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Nayak SS, Kuriyakose D, Polisetty LD, Patil AA, Ameen D, Bonu R, Shetty SP, Biswas P, Ulrich MT, Letafatkar N, Habibi A, Keivanlou MH, Nobakht S, Alotaibi A, Hassanipour S, Amini-Salehi E. Diagnostic and prognostic value of triglyceride glucose index: a comprehensive evaluation of meta-analysis. Cardiovasc Diabetol 2024; 23:310. [PMID: 39180024 PMCID: PMC11344391 DOI: 10.1186/s12933-024-02392-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Accepted: 08/05/2024] [Indexed: 08/26/2024] Open
Abstract
OBJECTIVE The present umbrella review aims to collate and summarize the findings from previous meta-analyses on the Triglyceride and Glucose (TyG) Index, providing insights to clinicians, researchers, and policymakers regarding the usefulness of this biomarker in various clinical settings. METHODS A comprehensive search was conducted in PubMed, Scopus, and Web of Science up to April 14, 2024, without language restrictions. The AMSTAR2 checklist assessed the methodological quality of the included meta-analyses. Statistical analyses were performed using Comprehensive Meta-Analysis (CMA) software. RESULTS A total of 32 studies were finally included. The results revealed significant associations between the TyG index and various health outcomes. For kidney outcomes, a high TyG index was significantly associated with an increased risk of contrast-induced nephropathy (CIN) (OR = 2.24, 95% CI: 1.82-2.77) and chronic kidney disease (CKD) (RR = 1.46, 95% CI: 1.32-1.63). High TyG index was significantly associated with an increased risk of type 2 diabetes mellitus (T2DM) (RR = 3.53, 95% CI: 2.74-4.54), gestational diabetes mellitus (GDM) (OR = 2.41, 95% CI: 1.48-3.91), and diabetic retinopathy (DR) (OR = 2.34, 95% CI: 1.31-4.19). Regarding metabolic diseases, the TyG index was significantly higher in patients with obstructive sleep apnea (OSA) (SMD = 0.86, 95% CI: 0.57-1.15), metabolic syndrome (MD = 0.83, 95% CI: 0.74-0.93), and non-alcoholic fatty liver disease (NAFLD) (OR = 2.36, 95% CI: 1.88-2.97) compared to those without these conditions. In cerebrovascular diseases, a higher TyG index was significantly associated with an increased risk of dementia (OR = 1.14, 95% CI: 1.12-1.16), cognitive impairment (OR = 2.31, 95% CI: 1.38-3.86), and ischemic stroke (OR = 1.37, 95% CI: 1.22-1.54). For cardiovascular outcomes, the TyG index showed significant associations with an increased risk of heart failure (HF) (HR = 1.21, 95% CI: 1.12-1.30), atrial fibrillation (AF) (SMD = 1.22, 95% CI: 0.57-1.87), and hypertension (HTN) (RR = 1.52, 95% CI: 1.25-1.85). CONCLUSION The TyG index is a promising biomarker for screening and predicting various medical conditions, particularly those related to insulin resistance and metabolic disorders. However, the heterogeneity and methodological quality of the included studies suggest the need for further high-quality research to confirm these findings and refine the clinical utility of the TyG index.
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Affiliation(s)
- Sandeep Samethadka Nayak
- Division of Hospital Medicine, Department of Internal Medicine, Bridgeport Hospital, Yale New Heaven, Bridgeport, CT, USA
| | - Dona Kuriyakose
- St. Joseph's Mission Hospital, Kollam District, Anchal, Kerala, India
| | - Lakshmi D Polisetty
- Division of Hospital Medicine, Department of Internal Medicine, Bridgeport Hospital, Yale New Heaven, Bridgeport, CT, USA
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, John Dempsey Hospital, University of Connecticut, Bridgeport, CT, USA
| | - Anjali Avinash Patil
- Rajarshee Chhatrapati Shahu Maharaj Government Medical College Kolhapur Shenda park, Kolhapur, Maharashtra, India
| | - Daniyal Ameen
- Division of Hospital Medicine, Department of Internal Medicine, Bridgeport Hospital, Yale New Heaven, Bridgeport, CT, USA
| | - Rakshita Bonu
- Vydehi Institute of Medical Sciences and Research Centre, Bengaluru. 82, Nallurahalli Main Road, Whitefield, Bengaluru, Karnataka, India
| | - Samatha P Shetty
- Director of Capacity Management, NYC Health Hospitals, Elmhurst, USA
| | - Pubali Biswas
- Vydehi Institute of Medical Sciences and Research Centre, Bengaluru. 82, Nallurahalli Main Road, Whitefield, Bengaluru, Karnataka, India
| | - Micheal T Ulrich
- Riverside University Health System Medical Center, Moreno Valley, CA, USA
| | | | - Arman Habibi
- Guilan University of Medical Sciences, Rasht, Iran
| | | | - Sara Nobakht
- Guilan University of Medical Sciences, Rasht, Iran
| | | | - Soheil Hassanipour
- Gastrointestinal and Liver Diseases Research Center, Guilan University of Medical Sciences, P.O. Box: 41448-95655, Rasht, Iran
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Xia X, Chen S, Tian X, Xu Q, Zhang Y, Zhang X, Li J, Wu S, Wang A. Association of triglyceride-glucose index and its related parameters with atherosclerotic cardiovascular disease: evidence from a 15-year follow-up of Kailuan cohort. Cardiovasc Diabetol 2024; 23:208. [PMID: 38898520 PMCID: PMC11188278 DOI: 10.1186/s12933-024-02290-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2024] [Accepted: 05/28/2024] [Indexed: 06/21/2024] Open
Abstract
BACKGROUND Triglyceride glucose (TyG) index and its related parameters have been introduced as cost-effective surrogate indicators of insulin resistance, while prospective evidence of their effects on atherosclerotic cardiovascular disease (ASCVD) remained scattered and inconsistent. We aimed to evaluate the association of TyG and its related parameters with new-onset ASCVD, and the predictive capacity were further compared. METHOD A total of 95,342 ASCVD-free participants were enrolled from the Kailuan study. TyG and its related parameters were defined by fasting blood glucose, triglyceride, body mass index (BMI), waist circumstance (WC) and waist-to-height ratio (WHtR). The primary outcome was incident ASCVD, comprising myocardial infarction (MI) and ischemic stroke (IS). Cox proportional hazard models and restricted cubic spline (RCS) analyses were adopted to investigate the association between each index and ASCVD. The C-index, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were used for comparison of their predictive value for ASCVD. RESULTS During a median follow-up of 15.0 years, 8,031 new cases of ASCVD were identified. The incidence rate of ASCVD increased along with elevated levels of each index, and the relationships were found to be nonlinear in the RCS analyses. The hazard ratio (HR) and 95% confidence interval (95% CI) for ASCVD was 1.39 (1.35, 1.43), 1.46 (1.41, 1.50), 1.50 (1.46, 1.55), and 1.52 (1.48, 1.57) per 1 IQR increase of baseline TyG, TyG-BMI, TyG-WC, and TyG-WHtR, respectively, and the association were more pronounced for females and younger individuals aged < 60 years (Pfor interaction<0.05). Using the updated mean or time-varying measurements instead of baseline indicators did not significantly alter the primary findings. Additionally, TyG-WC and TyG-WHtR showed better performance in predicting risk of ASCVD than TyG, with the IDI (95% CI) of 0.004 (0.001, 0.004) and 0.004 (0.001, 0.004) and the category-free NRI (95% CI) of 0.120 (0.025, 0.138) and 0.143 (0.032, 0.166), respectively. Similar findings were observed for MI and IS. CONCLUSIONS Both the TyG index and its related parameters were significantly and positively associated with ASCVD. TyG-WC and TyG-WHtR had better performance in predicting incident ASCVD than TyG, which might be more suitable indices for risk stratification and enhance the primary prevention of ASCVD.
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Affiliation(s)
- Xue Xia
- Department of Epidemiology, Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Clinical Epidemiology and Clinical Trial, Capital Medical University, Beijing, China
| | - Shuohua Chen
- Department of Cardiology, Kailuan General Hospital, North China University of Science and Technology, Tangshan, Hebei, China
| | - Xue Tian
- Department of Epidemiology, Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Clinical Epidemiology and Clinical Trial, Capital Medical University, Beijing, China
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Qin Xu
- Department of Epidemiology, Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Clinical Epidemiology and Clinical Trial, Capital Medical University, Beijing, China
| | - Yijun Zhang
- Department of Epidemiology, Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Clinical Epidemiology and Clinical Trial, Capital Medical University, Beijing, China
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Xiaoli Zhang
- Department of Epidemiology, Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jing Li
- Department of Epidemiology, Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Shouling Wu
- Department of Cardiology, Kailuan General Hospital, North China University of Science and Technology, Tangshan, Hebei, China.
| | - Anxin Wang
- Department of Epidemiology, Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
- Department of Clinical Epidemiology and Clinical Trial, Capital Medical University, Beijing, China.
- Department of Epidemiology, Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, No. 119 South Fourth Ring West Road, 100070, Beijing, China.
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Cui C, Qi Y, Song J, Shang X, Han T, Han N, Yue S, Zha Y, Xu Z, Li J, Liu L. Comparison of triglyceride glucose index and modified triglyceride glucose indices in prediction of cardiovascular diseases in middle aged and older Chinese adults. Cardiovasc Diabetol 2024; 23:185. [PMID: 38812015 PMCID: PMC11138075 DOI: 10.1186/s12933-024-02278-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Accepted: 05/17/2024] [Indexed: 05/31/2024] Open
Abstract
BACKGROUND Triglyceride and glucose (TyG) index, a surrogate marker of insulin resistance, has been validated as a predictor of cardiovascular disease. However, effects of TyG-related indices combined with obesity markers on cardiovascular diseases remained unknown. We aimed to investigate the associations between TyG index and modified TyG indices with new-onset cardiovascular disease and the time-dependent predictive capacity using a national representative cohort. METHODS This study is a retrospective observational cohort study using data from China Health and Retirement Longitudinal Study (CHARLS) of 7 115 participants. The TyG index was calculated as Ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. The modified TyG indices were developed combining TyG with body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR). We used adjusted Cox proportional hazards regression to analyze the association and predictive capacity based on hazard ratio (HR) and Harrell's C-index. RESULTS Over a 7-year follow-up period, 2136 participants developed cardiovascular disease, including 1633 cases of coronary heart disease and 719 cases of stroke. Compared with the lowest tertile group, the adjusted HR (95% CI) for new-onset cardiovascular disease in the highest tertile for TyG, TyG-BMI, TyG-WC, and TyG-WHtR were 1.215 (1.088-1.356), 1.073 (0.967-1.191), 1.078 (0.970-1.198), and 1.112 (1.002-1.235), respectively. The C-indices of TyG index for cardiovascular disease onset were higher than other modified TyG indices. Similar results were observed for coronary heart disease and stroke. CONCLUSION TyG and TyG-WhtR were significantly associated with new-onset cardiovascular diseases, and TyG outperformed the modified TyG indices to identify individuals at risk of incident cardiovascular event.
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Affiliation(s)
- Cancan Cui
- China-Japan Union Hospital of Jilin University, Jilin University, Jilin, China
| | - Yitian Qi
- China-Japan Union Hospital of Jilin University, Jilin University, Jilin, China
| | - Jiayin Song
- China-Japan Union Hospital of Jilin University, Jilin University, Jilin, China
| | - Xinyun Shang
- China-Japan Union Hospital of Jilin University, Jilin University, Jilin, China
| | - Tianjiao Han
- China-Japan Union Hospital of Jilin University, Jilin University, Jilin, China
| | - Ning Han
- China-Japan Union Hospital of Jilin University, Jilin University, Jilin, China
| | - Siqi Yue
- China-Japan Union Hospital of Jilin University, Jilin University, Jilin, China
| | - Yining Zha
- Harvard T H Chan School of Public Health, Boston, USA
| | - Zhonghang Xu
- China-Japan Union Hospital of Jilin University, Jilin University, Jilin, China.
| | - Jiannan Li
- China-Japan Union Hospital of Jilin University, Jilin University, Jilin, China.
| | - Lin Liu
- China-Japan Union Hospital of Jilin University, Jilin University, Jilin, China.
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Ahn SH, Lee HS, Lee JH. Triglyceride-glucose-waist circumference index predicts the incidence of cardiovascular disease in Korean populations: competing risk analysis of an 18-year prospective study. Eur J Med Res 2024; 29:214. [PMID: 38566247 PMCID: PMC10985901 DOI: 10.1186/s40001-024-01820-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Accepted: 03/29/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND The triglyceride and glucose-waist circumference (TyG-WC) index demonstrated a strong association with insulin resistance, especially in Asian population. However, evidence on the association between TyG-WC index and the occurrence of cardiovascular disease (CVD) is limited. This study aimed to verify association between the TyG-WC index and the occurrence of CVD by considering all-cause mortality as a competing risk. METHODS The study included 7482 participants divided into four groups based on the TyG-WC index quartiles. Kaplan-Meier curves illustrated cumulative incidence rates of CVD and all-cause mortality during the follow-up period. Log-rank tests determined group differences. The Cox proportional hazard spline curve demonstrates the dose-dependent relationship between the TyG-WC index and incident CVD. Modified Cox regression (Fine and Gray) estimated hazard ratios (HRs) with 95% CIs for incident CVD, treating death as a competing risk. Death event after incident CVD was excluded from the death count. RESULTS During the median 15.94 year of follow-up period, a total of 691 (9.24%) new-onset CVD cases and 562 (7.51%) all-cause mortality cases were confirmed. Cox proportional hazard spline curves suggested that TyG-WC index exhibited a dose-dependent positive correlation with incident CVD. The cumulative incidence rate of CVD was significantly higher in the groups with higher TyG-WC index quartiles in Kaplan-Meier curves. The adjusted HR (95% CI) for incident CVD in Q2-Q4, compared with Q1, was 1.47 (1.12-1.93), 1.91 (1.44-2.54) and 2.24 (1.63-3.07), respectively. There was no significant association between TyG-WC index and all-cause mortality. Specifically, angina and stroke were significantly associated with the TyG-WC index, in contrast to myocardial infarction and peripheral artery disease. CONCLUSIONS The TyG-WC index was positively associated with incident CVD even considering all-cause mortality as a competing risk. Therefore, TyG-WC index may be a valuable marker for predicting the occurrence of CVD.
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Affiliation(s)
- Sung Ho Ahn
- Department of Family Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, 03722, Republic of Korea
| | - Hye Sun Lee
- Biostatistics Collaboration Unit, Department of Research Affairs, Yonsei University College of Medicine, Seoul, 03277, Republic of Korea
| | - Jun-Hyuk Lee
- Department of Family Medicine, Nowon Eulji Medical Center, Eulji University School of Medicine, Seoul, 01830, Republic of Korea.
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Dang K, Wang X, Hu J, Zhang Y, Cheng L, Qi X, Liu L, Ming Z, Tao X, Li Y. The association between triglyceride-glucose index and its combination with obesity indicators and cardiovascular disease: NHANES 2003-2018. Cardiovasc Diabetol 2024; 23:8. [PMID: 38184598 PMCID: PMC10771672 DOI: 10.1186/s12933-023-02115-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 12/29/2023] [Indexed: 01/08/2024] Open
Abstract
BACKGROUND In the American population, the relationship between the triglyceride-glucose (TyG) index and TYG combined with indicators of obesity and cardiovascular disease (CVD) and its mortality has been less well studied. METHODS This cross-sectional study included 11,937 adults from the National Health and Nutrition Examination Survey (NHANES) 2003-2018. Cox proportional hazards model, binary logistic regression analyses, restricted cubic spline (RCS), and receiver operating characteristic (ROC) were used to analyze the relationship between TyG and its combined obesity-related indicators and CVD and its mortality. Mediation analysis explored the mediating role of glycated hemoglobin and insulin in the above relationships. RESULTS In this study, except for no significant association between TyG and CVD mortality, TyG, TyG-WC, TyG-WHtR, and TyG-BMI were significantly and positively associated with CVD and CVD mortality. TyG-WHtR is the strongest predictor of CVD mortality (HR 1.66, 95% CI 1.21-2.29). The TyG index correlated better with the risk of coronary heart disease (OR 2.52, 95% CI 1.66-3.83). TyG-WC correlated best with total CVD (OR 2.37, 95% CI 1.77-3.17), congestive heart failure (OR 2.14, 95% CI 1.31-3.51), and angina pectoris (OR 2.38, 95% CI 1.43-3.97). TyG-WHtR correlated best with myocardial infarction (OR 2.24, 95% CI 1.45-3.44). RCS analyses showed that most of the above relationships were linear (P-overall < 0.0001, P-nonlinear > 0.05). Otherwise, ROC curves showed that TyG-WHtR and TyG-WC had more robust diagnostic efficacy than TyG. In mediation analyses, glycated hemoglobin mediated in all the above relationships and insulin-mediated in partial relationships. CONCLUSIONS TyG-WC and TyG-WtHR enhance CVD mortality prediction, diagnostic efficacy of CVD and its mortality, and correlation with some CVD over and above the current hottest TyG. TyG-WC and TyG-WtHR are expected to become more effective metrics for identifying populations at early risk of cardiovascular disease and improve risk stratification.
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Affiliation(s)
- Keke Dang
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China
| | - Xuanyang Wang
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China
| | - Jinxia Hu
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China
| | - Yuntao Zhang
- MED-X Institute, Center for Immunological and Metabolic Diseases (CIMD), First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710000, China
| | - Licheng Cheng
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China
| | - Xiang Qi
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China
| | - Lin Liu
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China
| | - Zhu Ming
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China
| | - Xinmiao Tao
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China
| | - Ying Li
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
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Park HM, Han T, Heo SJ, Kwon YJ. Effectiveness of the triglyceride-glucose index and triglyceride-glucose-related indices in predicting cardiovascular disease in middle-aged and older adults: A prospective cohort study. J Clin Lipidol 2024; 18:e70-e79. [PMID: 38044202 DOI: 10.1016/j.jacl.2023.11.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 11/06/2023] [Accepted: 11/10/2023] [Indexed: 12/05/2023]
Abstract
BACKGROUNDS Cardiovascular disease (CVD) risk assessment is a crucial component of public health. We aimed to determine the predictive value of the triglyceride-glucose (TyG) index and TyG-related indices for new-onset CVD. METHODS This prospective study included 7,808 participants aged 40-69 years from the Ansung-Ansan cohort database. Our analysis was stratified by diabetes status. The hazard ratio (HR) with a 95% confidence interval (CI) for incident CVD was computed using multiple Cox proportional-hazards regression models. To evaluate the predictive performance of these indices for new-onset CVD, we calculated the Harrell's C-index (95% CI). RESULTS In this study, a total of 6,890 participants did not have diabetes at baseline, while 918 participants had diabetes. In participants without diabetes, compared to the lowest tertile, fully adjusted HR and 95% CI for new-onset CVD in the highest tertile were as follows: TyG (HR 1.42, 95% CI 1.06-1.90), TyG-body mass index (BMI) (HR 1.92, 95% CI 1.19-3.10), TyG-waist circumference (WC) (HR 2.37, 95% CI 1.61-3.49), and TyG-waist-to-height ratio (WHtR) (HR 2.20, 95% CI 1.47-3.28). However, no significant associations were observed between TyG, modified TyG indices, and new-onset CVD in participants with diabetes. Notably, the C-indice of TyG-WC and TyG-WHtR were significantly higher than those of TyG and TyG-BMI in participants without diabetes. CONCLUSIONS TyG-BMI, TyG-WC, and TyG-WHtR were associated with an increased risk of new-onset CVD in participants without diabetes. Furthermore, TyG-WC and TyG-WHtR showed better predictive performances for new-onset CVD than TyG and TyG-BMI in participants without diabetes.
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Affiliation(s)
- Hye-Min Park
- Standard Primary Care Center, National Health Insurance Service Ilsan Hospital, Goyang, Republic of Korea (Hye-Min Park)
| | - Taehwa Han
- Health-IT Center, Yonsei University Severance Hospital, Seoul 03722, Republic of Korea (Taehwa Han)
| | - Seok-Jae Heo
- Division of Biostatistics, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul 03722, Republic of Korea (Seok-Jae Heo)
| | - Yu-Jin Kwon
- Department of Family Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin 16995, Republic of Korea (Yu-Jin Kwon).
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Yang C, Song Y, Wang X, Yang Y, Zhou Y, Wang D, Hou J, Wang P. Association of hypertension with the triglyceride-glucose index and its associated indices in the Chinese population: A 6-year prospective cohort study. J Clin Hypertens (Greenwich) 2024; 26:53-62. [PMID: 38133535 PMCID: PMC10795092 DOI: 10.1111/jch.14758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 12/05/2023] [Accepted: 12/07/2023] [Indexed: 12/23/2023]
Abstract
The authors aim to assess the correlation between hypertension and the triglyceride-glucose (TyG) index and its associated indices, and to compare their abilities to identify hypertension. Four thousand eight hundred and sixty-six non-hypertensive participants were enrolled from the China National Health Survey in 2009. The data on new-onset hypertension were gathered in both 2011 and 2015. The TyG index and its associated indices were derived from the fasting triglyceride, blood glucose levels, and anthropometric parameters. Multivariate logistic regression analyses and receiver operating characteristic curve analysis were used. The adjusted odds ratio (OR) and 95% confidence interval (CI) for the new-onset hypertension for the TyG-waist-to-height ratio (TyG-WHtR), TyG-waist circumference (TyG-WC), TyG-waist-to-hip ratio (TyG-WHR), TyG-body mass index (TyG-BMI), and TyG index were 1.379 (1.230-1.546), 1.002 (1.001-1.003), 1.156 (1.069-1.251), 1.007 (1.005-1.009), and 1.187 (1.051-1.341), respectively. In addition, comparing the lowest quartile (Q1) group with the highest quartile (Q4), the adjusted OR and 95% CI for the new-onset hypertension were found to be 1.86 (1.48-2.35), 1.93 (1.53-2.43), 1.71 (1.36-2.16), 2.00 (1.60-2.50), and 1.49 (1.19-1.88) for TyG-WHtR, TyG-WC, TyG-WHR, TyG-BMI, and TyG index, respectively, among all participants. The TyG-WHtR had the largest area under the curve (AUC) for hypertension (AUC, 0.628; 95% CI, 0.614-0.641) in all participants. Stratified analysis also indicated that the TyG-WHtR exhibited the greatest AUC in both males (AUC, 0.608; 95% CI, 0.587-0.629) and females (AUC, 0.648; 95% CI, 0.629-0.666). In conclusions, the TyG index and its associated indices were positively associated with hypertension. Among these indices, TyG-WHtR was the most valuable indicator for predicting hypertension.
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Affiliation(s)
- Changqiang Yang
- Department of Cardiologythe First Affiliated Hospital, Chengdu Medical CollegeChengduSichuanChina
- Sichuan Clinical Research Center for Geriatricsthe First Affiliated Hospital of Chengdu Medical CollegeChengduSichuanChina
- Key Laboratory of Aging and Vascular Homeostasis of Sichuan Higher Education InstitutesChengduSichuanChina
| | - Yue Song
- Department of Pediatricsthe First Affiliated Hospital, Chengdu Medical CollegeChengduSichuanChina
| | - Xinquan Wang
- Department of Cardiologythe First Affiliated Hospital, Chengdu Medical CollegeChengduSichuanChina
- Sichuan Clinical Research Center for Geriatricsthe First Affiliated Hospital of Chengdu Medical CollegeChengduSichuanChina
- Key Laboratory of Aging and Vascular Homeostasis of Sichuan Higher Education InstitutesChengduSichuanChina
| | - Yi Yang
- Department of Cardiologythe First Affiliated Hospital, Chengdu Medical CollegeChengduSichuanChina
- Sichuan Clinical Research Center for Geriatricsthe First Affiliated Hospital of Chengdu Medical CollegeChengduSichuanChina
- Key Laboratory of Aging and Vascular Homeostasis of Sichuan Higher Education InstitutesChengduSichuanChina
| | - Yaqiong Zhou
- Department of Cardiologythe First Affiliated Hospital, Chengdu Medical CollegeChengduSichuanChina
- Sichuan Clinical Research Center for Geriatricsthe First Affiliated Hospital of Chengdu Medical CollegeChengduSichuanChina
- Key Laboratory of Aging and Vascular Homeostasis of Sichuan Higher Education InstitutesChengduSichuanChina
| | - Dan Wang
- Department of Cardiologythe First Affiliated Hospital, Chengdu Medical CollegeChengduSichuanChina
- Sichuan Clinical Research Center for Geriatricsthe First Affiliated Hospital of Chengdu Medical CollegeChengduSichuanChina
- Key Laboratory of Aging and Vascular Homeostasis of Sichuan Higher Education InstitutesChengduSichuanChina
| | - Jixin Hou
- Department of Cardiologythe First Affiliated Hospital, Chengdu Medical CollegeChengduSichuanChina
- Sichuan Clinical Research Center for Geriatricsthe First Affiliated Hospital of Chengdu Medical CollegeChengduSichuanChina
- Key Laboratory of Aging and Vascular Homeostasis of Sichuan Higher Education InstitutesChengduSichuanChina
| | - Peijian Wang
- Department of Cardiologythe First Affiliated Hospital, Chengdu Medical CollegeChengduSichuanChina
- Sichuan Clinical Research Center for Geriatricsthe First Affiliated Hospital of Chengdu Medical CollegeChengduSichuanChina
- Key Laboratory of Aging and Vascular Homeostasis of Sichuan Higher Education InstitutesChengduSichuanChina
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Yang H, Chen Y, Liu C. Triglyceride-glucose index is associated with metabolic syndrome in women with polycystic ovary syndrome. Gynecol Endocrinol 2023; 39:2172154. [PMID: 36708155 DOI: 10.1080/09513590.2023.2172154] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
OBJECTIVE To explore the correlation of triglyceride-glucose index (TyG) index with metabolic syndrome (MetS) and metabolic risk factors, and to assess the predictive value of TyG for MetS in women with PCOS. METHODS This is a retrospective cross-sectional study that included 819 women diagnosed with PCOS and 3122 women without PCOS from January 2018 to December 2021. The definition of MetS adopted in this study was the International Diabetes Federation (IDF) criteria. The TyG index was calculated as the ln (fasting triglyceride level [mg/dL] × fasting glucose level [mg/dL]/2). RESULTS MetS was diagnosed in 266 women (32.5%) among 819 subjects with PCOS, and in 287 women (9.2%) among 3122 subjects without PCOS. Logistic regression analysis showed that women in the highest tertile of TyG index had the highest prevalence of MetS (OR = 3.66, 95%CI: 1.28-10.49) after adjusting for confounding factors. Compared with the lowest tertile, PCOS women in the highest tertile showed the highest odds ratio of hypertension, obesity, central obesity, hyperglycemia and dyslipidemia. Furthermore, TyG index was able to identify MetS in women with PCOS, and the optimal cutoff values were 8.65 (Youden index = 0.65). CONCLUSION TyG index was positively and independently correlated with the prevalence of MetS, which also indicated a good predictive ability in women with PCOS.
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Affiliation(s)
- Haiyan Yang
- Reproductive Medicine Center, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, PR China
| | - Yufeng Chen
- Gynaecology, The First People's Hospital of Jiashan County, Jiaxing, Zhejiang, PR China
| | - Chang Liu
- Reproductive Medicine Center, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, PR China
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Lee JH, Heo S, Kwon Y. Sex-Specific Comparison Between Triglyceride Glucose Index and Modified Triglyceride Glucose Indices to Predict New-Onset Hypertension in Middle-Aged and Older Adults. J Am Heart Assoc 2023; 12:e030022. [PMID: 37721166 PMCID: PMC10547265 DOI: 10.1161/jaha.123.030022] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 08/18/2023] [Indexed: 09/19/2023]
Abstract
Background Triglyceride and glucose (TyG) index and TyG-related indices combined with obesity-related markers are considered important markers of insulin resistance. We aimed to examine the association between the TyG index and modified TyG indices with new-onset hypertension and their predictive ability stratified by sex. Methods and Results We analyzed data from 5414 Korean Genome and Epidemiology Study participants aged 40 to 69 years. Multiple Cox proportional hazard regression analyses were conducted to estimate the hazard ratio (HR) and 95% CI for new-onset hypertension according to sex-specific tertile groups after confounder adjustments. To evaluate the predictive performance of these indices for new-onset hypertension, we calculated Harrell's C-index (95% CI). Over a 9.5-year follow-up period, 1014 men and 1012 women developed new-onset hypertension. Compared with the lowest tertile (T) group, the adjusted HR and 95% CI for new-onset hypertension in T3 for TyG, TyG-body mass index, TyG-waist circumference, and TyG-waist-to-height ratio were 1.16 (0.95-1.40), 1.11 (0.84-1.48), 1.77 (1.38-2.27), and 1.68 (1.33-2.13) in men and 1.37 (1.13-1.66), 1.55 (1.16-2.06), 1.43 (1.15-1.79), and 1.64 (1.30-2.07) in women, respectively. The C-indices of TyG-waist-to-height ratio for new-onset hypertension were significantly higher than those of TyG and TyG-body mass index in both men and women. Conclusions TyG and TyG-body mass index were significantly associated with new-onset hypertension only in women. TyG-waist circumference and TyG-waist-to-height ratio were significantly associated with new-onset hypertension in both men and women. A sex-specific approach is required when using TyG and modified TyG indices to identify individuals at risk of incident hypertension.
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Affiliation(s)
- Joo Hyung Lee
- Department of Family Medicine, Yongin Severance HospitalYonsei University College of MedicineYonginRepublic of Korea
| | - Seok‐Jae Heo
- Division of Biostatistics, Department of Biomedical Systems InformaticsYonsei University College of MedicineSeoulRepublic of Korea
| | - Yu‐Jin Kwon
- Department of Family Medicine, Yongin Severance HospitalYonsei University College of MedicineYonginRepublic of Korea
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Li Y, Gui J, Liu H, Guo LL, Li J, Lei Y, Li X, Sun L, Yang L, Yuan T, Wang C, Zhang D, Wei H, Li J, Liu M, Hua Y, Zhang L. Predicting metabolic syndrome by obesity- and lipid-related indices in mid-aged and elderly Chinese: a population-based cross-sectional study. Front Endocrinol (Lausanne) 2023; 14:1201132. [PMID: 37576971 PMCID: PMC10419183 DOI: 10.3389/fendo.2023.1201132] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 07/12/2023] [Indexed: 08/15/2023] Open
Abstract
Objective To predict the optimal cut-off values for screening and predicting metabolic syndrome(MetS) in a middle-aged and elderly Chinese population using 13 obesity and lipid-related indicators, and to identify the most suitable predictors. Methods The data for this cross-sectional investigation came from the China Health and Retirement Longitudinal Study (CHARLS), including 9457 middle-aged and elderly people aged 45-98 years old. We examined 13 indicators, including waist circumference (WC), body mass index (BMI), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), lipid accumulation product index (LAP), conicity index (CI), Chinese visceral adiposity index (CVAI), triglyceride-glucose index (TyG-index) and their combined indices (TyG-BMI, TyG-WC, TyG-WHtR). The receiver operating characteristic curve (ROC) was used to determine the usefulness of indicators for screening for MetS in the elderly and to determine their cut-off values, sensitivity, specificity, and area under the curve (AUC). Association analysis of 13 obesity-related indicators with MetS was performed using binary logistic regression analysis. Results A total of 9457 middle-aged and elderly Chinese were included in this study, and the overall prevalence of the study population was 41.87% according to the diagnostic criteria of NCEP ATP III. According to age and gender, the percentage of males diagnosed with MetS was 30.67% (45-54 years old: 30.95%, 55-64 years old: 41.02%, 65-74 years old: 21.19%, ≥ 75 years old: 6.84%). The percentage of females diagnosed with MetS was 51.38% (45-54 years old: 31.95%, 55-64 years old: 39.52%, 65-74 years old: 20.43%, ≥ 75 years old: 8.10%). The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS. ABSI had a poor prediction ability. Conclusions Among the middle-aged and elderly population in China, after adjusting for confounding factors, all the indicators except ABSI had good predictive power. The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS.
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Affiliation(s)
- Yuqing Li
- Department of Graduate School, Wannan Medical College, Wuhu, An Hui, China
| | - Jiaofeng Gui
- Department of Graduate School, Wannan Medical College, Wuhu, An Hui, China
| | - Haiyang Liu
- Health Center, Wannan Medical College, Wuhu, An Hui, China
| | - Lei-lei Guo
- Department of Surgical Nursing, School of Nursing, Jinzhou Medical University, Jinzhou, Liaoning, China
| | - Jinlong Li
- Department of Occupational and Environmental Health, Key Laboratory of Occupational Health and Safety for Coal Industry in Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan, Hebei, China
| | - Yunxiao Lei
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Xiaoping Li
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Lu Sun
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Liu Yang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Ting Yuan
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Congzhi Wang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Dongmei Zhang
- Department of Pediatric Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Huanhuan Wei
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Jing Li
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Mingming Liu
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Ying Hua
- Rehabilitation Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
| | - Lin Zhang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, An Hui, China
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Lee HJ, Lee JW, Kim S, Kwon YJ. Comparison of the triglyceride glucose index and modified triglyceride glucose indices in assessing periodontitis in Korean adults. J Periodontal Res 2023; 58:503-510. [PMID: 36840374 DOI: 10.1111/jre.13108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 02/02/2023] [Accepted: 02/07/2023] [Indexed: 02/26/2023]
Abstract
BACKGROUND Periodontal diseases are closely connected with insulin resistance (IR) and metabolic syndrome. The Triglyceride Glucose Index (TyG) assesses IR, and recently, a few indices combining TyG and body composition have emerged with higher IR predictive performance than TyG alone. We aimed to examine which TyG-related parameters are most helpful in predicting the risk of periodontal disease. METHODS From 2013 to 2015, data were collected through the Korean National Health and Nutrition Examination Survey. Periodontitis was defined using the Community Periodontal Index. TyG-body mass index (BMI), TyG-waist circumference (WC), and TyG-waist-to-height ratio (WHtR) were calculated by multiplying TyG index score by BMI, WC, and WHtR, respectively. Multiple logistic regression analysis was used to calculate odds ratio (OR) and 95% confidence intervals (CI). Receiver operating characteristic curves were used to estimate areas under the curve (AUC). RESULTS Compared to each reference quartile (Q)1, Q4 of the TyG index, TyG-BMI, TyG-WC, and TyG-WHtR were significantly associated with a higher risk of periodontitis after adjusting for confounders (OR, 95% CI; 1.23, 1.01-1.49 for TyG; 1.63, 1.22-2.17 for TyG-BMI; 1.37, 1.04-1.81 for TyG-WC; and 1.53, 1.16-2.02 for TyG-WHtR). The AUC and 95% CIs of TyG, TyG-BMI, TyG-WC, and TyG-WHtR in predicting periodontitis were 0.609 (0.600-0.617), 0.605 (0.596-0.617), 0.629 (0.621-0.637), and 0.636 (0.628-0.644), respectively (all p < .001). CONCLUSIONS TyG, TyG-BMI, TyG-WC, and TyG-WHtR appear to be significantly associated with the prevalence of periodontitis. Among the TyG and modified TyG indices, TyG-WHtR exhibited the highest predictive performance for periodontitis.
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Affiliation(s)
- Hyun-Jeong Lee
- Department of Family Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Ji-Won Lee
- Department of Family Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Sue Kim
- International Health Care Center, Severance Hospital, Yonsei University Health System, Seoul, Korea
| | - Yu-Jin Kwon
- Department of Family Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si, Korea
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Waist Circumference Is an Essential Factor in Predicting Insulin Resistance and Early Detection of Metabolic Syndrome in Adults. Nutrients 2023; 15:nu15020257. [PMID: 36678129 PMCID: PMC9861022 DOI: 10.3390/nu15020257] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 12/27/2022] [Accepted: 12/28/2022] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Metabolic syndrome (Met-S) is considered one of the most important health problems of the 21st century. It includes a group of metabolic disorders that increase the risk of cardiovascular diseases such as overweight and obesity, elevated lipid profile and blood pressure and insulin resistance (IR). Based on the information mentioned above in which there seems to be a relationship between IR and Met-S, the objective of this work was twofold: on the one hand, to assess the relationship between the values of different insulin resistance risk scales and Met-S determined with three different scales, and on the other, to determine whether any of the components of Met-S predispose more to the appearance of IR. METHODS A descriptive cross-sectional study of 418,343 workers. Waist circumference was measured and evaluated together with six formulas to assess the insulin resistance index. Categorical variables were evaluated by calculating the frequency and distribution of each one. For quantitative variables, mean and standard deviation were determined, and Student's t-test was applied, while for qualitative variables, the chi-square test was performed. The usefulness of the different risk scales for insulin resistance for predicting metabolic syndrome was evaluated using ROC curves, the area under the curve (AUC), as well as their cut-off points for sensitivity, specificity, and the Youden index. RESULTS People with metabolic syndrome applying any criteria had higher values in the IR risk scales. The different IR scales made it possible to adequately classify people with metabolic syndrome. Of the three definitions of Met-S, the one that showed the greatest relationship with IR was IDF. CONCLUSIONS Most risk scales for insulin resistance enable the presence of metabolic syndrome to be adequately classified, finding the best ones if the International Diabetes Federation (IDF) criteria are applied. Of the elements included in the Met-S, the one that seems to increase the risk of presenting IR the most is waist circumference; hence, the Met-S definition that is most related to IR is that of the IDF, which is the only one of the three in which a high value of waist circumference is necessary to be able to diagnose Met-S. Waist circumference can be considered the central essential component for detecting insulin resistance and, therefore, the early detection of metabolic syndrome.
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Zhang X, Zhang T, He S, Jia S, Zhang Z, Ye R, Yang X, Chen X. Retraction Note to: Association of metabolic syndrome with TyG index and TyG-related parameters in an urban Chinese population: a 15-year prospective study. Diabetol Metab Syndr 2022; 14:118. [PMID: 35986407 PMCID: PMC9392348 DOI: 10.1186/s13098-022-00889-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Affiliation(s)
- Xin Zhang
- Department of Cardiology, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Chengdu, 610041, China
| | - Ting Zhang
- Department of Cardiology, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Chengdu, 610041, China
| | - Sen He
- Department of Cardiology, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Chengdu, 610041, China.
| | - Shanshan Jia
- Department of Cardiology, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Chengdu, 610041, China
| | - Zhipeng Zhang
- Department of Cardiology, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Chengdu, 610041, China
| | - Runyu Ye
- Department of Cardiology, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Chengdu, 610041, China
| | - Xiangyu Yang
- Department of Cardiology, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Chengdu, 610041, China
| | - Xiaoping Chen
- Department of Cardiology, West China Hospital, Sichuan University, No. 37 Guo Xue Alley, Chengdu, 610041, China.
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