The Third Division of Xinjiang Kashgar Corps was selected as the investigation site， and the Uygur residents who lived in this area and had an age of >18 years were selected as subjects. Follow-up studies were conducted in 2019， 2020， and 2021， and the investigation of outcomes was completed in June to August of 2021. Finally 10 597 subjects were enrolled for analysis. The Kruskal-Wallis H test was used for comparison of continuous variables between groups， and the chi-square test was used for comparison of categorical variables between groups. The subjects were divided into Q1-Q4 groups according to the level of ZJU index. The Kaplan-Meier curve was used to predict the incidence rate of NAFLD， and the Cox regression model was used to analyze the association between ZJU index and the risk of NAFLD； the area under the ROC curve （AUC） was used to evaluate the value of ZJU index in predicting the risk of NAFLD. ResultsDuring the median follow-up time of 4.92 years， the incidence rate of NAFLD was 9.4% （992/10 597） among the study population. After adjustment for multiple factors， there was a significant increase in the risk of NAFLD with the increase in ZJU index， with a hazard ratio of 2.55 （95% confidence interval ［CI］： 1.60 — 4.06）， 7.32 （95%CI： 4.78 — 11.20）， and 21.74 （95%CI： 14.32 — 33.00）， respectively （all Ptrend<0.001）. The ROC curve showed that ZJU index had a higher value in predicting NAFLD （AUC=0.816）， and the male subgroup had a significantly higher predictive accuracy of ZJU index than the female subgroup （AUC： 0.829 vs 0.809）. ConclusionZJU index is a predictive factor for the onset of NAFLD in the Uygur population in rural areas of Xinjiang and has a good value in predicting the risk of NAFLD.
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Objective@#To construct and confirm a predictive model for the risks of cardiovascular diseases (CVD) with metabolic syndrome (MS) and its factors in Xinjiang Kazakh population.@*Methods@#A total of 2 286 Kazakh individuals were followed for 5 years from 2010 to 2012 as baseline survey. They were recruited in Xinyuan county, Yili city, Xinjiang. CVD cases were identified via medical records of the local hospitals in 2013, 2016 and 2017, respectively. Factor analysis was performed on 706 MS patients at baseline, and main factors, age, and sex were extracted from 18 medical examination indexs to construct a predictive model of CVD risk. After excluding the subjects with CVD at baseline and incomplete data, 2007 were used as internal validation, and 219 Kazakhs in Halabra Township were used as external validation. Logistic regression discriminations were used for internal validation and external validation, as well as to calculate the probability of CVD for each participant and receiver operating characteristic curves.@*Results@#The prevalence of MS in Kazakh was 30.88%. Seven main factors were extracted from the Kazakh MS population, namely obesity factor, blood lipid and blood glucose factor, liver function factor, blood lipid factor, renal metabolic factor, blood pressure factor, and liver enzyme factor. The area under the curve (AUC) for predicting CVD in the internal validation was 0.773 (95%CI 0.754-0.792). In the external validation, the AUC for predicting CVD was 0.858 (95%CI 0.805-0.901).@*Conclusions@#The CVD risk prediction model constructed by 7 main factors extracted from Kazakh MS patients has high validation efficiency and can be used for risk assessment of CVD in Xinjiang Kazakh population.
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Objective:To construct and confirm a predictive model for the risks of cardiovascular diseases (CVD) with metabolic syndrome (MS) and its factors in Xinjiang Kazakh population.Methods:A total of 2 286 Kazakh individuals were followed for 5 years from 2010 to 2012 as baseline survey. They were recruited in Xinyuan county, Yili city, Xinjiang. CVD cases were identified via medical records of the local hospitals in 2013, 2016 and 2017, respectively. Factor analysis was performed on 706 MS patients at baseline, and main factors, age, and sex were extracted from 18 medical examination indexs to construct a predictive model of CVD risk. After excluding the subjects with CVD at baseline and incomplete data, 2007 were used as internal validation, and 219 Kazakhs in Halabra Township were used as external validation. Logistic regression discriminations were used for internal validation and external validation, as well as to calculate the probability of CVD for each participant and receiver operating characteristic curves.Results:The prevalence of MS in Kazakh was 30.88%. Seven main factors were extracted from the Kazakh MS population, namely obesity factor, blood lipid and blood glucose factor, liver function factor, blood lipid factor, renal metabolic factor, blood pressure factor, and liver enzyme factor. The area under the curve (AUC) for predicting CVD in the internal validation was 0.773 (95% CI 0.754-0.792). In the external validation, the AUC for predicting CVD was 0.858 (95% CI 0.805-0.901). Conclusions:The CVD risk prediction model constructed by 7 main factors extracted from Kazakh MS patients has high validation efficiency and can be used for risk assessment of CVD in Xinjiang Kazakh population.
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Objective@#To compare metabolic syndrome(MS)with Framingham risk score as predictors of cardiovascular disease(CVD)among Kazakhs population.@*Methods@#The participants were the residents who had been followed up for more than 5 years in representative areas of Kazakhs in Xinjiang. We assigned MS a continuous risk score for predicting the development of CVD based on the weights of MS components. MS and Framingham risk score were compared in terms of their ability in predicting years in representative areas of Kazakhs in Xinjiang. We assigned MS a continuous risk score for predicting the development of CVD based on the weights of MS components. MS and Framingham risk score were compared in terms of their ability in predicting development of CVD using Cox regression and receiver operating characteristic curve.@*Results@#The incidence of CVD was 13.87%. The incidence of CVD was higher in the MS group than it in the non-MS group(21.59% vs 11.10%, P<0.001). The area under the receiver operating characteristic(ROC)curve of MS risk score was significantly larger than that of MS classification(0.727 vs 0.585, P<0.001); the area under the curve of MS risk score was close to that of Framingham risk score(0.732 vs 0.727, P=0.673). The association between CVD and each quintile of MS risk score was more significant than that between Framingham risk score and CVD under the same exposed condition(4.61, 9.33, 14.15, 22.29 vs 3.69, 6.36, 8.47, 16.99).@*Conclusion@#MS risk score that included age may be a better predictor of CVD among Kazakhs population.
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Objective To compare metabolic syndrome(MS)with Framingham risk score as predictors of cardiovascular disease( CVD) among Kazakhs. Methods The participants were the residents who had been followed up for more than 5 years in representative areas of Kazakhs in Xinjiang. We assigned MS a continuous risk score for predicting the development of CVD based on the weights of MS components. MS and Framingham risk score were compared in terms of their ability in predicting years in representative areas of Kazakhs in Xinjiang. We assigned MS a continuous risk score for predicting the development of CVD based on the weights of MS components. MS and Framingham risk score were compared in terms of their ability in predicting development of CVD using Cox regression and receiver operating characteristic curve. Results The incidence of CVD was 13.87％. The incidence of CVD was higher in the MS group than it in the non-MS group(21.59％ vs 11.10％, P<0.001). The area under the receiver operating characteristic(ROC)curve of MS risk score was significantly larger than that of MS classification(0.727 vs 0.585, P<0.001);the area under the curve of MS risk score was close to that of Framingham risk score ( 0. 732 vs 0.727, P=0.673). The association between CVD and each quintile of MS risk score was more significant than that between Framingham risk score and CVD under the same exposed condition(4.61、9.33、14.15、22.29对3.69、6.36、8.47、16.99) . Conclusion MS risk score that included age may be a better predictor of CVD among Kazakhs.
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Objective To investigate the prevalence of metabolic syndrome and appropriate cut-off point of waist circumference of abdominal obesity for components of metabolic syndrome in Uygur population in Xinjiang. Methods A questionnaire-based survey, physical examination, and blood testing were conducted according to cluster random sampling in Uygur residents above 18 years old in Xinjiang.There were 3 542 samples collected,based on the International Diabetes Federation(IDF)standard of metabolic syndrome, the relativities of clustering of metabolic syndrome components and different strata of waist circumference for Uygur were analyzed,and looking for the appropriate cut-off points for identifying two or more components of metabolic syndrome within the shortest distance of receiver operating characteristic(ROC)curve.Results According to IDF standard,the waist circumference(85 cm for men,82 cm for women)corresponded to the shortest distance in ROC curve,at these cut-offs of abdominal obesity for component of metabolic syndrome,the prevalences of metabolic syndrome were 21.3%,19.5%in men, while 23.0%in women,the prevalence of women was higher than that of men(P<0.05).The prevalences of≥1,≥2 components of metabolic syndrome were shown an increasing trend with the increasing size of waist circumference, and the odds ratio of clustering of metabolic syndrome components were also increased significantly.Conclusion The prevalence of metabolic syndrome among Xinjiang Uygur population was higher than that of national level.The cut-off points of waist circumference(85 cm for men,82 cm for women)combining other components definition of IDF standard were recommended for identifying metabolic syndrome of Uygurs.
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Objective To investigate the effect of haplotype and linkage disequilibrium of PPARγgene rs3856806, rs12490265, rs1797912, and rs1175543 in patients with metabolic syndrome ( MS) in Kazakhs of Xinjiang.Methods MALDI-TOF-MS was used to detect PPARγgene rs3856806, rs12490265, rs1797912, and rs1175543 genotypes in 489 subjects ( including 245 MS and 244 controls ) .Results ( 1 ) The frequencies of rs3856806T, rs12490265A, rs1797912C and rs1175543G alleles for MS group in Kazakhs were all significantly lower than those for controls [ rs3856806T allele:12.53% vs 17.01%; rs12490265A allele: 31.84% vs 38.52%;rs1797912C allele:35.31%vs 43.24%;rs1175543G allele:40.61%vs 47.54%(all P<0.05)].(2)Significant linkage disequilibrium were observed between PPARγgene rs1797912 and rs1175543, rs12490265, and rs1175543 polymorphisms.(3)AGCC and GAAT were significantly different between MS and control group in Kazakhs(both P<0.05).(4) Carrying rs3856806T, rs12490265A, rs1797912C, rs1175543G was 0.267 times that of carrying rs3856806C, rs12490265G, rs1797912A, rs1175543A.Conclusions The PPARγgene rs3856806, rs12490265, rs1797912 and rs1175543 polymorphisms were associated with metabolic syndrome in Kazakhs.There were very strong linkage disequilibrium between PPARγgene rs1797912 and rs1175543, rs12490265 and rs1175543 polymorphisms, The AGCC haplotype and GAAT haplotype may serve as protective factors of metabolic syndrome.Carrying rs3856806T, rs12490265A, rs1797912C, and rs1175543G may confer lower risk of MS in Kazakhs.
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Objective To investigate the prevalence and associated risk factors of diabetes mellitus in populations of Hans and Kazaks in Xinjiang. Methods A total of 7 299 Hans and Kazaks adults from Shihezi, Xinyuan County of Yining city, and Shawan town of Tacheng City were surveyed. The data were collected according to questionnaire and physical examination and laboratory test. Results The prevalence rates of diabetes mellitus for male, female and all subjects were 8. 14% , 7. 77% , 7. 93% (Hans), and 7. 41% , 4. 90% , 5. 89% (Kazaks), respectively in Hans and Kazaks, Standardized rates were 6. 40% , 7. 06% , 6. 66% (Hans), and 5. 87% , 4. 60% , 5. 28% ( Kazaks), respectively . The prevalence rates of impaired fasting glucose( IFG) were 9. 54% , 8. 08% , 8. 70% ( Hans), and 12. 18% , 8. 62% , 10. 03% ( Kazaks), respectively. Standardized rates were 7. 04% , 7. 23% , 8. 54% ( Hans), and 10. 12% , 8. 09% , 9. 31% ( Kazaks), respectively. Old age, hypertension, dyslipidemia, overweight and obesity, and central obesity were risk factors for diabetes mellitus. Conclusion The prevalence rates of diabetes mellitus and IFG in Hans and Kazaks are higher than those in ethnic minorities in other region. Primary or secondary prevention should be implemented in time.
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Objective To investigate the relationship between polymorphisms of PPARγ gene(rs1801282, rs3856806 and rs4684847) and hypertension in Uygur. Methods Polymorphisms of PPARγ gene,rs1801282, rs3856806 and rs4684847, were identified in 145 hypertension patients and 165 healthy volunteersby matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Results(1)Frequencies of rs1801282 CC genotype and C allele were 75.9% and 87.2% in hypertension grouprespectively, which were higher than those in control group (63.6% and 79.7%, respectively, P 0.05). (5) SBP in rs1801282 CC genotypecarriers was higher than in CG / GG gene ones, whereas TC was opposite (P < 0.05). Conclusions In theUygur, individuals with CC genotype and C allele at rs1801282 of PPARγ gene are at higher risk ofhypertension. Polymorphism of rs3856806 and rs4684847 may be irrelevant with hypertension in the Uygur.
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Objective: To observe the characteristics of serum homocysteine (Hcy) distribution and the epidemiological characteristics of high serum level of Hcy (HHcy) in Kazakh population. Methods: The stratiifed cluster random sampling method was used to investigate 1003 kazakh individuals in Xinyuan county of Xinjiang including 433 male and 570 female, and they were individuals into 5 age groups:①(25-34) years, n=333,②(35-44) years, n=306, ③(45-54) years, n=230, ④(55-65) years, n=90, ⑤>65 years, n=44. The questionnaire survey, physical check-up and blood biochemical examination were performed and compared among different groups. Results: ① The geometrical mean of Hcy was 13.3μmol/L, and the male was higher than female as 16.0μmol/L vs 11.6μmol/L. ②By age stratiifcation, the serum levels of Hcy elevated with the increased age accordingly. Except for those with the age>65 years, the serum levels of Hcy were all higher in male than female in other 4 age groups. ③The average rate of HHcy prevalence was 31.5%, and the male was higher than female as 49.9%vs 17.5%.④The average rate of H type hypertension prevalence was 35.1%, and the male was higher than female as 44.3%vs 28.1%. There were 87.6%of H type hypertensive patients with H type hypertension, and the male was higher than female as 95.0%vs 80.0%, all P Conclusion: The serum levels of Hcy were different from gender and age; the prevalences of HHcy and H type hypertension were higher in Kazakh population at Xinyuan county of Xinjiang. Community intervention should be conducted to improve the public health condition in Kazakh population.
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Questionnaire-based survey, physical examination, and blood testing were conducted according to cluster random samplings in Kazakh residents in Xinjiang.2 760 samples were collected to analyze the association of different strata of waist circumference and clustering of metabolic syndrome (MS) components.Accoding to International Diabetes Federation standard, the prevalence of ≥1and ≥2 components of MS showed increasing trend with the increase of waist circunference, and odds ratio of clustering of MS components also increased significantly.The distance of receiver operating characteristic curve was the shortest and the prevalence of MS was 22.1% ;22.4% in men, and 21.9% in women;when the waist circumference was ≥91 cm for men, and ≥88 cm for women.
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Objective To investigate the association of lipoprotein lipase gene Hind Ⅲ and S447X polymorphisms with metabolic syndrome. Methods PCR-RFLP was used to detect lipoprotein lipase Hind Ⅲ and S447X genotypes in 401 subjects(including 201 controls, 200 metabolic syndrome patients). Results ( 1 ) The levels of waist circumference ( WC ) , hip circumference ( HC ) , waist-to-hip ratio ( WHR ) , body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure ( DBP) , total cholesterol ( TC) , triglyceride (TG), high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), and fasting plasma glucose (FPG) were significantly different between metabolic syndrome group and control group (all P< 0.05). (2)The frequencies of H+H+ genotype,H+allele,SS genotype, and S allele for metabolic syndrome were all significantly higher than those for controls( H+H+ genotype:66. 5% vs 54.2% ,P=0.012; H+ allele:78.0% vs 71.4%, P=0.031;SS genotype:89.5% vs 77. 1% , P = 0.001; Sallel:94.5% vs 87. 56% , P = 0.001). (3) The levels of WC, HC, WHR, BMI, SBP, DBP, TG, LDL-C, and FPG in H + H-/H-H- genotype were significantly lower than those in H+H+ genotype, HDL-C was significantly higher than that in H+H+ genotype ( all P<0. 05). The levels of WC, HC, WHR, BMI, SBP, DBP, TC, TG, and FPG in SX/XX genotype were significantly lower than those in SS genotype, HDL-C was significantly higher than that in SS genotype ( all P< 0.05). (4)Multi-way logistic regression analysis suggested that risk factors for metabolic syndrome were smoking, drinking, and SS genotype (OR value was 4.289,2.268, and 2. 597, respectively ). (5) Result of interaction analysis among different factors indicated that the risk for metabolic syndrome in smoker with SS genotype was 3. 996 times of non-smokers with SX/XX genotype. Conclusions The lipoprotein lipase gene S447X polymorphism is associated with metabolic syndrome risk in Kazakh, and SS genotype and S allele may serve as genetic risk factors of metabolic syndrome, H + H-/H-H- and SX/XX genotypes yield beneficial effect for lipid and blood pressure. SS genotype and smoking may exist additive effect.