Changes in Metabolic Health Status Over Time and Risk of Developing Type 2 Diabetes: A Prospective Cohort Study

Clinical Classification of Obesity and Implications for Metabolic Dysfunction-Associated Fatty Liver Disease and Treatment

Obesity,and metabolic dysfunction-associated fatty liver disease (MAFLD) have reached epidemic proportions globally. Obesity and MAFLD frequently coexist and act synergistically to increase the risk of adverse clinical outcomes (both hepatic and extrahepatic). Type 2 diabetes mellitus (T2DM) is the most important risk factor for rapid progression of steatohepatitis and advanced fibrosis. Conversely, the later stages of MAFLD are associated with an increased risk of T2DM incident. According to the proposed criteria, MAFLD is diagnosed in patients with liver steatosis and in at least one in three: overweight or obese, T2DM, or signs of metabolic dysregulation if they are of normal weight. However, the clinical classification and correlation between obesity and MAFLD is more complex than expected. In addition, treatment for obesity and MAFLD are associated with a reduced risk of T2DM, suggesting that liver-based treatments could reduce the risk of developing T2DM. This review describes the clinical classification of obesity and MAFLD, discusses the clinical features of various types of obesity and MAFLD, emphasizes the role of visceral obesity and insulin resistance (IR) in the development of MAFLD,and summarizes the existing treatments for obesity and MAFLD that reduce the risk of developing T2DM.

Transitions in Metabolic Health Status and Obesity Over Time and Risk of Diabetes: The Dongfeng-Tongji Cohort Study

CONTEXT

Evidence regarding the association between metabolically healthy overweight or obesity (MHOO) and diabetes is controversial, and mostly ignores the dynamic change of metabolic health status and obesity.

OBJECTIVE

To explore the association between transitions of metabolic health status and obesity over 5 years and diabetes incidence.

METHODS

We examined 17 309 participants derived from the Dongfeng-Tongji cohort and followed from 2008 to 2018 (median follow-up 9.9 years). All participants were categorized into 4 phenotypes based on body mass index (BMI) and metabolic health status: metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), MHOO, and metabolically unhealthy overweight or obesity (MUOO). The associations of changes in BMI-metabolic health status (2008-2013) with diabetes incidence (2018) were performed among 12 206 individuals with 2 follow-up examinations.

RESULTS

Compared with stable MHNW, stable MHOO (hazard ratio [HR] 1.76; 95% CI 1.26, 2.45) and transition from MHOO to metabolically unhealthy phenotypes were associated with higher risk for diabetes (HR 2.97; 95% CI 1.79, 4.93 in MHOO to MUNW group and HR 3.38; 95% CI 2.54, 4.49 in MHOO to MUOO group). Instead, improvements to metabolic healthy phenotypes or weight loss occurring in MUOO reduced the risk of diabetes compared with stable MUOO, changing from MUOO to MHNW, MUNW, and MHOO resulted in HRs of 0.57 (95% CI 0.37, 0.87), 0.68 (95% CI 0.50, 0.93), and 0.45 (95% CI 0.34, 0.60), respectively.

CONCLUSION

People with MHOO, even stable MHOO, or its transition to metabolically unhealthy phenotypes were at increased risk of diabetes. Metabolic improvements and weight control may reduce the risk of diabetes.

Association of Metabolically Healthy Obesity and Risk of Cardiovascular Disease Among Adults in China: A Retrospective Cohort Study

PURPOSE

Previous studies have shown that metabolically healthy obesity (MHO) and changes in its status are connected to an increased incidence of cardiovascular disease (CVD). Yet, fewer studies have been conducted in China, especially for the middle-aged and elderly population, a high-risk group. The purpose of the study was to investigate the association between metabolic health status and CVD events.

PATIENTS AND METHODS

A total of 46,055 participants were categorized into 6 subgroups with different metabolic states according to the existence of metabolic syndrome and body mass index (BMI). The changes in obesity and metabolic health status were defined from baseline to follow-up outcomes with a combination of overweight and obesity. Cox proportional hazards models estimated the association of CVD events and each BMI-metabolic groups.

RESULTS

MHO and metabolic abnormality normal weight (MANW) subjects had a higher HR of CVD, 1.62 (95% CI, 1.36-1.92) and 1.24 (95% CI, 1.07-1.44), respectively, than their metabolically healthy normal weight (MHNW) counterparts. Then, more than 50% and 30% of the metabolically healthy overweight or obesity (MHOO) populations maintained their status and converted to a metabolically unhealthy state, respectively. Stable MANW, MHOO and metabolically abnormal obesity (MAO) were associated with a higher risk for CVD, 1.68 (95% CI, 1.37-2.05),1.26 (95% CI, 1.08-1.47) and 1.65 (95% CI, 1.45-1.88), respectively, than stable MHNW.

CONCLUSION

Despite being of normal weight, MANW status is in fact a risk factor for CVD, as well as MHO, especially for the Chinese middle-aged and elderly population. Furthermore, metabolic health is a transient state for partial middle-aged and elderly Chinese individuals, and MAO has the highest risk of CVD, including coronary heart disease (CHD) and stroke.

Association between non-alcoholic fatty liver disease and metabolically healthy deterioration across different body shape phenotypes at baseline and change patterns

Non-alcoholic fatty liver disease (NAFLD) is a hepatic manifestation of metabolic syndrome (MetS), and the relationship between NAFLD and metabolic deterioration remains unclear. This study aimed to investigate dynamic changes in metabolically healthy phenotypes and to assess the impact of non-alcoholic fatty liver disease (NAFLD) on the conversion from metabolically healthy (MH) to metabolically unhealthy (MU) phenotypes across body shape phenotypes and phenotypic change patterns. We defined body shape phenotypes using both the body mass index (BMI) and waist circumference (WC) and defined metabolic health as individuals scoring ≤ 1 on the NCEP-ATP III criteria, excluding WC. A total of 12,910 Chinese participants who were MH at baseline were enrolled in 2013 and followed-up in 2019 or 2020. During a median follow-up of 6.9 years, 27.0% (n = 3,486) of the MH individuals developed an MU phenotype. According to the multivariate Cox analyses, NAFLD was a significant predictor of conversion from the MH to MU phenotype, independent of potential confounders (HR: 1.12; 95% confidence interval: 1.02–1.22). For the MH-normal weight group, the relative risk of NAFLD in phenotypic conversion was 1.21 (95% CI 1.03–1.41, P = 0.017), which was relatively higher than that of MH-overweight/obesity group (HR: 1.14, 95% CI 1.02–1.26, P = 0.013). Interestingly, the effect of NAFLD at baseline on MH deterioration was stronger in the “lean” phenotype group than in the “non-lean” phenotype group at baseline and in the “fluctuating non-lean” phenotype change pattern group than in the “stable non-lean” phenotype change pattern group during follow-up. In conclusion, lean NAFLD is not as benign as currently considered and requires more attention during metabolic status screening.

Pathogenesis, Murine Models, and Clinical Implications of Metabolically Healthy Obesity

Although obesity is commonly associated with numerous cardiometabolic pathologies, some people with obesity are resistant to detrimental effects of excess body fat, which constitutes a condition called “metabolically healthy obesity” (MHO). Metabolic features of MHO that distinguish it from metabolically unhealthy obesity (MUO) include differences in the fat distribution, adipokine types, and levels of chronic inflammation. Murine models are available that mimic the phenotype of human MHO, with increased adiposity but preserved insulin sensitivity. Clinically, there is no established definition of MHO yet. Despite the lack of a uniform definition, most studies describe MHO as a particular case of obesity with no or only one metabolic syndrome components and lower levels of insulin resistance or inflammatory markers. Another clinical viewpoint is the dynamic and changing nature of MHO, which substantially impacts the clinical outcome. In this review, we explore the pathophysiology and some murine models of MHO. The definition, variability, and clinical implications of the MHO phenotype are also discussed. Understanding the characteristics that differentiate people with MHO from those with MUO can lead to new insights into the mechanisms behind obesity-related metabolic derangements and diseases.

Triglyceride and Glucose Index Predicts Acute Coronary Syndrome in Patients with Antineutrophil Cytoplasmic Antibody-Associated Vasculitis

This study investigated whether the triglyceride (TG) glucose (TyG) index at diagnosis could predict acute coronary syndrome (ACS) in patients with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). The medical records of 152 AAV were reviewed. Clinical and laboratory data were collected. The TyG index was calculated by TyG index = Ln (fasting TG (mg/dL) × fasting glucose (mg/dL)/2). The cut-offs of Birmingham vasculitis activity score (BVAS) and the TyG were obtained by the receiver operator characteristic (ROC) curve and the highest tertile (9.011). The mean age was 57.2 years and 32.9% were male. AAV patients with a TyG index ≥ 9.011 exhibited a lower cumulative ACS-free survival rate than those with a TyG index < 9.011. However, a TyG index ≥ 9.011 was not independently associated with ACS in the multivariable Cox analysis. Meanwhile, there might be a close relationship for predicting ACS among the TyG index, metabolic syndrome (MetS), and BVAS. AAV patients with a TyG index ≥ 9.011 exhibited a higher risk for MetS than those with a TyG index < 9.011 (relative risk 2.833). AAV patients with BVAS ≥ 11.5 also exhibited a higher risk for ACS than those with BVAS < 11.5 (relative risk 10.225). Both AAV patients with MetS and those with BVAS ≥11.5 exhibited lower cumulative ACS-free survival rates than those without. The TyG index at AAV diagnosis could estimate the concurrent presence of MetS and predict the occurrence of ACS during follow-up along with high BVAS at diagnosis in patients with AAV.

Distinct triglyceride-glucose trajectories are associated with different risks of incident cardiovascular disease in normal-weight adults

BACKGROUND

Long-term patterns of the triglyceride-glucose index (TyG index) and their effects on cardiovascular disease (CVD) among normal-weight adults are poorly characterized. This study aimed to identify TyG index trajectories in normal-weight adults and to determine their association with the risk of incident CVD.

METHODS

This study included 40,473 normal-weight participants who were free of stroke and myocardial infarction prior to or in 2012. The TyG index was calculated as ln (fasting triglyceride [mg/dL] × fasting glucose [mg/dL]/2), and the TyG index trajectories during 2006-2012 were identified by latent mixture modeling.

RESULTS

We identified five distinct TyG index trajectories according to TyG index range and changing pattern over time: low-stable (n = 9,806; mean TyG index 7.84-7.93), moderate-stable (n = 22,066; mean TyG index 8.43-8.52), high-decreasing (n = 1,469; mean TyG index 9.83-8.75), moderate-increasing (n = 5,842; mean TyG index 8.98-9.26), and high-stable (n = 1,290; mean TyG index 9.91-10.07). During 6.74 years of follow-up, we documented 1,577 incident CVD events. Compared with the low-stable pattern, the highest risk of CVD was observed in the high-stable pattern (hazard ratio [HR], 2.24; 95% confidence interval [CI]: 1.73-2.90), followed by the moderate-increasing pattern (HR, 1.70; 95% CI, 1.43-2.04), the high-decreasing pattern (HR, 1.45; 95% CI, 1.11-1.89), and the moderate-stable pattern (HR, 1.25; 95% CI, 1.08-1.44). Similar results were also observed for stroke and myocardial infarction.

CONCLUSIONS

Distinct TyG index trajectories were significantly associated differently subsequent risk of CVD in normal-weight individuals. These observations suggested that long-term trajectories of TyG index may be useful for predicting CVD among normal-weight adults.

Metabolic phenotypes and risk of colorectal cancer: a systematic review and meta-analysis of cohort studies

BACKGROUND

The association of obesity with colorectal cancer (CRC) may vary depending on metabolic status.

OBJECTIVE

This meta-analysis aimed to investigate the combined impacts of obesity and metabolic status on CRC risk.

METHODS

The Scopus, PubMed, and web of sciences databases were systematically searched up to Jun 2021 to find all eligible publications examining CRC risk in individuals with metabolically unhealthy normal-weight (MUHNW), metabolically healthy obesity (MHO), and metabolically unhealthy obesity (MUHO) phenotypes.

RESULTS

A total of 7 cohort studies with a total of 759,066 participants were included in this meta-analysis. Compared with healthy normal-weight people, MUHNW, MHO, and MUHO individuals indicated an increased risk for CRC with a pooled odds ratio of 1.19 (95% CI = 1.09-1.31) in MUHNW, 1.14 (95% CI = 1.06-1.22) in MHO, and 1.24 (95% CI = 1.19-1.29) in MUHO subjects. When analyses were stratified based on gender, associations remained significant for males. However, the elevated risk of CRC associated with MHO and MUHO was not significant in female participants.

CONCLUSIONS

The individuals with metabolic abnormality, although at a normal weight, have an increased risk for CRC. Moreover, obesity is associated with CRC irrespective of metabolic status.

Transitions in metabolic health status over time and risk of heart failure: a prospective study

AIMS

- Evidence for the effects of metabolically healthy obese (MHO) status on heart failure (HF) is limited and ignores the dynamic change of metabolic health and obesity phenotypes. We aimed to investigate the associations of metabolic health and its transition with HF across body mass index (BMI) and waist circumference (WC) categories.

METHODS

- This prospective cohort study was conducted with 93,288 Chinese adults who were free of cardiovascular disease, cancer or HF at baseline (2006-2007). Metabolic health was defined as having no or only one abnormality in blood pressure, glucose, high-density lipoprotein cholesterol, or triglyceride levels. Participants were cross-classified at baseline by metabolic health and obesity (defined by BMI and WC criteria). Transitions in metabolic health status from 2006-2007 to 2010-2011 were considered. The hazard ratios (HRs) and 95% confidence intervals (CIs) for HF were assessed by Cox proportional hazards regression.

RESULTS

- During a mean ± standard deviation follow-up of 9.7 ± 1.5 years, 1,628 participants developed HF. Individuals with MHO (HR: 1.78, 95% CI: 1.45, 2.19 for BMI criteria; HR: 1.51, 95% CI: 1.30, 1.76 for WC criteria) had higher risk of HF than those with metabolically healthy normal weight (MH-NW). Individuals with initial MHO who shifted to metabolically unhealthy phenotype during follow-up had higher risk of HF compared with stable MH-NW individuals (HR 3.12; 95% CI: 2.01, 4.85 for BMI categories; HR 1.98; 95% CI: 1.42, 2.77 for WC categories). Even stable MHO individuals were at an increased risk of HF compared with stable MH-NW individuals (HR: 2.17; 95% CI: 1.39, 3.39 for BMI categories; HR: 1.33; 95% CI: 0.96, 1.85 for WC categories).

CONCLUSIONS

- MHO phenotype is dynamic and its transition to metabolically unhealthy phenotype or even stable MHO is associated with increased risk of HF. Maintaining metabolic health may provide a clue for preventing HF.

The risk of Alzheimer's disease according to dynamic changes in metabolic health and obesity: a nationwide population-based cohort study

We evaluated the association of metabolic health and obesity phenotypes with the risk of Alzheimer's disease (AD). This study enrolled 136,847 elderly participants aged 60 or above from the Korean National Health Insurance System. At baseline examinations in 2009 and 2010, subjects were categorized into four groups: the metabolically healthy non-obese (MHNO), metabolically healthy obese (MHO), metabolically unhealthy non-obese (MUNO), and metabolically unhealthy obese (MUO) groups. Based on the phenotypic transition after 2 years, the subjects were further categorized into 16 subgroups. They were followed from 2009 to 2015 to monitor for AD development. The MHO phenotype protected subjects from AD, relative to the MHNO phenotype (HR, 0.73; 95% CI, 0.65-0.81). Among subjects initially classified as MHO, 41.8% remained MHO, with a significantly lower risk of AD compared with the stable MHNO group (HR, 0.62; 95% CI, 0.50-0.77). Among MUO subjects at baseline, those who changed phenotype to MUNO were at higher risk of AD (HR, 1.47; 95% CI, 1.28-1.70), and the transition to the MHO phenotype protected subjects from AD (HR, 0.62; 95% CI, 0.50-0.78). The MHO phenotype conferred a decreased risk of AD. Maintenance or recovery of metabolic health might mitigate AD risk among obese individuals.

Natural course of metabolically healthy phenotype and risk of developing Cardiometabolic diseases: a three years follow-up study

BACKGROUND

Whether the metabolically healthy obese (MHO) phenotype is a single, stable or a transitional, fluctuating state is currently unknown. The Mexican-Mestizo population has a genetic predisposition for the development of type 2 diabetes (T2D) and other cardiometabolic complications. Little is known about the natural history of metabolic health in this population. The aim of this study was to analyze the transitions over time among individuals with different degrees of metabolic health and body mass index, and evaluate the incidence of cardiometabolic outcomes according to phenotype.

METHODS

The study population consisted of a metabolic syndrome cohort with at least 3 years of follow up. Participants were apparently-healthy urban Mexican adults ≥20 years with a body mass index (BMI) ≥20 kg/m2. Metabolically healthy phenotype was defined using the criteria of the National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III) metabolic syndrome criteria and the subjects were stratified into 4 groups according to their BMI and metabolic health. For cardiometabolic outcomes we estimated the incidence of cardiometabolic outcomes and standardized them per 1, 000 person-years of follow-up. Finally, to evaluate the risk for transition and development of cardiometabolic outcomes, we fitted Cox Proportional Hazard regression models.

RESULTS

Amongst the 5541 subjects, 54.2% were classified as metabolically healthy and 45.8% as unhealthy. The MHO prevalence was 39.3%. Up to a third of the population changed from their initial category to another and the higher transition rate was observed in MHO (42.9%). We also found several novel factors associated to transition to metabolically unhealthy phenotype; socioeconomic status, number of pregnancies, a high carbohydrate intake, history of obesity and consumption of sweetened beverages. Similarly, visceral adipose tissue (VAT) was a main predictor of transition; loss of VAT ≥5% was associated with reversion from metabolically unhealthy to metabolically healthy phenotype (hazard ratio (HR) 1.545, 95%CI 1.266-1.886). Finally, we observed higher incidence rates and risk of incident T2D and hypertension in the metabolically unhealthy obesity (MUHO) and metabolically unhealthy lean (MUHL) phenotypes compared to MHO.

CONCLUSIONS

Metabolic health is a dynamic and continuous process, at high risk of transition to metabolically unhealthy phenotypes over time. It is imperative to establish effective processes in primary care to prevent such transitions.

Association between Triglyceride Glucose Index and Corrected QT Prolongation in Chinese Male Steelworkers

Objectives: Increased triglyceride glucose (TyG) index appears to be linked to carotid and coronary atherosclerosis and calcifications and possesses an elevated future risk of developing cardiovascular disease. Corrected QT (QTc) interval prolongation is associated with ventricular arrhythmias and sudden cardiac death, and a high prevalence of prolonged QTc interval was previously reported in blue-collar workers. The purpose of this study was to find the possible causal inter-relationship between TyG index and QTc interval in a large population of Chinese male steelworkers. Methods: A total of 3189 male workers from two steel plants were enrolled. They responded to a cross-sectional questionnaire on basic attributes and lifestyle, including sleep patterns. All workers in the two plants underwent periodic health checkups, including twelve-lead electrocardiography. Structural equation modeling (SEM) was used to assess the direct and indirect effects of TyG index on QTc interval. Results: With increasing TyG index tertile, the male steelworkers had an increased QTc interval. Applying multivariate analysis, TyG index was associated independently with the odds of QTc prolongation (adjusted odds ratio = 2.73, 95% confidence interval = 1.39–5.24, p = 0.004). SEM revealed that TyG index, hypertension, obesity, lifestyle, white blood cell (WBC) count, and liver function had statistically significant direct effects on QTc interval. Furthermore, TyG index also had an indirect effect on QTc interval through hypertension, obesity, WBC count, and liver function. Moreover, lifestyle had an indirect effect on QTc interval through TyG index. The final model explained 14% of the variability in QTc interval. Conclusions: An increased TyG index was associated with QTc interval prolongation in this study, and SEM delineated possible causal pathways and inter-relationships of the risk factors contributing to the occurrence of QTc prolongation among Chinese male steelworkers.

The Triglyceride-Glucose Index is Associated with Diabetic Retinopathy in Chinese Patients with Type 2 Diabetes: A Hospital-Based, Nested, Case-Control Study

BACKGROUND

This study aimed to investigate the association between the triglyceride-glucose (TyG) index and diabetic retinopathy (DR) in Chinese patients with type 2 diabetes.

METHODS

In this nested case-control study, all diabetic participants were registered hospitalizations during 2012-2018, including 596 with DR as cases and three matching controls per case. DR was assessed using Early Treatment Diabetic Retinopathy Study criteria. The TyG index was calculated: Ln (fasting blood glucose [mg/dL] × fasting triglycerides [mg/dL] ÷ 2). Multivariate logistic regression, a receiver-operating characteristic (ROC) curve, linear regression models, and mediation analysis were used to explore associations.

RESULTS

The TyG index was lower in DR and decreased as its severity advanced among 2,112 subjects (P=0.005). After confounders (sex, duration of diabetes, use of antidiabetic agents, heart rate, systolic blood pressure, pulse pressure, height, weight, body-mass index, and glycated hemoglobin) had been accounted for, there were significant associations between the TyG index and any-severity DR (OR 0.83, 95% CI 0.73-0.95; P=0.006), as well as vision-threatening DR (VTDR; OR 0.53, 95% CI 0.36-0.76; P=0.001). ROC analysis indicated that the TyG index showed significant discriminatory ability in any-severity DR (area under curve [AUC] 0.534, P=0.015) and VTDR (AUC 0.624, P=0.001).

CONCLUSION

The TyG index was associated with the presence and severity of DR. Our findings suggest that the TyG index may become a useful biomarker in evaluating and following the presence of DR and VTDR.

Metabolic health is a determining factor for incident colorectal cancer in the obese population: A nationwide population-based cohort study

Background

The association of the risk of colorectal cancer (CRC) with obesity or obesity‐induced metabolic disturbances remains controversial. We assessed the association of metabolic health status with incident CRC among subjects with obesity.

Methods

This study included 319,397 subjects from the Korean National Health Insurance Service‐National Health Screening Cohort. Transitions in metabolic health status and obesity were examined during 2009–2010 and 2011–2012. We categorized subjects with obesity into four separate groups according to their dynamic metabolic health status: metabolically healthy obesity (MHO), MHO to metabolically unhealthy obesity (MUO), MUO to MHO, and stable MUO. Subjects were followed up from 2009 to 2015 for incident CRC.

Results

The stable MHO group showed no increased risk of incident CRC (hazard ratio [HR], 0.97; 95% confidence interval [CI], 0.83–1.14). However, the MHO to MUO group had a higher risk of incident CRC than the stable metabolically healthy nonobese (MHNO) group (HR, 1.34; 95% CI, 1.15–1.57). Among patients with MUO at baseline, those in the subgroup who transitioned to MHO group were not at increased risk of CRC (HR, 1.06; 95% CI, 0.91–1.25), whereas those who remained in the stable MUO group had a higher risk of incident CRC than those in the stable MHNO group (HR, 1.29; 95% CI, 1.19–1.41).

Conclusions

The transition of metabolic health was a determining factor for CRC among subjects with obesity. Hence, maintenance or recovery of metabolic health should be addressed to prevent CRC in individuals with obesity.

Exposure-weighted scoring for metabolic syndrome and the risk of myocardial infarction and stroke: a nationwide population-based study

BACKGROUND

Metabolic syndrome (MetS) status changes over time, but few studies have investigated the relationship between the extent or duration of exposure to MetS and the risk of cardiovascular disease (CVD). We investigated the cumulative effects of MetS and its components on the risk of myocardial infarction (MI) and stroke.

METHODS

From the Korean National Health Insurance database, 2,644,851 people who received annual health examinations from 2010 to 2013 were recruited. Exposure-weighted scores for MetS during this 4-year period were calculated in two ways: cumulative number of MetS diagnoses (MetS exposure score, range: 0-4) and the composite of its five components (MetS component exposure score, range: 0-20). The multivariable Cox proportional-hazards model was used to assess CVD risk according to the exposure-weighted scores for MetS.

RESULTS

MetS was identified at least once in 37.6% and persistent MetS in 8.2% of subjects. During the follow-up (median, 4.4 years), 10,522 cases of MI (0.4%) and 10,524 cases of stoke (0.4%) occurred. The risk of MI and stroke increased gradually with increasing exposure scores of MetS and its components (each P for trend < 0.0001). The hazard ratio [(HR) (95% CI)] of MI and stroke were 5.27 (4.20-6.62) and 3.90 (3.09-4.93), respectively, in those with a score of 20 compared with those with a MetS component exposure score of 0. People fulfilling only two MetS components out of 20 already had 22% increased risk of MI, and those with three MetS components had 24% increased risk of stroke. These associations were consistent in the subgroup and sensitivity analyses.

CONCLUSIONS

A dose-response relationship between the cumulative exposure to metabolic disturbances and incident MI or stroke was evident. Even minimal exposure to MetS components was sufficient to increase the risk of CVD significantly, highlighting the importance of intensive risk management for the prevention of CVD.

Predictive performance of traditional and novel lipid combined anthropometric indices to identify prediabetes

BACKGROUND AND AIMS

Diabetes mellitus is one of the critical public health challenges in the Indian healthcare scenario. Novel anthropometric indices are promising surrogate markers to detect prediabetes compared to the traditional anthropometric indices that only reflect gross obesity. Thus, the authors aim to analyse the potential of three novel lipid combined anthropometric indices in predicting prediabetes in the Asian Indian population.

METHODS

We conducted an age and gender-matched case-control study to identify the predictors of prediabetes. Prediabetes was diagnosed as per the American Diabetes Association (ADA) guidelines 2010. The traditional anthropometric measurements including waist circumference (WC), waist to hip ratio (WHR) and body mass index (BMI) were executed using standardised methods. Fasting lipid profile was obtained and using standardised formulas, the novel lipid combined anthropometric indices such as lipid accumulation product (LAP), visceral adiposity index (VAI) and triglyceride glucose index (TyG index) were derived. TyG related indices such as triglyceride glucose-waist circumference (TyG-WC) and triglyceride glucose-body mass index (TyG-BMI) were also calculated.

RESULTS

The novel lipid combined anthropometric indices LAP, VAI, TyG index, TyG-WC and TyG-BMI were significantly higher in subjects with prediabetes of both the genders (p < 0.05). During receiver operating characteristic (ROC) curve evaluation, TyG index (AUC = 0.802) was the superior predictive measure in males, while in females, TyG-WC (AUC = 0.767) was the best among all the markers.

CONCLUSION

TyG index and TyG-WC seem to be a superior indicator of prediabetes in the Asian Indian population in comparison with other anthropometric indices to screen prediabetes.

Impact of Transition in Metabolic Health and Obesity on the Incident Chronic Kidney Disease: A Nationwide Cohort Study

CONTEXT

Metabolically healthy obesity (MHO) is a dynamic condition.

OBJECTIVE

To evaluate the risk of chronic kidney disease (CKD) among people with MHO according to its longitudinal change.

DESIGN

Observational study.

SETTING

A nationwide population-based cohort.

PARTICIPANTS

A total of 514 866 people from the Korean National Health Insurance Service-National Sample Cohort.

INTERVENTION

The initial presence and changes of obesity (using body mass index [BMI] and waist circumference [WC]) and metabolic health status.

MAIN OUTCOME MEASURE

Incident CKD from 2011 to 2015.

RESULTS

Of the people classified as MHO at baseline (BMI criteria), 47.6% remained as MHO in 2011 and 2012, whereas 12.1%, 5.5%, and 34.8% were classified as metabolically healthy, non-obese (MHNO), metabolically unhealthy, non-obese, and metabolically unhealthy, obese, respectively. The risk of incident CKD in the baseline MHO group was higher than that in the MHNO group (hazard ratio, 1.23; 95% confidence interval, 1.12-1.36). However, when transition was taken into account, people who converted to MHNO were not at increased risk (hazard ratio, 0.98; 95% confidence interval, 0.72-1.32), whereas the stable MHO group and the groups that evolved to metabolically unhealthy status had a higher risk of incident CKD than the stable MHNO group. When the risk was analyzed using WC criteria, it showed a similar pattern to BMI criteria except for the stable MHO group.

CONCLUSIONS

MHO was a dynamic condition, and people with MHO constituted a heterogeneous group. Although the MHO phenotype was generally associated with incident CKD, maintenance of metabolic health and weight reduction might alleviate the risk of CKD.

Metabolic Unhealthiness Increases the Likelihood of Having Metabolic Syndrome Components in Normoweight Young Adults

Findings on risk detection for having metabolic syndrome (MetS) components, each of which may individually increase the risk of disease and mortality, are limited in young adults. In this study, we aimed to calculate the likelihood of having ≥1 MetS component in normoweight young adults using two different metabolic health criteria. We recruited 1182 normoweight young adults from the Taiwan Survey on the Prevalence of Hypertension, Hyperglycemia, and Hyperlipidemia and the National Health Interview Survey (aged 16–45 years, 39% male, body mass index = 18.5–22.99, all without MetS) and followed them for 5 years. Metabolic health criteria were derived from the Harmonized criteria (unhealthy if showing abnormality in one or two MetS components) and the triglyceride-glucose index (TyG-i; unhealthy if TyG-i was in the >75th percentile). Odds ratio (OR) and 95% confidence interval (CI) estimations for having ≥1 MetS component and for having each MetS component in 5 years were assessed using multivariable-adjusted logistic regression. We observed a significantly increased likelihood of the presence of ≥1 MetS component in the unhealthy group by using the Harmonized criteria and TyG-i (adjusted OR (aOR); 95%CI: 2.64; 2.02–3.45 and 2.1; 1.57–2.82, respectively). The areas under the receiver-operating characteristics curves were 0.679 and 0.652 for the final models using Harmonized and TyG-i criteria, respectively. These findings support the recommendation of treating any metabolic component abnormality, even in young adults without a MetS diagnosis.

Metabolic health in normal-weight and obese individuals

Cardiovascular complications are commonly associated with obesity. However, a subgroup of obese individuals may not be at an increased risk for cardiovascular complications; these individuals are said to have metabolically healthy obesity (MHO). In contrast, metabolically unhealthy individuals are at high risk of cardiovascular disease (CVD), irrespective of BMI; thus, this group can include individuals within the normal weight category (BMI 18.5-24.9 kg/m²). This review provides a summary of prospective studies on MHO and metabolically unhealthy normal-weight (MUHNW) phenotypes. Notably, there is ongoing dispute surrounding the concept of MHO, including the lack of a uniform definition and the potentially transient nature of metabolic health status. This review highlights the relevance of alternative measures of body fatness, specifically measures of fat distribution, for determining MHO and MUHNW. It also highlights alternative approaches of risk stratification, which account for the continuum of risk in relation to CVD, which is observable for most risk factors. Moreover, studies evaluating the transition from metabolically healthy to unhealthy phenotypes and potential determinants for such conversions are discussed. Finally, the review proposes several strategies for the use of epidemiological research to further inform the current debate on metabolic health and its determination across different stages of body fatness.

Triglyceride glucose index for predicting cardiovascular outcomes in patients with coronary artery disease

Background

Triglyceride glucose (TyG) index is a novel marker for metabolic disorders and recently it has been reported to be associated with cardiovascular disease (CVD) risk in apparently healthy individuals. However, the prognostic value of TyG index in patients with stable coronary artery disease (CAD) is not determined.

Methods

We conducted a nested case-control study among 3,745 patients with stable CAD. Patients were followed up for 11,235 person-years. The cardiovascular events (CVEs) were defined as all-cause death, non-fatal myocardial infarction (MI), stroke and post-discharge revascularization [percutaneous coronary intervention (PCI) coronary artery bypass grafting (CABG)]. In total, 290 (7.7%) patients with CVEs and 1,450 controls were matched according to age, gender, previous history of PCI or CABG and the duration of follow-up. TyG index was calculated as formula: ln[fasting triglycerides (mg/dL) × fasting plasma glucose (mg/dL)/2].

Results

Multivariable Cox proportional hazards models revealed that TyG index was positively associated with CVEs risk (hazard ratio: 1.364, 95% confidence interval: 1.100-1.691, P=0.005). The Kaplan-Meier analysis indicated that patients within the highest quartile of TyG index presented the lowest event-free survival (P=0.029). Moreover, a 1-standard deviation (SD) increment in TyG index was associated with 23.2% [hazard ratio (HR): 1.232, 95% confidence interval (95% CI): 1.084-1.401] higher risk of CVEs, which was superior to other triglyceride or glycemic related markers.

Conclusions

The present study, firstly, showed that TyG index was positively associated with future CVEs, suggesting that TyG may be a useful marker for predicting clinical outcomes in patients with CAD.

Transition from metabolic healthy to unhealthy phenotypes and association with cardiovascular disease risk across BMI categories in 90 257 women (the Nurses' Health Study): 30 year follow-up from a prospective cohort study

BACKGROUND

Cardiovascular disease risk among individuals across different categories of BMI might depend on their metabolic health. It remains unclear to what extent metabolic health status changes over time and whether this affects cardiovascular disease risk. In this study, we aimed to examine the association between metabolic health and its change over time and cardiovascular disease risk across BMI categories.

METHODS

Between June and December, 1976, 121 701 female nurses were recruited to the Nurses' Health Study (NHS) of whom 103 298 returned a questionnaire in 1980 used as baseline in this study. After excluding women with a history of cardiovascular disease or cancer, with missing body weight and with underweight. 90 257 women were followed-up from 1980 to 2010 for incident cardiovascular disease. Participants were cross-classified by BMI categories, metabolic health (defined by absence of diabetes, hypertension and hypercholesterolaemia), and change in metabolic health status during follow-up. The cardiovascular component of the NHS is registered with ClinicalTrials.gov, number NCT00005152.

FINDINGS

During 2 127  391 person-years of follow-up with a median follow-up of 24 years, we documented 6306 cases of cardiovascular disease including 3304 myocardial infarction cases and 3080 strokes. Cardiovascular disease risk of women with metabolically healthy obesity was increased compared with women with metabolically healthy normal weight (HR 1·39, 95% CI 1·15-1·68), but risk was considerably higher in women with metabolically unhealthy normal weight (2·43, 2·19-2·68), overweight (2·61, 2·36-2·89) and obesity (3·15, 2·83-3·50). The majority of metabolically healthy women converted to unhealthy phenotypes (2555 [84%] of 3027 women with obesity, 22 215 [68%] of 32 882 women with normal-weight after 20 years). Women who maintained metabolically healthy obesity during follow-up were still at a higher cardiovascular disease risk compared with women with stable healthy normal weight (HR 1·57, 1·03-2·38), yet this risk was lower than for initially metabolically healthy women who converted to an unhealthy phenotype (normal-weight 1·90, 1·66-2·17 vs obesity 2·74, 2·30-3·27). Particularly incident diabetes and hypertension increased the risk among women with initial metabolic health.

INTERPRETATION

Even when metabolic health is maintained during long periods of time, obesity remains a risk factor for cardiovascular disease. However, risks are highest for metabolically unhealthy women across all BMI categories. A large proportion of metabolically healthy women converted to an unhealthy phenotype over time across all BMI categories, which is associated with an increased cardiovascular disease risk.

FUNDING

US National Institutes of Health, German Federal Ministry of Education and Research.

Serum Betatrophin Concentrations and the Risk of Incident Diabetes: A Nested Case-Control Study from Chungju Metabolic Disease Cohort

BACKGROUND

Betatrophin is a newly identified hormone derived from the liver and adipose tissue, which has been suggested to regulate glucose and lipid metabolism. Circulating levels of betatrophin are altered in various metabolic diseases, although the results are inconsistent. We aimed to examine whether betatrophin is a useful biomarker in predicting the development of diabetes.

METHODS

A nested case-control study was performed using a prospective Chungju Metabolic disease Cohort Study. During a 4-year follow-up period, we analyzed 167 individuals who converted to diabetes and 167 non-converters, who were matched by age, sex, and body mass index. Serum betatrophin levels were measured by an ELISA (enzyme-linked immunosorbent assay).

RESULTS

Baseline serum betatrophin levels were significantly higher in the converter group compared to the non-converter group (1,315±598 pg/mL vs. 1,072±446 pg/mL, P<0.001). After adjusting for age, sex, body mass index, fasting plasma glucose, systolic blood pressure, total cholesterol, and family history of diabetes, the risk of developing diabetes showed a stepwise increase across the betatrophin quartile groups. Subjects in the highest baseline quartile of betatrophin levels had more than a threefold higher risk of incident diabetes than the subjects in the lowest quartile (relative risk, 3.275; 95% confidence interval, 1.574 to 6.814; P=0.010). However, no significant relationships were observed between serum betatrophin levels and indices of insulin resistance or β-cell function.

CONCLUSION

Circulating levels of betatrophin could be a potential biomarker for predicting new-onset diabetes. Further studies are needed to understand the underlying mechanism of this association.

Triglycerides/Glucose and Triglyceride/High-Density Lipoprotein Cholesterol Indices in Normal and Preeclamptic Pregnancies: A Longitudinal Study

Metabolic changes have been correlated with adverse pregnancy outcomes. The aim of the present study is to determine the TyG and TG/HDL-c indices in a cohort of healthy pregnant (n = 142), preeclamptic (n = 18), and healthy nonpregnant women (n = 56). Preeclamptic women were selected from the same cohort. Pregnant women were followed during three periods of pregnancy and postpartum. The results showed a significant increase in the values of TyG and TG/HDL-c (p < 0.01) as pregnancy progresses, without significant differences between healthy and preeclamptic women. TyG and TG/HDL-c indices are significantly low in nonpregnant and three months' postpartum women when compared with each gestational period studied. TyG and TG/HDL-c indices are positively correlated with HOMA-IR in the early and middle pregnancy (p < 0.05). Multiple linear regression using the TyG and TG/HDL-c indices as dependent variables showed that TyG index was significantly associated with HOMA-IR, gestational age, HDL-c, TC, LDL, fasting insulin, and mean BP (p < 0.001); meanwhile, TG/HDL-c index was only associated with HOMA-IR (p < 0.0242) and gestational age (p < 0.001). In conclusion, the TyG and TG/HDL-c indices could be useful in monitoring insulin resistance during pregnancy.

Assessment of disturbed glucose metabolism and surrogate measures of insulin sensitivity in obese children and adolescents

BACKGROUND

With the rising prevalence of obesity and type 2 diabetes (T2D) in obese children, it is becoming imperative to detect disturbed glucose metabolism as early as possible in order to prevent T2D development.

SUBJECTS/METHODS

Cross-sectional study of 92 obese children (median age 11.7 years, 51% female) and 7 lean children (median age 11.4 years, 57% female) who underwent an oral glucose tolerance test (OGTT) in a tertiary pediatric care center. Glucose tolerance was assessed and different indices for β-cell function, insulin sensitivity and insulin secretion were calculated.

RESULTS

Nineteen obese children were identified with prediabetes (PD, 12 impaired glucose tolerance, 4 increased fasting glucose and 3 combined). Compared with the 73 obese children with normal glucose tolerance (nGT), subjects with PD had higher insulin resistance, but lower insulin sensitivity and β-cell function, although their glycated hemoglobin (HbA1c) levels were comparable. The Whole Body Insulin Sensitivity Index (WBISI) and β-cell function by Insulin Secretion-Sensitivity Index-2 (ISSI-2) strongly correlated with the OGTT glucose area under the curve 0-120 min (r = 0.392, p < 0.0002; r = 0.547, p < 0.0001, respectively). When testing the relation between early insulin response during OGTT by insulinogenic index and insulin sensitivity assessed by WBISI, a hyperbolic relationship between insulin secretion and insulin sensitivity was found. The calculated disposition index was lower in subjects with PD vs. nGT (median 459 vs. 792, p = 0.004). We identified the OGTT 30-min/120-min insulin ratio as a simple marker, which is significantly lower in obese children with vs. without PD (median 0.87 vs. 1.29, p = 0.021) and which has a better sensitivity and specificity for detecting PD than HbA1c among obese children.

CONCLUSIONS

Children with identified PD had changes of several markers for β-cell function, insulin sensitivity and resistance before changes in HbA1c occurred. The lower disposition index indicates that these children have already inadequate β-cell compensation for the degree of insulin resistance.

Risk of diabetes according to the metabolic health status and degree of obesity

AIM

To determine the progression rates from metabolically healthy or unhealthy normal weight, overweight and obese phenotype to type 2 diabetes (T2D) in a non-diabetic high risk population in Isfahan, Iran.

METHODS

T2D incidence during a mean (SD) follow-up of 10.1 (2.3) years was examined among 1,982 non-diabetic first-degree relatives (FDR) of patients with T2D 30-70 years old. Participants were divided into 6 groups based on body mass index and metabolic syndrome component, except waist circumference, at baseline: metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOW), metabolically healthy obese (MHO), metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOW) and metabolically unhealthy obese (MUO).

RESULTS

The MHO, MUOW, and MUO individuals at baseline were associated with incidence of T2D, independently of age and gender. MHO were 3 times (OR 2.96; 95% CI 1.07, 8.24) and MUOW were 2.75 times (95% CI 1.17, 6.45) more likely to develop T2D than those with MHNW. There was excess risk in MUO than MHO (OR 3.86; 95% CI 1.64, 9.11).

CONCLUSIONS

Obesity was a risk factor for T2D, even in the absence of any metabolic abnormalities. Metabolic abnormalities were a stronger predictor of incident T2D than obesity.

The prevalence, metabolic risk and effects of lifestyle intervention for metabolically healthy obesity: a systematic review and meta-analysis: A PRISMA-compliant article

BACKGROUND

We conducted a systematic review and meta-analysis to firstly obtain a reliable estimation of the prevalence of metabolically healthy obese (MHO) individuals in obesity, then assessed the risk of developing metabolic abnormalities (MA) among MHO individuals. At last, we evaluated the effects of traditional lifestyle interventions on metabolic level for MHO subjects.

METHODS

A systematic review and meta-analysis (PRISMA) guideline were conducted, and original studies were searched up to December 31, 2016. The prevalence of MHO in obesity from each study was pooled using random effects models. The relative risks (RRs) were pooled to determine the risk of developing MA for MHO compared with metabolically healthy normal-weight (MHNW) subjects. For the meta-analysis of intervention studies, the mean difference and standardized mean differences were both estimated for each metabolic parameter within each study, and then pooled using a random-effects model.

RESULTS

Overall, 40 population-based studies reported the prevalence of MHO in obesity, 12 cohort studies and 7 intervention studies were included in the meta-analysis. About 35.0% obese individuals were metabolically healthy in the obese subjects. There were dramatic differences in the prevalence among different areas. However, 0.49 (95% confidence intervals [CI]: 0.38 to 0.60) of the MHO individuals would develop one or more MA within 10 years. Compared with MHNW subjects, the MHO subjects presented higher risk of incident MA (pooled RR = 1.80, 95%CI: 1.53-2.11). Following intervention, there was certain and significant improvement of metabolic state for metabolically abnormal obesity (MAO) subjects. Only diastolic blood pressure had reduced for MHO individuals after intervention.

CONCLUSIONS

Almost one-third of the obese individuals are in metabolic health. However, they are still at higher risk of advancing to unhealthy state. Therefore, it is still needed to advise MHO individuals to maintain or adopt a healthy lifestyle, so as to counterbalance the adverse effects of obesity.

A Novel Index Using Soluble CD36 Is Associated with the Prevalence of Type 2 Diabetes Mellitus: Comparison Study with Triglyceride-Glucose Index

BACKGROUND

Plasma soluble cluster determinant 36 (sCD36) level is closely related with insulin resistance and atherosclerosis, but little is known whether it could be a surrogate for estimating risk of developing diabetes or not. To address this, we evaluated association between sCD36 index, the product of sCD36 and fasting plasma glucose (FPG), and the prevalence of type 2 diabetes mellitus (T2DM), and then compared with triglyceride-glucose (TyG) index which has been suggested simple index for insulin resistance.

METHODS

This was cross-sectional study, and participants were classified as normal glucose tolerance (NGT), prediabetes, and T2DM according to glucose tolerance. The formula of TyG index was 'ln [FPG (mg/dL)×triglyceride (mg/dL)/2],' and the sCD36 index was 'ln [sCD36 (pg/mL)×FPG (mg/dL)/2].'

RESULTS

One hundred and fifty-five subjects (mean age, 55.2 years) were enrolled, and patients with T2DM were 75. Both indexes were significantly increased in prediabetes and T2DM rather than NGT, and sCD36 index was positively correlated with both glycosylated hemoglobin and homeostasis model assessment of insulin resistance (r=0.767 and r=0.453, respectively; P<0.05) and negatively with homeostasis model assessment estimate of β-cell function (r=-0.317). The odds ratio (OR) of sCD36 index for T2DM was 4.39 (95% confidential interval, 1.51 to 12.77) after adjusting age, gender, blood pressure, smoking, alcohol, non-high density lipoprotein cholesterol and high-sensitivity C-reactive protein. However, OR of TyG index did not remained significance after adjustment.

CONCLUSION

sCD36 index has an independent association with the risk of T2DM, and showed better correlation than TyG index. These results suggest sCD36 index might be useful surrogate marker for the risk of diabetes.

Optimal cutoff for the evaluation of insulin resistance through triglyceride-glucose index: A cross-sectional study in a Venezuelan population

Background: Insulin resistance (IR) evaluation is a fundamental goal in clinical and epidemiological research. However, the most widely used methods are difficult to apply to populations with low incomes. The triglyceride-glucose index (TGI) emerges as an alternative to use in daily clinical practice. Therefore the objective of this study was to determine an optimal cutoff point for the TGI in an adult population from Maracaibo, Venezuela.

Methods: This is a sub-study of Maracaibo City Metabolic Syndrome Prevalence Study, a descriptive, cross-sectional study with random and multi-stage sampling. For this analysis, 2004 individuals of both genders ≥18 years old with basal insulin determination and triglycerides < 500 mg/dl were evaluated.. A reference population was selected according to clinical and metabolic criteria to plot ROC Curves specific for gender and age groups to determine the optimal cutoff point according to sensitivity and specificity.The TGI was calculated according to the equation: ln [Fasting triglyceride (mg / dl) x Fasting glucose (mg / dl)] / 2.

Results: The TGI in the general population was 4.6±0.3 (male: 4.66±0.34 vs. female: 4.56±0.33, p=8.93x10 ^-10). The optimal cutoff point was 4.49, with a sensitivity of 82.6% and specificity of 82.1% (AUC=0.889, 95% CI: 0.854-0.924). There were no significant differences in the predictive capacity of the index when evaluated according to gender and age groups. Those individuals with TGI≥4.5 had higher HOMA2-IR averages than those with TGI <4.5 (2.48 vs 1.74, respectively, p<0.001).

Conclusions: The TGI is a measure of interest to identify IR in the general population. We propose a single cutoff point of 4.5 to classify individuals with IR. Future studies should evaluate the predictive capacity of this index to determine atypical metabolic phenotypes, type 2 diabetes mellitus and even cardiovascular risk in our population.

Optimal cutoff for the evaluation of insulin resistance through triglyceride-glucose index: A cross-sectional study in a Venezuelan population

Background: Insulin resistance (IR) evaluation is a fundamental goal in clinical and epidemiological research. However, the most widely used methods are difficult to apply to populations with low incomes. The triglyceride-glucose index (TGI) emerges as an alternative to use in daily clinical practice. Therefore the objective of this study was to determine an optimal cutoff point for the TGI in an adult population from Maracaibo, Venezuela. Methods: This is a sub-study of Maracaibo City Metabolic Syndrome Prevalence Study, a descriptive, cross-sectional study with random and multi-stage sampling. For this analysis, 2004 individuals of both genders ≥18 years old with basal insulin determination and triglycerides < 500 mg/dl were evaluated.. A reference population was selected according to clinical and metabolic criteria to plot ROC Curves specific for gender and age groups to determine the optimal cutoff point according to sensitivity and specificity.The TGI was calculated according to the equation: ln [Fasting triglyceride (mg / dl) x Fasting glucose (mg / dl)] / 2. Results: The TGI in the general population was 4.6±0.3 (male: 4.66±0.34 vs. female: 4.56±0.33, p=8.93x10 -10). The optimal cutoff point was 4.49, with a sensitivity of 82.6% and specificity of 82.1% (AUC=0.889, 95% CI: 0.854-0.924). There were no significant differences in the predictive capacity of the index when evaluated according to gender and age groups. Those individuals with TGI≥4.5 had higher HOMA2-IR averages than those with TGI <4.5 (2.48 vs 1.74, respectively, p<0.001). Conclusions: The TGI is a measure of interest to identify IR in the general population. We propose a single cutoff point of 4.5 to classify individuals with IR. Future studies should evaluate the predictive capacity of this index to determine atypical metabolic phenotypes, type 2 diabetes mellitus and even cardiovascular risk in our population.

Optimal cutoff for the evaluation of insulin resistance through triglyceride-glucose index: A cross-sectional study in a Venezuelan population

Background: Insulin resistance (IR) evaluation is a fundamental goal in clinical and epidemiological research. However, the most widely used methods are difficult to apply to populations with low incomes. The triglyceride-glucose index (TGI) emerges as an alternative to use in daily clinical practice. Therefore the objective of this study was to determine an optimal cutoff point for the TGI in an adult population from Maracaibo, Venezuela. Methods: This is a sub-study of Maracaibo City Metabolic Syndrome Prevalence Study, a descriptive, cross-sectional study with random and multi-stage sampling. For this analysis, 2004 individuals of both genders ≥18 years old with basal insulin determination and triglycerides < 500 mg/dl were evaluated.. A reference population was selected according to clinical and metabolic criteria to plot ROC Curves specific for gender and age groups to determine the optimal cutoff point according to sensitivity and specificity.The TGI was calculated according to the equation: ln [Fasting triglyceride (mg / dl) x Fasting glucose (mg / dl)] / 2. Results: The TGI in the general population was 4.6±0.3 (male: 4.66±0.34 vs. female: 4.56±0.33, p=8.93x10 -10). The optimal cutoff point was 4.49, with a sensitivity of 82.6% and specificity of 82.1% (AUC=0.889, 95% CI: 0.854-0.924). There were no significant differences in the predictive capacity of the index when evaluated according to gender and age groups. Those individuals with TGI≥4.5 had higher HOMA2-IR averages than those with TGI <4.5 (2.48 vs 1.74, respectively, p<0.001). Conclusions: The TGI is a measure of interest to identify IR in the general population. We propose a single cutoff point of 4.5 to classify individuals with IR. Future studies should evaluate the predictive capacity of this index to determine atypical metabolic phenotypes, type 2 diabetes mellitus and even cardiovascular risk in our population.

Potential Association of Triglyceride Glucose Index with Cardiac Autonomic Neuropathy in Type 2 Diabetes Mellitus Patients

Cardiac autonomic neuropathy (CAN) is a common and most neglected complication of diabetes, estimated to be roughly 8% in recently diagnosed patients and greater than 50% in patients with chronic disease history. The insulin resistance (IR) itself is bidirectionally associated with increased risk of type 2 diabetes mellitus (T2DM) and CAN is a predisposing factor. The primary objective of the present study was aimed to find a correlation of triglyceride glucose index (TyG index) in CAN patients along with the prevalence of CAN in T2DM patients as a secondary objective. This prevalence study was conducted on 202 patients visiting the diabetic clinic of Hamdard Institute of Medical Sciences and Research, Jamia Hamdard (HIMSR) teaching hospital in New Delhi, India who fulfilled the inclusion criteria. The Ewings autonomic function test was used for diagnosis of CAN. TyG index was calculated for patients based on fasting levels of glucose and triglyceride. The CAN was diagnosed in 62 participants out of 202 T2DM patients (overall prevalence 30.7%). The mean ± standard deviation (SD) for TyG index was 10.3 ± 0.2 and 9.5 ± 0.2 in CAN positive, T2DM patients, respectively. The difference of TyG index, in CAN positive and T2DM patients, was highly significant (P < 0.001). Further correlation analysis was performed to find an association of TyG index, duration, and age with patient groups. TyG index showed a positive correlation with heart rate during deep breathing (HRD), heart rate variation during standing (HRS), blood pressure (BP) response to handgrip and BP response to standing. Our finding highlights the TyG index, low-cost IR index, might be useful as an alternative tool for the early screening of patients at a high risk of diabetic neuropathy.

Cumulative increased risk of incident type 2 diabetes mellitus with increasing triglyceride glucose index in normal-weight people: The Rural Chinese Cohort Study

Background

Risk of type 2 diabetes mellitus (T2DM) is increased in metabolically obese but normal-weight people. However, we have limited knowledge of how to prevent T2DM in normal-weight people. We aimed to evaluate the association between triglyceride glucose (TyG) index and incident T2DM among normal-weight people in rural China.

Methods

We included data from 5706 people with normal body mass index (BMI) (18.5–23.9 kg/m²) without baseline T2DM in a rural Chinese cohort followed for a median of 6.0 years. A Cox proportional-hazard model was used to assess the risk of incident T2DM by quartiles of TyG index and difference in TyG index between follow-up and baseline (TyG-D), estimating hazard ratios (HRs) and 95% confidence intervals (CIs). A generalized additive plot was used to show the nonparametric smoothed exposure–response association between risk of T2DM and TyG index as a continuous variable. TyG was calculated as ln [fasting triglyceride level (mg/dl) × fasting plasma glucose level (mg/dl)/2].

Results

Risk of incident T2DM was increased with quartiles 2, 3 and 4 versus quartile 1 of TyG index (adjusted HR [aHR] 2.48 [95% CI 1.20–5.11], 3.77 [1.83–7.79], and 5.30 [2.21–12.71], P_trend < 0.001 across quartiles of TyG index). Risk of incident T2DM was increased with quartile 4 versus quartile 1 of TyG-D (aHR 3.91 [2.22–6.87]). The results were consistent when analyses were restricted to participants without baseline metabolic syndrome and impaired fasting glucose level. The generalized additive plot showed cumulative increased risk of T2DM with increasing TyG index.

Conclusions

Risk of incident T2DM is increased with increasing TyG index among rural Chinese people, so the index might be an important indicator for identifying people at high risk of T2DM.

Are all metabolically healthy individuals with obesity at the same risk of diabetes onset?

OBJECTIVE

To examine the risk of diabetes and the development of an unhealthy status according to metabolic health. To assess the effect of changes in metabolic health among participants with metabolically healthy obesity (MHO) on the risk of diabetes.

METHODS

A total of 4,340 subjects were included. Unhealthy metabolic status was defined as having three or more risk factors of the Adult Treatment Panel-III criteria. A Cox proportional-hazard analysis was conducted to estimate the hazard ratio (HR) of developing diabetes across the change in the metabolic status of subjects with MHO.

RESULTS

After 40,622 person-years of follow-up, the risk of becoming unhealthy was 1.53 times higher for participants with MHO, compared with lean or overweight healthy subjects. A greater risk of diabetes was found in MHO, but it was attributable to those who progressed to an unhealthier status over time: HR of 4.78 (95% CI: 3.38-6.78). The combination of being metabolically unhealthy and obesity heightened the risk of diabetes: HR of 10.09 (95% CI: 4.82-21.55).

CONCLUSIONS

The increased risk of diabetes in MHO is attributed to the progression to an unhealthier state. "Healthy obesity" is not a permanent situation but a transitory state.

Predictive Value of Triglyceride Glucose Index for the Risk of Incident Diabetes: A 4-Year Retrospective Longitudinal Study

The Triglyceride Glucose Index (TyG index) is considered a surrogate marker of insulin resistance. The aim of this study is to investigate whether the TyG index has a predictive role in identifying individuals with a high risk of incident diabetes and to compare it with other indicators of metabolic health. A total 2900 non-diabetic adults who attended five consecutive annual health check-ups at Kangbuk Samsung Hospital was divided into four subgroups using three methods: (1) baseline TyG index; (2) obesity status (body mass index ≥25 kg/m2) and cutoff value of TyG index; (3) obesity status and metabolic health, defined as having fewer than two of the five components of high blood pressure, fasting blood glucose, triglyceride, low high-density lipoprotein cholesterol, and highest decile of homeostasis model assessment-insulin resistance. The development of diabetes was assessed annually using self-questionnaire, fasting glucose, and glycated hemoglobin. We compared the risk of incident diabetes using multivariate Cox analysis. During 11623 person-years there were 101 case of incident diabetes. Subjects with high TyG index had a high risk of diabetes. For TyG index quartiles, hazard ratios (HRs) of quartiles 3 and 4 were 4.06 (p = 0.033) and 5.65 (p = 0.006) respectively. When the subjects were divided by obesity status and cutoff value of TyG index of 8.8, the subgroups with TyG index ≥ 8.8 regardless of obesity had a significantly high risk for diabetes (HR 2.40 [p = 0.024] and 2.25 [p = 0.048]). For obesity status and metabolic health, the two metabolically unhealthy subgroups regardless of obesity had a significantly high risk for diabetes (HRs 2.54 [p = 0.024] and 2.73 [p = 0.021]). In conclusion, the TyG index measured at a single time point may be an indicator of the risk for incident diabetes. The predictive value of the TyG index was comparable to that of metabolic health.

Obesity, metabolic health, and mortality in adults: a nationwide population-based study in Korea

BMI, metabolic health status, and their interactions should be considered for estimating mortality risk; however, the data are controversial and unknown in Asians. We aimed to investigate this issue in Korean population. Total 323175 adults were followed-up for 96 (60–120) (median [5–95%]) months in a nationwide population-based cohort study. Participants were classified as “obese” (O) or “non-obese” (NO) using a BMI cut-off of 25 kg/m². People who developed ≥1 metabolic disease component (hypertension, diabetes, dyslipidaemia) in the index year were considered “metabolically unhealthy” (MU), while those with none were considered “metabolically healthy” (MH). The MUNO group had a significantly higher risk of all-cause (hazard ratio, 1.28 [95% CI, 1.21–1.35]) and cardiovascular (1.88 [1.63–2.16]) mortality, whereas the MHO group had a lower mortality risk (all-cause: 0.81 [0.74–0.88]), cardiovascular: 0.73 [0.57–0.95]), compared to the MHNO group. A similar pattern was noted for cancer and other-cause mortality. Metabolically unhealthy status was associated with higher risk of all-cause and cardiovascular mortality regardless of BMI levels, and there was a dose-response relationship between the number of incident metabolic diseases and mortality risk. In conclusion, poor metabolic health status contributed more to mortality than high BMI did, in Korean adults.

TyG Index Change Is More Determinant for Forecasting Type 2 Diabetes Onset Than Weight Gain

The risk of type 2 diabetes associated with obesity appears to be influenced by other metabolic abnormalities, and there is controversy about the harmless condition of the metabolically healthy obese (MHO) state. The aim of this study is to assess the risk of diabetes and the impact of changes in weight and in triglyceride-glucose index (TyG index), according to the metabolic health and obesity states.We analyzed prospective data of the Vascular Metabolic CUN cohort, a population-based study among a White European population (mean follow-up, 8.9 years). Incident diabetes was assessed in 1923 women and 3016 men with a mean age at baseline of 55.33 ± 13.68 and 53.78 ± 12.98 years old.A Cox proportional-hazard analysis was conducted to estimate the hazard ratio (HR) of diabetes on metabolically healthy nonobese (MHNO), metabolically healthy obese, metabolically unhealthy nonobese (MUNO), and metabolically unhealthy obese (MUO). A continuous standardized variable (z-score) was derived to compute the HR for diabetes per 1-SD increment in the body mass index (BMI) and the TyG index.MHO, MUNO, and MUO status were associated with the development of diabetes, HR of 2.26 (95% CI: 1.25-4.07), 3.04 (95% CI: 1.69-5.47), and 4.04 (95% CI: 2.14-7.63), respectively. MUNO individuals had 1.82 greater risk of diabetes compared to MHO subjects (95% CI: 1.04-3.22). The HRs for incident diabetes per 1-SD increment in BMI and TyG indexes were 1.23 (95% CI: 1.04-1.44) and 1.54 (95% CI: 1.40-1.68). The increase in BMI did not raise the risk of developing diabetes among metabolically unhealthy subjects, whereas increasing the TyG index significantly affect the risk in all metabolic health categories.Metabolic health is more important determinant for diabetes onset than weight gain. The increase in weight does not raise the risk of developing diabetes among metabolically unhealthy subjects.

Triglyceride-glucose index (TyG index) in comparison with fasting plasma glucose improved diabetes prediction in patients with normal fasting glucose: The Vascular-Metabolic CUN cohort

AIMS

We evaluated the potential role of the triglyceride-glucose index (TyG index) as a predictor of diabetes in a White European cohort, and compared it to fasting plasma glucose (FPG) and triglycerides.

METHODS

4820 patients of the Vascular-Metabolic CUN cohort (VMCUN cohort) were examined and followed up for 8.84years (±4.39). We performed a Cox proportional hazard ratio with repeated-measures analyses to assess the risk of developing type 2 diabetes across quartiles of FPG, triglycerides and the TyG index (ln[fasting triglycerides (mg/dl)×fasting plasma glucose (mg/dl)/2]), and plotted a receiver operating characteristics (ROC) curve for discrimination.

RESULTS

There were 332 incident cases of type 2 diabetes involving 43,197.32person-years of follow-up. We observed a progressively increased risk of diabetes in subjects with TyG index levels of 8.31 or more. Among those with normal fasting glucose at baseline, <100mg/dl, subjects with the TyG index in the fourth quartile were 6.87 times more likely to develop diabetes (95% CI, 2.76-16.85; P for trend<0.001), as compared with the bottom quartile. The areas under the ROC curves (95% CI) were 0.75 (0.70-0.81) for TyG index, 0.66 (0.60-0.72) for FPG and 0.71 (0.65-0.77) for TG, in subjects with normal fasting glucose (p=0.017).

CONCLUSIONS

Our data suggest that the TyG index is useful for the early identification of individuals at risk of type 2 diabetes. The TyG index seems to be a better predictor than FPG or triglycerides of the potential development of type 2 diabetes in normoglycemic patients.

Risk of the Development of Diabetes and Cardiovascular Disease in Metabolically Healthy Obese People: The Korean Genome and Epidemiology Study

The reported effects of a metabolically healthy obese (MHO) phenotype on diabetes and cardiovascular disease (CVD) risk are contradictory. Within the context of a population-based cohort study, we aimed to investigate the long-term risk of an MHO status for the development of diabetes and CVD, and whether consistency of this phenotype or age affected cardiometabolic outcomes. We recruited 7588 subjects without diabetes or CVD, aged 40 to 69 years at baseline examination, from the Korean Genome and Epidemiology Study, and followed-up these subjects for 10 years biennially. Participants were divided into 4 groups based on the body mass index and the presence of metabolic syndrome: metabolically healthy normal weight (MHNW), MHO, metabolically unhealthy normal weight (MUNW), and metabolically unhealthy obese (MUO). We defined persistent phenotypes if subjects maintained the same phenotype at every visit from baseline to their last visit. Incident diabetes and CVD morbidity or mortality were identified during 10 years of follow-up. Compared to MHNW controls, MUNW and MUO groups had increased risk for development of diabetes (hazard ratio [HR] 3.0 [95% CI: 2.5-3.6], and 4.0 [3.4-4.7], respectively) and CVD (HR 1.6 [1.3-2.0], and 1.9 [1.5-2.4], respectively). However, the MHO group showed only a marginal increase in risk for diabetes and CVD (HR 1.2 [0.99-1.6], 1.4 [0.99-1.8], respectively). The impact of MHO on the development of diabetes was more prominent in younger individuals (HR 1.9 [1.2-3.1] vs 1.1 [0.8-1.4], <45 years vs ≥45 years at baseline). Only 15.8% of MHO subjects maintained the MHO phenotype at every visit from baseline to the 5th biennial examination (persistent MHO). In subjects with persistent MHO, the risk for diabetes and CVD was significantly higher than those with persistent MHNW (1.9 [1.2-3.1], 2.1 [1.2-3.7], respectively). MHO phenotype, even if maintained for a long time, was associated with a significantly higher risk for the development of diabetes and CVD in Korean subjects.

The TyG index may predict the development of cardiovascular events

BACKGROUND

Cardiovascular disease (CVD) is the worldwide leading cause of morbidity and mortality. An early risk detection of apparently healthy people before CVD onset has clinical relevance in the prevention of cardiovascular events. We evaluated the association between the product of fasting plasma glucose and triglycerides (TyG index) and CVD.

MATERIAL AND METHODS

A total of 5014 patients of the Vascular Metabolic CUN cohort (VMCUN cohort) were followed up during a median period of 10 years. We used a Cox proportional-hazard ratio with repeated measures to estimate the risk of incidence of CVD across quintiles of the TyG index, calculated as ln[fasting triglycerides (mg/dL) × fasting plasma glucose (mg(dL)/2], and plotted a receiver-operating characteristics (ROC) curve to compare a prediction model fitted on the variables used in the Framingham risk score, a new model containing the Framingham variables with the TyG index, and the risk of coronary heart disease.

RESULTS

A higher level of TyG index was significantly associated with an increased risk of developing CVD independent of confounding factors with a value of 2·32 (95% CI: 1·65-3·26) for those in the highest quintile and 1·52 (95% CI: 1·07-2·16) for those in the fourth quintile. The areas under the curve (AUC) of the ROC plots were 0·708 (0·68-0·73) for the Framingham model and 0·719 (0·70-0·74) for the Framingham + TyG index model (P = 0·014).

CONCLUSIONS

The TyG index, a simple measure reflecting insulin resistance, might be useful to early identify individuals at a high risk of developing a cardiovascular event.