Association of Obesity Indices with Diabetic Kidney Disease and Diabetic Retinopathy in Type 2 Diabetes: A Real-World Study

Association between phase angle, body mass index and insulin resistance in patients with type 2 diabetes mellitus: a cross-sectional study

Background: The purpose of this analysis was to investigate the associations between phase angle (PhA), body mass index (BMI) and insulin resistance (IR) in patients with type 2 diabetes mellitus (T2DM). Methods: The retrospective cross-sectional study included 200 T2DM patients treated during 2018 to 2019 in Zhongda Hospital Southeast University. PhA and other body composition indicators were measured by bioelectrical impedance analysis (BIA). Subjects were classified into four groups based on body composition: low phase angle and low body mass index (LPLB), low phase angle and high body mass index (LPHB), high phase angle and low body mass index (HPLB) and high phase angle and high body mass index (HPHB). Results: Overall, in the unadjusted model and minor, all adjusted models (unadjusted model, models 1-4), homeostasis model assessment of insulin resistance (HOMA-IR) was higher in the LPHB group than in the LPLB group (P = 0.034). In the unadjusted model, Model 1 (adjustment for age), Model 2 (adjust for age+duration), Model 3 (adjust for age+duration+sex+UA+TG+TC) and Model 4 (adjust for age+duration+sex+UA+TG+TC+HDL+HbA1c), the adjusted ORs for participants were 4.4 (95% CI [1.72-11.24]), 4.41 (95% CI [1.73-11.27]), 4.75 (95% CI [1.83-12.32]), 2.93 (95% CI [1.04-8.23]) and 3.1 (95% CI [1.09-8.86]) respectively, compared to LPHB group. Conclusions: T2DM patients with the body composition of low phase angle and high body mass index exhibited the most severe degree and the highest risk of insulin resistance.

Elevated Fasting C-Peptide Levels Correlate with Increased 10-Year Risk of Atherosclerotic Cardiovascular Disease in Newly Diagnosed Type 2 Diabetes Patients

Purpose

This study aims to analyze the impact of serum C-peptide levels in patients with newly diagnosed type 2 diabetes (T2DM) on the 10-year risk of atherosclerotic cardiovascular disease (ASCVD).

Patients and Methods

A total of 1923 patients with newly diagnosed T2DM were selected and categorized into four groups based on the interquartile range of fasting C-peptide (FCP) levels: Q1 group (FCP≤0.568 ng/mL), Q2 group (0.568 < FCP≤0.751 ng/mL), Q3 group (0.751 < FCP≤0.980 ng/mL), and Q4 group (FCP > 0.980 ng/mL). Clinical data were collected, and the China-PAR model was employed to evaluate the risk score of ASCVD within 10 years. Additionally, the correlation between FCP levels and the risk of ASCVD was analyzed.

Results

As the quartiles of FCP increased, the 10-year ASCVD risk exhibited a gradual increase. The risk score in the FCP > 0.980 ng/mL group was significantly higher than that in the other groups, with noted differences related to gender and weight. Multiple linear regression analysis indicated that, even after adjusting for confounding factors such as gender, age, body mass index (BMI), and glycosylated hemoglobin, FCP levels remained a positive predictor of the 10-year ASCVD risk.

Conclusion

High FCP levels are identified as a risk factor for ASCVD within 10 years in patients with newly diagnosed T2DM.

The relationship between weight-adjusted-waist index, body mass index and diabetic retinopathy among American adults: a population-based analysis

Diabetic retinopathy (DR) is a common complication of diabetes, with its prevalence increasing globally. While previous research has linked obesity indices such as body mass index (BMI) to DR, the association with weight-adjusted-waist index (WWI) remains unclear. Additionally, the relationship between WWI and DR has not been fully elucidated. This cross-sectional study analyzed data from the National Health and Nutrition Examination Survey (2005-2008) to investigate these associations in Americans aged 40 and above. The study included 5436 participants (2705 men and 2731 women). Weighted logistic regression analysis revealed a significant increase in DR prevalence with higher WWI and BMI values. Smooth curve analysis demonstrated a linear correlation between WWI and DR. The findings suggest that both WWI and BMI are independently associated with DR risk among older US adults, highlighting the importance of considering central obesity measures in assessing diabetic complications.

Construction of a Nomogram-Based Prediction Model for the Risk of Diabetic Kidney Disease in T2DM

Introduction

To investigate the predictors of diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM) patients and establish a nomogram model for predicting the risk of DKD.

Methods

The clinical data of T2DM patients, admitted to the Endocrinology Department of Chengde Central Hospital from October 2019 to September 2020 and divided into a case group or a control group based on whether they had DKD, were collected. The predictive factors of DKD were screened by univariate and multivariate analysis, and a nomogram prediction model was constructed for the risk of DKD in T2DM. Bootstrapping was used for model validation, receiver operating characteristic (ROC) curve and GiViTI calibration curve were used for evaluating the discrimination and calibration of prediction model, and decision analysis curve (DCA) was used for evaluating the practicality of model.

Results

Predictors for DKD are diabetic retinopathy (DR), hypertension, history of gout, smoking history, using insulin, elevation of body mass index (BMI), triglyceride (TG), cystatin C (Cys-C), and reduction of 25 (OH) D. The nomogram prediction model based on the above nine predictors had good representativeness (Bootstrap method: precision: 0.866, Kappa: 0.334), differentiation [the area under curve (AUC) value: 0.868], and accuracy (GiViTI-corrected curved bands, P = 0.836); the DAC curve analysis showed that the prediction model, whose threshold probability was in the range of 0.10 to 0.70, had clinical practical value.

Conclusion

The risk of DKD in T2DM could be predicted accurately by DR, hypertension, history of gout, smoking history, using insulin, elevation of BMI, TG, Cys-C, and reduction of 25 (OH) D.

Waist to height ratio as a simple tool for predicting mortality: a systematic review and meta-analysis

BACKGROUND

The association of central obesity with higher rates of mortality is not well studied. This study evaluates the association between waist-to-height ratio (WHtR), as a measure of central obesity, with mortality.

METHODS

Documents were retrieved from PubMed, Web of Science, Scopus, and Google Scholar databases until May 2022. Data were extracted from cohort studies reporting effect size (hazard ratio (HR)) regarding the association between WHtR as a continuous (per 1 SD increment) or categorical (highest/lowest) measure and all-cause and cause-specific mortality. Screening of included studies was performed independently by two authors. Moreover, the quality assessment of included studies was performed based on the Newcastle-Ottawa assessment scale. Finally, random effect meta-analysis was performed to pool the data, and the outcomes' certainty level was assess based on the GRADE criteria.

RESULTS

Of the 815 initial studies, 20 were included in the meta-analysis. Random effect meta-analysis showed that in the general population, the all-cause mortality HRs for categorical and continuous measurements of WHtR increased significantly by 23% (HR:1.23; 95% CI: 1.04-1.41) and 16% (HR:1.16; 95% CI: 1.07-1.25), respectively. Moreover, the hazard of cardiovascular (CVD) mortality increased significantly for categorical and continuous measurements of WHtR by 39% (HR:1.39; 95% CI: 1.18-1.59) and 19% (HR:1.19; 95% CI: 1.07-1.31). The quality assessment score of all included studies was high.

CONCLUSIONS

Higher levels of WHtR, indicating central obesity, were associated with an increased hazard of CVD and all-cause mortality. This measure can be used in the clinical setting as a simple tool for predicting mortality.