Associations Between the Metabolic Score for Insulin Resistance Index and the Risk of Type 2 Diabetes Mellitus Among Non-Obese Adults: Insights from a Population-Based Cohort Study

Association of Metabolic Score for Visceral Fat (METS-VF) with Gout Risk in Patients with Hypertension and Hyperuricemia: A Multicenter Study Based on the Chinese Population

Background

Gout, a rheumatic disease precipitated by hyperuricemia, has become a global health concern due to its increasing prevalence, especially in China. Hyperuricemia and hypertension are significant risk factors for gout, and their coexistence amplifies this risk. Visceral adipose tissue (VAT) plays a crucial role in cardiometabolic diseases, and the metabolic score for visceral fat (METS-VF) is a non-invasive tool for estimating VAT and predicting cardiometabolic risk.

Methods

We conducted a multicenter cross-sectional study involving 8877 patients with hypertension and hyperuricemia from three Chinese medical centers between March 2021 and September 2024. We calculated the METS-VF and other obesity indices and analyzed their associations with gout risk using logistic regression models. The predictive performance of these indices was evaluated using receiver operating characteristic (ROC) curve analysis and clinical decision curve analysis (DCA).

Results

The METS-VF demonstrated a significant positive association with gout risk, independent of traditional risk factors. Each 1-standard deviation increase in the METS-VF was associated with an 82% higher odds of gout (OR=1.82, 95% CI: 1.62 to 2.03). The METS-VF outperformed other obesity indices in predicting gout risk, with a higher area under the ROC curve (AUC) value. DCA indicated that the METS-VF provided a significant net benefit across a wide range of threshold probabilities for predicting gout risk in both genders.

Conclusion

The METS-VF's robust association with gout risk in our multicenter study, independent of conventional risk factors, positions it as a potent predictor for gout. Further investigation is warranted to clarify the underlying mechanisms and the long-term predictive validity of the METS-VF across diverse populations.

Sex-specific optimal cut-off points for metabolic health indicators to predict incident type 2 diabetes mellitus

BACKGROUND AND AIM

We aimed to determine the optimal cut-off points for metabolic health indicators, including insulin resistance (IR), glucose, insulin, BMI, and waist circumference, in middle-aged nondiabetic people to predict future type 2 diabetes mellitus (T2DM).

METHODS AND RESULTS

The data came from 12,543 Atherosclerosis Risk Communities Study participants, including 5758 men and 6785 women. They did not have diabetes at baseline and were followed for incident T2DM within 3, 6, and 9 years. IR was estimated using four IR metrics: HOMA-IR, METS-IR, TyG index, and TG/HDL-C. We used the Youden index to determine the optimal cut-off values. In females, the cut-off points for glucose to predict incident T2DM ranged from 96 to 102 mg/dL, with Area Under the Curve (AUC) values of 0.64-0.85. In males, the cut-off points ranged from 102 to 106 mg/dL, with AUC values of 0.60-0.83. For HOMA-IR, the cut-off points in females varied from 2.4 to 3.2, with AUC values of 0.69-0.78, while they ranged from 2.8 to 3.2 in males. The optimal cut-off values for METS-IR, TyG index, TG/HDL-C, insulin, BMI, and waist circumference were 40-43, 8.6-8.9, 2.0-3.2, 9-15 μU/mL, 28-29 kg/m2, and 91-97 cm in women, and 44-45, 8.8-8.9, 2.9-3.2, 11-12 μU/mL, 27-29 kg/m2, and 99-103 cm in men.

CONCLUSIONS

The optimal threshold for each predictor's prediction of incident T2DM varied by sex. The eight predictors' order of predictive performance were fasting glucose, HOMA-IR, METS-IR, insulin, BMI, waist circumference, TyG index, and TG/HDL-C.

Association of metabolic score for insulin resistance with incident metabolic syndrome: a cohort study in middle-aged and older adult Chinese population

Background

Recent studies suggest that the metabolic score for insulin resistance (MetS-IR) is an effective indicator of metabolic disorders. However, evidence on the relationship between MetS-IR and metabolic syndrome (MetS) among the Chinese middle-aged and older adult population is limited.

Objective

This cohort study aims to assess the associations of MetS-IR levels with MetS risk and its components.

Methods

Data used in this study from the National Basic Public Health Service Project Management System (2020-2023). Multivariable Cox proportional hazards model and restricted cubic spline (RCS) were employed to evaluate the associations of baseline MetS-IR levels with MetS risk and its components, receiver operating characteristic (ROC) curves were further utilized to assess the efficacy of MetS-IR in predicting the risk of MetS and its component.

Results

Of 1,498 subjects without MetS at baseline, 392 incident MetS cases were observed during a median of 27.70 months of follow-up. The adjusted multivariable Cox regression analysis indicated an elevated 15% risk of developing MetS for 1-SD increment of MetS-IR [hazard ratios (HRs) and 95% confidence intervals: 1.16 (1.13-1.18)]. Compared to the first tertile of MetS-IR, the HRs of the third tertile and second tertile were 6.31 (95% CI 4.55-8.76) and 2.72 (95% CI 1.92-3.85), respectively. Consistent findings were further detected across subgroups. Moreover, nonlinear associations were observed between MetS-IR and the risk of MetS, abdominal obesity, and reduced high-density lipoprotein concentration (HDL-C) (P nonlinear < 0.01), with the cutoff of MetS-IR was 32.89. The area under the curve for MetS-IR in predicting MetS was 0.740 (95% CI 0.713-0.768), which was better than those of other indicators.

Conclusion

Our cohort study indicates a positive nonlinear association between MetS-IR with incident MetS, abdominal obesity, and reduced HDL-C, but positive linear associations of MetS-IR and elevated blood pressure (BP), elevated fasting blood glucose (FBG), elevated triglycerides (TG) in middle-aged and older adult people, more studies are warranted to verify our findings.

Association between metabolic score for insulin resistance and stroke: a nationally representative cross-sectional study from NHANES 2007-2018

Background

Stroke is a significant cerebrovascular disease and remains one of the leading causes of death and disability worldwide. Insulin resistance has been strongly linked to the incidence of stroke. Employing characteristics of metabolic syndrome, the Metabolic Score for Insulin Resistance (METS-IR) accurately measures insulin resistance. Nonetheless, the relationship between METS-IR and stroke risk is not well-established.

Methods

We analyzed data from the National Health and Nutrition Examination Survey (NHANES) covering the years 2007-2018. Participants providing complete METS-IR data and self-reported stroke information were included in the study. We utilized weighted multivariate regression to explore the relationship between METS-IR and stroke, performing subgroup analyses as well.

Results

A total of 14,794 participants were included, with an average METS-IR of 43.44 ± 12.68. The overall prevalence of self-reported stroke was 3.79%, with higher rates observed in upper METS-IR tertiles. An increase of one unit in METS-IR was associated with a 1% increase in stroke risk (OR = 1.01; 95% CI: 1.01-1.02). Interaction tests indicated no significant effects of gender, smoking status, alcohol consumption, hypertension, diabetes, physical activity, or serum cholesterol levels on this relationship. Notably, for participants younger than 60 years, the association was significantly stronger (OR = 1.02; 95% CI: 1.01-1.03), with a marked interaction (p = 0.0061).

Conclusion

Our findings indicate a positive correlation between higher METS-IR and increased stroke risk. Early intervention targeting insulin resistance may be a viable preventive measure against stroke, particularly in individuals under 60 years of age.

The association between the metabolic score for insulin resistance and mortality in patients with cardiovascular disease: a national cohort study

Background

The metabolic score for insulin resistance (METS-IR) is a novel index for evaluating insulin resistance and identifying high-risk cardiovascular disease (CVD) patients. This study aims to assess the prognostic value of METS-IR in predicting mortality risk in CVD patients.

Methods

We analyzed data from 2,515 CVD patients in the National Health and Nutrition Examination Survey (NHANES). Associations between METS-IR and all-cause mortality and cardiovascular mortality were evaluated using multivariable Cox proportional hazards models and restricted cubic splines (RCS). Threshold effects and sensitivity analyses were conducted to ensure robustness.

Results

Over a median follow-up of 91.4 months, 1,090 patients died, including 447 from cardiovascular causes. A U-shaped relationship was identified between lnMETS-IR and all-cause and cardiovascular mortality, with thresholds at 3.70 and 3.67. Below thresholds, an increase of lnMETS-IR was associated with a 75% reduction in the risk of all-cause mortality (HR: 0.25, 95% CI: 0.14-0.46) and a 79% reduction in the risk of cardiovascular mortality (HR: 0.21, 95% CI: 0.07-0.56). While above thresholds, an increase of lnMETS-IR was associated with a 180% increase in the risk of all-cause mortality (HR: 2.80, 95% CI: 1.61-4.88) and a 233% increase in the risk of cardiovascular mortality (HR: 3.33, 95% CI: 1.43-7.75).

Conclusions

This study identified a U-shaped association between lnMETS-IR and mortality among CVD patients, underscoring the potential of METS-IR as a valuable prognostic marker for mortality risk in patients with CVD.

Association between metabolic score for visceral fat and obstructive sleep apnea: a cross-sectional study

Background

Previous studies have established a connection between obesity and obstructive sleep apnea (OSA), novel surrogate markers of adipose accumulation may serve as more critical and reliable factors for consideration. Consequently, this study aims to explore and elucidate the correlation between metabolic score for visceral fat (METS-VF) and OSA.

Methods

In this cross-sectional study, the data from the National Health and Nutrition Examination Survey (NHANES) during the period from 2013 to 2020 were adopted. Through multivariate logistic regression, restricted cubic spline regression (RCS), subgroup analyses and sensitivity analyses, the correlation between METS-VF and OSA was explored.

Results

Among 8,284 subjects, 4,176 of them were categorized as having OSA. It was observed that the quartile range of METS-VF increased, with a notable rise in the prevalence of OSA (32.8% vs. 49.8% vs. 56.9% vs. 62.1%, p < 0.001). Logistic regression analyses showed a significant positive correlation between METS-VF and the risk of having OSA, even after accounting for potential confounders (OR = 2.436, 95% CI: 2.065, 2.874). Subgroup analyses further revealed a stronger correlation between OSA and METS-VF among subjects who were female, younger, and Mexican Americans. RCS regression identified a positive linear correlation, without threshold effects. Sensitivity analyses with stop breathing (OR = 2.283, 95%CI: 1.169, 3.070) or snoring (OR = 2.716, 95%CI: 2.273, 3.246) as outcomes reaffirmed the positive correlation with METS-VF.

Conclusion

Elevated METS-VF demonstrated a linear correlation with the increased incidence of OSA, suggesting the potential utility as a predictive index for OSA.

Changes in the metabolic score for insulin resistance index for risk prediction of stroke in middle-aged and older Chinese population

Background

As a major noncommunicable disease, stroke poses a major threat to public health. In the context of predictive, preventative, and personalised medicine (PPPM/3PM), early identification of high-risk individuals is crucial for targeted prevention and personalised treatment for stroke. This study aimed to investigate the association between changes in the Metabolic Score for Insulin Resistance Index (METS-IR) and incident stroke. From the perspective of PPPM/3PM, we hypothesised that monitoring dynamic changes of the METs-IR levels and targeting cumulative METs-IR index contribute to risk prediction, targeted prevention, and personalised management of stroke.

Methods

All data were obtained from the China Health and Retirement Longitudinal Study (CHARLS), a nationwide prospective cohort study. The individuals were categorised into four subgroups based on the quartiles (Q) of the cumulative METS-IR index as a reflection of changes in the METS-IR values from 2012 to 2015. Logistic regression was employed to examine the association between cumulative METS-IR index and stroke incidence. Additionally, restricted cubic spline regression analysis was used to assess potential linearity.

Results

Among the 4288 participants, 275 (6.4%) experienced a stroke. The risk of stroke events increased with higher cumulative METS-IR index levels. Compared with the lowest quartile (Q1), the OR of having a stroke was 1.20 (0.81, 1.78) for Q2, 1.51 (1.04, 2.21) for Q3 and 2.17 (1.52, 3.10) for the highest quartile (Q4). After adjusting for multiple potential confounders, Q4 (OR: 1.57, 95% CI: 1.04, 2.35) remained significantly associated with stroke. The association between the cumulative METS-IR index and stroke incidence was linear in males, females, and the overall population (all P values for nonlinearity > 0.05).

Conclusions

A higher cumulative METS-IR index was associated with an increased risk of incident stroke among middle-aged and older Chinese individuals. In the context of PPPM/3PM, incorporating metabolic health into stroke risk assessment advances the prediction, prevention and personalised management of stroke.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00388-y.

Association of metabolic score for insulin resistance with progression or regression of prediabetes: evidence from a multicenter Chinese medical examination cohort study

Objective

Few studies have evaluated the changes in blood glucose status in individuals with prediabetes, and this study aimed to analyze the association between metabolic score for insulin resistance (MetS-IR) and the progression or regression of prediabetes.

Methods

This retrospective cohort study used research data from medical examination institutions under the Rich Healthcare Group in 32 regions across 11 cities in China. Progression of prediabetes to diabetes and regression to normal fasting glucose (NFG) were defined based on glycemic changes during follow-up. The association between MetS-IR and the progression or regression of prediabetes was analyzed using multivariate Cox regression, restricted cubic splines, and piecewise regression models.

Results

Data from 15,421 prediabetic subjects were analyzed. Over an average follow-up of 2.96 years, 6,481 individuals (42.03%) returned to NFG, and 2,424 (15.72%) progressed to diabetes. After controlling for confounding factors, an increase in MetS-IR was observed to increase the risk of diabetes onset in the prediabetic population, whereas a decrease in MetS-IR had a protective effect for returning to NFG. Additionally, a nonlinear relationship between MetS-IR and prediabetes regression was observed, with 37.22 identified as the inflection point; prediabetes regression rates were significantly higher before this point and markedly decreased after it.

Conclusion

For individuals with prediabetes, an increase in MetS-IR may lead to an increased risk of diabetes; conversely, a decrease in MetS-IR enhances the protective effect for returning to NFG and keeping MetS-IR below 37.22 is significant for the regression of prediabetes.

Association of METS-IR index with Type 2 Diabetes: A cross-sectional analysis of national health and nutrition examination survey data from 2009 to 2018

BACKGROUND

With rising global diabetes prevalence, precise early identification and management of diabetes risk are critical research areas. The metabolic score for insulin resistance (METS-IR), a novel non-insulin-based tool, is gaining attention for quantifying insulin resistance using multiple metabolic parameters. Despite its potential in predicting diabetes and its precursors, evidence on its specific relationship with diabetes is limited, especially in large-scale population validation and mechanistic exploration.

OBJECTIVE

This study aims to analyze the association between METS-IR and type 2 diabetes (T2DM) in American adults.

METHODS

We conducted a cross-sectional analysis of the National Health and Nutrition Examination Survey (NHANES) data from 2009 to 2018. Participants aged 20 years and above were included, excluding individuals with missing data on BMI, fasting blood glucose, high-density lipoprotein cholesterol glycated hemoglobin and diabetes status. Logistic regression analysis, subgroup analysis, and restricted cubic spline analysis were used to assess the association between METS-IR and T2DM, controlling for potential confounding factors.

RESULTS

After adjusting for age, gender, race, education level, smoking status, drinking habits, depression, physical activity, hypertension, and hyperlipidemia, we found a positive association between METS-IR and the risk of T2DM. Specifically, each unit increase in METS-IR was associated with a 7% increase in the risk of T2DM (OR = 1.07, 95% CI: 1.06, 1.08). Subgroup analysis showed that the association between METS-IR and T2DM incidence was significantly positive in the highest quartile group, particularly among Mexican Americans over 40 years old and those diagnosed with depression, hypertension, or hyperlipidemia.

CONCLUSION

Our study revealed a significant positive association between METS-IR and the prevalence of T2DM, indicating that this relationship persists even after controlling for various confounding factors. Therefore, monitoring METS-IR may provide a valuable tool for the early identification of individuals at risk of glucose metabolism disorders. Further research should focus on the applicability of METS-IR in different populations and its potential impact on clinical practice.

Assessing the validity of METS-IR for predicting the future onset of diabetes: an analysis using time-dependent receiver operating characteristics

BACKGROUND

The Metabolic Insulin Resistance Score (METS-IR) is a non-invasive proxy for insulin resistance (IR) that has been newly developed in recent years and has been shown to be associated with diabetes risk. Our aim was to assess the predictive value of METS-IR for the future development of diabetes and its temporal differences in people of different sex, age, and body mass index (BMI).

METHODS

The current study included 15,453 baseline non-diabetic subjects in the NAGALA cohort and then grouped according to the World Health Organization's (WHO) recommended criteria for age and BMI. Multivariate Cox regression and time-dependent receiver operator characteristics (ROC) curves were used to analyze the value of METS-IR in assessing and predicting the risk of diabetes in people of different sexes, ages, and BMIs.

RESULTS

373 individuals developed diabetes during the observation period. By multivariate COX regression analysis, the development of future diabetes was significantly associated with increased METS-IR, and this positive association was stronger in women than in men and in individuals < 45 years than in individuals ≥ 45 years; while no significant differences were observed between non-obese and overweight/obesity individuals. Using time-dependent ROC analysis we also assessed the predictive value of METS-IR for future diabetes at a total of 11-time points between 2 and 12 years. The results showed that METS-IR had a higher predictive value for the future development of diabetes in women or individuals < 45 years of age compared to men or individuals ≥ 45 years of age for almost the entire follow-up period. Furthermore, across different BMI categories, we also found that in the short term (3-5 years), METS-IR had a higher predictive value for the development of diabetes in individuals with overweight/obesity, while in the medium to long term (6-12 years), METS-IR was more accurate in predicting the development of diabetes in non-obese individuals.

CONCLUSIONS

Our study showed that METS-IR was independently associated with the development of future diabetes in a non-diabetic population. METS-IR was a good predictor of diabetes, especially for women and individuals < 45 years old for predicting the future risk of developing diabetes at all times.

Non-Insulin-Based Indices of Insulin Resistance for Predicting Incident Albuminuria: A Nationwide Population-Based Study

BACKGROUND

Studies have shown that incident albuminuria is associated with insulin resistance (IR); however, an IR marker that best predicts the prevalence of albuminuria has not yet been established. This study explored the association between IR and incident albuminuria using various IR indices, including the homeostasis model assessment of IR (HOMA-IR), metabolic score for IR (METS-IR), and triglyceride-glucose (TyG) index, and compared their predictive abilities for the prevalence of albuminuria.

METHODS

A total of 4,982 Korean adults from the 2019 Korea National Health and Nutritional Examination Survey were analyzed. The odds of albuminuria were determined using the quartiles of the IR indices. Receiver operating characteristic (ROC) curves were used to calculate the area under the ROC curve and predictability. The cutoff values for albuminuria detection were also computed.

RESULTS

An increase in the quartiles of all three IR indices was associated with incident albuminuria, even after full adjustment for covariates (HOMA-IR: odds ratio [OR], 1.906; 95% confidence interval [CI], 1.311-2.772; P=0.006; METS-IR: OR, 2.236; 95% CI, 1.353-3.694; P=0.002; TyG index: OR, 1.757; 95% CI, 1.213-2.544; P=0.003). The area under the ROC curve for incident albuminuria based on the HOMA-IR, METS-IR, and TyG indices was 0.594 (95% CI, 0.568-0.619), 0.633 (95% CI, 0.607-0.659), and 0.631 (95% CI, 0.606-0.656), respectively. The optimal cutoff values for predicting albuminuria were 2.38, 35.38, and 8.72 for the HOMA-IR, METS-IR, and TyG indices, respectively.

CONCLUSION

The METS-IR and TyG indices outperformed HOMA-IR in predicting incident albuminuria.

bta-miR-224 regulates milk fat metabolism by targeting FABP4 in bovine mammary epithelial cells

Milk fat is produced and secreted by the mammary gland, which is mainly regulated by diet and gene-molecule network. Therefore, understanding the molecular mechanism of milk fat synthesis is of practical significance for improving milk quality. Fatty acid-binding protein 4 (FABP4) is a candidate messenger RNA (mRNA) closely linked to milk fat metabolism obtained from transcriptomic analysis of mammary epithelial cells of cows in the pre-existing high- and low-milk-fat groups, and its expression pattern and function are still unclear. The qRT-PCR results depicted that FABP4 was highly expressed in bovine mammary epithelial cells (BMECs) in breast tissues and the high milk fat group. Subsequently, the regulatory effects of FABP4 on BMECs were analyzed by CCK8, EdU, and flow cytometry, and the results demonstrated that FABP4 inhibited the proliferation and viability of BMECs and promoted their apoptosis. Next, the effect of FABP4 on milk lipid metabolism was explored. pEGFP-N1-FABP4 was transfected into BMECs, and FABP4 upregulated the expression levels of the milk lipid marker genes XDH, PPARG, and ACSS2, and promoted the formation of triglycerides (TGs), cholesterol, lipid droplets, and β-casein. Strong interactions between FABP4 and PPARG were identified using STRING prediction. Western blotting revealed that FABP4 interacted with PPARG to promote PPARG expression, while the opposite result was observed after interfering with FABP4. The gene regulation of microRNA (miRNA) is essential for fatty acid metabolism and synthesis. Predicted by website and combined with pre-miRNA transcriptome sequencing results, we hypothesized that FABP4 might be the target gene of bta-miR-224. The results of the dual-luciferase reporter gene and qRT-PCR revealed that bta-miR-224 negatively regulated FABP4 expression by targeting the 3'-UTR of FABP4. By exploring the function of bta-miR-224, we observed that bta-miR-224 mimics downregulated the expression of the milk fat marker genes AGPAT6, ACSS2, and XDH and inhibited TG synthesis and lipid droplet secretion. However, the bta-miR-224 inhibitor depicted the opposite results. In conclusion, FABP4 plays a crucial role in regulating BMEC proliferation and differentiation. Bta-miR-224 targeting FABP4 may promote biological processes such as TG synthesis and lipid droplet formation through PPARG, which lays a solid foundation for further analysis of the functional mechanism of milk lipid metabolism in dairy cows from a miRNA-mRNA perspective.

Exploring the Relationship Between Different Obesity Metabolism Indices and Hyperuricemia in Patients with Hypertension and Coronary Heart Disease

Background

Previous studies have established a strong association between obesity, high metabolism, and the development of hyperuricemia. However, the relationship between obesity metabolism indices and hyperuricemia in high-risk patients with hypertension and coronary heart disease (CHD) remains unclear. The purpose of this study was to investigate this relationship in patients with both hypertension and CHD, and to identify the obesity metabolism index with the best diagnostic value.

Methods

A two-center study encompassed 6344 participants with hypertension and CHD. Multiple logistic regression was utilized to examine the correlation between six obesity metabolism indices and hyperuricemia, with restricted cubic spline (RCS) analysis to identify non-linear relationships. Diagnostic value was assessed via receiver operating characteristic (ROC) curves and decision curve analysis (DCA).

Results

Multivariable logistic regression revealed a significant correlation between increased obesity metabolism indices and hyperuricemia. Furthermore, RCS analysis revealed a nonlinear dose-response relationship (P for nonlinear < 0.001). Moreover, ROC and DCA results showed that METS-VF index, which combined visceral obesity and metabolic parameters, became the most reliable diagnostic tool.

Conclusion

The study underscores a strong association between elevated obesity metabolism indices and hyperuricemia in patients with hypertension and CHD. The METS-VF index, amalgamating visceral obesity and metabolic parameters, emerged as the most reliable diagnostic tool.

METS-IR as an important predictor of neurological impairment severity in patients with severe cerebral infarction: a multicenter study based on the Chinese population

Background

Insulin resistance (IR) is linked to an increased risk of neurological impairment following a stroke and may contribute to poor neurological prognosis in affected patients. The metabolic score for the insulin resistance index, shortened as the METS-IR, generally serves as a surrogate index for IR. However, its association with the severity of neurological impairment in patients with severe cerebral infarction (CI) in neurological intensive care units (ICU) has not been fully established.

Methods

Patients with a diagnosis of CI, admitted to the neurological ICUs of Yangzhou University's Affiliated Hospital and Xuzhou Medical University's Affiliated Hospital, were included in the study. A multivariate logistic regression model and restricted cubic splines (RCS) were employed to explore the relationship between the METS-IR index and the severity of neurological impairment in these patients. The predictive capabilities of the METS-IR index and the triglyceride-glucose (TyG) index for outcome measures were compared through the ROC curve. Furthermore, a decision curve analysis was executed, and the integrated discrimination improvement (IDI) index was computed to evaluate the enhancements in predictive performance and clinical utility of various scoring systems with the inclusion of the METS-IR index. Subgroup analysis was conducted regarding age, BMI, and smoking status.

Results

The study ultimately included 504 participants. Adjusted logistic regression and RCS results showed that as the METS-IR index increases, the risk of neurological impairment in patients with severe CI consistently grows (P for overall = 0.0146, P-nonlinear: 0.0689). The METS-IR index's predictive capability for neurological impairment (AUC = 0.669) was superior to that of the TyG index (AUC = 0.519).

Conclusion

From the study results, the METS-IR index can serve as an important predictor for neurological impairment in ICU patients with severe CI. It can aid in the identification and early intervention of neurological impairment in these patients.

METS-IR, a Novel Simple Insulin Resistance Index, is Associated with NAFLD in Patients with Type 2 Diabetes Mellitus

Purpose

Substantial evidence has established a strong association between non-alcoholic fatty liver disease (NAFLD), type 2 diabetes mellitus (T2DM) and insulin resistance (IR). Insulin resistance metabolic score (METS-IR) is a new and more effective comprehensive indicator for measuring IR. Our aim was to investigate the relationship between METS-IR and NAFLD in T2DM population.

Patients and methods

This cross-sectional study included 1097 adult patients with T2DM. Anthropometric measurements and biochemical indicators were collected, and the NAFLD was diagnosed by ultrasound. The METS-IR was calculated. Based on the presence of NAFLD, the population was divided into non-NAFLD and NAFLD groups. The relationship between METS-IR and NAFLD was evaluated.

Results

Compared with the non-NAFLD group, the METS-IR was higher in the NAFLD group (P < 0.001). The incidence rate of NAFLD increased across the quartiles of the METS-IR (P < 0.001). Spearman correlation analysis showed that METS-IR was positively correlated with NAFLD (Correlation Coefficient: 0.441, P < 0.001). The binary logistic regression analysis indicated that METS-IR was independently associated with NAFLD (OR: 1.120, 95% CI 1.080-1.161). Furthermore, the area under the receiver operating characteristic curve of the METS-IR was 0.781 (95% CI 0.746-0.817) and relatively higher than other evaluation variables.

Conclusion

In patients with T2DM, METS-IR is closely associated with NAFLD, and might be a valuable predictor of NAFLD. Further research is needed to verify this association.

Lipid accumulation product and type 2 diabetes risk: a population-based study

BACKGROUND

The Lipid Accumulation Product (LAP) is a measure that indicates excessive fat accumulation in the body. LAP has been the focus of research in epidemiological studies aimed at forecasting chronic and metabolic diseases. This study aimed to evaluate the association between LAP and type 2 diabetes mellitus (T2DM) among adults in western Iran.

METHODS

The study involved 9,065 adults who participated in the initial phase of the Ravansar non-communicable diseases study (RaNCD) cohort. To investigate the association between LAP and T2DM, multiple logistic regressions were employed. Additionally, the receiver operating characteristic (ROC) curve was used to evaluate LAP's predictive ability concerning T2DM.

RESULTS

The participants had an average age of 47.24 ± 8.27 years, comprising 49.30% men and 50.70% women. The mean LAP was 53.10 ± 36.60 for the healthy group and 75.51 ± 51.34 for the diabetic group (P < 0.001). The multiple regression analysis revealed that the odds of T2DM in the second quartile of LAP were 1.69 (95% CI: 1.25, 2.29) times greater than in the first quartile. Furthermore, the odds in the third and fourth quartiles were 2.67 (95% CI: 2.01, 3.55) and 3.73 (95% CI: 2.83, 4.92) times higher, respectively. The ROC analysis for predicting T2DM showed that the LAP index had an area under the curve (AUC) of 0.66 (95% CI: 0.64, 0.68).

CONCLUSION

A strong association was identified between elevated LAP levels and T2DM in the adult population of western Iran. LAP is recommended as a potential tool for screening diabetes susceptibility.

METS-IR/HOMA-IR and MAFLD in U.S. adults: dose-response correlation and the effect mediated by physical activity

OBJECTIVES

Metabolic dysfunction-associated fatty liver disease (MAFLD), a globally prevalent disease, is closely linked to insulin resistance (IR). Physical activity (PA) is closely linked to both MAFLD and IR. We aim to explore the dose-response relationship between metabolic score for IR (METS-IR)/homeostasis model assessment of IR (HOMA-IR) and MAFLD, and investigate the relationship between PA, IR and MAFLD.

METHODS

Participants from the NHANES study were included in this cross-section study. Logistic regression and the receiver operating characteristic were used to assess the predictive performance of METS-IR/HOMA-IR for MAFLD. Restrictive cubic splines were performed to visualize their dose-response relationship. Decision tree analysis was used to identify high-risk populations of MAFLD. PA's mediating effect in the association between METS-IR/HOMA-IR and MAFLD was also examined.

RESULTS

Of all 1,313 participants, 693 had MAFLD (52.78%). There were a positive association between METS-IR (OR = 1.162, 95% CI = 1.126-1.199) and HOMA-IR (OR = 1.630, 95% CI = 1.431-1.856) and MAFLD risk. The AUCs of the METS-IR and HOMA-IR were 0.831 (0.809, 0.853) and 0.767 (0.741, 0.791), respectively, with significantly different predictive performance (P < 0.001). Adding METS-IR/HOMA-IR to the basic model greatly improved the statistical significance for MAFLD. Five high-risk subgroups were identified for MAFLD. PA mediated about 0.81% and 0.78% (indirect effect/total effect) in the association between METS-IR/HOMA-IR and MAFLD.

CONCLUSIONS

MAFLD risk might be predicted by METS-IR/HOMA-IR, among which METS-IR performed better. And PA mediated the association between them. More attention should be paid to the therapeutic effect of lifestyle changes on MAFLD.

HIGHLIGHTS

1. Positive associations were found between METS-IR and HOMA-IR and MAFLD risk. 2. METS-IR has better predictive performance for MAFLD risk than HOMA-IR. 3.Two high-risk subgroups were identified for MAFLD by METS-IR: individuals with METS-IR ≥ 40; Hispanic black individuals with 34 ≤ METS-IR < 40 and aged ≥ 46. 4. In the significant association between METS-IR/HOMA-IR and MAFLD, about 0.81% and 0.78% (indirect effect/total effect), respectively, were mediated by physical activity.

Sex differences in the association between metabolic score for insulin resistance and the reversion to normoglycemia in adults with prediabetes: a cohort study

BACKGROUND

The metabolic score for insulin resistance (MetS-IR) has become a valid indicator to evaluate insulin resistance. Our investigation sought gender differences in the correlation between MetS-IR and the reversion from prediabetes to normoglycemic status.

METHODS

This retrospective research, carried out in 32 areas across 11 cities with several centers in China, encompassed 15,423 participants with prediabetes. We employed a Cox proportional hazards regression model to examine the link between MetS-IR and the reversion to normoglycemic status. We also applied cubic spline functions and smooth curve fitting to detect non-linear relationships. Additionally, we embarked on a range of sensitivity analyses.

RESULTS

The study included 15,423 participants, with 10,009 males (64.90%) and 5,414 females (35.10%). The average follow-up time was 2.96 ± 0.93 years, and 6,623 individuals (42.94%) reversed normoglycemia. A non-linear correlation was discovered among MetS-IR and reversion to normoglycemic status in men, with a turning point at 55.48. For a one-unit rise in MetS-IR below this point, the chance of reversal to normoglycemic levels declined by 3% (HR = 0.97, 95% CI:0.96-0.97, P < 0.0001). In women, the association was linear, with every unit rise in MetS-IR leading to a 3% reduction in transitioning to normal glycemic levels. (HR = 0.97, 95% CI: 0.97-0.98, p < 0.0001).

CONCLUSION

A negative correlation was discovered between MetS-IR and reversion to normoglycemic status in adults with prediabetes. Specifically, a non-linear association was observed for males, while females exhibited a linear correlation.

Follow-up study to explore the relationship between Neutrophil to lymphocyte ratio and impaired fasting glucose-using the group-based trajectory modeling

Previous studies have indicated a link between neutrophil to lymphocyte ratio (NLR) and impaired fasting glucose (IFG), but the findings have been disputed. By conducting a real-world follow-up study, we can monitor the development of diseases and confirm the connection between NLR and IFG. A total of 1168 patients without IFG or T2DM were followed up for six years. At baseline, participants' NLR levels, fasting plasma glucose and other clinical characteristics were recorded. During the follow-up period, NLR levels and the prevalence of IFG were recorded. Ultimately, 45 individuals were lost to follow-up, leaving 1,123 participants for analysis. Using Group-Based Trajectory Modeling (GBTM), the sample was divided into three groups. The prevalence of IFG in the three groups was 12.1%, 19.4%, and 20.85%, respectively. Compared with the low-level NLR group, the hazard ratio of IFG in the moderate-level NLR group and high-level NLR group were 1.628 (1.109-2.390) and 1.575 (1.001-2.497), respectively. There was a significant interaction effect of BMI and NLR on the risk of IFG (P < 0.001). In this real-world follow-up study, we observed a positive association between NLR and the risk of IFG, with this relationship being exacerbated by obesity status.

Metabolic Score for Insulin Resistance and New-Onset Type 2 Diabetes in a Middle-Aged and Older Adult Population: Nationwide Prospective Cohort Study and Implications for Primary Care

BACKGROUND

The metabolic score for insulin resistance (METS-IR) has emerged as a noninsulin-based index for the approximation of insulin resistance (IR), yet longitudinal evidence supporting the utility of METS-IR in the primary prevention of type 2 diabetes mellitus (T2DM) remains limited.

OBJECTIVE

We aimed to investigate the longitudinal association between METS-IR, which combines fasting plasma glucose (FPG), lipid profiles, and anthropometrics that can be routinely obtained in resource-limited primary care settings, and the incidence of new-onset T2DM.

METHODS

We conducted a closed-cohort analysis of a nationwide, prospective cohort of 7583 Chinese middle-aged and older adults who were free of T2DM at baseline, sampled from 28 out of 31 provinces in China. We examined the characteristics of participants stratified by elevated blood pressure (BP) at baseline and new-onset T2DM at follow-up. We performed Cox proportional hazard regression analysis to explore associations of baseline METS-IR with incident T2DM in participants overall and in participants stratified by baseline BP. We also applied net reclassification improvement and integrated discrimination improvement to examine the incremental value of METS-IR.

RESULTS

During a mean follow-up period of 6.3 years, T2DM occurred in 527 participants, among which two-thirds (332/527, 62.9%; 95% CI 58.7%-67.1%) had baseline FPG<110 mg/dL. A SD unit increase in baseline METS-IR was associated with the first incidence of T2DM (adjusted hazard ratio [aHR] 1.33, 95% CI 1.22-1.45; P<.001) in all participants. We obtained similar results in participants with normal baseline BP (aHR 1.41, 95% CI 1.22-1.62; P<.001) and elevated baseline BP (aHR 1.29, 95% CI 1.16-1.44; P<.001). The predictive capability for incident T2DM was improved by adding METS-IR to FPG. In study participants with new-onset T2DM whose baseline FPG was <126 mg/dL and <110 mg/dL, 62.9% (332/527; 95% CI 60%-65.9%) and 58.1% (193/332; 95% CI 54.3%-61.9%) of participants had baseline METS-IR above the cutoff values, respectively.

CONCLUSIONS

METS-IR was significantly associated with new-onset T2DM, regardless of baseline BP level. Regular monitoring of METS-IR on top of routine blood glucose in clinical practice may add to the ability to enhance the early identification of primary care populations at risk for T2DM.

Negative correlation between metabolic score for insulin resistance index and testosterone in male adults

BACKGROUND

Insulin resistance (IR) is strongly correlated with the decreased deficiency of testosterone levels in males. The metabolic score for insulin resistance (METS-IR) index is regarded as an innovative measure for the assessment on IR. The research aims to explore the correlation between the METS-IR index and the testosterone levels in males.

METHODS

In this study, a cross-sectional design was made through the data obtained from the National Health and Nutrition Examination Survey (NHANES) from 2013 to 2020. Besides, the METS-IR index was derived from serum triglyceride levels, fasting plasma glucose, HDL-C and BMI.

RESULTS

A total of 2082 participants were included in the final analysis. After controlling for confounding variables, it was found that METS-IR was independently and negatively correlated with testosterone levels (β = -3.88, 95% CI = -4.49, -3.27, P < 0.001). As shown by the generalized smooth curve fitting, METS-IR had a linear correlation with testosterone levels without threshold or saturation effects, which was consistently observed across all subgroups through stratified analysis (all P > 0.05). As revealed by the analysis on the ROC curve, the area under the curve (AUC) for the METS-IR index (0.732, 95% CI = 0.705, 0.760) was significantly larger than that of homeostatic model assessment of insulin resistance (HOMA-IR), TG/HDL ratio, triglyceride-glucose index (TyG) and body mass index (BMI).

CONCLUSION

The findings suggest a negative relationship between the METS-IR index and the testosterone levels in male adults. Furthermore, the METS-IR index demonstrates superior predictive ability for testosterone deficiency in comparison to HOMA-IR, TG/HDL ratio, TyG and BMI.

Association of phthalate exposure with type 2 diabetes and the mediating effect of oxidative stress: A case-control and computational toxicology study

Phthalic acid esters (PAEs) are widely used as plasticizers and have been suggested to engender adverse effects on glucose metabolism. However, epidemiological data regarding the PAE mixture on type 2 diabetes (T2DM), as well as the mediating role of oxidative stress are scarce. This case-control study enrolled 206 T2DM cases and 206 matched controls in Guangdong Province, southern China. The concentrations of eleven phthalate metabolites (mPAEs) and the oxidative stress biomarker 8-hydroxy-2'-deoxyguanosine (8-OHdG) in urine were determined. Additionally, biomarkers of T2DM in paired serum were measured to assess glycemic status and levels of insulin resistance. Significantly positive associations were observed for mono-(2-ethylhexyl) phthalate (MEHP) and Mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) with T2DM (P < 0.001). Restricted cubic spline modeling revealed a non-linear dose-response relationship between MEHHP and T2DM (Pnon-linear = 0.001). The Bayesian kernel machine regression and quantile g-computation analyses demonstrated a significant positive joint effect of PAE exposure on T2DM risk, with MEHHP being the most significant contributor. The mediation analysis revealed marginal evidence that oxidative stress mediated the association between the mPAEs mixture and T2DM, while 8-OHdG respectively mediated 26.88 % and 12.24 % of MEHP and MEHHP on T2DM risk individually (Pmediation < 0.05). Di(2-ethylhexyl) phthalate (DEHP, the parent compound for MEHP and MEHHP) was used to further examine the potential molecular mechanisms by in silico analysis. Oxidative stress may be crucial in the link between DEHP and T2DM, particularly in the reactive oxygen species metabolic process and glucose import/metabolism. Molecular simulation docking experiments further demonstrated the core role of Peroxisome Proliferator Activated Receptor alpha (PPARα) among the DEHP-induced T2DM. These findings suggest that PAE exposure can alter oxidative stress via PPARα, thereby increasing T2DM risk.

Insight into the Predictive Power of Surrogate Diagnostic Indices for Identifying Individuals with Metabolic Syndrome

BACKGROUND

This study aimed to assess the diagnostic capability of insulin surrogate measurements in identifying individuals with metabolic syndrome (MetS) and propose applicable indices derived from fasting values, particularly in large study populations.

METHODS

Data were collected from the datasets of the Surveillance of Risk Factors of NCDs in Iran Study (STEPS). MetS was defined based on the National Cholesterol Education Program (NCEP) criteria. Various insulin surrogate indices, including Homeostasis Model Assessment (HOMA), Quantitative Insulin Sensitivity Check Index (QUICKI), Fasting glucose to insulin ratio (FGIR), Reynaud, Reciprocal insulin, McAuley, Metabolic Score for Insulin Resistance (METS-IR), Triglyceride-glucose index (TyG), TG/ HDL-C, TG/ BMI, and TG/ WC ratio were assessed. Receiver Operating Characteristic (ROC) curves were used to assess pathologic conditions and determine the optimal cut-off through the highest score of the Youden index. Also, Area Under the Curve (AUC) values were established for each index totally and according to sex, age, and BMI differences.

RESULTS

The study population consisted of 373 individuals (49.9% women; 75.1% middle age, 39.1% obese, and 27.3% overweight), of whom 117 (31.4%) had MetS. The METS-IR (AUC: 0.856; 95% CI: 0.817-0.895), TG/ HDL-C (AUC: 0.820; 95% CI: 0.775-0.886), TyG (AUC: 0.808; 95% CI: 0.759-0.857), and McAuley (AUC: 0.804; 95% CI: 0.757-0.852) indices provided the greatest AUC respectively for detection of MetS. The values of AUC for all the indices were higher in men than women. This trend was consistent after data stratification based on BMI categories, middle age, and senile individuals.

CONCLUSION

The present study indicated that indices of insulin, including METS-IR, TG/HDLC, TyG, and McAuley, have an equal or better capacity in determining the risk of MetS than HOMA-IR, are capable of identifying individuals with MetS and may provide a simple approach for identifying populations at risk of insulin resistance.

Predictive values of metabolic score for insulin resistance on risk of major adverse cardiovascular events and comparison with other insulin resistance indices among Chinese with and without diabetes mellitus: Results from the 4C cohort study

AIMS/INTRODUCTION

To investigate the relationship between the metabolic score for insulin resistance (METS-IR) index and major adverse cardiac events (MACEs) and to compare its ability to predict MACEs with other IR indices including homeostatic model assessment for IR (HOMA-IR) and triglyceride glucose (TyG) index-related parameters.

MATERIALS AND METHODS

We conducted a cohort study enrolling 7,291 participants aged ≥40 years. Binary logistic regression and restricted cubic splines were performed to determine the association between METS-IR and MACEs, and the receiver operating curve (ROC) was utilized to compare the predictive abilities of IR indices and to determine the optimal cut-off points.

RESULTS

There were 348 (4.8%) cases of MACEs during a median follow-up of 3.8 years. Compared with participants with a METS-IR in the lowest quartile, the multivariate-adjusted RRs and 95% CIs for participants with a METS-IR in the highest quartile were 1.47 (1.05-2.77) in all participants, 1.42 (1.18-2.54) for individuals without diabetes, and 1.75 (1.11-6.46) for individuals with diabetes. Significant interactions were found between the METS-IR and the risk of MACEs by sex in all participants and by age and sex in individuals without diabetes (all P values for interaction < 0.05). In the ROC analysis, the METS-IR had a higher AUC value than other indices for predicting MACEs in individuals with diabetes and had a comparable or higher AUC than other indices for individuals without diabetes.

CONCLUSIONS

The METS-IR can be an effective clinical indicator for identifying MACEs, as it had superior predictive power when compared with other IR indices in individuals with diabetes.

Mets-IR as a predictor of cardiovascular events in the middle-aged and elderly population and mediator role of blood lipids

Background

Cardiovascular disease (CVD) is a global health concern, with a significant impact on morbidity and mortality rates. Using fasting glucose, fasting triglycerides, body mass index (BMI), and high-density lipoprotein cholesterol (HDL-C), the metabolic score of insulin resistance (Mets-IR), a novel index created by Mexican researchers to assess insulin sensitivity, is a more precise way to measure insulin sensitivity. This study aimes to explore the association between Mets-IR and CVD, as well as investigate the potential mediating role of of low-density lipoprotein cholesterol (LDL-C).

Methods

The study's data came from the 2011 and 2018 China Health and Retirement Longitudinal Studies (CHARLS). We used three logistic regression models to account for the potential effects of ten factors on cardiovascular disease/stroke/heart disease. Moreover, We performed mediation analyses to evaluate the role of LDL-C in the association between Mets-IR and incident CVD.

Results

This study comprised 4,540 participants, of whom 494 (10.88%) were found to develop disease (CVD). Each interquartile range (IQR) increased in Mets-IR raised the risk of developing CVD by 38% (OR=1.38; 95% CI, 1.21-1.56) and there was a linear dose-response relationship between Mets-IR and the risk of new-onset cardiovascular disease, stroke, and heart disease (P overall<0.05, P non-linear>0.05). Approximately 5% (indirect effect/total effect) of the significant association of Mets-IR with stroke was mediated by LDL-C, respectively. With the addition of Mets-IR to the base model, the continuous net reclassification improvement and integrated discrimination improvement for predicting cardiovascular disease increased by 0.175 (P <0.001) and 0.006 (P <0.001), respectively.

Conclusion

ets-IR is associated with an increased risk of cardiovascular disease/stroke/cardiac issues, with LDL-C mediating these relationships. Improving insulin sensitivity and lipid regulation may be essential and effective preventive measures for cardiovascular events.

Association between MetS-IR and prediabetes risk and sex differences: a cohort study based on the Chinese population

Objective

The metabolic score for insulin resistance (MetS-IR) is an emerging surrogate marker for insulin resistance (IR). This study aimed to investigate the association and sex differences between MetS-IR and prediabetes risk in a Chinese population.

Methods

This cohort study included 100,309 adults with normoglycemia at baseline and had followed longitudinally for 5 years, and with prediabetes, defined according to the 2018 American Diabetes Association (ADA) recommended diagnostic criteria, as the outcome of interest. Multivariate Cox proportional hazards regression and restricted cubic spline (RCS) regression models were used to assess the association between MetS-IR and prediabetes risk.

Results

During an observation period of 312,843 person-years, 7,735 (14.84%) men and 4,617 (9.57%) women with pre-diabetes onset were recorded. After fully adjusting for confounders, we found an independent and positive correlation between MetS-IR and the risk of prediabetes in the Chinese population, and the degree of correlation was stronger in women than in men (HR: 1.24 vs 1.16, P-interaction<0.05). Furthermore, using RCS nested in the Cox regression model, we found that there was a nonlinear correlation between MetS-IR and prediabetes risk in both sexes with an obvious saturation effect point, and when the MetS-IR was greater than the value of the saturation effect point, the risk of prediabetes was gradually leveling off. We further calculated the saturation effect points of MetS-IR used to evaluate the risk of prediabetes which in men was 42.82, and in women was 41.78.

Conclusion

In this large cohort study, our results supported that MetS-IR was independently and positively associated with the risk of prediabetes in the Chinese population, with the association being stronger in women than in men.

Association Between the Metabolic Score for Insulin Resistance and Hypertension in Adults: A Meta-Analysis

The metabolic score for insulin resistance (METS-IR) is a recently developed parameter for screening of metabolic disorder. However, the association between METS-IR and risk of hypertension in general adult population remains not fully determined. A meta-analysis was therefore performed. Observational studies evaluating the association between METS-IR and hypertension in adults were retrieved by searching PubMed, Embase, and Web of Science databases from inception to October 10, 2022. A random-effects model, which incorporates the potential influence of heterogeneity, was used to pool the results. Eight studies with 305 341 adults were included in the meta-analysis, and 47 887 (15.7%) of them had hypertension. Pooled results showed that a higher METS-IR was associated with hypertension after adjusting for multiple conventional risk factors [relative risk (RR) for highest versus lowest category of METS-IR: 1.67, 95% confidence interval (CI): 1.53 to 1.83, p<0.001, I2=8%]. The results were consistent in subgroup analyses according to study design, source of the cohort, age, sex, body mass index of the participants, and quality scores of the study (p for subgroup difference all>0.05). Results of meta-analysis with METS-IR analyzed in continuous variables also showed that METS-IR was associated with the risk of hypertension (RR for 1-unit increment of METS-IR: 1.15, 95% CI: 1.08 to 1.23, p<0.001, I2=79%). In conclusion, a high METS-IR is associated with hypertension in general adult population. Measuring METS-IR may be useful for screening participants at high risk of hypertension.

The Metabolic Score for Insulin Resistance (METS-IR) Predicts Cardiovascular Disease and Its Subtypes in Patients with Hypertension and Obstructive Sleep Apnea

Objective

We aimed to evaluate the METS-IR (metabolic score for insulin resistance) index for the prediction of incident cardiovascular disease (CVD) and its subtypes (coronary artery disease and stroke) in patients with hypertension and obstructive sleep apnea (OSA).

Methods

A retrospective cohort study was conducted with 2031 adults with hypertension and OSA, participants from the Urumqi Research on Sleep Apnea and Hypertension study (UROSAH). The hazard ratios and 95% CIs (credibility interval) for CVD and its subtypes were estimated using multivariate Cox proportional hazards regression models.

Results

After a median follow-up of 6.80 years (interquartile range: 5.90-8.00 years), a total of 317 (15.61%) participants developed new-onset CVD, including 198 (9.75%) incident coronary heart disease (CHD) and 119 (5.86%) incident stroke. After adjusting for as many relevant confounding factors as possible, each SD increase in METS-IR was associated with a 30% increased risk of new onset overall CVD events, a 32% increased risk of new onset CHD, and a 27% increased risk of new onset stroke. When METS-IR was assessed as tertiles, after adjustment for fully confounding factors, the highest tertiles versus the lowest tertiles were associated with a greater hazard of CVD (HR 2.05; 95% CI 1.52,-2.77), CHD (HR 1.96; 95% CI 1.35-2.84), and stroke (HR 2.24; 95% CI 1.35-3.72). The results of various subgroups and sensitivity analyses were similar. When METS-IR was added, CVD predictions were reclassified and identified more accurately than baseline models for the C-index, continuous net reclassification improvement, and integrated discrimination index. CHD and stroke showed similar results.

Conclusion

METS-IR is a powerful predictor of CVD and its subtypes in patients with hypertension and OSA, which can facilitate the identification of high-risk individuals and provide individualized CVD prevention.

A nonlinear associations of metabolic score for insulin resistance index with incident diabetes: A retrospective Chinese cohort study

Background

The Metabolic score of insulin resistance (METS-IR) has recently been accepted as a reliable alternative to insulin resistance (IR), which was demonstrated to be consistent with the hyperinsulinemic-euglycemic clamp. Few pieces of research have focused on the relationship between METS-IR and diabetes in Chinese. The purpose of this research was to explore the effect of METS-IR on new-onset diabetes in a large multicenter Chinese study.

Methods

At the baseline of this retrospective longitudinal research, 116855 participators were included in the Chinese cohort study administered from 2010 to 2016. The subjects were stratified by quartiles of METS-IR. To assess the effect of METS-IR on incident diabetes, the Cox regression model was constructed in this study. Stratification analysis and interaction tests were applied to detect the potential effect of METS-IR and incident diabetes among multiple subgroups. To verify whether there was a dose-response relationship between METS-IR and diabetes, a smooth curve fitting was performed. In addition, to further determine the performance of METS -IR in predicting incident diabetes, the receiver operating characteristic curve (ROC) was conducted.

Results

The average age of the research participators was 44.08 ± 12.93 years, and 62868 (53.8%) were men. METS-IR were significant relationship with new-onset diabetes after adjusting for possible variables (Hazard ratio [HR]: 1.077; 95% confidence interval [CI]: 1.073-1.082, P &lt; 0.0001), the onset risk for diabetes in Quartile 4 group was 6.261-fold higher than those in Quartile 1 group. Moreover, stratified analyses and interaction tests showed that interaction was detected in the subgroup of age, body mass index, systolic blood pressure, diastolic blood pressure, and fasting plasma glucose, there was no significant interaction between males and females. Furthermore, a dose-response correlation was detected between METS-IR and incident diabetes, the nonlinear relationship was revealed and the inflection point of METS-IR was calculated to be 44.43. When METS-IR≥44.43, compared with METS-IR &lt; 44.43, the trend was gradually saturated, with log-likelihood ratio test P &lt; 0.001. Additionally, the area under receiver operating characteristic of the METS-IR in predicting incident diabetes was 0.729, 0.718, and 0.720 at 3, 4, and 5 years, respectively.

Conclusions

METS-IR was correlated with incident diabetes significantly, and showed a nonlinear relationship. This study also found that METS-IR had good discrimination of diabetes.

Association between METS-IR and Prediabetes or Type 2 Diabetes Mellitus among Elderly Subjects in China: A Large-Scale Population-Based Study

The metabolic score for insulin resistance (METS-IR) was recently proposed as a non-insulin-based, novel index for assessing insulin resistance (IR) in the Western population. However, evidence for the link between METS-IR and prediabetes or type 2 diabetes mellitus (T2DM) among the elderly Chinese population was still limited. We aimed to investigate the associations between METS-IR and prediabetes or T2DM based on large-scale, cross-sectional, routine physical examination data. In a total of 18,112 primary care service users, an increased METS-IR was independently associated with a higher prevalence of prediabetes (adjusted odds ratio [aOR] = 1.457, 95% confidence interval [CI]: 1.343 to 1.581, p < 0.001) and T2DM (aOR = 1.804, 95%CI: 1.720 to 1.891, p < 0.001), respectively. The aOR for prediabetes in subjects with the highest quartile of METS-IR was 3.060-fold higher than that in those with the lowest quartile of METS-IR. The aOR for T2DM in subjects with the highest quartile of METS-IR was 6.226-fold higher than that in those with the lowest quartile of METS-IR. Consistent results were obtained in subgroup analyses. Our results suggested that METS-IR was significantly associated with both prediabetes and T2DM. The monitoring of METS-IR may add value to early identification of individuals at risk for glucose metabolism disorders in primary care.

Hepatic Steatosis Index and the Risk of Type 2 Diabetes Mellitus in China: Insights from a General Population-Based Cohort Study

Purpose

In the Chinese population, we looked at the relationship between the hepatic steatosis index (HSI) and the risk of type 2 diabetes mellitus (T2DM).

Methods

To evaluate the association between HSI and the risk of T2DM, Cox regression models were employed. Hazard ratios (HR) and 95 percent confidence intervals (CI) were computed. A stratified analysis with interaction testing was also carried out. Additionally, we evaluated the incremental predictive value of the HSI over the established risk factors using the C-statistic, the IDI, and the NRI.

Results

During a median follow-up period of 2.97 years, 433 (1.97%) participants developed new-onset T2DM. The smoothing curve fit plot showed a positive correlation between HSI and the risk of T2DM. After adjusting for all noncollinear variables, the risk of T2DM increased by 62% for every 1 standard deviation (SD) increase in HSI. Subgroup analysis indicated that higher HSI levels were associated with a higher risk of T2DM in those aged < 40 years. The addition of HSI enhanced the reclassification and discrimination of established risk factors, with an IDI of 0.027 and an NRI of 0.348 (both P < 0.001).

Conclusion

Our findings suggest that an elevated HSI is substantially associated with a greater risk of T2DM in the Chinese population. HSI has the potential to be an available and supplementary monitoring method for the management of T2DM risk stratification in the Chinese population.

Establishment and validation of a nomogram that predicts the risk of type 2 diabetes in obese patients with non-alcoholic fatty liver disease: a longitudinal observational study

OBJECTIVE

This study aimed to establish and validate a nomogram for better assessment of the risk of type 2 diabetes (T2D) in obese patients with non-alcoholic fatty liver disease (NAFLD) based on independent predictors.

METHODS

Of 1820 eligible participants from the NAGALA cohort enrolled in the study. Multivariate Cox regression was employed to construct the nomogram. The performance was assessed by area under the receiver operating characteristic curve (AUC), C-index, calibration curve, decision curve analysis, and Kaplan-Meier analysis.

RESULTS

Five predictors were selected from 17 variables. The AUC values at different time points all indicated that the model constructed with these five predictors had good predictive power. Decision curves indicated that the model could be applied to clinical applications.

CONCLUSIONS

We established and validated a reasonable, economical nomogram for predicting the risk of T2D in obese NAFLD patients. This simple clinical tool can help with risk stratification and thus contribute to the development of effective prevention programs against T2D in obese patients with NAFLD.

Dose-Response Associations of Metabolic Score for Insulin Resistance Index with Nonalcoholic Fatty Liver Disease among a Nonobese Chinese Population: Retrospective Evidence from a Population-Based Cohort Study

Purpose

This study is aimed at investigating the association between the metabolic score for insulin resistance (METS-IR) index and nonalcoholic fatty liver disease (NAFLD) in the nonobese population and its predictive value.

Methods

10730 nonobese subjects were selected from longitudinal cohort research conducted from January 2010 to December 2014. Cox proportional hazards models were employed to assess the relationship between METS-IR and new-onset NAFLD. Generalized additive models were used to identify nonlinear relationships. In addition, we performed subgroup analyses and interaction tests. The time-dependent receiver operating curve (ROC) and area under the ROC (AUC) were utilized to measure the discriminatory ability of METS-IR for new-onset NAFLD. Beyond clinical risk factors, the incremental predictive value of METS-IR was appraised using integrated discrimination improvement (IDI), C-index, and net reclassification index (NRI).

Results

Over a median period of 804.50 days of follow-up, 1859 (17.33%) participants had a new onset of NAFLD. After adjusting for confounders, the HR for new-onset NAFLD in the Q4 group was 6.40 compared with the Q1 group. When METS-IR was considered a continuous variable, the risk of NAFLD increased by 34% for every 1 SD increase in METS-IR. The smoothing curve shows the dose-response relationship between METS-IR and the presence of new-onset NAFLD. Using a two-piecewise linear regression model, we derived a METS-IR inflection point of 36. HRs were 1.31 on the left side of the inflection point and 1.04 on the right side of the inflection point (log-likelihood ratio test, P < 0.001). Subgroup analyses and interaction tests revealed an interaction between gender and SBP in the association between METS-IR and new-onset NAFLD. In the subgroup analysis of gender and SBP, we observed a higher risk of new-onset NAFLD in men and in those with abnormal SBP levels. We evaluated the ability of METS-IR to identify new-onset NAFLD at different time points. The AUCs at 1, 2, 3, and 4 years were 0.784, 0.756, 0.758, and 0.752, respectively, which represent good discrimination of new-onset NAFLD. The addition of METS-IR greatly improved the reclassification and differentiation of clinical risk factors, with an NRI of 0.276 and an IDI of 0.068. In addition, the addition of METS-IR increased the C-index from 0.719 to 0.771.

Conclusion

In a nonobese Chinese population, elevated METS-IR was independently associated with an enhanced risk of NAFLD development and a dose-response relationship existed. In addition, METS-IR might be a reliable indicator for screening individuals at risk for early NAFLD, especially in nonobese populations.

Association of Non-Insulin-Based Insulin Resistance Indices with Risk of Incident Prediabetes and Diabetes in a Chinese Rural Population: A 12-Year Prospective Study

OBJECTIVE

Three non-insulin-based insulin resistance (IR) indices, ie, triglyceride-glucose (TyG) index, triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio, and metabolic score for IR (METS-IR), were considered powerful and simplified alternatives for IR. However, evidence for the association between the three IR indices and incident type 2 diabetes mellitus (T2DM), especially impaired fasting glucose (IFG), remains limited. Therefore, this study aimed to explore the association among IR indices, incident IFG, and T2DM in a rural population cohort.

METHODS

We analyzed data from 2209 adults (aged 24-75 years) at baseline and from 1205 normoglycemic participants who were followed up. Cox proportional hazards models were used to evaluate the associations between the three indices and IFG or T2DM. Restricted cubic spline curves based on the Cox regression model were used to examine the association between baseline indices and incident T2DM.

RESULTS

For the baseline data, logistic analyses demonstrated that the TyG index, TG/HDL-C ratio, and METS-IR had a significantly positive correlation with IFG or T2DM after multivariable adjustment. During a median follow-up of 12.17 years, 157 incident cases of IFG and 97 incident cases of T2DM were noted. The risk of T2DM, but not IFG, was strongly associated with the baseline TyG index in the adjusted model, and participants with the TyG index in the third tertile had a higher risk of developing T2DM (adjusted hazards ratio, 2.84; 95% confidence intervals, 1.26-6.37; p for trend <0.001) than those in the lowest tertile (reference). Moreover, a linear relationship was observed between the TyG index and T2DM incidence. The TG/HDL-C ratio and METS-IR had no significant relationship with the risk of IFG or T2DM.

CONCLUSION

The TyG index is more useful than the TG/HDL-C ratio and METS-IR in predicting T2DM in the normoglycemic population.

Association Between Triglyceride Glucose Index-Waist Circumference and Risk of First Myocardial Infarction in Chinese Hypertensive Patients with Obstructive Sleep Apnoea: An Observational Cohort Study

PURPOSE

This study aimed to investigate the association between triglyceride glucose index-waist circumference (TyG-WC) and the risk of first myocardial infarction (MI) in Chinese hypertensive patients with obstructive sleep apnoea (OSA).

METHODS

This study was an observational cohort study. A total of 2224 Chinese hypertensive patients with OSA without a history of MI were included in this study. Hazard ratio (HR) and 95% confidence interval (CI) were estimated using multivariable Cox proportion hazard models. A generalized additive model was used to identify nonlinear relationships. Additionally, we performed hierarchical analysis and test for interaction.

RESULTS

During a median follow-up of 7.15 years, 85 incidents of MI developed. Overall, there was a positive association between TyG-WC and the risk of first MI. In the multivariable-adjusted model, the risk of MI increased with quartiles of the TyG-WC, the HR in quartile 4 versus quartile 1 was 4.29. A generalized additive model and a smooth curve fitting showed that there existed a similar J-shaped association between TyG-WC and the risk of first MI, with an inflection point at about 785.

CONCLUSION

Elevated levels of the baseline TyG-WC are associated with an increased risk of first MI. This finding indicates that the TyG-WC might be useful to identify the high risk of first MI in Chinese hypertensive patients with OSA.

Relationship of the metabolic score for insulin resistance and the risk of stroke in patients with hypertension: A cohort study

BACKGROUND

The current status of the dose-response relationship between the metabolic score for insulin resistance (METS-IR) and new-onset stroke in hypertensive patients and its subtypes is unclear. This study aimed to determine the association between METS-IR and incident stroke and its subtypes within a cohort of Chinese hypertensive patients.

METHODS

A total of 14032 hospitalized patients with hypertension from January 1, 2010, to December 31, 2021, were included in this retrospective cohort study. Cox models and restricted cubic splines were applied to determine the association between METS-IR and the risk of stroke.

RESULTS

During a median follow-up of 4.80 years, 1067 incident stroke cases occurred. Patients in the highest quartile group of METS-IR levels exhibited a higher risk of stroke (HR, 1.80; 95% CI, 1.50-2.17) and ischemic stroke (HR, 1.96; 95% CI, 1.60-2.42) than those in the lowest quartile group. However, no significant associations were observed between METS-IR and the risk of hemorrhagic stroke. Restricted cubic spline analysis suggested a nearly J-shaped association between METS-IR and risk of stroke and ischemic stroke (P for nonlinearity < 0.001). METS-IR did produce a significant improvement in the C statistic when added to the basic model (from 0.637 to 0.664, P < 0.001). Notably, the addition of METS-IR to the basic model resulted in a significant improvement in predicting incident total stroke and ischemic stroke.

CONCLUSIONS

This cohort study suggests a relationship between METS-IR and the risk of stroke and ischemic stroke. Further studies are required to elucidate the underlying mechanisms.