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Triglyceride glucose-waist circumference as a predictor of mortality and subtypes of cardiovascular disease: a systematic review and meta-analysis

Diabetology & Metabolic Syndrome volume 17, Article number: 59 (2025) Cite this article

Abstract

Background

The significant burden of cardiovascular diseases underscores the necessity for identifying novel predictive markers that can forecast both cardiovascular diseases and mortality. In recent years, TyG-obesity-related parameters have gained special attention in this regard. This study aimed to assess the association between TyG-waist circumference (TyG-WC) and cardiovascular diseases and mortality.

Methods

A comprehensive search was performed in databases including PubMed, Scopus, and Web of Science from their inception until October 6, 2024. The key outcomes of interest included all-cause mortality, cardiovascular mortality, cardiovascular diseases, myocardial infarction, stroke, coronary artery diseases, peripheral artery diseases, and heart failure. The pooled risk ratio (RR) with corresponding 95% confidence intervals (CI) was calculated. Meta-analysis was carried out using StataMP 14.0.

Results

A total of 17 studies were included in the analysis. The number of participants ranged between 2,224 and 95,342. The meta-analysis revealed that TyG-WC is significantly associated with an increased risk of all-cause mortality, cardiovascular mortality, cardiovascular diseases, myocardial infarction, stroke, coronary artery diseases, and peripheral artery diseases. However, only one study addressed the relationship between TyG-WC and heart failure with a positive correlation.

Conclusion

This study indicates that TyG-WC could serve as a promising predictor of cardiovascular diseases, along with cardiovascular and all-cause mortality. Given its accessibility, TyG-WC may be a practical tool for screening purposes.

Introduction

The global burden of cardiovascular disease (CVD) remains a rising and major public health concern, representing the leading cause of morbidity and mortality from non-communicable diseases worldwide [1, 2]. Recognizing dependable indicators during the early stages of cardiovascular disease (CVD) is crucial for enhancing patient outcomes and preserving quality of life [3]. Traditional risk factors such as hypertension, dyslipidemia, obesity, and diabetes mellitus (DM) remain well-established contributors to CVD [4, 5]. However, the development of straightforward and novel indicators that combine multiple risk factors and reflect laboratory assessments or anthropometric evaluations is gaining increasing attention for their potential to enhance predictive accuracy [6].

One such index, the triglyceride-glucose-waist circumference (TyG-WC) index, has emerged as a promising tool for assessing insulin resistance (IR) and abdominal obesity, which are strongly linked to CVD risk [7].

IR is a pathological feature that is attributed to the development of DM and has been established to have a role in the pathogenesis of atherosclerotic CVD [8]. The glucose clamp technique, considered the gold standard for measuring IR, is highly accurate but impractical for routine clinical use due to its complexity, time requirements, and high cost [9, 10]. Therefore, other indirect methods, such as homeostatic assessment of insulin resistance (HOMA-IR) and TyG index, were developed for assessing IR [10].

In particular, the TyG index, by combining fasting triglyceride (TG) and fasting blood sugar (FBS), is firmly associated with the development of CVD [11,12,13]. Also, WC constitutes a simple, cost-effective, and non-invasive anthropometric measure that directly reflects abdominal adiposity and body fat distribution and better predicts health risks related to obesity [14]. More importantly, various studies have demonstrated that TyG-associated indicators, which integrate obesity metrics, such as TyG-WC, exhibit more efficacy as surrogate markers for assessing IR compared to the TyG index alone [15, 16].

TyG-WC index has also been significantly associated with increased CVD risk, coronary heart disease (CHD), stroke, and myocardial infarction (MI) in several cohort studies [7, 17]. However, the strength and consistency of this association across different populations and clinical settings remain unclear, as some insignificant results have also been reported regarding the association between TyG-WC and CVD [3, 18].

Given the increasing prevalence of obesity and IR and their role in CVD, understanding the association between the TyG-WC index and cardiovascular outcomes is crucial for informing public health strategies and clinical practice. Therefore, this systematic review and meta-analysis aims to assess the available evidence on this association, synthesizing data from observational studies to provide a clear understanding of the TyG-WC index’s utility in predicting CVD and clarify the role of this novel index in CVD prevention and risk stratification.

Materials and methods

Study design

This systematic review and meta-analysis was conducted following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [19].

Eligibility criteria

In this study, we included observational original studies that assessed the role of TyG-WC in predicting CVDs in the adults (age > 18). Furthermore, we included studies that reported on the risk of All-cause mortality, cardiovascular mortality, cardiovascular diseases (CVD), myocardial infarction (MI), coronary artery diseases (CAD), stroke, heart failure (HF), peripheral artery diseases (PAD).

This study did not include studies with incomplete data, studies on children and adolescents, conference abstracts, abstracts, expert opinions, reviews, case reports, case series, non-human and basic science studies, editorials, erratum, and letters. Also, we did not include kidney or liver-related outcomes. When a similar database was employed across several studies, we included the publication that provided the most comprehensive data or the most substantial sample size.

Search strategy

We systematically searched the following electronic databases from their inception until July 18, 2024: MEDLINE, EMBASE, Web of Science, Scopus. Additionally, we investigated Google Scholar and Google search engines. The comprehensive search query and the specific set of search terms related to TyG-WC and CVD for each database are delineated in Supplementary Table 1. Non-English studies were excluded from our review. To ensure complete coverage, no restrictions were imposed regarding publication dates.

Study selection

All studies retrieved will undergo a screening process characterized by two phases: Initially and after removing duplicates, two authors (H.S. and S.M.) independently evaluated the titles and abstracts of the search outcomes according to established eligibility criteria to identify potentially relevant studies. Subsequently, the full texts of articles that successfully passed the preliminary screening were subjected to an independent assessment by the same two authors to ascertain the final eligible studies for inclusion in this systematic review and data synthesis. Moreover, the authors manually examined related reviews’ reference and citation lists and included studies. In cases where critical data were lacking within the studies, additional information was solicited from the authors via email. A PRISMA flow diagram was used to systematically document the number of studies included at each phase of the screening process (Fig. 1). Any discrepancies encountered during the process were addressed through consultation with the third author (R.A.B). Endnote software version 21 was utilized to organize the search records.

Fig. 1
figure 1

Flowchart diagram of study selection

Full size image

Data extraction and management

Two independent authors (R.A.B. and B.D.) systematically extracted data from each research study, employing standardized data collection forms. The extracted information included several factors: the study design, the name of the first author, the year of publication, country, the study population, sample size, mean age, percent of female participants, TyG-WC values, and duration of follow-up. The fully adjusted effect estimates were derived for the following outcomes: Al-causes mortality, cardiovascular mortality, CVD, MI, CAD, stroke, HF, PAD. In instances where a study stratified participants into multiple groups (such as tertiles, quartiles, or quintiles), the authors exclusively extracted data that compared the highest with the lowest quantile.

Risk of bias assessment

The quality of included studies were assessed independently by two reviewers (B.D. and R.A.B.) using the Newcastle–Ottawa Quality Assessment Scale (NOS) for cohort and case control studies and adapted NOS for cross-sectional studies [20]. A third reviewer (M.R.) resolved disagreements.

Statistical analysis and data synthesis

The effect measure used in this meta-analysis was the relative risk (RR) for binary outcomes. Heterogeneity across studies was assessed using the I² statistic and Cochran’s Q test. A random-effects model was used if I2 ≥ 0.5 and p < 0.1. Subgroup analyses were performed to explore the potential influence of study-level characteristics on the observed associations. Sensitivity analyses were conducted to assess the robustness of the findings by excluding studies with high risk of bias. A subgroup analysis was performed according to the study design. Publication bias was evaluated visually using funnel plots and statistically using Egger’s regression test. The degree of interobserver agreement was evaluated using Cohen’s kappa test. All statistical analyses were performed using Stata (version 14.0).

Results

The initial search yielded a total of 2239 records. After removing duplicates, 1475 records remained. These records were then screened based on title and abstract, resulting in the exclusion of 981 records due to various reasons, including irrelevance to the topic, language restrictions, publication type, and non-human studies. The remaining 494 records were assessed for eligibility through full-text review. Of these, 477 were further excluded based on specific eligibility criteria. Ultimately, a total of 17 studies met the inclusion criteria and were included in the quantitative synthesis (Fig. 1). Kappa statistics indicated high interrater reliability for study selection (k = 0.87) and data extraction (k = 0.91).

Study characteristics

The summary enrolled studies are presented in Table 1. Most of the studies were published in 2024, except two studies which published in 2023 and 2022. The eligible studies compromised participants from Chine (eight studies), USA (six studies), Korea (two studies), and Iran (one study). The number of participants ranged between 2,224 and 95,342. Twelve studies were cohort and five studies were conducted in the cross-sectional design. The duration of follow up ranged from 2 to 15.9 years. The NOS score of all studies were ≥ 8, indicating high quality of all included papers.

Table 1 Summary of included studies
Full size table

All-causes mortality

The meta-analysis of four studies that investigated the association between TyG-WC and the risk of all-cause mortality revealed a significant association between TyG-WC and all-cause mortality risk (RRs = 1.23; 95% CI: 1.13–1.35; p < 0.001). No significant heterogeneity was found between the studies (I² = 0.0%, p = 0.464) (Fig. 2).

Fig. 2
figure 2

Forest plot for the association of TyG-WC with all-causes and cardiovascular mortality

Full size image

Cardiovascular mortality

A meta-analysis of four studies to investigate the relationship between TyG-WC and cardiovascular mortality. The analysis revealed a significant positive association between TyG-WC and higher risk of cardiovascular mortality (RR = 1.55, 95% CI 1.33–1.80; p < 0.001) with an absence of significant heterogeneity (I² = 0.0%, p = 0.764) (Fig. 2).

CVD

A total of eight studies examining the association between TyG-WC and the risk of cardiovascular disease. The pooled random-effects model revealed a significant association between TyG-WC and cardiovascular disease risk (RR = 1.69; 95% CI: 1.20–2.39; p = 0.003) with substantial heterogeneity observed between studies (I² = 98.8%, p < 0.001) (Fig. 3).

Fig. 3
figure 3

Forest plot for the association of TyG-WC with cardiovascular disease

Full size image

MI

A total of four studies investigating the association between TyG-WC and the risk of MI. A random-effects model was used to pool the results due to observed heterogeneity (I² = 57.4%, p = 0.071). The pooled analysis demonstrated a significant association between TyG-WC and MI risk (RR = 2.73; 95% CI: 1.96–3.82; p < 0.001) (Fig. 4).

Fig. 4
figure 4

Forest plots for the association of TyG-WC with subtypes of cardiovascular disease

Full size image

CAD

A meta-analysis of four studies was performed to evaluate the association between TyG-WC and the risk of CAD. The pooled analysis showed a significant association between TyG-WC and CAD risk (RR = 1.65; 95% CI: 1.04, 2.60; p = 0.033). Substantial heterogeneity was observed among the studies (I² = 83.1%, p < 0.000) (Fig. 4).

Stroke

A total of four studies included in the analysis of the association between TyG-WC and the risk of stroke. The pooled analysis revealed a significant association between TyG-WC and stroke risk (RR = 1.99; 95% CI: 1.71, 2.31; p < 0.001). There was no significant heterogeneity among the studies (I² = 18.7%, p = 0.297) (Fig. 4).

HF

Only one study by Dang et al. was included in the analysis. Due to the inclusion of a single study, which reported a significant association between TyG-WC and HF risk (RR = 2.14; 95% CI: 1.31, 3.51; p = 0.002) (Fig. 4).

PAD

Pooled analysis of two studies demonstrated a significant association between TyG-WC and PAD risk (RR = 2.51; 95% CI: 1.01, 6.27; p = 0.049) with no significant heterogeneity (I² = 11.2%, p = 0.288) (Fig. 4).

Subgroup analysis

We performed a subgroup analysis categorized by study design: prospective cohorts, retrospective cohorts, and cross-sectional studies The association between TyG-WC and all-cause mortality, cardiovascular mortality, PAD, HF, stroke, and MI remained significant across the overall analysis. For cross-sectional studies, the result regarding CVD was not significant (RR = 1.53; 95% CI: 0.82, 2.87). A single retrospective study did not demonstrate a significant relationship for the association with CVD (RR = 1.08; 95% CI: 0.97, 1.20) and CAD (RR = 1.08; 95% CI: 0.96, 1.22). In studies using a prospective cohort design, the association between TyG-WC and all outcomes was consistently significant.

Publication bias and sensitivity analysis

Visual funnel plots were used to assess potential publication bias across the studies. While these plots suggested no significant bias for most outcomes, a potential asymmetry was observed for CVD (Fig. 5). However, Egger’s test (P = 0.088) and Begg’s test (P = 0.902) did not confirm this visual indication of bias. We performed sensitivity analysis for the CVD, all-causes mortality, and CVD-mortality, CAD, MI, and stroke, which found that alterations in odds ratios had no significant influence on the overall conclusions.

Fig. 5
figure 5

Funnel plots for the outcomes, (A) All-causes mortality, (B) Cardiovascular mortality, (C) Cardiovascular disease, (D) Myocardial infarction, (E) Peripheral artery disease, (F) Stroke

Full size image

Discussion

The TyG-WC index, which integrates TG, FBS, and WC, can be a promising forecasting tool for cardiovascular diseases and mortality. This meta-analysis demonstrated that elevated levels of TyG-WC are significantly associated with increased overall mortality, cardiovascular mortality, and various cardiovascular conditions, including MI, CAD, stroke, and PAD. Notably, our systematic search identified only one study on the relation between TyG-WC and HF, which suggested a positive and significant correlation.

Since the elements of this marker—TG, FBS, and waist circumference—are easy to measure and cost-effective in a hospital setting, TyG-WC could be a useful screening tool that wouldn’t significantly raise costs for patients or the overall healthcare system. To the best of our knowledge, this is the first meta-analysis evaluating the relationship between TYG-WC and cardiovascular diseases and mortality.

The impact of TyG-WC on cardiovascular diseases can be anticipated considering its two components (TyG and WC), as TyG and WC are related to cardiovascular diseases. Prior research has demonstrated that TyG is a marker with considerable sensitivity and specificity in identifying vascular diseases and metabolic disorders, and it can significantly predict insulin resistance (IR). IR is a key factor in metabolic abnormalities, systemic inflammation, endothelial dysfunction, and atherosclerosis [21,22,23]. Furthermore, TyG has been linked to hypertension, a condition that contributes to various cardiovascular diseases, including coronary artery disease, heart failure, and increased overall mortality [24, 25]. Obesity, particularly abdominal obesity indicative of visceral fat, can affect atherosclerotic processes and, together with TyG, may predict hypertension and insulin resistance [24, 26, 27]. Also, a study evaluating the codependence of TyG and obesity’s role in cardiovascular diseases suggested that TyG was significantly related to cardiovascular diseases in obese patients, in contrast this correlation was insignificant for nonobese adults [28]. This highlights the importance of considering obesity-related modalities while interpreting TyG.

Several studies have evaluated the predictive value of the TyG index when combined with obesity measurements like BMI, WtHR, and WC [29, 30]. Among these combinations, TyG-WC and TyG-WtHR are recommended as more effective tools for identifying individuals at risk for cardiovascular disease [29]. Research involving 1,145 asymptomatic participants suggested that TyG-WC is a stronger and more reliable predictor of coronary artery calcification—a marker associated with cardiovascular diseases—comparing the the HOMA-IR, TyG index, and TyG-BMI [30]. Given that TyG-WC emphasizes visceral adiposity compared to TyG-BMI, which focuses on overall obesity, it may serve as a superior predictor of metabolic and cardiovascular diseases. Additionally, previous investigations have suggested that TyG-WC correlates more strongly with cardiovascular mortality in men than in women, while it is more associated with cardiovascular diseases in women comparing men [29]. However, because of limited gender-specific studies, we couldn’t perform subgroup meta-analyses based on gender. And the need for further research on this cofounding modality should be considered.

The results regarding the effect of obesity and TYG body weight indices were always a matter of contradiction. Some studies suggested that there is an obesity paradox in terms of the severity and mortality of cardiovascular diseases [31, 32]. The increased glucose availability because of elevated endogenous glucose production and macrophage availability in high glucose status can bring pathophysiological background for lower cardiovascular mortality in obese patients [33, 34]. However, some studies suggest that some biases like higher socioeconomic status in obese patients and comorbidities that lead to medication intake protecting regarding cardiovascular death like statin can participate in this paradox [35,36,37]. Also, a meta-analysis on the effect of TyG on cardiovascular mortality suggested no significant association between these two factors [38]. However, our study draws a line on these contradictory findings by determining a significant higher cardiovascular mortality by elevated TyG-WC after systematic and meta-analysis evaluating these factors. Hence, this marker can be used instead of obesity indices for predicting cardiovascular outcome.

This study acknowledges several limitations. Firstly, the number of studies eligible for inclusion in this meta-analysis was limited. Consequently, we were not able to conduct meta-analyses on some of the cardiovascular diseases like HF considering only one study examining the impact of TyG-WC on HF. Therefore, further research exploring this relationship is necessary. Additionally, considering obesity and its various markers present distinct effects on genders, conducting subgroup analyses based on gender would be advantageous. However, the limited number of gender-specific studies prevented us from undertaking such analyses, highlighting the need for further investigations. Thirdly, the inclusion of various study designs (prospective, retrospective, and cross-sectional) may contribute to variability in our results. While subgroup analyses revealed significant findings primarily in prospective cohorts, the lack of significance for certain outcomes in the other study designs may limit the broader applicability of our conclusions. Finally, our meta-analysis did not account for various lifestyle factors, such as smoking, dietary habits, physical activity levels, age, and socioeconomic status, which can significantly influence both TyG-WC and cardiovascular outcomes.

The strength of this study primarily lies in the comprehensiveness of its findings. While previous research has addressed the relationship between TyG-WC and cardiovascular diseases, there has been a lack of systematic evaluations in this regard. By including a range of cardiovascular conditions, such as MI, PAD, CAD and stroke, this study offers insights more specific than a general assessment of cardiovascular health. Future research should focus on determining precise cut-off values for the TyG-WC index. Defining specific thresholds would improve risk stratification in clinical practice, allowing healthcare providers to identify individuals at higher risk for adverse cardiovascular outcomes more effectively. Additionally, follow-up studies should aim to evaluate the predictive value of TyG-WC in patients with various comorbidities. Understanding how TyG-WC correlates with cardiovascular risk in individuals with conditions such as diabetes, hypertension, or metabolic syndrome could provide critical insights into its clinical utility.

In conclusion, this study emphasizes the significant role of TyG-WC in cardiovascular and overall mortality, as well as its association with various cardiovascular diseases, including MI, stroke, PAD, and CAD. Additionally, it identifies a current knowledge gap regarding the relationship between TyG-WC and HF, as well as the need for gender-specific studies.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

CAD:

Coronary artery diseases

CVD:

Cardiovascular diseases

MI:

Myocardial infarction

PAD:

Peripheral artery disease

WC:

Waist circumference

TyG-WC:

Triglyceride-glucose-waist circumference

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Authors and Affiliations

  1. Isfahan Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran

    Mehrdad Rabiee Rad & Ghazal Ghasempour Dabaghi

  2. Student Research Committee, Kashan University of Medical Sciences, Kashan, Iran

    Hossein Sadri

  3. Heart Failure Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran

    Bahar Darouei & Reza Amani-Beni

  4. Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-Communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran

    Sadegh Mazaheri-Tehrani

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Contributions

M.R.R and G.G.D designed the research. S.M.T; H.S.; R.A.B; and B.D collected data in electronic database. M.R.R and G.G.D performed statistical analysis. All authors contributed to drafting of the manuscript, had full access to all the data in the study, approved the final version of the manuscript and had final decision to submit for publication. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Ghazal Ghasempour Dabaghi.

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Author contributions

MRR and GGD designed the research. S.M.T; H.S.; R.A.B; and BD collected data in electronic database. MRR and GGD performed statistical analysis. All authors contributed to drafting of the manuscript, had full access to all the data in the study, approved the final version of the manuscript and had final decision to submit for publication. All authors read and approved the final manuscript.

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Rabiee Rad, M., Ghasempour Dabaghi, G., Sadri, H. et al. Triglyceride glucose-waist circumference as a predictor of mortality and subtypes of cardiovascular disease: a systematic review and meta-analysis. Diabetol Metab Syndr 17, 59 (2025). https://doi.org/10.1186/s13098-025-01616-9

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  • DOI: https://doi.org/10.1186/s13098-025-01616-9

Keywords

Diabetology & Metabolic Syndrome

ISSN: 1758-5996

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