Assessment of six insulin resistance surrogate indexes for predicting stroke incidence in Chinese middle-aged and elderly populations with abnormal glucose metabolism: a nationwide prospective cohort study
Abstract Background Estimate glucose disposal rate (eGDR), Chinese visceral adiposity index (CVAI), triglyceride-glucose (TyG), TyG-body mass index (TyG-BMI), metabolic score for insulin resistance (METS-IR), and atherogenic index of plasma (AIP) are considered surrogate indexes of insulin resistanc...
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BMC
2025-02-01
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| Series: | Cardiovascular Diabetology |
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| Online Access: | https://doi.org/10.1186/s12933-025-02618-7 |
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| author | Luqing Jiang Tengxiao Zhu Wenjing Song Ying Zhai Yu Tang Fengxia Ruan Zichen Xu Lei Li Xia Fu Daoqin Liu Aidong Chen Qiwen Wu |
| author_facet | Luqing Jiang Tengxiao Zhu Wenjing Song Ying Zhai Yu Tang Fengxia Ruan Zichen Xu Lei Li Xia Fu Daoqin Liu Aidong Chen Qiwen Wu |
| author_sort | Luqing Jiang |
| collection | DOAJ |
| description | Abstract Background Estimate glucose disposal rate (eGDR), Chinese visceral adiposity index (CVAI), triglyceride-glucose (TyG), TyG-body mass index (TyG-BMI), metabolic score for insulin resistance (METS-IR), and atherogenic index of plasma (AIP) are considered surrogate indexes of insulin resistance (IR). There is a lack of studies comparing the predictive values of different IR surrogate indexes for stroke risk among individuals with abnormal glucose metabolism. This study aimed to investigate the relationships between six IR surrogate indexes and stroke risk in individuals with abnormal glucose metabolism, evaluate their predictive abilities for stroke risk. Methods Data from the China Health and Retirement Longitudinal Study (CHARLS) were analysed in this study. Multivariate logistic regression models were applied to analyse the relationships of IR surrogate indexes with stroke risk. The dose-response relationships between IR surrogate indexes and stroke risk were explored using restricted cubic splines. The areas under the curve (AUCs) of IR surrogate indexes were calculated by receiver operating characteristic (ROC) analysis. Results After adjusting for potential confounders, we observed that each standard deviation (SD) increase in eGDR was associated with a reduced risk of stroke, with an adjusted odds ratio (OR) of 0.746 [95% confidence interval (CI): 0.661–0.842]. In contrast, each SD increase in CVAI, TyG, TyG-BMI, METS-IR, and AIP were associated with an increased risk of stroke, with adjusted ORs (95% CIs) of 1.232 (1.106–1.373), 1.246 (1.050–1.479), 1.186 (1.022–1.376), 1.222 (1.069–1.396), and 1.193 (1.050–1.355), respectively. Dose-response analyses showed that eGDR, CVAI, TyG-BMI and METS-IR were linearly associated with stroke risk (P nonlinear ≥ 0.05), whereas TyG and AIP were nonlinearly associated with stroke risk (P nonlinear < 0.05). According to ROC analysis, The AUC of eGDR for predicting stroke risk in the overall population with abnormal glucose metabolism (AUC: 0.612, 95% CI: 0.584–0.640) was significantly higher than that of other indexes. Conclusion The six IR surrogate indexes were closely associated with high risk of stroke in individuals with abnormal glucose metabolism. The eGDR showed promising potential in predicting stroke risk in Chinese middle-aged and elderly populations with abnormal glucose metabolism. |
| format | Article |
| id | doaj-art-58b3dddd36d54c24b589a53230082967 |
| institution | Kabale University |
| issn | 1475-2840 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMC |
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| series | Cardiovascular Diabetology |
| spelling | doaj-art-58b3dddd36d54c24b589a532300829672025-02-09T12:10:50ZengBMCCardiovascular Diabetology1475-28402025-02-0124111310.1186/s12933-025-02618-7Assessment of six insulin resistance surrogate indexes for predicting stroke incidence in Chinese middle-aged and elderly populations with abnormal glucose metabolism: a nationwide prospective cohort studyLuqing Jiang0Tengxiao Zhu1Wenjing Song2Ying Zhai3Yu Tang4Fengxia Ruan5Zichen Xu6Lei Li7Xia Fu8Daoqin Liu9Aidong Chen10Qiwen Wu11Department of Laboratory, The First Affiliated Hospital of Wannan Medical CollegeDepartment of Laboratory, The First Affiliated Hospital of Wannan Medical CollegeDepartment of Laboratory, The First Affiliated Hospital of Wannan Medical CollegeDepartment of Laboratory, The First Affiliated Hospital of Wannan Medical CollegeDepartment of Laboratory, The First Affiliated Hospital of Wannan Medical CollegeDepartment of Laboratory, The Second People’s Hospital of WuhuDepartment of Laboratory, The First Affiliated Hospital of Wannan Medical CollegeDepartment of Laboratory, The First Affiliated Hospital of Wannan Medical CollegeDepartment of Laboratory, The First Affiliated Hospital of Wannan Medical CollegeDepartment of Nephrology, The First Affiliated Hospital of Wannan Medical CollegeThe Key Laboratory of Targeted Intervention of Cardiovascular Disease, Collaborative Innovation Center for Cardiovascular Disease Translational Medicine, Department of Physiology, Nanjing Medical UniversityDepartment of Laboratory, The First Affiliated Hospital of Wannan Medical CollegeAbstract Background Estimate glucose disposal rate (eGDR), Chinese visceral adiposity index (CVAI), triglyceride-glucose (TyG), TyG-body mass index (TyG-BMI), metabolic score for insulin resistance (METS-IR), and atherogenic index of plasma (AIP) are considered surrogate indexes of insulin resistance (IR). There is a lack of studies comparing the predictive values of different IR surrogate indexes for stroke risk among individuals with abnormal glucose metabolism. This study aimed to investigate the relationships between six IR surrogate indexes and stroke risk in individuals with abnormal glucose metabolism, evaluate their predictive abilities for stroke risk. Methods Data from the China Health and Retirement Longitudinal Study (CHARLS) were analysed in this study. Multivariate logistic regression models were applied to analyse the relationships of IR surrogate indexes with stroke risk. The dose-response relationships between IR surrogate indexes and stroke risk were explored using restricted cubic splines. The areas under the curve (AUCs) of IR surrogate indexes were calculated by receiver operating characteristic (ROC) analysis. Results After adjusting for potential confounders, we observed that each standard deviation (SD) increase in eGDR was associated with a reduced risk of stroke, with an adjusted odds ratio (OR) of 0.746 [95% confidence interval (CI): 0.661–0.842]. In contrast, each SD increase in CVAI, TyG, TyG-BMI, METS-IR, and AIP were associated with an increased risk of stroke, with adjusted ORs (95% CIs) of 1.232 (1.106–1.373), 1.246 (1.050–1.479), 1.186 (1.022–1.376), 1.222 (1.069–1.396), and 1.193 (1.050–1.355), respectively. Dose-response analyses showed that eGDR, CVAI, TyG-BMI and METS-IR were linearly associated with stroke risk (P nonlinear ≥ 0.05), whereas TyG and AIP were nonlinearly associated with stroke risk (P nonlinear < 0.05). According to ROC analysis, The AUC of eGDR for predicting stroke risk in the overall population with abnormal glucose metabolism (AUC: 0.612, 95% CI: 0.584–0.640) was significantly higher than that of other indexes. Conclusion The six IR surrogate indexes were closely associated with high risk of stroke in individuals with abnormal glucose metabolism. The eGDR showed promising potential in predicting stroke risk in Chinese middle-aged and elderly populations with abnormal glucose metabolism.https://doi.org/10.1186/s12933-025-02618-7Insulin resistance surrogate indexStrokeAbnormal glucose metabolismCHARLS |
| spellingShingle | Luqing Jiang Tengxiao Zhu Wenjing Song Ying Zhai Yu Tang Fengxia Ruan Zichen Xu Lei Li Xia Fu Daoqin Liu Aidong Chen Qiwen Wu Assessment of six insulin resistance surrogate indexes for predicting stroke incidence in Chinese middle-aged and elderly populations with abnormal glucose metabolism: a nationwide prospective cohort study Cardiovascular Diabetology Insulin resistance surrogate index Stroke Abnormal glucose metabolism CHARLS |
| title | Assessment of six insulin resistance surrogate indexes for predicting stroke incidence in Chinese middle-aged and elderly populations with abnormal glucose metabolism: a nationwide prospective cohort study |
| title_full | Assessment of six insulin resistance surrogate indexes for predicting stroke incidence in Chinese middle-aged and elderly populations with abnormal glucose metabolism: a nationwide prospective cohort study |
| title_fullStr | Assessment of six insulin resistance surrogate indexes for predicting stroke incidence in Chinese middle-aged and elderly populations with abnormal glucose metabolism: a nationwide prospective cohort study |
| title_full_unstemmed | Assessment of six insulin resistance surrogate indexes for predicting stroke incidence in Chinese middle-aged and elderly populations with abnormal glucose metabolism: a nationwide prospective cohort study |
| title_short | Assessment of six insulin resistance surrogate indexes for predicting stroke incidence in Chinese middle-aged and elderly populations with abnormal glucose metabolism: a nationwide prospective cohort study |
| title_sort | assessment of six insulin resistance surrogate indexes for predicting stroke incidence in chinese middle aged and elderly populations with abnormal glucose metabolism a nationwide prospective cohort study |
| topic | Insulin resistance surrogate index Stroke Abnormal glucose metabolism CHARLS |
| url | https://doi.org/10.1186/s12933-025-02618-7 |
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