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Published in: Cardiovascular Diabetology 1/2024

Open Access 01-12-2024 | Research

Association between triglyceride-glucose related indices with the all-cause and cause-specific mortality among the population with metabolic syndrome

Authors: Xiaoyuan Wei, Yu Min, Ge Song, Xin Ye, Lei Liu

Published in: Cardiovascular Diabetology | Issue 1/2024

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Abstract

Background

Triglyceride-glucose (TyG) index has been determined to play a role in the onset of metabolic syndrome (MetS). Whether the TyG index and TyG with the combination of obesity indicators are associated with the clinical outcomes of the MetS population remains unknown.

Method

Participants were extracted from multiple cycles of the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018 years. Three indicators were constructed including TyG index, TyG combining with waist circumference (TyG-WC), and TyG combining with waist-to-height ratio (TyG-WHtR). The MetS was defined according to the National Cholesterol Education Program (NCPE) Adult Treatment Panel III. Kaplan-Meier (KM) curves, restricted cubic splines (RCS), and the Cox proportional hazard model were used to evaluate the associations between TyG-related indices and mortality of the MetS population. The sensitive analyses were performed to check the robustness of the main findings.

Results

There were 10,734 participants with MetS included in this study, with 5,570 females and 5,164 males. The median age of the study population was 59 years old. The multivariate Cox regression analyses showed high levels of TyG-related indices were significantly associated with the all-cause mortality of MetS population [TyG index: adjustedhazard ratio (aHR): 1.36, 95%confidence interval (CI): 1.18–1.56, p < 0.001; TyG-WHtR index: aHR = 1.29, 95%CI: 1.13–1.47, p < 0.001]. Meanwhile, the TyG-WC and TyG-WHtR index were associated with cardiovascular mortality of the MetS population (TyG-WC: aHR = 1.45, 95%CI: 1.13–1.85, p = 0.004; TyG-WHtR: aHR = 1.50 95%CI: 1.17–1.92, p = 0.002). Three TyG-related indices showed consistent significant correlations with diabetes mortality (TyG: aHR = 4.06, 95%CI: 2.81–5.87, p < 0.001; TyG-WC: aHR = 2.55, 95%CI: 1.82–3.58, p < 0.001; TyG-WHtR: aHR = 2.53 95%CI: 1.81–3.54, p < 0.001). The RCS curves showed a non-linear trend between TyG and TyG-WC indices with all-cause mortality (p for nonlinearity = 0.004 and 0.001, respectively). The sensitive analyses supported the positive correlations between TyG-related indices with mortality of the MetS population.

Conclusion

Our study highlights the clinical value of TyG-related indices in predicting the survival of the MetS population. TyG-related indices would be the surrogate biomarkers for the follow-up of the MetS population.
Appendix
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Literature
1.
4.
go back to reference Beltrán-Sánchez H, Harhay MO, Harhay MM, McElligott S. Prevalence and trends of metabolic syndrome in the adult U.S. population, 1999–2010. J Am Coll Cardiol. 2013;62(8):697–703.PubMedPubMedCentralCrossRef Beltrán-Sánchez H, Harhay MO, Harhay MM, McElligott S. Prevalence and trends of metabolic syndrome in the adult U.S. population, 1999–2010. J Am Coll Cardiol. 2013;62(8):697–703.PubMedPubMedCentralCrossRef
5.
go back to reference Shin D, Kongpakpaisarn K, Bohra C. Trends in the prevalence of metabolic syndrome and its components in the United States 2007–2014. Int J Cardiol. 2018;259:216–9.PubMedCrossRef Shin D, Kongpakpaisarn K, Bohra C. Trends in the prevalence of metabolic syndrome and its components in the United States 2007–2014. Int J Cardiol. 2018;259:216–9.PubMedCrossRef
6.
go back to reference Li W, Qiu X, Ma H, Geng Q. Incidence and long-term specific mortality trends of metabolic syndrome in the United States. Front Endocrinol. 2022;13:1029736.CrossRef Li W, Qiu X, Ma H, Geng Q. Incidence and long-term specific mortality trends of metabolic syndrome in the United States. Front Endocrinol. 2022;13:1029736.CrossRef
7.
go back to reference Mottillo S, Filion KB, Genest J, Joseph L, Pilote L, Poirier P, et al. The metabolic syndrome and cardiovascular risk a systematic review and meta-analysis. J Am Coll Cardiol. 2010;56(14):1113–32.PubMedCrossRef Mottillo S, Filion KB, Genest J, Joseph L, Pilote L, Poirier P, et al. The metabolic syndrome and cardiovascular risk a systematic review and meta-analysis. J Am Coll Cardiol. 2010;56(14):1113–32.PubMedCrossRef
9.
go back to reference Li W, Chen D, Peng Y, Lu Z, Kwan MP, Tse LA. Association between metabolic syndrome and mortality: prospective cohort study. JMIR Public Health Surveillance. 2023;9:e44073.PubMedPubMedCentralCrossRef Li W, Chen D, Peng Y, Lu Z, Kwan MP, Tse LA. Association between metabolic syndrome and mortality: prospective cohort study. JMIR Public Health Surveillance. 2023;9:e44073.PubMedPubMedCentralCrossRef
10.
go back to reference Fahed G, Aoun L, Bou Zerdan M, Allam S, Bou Zerdan M, Bouferraa Y et al. Metabolic syndrome: updates on pathophysiology and management in 2021. Int J Mol Sci. 2022;23(2). Fahed G, Aoun L, Bou Zerdan M, Allam S, Bou Zerdan M, Bouferraa Y et al. Metabolic syndrome: updates on pathophysiology and management in 2021. Int J Mol Sci. 2022;23(2).
11.
go back to reference Tahapary DL, Pratisthita LB, Fitri NA, Marcella C, Wafa S, Kurniawan F, et al. Challenges in the diagnosis of insulin resistance: focusing on the role of HOMA-IR and Tryglyceride/glucose index. Diabetes Metabolic Syndrome. 2022;16(8):102581.PubMedCrossRef Tahapary DL, Pratisthita LB, Fitri NA, Marcella C, Wafa S, Kurniawan F, et al. Challenges in the diagnosis of insulin resistance: focusing on the role of HOMA-IR and Tryglyceride/glucose index. Diabetes Metabolic Syndrome. 2022;16(8):102581.PubMedCrossRef
12.
go back to reference Tao LC, Xu JN, Wang TT, Hua F, Li JJ. Triglyceride-glucose index as a marker in cardiovascular diseases: landscape and limitations. Cardiovasc Diabetol. 2022;21(1):68.PubMedPubMedCentralCrossRef Tao LC, Xu JN, Wang TT, Hua F, Li JJ. Triglyceride-glucose index as a marker in cardiovascular diseases: landscape and limitations. Cardiovasc Diabetol. 2022;21(1):68.PubMedPubMedCentralCrossRef
13.
go back to reference Mirr M, Skrypnik D, Bogdański P, Owecki M. Newly proposed insulin resistance indexes called TyG-NC and TyG-NHtR show efficacy in diagnosing the metabolic syndrome. J Endocrinol Investig. 2021;44(12):2831–43.CrossRef Mirr M, Skrypnik D, Bogdański P, Owecki M. Newly proposed insulin resistance indexes called TyG-NC and TyG-NHtR show efficacy in diagnosing the metabolic syndrome. J Endocrinol Investig. 2021;44(12):2831–43.CrossRef
14.
go back to reference Son DH, Lee HS, Lee YJ, Lee JH, Han JH. Comparison of triglyceride-glucose index and HOMA-IR for predicting prevalence and incidence of metabolic syndrome. Nutrition, metabolism, and cardiovascular diseases. NMCD. 2022;32(3):596–604.PubMed Son DH, Lee HS, Lee YJ, Lee JH, Han JH. Comparison of triglyceride-glucose index and HOMA-IR for predicting prevalence and incidence of metabolic syndrome. Nutrition, metabolism, and cardiovascular diseases. NMCD. 2022;32(3):596–604.PubMed
15.
go back to reference Li Y, Zheng R, Li S, Cai R, Ni F, Zheng H, et al. Association between four anthropometric indexes and metabolic syndrome in US adults. Front Endocrinol. 2022;13:889785.CrossRef Li Y, Zheng R, Li S, Cai R, Ni F, Zheng H, et al. Association between four anthropometric indexes and metabolic syndrome in US adults. Front Endocrinol. 2022;13:889785.CrossRef
16.
go back to reference Kang SW, Kim SK, Kim YS, Park MS. Risk prediction of the metabolic syndrome using TyG index and SNPs: a 10-year longitudinal prospective cohort study. Mol Cell Biochem. 2023;478(1):39–45.PubMedCrossRef Kang SW, Kim SK, Kim YS, Park MS. Risk prediction of the metabolic syndrome using TyG index and SNPs: a 10-year longitudinal prospective cohort study. Mol Cell Biochem. 2023;478(1):39–45.PubMedCrossRef
17.
go back to reference Primo D, Izaola O, de Luis DA. Triglyceride-glucose index cutoff point is an accurate marker for Predicting the prevalence of metabolic syndrome in obese caucasian subjects. Ann Nutr Metab. 2023;79(2):70–7.CrossRef Primo D, Izaola O, de Luis DA. Triglyceride-glucose index cutoff point is an accurate marker for Predicting the prevalence of metabolic syndrome in obese caucasian subjects. Ann Nutr Metab. 2023;79(2):70–7.CrossRef
18.
go back to reference Li Y, Gui J, Liu H, Guo LL, Li J, Lei Y, et al. Predicting metabolic syndrome by obesity- and lipid-related indices in mid-aged and elderly Chinese: a population-based cross-sectional study. Front Endocrinol. 2023;14:1201132.CrossRef Li Y, Gui J, Liu H, Guo LL, Li J, Lei Y, et al. Predicting metabolic syndrome by obesity- and lipid-related indices in mid-aged and elderly Chinese: a population-based cross-sectional study. Front Endocrinol. 2023;14:1201132.CrossRef
19.
go back to reference Nabipoorashrafi SA, Seyedi SA, Rabizadeh S, Ebrahimi M, Ranjbar SA, Reyhan SK, et al. The accuracy of triglyceride-glucose (TyG) index for the screening of metabolic syndrome in adults: a systematic review and meta-analysis. Nutrition, metabolism, and cardiovascular diseases. NMCD. 2022;32(12):2677–88.PubMed Nabipoorashrafi SA, Seyedi SA, Rabizadeh S, Ebrahimi M, Ranjbar SA, Reyhan SK, et al. The accuracy of triglyceride-glucose (TyG) index for the screening of metabolic syndrome in adults: a systematic review and meta-analysis. Nutrition, metabolism, and cardiovascular diseases. NMCD. 2022;32(12):2677–88.PubMed
20.
go back to reference Liao Y, Zhang R, Shi S, Zhao Y, He Y, Liao L, et al. Triglyceride-glucose index linked to all-cause mortality in critically ill patients: a cohort of 3026 patients. Cardiovasc Diabetol. 2022;21(1):128.PubMedPubMedCentralCrossRef Liao Y, Zhang R, Shi S, Zhao Y, He Y, Liao L, et al. Triglyceride-glucose index linked to all-cause mortality in critically ill patients: a cohort of 3026 patients. Cardiovasc Diabetol. 2022;21(1):128.PubMedPubMedCentralCrossRef
21.
go back to reference Boshen Y, Yuankang Z, Xinjie Z, Taixi L, Kaifan N, Zhixiang W, et al. Triglyceride-glucose index is associated with the occurrence and prognosis of cardiac arrest: a multicenter retrospective observational study. Cardiovasc Diabetol. 2023;22(1):190.PubMedPubMedCentralCrossRef Boshen Y, Yuankang Z, Xinjie Z, Taixi L, Kaifan N, Zhixiang W, et al. Triglyceride-glucose index is associated with the occurrence and prognosis of cardiac arrest: a multicenter retrospective observational study. Cardiovasc Diabetol. 2023;22(1):190.PubMedPubMedCentralCrossRef
22.
go back to reference Liang S, Wang C, Zhang J, Liu Z, Bai Y, Chen Z, et al. Triglyceride-glucose index and coronary artery disease: a systematic review and meta-analysis of risk, severity, and prognosis. Cardiovasc Diabetol. 2023;22(1):170.PubMedPubMedCentralCrossRef Liang S, Wang C, Zhang J, Liu Z, Bai Y, Chen Z, et al. Triglyceride-glucose index and coronary artery disease: a systematic review and meta-analysis of risk, severity, and prognosis. Cardiovasc Diabetol. 2023;22(1):170.PubMedPubMedCentralCrossRef
23.
go back to reference Zhou Y, Wang C, Che H, Cheng L, Zhu D, Rao C, et al. Association between the triglyceride-glucose index and the risk of mortality among patients with chronic heart failure: results from a retrospective cohort study in China. Cardiovasc Diabetol. 2023;22(1):171.PubMedPubMedCentralCrossRef Zhou Y, Wang C, Che H, Cheng L, Zhu D, Rao C, et al. Association between the triglyceride-glucose index and the risk of mortality among patients with chronic heart failure: results from a retrospective cohort study in China. Cardiovasc Diabetol. 2023;22(1):171.PubMedPubMedCentralCrossRef
24.
go back to reference Kityo A, Lee SA. Association of cardiometabolic factors and insulin resistance surrogates with mortality in participants from the Korean Genome and Epidemiology Study. Lipids Health Dis. 2023;22(1):210.PubMedPubMedCentralCrossRef Kityo A, Lee SA. Association of cardiometabolic factors and insulin resistance surrogates with mortality in participants from the Korean Genome and Epidemiology Study. Lipids Health Dis. 2023;22(1):210.PubMedPubMedCentralCrossRef
25.
go back to reference Dang K, Wang X, Hu J, Zhang Y, Cheng L, Qi X, et al. The association between triglyceride-glucose index and its combination with obesity indicators and cardiovascular disease: NHANES 2003–2018. Cardiovasc Diabetol. 2024;23(1):8.PubMedPubMedCentralCrossRef Dang K, Wang X, Hu J, Zhang Y, Cheng L, Qi X, et al. The association between triglyceride-glucose index and its combination with obesity indicators and cardiovascular disease: NHANES 2003–2018. Cardiovasc Diabetol. 2024;23(1):8.PubMedPubMedCentralCrossRef
26.
go back to reference Er LK, Wu S, Chou HH, Hsu LA, Teng MS, Sun YC, et al. Triglyceride glucose-body Mass Index is a simple and clinically useful surrogate marker for insulin resistance in nondiabetic individuals. PLoS ONE. 2016;11(3):e0149731.PubMedPubMedCentralCrossRef Er LK, Wu S, Chou HH, Hsu LA, Teng MS, Sun YC, et al. Triglyceride glucose-body Mass Index is a simple and clinically useful surrogate marker for insulin resistance in nondiabetic individuals. PLoS ONE. 2016;11(3):e0149731.PubMedPubMedCentralCrossRef
27.
go back to reference Johnson CL, Dohrmann SM, Burt VL, Mohadjer LK. National health and nutrition examination survey: sample design, 2011–2014. Vital and health statistics Series 2, Data evaluation and methods research. 2014(162):1–33. Johnson CL, Dohrmann SM, Burt VL, Mohadjer LK. National health and nutrition examination survey: sample design, 2011–2014. Vital and health statistics Series 2, Data evaluation and methods research. 2014(162):1–33.
28.
go back to reference Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP). Expert Panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). JAMA. 2001;285(19):2486–97.CrossRef Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP). Expert Panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). JAMA. 2001;285(19):2486–97.CrossRef
29.
go back to reference Ding Z, Ge M, Tan Y, Chen C, Hei Z. The triglyceride-glucose index: a novel predictor of stroke and all-cause mortality in liver transplantation recipients. Cardiovasc Diabetol. 2024;23(1):27.PubMedPubMedCentralCrossRef Ding Z, Ge M, Tan Y, Chen C, Hei Z. The triglyceride-glucose index: a novel predictor of stroke and all-cause mortality in liver transplantation recipients. Cardiovasc Diabetol. 2024;23(1):27.PubMedPubMedCentralCrossRef
30.
go back to reference Yan F, Yan S, Wang J, Cui Y, Chen F, Fang F, et al. Association between triglyceride glucose index and risk of cerebrovascular disease: systematic review and meta-analysis. Cardiovasc Diabetol. 2022;21(1):226.PubMedPubMedCentralCrossRef Yan F, Yan S, Wang J, Cui Y, Chen F, Fang F, et al. Association between triglyceride glucose index and risk of cerebrovascular disease: systematic review and meta-analysis. Cardiovasc Diabetol. 2022;21(1):226.PubMedPubMedCentralCrossRef
31.
go back to reference Ashwell M, Gunn P, Gibson S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obes Reviews: Official J Int Association Study Obes. 2012;13(3):275–86.CrossRef Ashwell M, Gunn P, Gibson S. Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obes Reviews: Official J Int Association Study Obes. 2012;13(3):275–86.CrossRef
32.
go back to reference Simental-Mendía LE, Rodríguez-Morán M, Guerrero-Romero F. The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects. Metab Syndr Relat Disord. 2008;6(4):299–304.PubMedCrossRef Simental-Mendía LE, Rodríguez-Morán M, Guerrero-Romero F. The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects. Metab Syndr Relat Disord. 2008;6(4):299–304.PubMedCrossRef
33.
go back to reference Zheng S, Shi S, Ren X, Han T, Li Y, Chen Y, et al. Triglyceride glucose-waist circumference, a novel and effective predictor of diabetes in first-degree relatives of type 2 diabetes patients: cross-sectional and prospective cohort study. J Translational Med. 2016;14(1):260.CrossRef Zheng S, Shi S, Ren X, Han T, Li Y, Chen Y, et al. Triglyceride glucose-waist circumference, a novel and effective predictor of diabetes in first-degree relatives of type 2 diabetes patients: cross-sectional and prospective cohort study. J Translational Med. 2016;14(1):260.CrossRef
34.
go back to reference Lim J, Kim J, Koo SH, Kwon GC. Comparison of triglyceride glucose index, and related parameters to predict insulin resistance in Korean adults: an analysis of the 2007–2010 Korean National Health and Nutrition Examination Survey. PLoS ONE. 2019;14(3):e0212963.PubMedPubMedCentralCrossRef Lim J, Kim J, Koo SH, Kwon GC. Comparison of triglyceride glucose index, and related parameters to predict insulin resistance in Korean adults: an analysis of the 2007–2010 Korean National Health and Nutrition Examination Survey. PLoS ONE. 2019;14(3):e0212963.PubMedPubMedCentralCrossRef
35.
go back to reference Cao C, Cade WT, Li S, McMillan J, Friedenreich C, Yang L. Association of balance function with all-cause and cause-Specific Mortality among US adults. JAMA otolaryngology– head neck Surg. 2021;147(5):460–8.CrossRef Cao C, Cade WT, Li S, McMillan J, Friedenreich C, Yang L. Association of balance function with all-cause and cause-Specific Mortality among US adults. JAMA otolaryngology– head neck Surg. 2021;147(5):460–8.CrossRef
36.
go back to reference Abha P, Keshari JR, Sinha SR, Nishant K, Kumari R, Prakash P. Association of thyroid function with lipid Profile in patients with metabolic syndrome: a prospective cross-sectional study in the Indian Population. Cureus. 2023;15(9):e44745.PubMedPubMedCentral Abha P, Keshari JR, Sinha SR, Nishant K, Kumari R, Prakash P. Association of thyroid function with lipid Profile in patients with metabolic syndrome: a prospective cross-sectional study in the Indian Population. Cureus. 2023;15(9):e44745.PubMedPubMedCentral
37.
go back to reference Bland JM, Altman DG. Multiple significance tests: the Bonferroni method. BMJ (Clinical Res ed). 1995;310(6973):170.CrossRef Bland JM, Altman DG. Multiple significance tests: the Bonferroni method. BMJ (Clinical Res ed). 1995;310(6973):170.CrossRef
38.
go back to reference Nilsson PM, Tuomilehto J, Rydén L. The metabolic syndrome - what is it and how should it be managed? Eur J Prev Cardiol. 2019;26(2suppl):33–46.PubMedCrossRef Nilsson PM, Tuomilehto J, Rydén L. The metabolic syndrome - what is it and how should it be managed? Eur J Prev Cardiol. 2019;26(2suppl):33–46.PubMedCrossRef
39.
go back to reference Duan Y, Zhang W, Li Z, Niu Y, Chen Y, Liu X, et al. Predictive ability of obesity- and lipid-related indicators for metabolic syndrome in relatively healthy Chinese adults. Front Endocrinol. 2022;13:1016581.CrossRef Duan Y, Zhang W, Li Z, Niu Y, Chen Y, Liu X, et al. Predictive ability of obesity- and lipid-related indicators for metabolic syndrome in relatively healthy Chinese adults. Front Endocrinol. 2022;13:1016581.CrossRef
40.
go back to reference Zheng R, Qian S, Shi Y, Lou C, Xu H, Pan J. Association between triglyceride-glucose index and in-hospital mortality in critically ill patients with sepsis: analysis of the MIMIC-IV database. Cardiovasc Diabetol. 2023;22(1):307.PubMedPubMedCentralCrossRef Zheng R, Qian S, Shi Y, Lou C, Xu H, Pan J. Association between triglyceride-glucose index and in-hospital mortality in critically ill patients with sepsis: analysis of the MIMIC-IV database. Cardiovasc Diabetol. 2023;22(1):307.PubMedPubMedCentralCrossRef
41.
go back to reference Huang R, Xu X, Xu C, Zhang S, Xiong Z, Liu M, et al. Association between the insulin resistance and all-cause mortality in patients with moderate and severe aortic stenosis: a retrospective cohort study. Cardiovasc Diabetol. 2023;22(1):238.PubMedPubMedCentralCrossRef Huang R, Xu X, Xu C, Zhang S, Xiong Z, Liu M, et al. Association between the insulin resistance and all-cause mortality in patients with moderate and severe aortic stenosis: a retrospective cohort study. Cardiovasc Diabetol. 2023;22(1):238.PubMedPubMedCentralCrossRef
42.
go back to reference Ren H, Yang Y, Wang F, Yan Y, Shi X, Dong K, et al. Association of the insulin resistance marker TyG index with the severity and mortality of COVID-19. Cardiovasc Diabetol. 2020;19(1):58.PubMedPubMedCentralCrossRef Ren H, Yang Y, Wang F, Yan Y, Shi X, Dong K, et al. Association of the insulin resistance marker TyG index with the severity and mortality of COVID-19. Cardiovasc Diabetol. 2020;19(1):58.PubMedPubMedCentralCrossRef
43.
go back to reference Zhang R, Shi S, Chen W, Wang Y, Lin X, Zhao Y, et al. Independent effects of the triglyceride-glucose index on all-cause mortality in critically ill patients with coronary heart disease: analysis of the MIMIC-III database. Cardiovasc Diabetol. 2023;22(1):10.PubMedPubMedCentralCrossRef Zhang R, Shi S, Chen W, Wang Y, Lin X, Zhao Y, et al. Independent effects of the triglyceride-glucose index on all-cause mortality in critically ill patients with coronary heart disease: analysis of the MIMIC-III database. Cardiovasc Diabetol. 2023;22(1):10.PubMedPubMedCentralCrossRef
44.
go back to reference Antonopoulos AS, Oikonomou EK, Antoniades C, Tousoulis D. From the BMI paradox to the obesity paradox: the obesity-mortality association in coronary heart disease. Obes Reviews: Official J Int Association Study Obes. 2016;17(10):989–1000.CrossRef Antonopoulos AS, Oikonomou EK, Antoniades C, Tousoulis D. From the BMI paradox to the obesity paradox: the obesity-mortality association in coronary heart disease. Obes Reviews: Official J Int Association Study Obes. 2016;17(10):989–1000.CrossRef
45.
go back to reference Strulov Shachar S, Williams GR. The obesity Paradox in Cancer-moving beyond BMI. Cancer epidemiology, biomarkers & prevention: a publication of the American Association for Cancer Research. Cosponsored Am Soc Prev Oncol. 2017;26(1):13–6. Strulov Shachar S, Williams GR. The obesity Paradox in Cancer-moving beyond BMI. Cancer epidemiology, biomarkers & prevention: a publication of the American Association for Cancer Research. Cosponsored Am Soc Prev Oncol. 2017;26(1):13–6.
46.
48.
go back to reference Jayedi A, Soltani S, Zargar MS, Khan TA, Shab-Bidar S. Central fatness and risk of all cause mortality: systematic review and dose-response meta-analysis of 72 prospective cohort studies. BMJ (Clinical Res ed). 2020;370:m3324. Jayedi A, Soltani S, Zargar MS, Khan TA, Shab-Bidar S. Central fatness and risk of all cause mortality: systematic review and dose-response meta-analysis of 72 prospective cohort studies. BMJ (Clinical Res ed). 2020;370:m3324.
49.
go back to reference Ramírez-Manent JI, Jover AM, Martinez CS, Tomás-Gil P, Martí-Lliteras P, López-González. Á A. Waist circumference is an essential factor in Predicting insulin resistance and early detection of metabolic syndrome in adults. Nutrients. 2023;15(2). Ramírez-Manent JI, Jover AM, Martinez CS, Tomás-Gil P, Martí-Lliteras P, López-González. Á A. Waist circumference is an essential factor in Predicting insulin resistance and early detection of metabolic syndrome in adults. Nutrients. 2023;15(2).
50.
go back to reference Kawada T, Andou T, Fukumitsu M. Waist circumference, visceral abdominal fat thickness and three components of metabolic syndrome. Diabetes Metabolic Syndrome. 2016;10(1):4–6.PubMedCrossRef Kawada T, Andou T, Fukumitsu M. Waist circumference, visceral abdominal fat thickness and three components of metabolic syndrome. Diabetes Metabolic Syndrome. 2016;10(1):4–6.PubMedCrossRef
51.
go back to reference Claypool K, Long MT, Patel CJ. Waist circumference and insulin resistance are the most predictive metabolic factors for steatosis and fibrosis. Clin Gastroenterol Hepatology: Official Clin Pract J Am Gastroenterological Association. 2023;21(7):1950–e41.CrossRef Claypool K, Long MT, Patel CJ. Waist circumference and insulin resistance are the most predictive metabolic factors for steatosis and fibrosis. Clin Gastroenterol Hepatology: Official Clin Pract J Am Gastroenterological Association. 2023;21(7):1950–e41.CrossRef
52.
go back to reference Xia B, He Q, Pan Y, Gao F, Liu A, Tang Y, et al. Metabolic syndrome and risk of pancreatic cancer: a population-based prospective cohort study. Int J Cancer. 2020;147(12):3384–93.PubMedCrossRef Xia B, He Q, Pan Y, Gao F, Liu A, Tang Y, et al. Metabolic syndrome and risk of pancreatic cancer: a population-based prospective cohort study. Int J Cancer. 2020;147(12):3384–93.PubMedCrossRef
53.
go back to reference Wu CJ, Kao TW, Chen YY, Yang HF, Chen WL. Peripheral fat distribution versus waist circumference for predicting mortality in metabolic syndrome. Diab/Metab Res Rev. 2019;35(4):e3116.CrossRef Wu CJ, Kao TW, Chen YY, Yang HF, Chen WL. Peripheral fat distribution versus waist circumference for predicting mortality in metabolic syndrome. Diab/Metab Res Rev. 2019;35(4):e3116.CrossRef
54.
go back to reference Katzmarzyk PT, Janssen I, Ross R, Church TS, Blair SN. The importance of waist circumference in the definition of metabolic syndrome: prospective analyses of mortality in men. Diabetes Care. 2006;29(2):404–9.PubMedCrossRef Katzmarzyk PT, Janssen I, Ross R, Church TS, Blair SN. The importance of waist circumference in the definition of metabolic syndrome: prospective analyses of mortality in men. Diabetes Care. 2006;29(2):404–9.PubMedCrossRef
55.
go back to reference Xiao X, Yu X, Zhu H, Zhai X, Li S, Ma W et al. Arm circumference, arm-to-Waist ratio in relation to Cardiovascular and all-cause mortality among patients with diabetes Mellitus. Nutrients. 2023;15(4). Xiao X, Yu X, Zhu H, Zhai X, Li S, Ma W et al. Arm circumference, arm-to-Waist ratio in relation to Cardiovascular and all-cause mortality among patients with diabetes Mellitus. Nutrients. 2023;15(4).
56.
go back to reference Yuan Y, Liu K, Zheng M, Chen S, Wang H, Jiang Q, et al. Analysis of changes in Weight, Waist circumference, or both, and all-cause mortality in Chinese adults. JAMA Netw open. 2022;5(8):e2225876.PubMedPubMedCentralCrossRef Yuan Y, Liu K, Zheng M, Chen S, Wang H, Jiang Q, et al. Analysis of changes in Weight, Waist circumference, or both, and all-cause mortality in Chinese adults. JAMA Netw open. 2022;5(8):e2225876.PubMedPubMedCentralCrossRef
57.
go back to reference Lo K, Huang YQ, Shen G, Huang JY, Liu L, Yu YL, et al. Effects of waist to height ratio, waist circumference, body mass index on the risk of chronic diseases, all-cause, cardiovascular and cancer mortality. Postgrad Med J. 2021;97(1147):306–11.PubMedCrossRef Lo K, Huang YQ, Shen G, Huang JY, Liu L, Yu YL, et al. Effects of waist to height ratio, waist circumference, body mass index on the risk of chronic diseases, all-cause, cardiovascular and cancer mortality. Postgrad Med J. 2021;97(1147):306–11.PubMedCrossRef
58.
go back to reference Schneider HJ, Friedrich N, Klotsche J, Pieper L, Nauck M, John U, et al. The predictive value of different measures of obesity for incident cardiovascular events and mortality. J Clin Endocrinol Metab. 2010;95(4):1777–85.PubMedCrossRef Schneider HJ, Friedrich N, Klotsche J, Pieper L, Nauck M, John U, et al. The predictive value of different measures of obesity for incident cardiovascular events and mortality. J Clin Endocrinol Metab. 2010;95(4):1777–85.PubMedCrossRef
59.
go back to reference Parente EB, Mutter S, Harjutsalo V, Ahola AJ, Forsblom C, Groop PH. Waist-height ratio and waist are the best estimators of visceral fat in type 1 diabetes. Sci Rep. 2020;10(1):18575.PubMedPubMedCentralCrossRef Parente EB, Mutter S, Harjutsalo V, Ahola AJ, Forsblom C, Groop PH. Waist-height ratio and waist are the best estimators of visceral fat in type 1 diabetes. Sci Rep. 2020;10(1):18575.PubMedPubMedCentralCrossRef
61.
go back to reference Olefsky JM, Glass CK. Macrophages, inflammation, and insulin resistance. Annu Rev Physiol. 2010;72:219–46.PubMedCrossRef Olefsky JM, Glass CK. Macrophages, inflammation, and insulin resistance. Annu Rev Physiol. 2010;72:219–46.PubMedCrossRef
62.
go back to reference Glass CK, Olefsky JM. Inflammation and lipid signaling in the etiology of insulin resistance. Cell Metabol. 2012;15(5):635–45.CrossRef Glass CK, Olefsky JM. Inflammation and lipid signaling in the etiology of insulin resistance. Cell Metabol. 2012;15(5):635–45.CrossRef
Metadata
Title
Association between triglyceride-glucose related indices with the all-cause and cause-specific mortality among the population with metabolic syndrome
Authors
Xiaoyuan Wei
Yu Min
Ge Song
Xin Ye
Lei Liu
Publication date
01-12-2024
Publisher
BioMed Central
Published in
Cardiovascular Diabetology / Issue 1/2024
Electronic ISSN: 1475-2840
DOI
https://doi.org/10.1186/s12933-024-02215-0

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