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The Chinese visceral adiposity index (CVAI) is a recently developed indicator of visceral adiposity. We investigated the predictive value of the CVAI for the development of dysglycemia (pre-diabetes and type 2 diabetes) and compared its predictive power with that of the Visceral adiposity index (VAI) and various anthropometric indices. This community-based study included 2,383 participants. We assessed the predictive power of adiposity indices by performing univariate and multivariate binary logistic regression analysis and calculating the area under the receiver-operating characteristic (ROC) curve according to their quartiles. Logistic regression analysis showed that individuals in higher CVAI quartiles at baseline were more likely to develop dysglycemia than those in lower CVAI quartiles. The area under the ROC curve for CVAI was significantly higher than that of other adiposity indices. In addition, among the various adiposity indices tested, the CVAI had the greatest Youden index for identifying dysglycemia in both genders. Our data demonstrate that the CVAI is a better predictor of type 2 diabetes and pre-diabetes than the VAI, BMI, waist circumference, waist-to-hip ratio and waist-to-height ratio in Chinese adults.

Background Previous studies found elevated serum uric acid (SUA) was associated with the development or progression of non-alcoholic fatty liver disease (NAFLD) in general population; in this study we aim to investigate the association of SUA and the severity of NAFLD based on grade of fatty liver on ultrasonography in non-obese subjects. Methods Data were obtained from subjects via routine physical examinations in the Public Health Center of our hospital between 2011 and 2014. The data included completed anthropometry and blood biochemical indicators and the results of abdominal ultrasound. The diagnosis of NAFLD was according to the clinical diagnosis of the Guidelines for the diagnosis and treatment of nonalcoholic fatty liver disease in 2008. Results In total, 95,924 subjects were analyzed in this study. The prevalence rate of lean-NAFLD was 8.16%, among which 7.58% had mild steatosis, and 0.58% had moderate and severe steatosis. The prevalence of fatty liver was increased progressively with SUA. Among which the prevalence of mild fatty liver from Q1 to Q4 were 10.33%, 18.39%, 23.11% and 25.93%; the prevalence of moderate and severe fatty liver from Q1 to Q4 were 1.06%, 2.82%, 5.05% and 7.27%. Lean-subjects with hyperuricemia had an OR of 1.718 (95% CI 1.622–1.820) to have NAFLD, after adjusted for other metabolic disorders. The area under curve (AUC) for detecting mild fatty liver based on SUA was 0.70; and the AUC for detecting moderate and severe fatty liver based on SUA was 0.78. Conclusions Our data showed positive associations between elevated SUA levels and lean-NAFLD risk in the inland Chinese adults, independent of other metabolic factors. Our study also suggests that SUA could be considered as a simple and non-invasive method to follow up patients with lean-NAFLD.

Background Little is known about the relationship between serum uric acid (SUA) and cardio-ankle vascular index (CAVI) in Chinese population. Therefore, we aimed to investigate the gender difference in the association of SUA and CAVI in a southwestern Chinese population. Methods Data were obtained from subjects via routine physical examinations in the Public Health Center of our hospital between 2011 and 2014 in Chongqing. The data included completed anthropometry and blood biochemical indicators. The CAVI were recorded using an automatically VaseraVS-1000 vascular screening system. Results We found females with hyperuricemia (HUA) had significantly higher CAVI than women with normal SUA (8.45 ± 1.40 vs 7.67 ± 1.15, P<0.05). Then we defined high CAVI as CAVI≥9 m/s, and compared the percentage of high CAVI, we found women with HUA had higher percentage of high CAVI than women with normal SUA (26.83% vs 9.38%, P<0.05). Those differences were not significant in males. Also, the logistic regression analysis found age and hypertension were major independent risk factors associated with high CAVI in both genders. HUA and hyperglycemia were independently associated with high CAVI in females with an OR of 3.65, 95%CI (1.37-9.73) and 3.02, 95%CI (1.38-6.63) respectively. However, these significant associations were not be found in males. Conclusions Our data showed positive associations between elevated SUA levels and higher CAVI risk in the inland Chinese females, but not in males. The reason for the gender differences were still unclear, sex hormones may play a role. Further prospective studies including detailed personal information and multicenter were required.

Lipopolysaccharide-binding protein (LBP) is closely associated with many metabolic disorders. However, no study has been done to explore the relationship between LBP and polycystic ovary syndrome (PCOS). The objective of this study was to investigate whether the serum LBP level is elevated and associated with insulin resistance (IR) in PCOS. In this cross-sectional study, 117 PCOS patients and 121 age-matched controls were recruited. Hyperinsulinemic-euglycemic clamp was performed with an expression of M value for insulin sensitivity. Fasting serum samples were collected to detect LBP, lipids, insulin, sex hormones and high sensitive C reactive protein (hs-CRP). Pearson's correlation and multiple linear regression was used to analyze the associations between M value and LBP level. The study was performed in a clinical research center. Compared with controls, PCOS subjects had a significantly higher LBP concentration (33.03±14.59 vs. 24.35±10.31 μg/ml, p<0.001), and lower M value (8.21±3.06 vs. 12.31±1.72 mg/min/kg, p<0.001). Both in lean and overweight/obese individuals, serum LBP level was higher in PCOS subjects than that in controls. M value was negatively correlated with body mass index (BMI), fasting serum insulin, triglycerides, low-density lipoprotein cholesterol (LDL-c), free testosterone, high sensitive C reactive protein (hs-CRP) and LBP, whereas positively correlated with high-density lipoprotein cholesterol (HDL-c) and sex hormone binding globulin (SHBG). Serum LBP level was associated with M value after adjusting for BMI, fasting serum insulin, SHBG, as well as hs-CRP. Serum LBP level significantly is elevated in PCOS, and is independently associated with IR in PCOS.

AimsCell-free DNA (cfDNA) is associated with diabetes and cardiovascular diseases. Our study was to evaluate whether serum cfDNA could predict the progression of diabetic kidney disease (DKD).MethodsIn this prospective study, a total of 160 patients with DKD were enrolled, and the kidney function was followed up by measurement of estimated glomerular filtration rate (eGFR) and urinary albumin–creatinine ratio (UACR) for three consecutive years. At baseline, concentrations of serum cfDNA were measured. DKD progression was defined as two-continuous decrease in eGFR and changes of UACR from less than 300 mg/g at baseline to higher than 300 mg/g at last follow-up. Regression models were used to analyze associations of serum cfDNA with the DKD progression.ResultsIn total, 131 patients finished all the follow-up visits. At the end of the study, 64 patients showed decreased eGFR and 29 patients had changes of UACR from less than 300 mg/g at baseline to higher than 300 mg/g at follow-up. At baseline, the progression group had higher serum cfDNA levels than the non-progression group (960.49 (816.53, 1073.65) ng/mL vs 824.51 (701.34, 987.06) ng/mL, p=0.014). Serum cfDNA levels were significantly negatively associated with the 1.5-year eGFR change (r=−0.219 p=0.009) and 3-year eGFR change (r=−0.181, p=0.043). Multivariate logistic analyses showed that after adjustment of age, gender, body mass index, fast plasma glucose, smoking, triglycerides, total cholesterol, duration of diabetes, systolic blood pressure, diabetic retinopathy, eGFR, high sensitivity C-reactive protein, angiotensin receptor blocker/ACE inhibitor usage, with the increase of one SD of serum cfDNA levels, the risk of DKD progression increased by 2.4 times (OR, 2.46; 95% CI 1.84 to 4.89).ConclusionSerum cfDNA is closely associated with DKD, and it might be a predictor of DKD progression in patients with type 2 diabetes.

Background This study aimed to compare the prevalence of sarcopenia according to the old and new Asian Working Group on Sarcopenia (AWGS) operational criteria and explore the effects of sarcopenia on adverse outcomes in older adults with type 2 diabetes (T2D). Methods A total of 386 patients with T2D aged ≥ 60 years were recruited in retrospective cohort study. Sarcopenia was assessed with different versions of the AWGS consensus, including the AWGS2014, AWGS2019H (muscle mass adjusted for height), and AWGS2019B (muscle mass adjusted for body mass index). The median follow-up period was 47 months. The composite primary endpoint was the first occurrence of cardiovascular disease (CVD), fragility fracture, and all-cause mortality and the secondary outcomes included the three separate components of the primary outcome. Results In this study, the prevalence of sarcopenia under different criteria was significantly different, with AWGS2019H having the highest prevalence of 31.3%. The agreement among sarcopenia criteria was unsatisfactory. By Cox regression analysis, all three AWGS definitions of sarcopenia were associated with the composite outcome of all-cause mortality, fracture and CVD (hazard ratio [HR], 2.69 vs. HR, 2.63; vs. HR, 2.23; model 3). Further exploratory analysis, sarcopenia defined by the AWGS2019H criteria was an independent risk factor for death, incident CVD, and fractures. While AWGS2014 criteria was an increased risk factor of death and CVD. The AWGS2019B criteria were only associated with incident fractures. Conclusion All three AWGS definitions of sarcopenia were associated the composite primary endpoint. Additionally, the AWGS2019H criteria may be a better independent risk factor for negative health outcomes.

Background: Diabetic kidney disease (DKD) lacks a simple and relatively accurate predictor. The Triglyceride-Glucose (TyG) Index is a proxy of insulin resistance, but the association between the TyG Index and DKD is less certain. We investigated if the TyG Index can predict DKD onset effectively. Materials and Methods: Cross-sectional and longitudinal analyses were undertaken. In total, 1432 type-2 diabetes mellitus (T2DM) patients were included in the cross-sectional analysis. The TyG Index (calculated by In [fasting triglycerides (mg/dL) * fasting glucose (mg/dL)/2]) was split into three tertiles. Associations of the TyG Index with microalbuminuria and estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 [m.sup.2] were calculated. Longitudinally, 424 patients without DKD at baseline were followed up for 21 (range, 12-24) months. The main outcome was DKD prevalence as defined with eGFR <60 mL/min/1.73 [m.sup.2] or continuously increased urinary microalbuminuria: creatinine ratio (>30 mg/mL) over 3 months. Cox regression was used to analyze the association between the TyG Index at baseline and DKD. Receiver operating characteristics curve (ROC) analysis was used to assess the sensitivity and specificity of the TyG Index in predicting DKD. Results: In cross-sectional analysis, patients with a higher TyG Index had a higher risk of microalbuminuria (OR = 2.342, 95% CI = 1.744-3.144, p < 0.001), and eGFR <60 mL/min/1.73 [m.sup.2] (1.696, 95% CI =1.096-2.625, p = 0.018). Longitudinally, 94 of 424 participants developed DKD. After confounder adjustment, patients in the high tertile of the TyG Index at baseline had a greater risk to developing DKD than those in the low tertile (HR = 1.727, 95% CI = 1.042-2.863, p = 0.034). The area under the ROC curve was 0.69 (0.63-0.76). Conclusion: The TyG Index is a potential predictor for DKD in T2DM patients. Clinical Trial: Clinical Trials identification number = NCT03692884. Keywords: diabetic kidney disease, triglyceride-glucose index, insulin resistance

Aims Recently, the association between anemia and diabetic microvascular complications has been studied. Diabetic peripheral neuropathy (DPN) is also a common complication of type 2 diabetes mellitus (T2DM), while the relationship between anemia and DPN is rarely investigated. The aim of this study is to evaluate the association between anemia and DPN in T2DM. Methods In this cross-sectional study, 1134 T2DM inpatients were enrolled. The diagnosis of DPN was based on neuropathy system score (NSS) and neuropathy disability score (NDS). Logistic regression was conducted to analyze the association between anemia and DPN. Results The proportions of anemia in DPN and non-DPN group were 25.4 and 15.2%, respectively. Compared with non-anemia group, the proportions of moderate/severe NSS (42.7 vs. 24.5%, P  < 0.001) and moderate/severe NDS (51.5 vs. 38.0%, P  < 0.001) were higher while the nerve conduction velocity (NCV) was lower in anemia group. Univariate logistic regression analysis showed patients with anemia possessed an increased risk of DPN [ OR  = 1.906, 95% CI : 1.416, 2.567, P  < 0.001]. Multivariate logistic regression analysis suggested anemia was an independent risk factor of DPN in model 1 and model 2 [model 1: OR  = 1.472, 95% CI: 1.047, 2.070, P  = 0.026; model 2: OR  = 1.448, 95% CI : 1.013, 2.071, P  = 0.043]. Conclusions Anemia is an independent risk factor of DPN in T2DM patients.

To investigate age-related changes in body composition (BC) and bone mineral density (BMD) in type 2 diabetes (T2D) and analyse whether diabetes duration or glycaemic control affects these factors. We enrolled 1474 hospitalized T2D patients (817 males and 657 females; 45-85 years). BC and BMD were assessed by dual-energy X-ray absorptiometry (DEXA). Patients were stratified into age groups: 45-54, 55-64, 65-74, and ≥75 years. Continuous variables were compared using -tests or one-way analysis of variance (ANOVA), and categorical variables were compared using chi-square tests. Effects of age, diabetes duration, and haemoglobin A (HbA ) on BC and BMD were assessed with multiple linear regression models. In T2D, in females, changes in fat mass index (FMI) were positively correlated with age, while changes in lean mass index (LMI) were unrelated to age. Changes in FMI or LMI in males were unrelated to age. For regional BC distribution, changes in visceral adipose tissue (VAT) were positively correlated with age for both males and females, while changes in appendage lean mass (ALM) were negatively correlated with age. For BMD, changes in total BMD (TBMD) in males were not correlated with age, while changes in lumbar spine BMD (LBMD) were positively correlated with age, and femoral neck BMD (FNBMD) was negatively correlated with age. Changes in BMD in all parts of females were negatively correlated with age. In addition, changes in BC and BMD were unrelated to diabetes duration, and HbA was mainly associated with decreases in lean mass but had little effect on other BC and BMD parameters. In T2D, changes in BC and BMD were associated with age but not diabetes duration. A higher HbA is associated with lower lean mass.

The prevalence of general obesity (commonly defined by body mass index (BMI) in kg/m ) and abdominal obesity (commonly assessed by waist circumference (WC)) has increased rapidly in China. The aim of this study was to investigate the diagnostic accuracy of traditional cut-offs for BMI or WC to identify general or abdominal obesity in Chinese type 2 diabetic patients and propose optimal cut-offs. BMI and WC were obtained from 1539 type 2 diabetic patients. Body fat percentage and visceral fat area measured by dual-energy x-ray absorptiometry were set as the gold standard to identify general and abdominal obesity. We assessed the diagnostic power of traditional cut-offs for BMI and WC to define obesity, and analyzed receive operating characteristic (ROC) curves to obtain the optimal cut-offs to identify obesity in Chinese type 2 diabetic patients. In Chinese type 2 diabetic patients, the optimal BMI was 25 kg/m with the best trade-off between sensitivity and specificity (men: 74.6% (95% CI: 70.7-78.2%) and 65.1% (95% CI: 59.7-70.3%), AUC 0.78 (95% CI: 0.75-0.81), <0.05; women: 65.8% (95% CI: 60.3-71.0%) and 80.3% (95% CI: 75.7-84.3%), AUC 0.80 (95% CI: 0.77-0.83), <0.05) in both genders. The optimal WC was 93 cm in men and 90 cm in women with the best trade-off between sensitivity and specificity (men: 87.2% (95% CI: 84.3-89.8%) and 80.2% (95% CI: 74.9-84.8%), AUC 0.91 (95% CI: 0.88-0.92), <0.05; women: 81.0% (95% CI: 76.9-84.6%) and 88.7% (95% CI: 83.9-92.4%), AUC 0.92 (95% CI: 0.90-0.94), <0.05). For the Chinese patients with type 2 diabetes, the optimal cut-offs for BMI or WC to identify general or abdominal obesity need to be reconsidered.