Assessing different anthropometric indices and their optimal cutoffs for prediction of type 2 diabetes and impaired fasting glucose in Asians: The Jinchang Cohort Study

Association between triglyceride glucose-body mass index and obstructive sleep apnea: a study from NHANES 2015-2018

Background

The association between TyG-BMI index and the risk of obstructive sleep apnea (OSA), a recently identified biomarker indicating insulin resistance, has yet to be elucidated. Therefore, this study aimed to investigate the association between TyG-BMI index and the risk of OSA using the NHANES database.

Methods

Analyses were performed on NHANES data conducted between 2015 and 2018. Logistic regression, stratified analyses, curve-fitting analyses, and threshold effects analyses were utilized to assess the association between TyG-BMI index and the risk of OSA.

Results

The study included 4,588 participants. Multifactorial logistic regression analyses found a significant association between TyG-BMI and increased risk of OSA [OR: 1.54 (CI:1.39-1.70)]. In stratified analyses, age interacted with the association, with TyG-BMI being associated with increased risk of OSA only in a subgroup of subjects younger than 60 years [1.31 (1.14-1.50)], but gender, smoking status, and alcohol use, did not influence the association. The presence of diabetes, hypertension, and cardiovascular diseases also modified the association, but the number of the included subjects with such conditions was significantly lower, therefore the significance of associations was not observed in those subgroups. Additionally, the risk was non-linearly associated, with the inflection point of TyG-BMI at 12.09, after which the lower slope in the risk was observed.

Conclusion

This study demonstrates that elevated levels of the TyG-BMI index are correlated with risk for OSA, underscoring the significance of these findings in facilitating early prevention or timely intervention for OSA.

Novel anthropometric indices for predicting type 2 diabetes mellitus

BACKGROUND

This study aimed to compare anthropometric indices to predict type 2 diabetes mellitus (T2DM) among first-degree relatives of diabetic patients in the Iranian community.

METHODS

In this study, information on 3483 first-degree relatives (FDRs) of diabetic patients was extracted from the database of the Endocrinology and Metabolism Research Center of Isfahan University of Medical Sciences. Overall, 2082 FDRs were included in the analyses. A logistic regression model was used to evaluate the association between anthropometric indices and the odds of having diabetes. Furthermore, a receiver operating characteristic (ROC) curve was applied to estimate the optimal cutoff point based on the sensitivity and specificity of each index. In addition, the indices were compared based on the area under the curve (AUC).

RESULTS

The overall prevalence of diabetes was 15.3%. The optimal cutoff points for anthropometric measures among men were 25.09 for body mass index (BMI) (AUC = 0.573), 0.52 for waist-to-height ratio (WHtR) (AUC = 0.648), 0.91 for waist-to-hip ratio (WHR) (AUC = 0.654), 0.08 for a body shape index (ABSI) (AUC = 0.599), 3.92 for body roundness index (BRI) (AUC = 0.648), 27.27 for body adiposity index (BAI) (AUC = 0.590), and 8 for visceral adiposity index (VAI) (AUC = 0.596). The optimal cutoff points for anthropometric indices were 28.75 for BMI (AUC = 0.610), 0.55 for the WHtR (AUC = 0.685), 0.80 for the WHR (AUC = 0.687), 0.07 for the ABSI (AUC = 0.669), 4.34 for the BRI (AUC = 0.685), 39.95 for the BAI (AUC = 0.583), and 6.15 for the VAI (AUC = 0.658). The WHR, WHTR, and BRI were revealed to have fair AUC values and were relatively greater than the other indices for both men and women. Furthermore, in women, the ABSI and VAI also had fair AUCs. However, BMI and the BAI had the lowest AUC values among the indices in both sexes.

CONCLUSION

The WHtR, BRI, VAI, and WHR outperformed other anthropometric indices in predicting T2DM in first-degree relatives (FDRs) of diabetic patients. However, further investigations in different populations may need to be implemented to justify their widespread adoption in clinical practice.

Association between triglyceride glucose-body mass index and heart failure in subjects with diabetes mellitus or prediabetes mellitus: a cross-sectional study

Background

The triglyceride glucose-body mass index (TyG-BMI) is a surrogate indicator of insulin resistance. However, the association of TyG-BMI with heart failure (HF) in individuals with diabetes mellitus or prediabetes mellitus is unknown.

Methods

This study included 7,472 participants aged 20-80 years old with prediabetes or diabetes from the National Health and Nutrition Examination Survey (2007-2018). The TyG-BMI was calculated as Ln [triglyceride (mg/dL) × fasting blood glucose (mg/dL)/2] × BMI, and individuals were categorized into tertiles based on TyG-BMI levels. The relationship of TyG-BMI with HF was analyzed using multiple logistic regression models. Subgroup analyses were stratified by gender, age, hypertension, and diabetes mellitus status.

Results

This cross-sectional study had 7,472 participants (weighted n = 111,808,357), including 329 HF participants. Participants with a high TyG-BMI were prone to HF. The highest tertile group with a fully adjusted model was more likely to have HF compared to the lowest tertile group (odds ratio [OR], 2.645; 95% CI, 1.529-4.576). Restricted cubic spline analysis showed a significant dose-response relationship between TyG-BMI and HF (P < 0.001). In subgroup analyses, similar results were seen in terms of age (≥50 years old), gender, hypertension, and diabetes mellitus status.

Conclusion

A high TyG-BMI is significantly associated with HF risk in participants with diabetes mellitus or prediabetes mellitus.

Detection of high risk people for diabetes by American diabetes association risk score in PERSIAN Guilan cohort study

BACKGROUND

Diabetes mellitus (DM) is known as one of the most prevalent non communicable diseases with high cost of health services in the world. Present study was conducted to assess the frequency of high risk people for diabetes mellitus based on American Diabetes Association (ADA) risk score among Iranian people.

METHODS

Present study was a cross sectional study on non-diabetic subjects aged 35-70 years from 10,520 PERSIAN Guilan Cohort Study (PGCS). ADA risk score was calculated for every individual through an online calculator. Receiver operating characteristic (ROC) curves was used to assess diagnostic accuracy of the anthropometric indices to identify individuals with high risk ADA score for developing DM, represented by the area under the curve (AUC).

RESULTS

From 7989 study subjects, ADA risk score found 3874 (48.5%) and 1912 (23%) at risk for developing PreDM and DM, respectively. The results of ROC curve analyses showed the highest diagnostic value was related to waist circumference (WC) in total population and Waist to Height Ratio in both sex (0.695 total, 0.743 female, 0.744 male). The cut-points of WC in total population to identifying high risk group were 97 cm.

CONCLUSIONS

A considerable number of populations were classified as high ADA risk for developing DM and PreDM that provide the importance of prevention strategies. Present study showed WC and Waist to Height Ratio have the highest diagnostic value to identify high risk people for DM.

Cost-effectiveness of community diabetes screening: Application of Akaike information criterion in rural communities of Nigeria

Background

The prevalence of diabetes mellitus (DM) is increasing globally, and this requires several approaches to screening. There are reports of alternative indices for prediction of DM, besides fasting blood glucose (FBG) level. This study, investigated the ability of combination of biochemical and anthropometric parameters and orodental disease indicators (ODIs) to generate models for DM prediction, using Akaike information criterion (AIC) to substantiate health economics of diabetes screening.

Methods

Four hundred and thirty-three subjects were enrolled in the study in Ndokwa communities, Delta State, Nigeria, and their glycaemic status was determined, using the CardioChek analyser^® and previous data from the Prediabetes and Cardiovascular Complications Study were also used. The cost of screening for diabetes (NGN 300 = $0.72) in a not-for-profit organization/hospital was used as basis to calculate the health economics of number of individuals with DM in 1,000 participants. Data on the subjects' anthropometric, biochemical and ODI parameters were used to generate different models, using R statistical software (version 4.0.0). The different models were evaluated for their AIC values. Lowest AIC was considered as best model. Microsoft Excel software (version 2020) was used in preliminary analysis.

Result

The cost of identifying <2 new subjects with hyperglycemia, in 1,000 people was ≥NGN 300,000 ($ 716). A total of 4,125 models were generated. AIC modeling indicates FBG test as the best model (AIC = 4), and the least being combination of random blood sugar + waist circumference + hip circumference (AIC ≈ 34). Models containing ODI parameters had AIC values >34, hence considered as not recommendable.

Conclusion

The cost of general screening for diabetes in rural communities may appear high and burdensome in terms of health economics. However, the use of prediction models involving AIC is of value in terms of cost-benefit and cost-effectiveness to the healthcare consumers, which favors health economics.

Evaluation of anthropometric indices as a predictor of diabetes in Dong and Miao ethnicities in China: A cross-sectional analysis of China Multi-Ethnic Cohort Study

BACKGROUND

Although it is known that obesity is inseparable from diabetes, many anthropometric indices are used for determining obesity. At the same time, research on the predictive indices of diabetes in Chinese minority populations is lacking. Therefore, this study determines the relationship between different anthropometric indices and diabetes, and identifies the best index and best cut-off values for predicting diabetes.

METHOD

In total, 11,035 Dong and Miao ethnic participants (age: 30-79 years) from the China Multi-Ethnic Cohort study were included. The logistic regression model was used to examine the relationship between the different anthropometric indices and diabetes risk. The receiver operating characteristic curve and the area under the curve (AUC) were used to identify the best predictor of diabetes.

RESULTS

In multivariate adjusted logistic regression models, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), and visceral adiposity index (VAI) were positively correlated with diabetes risk. Among Chinese Dong men and women and Miao men, WHR had the largest AUC (0.654/0.719/0.651). Among Miao women, VAI had the largest AUC(0.701). The best cut-off values of WHR for Dong men and women and Miao men were 0.94, 0.92, and 0.91, respectively. The best cut-off value of VAI for Miao women was 2.20.

CONCLUSION

Obesity indicators better predict diabetes in women than men. WHR may be the best predictor of diabetes risk in both sex of Dong ethnicity and Miao men, and VAI may be the best predictor of diabetes risk in Miao women.

Association of body mass index with risk of prediabetes in Chinese adults: a population-based cohort study

Aims/Introduction

Overweight and obesity in adults are strongly associated with an increased risk of prediabetes, and this study set out to gain a better understanding of the optimal body mass index (BMI) range for assessing the risk of prediabetes in the Chinese population.

Materials and Methods

The cohort study included 100,309 Chinese adults who underwent health screening. Participants were divided into six groups based on the cut‐off point for BMI recommended by the World Health Organization (underweight: <18.5 kg/m², normal‐weight: 18.5–24.9 kg/m², pre‐obese: 25.0–29.9 kg/m², obese class I: 30.0–34.9 kg/m², obese class II: 35.0–39.9 kg/m², and obese class III ≥40 kg/m²). The association of BMI with prediabetes and the shape of the correlation were modeled using multivariate Cox regression and restricted cubic spline regression, respectively.

Results

In the multivariate Cox regression model, with normal weight as the control group, underweight people had a lower risk of developing prediabetes, whereas obese and pre‐obese people had a higher risk of prediabetes. Additionally, in the restricted cubic spline model, we found that the association of BMI with prediabetes follows a positive dose–response relationship, but does not conform to the pattern of obesity paradox. Among the general population in China, a BMI of 23.03 kg/m² might be a potential intervention threshold for prediabetes.

Conclusions

The national cohort study found that the association of BMI with prediabetes follows a positive dose–response relationship, rather than a pattern of obesity paradox. For Chinese people with normal weight, more attention should be paid to glucose metabolism when BMI exceeds 23.03 kg/m².

Triglyceride Glucose-Body Mass Index and Risk of Incident Type 2 Diabetes Mellitus in Japanese People With Normal Glycemic Level: A Population-Based Longitudinal Cohort Study

BACKGROUND

It has been proved that triglyceride glucose-body mass index (TyG-BMI) is a readily available and clinically significant indicator of insulin resistance (IR). Nevertheless, the association between TyG-BMI and incident Type 2 diabetes mellitus (T2DM) remains uncertain. This study aimed to study the relationship between TyG-BMI and T2DM and explore the predictive characteristics of TyG-BMI.

METHODS

Our study was conducted as a longitudinal cohort study. 8,430 men and 7,034 women were enrolled and analyzed. They were both non-diabetic subjects with normal glycemic levels. Follow-up lasted for 13 years, from 1994 to 2016. To make the number of TyG-BMI in each group similar, the subjects were divided into four groups with 3866 subjects in each group.

RESULTS

During the 13-year follow-up period, 373 subjects were diagnosed with incident T2DM. Our multivariate Cox regression analysis revealed that TyG-BMI was an independent predictor of incident T2DM. In addition, our research identified four specific groups, young people (18-44 years old), women, the non-hypertensive population and non-drinkers were at significantly higher risk of developing TyG-BMI-related diabetes (P-interaction< 0.05). The best threshold TyG-BMI for predicting incident T2DM was 197.2987 (area under the curve 0.7738).

CONCLUSIONS

Our longitudinal cohort study demonstrated the positive correlation between baseline TyG-BMI and risk of incident T2DM in Japanese with normal glycemic levels, and this risk was significantly higher in the young people, women, the non-hypertensive population and non-drinkers.

Triglyceride glucose-body mass index in identifying high-risk groups of pre-diabetes

Background

Triglyceride glucose-body mass index (TyG-BMI) has been recommended as an alternative indicator of insulin resistance. However, the association between TyG-BMI and pre-diabetes remains to be elucidated.

Methods

More than 100,000 subjects with normal glucose at baseline received follow-up. The main outcome event of concern was pre-diabetes defined according to the diagnostic criteria recommended by the American Diabetes Association (ADA) in 2018 and the World Health Organization (WHO) in 1999. A Cox proportional hazard regression model was used to evaluate the role of TyG-BMI in identifying people at high risk of pre-diabetes.

Results

At a mean observation period of 3.1 years, the incidence of pre-diabetes in the cohort was 3.70 and 12.31% according to the WHO and ADA diagnostic criteria for pre-diabetes, respectively. The multivariate Cox regression analysis demonstrated that TyG-BMI was independently positively correlated with pre-diabetes, and there was a special population dependence phenomenon. Among them, non-obese people, women and people under 50 years old had a significantly higher risk of TyG-BMI-related pre-diabetes (P-interaction< 0.05).

Conclusions

These findings suggest that a higher TyG-BMI significantly increases an individual’s risk of pre-diabetes, and this risk is significantly higher in women, non-obese individuals, and individuals younger than 50 years of age.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-021-01594-7.

Sex-specific associations of blood and urinary manganese levels with glucose levels, insulin resistance and kidney function in US adults: National health and nutrition examination survey 2011-2016

Exposures to heavy metals play a role in the etiopathogenesis of diabetes. Epidemiological studies investigating a potential sex-specific linkage between manganese (Mn) exposures and glucose homeostasis are rare. We comprehensively estimated the associations of blood and urinary Mn levels with fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), homeostasis model assessment for insulin resistance (HOMA-IR), insulin, and estimated glomerular filtration rate (eGFR) among 1417 adults in the US National Health and Nutrition Examination Survey (NHANES) 2011-2016. We further examined the potential heterogeneities by sex and joint-effects of multiple metal exposures by the Bayesian kernel machine regression (BKMR). Among women, we found positive linear relationships between urinary Mn with FPG (P_overall = 0.003, P_nonlinear = 0.817) and HbA1c (P_overall = 0.023, P_nonlinear = 0.854). Among men, J-shaped relationships were observed between blood Mn with HOMA-IR (P_nonlinear = 0.042) and insulin (P_nonlinear = 0.014). For eGFR, positive linear relationships were obserned among women for blood Mn (P_nonlinear = 0.549) and among both men and women for urinary Mn levels. The joint-effects of urinary Mn with molybdenum (Mo) on FPG and HbA1c, urinary Mn with cadmium (Cd) and cesium (Cs) on eGFR, and blood Mn with Cd and lead (Pb) on eGFR were detected. In summary, blood and urinary Mn levels were independently associated with glucose levels, insulin resistance and kidney function with potential sex-dependent heterogeneities. These findings emphasize the probable role of Mn in the regulation of glucose metabolism and kidney function, and confirm the need for more studies on sex-specific risk of diabetes.

Beyond Asian-Specific Cutoffs: Gender Effects on the Predictability of Body Mass Index, Waist Circumference, and Waist Circumference to Height Ratio on Hemoglobin A1c

OBJECTIVES

This study examines the gender effect on the associations between body mass index (BMI), waist circumference (WC), and waist circumference to height ratio (WHtR) with hemoglobin A1c (HbA1c) when Asian-specific cutoffs are applied among Asians living in the USA.

DESIGN

This study used the pooled 2013-2014 and 2015-2016 National Health and Nutrition Examination Survey (NHANES) data to produce a sample of 900 Asians who were non-pregnant and non-Hispanic aged 20-65. Bivariate and general linear regression analyses were conducted based on gender and age group.

RESULTS

The group variations of BMI, WC, and WHtR all exhibited different patterns between males and females. Among the bivariate correlations with HbA1c, WHtR was the strongest in males and WC was the strongest in females. All three measures performed better in predicting HbA1c among younger Asians. WC predicted more of the variance in HbA1c among females, whereas WHtR predicted more of the variance in HbA1c among males.

CONCLUSIONS

WC and WHtR are two anthropometric measures that serve as appropriate proxy of HbA1c for gauging the risk of developing type 2 diabetes among Asians living in the USA. They can be easily performed at non-clinical settings and should be used by individuals to monitor their health and be a part of disease prevention.

Association of triglyceride glucose index and its combination of obesity indices with prehypertension in lean individuals: A cross-sectional study of Chinese adults

For normal-weight population, the management of prehypertension may be more beneficial by identifying insulin resistance (IR) status than relying solely on traditional indicators of obesity. We investigated the association of triglyceride glucose (TyG) index, a simple surrogate marker of IR, and its combination of obesity indices with prehypertension in lean individuals. A total of 105 070 lean adults without hypertension were included in this analysis. Body mass index (BMI), waist circumference (WC), waist-to-height ratio (WtHR), and TyG were calculated according to the corresponding formula; TyG-BMI, TyG-WC, and TyG-WHtR were calculated by multiplying the corresponding two parameters. Gardner-Altman plots, partial correlation, and logistic regression analyses were applied to explore the associations in continuous variables and quartiles. The prehypertensive ones had higher mean values of TyG, TyG-BMI, TyG-WC, and TyG-WHtR than normotensive individuals. All the four indicators showed positive correlations with systolic blood pressure and diastolic blood pressure. After full adjustment, only TyG-BMI and TyG-WC were significantly associated with prehypertension in both genders. Furthermore, TyG-BMI had the highest OR for prehypertension. Our study showed that TyG-BMI might be an accessible and complementary monitor in the hierarchical management of non-obese prehypertensive patients.