Relationships Between the Apolipoprotein Levels and Sarcopenia in Inpatients with Type 2 Diabetes Mellitus: A Cross-Sectional Study.

Background: Apolipoprotein (Apo) may be associated with sarcopenia in elderly inpatients with type 2 diabetes mellitus (T2DM), but fewer studies are available. In this study, we explored the association of ApoA1, ApoB, and ApoB/ApoA1 with sarcopenia and compared the predictive role of Apo indicators for sarcopenia in an elderly T2DM. Objective: To investigate the relationships between the Apo and sarcopenia in elderly inpatients with T2DM. Methods: This study included 253 inpatients with T2DM (mean age of 70.11±5.44 years, 32.8% male). The inpatients were divided into the sarcopenic group (n = 100) and non-sarcopenic group (n = 153). The associations among the Apo and sarcopenia were assessed using multivariate analyses. Results: Inpatients in the sarcopenia group showed lower ApoA1 levels than those in the non-sarcopenia group (1.25±0.21 vs 1.36±0.20 g/L, P < 0.05) and showed higher ApoB/ApoA1 and ApoB levels than those in the non-sarcopenia group (0.82±0.27 vs 0.69±0.19 g/L, P < 0.05;1.00±0.32 vs 0.93±0.24 g/L, P < 0.05, respectively). After adjusting for age and BMI, the logistic regression model indicated that ApoA1 was a protective factor for elderly inpatients with T2DM sarcopenia.(OR =0.079,95% CI: 0.021~0.306, P < 0.05);ApoB and AopB/AopA1 were risk factors for elderly inpatients with T2DM sarcopenia.(OR =3.578,95% CI:1.318~9.715, P < 0.05;OR =16.440,95% CI:4.437~60.427, P < 0.05, respectively). AopB/AopA1 provided an AUC value of 0.765 in elderly men.(95% CI: 0.665~0.866, P<0.05). Conclusion: ApoA1, AopB, and AopB/AopA1 are associated with sarcopenia in elderly inpatients with T2DM, and AopB/AopA1 may be a potential predictor of sarcopenia in elderly men with T2DM.

Height-Corrected Definition of Metabolic Syndrome Is a Simple and Effective Method for Identifying Insulin Resistance and Low-Grade Inflammation in Adolescents: Metabolic Syndrome in Adolescents.

The purpose of this study was to evaluate the feasibility of the height-corrected definition of metabolic syndrome(MetS) in adolescents. A retrospective study was conducted on US adolescents aged 12 to 17 years. Waist-to-height ratio and blood pressure-to-height ratio were substituted for waist circumference and blood pressure when defining MetS in adolescents. The proportions of insulin resistance of adolescents with 1 (30.1%), 2 (50.7%), and ≥3 components (77.8%) of MetS were 2.578 (P < .001), 6.882 (P < .001), and 23.992 (P < .001) times than the proportion of adolescents without the component of MetS (14.2%). The proportions of low-grade inflammation of adolescents with 1 (3.4%), 2 (5.3%), and ≥3 components (14.4%) of MetS were 2.050 (P = .106), 3.699 (P = .005), and 10.664 (P < .001) times than the proportion of adolescents without the component of MetS (1.7%). This study demonstrates that height-corrected definition of MetS is a simple and accurate method for identifying insulin resistance and low-grade inflammation in adolescents.

The relationship between obesity and bone mineral density in children and adolescents: analysis of the National Health and Nutrition Examination Survey.

Childhood and puberty are important period for the skeleton grows. Fat mass, especially visceral adipose tissue, was negatively correlated with areal bone mineral density in children and adolescents. The present study suggests that fat mass, especially visceral adipose tissue, has a slightly negative association with bone development in children and adolescents. PURPOSE: This study observed the relationship between fat mass and distribution, and areal bone mineral density (aBMD) in children and adolescents. METHODS: A retrospective study was conducted on US children and adolescents aged 8-19 years. Whole body (less head) aBMD was evaluated. Height (Ht) adjusted Z-scores for aBMD were calculated. RESULTS: After controlling for age, gender, race, and lean body mass index (LBMI) Z-score, there were significant negative associations between fat mass index (FMI) Z-score and aBMD Ht-Z-adjusted Z-score (ß = - 0.272, P < 0.001, R2 = 0.033). In the linear regression models with aBMD Ht-Z-adjusted Z-score as the dependent variable, the regression coefficients of android fat mass were - 0.241 (P < 0.05, R2 = 0.002), - 0.473 (P < 0.001, R2 = 0.036), and - 0.474 (P < 0.001, R2 = 0.038) for healthy weight, overweight, and obesity group, respectively. The regression coefficients of visceral adipose tissue (VAT) mass were - 0.218 (P > 0.05, R2 = 0.001), - 2.025 (P < 0.001, R2 = 0.044), and - 1.826 (P < 0.001, R2 = 0.039), and the regression coefficients of subcutaneous adipose tissue (SAT) mass were - 0.467 (P < 0.001, R2 = 0.004), - 0.339 (P < 0.01, R2 = 0.024), and - 0.347 (P < 0.001, R2 = 0.018) for healthy weight, overweight, and obesity group, respectively. CONCLUSIONS: The present study suggests that fat mass has a slightly negative association with bone development in children and adolescents. Trunk fat accumulation, especially visceral adipose tissue, was correlated with the lower level of aBMD. This association was obvious in overweight and obese children.

The dose-response relationship between sex hormones and hyperuricemia in different gender: NHANES 2013-2016.

Objectives: To access the dose-response relationship between sex hormones and hyperuricemia (HUA), and to find the cut-off value in different gender. Methods: 9,685 participants were derived from the database of National Health and Nutrition Examination Survey (NHANES). Restricted cubic spline (RCS) analysis were applied to explore the relationship between sex hormones and HUA after adjusting for confounding factors by propensity score match (PSM). Logistic regression was used to estimate the odds ratio (OR) and 95% CI. Results: The prevalence of HUA was 15.13% in female participants and 22.30% in male participants. Logistic regression analysis showed that estradiol (E2) was independently associated with HUA for a P value of 0.003 and 0.01in female and male participants, respectively. Testosterone (T) was only independently associated with HUA in male participants (P<0.001) but not in female participants (P = 0.59). RCS analysis showed a dose-response relationship between sex hormones and HUA. The risk of HUA increased as E2 lower than 29.6pg/mL in female participants and T lower than 389.1ng/dL in male participants. E2 higher than 23.6pg/ml was an independent risk factor for HUA in male participants. Conclusion: A dose-response relationship was found between sex hormones and HUA. The cut-off value of E2 in male and female participants was 29.6pg/mL and 23.6pg/mL, respectively, and the cut-off value of T in male participants was 389.1ng/dL. These results provide a reference for preventing HUA and hormone supplement therapy.

The relationship between metabolic syndrome and bone mineral density in adolescents: analysis of the National Health and Nutrition Examination Survey.

OBJECTIVES: The purpose of this study was to observe the relationship between metabolic syndrome (MetS) and height (Ht) adjusted Z-scores for areal bone mineral density (aBMD) in adolescents. METHODS: A retrospective study was conducted on the United States adolescents aged 12-17 years. Data were extracted from the National Health and Nutrition Examination Survey (NHANES) 2011-2012, 2013-2014 and 2015-2016 cycles. Ht adjusted Z-scores for aBMD were calculated. RESULTS: A total of 969 adolescents (493 boys and 476 girls), aged 14.5 ± 1.7 years were enrolled in this study. After control for age, gender, race, 25-hydroxyvitamin D [25(OH)D], and lean body mass index (LBMI) Z-score, adolescents with MetS had significantly lower levels of total body (less head) aBMD Ht-Z-adjusted Z-score than adolescents with one, two components of MetS and without component of MetS (p<0.05) and significantly lower levels of lumbar spine aBMD Ht-Z-adjusted Z-score than adolescents with one component of MetS and without component of MetS (p<0.05). There were significantly negative associations between total body (less head) aBMD Ht-Z-adjusted Z-score and waist circumference (WC) (ß=-0.027, p<0.001, R2=0.057) and homeostasis model assessment insulin resistance (HOMA-IR) (ß=-0.225, p<0.001, R2=0.016). There were significantly negative associations between lumbar spine aBMD Ht-Z-adjusted Z-score and WC (ß=-0.039, p<0.001, R2=0.058) and HOMA-IR (ß=-0.251, p<0.001, R2=0.008). CONCLUSIONS: The present study demonstrates that MetS may have a negative effect on bone mineral density in adolescents. Abdominal obesity and insulin resistance play a major role on the decline of aBMD in adolescents.

Age, Pulse, Urea, and Albumin Score: A Tool for Predicting the Short-Term and Long-Term Outcomes of Community-Acquired Pneumonia Patients With Diabetes.

Objective: The predictive performances of CURB-65 and pneumonia severity index (PSI) were poor in patients with diabetes. This study aimed to develop a tool for predicting the short-term and long-term outcomes of CAP in patients with diabetes. Methods: A retrospective study was conducted on 531 CAP patients with type 2 diabetes. The short-term outcome was in-hospital mortality. The long-term outcome was 24-month all-cause death. The APUA score was calculated according to the levels of Age (0-2 points), Pulse (0-2 points), Urea (0-2 points), and Albumin (0-4 points). The area under curves (AUCs) were used to evaluate the abilities of the APUA score for predicting short-term outcomes. Cox regression models were used for modeling relationships between the APUA score and 24-month mortality. Results: The AUC of the APUA score for predicting in-hospital mortality was 0.807 in patients with type 2 diabetes (P<0.001). The AUC of the APUA score was higher than the AUCs of CURB-65 and PSI class (P<0.05). The long-term mortality increased with the risk stratification of the APUA score (low-risk group (0-1 points) 11.5%, intermediate risk group (2-4 points) 16.9%, high risk group (≥5 points) 28.8%, P<0.05). Compared with patients in the low-risk group, patients in the high-risk group had significantly increased risk of long-term death, HR (95%CI) was 2.093 (1.041~4.208, P=0.038). Conclusion: The APUA score is a simple and accurate tool for predicting short-term and long-term outcomes of CAP patients with diabetes.

Influence of overweight and obesity on the mortality of hospitalized patients with community-acquired pneumonia.

BACKGROUND: Obesity is associated with a better prognosis in patients with community-acquired pneumonia (the so-called obesity survival paradox), but conflicting results have been found. AIM: To investigate the relationship between all-cause mortality and body mass index in patients with community-acquired pneumonia. METHODS: This retrospective study included patients with community-acquired pneumonia hospitalized in the First Hospital of Qinhuangdao from June 2013 to November 2018. The patients were grouped as underweight (< 18.5 kg/m2), normal weight (18.5-23.9 kg/m2), and overweight/obesity (≥ 24 kg/m2). The primary outcome was all-cause hospital mortality. RESULTS: Among 2327 patients, 297 (12.8%) were underweight, 1013 (43.5%) normal weight, and 1017 (43.7%) overweight/obesity. The all-cause hospital mortality was 4.6% (106/2327). Mortality was lowest in the overweight/obesity group and highest in the underweight group (2.8%, vs 5.0%, vs 9.1%, P < 0.001). All-cause mortality of overweight/obesity patients was lower than normal-weight patients [odds ratio (OR) = 0.535, 95% confidence interval (CI) = 0.334-0.855, P = 0.009], while the all-cause mortality of underweight patients was higher than that of normal-weight patients (OR = 1.886, 95%CI: 1.161-3.066, P = 0.010). Multivariable analysis showed that abnormal neutrophil counts (OR = 2.38, 95%CI: 1.55-3.65, P < 0.001), abnormal albumin levels (OR = 0.20, 95%CI: 0.06-0.72, P = 0.014), high-risk Confusion-Urea-Respiration-Blood pressure-65 score (OR = 2.89, 95%CI: 1.48-5.64, P = 0.002), and intensive care unit admission (OR = 3.11, 95%CI: 1.77-5.49, P < 0.001) were independently associated with mortality. CONCLUSION: All-cause mortality of normal-weight patients was higher than overweight/ obesity patients, lower than that of underweight patients. Neutrophil counts, albumin levels, Confusion-Urea-Respiration-Blood pressure-65 score, and intensive care unit admission were independently associated with mortality in patients with community-acquired pneumonia.

The Relationship Between Prediabetes and Bone Mass in Adolescents: Analysis of the National Health and Nutrition Examination Survey From 2005 to 2010.

Objective: The purpose of this study was to observe the relationship between impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and bone mineral density (BMD) in different sites in adolescents. Methods: A retrospective study was conducted on adolescents age 12-19 years of the United States. Data were extracted from the National Health and Nutrition Examination Survey (NHANES) 2005-2006, 2007-2008, and 2009-2010 cycles. IFG was defined as fasting plasma glucose (FPG) levels that were ≥5.6 and <7.0 mmol/L. IGT was defined as 2-h plasma glucose levels that were ≥7.8 and <11.1 mmol/L after the oral glucose tolerance test (OGTT). Results: After controlling for age, gender, race, and body mass index (BMI) Z-score, adolescents in different categories of IGT had significantly different levels of areal BMD (aBMD) and bone mineral apparent density (BMAD) (IGT main effect: P < 0.05 for all, two-way ANOVA). There was no main effect between different categories of IFG with regard to aBMD and BMAD (P > 0.05). There was no interaction between IFG and IGT with regard to aBMD and BMAD (P > 0.05). In multiple regression analysis, the 2-h plasma glucose maintained an independent association with femoral neck aBMD (ß = -0.011, 95% CI: -0.017~-0.006, P < 0.001, R2 = 0.012), total femur aBMD (ß = -0.015, 95% CI: -0.021~-0.009, P < 0.001, R2 = 0.018), total spine aBMD (ß = -0.015, 95% CI: -0.020~-0.010, P < 0.001, R2 = 0.018), and total spine BMAD (ß = -0.002, 95% CI: -0.003~0.000, P = 0.006, R2 = 0.003). Conclusion: The present study demonstrates that BMD was decreased in adolescents with IGT. Two-hour plasma glucose, not FPG, negatively correlated with BMD. The effect of 2-h plasma glucose was consistent across the sites of bone.

The Performance of CURB-65 and PSI for Predicting In-Hospital Mortality of Community-Acquired Pneumonia in Patients with Type 2 Diabetes Compared with the Non-Diabetic Population.

OBJECTIVE: To compare the performance of CURB-65 and Pneumonia Severity Index (PSI) for predicting in-hospital mortality of community-acquired pneumonia (CAP) between patients with and without type 2 diabetes (T2DM). METHODS: A retrospective study was conducted on 2365 CAP patients in The First Hospital of Qinhuangdao, China. The primary outcome was in-hospital mortality. The area under curves (AUCs) was used to evaluate the abilities of CRB-65, CURB-65, and PSI class for predicting in-hospital mortality in patients with CAP. RESULTS: Among CAP patients, 127 patients (5.4%) died, 80 patients were without diabetes, and 47 patients had T2DM. In-hospital mortality increased with the risk stratification defined as CURB-65 and PSI class in both non-diabetes and T2DM patients (P<0.05). The AUCs for predicting in-hospital mortality were 0.728～0.798 in patients without T2DM (CRB-65: 0.728, CURB-65: 0.757 and PSI class: 0.798) and 0.641～0.716 in patients with T2DM (CRB-65: 0.641, CURB-65: 0.677 and PSI class: 0.716)(P<0.001). The AUC of the PSI class was lower in patients with T2DM than in patients without T2DM (P<0.05). CONCLUSION: CURB-65 and PSI class are correlated with in-hospital mortality of CAP in patients with and without T2DM. Compared with non-diabetes patients, the predictive performance of CURB-65 and PSI class decreased in patients with T2DM. A prediction model for evaluating the CAP severity in the T2DM population should be developed by future studies.

Age, Pulse, Urea and Albumin (APUA) Model: A Tool for Predicting in-Hospital Mortality of Community-Acquired Pneumonia Adapted for Patients with Type 2 Diabetes.

OBJECTIVE: The aim of this study was to develop a tool for predicting in-hospital mortality of community-acquired pneumonia (CAP) in patients with type 2 diabetes (T2DM). METHODS: A retrospective study was conducted on 531 CAP patients with T2DM at The First Hospital of Qinhuangdao. The primary outcome was in-hospital mortality. Variables to develop the nomogram were selected using multiple logistic regression analysis. Discrimination was evaluated using receiver operating characteristic (ROC) curve. Calibration was evaluated using the Hosmer-Lemeshow test and calibration plot. RESULTS: Multiple logistic regression analysis showed that age, pulse, urea and albumin (APUA) were independent risk predictors. Based on these results, we developed a nomogram (APUA model) for predicting in-hospital mortality of CAP in T2DM patients. In the training set, the area under the curve (AUC) of the APUA model was 0.814 (95% CI: 0.770-0.853), which was higher than the AUCs of albumin alone, CURB-65 and Pneumonia Severity Index (PSI) class (p<0.05). The Hosmer-Lemeshow test (χ 2=5.298, p=0.808) and calibration plot (p=0.802) showed excellent agreement between the predicted possibility and the actual observation in the APUA model. The results of the validation set were similar to those of the training set. CONCLUSION: The APUA model is a simple and accurate tool for predicting in-hospital mortality of CAP, adapted for patients with T2DM. The predictive performance of the APUA model was better than CURB-65 and PSI class.

Glycosylated Hemoglobin A1c Improves the Performance of the Nomogram for Predicting the 5-Year Incidence of Type 2 Diabetes.

AIM: To develop and validate a model, which combines traditional risk factors and glycosylated hemoglobin A1c (HbA1c) for predicting the risk of type 2 diabetes (T2DM). MATERIALS AND METHODS: This is a historical cohort study from a collected database, which included 8419 males and 7034 females without diabetes at baseline with a median follow-up of 5.8-years and 5.1-years, respectively. Multivariate cox regression analysis was used to select significant prognostic factors of T2DM. Two nomograms were constructed to predict the 5-year incidence of T2DM based on traditional risk factors (Model 1) and traditional risk factors plus HbA1c (Model 2). C-index, calibration curve, and time-dependent receiver-operating characteristic (ROC) curve were conducted in the training sets and validation sets. RESULTS: In males, the C-index was 0.824 (95% CI: 0.795-0.853) in Model 1 and 0.867 (95% CI: 0.840-0.894) in Model 2; in females, the C-index was 0.830 (95% CI: 0.770-0.890) in Model 1 and 0.856 (95% CI: 0.795-0.917) in Model 2. The areas under curve (AUC) in Model 2 for prediction of T2DM development were higher than in Model 1 at each time point. The calibration curves showed excellent agreement between the predicted possibility and the actual observation in both models. The results of validation sets were similar to the results of training sets. CONCLUSION: The proposed nomogram can be used to accurately predict the risk of T2DM. Compared with the traditional nomogram, HbA1c can improve the performance of nomograms for predicting the 5-year incidence of T2DM.

The Effects of Type 2 Diabetes and Postoperative Pneumonia on the Mortality in Inpatients with Surgery.

OBJECTIVE: The aim of the study was to explore the relationship between type 2 diabetes (T2DM) and postoperative pneumonia, and the effects of T2DM and postoperative pneumonia on the mortality in inpatients with surgery. METHODS: A retrospective study was conducted on 43,174 inpatients with surgery in The First Hospital of Qinhuangdao. These patients were divided into four groups according to T2DM and postoperative pneumonia, Group A subjects without T2DM and postoperative pneumonia, Group B subjects with T2DM only, Group C subjects with postoperative pneumonia only and Group D subjects with T2DM and postoperative pneumonia. In-hospital mortality was collected. RESULTS: The incidences of postoperative pneumonia were higher in patients with T2DM than patients without T2DM (T2DM 3.2% vs Non-diabetes 1.7%, χ 2=36.219, P<0.001). The mortalities were 0.3% in Group A, 0.3% in Group B, 4.6% in Group C and 8.6% in Group D. In multiple logistic regression analysis, adjusted for sex, age, emergency admissions, coronary heart disease, heart failure, chronic kidney disease, hypoproteinemia, stroke and transient ischemic attack, the mortalities of Group C and Group D were 4.515 (95% CI: 2.779～7.336, P<0.001) times and 8.468 (95% CI: 3.567～20.099, P<0.001) times than the mortality of Group A. CONCLUSION: T2DM is susceptible to postoperative pneumonia. The mortality increased in patients with postoperative pneumonia. When patients with T2DM and postoperative pneumonia at the same time, the mortality increased further. In T2DM patients with postoperative pneumonia, perioperative management should be improved for patient safety.

The mortality in infectious inpatients with type 2 diabetes compared with non-diabetic population: Infection in type 2 diabetes.

The aim of the study was to determine the mortality in infectious inpatients with type 2 diabetes mellitus (T2DM) compared with non-diabetic population.A retrospective study was conducted on 13,916 infectious inpatients in The First Hospital of Qinhuangdao. Diabetic types were classified using International classification of Diseases-10. Mortality records were collected.The mortality was higher in patients with T2DM than patients without T2DM (T2DM 4.3% vs non-diabetes 1.7%, χ = 59.560, P < .001). In multiple logistic regression analysis, T2DM was an independent risk factor of death in infectious inpatients (OR = 1.539, 95% CI: 1.181∼2.006, P = .001). The mortalities between those with T2DM and those without T2DM were stratified by age. The mortalities of patients with T2DM were 0.0% in ∼39 years, 0.0% in 40 to 49 years, 2.7% in 50 to 59 years, 3.1% in 60 to 69 years, 4.1% in 70 to 79 years and 8.7% in 80∼ years groups. The mortalities of patients without T2DM were 0.2% in ∼39 years, 0.1% in 40 to 49 years, 0.6% in 50 to 59 years, 1.0% in 60 to 69 years, 3.1% in 70 to 79 years and 5.9% in 80∼ years groups. T2DM was an independent risk factor of death only in 60 to 69 years groups (OR = 2.323, 95% CI: 1.234∼4.372, P = .009).The increase of mortality appears earlier in patients with T2DM. Infectious inpatients with T2DM are at increased risk of death and brings heavy economic burden to patients, society and government.

Hypertriglyceridemic waist phenotype and abnormal glucose metabolism: a system review and meta-analysis.

OBJECTIVE: This study was to perform a meta-analysis to assess the relationship between hypertriglyceridemic-waist (HTW) phenotype and abnormal glucose metabolism. METHODS: The data sources were PubMed and EMBASE up to June 2018. Studies providing the relationship between HTW phenotype and abnormal glucose metabolism were included. RESULTS: In total, 48 eligible studies that evaluated 2,42,879 subjects were included in the meta-analysis. In the general population, the pooled odds ratios (ORs) for elevated blood glucose and diabetes related to HTW phenotype was 2.32 (95% confidence interval (CI): 1.98-2.71) and 2.69 (95% CI: 2.40-3.01), respectively. In cohort studies, the pooled OR for diabetes related to HTW phenotype was 2.89 (95% CI: 1.97-4.25) in subjects without diabetes. The levels of homeostasis model assessment of insulin resistance (HOMA-IR) in the HTW population were increased with values of mean differences (MD) 1.12 (95% CI: 0.81-1.43. P < 0.00001, I2 = 99%) in the general population and 0.89 (95% CI: 0.75-1.04, P < 0.00001, I2 = 67%) in subjects without diabetes. CONCLUSION: HTW phenotype was closely associated with increased risk of abnormal glucose metabolism. There was also a significant correlation between HTW phenotype and insulin resistance.

The relationship between hypertriglyceridemic-waist phenotype and vitamin D status in type 2 diabetes.

Background: The aim of the study was to explore the relationship between hypertriglyceridemic-waist (HTW) phenotype and vitamin D status in type 2 diabetes. Methods: A cross-sectional study was conducted in subjects with type 2 diabetes. This study enrolled 338 type 2 diabetic (190 males and 148 females). The HTW phenotype was defined as serum triglyceride concentrations ≥1.7 mmol/L and waist circumference ≥90 cm (male) and 85 cm (female). Multiple logistic regression models were used for modeling relationships between HTW phenotype and vitamin D status. Results: The prevalence of HTW phenotype was 36.4%. The prevalence of HTW phenotype was 10.5%, 27.2%, and 41.6% in type 2 diabetes with vitamin D sufficiency, vitamin D insufficiency, and vitamin D deficiency, respectively. In multiple logistic regression analysis, subjects with vitamin D deficiency were more likely to have HTW phenotype (OR=6.222, 95%CI: 1.307-29.620, P=0.022) compared with subjects with vitamin D sufficiency. Conclusions: There was a significant correlation between HTW phenotype and vitamin D status in type 2 diabetes.

Serum ferritin, an early marker of cardiovascular risk: a study in Chinese men of first-degree relatives with family history of type 2 diabetes.

BACKGROUND: Ferritin is one of the key proteins that regulate iron homeostasis and is widely available clinical biomarker of iron status. This study aimed to discuss the influence of serum ferritin (SF) on cardiovascular risk factors in the first-degree relatives with family history of type 2 diabetes (FHD). METHODS: This cross-sectional study included 232 men. Anthropometric measurements and blood samples were analyzed. The people were divided into four groups according to median SF (102.8 ng/ml) and people with or without FHD. Group A (FHD-and low SF), group B (FHD-and high SF), group C (FHD+ and low SF), and group D (FHD+ and high SF). RESULTS: The subjects in different categories of SF concentrations showed significant differences in BMI (SF main effect: P = 0.010), WC (P = 0.030), SBP (P < 0.001), FPG (P < 0.001), PPG-2 h (P < 0.001), FINS (P < 0.001), and HOMA-IR (P = 0.015; all: 2-way ANOVA). There was a significant difference in SBP (FHD main effect: P = 0.003), DBP (P = 0.006), and FINS (P = 0.013, all: 2-way ANOVA) between the groups with or without FHD. The interaction term between SF and FHD was significant for SBP (P = 0.011), DBP (P = 0.012), and PPG-2 h (P = 0.022). Logistic analysis showed that accumulation of CVD risk factors, which were ≥ 2 items and ≥ 3 items in group D were 7.546 and 3.343 times higher compared with group A (P < 0.05). CONCLUSIONS: The increased SF levels increased the risk of cardiovascular risk factors and the occurrence of insulin resistance in first-degree relatives with FHD.

The Relationship between Hypertriglyceridemic Waist Phenotype and Early Diabetic Nephropathy in Type 2 Diabetes.

BACKGROUND/AIMS: The aim of this study was to explore the relationship between hypertriglyceridemic waist (HW) phenotype and early diabetic nephropathy in type 2 diabetes. METHODS: A cross-sectional study was conducted on 538 type 2 diabetes patients in Qinhuangdao. The HW phenotype was defined as serum triglyceride concentrations ≥1.7 mmol/L and waist circumference ≥90 cm (males) and ≥85 cm (females). RESULTS: The prevalence of the HW phenotype was 34.9%. The prevalence of early diabetic nephropathy was 10.6% in type 2 diabetes patients with normal waist circumference and triglycerides and 24.5% in type 2 diabetes patients with HW phenotype. After adjustment for sex, age, body mass index, hypertension, history of diabetes, and glycosylated hemoglobin A1c, the prevalence of early diabetic nephropathy among type 2 diabetes patients with the HW phenotype was 2.81 (95% confidence interval 1.36-5.80, p = 0.005) times higher than that among type 2 diabetes patients with normal waist circumference and triglycerides. CONCLUSION: There was a significant correlation between HW phenotype and early diabetic nephropathy in type 2 diabetes.

Change in nonhigh-density lipoprotein cholesterol levels in adults with prediabetes.

This study aimed to observe the change in nonhigh-density lipoprotein cholesterol (non-HDL-C) levels and analyzed its related factors in adults with prediabetes (impaired fasting glucose and/or impaired glucose tolerance).This case-controlled study included 56 adults with normal glucose tolerance (NGT) and 74 adults with prediabetes. The cases and controls were age and gender-matched. Anthropometric measurements including height, weight, waist circumference, and blood pressure were performed. All patients underwent an oral glucose tolerance test (OGTT) after 8 hours of fasting, and the levels of glucose, insulin, lipids, and uric acid were measured.The levels of non-HDL-C (3.63 ±â€Š0.92 vs 3.27 ±â€Š1.00 mmol/L) were significantly higher in prediabetic subjects than in NGT subjects (P < .05). Non-HDL-C positively correlated with HOMA-IR (r = 0.253, P = .004), triglyceride (r = 0.204, P = .020), and uric acid (r = 0.487, P = .000). After multivariate analysis, uric acid continued to be significantly associated with non-HDL-C (ß = 0.006, P = .000).Non-HDL-C is elevated in adults with prediabetes. A relationship between non-HDL-C and uric acid was observed.

Three novel obese indicators perform better in monitoring management of metabolic syndrome in type 2 diabetes.

The present study evaluated the performance of three novel obese indicators, visceral adiposity index (VAI), lipid accumulation product (LAP) and waist circumference-triglyceride index (WTI), for identifying metabolic syndrome(MetS) in type 2 diabetes. A cross-sectional study was conducted on 711 type 2 diabetes in Qinhuangdao. The MetS was defined as the definition of Chinese Diabetes Society. Receiver operating characteristic curve analyses were performed to assess the accuracy of three obese indicators as diagnostic tests for MetS. The prevalence of MetS was 71.3%. In men, among all three obese indicators, the LAP had the highest area under curve (AUC) value (AUC = 0.894), followed by VAI (AUC = 0.860) and WTI (AUC = 0.855). In women, among all three obese indicators, the LAP had the highest AUC value (AUC = 0.906), followed by WTI (AUC = 0.887) and VAI (AUC = 0.881). However. there was no significant difference between the three obese indicators(P > 0.05). Three obese indicators were effective indicators for the screening of MetS, LAP and WTI are more simple.

The Levels of Serum Irisin as a Predictor of Insulin Resistance in Han Chinese Adults with Metabolically Healthy Obesity.

BACKGROUND: The aim of this study was to evaluate serum irisin levels and analyze its related factors in Han adults with metabolically healthy obesity. METHODS: This cross-sectional study included 75 metabolically healthy, non-obese adults and 51 metabolically healthy, obese adults. Anthropometric measurements, including height, weight, waist circumference (WC), and blood pressure, were performed. All patients underwent an oral glucose tolerance test (OGTT) after 8 hours of fasting, and the levels of glucose, insulin, lipids, and serum irisin were measured. RESULTS: The levels of serum irisin (5.40 ± 1.69 vs. 6.46 ± 1.37 µg/mL) were significantly lower in the metabolically healthy obese group (p < 0.05). Irisin correlated positively with high density lipoprotein cholesterol (HDL-C) (r = 0.303) and correlated negatively with body mass index (BMI) (r = -0.389), WC (r = -0.324), fasting plasma glucose (FPG) (r = -0.441), HOMA-IR (r = -0.429), triglycerides (TG) (r = -0.185), total cholesterol (TC) (r = -0.209), low density lipoprotein cholesterol (LDL-C) (r = -0.157) (p < 0.05). Multiple regression analysis revealed that FPG (ß = -1.720, p = 0.001) and HOMA-IR (ß = -0.399, p = 0.006) were still significantly associated with irisin. Serum irisin (ß = -0.246, p = 0.005) and BMI (ß = 0.078, p = 0.043) were significant independent predictors for HOMAIR. CONCLUSIONS: Serum irisin levels were reduced in metabolically healthy, obese Han adults. Irisin reduction appears to be associated with elevated FPG and insulin resistance but not obesity. In additional, falling irisin may increase the occurrence of insulin resistance in metabolically healthy Han adults and should be examined in future studies.