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Objective:To explore the characteristics of the association between the triglyceride glucose (TyG) index and nonfatal cardio-cerebrovascular disease risk in a community population.Method:This was a prospective cohort study. From December 2011 to April 2012, the first investigation was conducted among subjects with more than 40-year old who were from Shijingshan district and Pingguoyuan community in Beijing. The second investigation was conducted from April to October 2015. All the subjects were divided into three groups according to the tertile of the TyG index at baseline. The multivariate Cox proportional risk regression model was established to explore the correlation between the TyG index and nonfatal cardio-cerebrovascular disease risk and the Kaplan-Meier survival curve of the TyG index group was drawn. Subgroup analyses were performed according to age, gender, body mass index, type 2 diabetes mellitus (T2DM), hypertension, and hyperlipidemia to determine the correlation characteristics between the TyG index and nonfatal cardio-cerebrovascular disease among subgroups.Results:A total of 9 577 subjects were finally included to analyze. The mean follow-up time of this study was (34.14±3.84) months. During the follow-up, 363 subjects (3.8%) occurred nonfatal cardio-cerebrovascular disease. The multivariate Cox regression analysis results showed that the hazard ratio ( HR) of nonfatal cardio-cerebrovascular disease in the high TyG index group was 1.54 (95% CI 1.19-1.98), 1.60 (95% CI 1.23-2.10), and 1.57 (95% CI 1.20-2.05) in the three models, compared with the low TyG index group. The Kaplan-Meier analysis showed that the risk of nonfatal cardio-cerebrovascular disease increased from the low-TyG index group to the high-TyG index group ( P=0.015). In the six subgroups analysis, only gender was shown to have a significant interaction effect with the TyG index and nonfatal cardio-cerebrovascular disease risk. In the female population, the risk of nonfatal cardio-cerebrovascular disease is significantly increased with the increase in the TyG index level ( P<0.001). Conclusions:A high TyG index is independently related to the increased risk of nonfatal cardio-cerebrovascular disease in the Beijing community population. Gender has a significant interaction with the TyG index and nonfatal cardio-cerebrovascular disease risk. Therefore, the TyG index may be a useful marker to predict the nonfatal cardio-cerebrovascular disease risk of a community population.
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Objective:Development and validation of a nomogram for predicting the 4-year incidence of type-2 diabetes mellitus (T2DM) in a Chinese population was attempted.Methods:This prospective cohort study was conducted in Shijingshan District Pingguoyuan Community (Beijing, China) from December 2011 to April 2012 among adults aged≥40 years not suffering from T2DM. Finally, 8 058 adults free of T2DM were included with a median duration of follow-up of 4 years. Participants were divided into a modeling group and verification group using simple random sampling at a ratio of 7∶3. Univariate and multivariate Cox proportional risk models were applied to identify the independent risk predictors in the modeling group. A nomogram was constructed to predict the 4-year incidence of T2DM based on the results of multivariate analysis. The Concordance Index and calibration plots were used to evaluate the differentiation and calibration of the nomogram in both groups.Results:A total of 5 641 individuals were in the modeling group and 2 417 people were in the validation group, of which 265 and 106 had T2DM, respectively, at 4-year follow-up. In the modeling group, age ( HR=1.349, 95% CI 1.011-1.800), body mass index ( HR=1.347, 95% CI 1.038-1.746), hyperlipidemia ( HR=1.504, 95% CI 1.133-1.996), fasting blood glucose ( HR=4.189, 95% CI 3.010-5.830), 2-h blood glucose level according to the oral glucose tolerance test ( HR=3.005, 95% CI 2.129-4.241), level of glycosylated hemoglobin ( HR=3.162, 95% CI 2.283-4.380), and level of γ-glutamyl transferase ( HR=1.920, 95% CI 1.385-2.661) were independent risk factors for T2DM. Validation of the nomogram revealed the Concordance Index of the modeling group and validation group to be 0.906 (95% CI 0.888-0.925) and 0.844 (95% CI 0.796-0.892), respectively. Calibration plots showed good calibration in both groups. Conclusion:These data suggest that our nomogram could be a simple and reliable tool for predicting the 4-year risk of developing T2DM in a high-risk Chinese population.
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In this study, voltage was used as a disturbance factor to investigate the relationship between microbial community and methane (CH4) production flux in a microbial electrolytic cell coupled anaerobic digestion (MEC-AD). Metabolic flux analysis (MFA) was used to explore the relationship between the CH4 metabolic flux produced and the microbes. The results showed that both methane production flux and hydrogen production flux changed significantly upon voltage disturbance, while the voltage disturbance had little effect on acetic acid production flux. The maximum CH4 production flux under 0.6 V disturbance was 0.522±0.051, which increased by 77% and 32%, respectively, compared with that of the control group under 1.0 V (0.295±0.013) and under 1.4 V (0.395±0.029). In addition, an average of 15.7%±2.9% of H2 (flux) was used to reduce CO2 to produce CH4 and acetic acid, and an average of 27.7%±6.9% of acetic acid (flux) was converted to CH4. Moreover, the abundance of Lachnospiraceae significantly affected the flux of acetic acid. The flux of CH4 production is positively correlated with the abundances of Petrimonas, Syntrophomonas, Blvii28, and Acinetobacter, and negatively correlated with the abundances of Tuzzerella and Sphaerochaeta. The species that affected the flux of H2 and CH4 were similar, mostly belonging to Bacteroides, Clostridium, Pseudomonas and Firmicutes. Furthermore, the interspecies interaction is also an important factor affecting the MEC-AD methanogenesis flux.