Change in triglyceride-glucose index predicts the risk of cardiovascular disease in the general population: a prospective cohort study

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Abstract

Background

Previous studies has shown a significant relationship between baseline triglyceride-glucose (TyG) index and subsequent cardiovascular disease (CVD). However, the effect of longitudinal changes in TyG index on the risk of CVD remains uncertain. This study aimed to investigate the association between change in TyG index and the risk of CVD in the general population.

Methods

The current study included 62,443 Chinese population who were free of CVD. The TyG index was calculated as ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2], and change in TyG index was defined as the difference between the TyG index in 2010 and that in 2006. Multivariable-adjusted Cox proportional hazard models and restricted cubic spline analysis were used to examine the association between change in TyG index and the risk of CVD.

Results

During a median follow-up of 7.01 years, 2530 (4.05%) incident CVD occurred, including 2018 (3.23%) incident stroke and 545 (0.87%) incident myocardial infarction (MI). The risk of developing CVD increased with the quartile of change in TyG index, after adjustment for multiple potential confounders, the hazard ratios for the Q4 group versus the Q1 group were 1.37 (95% confidence interval [CI], 1.21–1.54) for the overall CVD, 1.38 (95% CI, 1.19–1.60) for stroke, and 1.36 (95% CI, 1.05–1.76) for MI. Restricted cubic spline analysis also showed a cumulative increase in the risk of CVD with increases in the magnitude of change in TyG index. The addition of change in TyG index to a baseline risk model for CVD improved the C-statistics ( P = 0.0097), integrated discrimination improvement value ( P < 0.0001), and category-free net reclassification improvement value ( P < 0.0001). Similar results were observed for stroke and MI.

Conclusions

Substantial changes in TyG index independently predict the risk of CVD in the general population. Monitoring long-term changes in TyG may assist with in the early identification of individuals at high risk of CVD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01305-7.

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Most cited references 39

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Association between insulin resistance and the development of cardiovascular disease

Valeska Ormazabal, Soumyalekshmi Nair, Omar Elfeky … (2018)

For many years, cardiovascular disease (CVD) has been the leading cause of death around the world. Often associated with CVD are comorbidities such as obesity, abnormal lipid profiles and insulin resistance. Insulin is a key hormone that functions as a regulator of cellular metabolism in many tissues in the human body. Insulin resistance is defined as a decrease in tissue response to insulin stimulation thus insulin resistance is characterized by defects in uptake and oxidation of glucose, a decrease in glycogen synthesis, and, to a lesser extent, the ability to suppress lipid oxidation. Literature widely suggests that free fatty acids are the predominant substrate used in the adult myocardium for ATP production, however, the cardiac metabolic network is highly flexible and can use other substrates, such as glucose, lactate or amino acids. During insulin resistance, several metabolic alterations induce the development of cardiovascular disease. For instance, insulin resistance can induce an imbalance in glucose metabolism that generates chronic hyperglycemia, which in turn triggers oxidative stress and causes an inflammatory response that leads to cell damage. Insulin resistance can also alter systemic lipid metabolism which then leads to the development of dyslipidemia and the well-known lipid triad: (1) high levels of plasma triglycerides, (2) low levels of high-density lipoprotein, and (3) the appearance of small dense low-density lipoproteins. This triad, along with endothelial dysfunction, which can also be induced by aberrant insulin signaling, contribute to atherosclerotic plaque formation. Regarding the systemic consequences associated with insulin resistance and the metabolic cardiac alterations, it can be concluded that insulin resistance in the myocardium generates damage by at least three different mechanisms: (1) signal transduction alteration, (2) impaired regulation of substrate metabolism, and (3) altered delivery of substrates to the myocardium. The aim of this review is to discuss the mechanisms associated with insulin resistance and the development of CVD. New therapies focused on decreasing insulin resistance may contribute to a decrease in both CVD and atherosclerotic plaque generation.

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Dose-response analyses using restricted cubic spline functions in public health research.

Loïc Desquilbet, François Mariotti (2010)

Taking into account a continuous exposure in regression models by using categorization, when non-linear dose-response associations are expected, have been widely criticized. As one alternative, restricted cubic spline (RCS) functions are powerful tools (i) to characterize a dose-response association between a continuous exposure and an outcome, (ii) to visually and/or statistically check the assumption of linearity of the association, and (iii) to minimize residual confounding when adjusting for a continuous exposure. Because their implementation with SAS® software is limited, we developed and present here an SAS macro that (i) creates an RCS function of continuous exposures, (ii) displays graphs showing the dose-response association with 95 per cent confidence interval between one main continuous exposure and an outcome when performing linear, logistic, or Cox models, as well as linear and logistic-generalized estimating equations, and (iii) provides statistical tests for overall and non-linear associations. We illustrate the SAS macro using the third National Health and Nutrition Examination Survey data to investigate adjusted dose-response associations (with different models) between calcium intake and bone mineral density (linear regression), folate intake and hyperhomocysteinemia (logistic regression), and serum high-density lipoprotein cholesterol and cardiovascular mortality (Cox model). 2010 John Wiley & Sons, Ltd.

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The TyG index may predict the development of cardiovascular events.

Laura Sánchez-Íñigo, David Navarro-González, Alejandro Fernández-Montero … (2016)

Cardiovascular disease (CVD) is the worldwide leading cause of morbidity and mortality. An early risk detection of apparently healthy people before CVD onset has clinical relevance in the prevention of cardiovascular events. We evaluated the association between the product of fasting plasma glucose and triglycerides (TyG index) and CVD.

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Author and article information

Contributors

Shouling Wu:

ORCID: http://orcid.org/0000-0001-7095-6022

drwusl@163.com

Yongjun Wang: yongjunwang@ncrcnd.org.cn

Journal

Journal ID (nlm-ta): Cardiovasc Diabetol

Journal ID (iso-abbrev): Cardiovasc Diabetol

Title: Cardiovascular Diabetology

Publisher: BioMed Central (London )

ISSN (Electronic): 1475-2840

Publication date (Electronic): 26 May 2021

Publication date PMC-release: 26 May 2021

Publication date Collection: 2021

Volume: 20

Electronic Location Identifier: 113

Affiliations

[1 ]GRID grid.24696.3f, ISNI 0000 0004 0369 153X, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, , Capital Medical University, ; No.119 South 4th Ring West Road, Fengtai District, Beijing, 100070 China

[2 ]GRID grid.24696.3f, ISNI 0000 0004 0369 153X, Department of Neurology, Beijing Tiantan Hospital, , Capital Medical University, ; Beijing, China

[3 ]GRID grid.24696.3f, ISNI 0000 0004 0369 153X, Department of Epidemiology and Health Statistics, School of Public Health, , Capital Medical University, ; Beijing, China

[4 ]Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China

[5 ]GRID grid.440734.0, ISNI 0000 0001 0707 0296, Department of Cardiology, Kailuan Hospital, , North China University of Science and Technology, ; 57 Xinhua East Road, Tangshan, 063000 China

Author information

Shouling Wu http://orcid.org/0000-0001-7095-6022

Article

Publisher ID: 1305

DOI: 10.1186/s12933-021-01305-7

PMC ID: 8157734

PubMed ID: 34039351

SO-VID: 71364f31-5d40-4077-925f-3c39c0ae1328

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 29 March 2021

Date accepted : 19 May 2021

Funding

Funded by: National Key R&D Program of China

Award ID: 2018YFC1312903

Award Recipient : Yongjun Wang

Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;

Award ID: 81870905

Award Recipient : Yongjun Wang

Funded by: Beijing Municipal Science & Technology Commission

Award ID: D171100003017002

Award ID: Z181100001818001

Award Recipient : Yongjun Wang

Funded by: Beijing Municipal Administration of Hospitals Incubating Program

Award ID: PX2020021

Award Recipient : Anxin Wang

Funded by: Beijing Excellent Talents Training Program

Award ID: 2018000021469G234

Award Recipient : Anxin Wang

Funded by: Young Elite Scientists Sponsorship Program by CAST

Award ID: 2018QNRC001

Award Recipient : Anxin Wang

Custom metadata

ScienceOpen disciplines: Endocrinology & Diabetes

Keywords: triglyceride-glucose index,longitudinal changes,cardiovascular disease,stroke,myocardial infarction,predictive value

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ScienceOpen disciplines: Endocrinology & Diabetes

Keywords: triglyceride-glucose index, longitudinal changes, cardiovascular disease, stroke, myocardial infarction, predictive value

Change in triglyceride-glucose index predicts the risk of cardiovascular disease in the general population: a prospective cohort study

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Abstract

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Supplementary Information

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Karger: Cardiovascular System

Most cited references 39

Association between insulin resistance and the development of cardiovascular disease

Dose-response analyses using restricted cubic spline functions in public health research.

The TyG index may predict the development of cardiovascular events.

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