Association between abdominal obesity indices and risk of cardiovascular events in Chinese populations with type 2 diabetes: a prospective cohort study.

BACKGROUND: Waist circumference (WC), visceral adiposity index (VAI), lipid accumulation product (LAP), and Chinese visceral adiposity index (CVAI) are considered surrogate indicators of abdominal fat deposition, but the longitudinal association of these indices with cardiovascular (CV) events in adults with type 2 diabetes (T2D) remains unclear. Our study aimed to examine the associations between abdominal obesity indices and incident CV events among people with T2D and to compare their predictive performance in risk assessment. METHODS: The present study included 2328 individuals with T2D from the Xinjiang Multi-Ethnic Cohort. Multivariable Cox regression analyses were applied to assess the associations between abdominal obesity indices and CV events. Harrell's concordance statistic (C-statistic), net reclassification improvement (NRI) index, and integrated discrimination improvement (IDI) index were utilized to evaluate the predictive performance of each abdominal obesity index. RESULTS: At a median follow-up period of 59 months, 289 participants experienced CV events. After multivariable adjustment, each 1-SD increase in WC, VAI, LAP, and CVAI was associated with a higher risk of CV events in people with T2D, with adjusted hazard ratios (HRs) being 1.57 [95% CI (confidence interval): 1.39-1.78], 1.11 (95% CI 1.06-1.16), 1.46 (95% CI 1.36-1.57), and 1.78 (95% CI 1.57-2.01), respectively. In subgroup analyses, these positive associations appeared to be stronger among participants with body mass index (BMI) < 25 kg/m2 compared to overweight/obese participants. As for the predictive performance, CVAI had the largest C-statistic (0.700, 95% CI 0.672-0.728) compared to VAI, LAP, WC, and BMI (C-statistic: 0.535 to 0.670, all P for comparison < 0.05). When the abdominal obesity index was added to the basic risk model, the CVAI index also showed the greatest incremental risk stratification (C-statistic: 0.751 vs. 0.701, P < 0.001; IDI: 4.3%, P < 0.001; NRI: 26.6%, P < 0.001). CONCLUSIONS: This study provided additional evidence that all abdominal obesity indices were associated with the risk of CV events and highlighted that CVAI might be a valuable abdominal obesity indicator for identifying the high risk of CV events in Chinese populations with T2D. These results suggest that proactive assessment of abdominal obesity could be helpful for the effective clinical management of the diabetic population.

Using Multiple Statistical Methods to Derive Dietary Patterns Associated with Cardiovascular Disease in Patients with Type 2 Diabetes: Results from a Multiethnic Population-Based Study.

Background: There are few reports on the relationship between dietary patterns and cardiovascular disease (CVD) risk in patients with type 2 diabetes (T2D). This study aimed to explore relationships between dietary patterns and CVD risk in the T2D population using multiple statistical analysis methods. Methods: A total of 2,984 patients with T2D from the Xinjiang Multi-Ethnic Cohort, 555 of whom were suffering from CVD, were enrolled in this study. Participants' dietary intake was measured by the semiquantitative food frequency questionnaire (FFQ). Three statistical methods were used to construct dietary patterns, including principal component analysis (PCA) method, reduced-rank regressions (RRR) method, and partial least-squares regression (PLS) method. Then, the association between dietary patterns and CVD risk in T2D patients was analyzed by logistic regression. After excluding participants with CVD, the associations between dietary patterns and 10-year CVD risk scores were subsequently evaluated to reduce reverse causality. Results: In this study, four dietary patterns were identified by three methods. Adjustment for confounding factors, subjects with the highest scores on the "high-protein and high-carbohydrate" patterns derived from PCA, RRR, and PLS had higher odds of CVD than those with the lowest scores (OR: 2.89, 95% CI: 2.11-3.96, P trend < 0.001; OR: 2.96, 95% CI: 2.17-4.03, P trend < 0.001; OR: 2.01, 95% CI: 1.50-2.70, P trend < 0.001, respectively). However, the dietary pattern of PCA-prudent was not significantly related to the odds of having CVD in T2D patients (adjusted ORQ4vsQ1: 0.93, 95% CI: 0.70-1.24, P trend =0.474). Interestingly, we also found significant associations between "high-protein and high-carbohydrate" patterns and the elevated predicted 10-year CVD risk in T2D patients (all P trend < 0.05). Conclusion: The positive correlation between "high-protein and high-carbohydrate" patterns and CVD risk in T2D patients was robust across all three data-driven approaches. These findings may have public health significance, encouraging an emphasis on food choices in the usual diet and promoting nutritional interventions for patients with T2D to prevent CVD.

Association between Dietary Inflammatory Index and Type 2 diabetes mellitus in Xinjiang Uyghur autonomous region, China.

BACKGROUND: Diet and inflammation have both been studied in relation to type 2 diabetes mellitus (T2DM). The aim of this cross-sectional study was to examine the association between the Dietary Inflammatory Index (DII®) and T2DM. METHODS: Subjects were adults enrolled in the baseline study of the Xinjiang multi-ethnic natural population cohort and health follow-up study from January to May 2019. The study involved 5,105 subjects (58.7% men) between 35 and 74 years of age. The DII score was calculated from a data obtained via a food frequency questionnaire consisting of 127 food items. RESULTS: Logistic regression analyses were used to estimate the odds ratios (ORs) and 95% confidence intervals (95% CIs) of DII in relation to T2DM. After adjusting for potential confounders, compared to subjects in the 1st DII quintile, subjects in the 5th quintile (i.e., with the most pro-inflammatory diet) had higher odds of T2DM (OR = 3.27, 95%CI:2.38,4.50; p < 0.001). CONCLUSIONS: Our results suggest that a pro-inflammatory diet is associated with a higher risk of T2DM in this population of Chinese adults.

Analysis of risk factors and construction of prediction model of drop out from peritoneal dialysis.

ABSTRACT: This study is to investigate the risk factors for the drop out from peritoneal dialysis.We retrospectively analyzed patients who underwent catheterization between January 1, 2009 and September 30, 2019. The follow-up period ended on November 30, 2019. End point events were the cessation of peritoneal dialysis, including death, conversion to hemodialysis, and kidney transplantation. Kaplan-Meier method was used to analyze peritoneal dialysis curve. Significant factors were included in the multivariate Cox proportional hazards model. Calibration curve was plotted.A total of 377 patients were included in this study. The dropout rate of peritoneal dialysis was 41.38%. The main drop out reason was conversion to hemodialysis, accounting for 41.67% of the total number of drop out, followed by kidney transplantation (28.21%) and death (25%). According to multivariable Cox proportional hazards model analysis, the medium education level (hazard ratio (HR): 2.53, 95% confidence interval (CI): 1.08-5.91, P = .03), high education level (HR: 2.47, 95% CI: 1.03-5.93, P = .04), diabetes (HR: 1.87, 95% CI: 1.24-2.83, P < .03), hypertension (HR: 2.40, 95% CI: 1.64-3.51, P < .01), repeated peritonitis (HR: 5.18, 95% CI: 3.04-8.80, P < .01), and repeated chest complications (HR: 4.98, 95% CI: 2.79-8.89, P < .01) were independent risk factors for dropping out from peritoneal dialysis, while the number of hospitalizations after catheterization (HR: 0.94, 95% CI: 0.89-0.98, P = .01) was protective factor for maintenance of peritoneal dialysis. The C index of the prediction model was 0.74.Higher education level, diabetes, hypertension, repeated peritonitis, and repeated chest complications were the risk factors of dropping out from peritoneal dialysis, while higher number of hospitalizations after catheterization was a protective factor for the maintenance of peritoneal dialysis. The nomogram could predict the probability of dropping out from peritoneal dialysis.

Dietary patterns and their associations with the metabolic syndrome and predicted 10-year risk of CVD in northwest Chinese adults.

The impact of diet on the metabolic syndrome (MetS) and CVD has been investigated widely, but few studies have investigated the association between dietary patterns (DP) and the predicted CVD, derived from reduced rank regression (RRR). The objectives of this study were to derive DP using RRR and principal component analysis (PCA) and investigate their associations with the MetS and estimated 10-year atherosclerotic CVD (ASCVD). We used the baseline dataset from the Xinjiang multi-ethnic cohort study in China, collected from June 2018 to May 2019. A total of 14 982 subjects aged 35-74 years from Urumqi, Huo Cheng and Mo Yu were included in the analysis. The 10-year ASCVD risk was estimated using the Chinese ASCVD risk equations. The associations of DP with the MetS and 10-year ASCVD were determined using multivariable logistic regression models. In Urumqi and Mo Yu, the increased RRR DP score was associated with a higher OR of having the MetS and with a higher OR of elevated 10-year ASCVD risk. However, only the first DP determined by PCA in Urumqi was inversely associated with the MetS and elevated 10-year ASCVD risk. The prevalence of the MetS and elevated ASCVD risk in urban population is higher than that in rural areas. Our results may help nutritionists develop more targeted dietary strategies to prevent the MetS and ASCVD in different regions in China.

Prevalence of, and risk factors for underweight or excess weight in patients with chronic obstructive emphysema from a multiethnic region of Xinjiang, China.

BACKGROUND: The purpose of this study is to assess the basic nutritional status (body metabolic index, BMI) and its risk factors in the patients suffering from chronic obstructive emphysema. METHODS: We described their demographic characteristics and comorbidity distribution of 2812 obstructive emphysema participants. Comparative analyzes were conducted on BMI with different demographic characteristics and comorbidities status, and comprehensive analysis on risk factors of excess weight and underweight in patients with different characters. RESULTS: The prevalence of underweight and excess weight was 17.57% and 31.54% respectively. There were differences in the distribution of three types of body mass index among patients with different demographic characteristics and different comorbidities. The study found that age of 50 ~ 64 (odds ratio, OR: 2.99), tuberculosis (OR: 2.41), and low TG (OR: 2.32) were the risk factors about underweight. Low HDL-C (OR: 4.15), nonalcoholic fatter liver (NAFLD) (OR: 3.96), and age of 50 ~ 64 (OR: 2.72) were closely related to the excess weight of participants. CONCLUSIONS: This study highlighted the prevalence of underweight and excess weight in patients among emphysema. Comorbidities were important risk factors of underweight or excess weight among chronic emphysema patients. These findings were important for the prevention and treatment of chronic obstructive emphysema in the future.

Comparison of lipid accumulation product and body mass index as indicators of diabetes diagnosis among 215,651 Chinese adults.

PURPOSE: We aimed to assess if lipid accumulation product (LAP) could outperform body mass index (BMI) as a marker for diabetes diagnosis. METHODS: We analyzed the results of a national physical examination project in Urumqi, China. This project was conducted in 442 community clinics in Urumqi from October 2016 to February 2017. RESULTS: LAP was highly correlated with diabetes. The subjects with higher amounts of LAP had a higher risk of diabetes, and the prevalence of diabetes in the fourth quartile of LAP was dramatically higher than in the first quartile (5.72% vs. 21.76%). The adjusted odds ratios (AOR) associated with diabetes in the fourth quartile of LAP was significantly higher than the AOR associated with diabetes in the first quartile, and when BMI ≥ 28 kg/m2 was compared with BMI < 28 kg/m2 (3.24 (3.11, 3.37) vs. 1.65 (1.60, 1.70)). The LAP's area under the curve (AUC) was significantly higher than the BMI's AUC when based on diabetes (0.655 vs. 0.604). In the normal BMI group, 34% of participants had a LAP value higher than the cutoff point found during ROC analysis. In this subgroup, we observed a significantly higher prevalence of diabetes that was similar to that of the subgroup with a BMI ≥ 28 kg/m2, and both of their LAP values were higher than the cutoff point. CONCLUSION: When use as a tool for diabetes diagnosis, LAP performed better than BMI, implying that LAP could be a preferable anthropometry assessment.