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Correlation between estimated glucose disposal rate, insulin resistance, and cardiovascular mortality among individuals with metabolic syndrome: a population-based analysis, evidence from NHANES 1999–2018

Diabetology & Metabolic Syndrome volume 17, Article number: 11 (2025) Cite this article

Abstract

Background

Estimated glucose disposal rate (eGDR), is an index of insulin resistance. It is intimately correlated with inflammation and endothelial dysfunction, both of which are contributory factors in the pathogenesis of cardiovascular disease (CVD) and premature mortality. This study aims to explore the correlation between eGDR and both all-cause and CVD-related mortality in adults with metabolic syndrome (MetS).

Methods

A total of 8215 subjects with MetS screened from the National Health and Nutrition Examination Survey (NHANES) during the period from 1999 to 2018 were evaluated for the predictive value of eGDR for CVD and all-cause mortality.

Results

Over a median follow-up for 8.3 years, a total of 1537 all-cause deaths (18.7%) and 467 CVD-related deaths (5.7%) were recorded. Logistic regression analyses revealed a significant inverse correlation between eGDR and the risk of having CVD (OR:0.845, 95%CI:0.807–0.884, p < 0.01). Multivariate Cox regression analysis and restricted cubic splines analysis demonstrated that eGDR is non-linearly correlated with both the mortality of CVD (HR: 0.906, 95% CI: 0.850–0.967, p = 0.003) and all-cause mortality (HR: 0.944, 95% CI: 0.912–0.977, p = 0.001), with an identified inflection point at 5.918. Further subgroup analyses indicated a more pronounced correlation between eGDR and all-cause mortality in individuals under 60 years old (HR: 0.893, 95%CI:0.823–0.970) or those with obesity (HR:0.891, 95%CI:0.839–0.946). Mediation analysis revealed that neutrophil to lymphocyte ratio mediated 8.9% of the correlation between eGDR and all-cause mortality.

Conclusion

This study demonstrates, for the first time, that a decrease in eGDR is associated with an increased risk of all-cause and CVD mortality in adults with MetS. The eGDR indices could serve as surrogate biomarkers for monitoring patients with MetS.

Introduction

Metabolic syndrome (MetS), is characterized by a constellation of metabolic abnormalities. It has been recognized as a major global public health concern due to its escalating prevalence worldwide [1,2,3]. In the United States, it is estimated that over 30% of the population, particularly older adults, has been affected by MetS [4, 5]. Accumulating evidence indicates that the constellation of symptoms correlated with MetS, including obesity, hypertension, and insulin resistance (IR), not only can elevate short- and long- term risks for chronic metabolic diseases, but also can contribute to premature mortality in later life [6,7,8,9]. Despite these findings, identifying prognostic biomarkers and developing personalized follow-up strategies for patients with MetS remain significant challenges [10].

A growing body of studies has underscored that IR, a fundamental pathogenic element of numerous metabolic disorders, has already existed in MetS [11]. Chronic hyperlipidemia resulting from IR can induce oxidative stress, exacerbate inflammatory responses, and promote the formation of foam cells [12]. Additionally, IR is correlated with the generation of glycosylation products and free radicals, which collectively reduce the bioavailability of nitric oxide (NO). Therefore, these processes damage the vascular endothelium, impair endothelium-dependent vasodilation, and contribute to the onset of various diseases [13]. Previous studies indicate that IR is a significant etiological factor for coronary heart disease (CHD), as a predictor for both CVD and overall mortality in patients with chronic kidney diseases, non-diabetes, post-menopausal females, and patients with diabetes [14,15,16,17]. It has been estimated that the prevention of IR can potentially reduce the mortality of CVD up to 40% [18]. Consequently, it was hypothesized that the measurement of IR can serve as a predictor for outcomes in patients with MetS.

Hyperinsulin–hyperglycemic clamp is considered as the gold standard for assessing IR, however, its complexity limits its practical application in clinical practice [19]. Instead, eGDR can incorporate obtainable clinical parameters easily, such as hypertension, waist circumference, and HbA1C. And it has been proposed as a straightforward surrogate marker for IR in patients with T1DM [20]. Previous studies have demonstrated that this method can exhibit high accuracy compared with the gold standard [20, 21]. Additionally, studies have applied eGDR to patients with T2DM, pre-diabetes, chronic kidney diseases, acute ischemic stroke, and general population earlier. This finding revealed a significant correlation between eGDR and outcomes, such as all-cause mortality, the mortality of CVD, and diabetic complications [22,23,24,25,26,27,28].

The correlation between eGDR, the risk of developing CVD, and both CVD and all-cause mortality in patients with MetS, particularly in countries with high MetS burdens, remains unknow. To address this knowledge gap, data from NHANES were utilized to explore the correlation between eGDR and the risk of developing CVD, as well as the predictive value of eGDR for all-cause and CVD-specific mortality in patients with MetS. Given that eGDR is an effective and inexpensive parameter, further exploration of the correlation between eGDR and mortality in the MetS population is crucial to promote its clinical use and enhance overall survival.

Methods

Research subjects and design

NHANES, conducted by NCHS [29], is a comprehensive study designed to assess the correlation between nutrition, health promotion, and disease prevention. This survey is conducted every two years by taking physical examinations, interviews, and various sections covering dietary, demographic, examinations, and laboratory data. Additional information regarding the NHANES database can be found at http://www.cdc.gov/nhanes.

For the present study, data were collected from NHANES during the period from 1999 to 2018. Subjects aged 18 years old and older were included (n = 59204). And those lacking follow-up data (n = 140), without diagnosis of MetS (n = 44067), and missing data including eGDR and the history of CVD (n = 6242) were excluded by exclusion criteria. Finally, a total of 8215 subjects were included in this study as samples (as shown in Fig. 1).

Fig. 1
figure 1

Flowchart of the sample selection from the 1999–2018 NHANES

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Measurement of eGDR

eGDR was calculated as a previously established formula: eGDR (mg/kg/min) = 21.158- (hypertension×3.407)-(0.551×HbA1C[%])-(0.09×waist circumference[cm]), where hypertension was coded as either 0 (absence of hypertension) or 1 (presence of hypertension) [30]. Previous studies have demonstrated that this method can exhibit high accuracy compared with the gold standard [20, 21]. Hypertension was defined as a physician diagnosis of hypertension, currently with antihypertensive medications, or the systolic and/or diastolic blood pressure ≥ 140/90mmHg [31]. According to previous studies [32], subjects were classified into four groups by their baseline of eGDR as < 4, 4–5.99, 6–7.99, and ≥ 8 mg/kg/min, with the lowest eGDR category (< 4 mg/kg/min) as the control group.

Definition of mets

MetS was defined according to established guidelines [33], with subjects meeting three or more of the following criteria: (1) HDL-C < 1.30 mmol/L in females and HDL-C < 1.04 mmol/L in males, or the medication for reducing HDL-C; (2) FBG > 100 mg/dL or the medication for diabetes; (3) TG > 1.7 mmol/L or the medication for elevating TG; (4) Waist circumference exceeding 88 cm in females or exceeding 102 cm in males; and (5) Blood pressure > 130/85 mmHg or the medication for hypertension.

Covariates

The analysis incorporated various covariates, including socioeconomic and demographic factors (age, poverty-income ratio (PIR), gender, marital status, and race), lifestyle variables (BMI, smoking, physical activities, and alcohol consumption), medical history (stroke, CHD, congestive heart failure, angina, and myocardial infarction), as well as test results (serum triglyceride, NLR, creatinine, urine albumin-to-creatinine ratio (UACR), ALT, uric acid, total cholesterol, AST, HDL-C, HbA1c, LDL-C). Less than 3% of values missed in total. Multiple imputation was performed for missing values. The definition for alcohol abuse and smoking was consistent with those previously reported [34]. eGFR was calculated as the CKD-EPI formula [35]. CKD was defined in accordance with current clinical guidelines as UACR exceeding 30 mg/g, less than 60 mL/min/1.73 m² of eGFR, or both of the two conditions [36, 37]. Subjects were classified as having CVD, with a positive medical history, for one or more conditions.

Ascertainment of all‑cause and CVD mortality

The data on CVD and all-cause mortality were sourced from the publicly available mortality records of NDI. The mortality of CVD was defined by the codes I13, I00-I09, I60-I69, I11, and I20-I51 of the International Classification of Diseases and Related Health Problems in the 10th edition (ICD-10). The observation was determined to be from the date of inspection at the mobile inspection center to the occurrence of death or December 31, 2019, whichever occurred first.

Statistical analyses

The data were presented as counts (weighted percentages) for categorical variables and mean ± SD for normally distributed variables. CVD and all-cause mortality in subjects stratified by various eGDR categories were assessed, and the differences in Kaplan–Meier survival curves was evaluated with the log-rank test. Additionally, the binary logistics and Cox regression were performed in the correlation between eGDR and the risk of having CVD, all-cause mortality and the mortality of CVD, respectively. Variables demonstrating clinical and statistical significance in the univariate analyses (p < 0.05) were incorporated into the multivariate analyses. Three models were employed in the analyses: Model 1 was unadjusted. Model 2 was adjusted for gender and age. Model 3, the final multivariable model, was adjusted for race, TG, NLR, alcohol abuse, BMI, smoking, TC, moderate physical activities, CVD, diabetes, CKD, ALT, PIR, AST, marital status, uric, and LDL-C. The dose-response correlation between mortality outcomes and eGDR was explored through restricted cubic spline (RCS) curves, with a particular focus on potential non-linearity. In addition, subgroup analyses were conducted to ascertain whether the correlation between eGDR and both CVD and all-cause mortality differed in subjects with varying characteristics. Subsequently, mediation analyses were conducted by using the mediation package, and the confidence interval of the mediation effect was evaluated using Bootstrap method, to quantify the proportion of the mediating effect accounted for by NLR. Finally, the robustness of the findings was evaluated through sensitivity analyses. Subjects with eGDR in the upper and lower 2.5% were excluded to mitigate the influence of potential outliers. Data analysis was conducted with R software and Free Statistics software, with the statistical significance defined as a two-sided P value of less than 0.05.

Results

Characteristics of research population

The analytic samples included 8215 subjects (at the mean age of 57.0 years old; 49.5% were males). Over a median follow-up interval for 8.3 years (interquartile range: 4.4–12.4 years), 1537 subjects (18.7%) died, including 467 (5.7%) for cardiovascular causes. Table 1 delineates the baseline characteristics of subjects stratified by eGDR. It is easy to see that both all-cause mortality and CVD mortality broadly show a gradual decrease as the eGDR indexes rise [all-cause mortality (23.2% vs. 20.3% vs. 18.6% vs. 14.2%, P < 0.001) and CVD mortality (7.6% vs. 6.7% vs. 5.8% vs. 3.2%, P < 0.001)]. Subjects in the higher eGDR group, indicative of lower IR, generally younger, married or living with other family members, had a lower WC, BMI, and a lower history of diabetes, hypertension, CVD, and CKD, compared to those in the lower eGDR group. Significant differences in biochemical indexes were observed across eGDR groups (Table 2). Specifically, the lower eGDR group exhibited elevated levels of NLR, ALT, HbA1c, TG, and uric acid compared to the higher eGDR group (all p < 0.05).

Table 1 Baseline characteristics of all participants according to categorised four groups of eGDR
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Table 2 Baseline laboratory characteristics of all participants according to categorised four groups of eGDR
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Correlation between eGDR and the prevalence of CVD

Table 3 presents the correlation between the risk of having CVD and eGDR among subjects with MetS. In the fully adjusted Model 3, an elevated eGDR was significantly correlated with a decreased OR for CVD (OR = 0.845, 95% CI: 0.807–0.887, p < 0.001). Additionally, RCS analysis (as shown in Fig. S1) indicated a linearly correlation between eGDR and the risk of having CVD.

Table 3 Associations between eGDR and risk of cardiovascular diseases in participants with metabolic syndrome
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Correlation between eGDR and mortality in subjects with MetS

Kaplan-Meier survival curves indicated increased all-cause and CVD-related survival in the higher eGDR quartiles group (p < 0.001) (as shown in Fig. 2). To evaluate the correlation between mortality and eGDR, a Cox regression model was employed. Table 4 presents the impact of eGDR on all-cause and CVD related mortality across various statistical models in subjects with MetS. In Model 3, eGDR, treated as a continuous variable, demonstrated an inverse correlation with both CVD and all-cause mortality, with HRs and 95% CIs of 0.906 (0.850–0.967) and 0.944 (0.912–0.977), respectively. In the fully adjusted Model 3, HR and 95% CI for subjects with MetS in the eGDR groups of 4–6, 6–8, and > 8 mg/kg/min were 0.710 (0.594–0.849), 0.761 (0.611–0.947), and 0.644 (0.514–0.808), compared to the control group with eGDR < 4 mg/kg/min, respectively, for all-cause mortality (p for trend = 0.006), and 0.736 (0.535–0.980), 0.816 (0.552–1.207), and 0.525 (0.344–0.803), for CVD related mortality (P for trend = 0.011), respectively. Cox proportional hazards regression analysis, incorporating RCS analysis, demonstrated a non-linear correlation between lower eGDR levels and an elevated risk of all-cause and CVD related mortality (as shown in Fig. 3). With a two-piecewise Cox regression model, a threshold eGDR value of 5.918 was identified for both all-cause and CVD related mortality (Table 5).

Fig. 2
figure 2

Kaplan–Meier curves depicting survival rate and the number (%) of a MetS population stratified by eGDR groups. (A) All-cause mortality. (B) CVD mortality

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Table 4 Cox regression analyses for the association between all-cause mortality, CVD mortality and eGDR
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Fig. 3
figure 3

Dose-response curve of eGDR and all-cause mortality (A) and CVD mortality (B) using restricted cubic splines

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Table 5 Threshold effect analysis of eGDR on all-cause mortality using the two-piecewise Cox regression model
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Subgroup analysis

As illustrated in Fig. 4A, subgroup analyses indicated that the correlation between eGDR and CVD related mortality remains unaltered by subjects’ age, gender, BMI, history of diabetes, hypertension, CVD and CKD. However, the correlation between all-cause mortality with a lower eGDR was stronger in subjects under 60 years old or obese, with HR (95% CI) of 0.804 (0.720–0.899) and 0.896 (0.851–0.943), respectively (as shown in Fig. 4B and Fig. S2-3).

Fig. 4
figure 4

Exploratory stratified analysis of the associations between eGDR and All-cause(A) or CVD mortality(B)

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Mediating role of inflammation related indexes

Figure 5 illustrates that NLR mediated 8.9% of the correlation between eGDR and all-cause mortality. The results of mediation analysis, encompassing indirect effects, direct effects, mediation ratios, and total effects, are detailed in Table 6.

Fig. 5
figure 5

The mediating effect of NLR on the relationship between eGDR and all-cause mortality

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Table 6 Mediation analysis of NLR in the association between eGDR and all-cause mortality
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Sensitivity analyses

The findings from the sensitivity analysis are detailed in Table S1. Exclusion of subjects within the upper and lower 2.5% of eGDR, the correlation between eGDR and both CVD and all-cause mortality persisted consistently, with HRs and 95% CIs of 0.922 (0.865–0.984) and 0.952 (0.920–0.985), respectively.

Discussion

The nationally representative data from Americans with MetS were included in this study to demonstrate that IR, as indicated by a lower eGDR, is correlated with a higher incidence of CVD. Additionally, a lower eGDR can be non-linearly correlated with elevated CVD and all-cause mortality in subjects with MetS, with an identified inflection point at 5.918. Subgroup analyses indicated that the correlation between eGDR and all-cause mortality were particularly pronounced among subjects under 60 years old or obese. Moreover, the mediation analysis demonstrated that NLR can partially mediate the correlation between eGDR and all-cause mortality. The findings suggested that eGDR can serve as a valuable surrogate biomarker for the clinical management and follow-up of patients with MetS.

Given that MetS accounts for a substantial portion of the general population and significantly elevates the risk of various diseases, thereby having adverse effects on health outcomes in later life, it is imperative to identify the potential risk and prognostic factors. Such identification can yield cost-saving benefits in the management of this specific population [38]. Current evidence indicates that IR can play a pivotal role in the onset of MetS. Consequently, pathophysiological factors correlated with IR have been examined within metabolic disorders of patients with MetS.

eGDR was initially assessed for IR in patients with T1DM. Recently, several studies have explored the role of eGDR in both individuals without diabetes and those with T2DM [14, 39,40,41]. In a comprehensive registry study conducted in Sweden, Zabala et al. [42] identified that patients with T2DM, with eGDR ≥ 8 mg/kg/min, had a 32% reduction in all-cause mortality and a 40% reduction in the risk of having stroke. This finding underscored the significant correlation between eGDR and vascular events [21]. Additionally, the study by Liu et al. demonstrated that a lower eGDR was strongly correlated with adverse prognostic outcomes in non-diabetic patients with PCI [39]. In a cohort study in China, Sun et al. demonstrated a robust correlation between a lower eGDR and a significantly elevated risk of long-term all-cause mortality [42]. Furthermore, previous research has found a correlation between eGDR and left ventricular hypertrophy as well as ischemic heart diseases in the general population [43, 44]. However, the correlation between eGDR, the risk of having CVD, and both CVD and all-cause mortality in patients with MetS has not been explored. To the best of our knowledge, this study is the first to establish the independent prognostic significance of eGDR in Americans diagnosed with MetS.

A significant interaction effect was identified between eGDR and age, as well as BMI, suggesting that the correlation between eGDR and all-cause mortality was particularly evident in younger individuals and those obese. It has been broadly accepted that younger and obese individuals exhibit a higher susceptibility to having IR [45, 46], resulting in decreased eGDR in this demographic [21, 32, 47]. Moreover, younger individuals exhibiting lower eGDR may experience early-onset IR, resulting in extended exposure to metabolic stress. This potentially accelerates the progression of vascular damage and elevates the mortality risk. Furthermore, it is plausible that as one ages, there might be more risk factors for cardiovascular disease, making the predictive capabilities of eGDR indices less potent in older populations. Additionally, obese individuals often exhibit visceral fat accumulation, which can produce inflammatory mediators such as tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6). These mediators may further induce low-grade systemic inflammation [48, 49], thereby contributing to the development of IR and atherosclerosis [50], ultimately increasing cardiovascular risk [51].

As far as we know, this study is the first to reveal a non-linear correlation between the baseline of eGDR and mortality, with a turning point at 5.918, which may be attributed to compensatory mechanisms, such as augmented insulin secretion, which can sustain normoglycemia during the initial phases of IR [52]. Nonetheless, when eGDR declines beneath a critical threshold, these metabolic mechanisms become insufficient, resulting in impaired metabolic regulation and an elevated risk of cardiovascular complications. These findings emphasize the importance for clinicians to pay particular attention to individuals with eGDR < 5.918. Hence, it is advantageous to identify individuals at early risk of death by evaluating eGDR, as this facilitates to implement preventive measures and treatment before the onset of the disease.

The precise mechanism linking eGDR indices to increased mortality remains unidentified; However, IR may play a pivotal role in mediating the correlation between eGDR and mortality. IR is a pathophysiological condition characterized by reduced insulin sensitivity in muscles and liver tissues, leading to decreased insulin bioavailability, impaired glucose uptake, resulting in hyperglycemia [53]. The hyperglycemic state further induces inflammation, as evidenced by elevated inflammatory cytokines such as TNF-α, IL-6, and IL-8, further leading to the proliferation of smooth muscle cells and the deposition of collagen, ultimately leading to vascular senescence and sclerosis [54,55,56]. IR also can promote the production of fibrinogen activator inhibitor-1, which further contributes to thrombosis [57], in addition to elevated expression of adhesion-inducing factor and thromboxane A2-dependent tissue factor in platelets, which further promotes platelet activation [58]. IR-induced systemic dyslipidemia may also contribute to the development of atherosclerosis [59]. IR is also correlated with enhanced oxidative stress, and excessive levels of oxidative stress are thought to be a key factor in stimulating the proliferation of smooth muscle cells and the deposition of collagen into damaged endothelial cell sites [60,61,62]. Inadequate bioavailability of nitric oxide in the endothelium further contributes to impaired endothelial function and aggravated endothelial cell damage [13, 63].

Neutrophil and lymphocyte counts are typically evaluated in blood tests due to the simplicity and cost-effectiveness, providing significant insights into systemic inflammatory status and the equilibrium between acquired immunity (lymphocytes) and natural immunity (neutrophils) [64]. The findings indicate that NLR partially mediates the correlation between IR (as determined by the lower eGDR) and mortality, suggesting that monitoring NLR in subjects with MetS with lower eGDR is crucial. IR can trigger oxidative stress, exacerbate inflammatory responses as indicated by elevated NLR, facilitate the formation of foam cells, and impair endothelial function, ultimately contributing to the development of various cardiovascular diseases [12]. Therefore, it is reasonable to speculate that in patients with MetS accompanied by elevated NLR and decreased eGDR, the combined use of hypoglycemic medications and anti-inflammatory drugs might synergistically contribute to improved survival outcomes.

Several noteworthy strengths of the present study should be highlighted. Firstly, this is the inaugural study to comprehensively evaluate the correlation between eGDR and both all-cause and CVD related mortality in patients with MetS. The findings underscore the promising potential of eGDR in the clinical management of MetS. Secondly, the population-based, prospective study design enables the determination of robust evidence regarding the correlation between eGDR and mortality in patients with MetS. Nonetheless, certain limitations of this study warrant the consideration. Firstly, the NHANES database depends on death certificates, and the precision of coding causes of death is susceptible to human reporting errors, such as assembly errors, inaccurate determinations of cause of death, and misclassifications of demographic information. Secondly, this study was confined to American subjects, thereby restricting the applicability of the findings to other ethnic groups. Thirdly, consecutive changes in eGDR during the follow-ups were not recorded. Finally, when considering several confounding variables, some potential confounding factors, including environmental factors and dietary patterns, were not evaluated. Despite these limitations, the findings hold clinical significance, as it has established a correlation between eGDR and the risk of having CVD as well as all-cause mortality within patients with MetS.

Conclusion

In conclusion, this study indicates that IR, as evaluated by eGDR, is correlated with increased odds of CVD in patients with MetS. More importantly, a lower eGDR independently predicts an increased risk of the mortality of CVD and all-cause mortality in American adults with MetS. Therefore, it is possible to manage the prognosis of patients with MetS according to eGDR and to facilitate the development of individualized treatment plans, including lifestyle modifications or pharmacological interventions such as metformin or SGLT2 inhibitors, to enhance survival outcomes. Future research should explore longitudinal alterations in eGDR and its correlation with cardiovascular events.

Supplementary Figure S1. Dose-response curve of eGDR and risk of CVD using restricted cubic splines.

Data availability

The datasets generated and analysis during the current study are available in the NHANES, www.cdc.gov/nchs/NHANEs/.

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Acknowledgements

We would like to thank the NHANES database for providing the data source for this study.

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Authors and Affiliations

  1. Department of Cardiology, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, China

    Dawei Xing

  2. Department of Endocrinology, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Lucheng District, Wenzhou, Zhejiang Province, P. R. China

    Jing Xu & Xiaolu Weng

  3. Department of Ultrasound, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, China

    Xiaochun Weng

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  1. Dawei Xing
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  2. Jing Xu
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  3. Xiaochun Weng
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  4. Xiaolu Weng
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Contributions

XLW designed the study; JX, and XCW collected biochemical data; DWX drafted the manuscript. All authors read and approved the final manuscript.

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Correspondence to Xiaolu Weng.

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The National Center for Health Statistics Ethics Review Board has approved the implementation of NHANES.

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Xing, D., Xu, J., Weng, X. et al. Correlation between estimated glucose disposal rate, insulin resistance, and cardiovascular mortality among individuals with metabolic syndrome: a population-based analysis, evidence from NHANES 1999–2018. Diabetol Metab Syndr 17, 11 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13098-024-01574-8

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s13098-024-01574-8

Keywords

Diabetology & Metabolic Syndrome

ISSN: 1758-5996

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