Most previous studies on metabolic syndrome (MetS) examined urban and high income settings. We thus investigated the prevalence of MetS among a multi-ethnic population living in a low income rural area and explored the use of visceral adiposity and anthropometric indicators to identify men and women with MetS. We recruited 10,029 individuals of nomadic Kazakhs, rural Uyghur and Han residents in Xinjiang, China. MetS was defined by the Joint Interim Statement criteria. The receiver operating characteristic curve (ROC) was used to compare the area under the ROC curve (AUC) of each index. The age-adjusted prevalence of MetS was 21.8%. The visceral adiposity index (VAI), lipid accumulation product (LAP), body adiposity index (BAI) and the waist-to-height ratio (WHtR) were significantly associated with MetS, independent of ethnic, age, and other covariates. The AUC of VAI, LAP and WHtR were all greater than 0.7, and the LAP was the index that most accurately identified MetS status in men (AUC = 0.853) and women (AUC = 0.817), with the optimal cut-offs of 34.7 and 27.3, respectively. In conclusion, the prevalence of MetS in low income rural adults of Xinjiang was high and the LAP was an effective indicator for the screening of MetS.

Objective: To compare the screening ability of various anthropometric and atherogenic indices for Metabolic syndrome (MetS) using three common criteria and to evaluate the validity of suitable parameters in combination for the screening of MetS among a Kazakh population in Xinjiang. Methods: A total of 3752 individuals were selected using the stratified cluster random sampling method from nomadic Kazakhs (≥18 years old) in Xinyuan county, Xinjiang, China, which is approximately 4407 km away from the capital Beijing. MetS was defined by the International Diabetes Federation (IDF), National Cholesterol Education Program Adult Treatment Panel III (ATP III) and Joint Interim Statement (JIS) criteria. The receiver operating characteristic curve (ROC) was used to compare the area under the ROC curve (AUC) of each index. The sensitivity, specificity, Youden’s index and cut-offs of each index for the screening of MetS were calculated. Results: According to the IDF, ATP III and JIS criteria, 18.61%, 10.51%, and 24.83% of males and 23.25%, 14.88%, and 25.33% of females had MetS. According to the IDF criteria, the waist-to-height ratio (WHtR) was the index that most accurately identified individuals with and without MetS both in males (AUC = 0.872) and females (AUC = 0.804), with the optimal cut-offs of 0.53 and 0.52, respectively. According to both the ATP III and JIS criteria, the lipid accumulation product (LAP) was the best index to discriminate between individuals with and without MetS in males (AUC = 0.856 and 0.816, respectively) and females (AUC = 0.832 and 0.788, respectively), with optimal cut-offs of 41.21 and 34.76 in males and 28.16 and 26.49 in females, respectively. On the basis of the IDF standard, Youden’s indices of WHtR and LAP serial tests for the screening of MetS were 0.590 and 0.455 in males and females, respectively, and those of WHtR and LAP parallel tests were 0.608 and 0.479, accordingly. Conclusion: According to the IDF, ATP III and JIS criteria, both the WHtR and LAP were better indices for the screening of MetS. The WHtR and LAP parallel test was the most accurate.

In 2020, a group of international experts proposed a new term ‘metabolic dysfunction-associated fatty liver disease’ (MAFLD) to replace ‘non-alcoholic fatty liver disease’. This study aimed to describe the epidemic characteristics of MAFLD, incidence of cardiovascular disease (CVD), and relationship between MAFLD and incident CVD. In 2016, 12,794 Uyghur adults from Kashgar, Xinjiang, were grouped according to the presence or absence of MAFLD. The primary outcome was the occurrence of CVD events. Fatty liver was diagnosed using ultrasound. The prevalence of MAFLD was 16.55%. After excluding patients with previous CVD, 11,444 participants were followed up for a median period of 4.7 years. During the follow-up period, the overall CVD incidence was 10.40% (1190/11,444). The incidence of CVD in the patients with MAFLD was significantly higher than that in the non-MAFLD patients (18.38% vs. 9.02%, p < 0.001; multivariable-adjusted hazard ratio = 1.37, 95% CI = 1.20–1.56). The prevalence of MAFLD was relatively low, whereas the incidence of CVD was relatively high among the Uyghur adults in rural Xinjiang. Individuals with MAFLD have a higher risk of developing CVD independent of traditional cardiovascular risk factors, obesity, type 2 diabetes mellitus (T2DM), and dyslipidaemia.

Metabolic syndrome (MS) and Framingham risk score (FRS) can be used for predicting the risk of developing cardiovascular diseases (CVD). Previous studies that compared FRS and MS have focused on high-income urban areas. This study focused on the comparison between FRS and MS when used in nomadic minorities in mountain areas. Moreover, an applicable tool for predicting the risk of developing CVD was identified. 2,286 participants who were recruited from the far west of China were followed-up for a median of 5.49 years. MS and FRS were compared in terms of their ability in predicting development of CVD using Cox regression and receiver operating characteristic curve. After each component of MS was appraised, its area under the curve (AUC) was 0.647. When age was included, the AUC of MS risk score increased from 0.647 to 0.758 (P < 0.001). After adjusting for age, the AUC of FRS decreased from 0.732 to 0.582 (P < 0.001). The association between CVD and each quintile of MS risk score that included age was more significant than that between FRS and CVD under the same exposed condition. In conclusion, MS risk score that included age may be a better predictor of CVD among Kazakhs.

Background. This study involved the development of a predictive 5-year morbidity nomogram for cardiovascular diseases (CVD) in Xinjiang Kazakhs based on cytokine levels. Methods. The nomogram was based on a baseline survey of the town of Nalati in the Kazakh Autonomous Prefecture of Xinjiang from 2009 to 2013. By 2016, we had monitored 1508 people for a median time of 5.17 years and identified CVD events in the study population by collecting case information from local hospitals. The study population was divided into the training (n=1005) and validation cohorts (n=503) in a 2 : 1 ratio. The area under the receiver operating characteristic curve (AUC) was used to verify the predictive accuracy of the nomogram. The result was assessed in a validation cohort. Results. At the end of the study, the incidence of CVD in Xinjiang Kazakhs was found to be 11.28%. We developed a new nomogram to predict the 5-year incidence of CVD based on age, interleukin-6 (IL-6), and adiponectin (APN) levels, diastolic blood pressure, and dyslipidemia. The AUC for the predictive accuracy of the nomogram was 0.836 (95% confidence interval: 0.802–0.869), which was higher than that for IL-6 and APN. These results were supported by validation studies. Conclusions. The nomogram model can more directly assess the risk of CVD in Kazakhs and can be used for CVD risk assessment.

Background: This study aimed to describe the prevalence of metabolically healthy obesity (MHO) and metabolically unhealthy normal weight (MUNW) rural adults in Xinjiang and to explore their influencing factors. Methods: We selected 13,525 Uyghur, Kazakh and Han participants in Kashi, Yili and Shihezi areas in Xinjiang from 2009 to 2010. Weight status was classified according to body mass index. Metabolic phenotype was further defined based on the National Cholesterol Education Program Adult Treatment Panel III criteria. Results: The prevalence of normal weight, overweight, and obesity were 51.6, 30.2, and 14.4%, respectively. The mean age of the population was 45.04 years. The prevalence of MHO was 5.5% overall and was 38.5% among obese participants. The prevalence of MUNW was 15.5% overall and was 30.1% among normal weight participants. A metabolically healthy phenotype among obese individuals was positively associated with females and vegetable consumption ≥4 plates per week. However, this was inversely associated with higher age, red meat consumption ≥2 kg per week, and larger waist circumference (WC). Conversely, a metabolically unhealthy phenotype among normal-weight individuals was positively associated with higher age, red meat consumption ≥2 kg per week, and larger WC; this was however inversely associated with vegetable consumption ≥4 plates per week. Conclusions: The prevalence of MHO among obese adults in Xinjiang is higher than that of Han adults, while the prevalence of MUNW among normal weight adults is lower than that among Han adults. In obese and normal weight participants, higher age, more red meat consumption, and larger WC increase the risk of metabolic abnormality, and more vegetable consumption reduces the risk of metabolic abnormality.