A study on the association between estimated glucose disposal rate and the risk of cardiovascular disease incidence in middle-aged and elderly individuals with and without diabetes_West China Medical Journal

Authors：

KONG Youli ^1,2 , ZHONG Wen ^1,2 , WANG Lu ^1,2 ,  WEI Quan ^1,2

1. Rehabilitation Medicine Center and Institute of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;
2. Key Laboratory of Rehabilitation Medicine in Sichuan Province, Chengdu, Sichuan 610041, P. R. China;

Corresponding author：

WEI Quan, Email: weiquan@scu.edu.cn

Keywords：

Estimated glucose disposal rate; diabetes; cardiovascular disease; China Health and Retirement Longitudinal Study

DOI：

10.7507/1002-0179.202502073

Video：

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Objective To investigate the relationship between estimated glucose disposal rate (eGDR) and the incidence of cardiovascular disease (CVD) in individuals without diabetes and those with diabetes. Methods Participants were drawn from the China Health and Retirement Longitudinal Study from 2011 to 2018. Participants were divided into four subgroups based on quartiles of baseline eGDR. In this study, data were analyzed using Kaplan-Meier survival curves, Cox proportional hazards models, restricted cubic spline curves, subgroup analyses, and receiver operator characteristic curves. Results A total of 6 283 participants were included. Among them, 47.2% are male, with an average age of (59.6±9.5) years; 285 cases (4.5%) had diabetes; there were 1 571 cases in Q1 group, 1 572 cases in Q2 group, 1 583 cases in Q3 group, and 1 557 cases in Q4 group. A total of 761 CVD events occurred. According to the multivariate-adjusted model, baseline eGDR levels were significantly associated with the risk of CVD events (P<0.05). Baseline eGDR was associated with the risk of CVD events in individuals without diabetes (P<0.05), but the results were not entirely consistent for those with diabetes [CVD: hazard ratio (HR)=0.85, 95% confidence interval (CI) (0.75, 0.96), P=0.012; heart disease: HR=0.91, 95%CI (0.78, 1.06), P=0.211; stroke: HR=0.74, 95%CI (0.58, 0.93), P=0.012]. Restricted cubic spline curves revealed significant negative linear relationships between baseline eGDR and CVD, heart disease, and stroke. Subgroup analyses with interaction testing revealed that the association between baseline eGDR and CVD was not modified by age, sex, smoking status, alcohol consumption, or dyslipidemia. Receiver operator characteristic curves further demonstrated that baseline eGDR exhibited significantly better predictive performance than the triglyceride-glucose (TyG) index, obesity indices, and the TyG index-obesity composite. Conclusions Low level baseline eGDR is associated with an increased risk of CVD in individuals without diabetes. This finding may help improve risk stratification to guide preventive measures and enhance the prognosis of CVD.

Citation： KONG Youli, ZHONG Wen, WANG Lu, WEI Quan. A study on the association between estimated glucose disposal rate and the risk of cardiovascular disease incidence in middle-aged and elderly individuals with and without diabetes. West China Medical Journal, 2025, 40(8): 1234-1241. doi: 10.7507/1002-0179.202502073 Copy

1.	Liu S, Li Y, Zeng X, et al. Burden of cardiovascular diseases in China, 1990-2016: findings from the 2016 global burden of disease study. JAMA Cardiol, 2019, 4(4): 342-352.
2.	Roberts CK, Hevener AL, Barnard RJ. Metabolic syndrome and insulin resistance: underlying causes and modification by exercise training. Compr Physiol, 2013, 3(1): 1-58.
3.	James D, Umekwe N, Edeoga C, et al. Multi-year reproducibility of hyperinsulinemic euglycemic clamp-derived insulin sensitivity in free-living adults: association with incident prediabetes in the POP-ABC study. Metabolism, 2020, 109: 154263.
4.	Bonora E, Targher G, Alberiche M, et al. Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity. Diabetes Care, 2000, 23(1): 57-63.
5.	Matthews DR, Hosker JP, Rudenski AS, et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia, 1985, 28(7): 412-419.
6.	Cai W, Xu J, Wu X, et al. Association between triglyceride-glucose index and all-cause mortality in critically ill patients with ischemic stroke: analysis of the MIMIC-IV database. Cardiovasc Diabetol, 2023, 22(1): 138.
7.	Peng J, Zhang Y, Zhu Y, et al. Estimated glucose disposal rate for predicting cardiovascular events and mortality in patients with non-diabetic chronic kidney disease: a prospective cohort study. BMC Med, 2024, 22(1): 411.
8.	Li H, Zuo Y, Qian F, et al. Triglyceride-glucose index variability and incident cardiovascular disease: a prospective cohort study. Cardiovasc Diabetol, 2022, 21(1): 105.
9.	Cheng Y, Fang Z, Zhang X, et al. Association between triglyceride glucose-body mass index and cardiovascular outcomes in patients undergoing percutaneous coronary intervention: a retrospective study. Cardiovasc Diabetol, 2023, 22(1): 75.
10.	Wang Z, Zhu J, Xuan S, et al. Associations of estimated glucose disposal rate with frailty progression: results from two prospective cohorts. Cardiovasc Diabetol, 2025, 24(1): 81.
11.	Zabala A, Darsalia V, Lind M, et al. Estimated glucose disposal rate and risk of stroke and mortality in type 2 diabetes: a nationwide cohort study. Cardiovasc Diabetol, 2021, 20(1): 202.
12.	Liu C, Liu X, Ma X, et al. Predictive worth of estimated glucose disposal rate: evaluation in patients with non-ST-segment elevation acute coronary syndrome and non-diabetic patients after percutaneous coronary intervention. Diabetol Metab Syndr, 2022, 14(1): 145.
13.	Penno G, Solini A, Orsi E, et al. Insulin resistance, diabetic kidney disease, and all-cause mortality in individuals with type 2 diabetes: a prospective cohort study. BMC Med, 2021, 19(1): 66.
14.	Han XD, Li YJ, Wang P, et al. Insulin resistance-varying associations of adiposity indices with cerebral perfusion in older adults: a population-based study. J Nutr Health Aging, 2023, 27(3): 219-227.
15.	Yao Y, Wang B, Geng T, et al. The association between TyG and all-cause/non-cardiovascular mortality in general patients with type 2 diabetes mellitus is modified by age: results from the cohort study of NHANES 1999-2018. Cardiovasc Diabetol, 2024, 23(1): 43.
16.	《中国心血管健康与疾病报告 2022》编写组. 《中国心血管健康与疾病报告 2022》要点解读. 中国心血管杂志, 2023, 28(4): 297-312.
17.	Elagizi A, Kachur S, Carbone S, et al. A review of obesity, physical activity, and cardiovascular disease. Curr Obes Rep, 2020, 9(4): 571-581.
18.	Kee CC, Sumarni MG, Lim KH, et al. Association of BMI with risk of CVD mortality and all-cause mortality. Public Health Nutr, 2017, 20(7): 1226-1234.
19.	Zhang X, Ding L, Hu H, et al. Associations of body-roundness index and sarcopenia with cardiovascular disease among middle-aged and older adults: findings from CHARLS. J Nutr Health Aging, 2023, 27(11): 953-959.
20.	Weiler Miralles CS, Wollinger LM, Marin D, et al. Waist-to-height ratio (WHtR) and triglyceride to HDL-C ratio (TG/HDL-c) as predictors of cardiometabolic risk. Nutr Hosp, 2015, 31(5): 2115-2121.
21.	Dong B, Chen Y, Yang X, et al. Estimated glucose disposal rate outperforms other insulin resistance surrogates in predicting incident cardiovascular diseases in cardiovascular-kidney-metabolic syndrome stages 0-3 and the development of a machine learning prediction model: a nationwide prospective cohort study. Cardiovasc Diabetol, 2025, 24(1): 163.
22.	Hu Y, Peng W, Ren R, et al. Sarcopenia and mild cognitive impairment among elderly adults: the first longitudinal evidence from CHARLS. J Cachexia Sarcopenia Muscle, 2022, 13(6): 2944-2952.
23.	Zhao Y, Hu Y, Smith JP, et al. Cohort profile: the China Health and Retirement Longitudinal Study (CHARLS). Int J Epidemiol, 2014, 43(1): 61-68.
24.	Chen J, Zhang F, Zhang Y, et al. Trajectories network analysis of chronic diseases among middle-aged and older adults: evidence from the China Health and Retirement Longitudinal Study (CHARLS). BMC Public Health, 2024, 24(1): 559.
25.	Williams B, Mancia G, Spiering W, et al. 2018 ESC/ESH Guidelines for the management of arterial hypertension. Eur Heart J, 2018, 39(33): 3021-3104.
26.	Yu J, Yi Q, Chen G, et al. The visceral adiposity index and risk of type 2 diabetes mellitus in China: a national cohort analysis. Diabetes Metab Res Rev, 2022, 38(3): e3507.
27.	Guo D, Wu Z, Xue F, et al. Association between the triglyceride-glucose index and impaired cardiovascular fitness in non-diabetic young population. Cardiovasc Diabetol, 2024, 23(1): 39.
28.	Lebovitz HE. Insulin resistance: definition and consequences. Exp Clin Endocrinol Diabetes, 2001, 109(Suppl 2): S135-S148.
29.	Tagi VM, Mainieri F, Chiarelli F. Hypertension in patients with insulin resistance: etiopathogenesis and management in children. Int J Mol Sci, 2022, 23(10): 5814.
30.	Sadeghi A, Niknam M, Momeni-Moghaddam MA, et al. Crosstalk between autophagy and insulin resistance: evidence from different tissues. Eur J Med Res, 2023, 28(1): 456.
31.	Lu Q, Chen B, Li A, et al. The correlation between HOMA-IR and cardiometabolic risk index among different metabolic adults: a cross-sectional study. Acta Diabetol, 2025, 62(1): 49-57.
32.	Zhang Q, Xiao S, Jiao X, et al. The triglyceride-glucose index is a predictor for cardiovascular and all-cause mortality in CVD patients with diabetes or pre-diabetes: evidence from NHANES 2001-2018. Cardiovasc Diabetol, 2023, 22(1): 279.
33.	Lee JH, Jeon S, Joung B, et al. Associations of homeostatic model assessment for insulin resistance trajectories with cardiovascular disease incidence and mortality. Arterioscler Thromb Vasc Biol, 2023, 43(9): 1719-1728.
34.	Liu C, Liang D, Xiao K, et al. Association between the triglyceride-glucose index and all-cause and CVD mortality in the young population with diabetes. Cardiovasc Diabetol, 2024, 23(1): 171.
35.	He HM, Xie YY, Chen Q, et al. The additive effect of the triglyceride-glucose index and estimated glucose disposal rate on long-term mortality among individuals with and without diabetes: a population-based study. Cardiovasc Diabetol, 2024, 23(1): 307.
36.	Song J, Ma R, Yin L. Associations between estimated glucose disposal rate and arterial stiffness and mortality among US adults with non-alcoholic fatty liver disease. Front Endocrinol (Lausanne), 2024, 15: 1398265.
37.	Xu YX, Pu SD, Zhang YT, et al. Insulin resistance is associated with the presence and severity of retinopathy in patients with type 2 diabetes. Clin Exp Ophthalmol, 2024, 52(1): 63-77.
38.	Kosmas CE, Bousvarou MD, Kostara CE, et al. Insulin resistance and cardiovascular disease. J Int Med Res, 2023, 51(3): 3000605231164548.
39.	Hill MA, Yang Y, Zhang L, et al. Insulin resistance, cardiovascular stiffening and cardiovascular disease. Metabolism, 2021, 119: 154766.
40.	Li ZY, Wang P, Miao CY. Adipokines in inflammation, insulin resistance and cardiovascular disease. Clin Exp Pharmacol Physiol, 2011, 38(12): 888-896.

1. Liu S, Li Y, Zeng X, et al. Burden of cardiovascular diseases in China, 1990-2016: findings from the 2016 global burden of disease study. JAMA Cardiol, 2019, 4(4): 342-352.
2. Roberts CK, Hevener AL, Barnard RJ. Metabolic syndrome and insulin resistance: underlying causes and modification by exercise training. Compr Physiol, 2013, 3(1): 1-58.
3. James D, Umekwe N, Edeoga C, et al. Multi-year reproducibility of hyperinsulinemic euglycemic clamp-derived insulin sensitivity in free-living adults: association with incident prediabetes in the POP-ABC study. Metabolism, 2020, 109: 154263.
4. Bonora E, Targher G, Alberiche M, et al. Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity. Diabetes Care, 2000, 23(1): 57-63.
5. Matthews DR, Hosker JP, Rudenski AS, et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia, 1985, 28(7): 412-419.
6. Cai W, Xu J, Wu X, et al. Association between triglyceride-glucose index and all-cause mortality in critically ill patients with ischemic stroke: analysis of the MIMIC-IV database. Cardiovasc Diabetol, 2023, 22(1): 138.
7. Peng J, Zhang Y, Zhu Y, et al. Estimated glucose disposal rate for predicting cardiovascular events and mortality in patients with non-diabetic chronic kidney disease: a prospective cohort study. BMC Med, 2024, 22(1): 411.
8. Li H, Zuo Y, Qian F, et al. Triglyceride-glucose index variability and incident cardiovascular disease: a prospective cohort study. Cardiovasc Diabetol, 2022, 21(1): 105.
9. Cheng Y, Fang Z, Zhang X, et al. Association between triglyceride glucose-body mass index and cardiovascular outcomes in patients undergoing percutaneous coronary intervention: a retrospective study. Cardiovasc Diabetol, 2023, 22(1): 75.
10. Wang Z, Zhu J, Xuan S, et al. Associations of estimated glucose disposal rate with frailty progression: results from two prospective cohorts. Cardiovasc Diabetol, 2025, 24(1): 81.
11. Zabala A, Darsalia V, Lind M, et al. Estimated glucose disposal rate and risk of stroke and mortality in type 2 diabetes: a nationwide cohort study. Cardiovasc Diabetol, 2021, 20(1): 202.
12. Liu C, Liu X, Ma X, et al. Predictive worth of estimated glucose disposal rate: evaluation in patients with non-ST-segment elevation acute coronary syndrome and non-diabetic patients after percutaneous coronary intervention. Diabetol Metab Syndr, 2022, 14(1): 145.
13. Penno G, Solini A, Orsi E, et al. Insulin resistance, diabetic kidney disease, and all-cause mortality in individuals with type 2 diabetes: a prospective cohort study. BMC Med, 2021, 19(1): 66.
14. Han XD, Li YJ, Wang P, et al. Insulin resistance-varying associations of adiposity indices with cerebral perfusion in older adults: a population-based study. J Nutr Health Aging, 2023, 27(3): 219-227.
15. Yao Y, Wang B, Geng T, et al. The association between TyG and all-cause/non-cardiovascular mortality in general patients with type 2 diabetes mellitus is modified by age: results from the cohort study of NHANES 1999-2018. Cardiovasc Diabetol, 2024, 23(1): 43.
16. 《中国心血管健康与疾病报告 2022》编写组. 《中国心血管健康与疾病报告 2022》要点解读. 中国心血管杂志, 2023, 28(4): 297-312.
17. Elagizi A, Kachur S, Carbone S, et al. A review of obesity, physical activity, and cardiovascular disease. Curr Obes Rep, 2020, 9(4): 571-581.
18. Kee CC, Sumarni MG, Lim KH, et al. Association of BMI with risk of CVD mortality and all-cause mortality. Public Health Nutr, 2017, 20(7): 1226-1234.
19. Zhang X, Ding L, Hu H, et al. Associations of body-roundness index and sarcopenia with cardiovascular disease among middle-aged and older adults: findings from CHARLS. J Nutr Health Aging, 2023, 27(11): 953-959.
20. Weiler Miralles CS, Wollinger LM, Marin D, et al. Waist-to-height ratio (WHtR) and triglyceride to HDL-C ratio (TG/HDL-c) as predictors of cardiometabolic risk. Nutr Hosp, 2015, 31(5): 2115-2121.
21. Dong B, Chen Y, Yang X, et al. Estimated glucose disposal rate outperforms other insulin resistance surrogates in predicting incident cardiovascular diseases in cardiovascular-kidney-metabolic syndrome stages 0-3 and the development of a machine learning prediction model: a nationwide prospective cohort study. Cardiovasc Diabetol, 2025, 24(1): 163.
22. Hu Y, Peng W, Ren R, et al. Sarcopenia and mild cognitive impairment among elderly adults: the first longitudinal evidence from CHARLS. J Cachexia Sarcopenia Muscle, 2022, 13(6): 2944-2952.
23. Zhao Y, Hu Y, Smith JP, et al. Cohort profile: the China Health and Retirement Longitudinal Study (CHARLS). Int J Epidemiol, 2014, 43(1): 61-68.
24. Chen J, Zhang F, Zhang Y, et al. Trajectories network analysis of chronic diseases among middle-aged and older adults: evidence from the China Health and Retirement Longitudinal Study (CHARLS). BMC Public Health, 2024, 24(1): 559.
25. Williams B, Mancia G, Spiering W, et al. 2018 ESC/ESH Guidelines for the management of arterial hypertension. Eur Heart J, 2018, 39(33): 3021-3104.
26. Yu J, Yi Q, Chen G, et al. The visceral adiposity index and risk of type 2 diabetes mellitus in China: a national cohort analysis. Diabetes Metab Res Rev, 2022, 38(3): e3507.
27. Guo D, Wu Z, Xue F, et al. Association between the triglyceride-glucose index and impaired cardiovascular fitness in non-diabetic young population. Cardiovasc Diabetol, 2024, 23(1): 39.
28. Lebovitz HE. Insulin resistance: definition and consequences. Exp Clin Endocrinol Diabetes, 2001, 109(Suppl 2): S135-S148.
29. Tagi VM, Mainieri F, Chiarelli F. Hypertension in patients with insulin resistance: etiopathogenesis and management in children. Int J Mol Sci, 2022, 23(10): 5814.
30. Sadeghi A, Niknam M, Momeni-Moghaddam MA, et al. Crosstalk between autophagy and insulin resistance: evidence from different tissues. Eur J Med Res, 2023, 28(1): 456.
31. Lu Q, Chen B, Li A, et al. The correlation between HOMA-IR and cardiometabolic risk index among different metabolic adults: a cross-sectional study. Acta Diabetol, 2025, 62(1): 49-57.
32. Zhang Q, Xiao S, Jiao X, et al. The triglyceride-glucose index is a predictor for cardiovascular and all-cause mortality in CVD patients with diabetes or pre-diabetes: evidence from NHANES 2001-2018. Cardiovasc Diabetol, 2023, 22(1): 279.
33. Lee JH, Jeon S, Joung B, et al. Associations of homeostatic model assessment for insulin resistance trajectories with cardiovascular disease incidence and mortality. Arterioscler Thromb Vasc Biol, 2023, 43(9): 1719-1728.
34. Liu C, Liang D, Xiao K, et al. Association between the triglyceride-glucose index and all-cause and CVD mortality in the young population with diabetes. Cardiovasc Diabetol, 2024, 23(1): 171.
35. He HM, Xie YY, Chen Q, et al. The additive effect of the triglyceride-glucose index and estimated glucose disposal rate on long-term mortality among individuals with and without diabetes: a population-based study. Cardiovasc Diabetol, 2024, 23(1): 307.
36. Song J, Ma R, Yin L. Associations between estimated glucose disposal rate and arterial stiffness and mortality among US adults with non-alcoholic fatty liver disease. Front Endocrinol (Lausanne), 2024, 15: 1398265.
37. Xu YX, Pu SD, Zhang YT, et al. Insulin resistance is associated with the presence and severity of retinopathy in patients with type 2 diabetes. Clin Exp Ophthalmol, 2024, 52(1): 63-77.
38. Kosmas CE, Bousvarou MD, Kostara CE, et al. Insulin resistance and cardiovascular disease. J Int Med Res, 2023, 51(3): 3000605231164548.
39. Hill MA, Yang Y, Zhang L, et al. Insulin resistance, cardiovascular stiffening and cardiovascular disease. Metabolism, 2021, 119: 154766.
40. Li ZY, Wang P, Miao CY. Adipokines in inflammation, insulin resistance and cardiovascular disease. Clin Exp Pharmacol Physiol, 2011, 38(12): 888-896.

West China Medical Journal

A study on the association between estimated glucose disposal rate and the risk of cardiovascular disease incidence in middle-aged and elderly individuals with and without diabetes

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