Comparison of different obesity indices associated with type 2 diabetes mellitus among different sex and age groups in Nantong, China: a cross-section study

Optimal obesity- and lipid-related indices for predicting type 2 diabetes in middle-aged and elderly Chinese

To investigate the screening and predicting functions of obesity- and lipid-related indices for type 2 diabetes (T2D) in middle-aged and elderly Chinese, as well as the ideal predicted cut-off value. This study's data comes from the 2011 China Health and Retirement Longitudinal Study (CHARLS). A cross-sectional study design was used to investigate the relationship of T2D and 13 obesity- and lipid-related indices, including body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), lipid accumulation product (LAP), conicity index (CI), Chinese visceral adiposity index (CVAI), triglyceride- glucose index (TyG index) and its correlation index (TyG-BMI, TyG-WC, TyG-WHtR). The unadjusted and adjusted correlations between 13 indices and T2D were assessed using binary logistic regression analysis. The receiver operating characteristic curve (ROC) was used to determine the usefulness of anthropometric indices for screening for T2D and determining their cut‑off value, sensitivity, specificity, and area under the curve (AUC). The study comprised 9488 people aged 45 years or above in total, of whom 4354 (45.89%) were males and 5134 (54.11%) were females. Among them were 716 male cases of T2D (16.44%) and 870 female cases of T2D (16.95%). A total of 13 obesity- and lipid-related indices were independently associated with T2D risk after adjusted for confounding factors (P < 0.05). According to ROC analysis, the TyG index was the best predictor of T2D among males (AUC = 0.780, 95% CI 0.761, 0.799) and females (AUC = 0.782, 95% CI 0.764, 0.799). The AUC values of the 13 indicators were higher than 0.5, indicating that they have predictive values for T2D in middle-aged and elderly Chinese. The 13 obesity- and lipid-related indices can predict the risk of T2D in middle‑aged and elderly Chinese. Among 13 indicators, the TyG index is the best predictor of T2D in both males and females. TyG-WC, TyG-BMI, TyG-WHtR, LAP, and CVAI all outperformed BMI, WC, and WHtR in predicting T2D.

Obesity and lipid indices as predictors of depressive symptoms in middle-aged and elderly Chinese: insights from a nationwide cohort study

BACKGROUND

Depressive symptoms are one of the most common psychiatric disorders, with a high lifetime prevalence rate among middle-aged and elderly Chinese. Obesity may be one of the risk factors for depressive symptoms, but there is currently no consensus on this view. Therefore, we investigate the relationship and predictive ability of 13 obesity- and lipid-related indices with depressive symptoms among middle-aged and elderly Chinese.

METHODS

The data were obtained from The China Health and Retirement Longitudinal Study (CHARLS). Our analysis includes individuals who did not have depressive symptoms at the baseline of the CHARLS Wave 2011 study and were successfully follow-up in 2013 and 2015. Finally, 3790 participants were included in the short-term (from 2011 to 2013), and 3660 participants were included in the long-term (from 2011 to 2015). The average age of participants in short-term and long-term was 58.47 years and 57.88 years. The anthropometric indicators used in this analysis included non-invasive [e.g. waist circumference (WC), body mass index (BMI), and a body mass index (ABSI)], and invasive anthropometric indicators [e.g. lipid accumulation product (LAP), triglyceride glucose index (TyG index), and its-related indices (e.g. TyG-BMI, and TyG-WC)]. Receiver operating characteristic (ROC) analysis was used to examine the predictive ability of various indicators for depressive symptoms. The association of depressive symptoms with various indicators was calculated using binary logistic regression.

RESULTS

The overall incidence of depressive symptoms was 20.79% in the short-term and 27.43% in the long-term. In males, WC [AUC = 0.452], LAP [AUC = 0.450], and TyG-WC [AUC = 0.451] were weak predictors of depressive symptoms during the short-term (P < 0.05). In females, BMI [AUC = 0.468], LAP [AUC = 0.468], and TyG index [AUC = 0.466] were weak predictors of depressive symptoms during the long-term (P < 0.05). However, ABSI cannot predict depressive symptoms in males and females during both periods (P > 0.05).

CONCLUSION

The research indicates that in the middle-aged and elderly Chinese, most obesity- and lipid-related indices have statistical significance in predicting depressive symptoms, but the accuracy of these indicators in prediction is relatively low and may not be practical predictors.

The role of adiponectin in the association between abdominal obesity and type 2 diabetes: a mediation analysis among 232,438 Chinese participants

Background

Adiposity and adipokines are closely associated with obesity-related metabolic abnormalities, but little is known regarding whether abdominal obesity is linked to type 2 diabetes mellitus (T2DM) through circulating adiponectin levels. Thus, this large-population-based study was designed to investigate the mediating effect of adiponectin in the relationship between abdominal obesity and T2DM.

Methods

A total of 232,438 adults who lived in Dongguan, Guangdong Province, China, were enrolled in the present study. The circulating adiponectin concentrations were measured using latex-enhanced immunoturbidimetric assay. The association between circulating adiponectin and other clinical parameters was detected by Spearman's correlation analysis. Restricted cubic spline (RCS) regression was also used to address the non-linearity of the relationship between waist circumference and diabetes. Mediation analyses of circulating adiponectin were conducted using linear and logistic regression.

Results

Subjects with abdominal obesity had lower levels of circulating adiponectin (P < 0.001). The circulating adiponectin value was inversely related to BMI (r = -0.370, P < 0.001), waist circumference (r = -0.361, P < 0.001), and fasting plasma glucose (r = -0.221, P < 0.001). The RCS plot showed a non-linear relation linking waist circumference with T2DM (P for non-linearity < 0.001). Patients with abdominal obesity presented 2.062 times higher odds of T2DM in comparison with those with non-abdominal obesity (odds ratio, 2.062; 95% confidence interval, 1.969-2.161) after adjusting for confounders. In the mediation analyses, the circulating adiponectin mediated the association between abdominal obesity and T2DM, with a mediation effect of 41.02% after adjustments. The above results were consistent in both men and women.

Conclusion

The relationship between abdominal obesity and T2DM is mediated through circulating adiponectin level in adults, suggesting that circulating adiponectin might be a potential predictor for controlling the adverse progression from adiposity to T2DM.

Obesity- and lipid-related indices as a predictor of type 2 diabetes in a national cohort study

Objective

Type 2 diabetes mellitus (T2DM) remains a major and widespread public health concern throughout the world. The prevalence of T2DM in the elderly has risen to the top of the list of public health concerns. In this study, obesity- and lipid-related indices were used to predict T2DM in middle-aged and elderly Chinese adults.

Methods

The data came from the China Health and Retirement Longitudinal Study (CHARLS), including 7902 middle-aged and elderly participants aged 45 years or above. The study assessed the association of obesity- and lipid-related indices and T2DM by measuring 13 indicators, including body mass index (BMI), waist circumference(WC), waist-height ratio (WHtR), conicity index(CI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), a body shape index (ABSI), body roundness index (BRI), triglyceride glucose index (TyG-index) and its correlation index (TyG-BMI, TyG-WC, TyG-WHtR). The association of 13 obesity- and lipid-related indices with T2DM was investigated by binary logistic regression. Additionally, the predictive anthropometric index was evaluated, and the ideal cut-off value was established using the receiver operating characteristic (ROC) curve analysis and area under the curve (AUC).

Results

The study included 7902 participants, of whom 3638(46.04) and 4264(53.96) were male and female. The prevalence of T2DM in mid-aged and old adults in China was 9.02% in males and 9.15% in females. All the above 13 indicators show a modest predictive power (AUC>0.5), which was significant for predicting T2DM in adults (middle-aged and elderly people) in China (P<0.05). The results revealed that TyG-WHtR [AUC =0.600, 95%CI: 0.566-0.634] in males and in females [AUC =0.664, 95%CI: 0.636-0.691] was the best predictor of T2DM (P<0.05).

Conclusion

Most obesity- and lipid-related indices have important value in predicting T2DM. Our results can provide measures for the early identification of T2DM in mid-aged and elderly Chinese to reduce the prevalence of T2DM and improve health.

Testosterone with Silymarin Improves Diabetes-obesity Comorbidity Complications by Modulating Inflammatory Responses and CYP7A1/ACC Gene Expressions in Rats

BACKGROUND

The co-morbidity of DMOB has become increasingly problematic among the world's population because of a high-calorie diet and sedentary lifestyle. DMOB is associated with lower testosterone (TN) levels, the male sex hormone. The phytochemical compound silymarin (SN) exerts antidiabetic activity by modifying β-cells and anti-obesity activity by inhibiting adipogenesis by methylxanthine.

AIM

The goal of this study was to find out how well testosterone (TN) with silymarin (SN) protects against oxidative stress and inflammation in the liver of the experimental rats with type 2 diabetes (T2D) and obesity (DMOB).

OBJECTIVES

The present study evaluates the efficacy of TN and SN combination (TNSN) on the levels of the potential parameters, such as body mass, serum marker enzymes, fasting glucose levels, HbA1c levels, lipid profile, enzymatic and non-enzymatic antioxidants, proinflammatory cytokines, gene expression pathways, and histopathology in a DMOB comorbidity rat model.

METHODS

Male Sprague-Dawley (SD) rats were fed a high-fat diet (HFD) for 20 weeks with an administration of a single dose of streptozotocin (STZ) i.p. injection (30 mg/kg) on the 9th week of the study. The procedure was to develop the DMOB co-morbidity model in the experimental animals. Co-treatment of TN and SN administration were followed throughout the experiment. Rats were sacrificed after overnight fasting to collect serum and liver tissue samples. Samples were analyzed using a clinical chemistry automated analyzer, spectrophotometry, and quantitative real-time PCR (qPCR) methods and protocols.

RESULTS

Analyses of body mass changes, serum marker enzymes, fasting glucose levels, HbA1c levels, lipid profiles, enzymatic and non-enzymatic antioxidants, TNF-α, IL-6, adiponectin, CYP7A1, ACC expression pathways, and histopathology showed significant abnormal levels (P ≤ 0.05) in the pathological group. These were efficiently treated to normal by the administration of TNSN.

CONCLUSION

These results concluded that TNSN exerted protective efficacy against the liver abnormalities in the co-morbidity of the DMOB rat model.

Association of the Clínica Universidad de Navarra-Body Adiposity Estimator With Type 2 Diabetes: A Retrospective Cohort Study

Objectives: Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) is considered to be a more accurate indicator of body fat estimation. We aimed to investigate the association of CUN-BAE with the risk of type 2 diabetes mellitus (T2DM) and to compare the strength of the association between CUN-BAE, body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR) and T2DM. Methods: The data were obtained from the annual health checkup database of residents in Xinzheng, China. From January 2011 to December 2021, 80,555 subjects aged ≥45 years met the inclusion criteria. Cox proportional hazard regression models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for CUN-BAE, BMI, WC, and WHtR in T2DM. Results: During a mean follow-up of 6.26 years, T2DM occurred in 12,967 subjects. The multivariable-adjusted HRs (95% CIs) of T2DM (highest vs. reference group) were 1.994 (1.811-2.196) for CUN-BAE, 1.751 (1.665-1.842) for WC, 1.715 (1.631-1.804) for WHtR, and 1.510 (1.436-1.588) for BMI, respectively. In addition, the risk of T2DM increased with baseline CUN-BAE (HR: 1.374; 95% CI: 1.328, 1.421), WC (HR: 1.236; 95% CI: 1.215, 1.256), WHtR (HR: 1.228; 95% CI: 1.208, 1.248), and BMI (HR: 1.175; 95% CI: 1.156, 1.195). Conclusion: Compared to BMI, WC or WHtR, CUN-BAE may more adequately reflect the adverse effects of adiposity on the risk of T2DM.

The Interaction Between Age and Risk Factors for Diabetes and Prediabetes: A Community-Based Cross-Sectional Study

OBJECTIVE

This study aimed to investigate the interaction between age groups and risk factors for diabetes and prediabetes in Shanghai communities and to identify the effect of age on other risk factors for diabetes and prediabetes.

METHODS

This study recruited 3540 participants with undiagnosed diabetes or prediabetes in 14 communities in Shanghai from February to August 2019. All participants underwent a comprehensive examination, including filling out a detailed questionnaire, physical examination, 75 g oral glucose tolerance test, and blood sample collection. In addition, logistic regression was used to analyze the interaction between age and risk factors for prediabetes and diabetes.

RESULTS

The statistical analysis included 2776 people. In this study, the prevalence of diabetes and prediabetes were 15.1% and 52.3%, respectively. The prevalence of diabetes and prediabetes is higher in the elderly than in the middle-aged group. Among the risk factors for diabetes, overweight was associated with higher age (P-interaction 0.028). In addition, among the risk factors for prediabetes, a high level of education was associated with higher age (P-interaction 0.039) and elevated serum cholesterol level was associated with lower age (P-interaction 0.019).

CONCLUSION

This study confirmed an interaction between age and other influencing factors, which may be important in explaining differences in risk factors for diabetes and prediabetes in the middle-aged and elderly populations. Community health facilities can provide health guidance to people of different age groups to prevent and control prediabetes and diabetes.

Patterns of change in obesity indices and other cardiometabolic risk factors before the diagnosis of type 2 diabetes: two decades follow-up of the Tehran lipid and glucose study

Background

Identifying patterns of variation in obesity indices and other cardiometabolic risk factors before the diagnosis of type 2 diabetes could provide insight into the critical period when drastic changes occurred and facilitate targeted interventions for the prevention of diabetes. Therefore, this study sought to explore patterns of change in obesity indices and other cardiometabolic risk factors before diabetes diagnosis.

Methods

We investigated 6305 participants (43.7% men) aged 20–65 from the Tehran Lipid and Glucose Study (TLGS) who were free of diabetes at baseline. First, we jointly estimated developmental multi-trajectories of obesity indices using multivariate latent class growth mixed model, and then patterns of cardiometabolic risk factors within the identified multi-trajectories were assessed using mixed-effects models.

Results

Three patterns of change in obesity indices were identified. Most participants belonged to the “progressing” group (83.4%; n = 742), with a slight but steadily rising in obesity indices until diagnosis in both men and women. All multi-trajectory groups showed similar exponential increases in fasting and 2-h plasma glucose concentrations 6 years before diagnosis and linear increases in blood pressure and total and LDL cholesterol throughout follow-up. Patterns of triglyceride and HDL cholesterol accompanied each group’s patterns of change in obesity indices.

Conclusion

Three patterns of the joint progression of obesity indices before diabetes diagnosis were accompanied by similar blood glucose patterns and other cardiometabolic risk factors. These findings suggest the impact of the increasing trend of obesity indices and other metabolic factors on the incidence of diabetes and emphasize the importance of assessing the metabolic risk factors at each visit.

Association of body mass index and waist circumference with type 2 diabetes mellitus in older adults: a cross-sectional study

BACKGROUND

The prevalence of obesity and diabetes is rising. The aim of this study was to determine the association of body mass index (BMI) and waist circumference (WC) with type 2 diabetes mellitus (T2DM) in the elderly and to compare the discriminatory abilities of BMI, WC and other anthropometric indicators, including waist-to-height ratio (WHtR), body adiposity estimator (BAE) and body roundness index (BRI) for T2DM.

METHODS

This cross-sectional study included 69,388 subjects aged ≥ 60 years living in Xinzheng, Henan Province, from January to December 2020. The data came from the residents' electronic health records of the Xinzheng Hospital Information System. Logistic regression was used to examine the relationships. Fully adjusted models adjusted for age, sex, place of residence, alcohol consumption, smoking, physical exercise, SBP and RHR. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminatory ability of different anthropometric indicators for T2DM under the influence of potential risk factors.

RESULTS

After adjusting for multiple covariates, compared with the first BMI quintile, the odds ratios (ORs) and 95% confidence intervals (CIs) from the second to fifth quintile for T2DM were 1.416 (1.335-1.502), 1.664 (1.570-1.764), 1.879 (1.774-1.990) and 2.156 (2.037-2.283), respectively. Compared with the first WC quintile, the ORs and 95% CIs from the second to fifth quintiles for T2DM were 1.322 (1.244-1.404), 1.549 (1.459-1.643), 1.705 (1.609-1.807) and 2.169 (2.048-2.297), respectively. Among men, compared with other anthropometric indicators (BMI, WHtR, BAE and BRI), WC showed the highest AUC (AUC: 0.629; 95% CI: 0.622-0.636). Among women, the AUCs of BMI (AUC: 0.600; 95% CI: 0.594-0.606), WC (AUC: 0.600; 95% CI: 0.593-0.606) and BAE (AUC: 0.600; 95% CI: 0.594-0.607) were similar, and the AUCs of BMI, WC and BAE were higher than WHtR, BRI.

CONCLUSIONS

All anthropometric indicators were positively associated with T2DM. In men, WC with the strongest positive association with T2DM was the best predictor of T2DM. In women, BMI was most strongly associated with T2DM, and the predictive powers of BMI, WC and BAE were similar. After adjusting the potential confounding factors including age, sex, place of residence, alcohol consumption, smoking, physical exercise, SBP and RHR, the effect of these factors was eliminated, the findings were independent of the covariates considered.

Association Between Some Different Obesity Anthropometric Indices and Type 2 Diabetes Mellitus in Middle-Aged and Elderly Chinese Men and Women in Beijing, China: A Cross-Sectional Study

BACKGROUND

Obesity can lead to the development of type 2 diabetes mellitus (T2DM). However, the predictive power of different obesity anthropometric indices (ObAIs) for T2DM varies with race and geographical area. Therefore, the study aimed to investigate the association between different ObAIs and T2DM and determine the best index for screening T2DM in middle-aged and elderly men and women in Beijing, China.

METHODS

A cross-sectional study was conducted in Shijingshan district (Beijing, China) from November 2011 to August 2012, involving a total of 14,558 subjects aged ≥40 years. Data on demographic information, lifestyle, history of T2DM, hypertension and dyslipidemia were collected. Body height, body weight, waist circumference (WC), hip circumference, and blood pressure were recorded. The oral glucose tolerance test or a standard meal test and blood lipid test were performed. The relationship between different ObAIs and T2DM was analyzed using multiple logistic regression.

RESULTS

After adjustment for age, smoking status, alcohol intake, occupation and education degree, diabetes family history, hypertension and dyslipidemia, body mass index (BMI), WC, waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were positively associated with T2DM in both men and women. Compared with the lowest BMI, WC, WHR, and WHtR quartiles, ORs of the highest quartiles were 2.131 (95% CI: 1.465-3.099), 1.752 (95% CI: 1.270-2.417), 1.342 (95% CI: 1.072-1.678), 2.739 (95% CI: 2.293-3.271) in men and 1.837 (95% CI: 1.584-2.130), 3.122 (95% CI: 1.980-4.924), 3.781 (95% CI: 2.855-5.007), 2.379 (85% CI: 2.040-2.775), respectively, in women. The areas under ROC curve of BMI, WC, WHR, and WHtR for men were 0.584 (95% CI: 0.568-0.600), 0.509 (95% CI: 0.492-0.525), 0.501 (95% CI: 0.485-0.518), and 0.642 (95% CI: 0.627-0.658) and 0.619 (95% CI: 0.607-0.632), 0.709 (95% CI: 0.697-0.720), 0.741 (95% CI: 0.730-0.752), and 0.654 (95% CI: 0.642-0.666), respectively, for women.

CONCLUSION

WHtR and WHR have been found to perform better as predictors of T2DM in middle-aged and elderly Chinese men and women, respectively.

Prevalence and clinical characteristics of T2DM patients with OTUD3 gene rs78466831 SNP at a single academic center in China

BACKGROUND

A novel, rare OTUD3 c.863G>A (rs78466831) in humans has been reported associated with diabetes, but the prevalence and clinical characteristics of T2DM patients with rs78466831 have not been reported before.

OBJECTIVE

To investigate the prevalence and clinical characteristics of T2DM patients with rs78466831 and provide a basis for clinical diagnosis and treatment.

METHODS

OTUD3 gene rs78466831 SNP was detected by Sanger sequencing in all the collected specimens of laboratory-confirmed T2DM patients and healthy people. Clinical characteristics indexes inconsisting of fasting blood glucose (FBG), glycosylated hemoglobin (HbA1c), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), total cholesterol (TC), triglyceride (TG) and a body mass index (BMI), T2DM-associated chronic complications (myocardial infarction, cerebrovascular disease, retinopathy, arterial plaque, peripheral neuropathy and nephropathy) were obtained from the clinical laboratory information systems and electronic medical record system. Clinical characteristic indicators were compared between the wild-type and variant (rs78466831) patients with T2DM.

RESULTS

The prevalence of rs78466831 in the T2DM patients group was significantly higher than the healthy control in our academic center. The general characteristic indicators were not significantly different between the wild-type and rs78466831 patients with T2DM, except the family history of diabetes. Clinical laboratory indicators including HbA1c, FBG, OGTT, TC, HDL-C, LDL-C and CP had no significant difference between the two groups. The therapeutic drug and target achievement rates were not significantly different between the two groups. The incidence of diabetic retinopathy in the variant group was significantly higher than the wild-type group.

CONCLUSIONS

The OTUD3 gene rs78466831 was associated with T2DM and may be a biological risk factor of diabetes retinopathy.