The Triglyceride-Glucose Index and Risk of End-Stage Renal Disease across Different Durations of Type 2 Diabetes Mellitus: A Longitudinal Cohort Study
Article information
Abstract
Background
This study investigated the association between the triglyceride-glucose (TyG) index, a marker of insulin resistance, and the risk of end-stage renal disease (ESRD) in individuals with type 2 diabetes mellitus (T2DM), focusing on variations by diabetes duration.
Methods
We analyzed 1,219,148 Korean adults with T2DM from National Health Insurance Service data who underwent biennial health evaluations (2015 to 2016). ESRD was defined using specific procedural codes (V codes), and Cox proportional hazard models were employed to estimate hazard ratios (HRs) for ESRD across TyG index quartiles and diabetes duration categories, adjusting for various confounders.
Results
Over 6,967,381 person-years of follow-up, 7,548 participants developed ESRD. Higher TyG index quartiles were independently associated with increased risk of ESRD, which was more pronounced with longer diabetes duration. The adjusted HR for ESRD in the highest TyG quartile (Q4) compared to the lowest quartile (Q1) was 1.235 (95% confidence interval [CI], 0.995 to 1.533) in new-onset diabetes, and 1.592 (95% CI, 1.465 to 1.730) in those with diabetes for ≥10 years. Compared to the lowest TyG quartile in new-onset diabetes, the adjusted HR for ESRD in the highest quartile with diabetes duration ≥10 years increased to 10.239 (95% CI, 8.440 to 12.422). Subgroup analysis revealed that a higher TyG index consistently increased the risk of ESRD, with stronger associations observed in younger individuals and those without comorbidities.
Conclusion
The TyG index is a significant predictor of ESRD in T2DM, particularly in those with prolonged diabetes duration. Targeting insulin resistance early may mitigate the risk of ESRD in this population.
INTRODUCTION
Type 2 diabetes mellitus (T2DM) poses a significant global public health challenge with a prevalence of 10.5%, affecting approximately 536.6 million people worldwide [1]. The rise in early-onset T2DM further extends disease duration and amplifies its complications [2]. Diabetic kidney disease, the leading cause of chronic kidney disease (CKD) and end-stage renal disease (ESRD), now accounts for 31.3% of ESRD cases globally [3,4]. Despite advances in treatment, the burden of ESRD continues to increase.
Insulin resistance (IR) is a critical feature of T2DM that not only impairs glucose regulation but also contributes to the progression of metabolic complications such as metabolic dysfunction- associated steatotic liver disease, cardiovascular disease, and CKD [5-7]. In the kidney, IR impairs insulin signaling, damages renal tubular cells and podocytes, and compromises vascular function [7,8]. These pathologic processes induce chronic tubulointerstitial inflammation, leading to CKD and eventually ESRD [7,8]. Thus, IR is a critical factor in the development of ESRD in patients with diabetes, and clinical scores assessing IR can help in predicting ESRD and identifying high-risk groups for developing ESRD. However, homeostasis model assessment- estimated insulin resistance (HOMA-IR), a widely used IR marker, is costly and often inaccessible due to its reliance on direct insulin measurements. In contrast, the triglyceride-glucose (TyG) index, calculated using fasting blood glucose and triglyceride levels, offers a more practical alternative for assessing IR [9,10]. Recent studies have validated the TyG index to be a reliable marker of IR and have demonstrated its association with cardiovascular and metabolic diseases, but the utility of TyG in predicting ESRD risk in patients with diabetes remains underexplored [11-15].
This study aims to investigate the association between the TyG index and the risk of developing ESRD in patients with T2DM using a large Korean population database. Recognizing that the risk of ESRD increases with the duration of diabetes, we also examine diabetes duration as a potential modifier of the relationship between the TyG index and ESRD risk. These findings may help identify individuals who could benefit from early interventions for metabolic disease and kidney protection strategies.
METHODS
Study population
This study used data from the National Health Insurance Service (NHIS) database, which covers approximately 50 million Koreans and manages the country’s National Health Insurance program. The NHIS database provides comprehensive demographic data, medical utilization records, insurance claims, and payment information for over 95% of the Korean population. Detailed descriptions of the NHIS database have been provided in previous studies [16].
We analyzed data from 2,616,505 Korean residents aged 20 years or older with T2DM who underwent a biennial medical evaluation between 2015 and 2016. Exclusions were applied for individuals taking lipid-lowering agents (n=1,334,205), those with a history of ESRD before the health examination (n=5,260), those with missing data (n=45,464), and those diagnosed with ESRD or who died within 1 year of the index year (n=12,428). A total of 1,219,148 participants (822,304 men and 396,844 women) were included in the final analysis (Supplemental Fig. S1). The mean follow-up period was 5.71±1.04 years (6,967,381 person-years).
The health examinations conducted in 2015 and 2016 included measurements of height, weight, and blood pressure and laboratory tests such as fasting glucose and cholesterol, serum creatinine, liver enzymes, and urinalysis. Data on medical history, and health-modifying behaviors, including smoking, alcohol consumption, and physical activity, were collected using standardized self-reporting questionnaires. Laboratory tests were performed in accordance with the Korean Association of Laboratory Quality Control’s guidelines. This study was exempted from review by the Institutional Review Board of Seoul St. Mary’s Hospital (IRB No. KC24ZASI0515). Informed consent was waived by the board. All data were deidentified and anonymized to ensure participant confidentiality.
Definition of T2DM and ESRD
T2DM was defined by a fasting plasma glucose (FPG) level ≥ 126 mg/dL or at least one annual claim for hypoglycemic medication under International Classification of Diseases, 10th Revision (ICD-10) codes E11–14 [17,18]. Patients with type 1 diabetes mellitus (ICD-10 code E10) were excluded [18]. Newly diagnosed diabetes was defined as cases identified during the 2015–2016 health examination. Diabetes duration was categorized into four groups: new-onset, <5, 5–9, and ≥10 years. For example, the <5 years group included patients diagnosed with T2DM between 2011 and 2014.
Hypertension was defined as a blood pressure ≥140/90 mm Hg or at least one annual claim for antihypertensive medication under ICD-10 codes I10–I15 [17]. CKD was defined by an estimated glomerular filtration rate of <60 mL/min/1.73 m2 [18]. TyG index was calculated as Ln[fasting triglycerides (mg/dL)×fasting glucose (mg/dL)/2] [9]. Participants were categorized into quartiles based on their TyG index (range, 3.75 to 12.94).
The primary endpoint of the study was the incidence of newly diagnosed ESRD, defined by specific procedural codes (V codes) for peritoneal dialysis (V003), hemodialysis (V001), or kidney transplantation (V005) [18,19]. A diagnosis of ESRD was considered new if the patient had no prior ESRD diagnosis in the database starting from 2015 to 2016. A washout period of over 1 year was used to ensure that the diagnosis of newly developed ESRD. Study participants were followed from baseline until the diagnosis of ESRD.
General health behaviors and sociodemographic variables
As part of the health examinations, body weight (kg), height (cm), waist circumference (cm), and blood pressure (mm Hg) were measured. Body mass index (BMI) was calculated as weight divided by height squared (kg/m2). Blood samples were collected after overnight fasting. Smoking status was categorized as non-smokers, former smokers, and current smokers. Alcohol consumption was classified as none, mild (≤30 g/day), or heavy (≥30 g/day). Regular exercise was defined as engaging in more than 20 minutes of vigorous physical activity or more than 30 minutes of moderate physical activity at least three times per week. Individuals eligible for medical aid or those within the lowest 20% of income distribution were classified as low-income.
Statistical analysis
Categorical variables were expressed as numbers (percentages) and analyzed using the chi-square test. Continuous variables were expressed as mean±standard deviation or as geometric mean (95% confidence interval [CI]) for non-normal distributions and analyzed using one-way analysis of variance (ANOVA). The incidence rate of ESRD was calculated by dividing the number of events by 1,000 person-years. Hazard ratio (HR) and 95% CI for ESRD across TyG index quartiles and diabetes duration categories were obtained using multivariable Cox proportional hazard models, with the lowest quartile of TyG index in each group as the reference. Adjustments were made for age, sex, BMI, smoking, alcohol consumption, physical activity, income, hypertension, CKD, use of anti-diabetic medications (including insulin), and total cholesterol level. Subgroup analyses were performed using multivariable Cox models, stratified by factors such as age (≥50 years), sex, obesity, smoking, alcohol consumption, and comorbidities like hypertension and CKD, with adjustments for all covariates. All statistical analyses were performed using SAS version 9.4 software (SAS Institute, Cary, NC, USA). A two-tailed P<0.05 was considered statistically significant.
RESULTS
Baseline characteristics of study population
The study cohort included 1,219,148 adult Korean individuals with T2DM, consisting of 822,304 men (67.5%) and 396,844 women (32.6%), none of whom had a prior diagnosis of ESRD. Mean age at baseline was 57.2±12.8 years. During the mean follow-up period of 5.71±1.04 years, 7,548 patients (0.6%) developed ESRD. Table 1 presents the baseline characteristics of participants stratified by TyG index quartiles. Significant differences were observed across TyG quartiles. Participants in the highest TyG quartile (Q4) were generally younger, male, obese, and with a relatively shorter duration of diabetes, higher blood pressure, a worse lipid profile, and unhealthy lifestyle behaviors, including greater smoking and alcohol consumption and decreased regular exercise. Conversely, the prevalence of comorbid conditions such as hypertension and CKD was lower in participants in the highest TyG quartile.
Baseline Characteristics of the Study Population
Risk of incident ESRD according to TyG index and diabetes duration
The incidence rate of ESRD varied across TyG index quartiles and different categories of diabetes duration, as shown in Fig. 1. Overall, higher TyG quartiles and longer duration of diabetes were associated with an increased risk of incident ESRD. The increase in ESRD incidence across higher TyG quartiles was particularly pronounced in individuals with longer duration of diabetes. For example, among individuals with diabetes duration of 10 years or more, incidence rate of ESRD increased from 2.72 cases per 1,000 person-years in the lowest TyG quartile (Q1) to 5.65 cases per 1,000 person-years in the highest TyG quartile (Q4) (Table 2, Fig. 1). In contrast, for those with new-onset diabetes, the incidence rate increased from 0.20 cases per 1,000 person-years in Q1 to 0.30 cases per 1,000 person-years in Q4.
Incidence rate of end-stage renal disease for each category of diabetes duration according to triglyceride-glucose (TyG) quartiles. PY, person-year.
HRs of ESRD for Each Category of Diabetes Duration according to TyG Quartiles
In the Cox proportional hazard model, a similar trend was observed, with individuals in the highest TyG quartile (Q4) exhibiting a significantly higher risk of ESRD compared to those in the lowest quartile (Q1) (Table 2, Fig. 2A). After adjusting for various confounders, including age, sex, BMI, income, smoking status, alcohol consumption, physical activity, hypertension, CKD, and total cholesterol level, the association between TyG index and ESRD risk remained significant. For example, in the new-onset diabetes group, the adjusted HR for ESRD in Q4 compared to Q1 was 1.235 (95% CI, 0.995 to 1.533). This trend persisted across different diabetes duration categories, with the strongest associations observed in individuals with longer diabetes durations. In participants with a diabetes duration of 10 years or more, the adjusted HR for ESRD in Q4 compared to Q1 was 1.592 (95% CI, 1.465 to 1.730).
Adjusted hazard ratio (HR) of end-stage renal disease for each category of diabetes duration according to triglyceride-glucose (TyG) quartiles. (A) Cox proportional hazard models, with the lowest quartile of TyG index in each group as the reference. (B) Cox proportional hazard models, with the lowest quartile of TyG index among individuals with new-onset diabetes as the reference. CI, confidence interval.
Further analyses using the lowest quartile of TyG index among individuals with new-onset diabetes as the reference reinforced these findings (Fig. 2B, Supplemental Table S1). In this comparison, the HR for ESRD in the highest TyG quartile among those with diabetes duration of 10 years or more increased to 28.805 (95% CI, 23.849 to 34.792). The adjusted HR for ESRD in the same group remained markedly elevated at 10.239 (95% CI, 8.440 to 12.422).
Subgroup analysis of risk of ESRD
Subgroup analyses were conducted based on age, sex, FPG, proteinuria, lifestyle factors, and comorbidities (Supplemental Tables S2-S10). Across all subgroups, a higher TyG index was consistently associated with an increased risk of incident ESRD. Notably, the adjusted HR for ESRD was highest in individuals younger than 50 years (adjusted HR, 68.224 for those with diabetes duration ≥10 years in the highest TyG quartile), compared to an HR of 6.516 for those aged 50 years or older (Supplemental Table S2), suggesting that younger individuals with prolonged diabetes may be particularly susceptible. The risk of ESRD in the highest TyG quartile was also greater in men (adjusted HR of 11.480) compared to women (adjusted HR of 8.095) (Supplemental Table S3).
In analyses stratified by fasting glucose levels (Supplemental Table S4), the association between TyG index and ESRD risk persisted across all glucose categories, reinforcing its predictive value regardless of baseline glycemic status. Additionally, subgroup analysis by proteinuria status revealed a stronger association in individuals without proteinuria (Supplemental Table S5), suggesting that the TyG index may serve as an early marker for ESRD risk before significant renal impairment develops. Moreover, the association between the TyG index and ESRD was more pronounced in individuals without comorbidities such as hypertension and CKD, highlighting the independent role of IR in ESRD progression. A stronger association was also observed in individuals with obesity compared to those without and in smokers compared to non-smokers. These findings were consistent across subgroups stratified by diabetes duration.
Taken together, these results support the robustness of the TyG index as a predictor of ESRD risk across diverse populations and clinical conditions, with potential implications for early identification of high-risk individuals.
DISCUSSION
The results of this study provide compelling evidence that a higher TyG index is associated with an increased risk of ESRD in individuals with diabetes, independent of diabetes duration. This association remains significant after adjusting for potential confounders including age, sex, lifestyle, and comorbidities, indicating that the TyG index may serve as an independent predictor of ESRD risk. These findings support the model that IR, as reflected by the TyG index, contributes to the progression of diabetic nephropathy. Given its feasibility and cost-effectiveness, we consider the TyG index to be a valuable tool for predicting kidney disease progression in patients with diabetes.
Our study demonstrates a synergistic effect between diabetes duration and a high TyG index, underscoring the compounded risk posed by these two factors. The interaction between prolonged diabetes duration and elevated TyG index as revealed by our analysis suggests that patients with long-standing diabetes and high IR are at an even greater risk of developing ESRD. This finding emphasizes the need for early detection and management of IR, particularly in patients with long-standing diabetes. Incorporating TyG index screening into routine clinical practice could help identify those who would benefit from early and aggressive kidney protection strategies, especially in patients with a diabetes duration of over 10 years, where the risk is notably higher.
Following the diagnosis of diabetes, beta cell function progressively declines, while IR persists or worsens over time [20]. Consequently, the predictive value of the TyG index may increase, even as the predictive utility of common risk factors for diabetic complications diminishes with prolonged diabetes duration. Additionally, previous studies have shown that chronic hyperglycemia and sustained IR, both closely associated with TyG index, significantly contribute to the progressive deterioration of renal function over time [7,8]. These cumulative effects further establish the TyG index as a robust predictor of ESRD risk, particularly as the duration of diabetes increases.
Subgroup analyses revealed a more pronounced synergistic effect between diabetes duration and a higher TyG index in individuals without traditional risk factors for ESRD, such as advanced age, hypertension, and pre-existing CKD [20,21]. This suggests that, in these populations, the combination of prolonged diabetes and a high TyG index may accelerate progression to ESRD. Notably, the interaction between diabetes duration and a high TyG index was more significant in younger patients, indicating that younger individuals and an elevated TyG index may face a worse prognosis and a greater lifetime risk of diabetes nephropathy, among other diabetes-related complications. This finding underscores the importance of early intervention in this group. Further studies are warranted to explore this potential risk and to determine targeted prevention strategies for young patients with diabetes who exhibit high IR.
We consider the TyG index as a more practical and cost-effective tool for assessing IR over the HOMA-IR index. It relies on simple lab parameters such as fasting glucose and triglycerides, without requiring insulin measurements, and its index provides a reliable assessment of IR in a broader population. The significant association between high TyG index and increased ESRD risk persisted after adjusting for factors such as income, smoking, drinking, physical activity, hypertension, CKD, and diabetes medication status. These findings suggest that the TyG index captures an independent aspect of metabolic risk not fully covered by traditional factors. Furthermore, our findings demonstrate the feasibility of integrating the TyG index into risk stratification tools for patients with diabetes, which would enable personalized treatment plans that prioritize kidney health. Public health initiatives should broadcast the importance of monitoring IR and its impact on long-term kidney outcomes, especially in younger populations with diabetes. While this study is associative, there is compelling scientific evidence that the cellular mechanisms underlying this association likely involve IR promoting glomerular hyperfiltration, inflammation, and fibrosis—key pathological processes that accelerate CKD progression to ESRD [7,8]. Furthermore, the TyG index is associated with other metabolic abnormalities, such as dyslipidemia and hyperglycemia, which may further exacerbate kidney damage.
Our findings corroborate previous studies that have demonstrated an increased risk of incident CKD or ESRD in individuals with or without diabetes [15,22-26]. However, our study significantly expands upon prior research by demonstrating the predictive value of the TyG index specifically for ESRD progression in a nationwide population, with a large sample size (>1 million) and extended follow-up (>5 years). Unlike previous studies, which primarily examined CKD rather than ESRD, our analysis provides stronger epidemiological evidence that IR, measured by TyG index, is an independent risk factor for ESRD beyond traditional risk markers.
Furthermore, by conducting extensive subgroup analyses across different metabolic conditions and diabetes durations, we clarify how the TyG index can stratify risk in various clinical scenarios, making it a more actionable marker in clinical practice. Only one prior study investigated the TyG–ESRD relationship in patients with preexisting CKD (n=1,936) with a follow-up of only 41 months [24]; our study greatly surpasses this in in both scope and duration, providing more robust evidence for the clinical utility of the TyG index.
The strengths of this study are its large sample size (>1 million participants), long follow-up (>5 years), and comprehensive adjustment for confounding factors. Our findings demonstrate a robust association between high TyG scores and ESRD risk, with consistent results across different durations of diabetes and in subgroup analyses. The main limitation of this study is its observational nature, which precludes establishment of causality. Reliance on a single measurement of the TyG index may also not fully capture the dynamic nature of IR over time. The lack of glycosylated hemoglobin data limits our ability to assess glycemic control during the follow-up period. Our analysis was conducted in Korean population, which limits the generalizability of our findings to other ethnic groups. Nonetheless, given that the TyG index reflects IR across ethnicities [9,10], similar results might be expected in other populations. Additionally, our analysis focused on individuals with T2DM, who generally exhibit elevated glucose and triglyceride levels. To minimize the effects of medications such as glucose- and lipid-lowering agents, we excluded participants who had already been treated with lipid-lowering agents and adjusted for the use of anti-diabetic medications in our risk assessment. Lastly, we acknowledge that excluding patients on lipid-lowering therapy may have led to an underestimation of the predictive power of TyG index. While this exclusion reduces confounding effects from medications that directly impact lipid levels, it also potentially removes a high-risk subgroup commonly managed with these therapies. Given that many patients with T2DM receive lipid-lowering agents in real-world clinical settings, the observed associations in our study may not fully capture the predictive strength of the TyG index in broader clinical practice. Future studies that include these patients will be essential to validate and refine our findings.
The TyG index emerges as a valuable marker for identifying individuals at higher risk of ESRD, particularly among those with long-standing diabetes or early-onset diabetes. These findings emphasize the need for further research to evaluate the potential role of the TyG index in guiding preventive strategies and interventions to reduce the burden of ESRD. Future studies should investigate whether improving IR and modifying lifestyle habits can improve the TyG index and, consequently, reduce the risk of ESRD and other complications. Additionally, longitudinal studies are needed to assess the impact of early interventions targeting the TyG index on long-term kidney outcomes and to explore the relationship between the TyG index and other diabetes-related complications, with a particular focus on younger patients with prolonged diabetes duration.
Supplementary Material
Supplemental Table S1.
HRs of ESRD for Each Category of Diabetes Duration according to TyG Quartiles
Supplemental Table S2.
Subgroup Analysis by Age of 50 Years
Supplemental Table S3.
Subgroup Analysis by Sex
Supplemental Table S4.
Subgroup Analysis by Fasting Plasma Glucose
Supplemental Table S5.
Subgroup Analysis by Proteinuria
Supplemental Table S6.
Subgroup Analysis by Hypertension
Supplemental Table S7.
Subgroup Analysis by CKD
Supplemental Table S8.
Subgroup Analysis by Obesity
Supplemental Table S9.
Subgroup Analysis by Smoking
Supplemental Table S10.
Subgroup Analysis by Alcohol Consumption
Supplemental Fig. S1.
Schematic diagram of study population. NHIS, National Health Insurance Service; ESRD, end-stage renal disease; TyG, triglyceride-glucose.
Notes
CONFLICTS OF INTEREST
No potential conflict of interest relevant to this article was reported.
ACKNOWLEDGMENTS
The authors thank the staff at the Big Data Steering Department at the NHIS for providing the data.
AUTHOR CONTRIBUTIONS
Conception or design: K.D.H., E.Y.L. Acquisition, analysis, or interpretation of data: K.N.L., J.L., J.K., K.D.H. Drafting the work or revising: M.K., S.H.L., H.S.K., J.H., E.Y.L. Final approval of the manuscript: M.K., K.N.L., J.L., J.K., S.H.L., H. S.K., J.H., K.D.H., E.Y.L.