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Associations of the triglyceride–glucose index and triglyceride–glucose/body mass index with all-cause mortality in Chinese centenarians

BMC Geriatrics volume 25, Article number: 266 (2025) Cite this article

Abstract

Background

The triglyceride–glucose (TyG) index and triglyceride–glucose/body mass index (TyG–BMI) have been shown to be associated with cardiovascular and cerebrovascular disorders and the risk of death. The aim of this study was to explore the relationships of the TyG index and TyG–BMI with all-cause mortality among Chinese centenarians.

Methods

Data from the China Hainan Centenarian Cohort Study (CHCCS) were analyzed. Eligible centenarians were divided into quartiles on the basis of their TyG and TyG–BMI indices. Kaplan‒Meier analysis was used to compare survival times across groups. The associations of the TyG index and TyG–BMI with all-cause mortality were investigated using restricted cubic splines (RCSs) and Cox proportional hazards regression models. Moreover, the concordance of the associations of the TyG index and TyG–BMI with all-cause mortality in different subgroups was further explored by subgroup analysis.

Results

A total of 921 centenarian participants were included in this study. During a median follow-up of 29.70 months, 852 (92.5%) centenarians died. The results of the RCS analysis demonstrated that the TyG index and TyG–BMI were both linearly and negatively associated with all-cause mortality. Compared with that for the highest the TyG index and TyG–BMI quartile groups, higher risks of death were found for the lowest quartile groups (TyG Q1 vs. Q4, HR 1.27, 95% CI 1.03–1.56, P = 0.024; TyG–BMI Q1 vs. Q4, HR 1.60, 95% CI 1.30–1.96, P < 0.001). Centenarians with lower TyG index and TyG–BMI values had significantly greater mortality risks according to the Kaplan‒Meier analysis (log-rank P = 0.020, log-rank P < 0.001, respectively). Subgroup analysis demonstrated that blood pressure could influence the linear negative correlation between the TyG–BMI and all-cause mortality.

Conclusion

Both lower TyG and TyG–BMI indices were significantly associated with higher all-cause mortality in Chinese centenarians, whereas the TyG–BMI was superior to the TyG index in predicting the mortality risk of centenarians.

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Introduction

Insulin resistance (IR) refers to a pathological condition in which cells respond inadequately to insulin, resulting in impaired glucose uptake and utilization. As a pathogenic factor of a series of metabolic disorders, IR plays a key role in the pathogenesis and development of metabolic syndrome, diabetes and a variety of cardiovascular and cerebrovascular diseases [1, 2]. The hyperinsulinemic–euglycemic clamp is still the gold standard for evaluating human insulin resistance, despite its complexity and high cost, which limits its wide application [3]. However, the accuracy of homeostasis model assessment of insulin resistance (HOMA-IR) is decreased in patients receiving exogenous insulin therapy and those with β-cell dysfunction. Consequently, the triglyceride–glucose (TyG) index, a simple and reliable surrogate indicator of insulin resistance, has been shown to be independently associated with atherosclerotic cardiovascular and cerebrovascular diseases as well as the risk of death. A prospective cohort study of older Chinese adults demonstrated that the TyG index was positively correlated with senile stroke risk and mediated the association between BMI and stroke risk [4]. Liang et al. reported that a higher TyG index was associated with an increased risk of cardiovascular disease (CVD) in American adults aged ≥ 60 years [5]. Some studies have reported that the TyG index combined with the obesity index is more efficient in identifying IR than the TyG index alone [6]. BMI is a simple and practical index closely related to total body fat and can reflect overweight and obesity status. The TyG–BMI combines lipid, glucose and obesity parameters to comprehensively detect and measure obesity and metabolic abnormalities in individuals. Previous studies have shown that the TyG–BMI is significantly associated with the incidence and mortality of nonalcoholic fatty liver disease, hypertension and heart disease [7,8,9,10].

Insulin sensitivity usually decreases gradually with age. Nonetheless, there is growing evidence that insulin sensitivity can be preserved in centenarians [11]. Paolisso et al. reported that glucose tolerance and insulin sensitivity were better preserved in healthy centenarians than in non-centenarians, suggesting that low insulin resistance and preserved β-cell function could contribute to longevity in humans [12]. The prevalence of metabolic syndrome is very low in centenarians worldwide [11, 13]. In a multicenter study of centenarians in Italy, less than 5% of 602 centenarians had type 2 diabetes [14]. Centenarians are breaking through the limit of the human lifespan and have become the best model of healthy aging. However, studies on the relationships of the TyG index and TyG–BMI with longevity in centenarians are still lacking. Therefore, this study was the first to examine the associations of the TyG index and TyG–BMI with all-cause mortality in centenarians in Hainan Province, China.

Patients and methods

Study subjects

All participants were from the China Hainan Centenarian Cohort Study (CHCCS), which was conducted in Hainan Province from July 2014 to December 2016. In brief, on the basis of the lists provided by local public security and civil affairs departments, our team surveyed 1002 centenarians aged 100 years or older. All the subjects signed informed consent forms, and basic information collection and blood sample analysis were performed. The exclusion criterion was missing data on triglyceride, glucose, height, or weight. Finally, 921 centenarians were included in this study (Fig. 1). This study was conducted in accordance with the World Medical Association Declaration of Helsinki and its subsequent revisions and was approved by the Ethics Committee of the Hainan Hospital of the Chinese PLA General Hospital (No. 301HNLL-2016-01).

Fig. 1
figure 1

Flow chart of subject selection

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Demographic, clinical and laboratory measures

The family interviews were conducted by professional staff to obtain sociodemographic and health-related behavioral data. Baseline information included age, education, marital status, height, weight, waist circumference, smoking status and alcohol consumption. Hypertension, diabetes and CVD were defined by self-reports or the use of related medications, as well as systolic blood pressure ≥ 140 mm Hg and/or diastolic blood pressure ≥ 90 mmHg or abnormal blood glucose (fasting blood glucose (FBG) ≥ 7 mmol/L or postprandial blood glucose (PBG) ≥ 11.1 mmol/L or random blood glucose (RBG) ≥ 11.1 mmol/L).

Peripheral venous blood samples from centenarians were collected by professional nurses using disposable vacuum negative pressure blood collectors and transported to the laboratory within 4 h at 4 °C. Blood samples were randomly collected. First, it was difficult to obtain fasting blood samples with a large sample size. Second, valuable clinical information can be obtained conveniently through random blood samples. A fully automatic biochemical autoanalyzer (COBAS c702; Roche Products, Ltd.) was used to measure the levels of total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and glucose (GLU).

TyG index and TyG–BMI were calculated according to the following formulas:

  1. (1)

    Body Mass Index (BMI) (kg/m2) = weight (kg)/height2 (m).

  2. (2)

    TyG index = ln[triglycerides(mg/dL) ∗ glucose (mg/dL)/2] [15].

  3. (3)

    TyG-BMI = TyG index ∗ BMI.

Follow-up

The follow-up of this study ended on March 31, 2023. The date and cause of death were checked by the National Cause of Death Registration and Reporting Information System of the Chinese Center for Disease Control and Prevention, verified by the local civil affairs department and telephone-surveyed by the family members of centenarians, ensuring the accuracy of the follow-up results.

Statistical analysis

Normally distributed data are presented as the means ± SDs. Independent-samples t tests or ANOVAs were used to analyze differences between groups. Asymmetrically distributed data are presented as the median and interquartile range M (QL, QU), and the Mann‒Whitney U test or Kruskal-Wallis test was used to analyze differences between groups. Categorical variables are presented as numbers with percentages (n (%)) and were compared with the χ2 test.

Centenarians were grouped according to the interquartile range of the TyG index and TyG–BMI levels, with quartile 4 as the reference group. Univariate and multivariate-adjusted Cox regression analyses were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of the TyG index and TyG–BMI for all-cause mortality. Adjusted confounders included age; sex; ethnicity; marital status; education; smoking and alcohol consumption status; history of hypertension, diabetes, and coronary heart disease (CHD); HDL-C, and LDL-C levels. The distribution of time to death is presented as a Kaplan‒Meier survival curve and was compared using the log-rank test. Restricted cubic spline (RCS) analysis was used to evaluate the associations of the TyG index and TyG–BMI with all-cause mortality, adjusted for multiple models as mentioned above. Finally, stratified analyses were performed to explore the consistency of the prognostic value of the TyG–BMI within different subgroups, employing likelihood ratio tests to probe for interactions. The final results of all data processing were analyzed via R language software (version 4.0.2). P < 0.05 was considered to indicate statistical significance.

Results

Baseline characteristics and follow-up

A total of 921 centenarians were included, with a median age of 102.0 (101.0, 104.0) years, and 751 (81.5%) were female. A total of 893 (88.2%) participants were Han Chinese, and 840 (91.2%) were illiterate. A total of 827 (89.8%) participants were nonsmokers, and 166 (18.0%) drank alcohol. A total of 680 (73.8%), 89 (9.7%) and 36 (3.9%) patients suffered from hypertension, diabetes and coronary heart disease, respectively. The median TyG index and TyG–BMI were 8.35 (7.99, 8.67) and 150.00 (132.00, 169.00), respectively. A higher TyG index was associated with female sex, lower alcohol consumption and HDL-C, and higher BMI, waist circumference, TC and LDL-C, whereas a higher TyG – index was associated with male sex, diabetes mellitus, lower HDL-C, and higher waist circumference, TC and LDL-C. During a median follow-up of 29.70 (14.50, 52.60) months, 852 (92.5%) of the centenarians died (Tables 1 and 2).

Table 1 The baseline characteristics of the study subjects according to TyG index quartiles
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Table 2 The baseline characteristics of the study subjects categorized by TyG-BMI index
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Associations of the TyG index and TyG–BMI with all-cause mortality

Specifically, the TyG index and TyG–BMI were significantly linearly associated with all-cause mortality in the unadjusted RCS model (P = 0.027, P-nonlinear = 0.896 and P < 0.001, P-nonlinear = 0.165, respectively; Fig. 2A and C) and in the multivariable adjusted RCS model (P = 0.049, P-nonlinear = 0.768 and P < 0.001, P-nonlinear = 0.114, respectively; Fig. 2B and D). Multivariate-adjusted analyses adjusted for age, sex, ethnicity, marital state, education, smoking status, alcohol status, diabetes mellitus, hypertension, coronary artery disease, HDL-C, LDL-C.

Fig. 2
figure 2

Restricted cubic splines (RCS) of all-cause mortality with TyG index and TyG-BMI. The solid red line indicated the hazard ratio, and the shaded areas represent the 95% CI. The horizontal coordinates indicated TyG index or TyG-BMI levels, the left vertical coordinates indicated the hazard ratios for all-cause mortality, and the right vertical coordinates indicated the percentages of centenarians with TyG index or TyG-BMI levels. Multivariate-adjusted analyses adjusted for age, sex, ethnicity, marital state, education, smoking status, alcohol status, diabetes mellitus, hypertension, coronary artery disease, HDL-C and LDL-C. The reference cut-off value of TyG index was the median of it, 8.35, and similarly, the reference cut-off value of TyG-BMI was 150. The relationships of TyG index and TyG-BMI with all-cause mortality were significantly linear in both unadjusted (A, C) and multivariable-adjusted (B, D) RCS models

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Cox proportional hazard analysis was further performed to analyze the relationships of the TyG index and TyG–BMI with all-cause mortality. The results demonstrated that when analyzed as continuous variables, both the TyG index and TyG–BMI were significantly associated with mortality in the unadjusted models (HR 0.82, 95% CI 0.71–0.93, P = 0.003) (HR 0.95, 95% CI 0.93–0.97, P < 0.001) and multivariate-adjusted models (HR 0.81, 95% CI 0.70–0.94, P = 0.007) (HR 0.94, 95% CI 0.92–0.97, P < 0.001) (Table 3), respectively.

Table 3 Univariate and multivariate Cox proportional hazards analyses of the associations of TyG index and TyG-BMI with all-cause mortality in centenarians
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When the TyG index and TyG–BMI were analyzed as nominal variables, centenarians in the lowest quartile of the TyG index and TyG–BMI levels presented significantly greater mortality than did subjects in the highest quartile in both unadjusted (HR 1.29, 95% CI 1.06–1.56, P = 0.010) (HR 1.51, 95% CI 1.25–1.83, P < 0.001) and multivariate adjusted models (HR 1.27, 95% CI 1.03–1.56, P = 0.024) (HR 1.60, 95% CI 1.30–1.96, P < 0.001) (Table 3), respectively.

Additionally, mortality was significantly higher in centenarians with a low TyG index [6.89–8.35) than in those with a high TyG index [8.35–10.60] in the unadjusted analysis (HR 1.17, 95% CI 1.03–1.34, P = 0.020) but not in the multivariate-adjusted analysis (P = 0.059) (Table 3). In contrast, mortality was significantly greater in centenarians with a low TyG–BMI [69.8–150.0] than in those with a high TyG–BMI [150.0-319.0] in both unadjusted (HR 1.26, 95% CI 1.10–1.44, P < 0.001) and multivariate-adjusted (HR 1.31, 95% CI 1.14–1.51, P < 0.001) analyses (Table 3).

The results from the Kaplan‒Meier survival curve based on the dichotomies of the TyG index and TyG–BMI showed that centenarians with a lower TyG index or lower TyG–BMI had a greater risk of death. The median survival time of centenarians in the low TyG group was significantly shorter than that in the high TyG group (29 months vs. 31 months, log rank P = 0.020) (Fig. 3A), whereas the median survival time of centenarians in the low TyG–BMI group was significantly shorter than that in the high TyG–BMI group (28 months vs. 36 months, log rank P < 0.001) (Fig. 3B).

Fig. 3
figure 3

Kaplan-Meier survival curves and log-rank tests for the association of all-cause mortality with TyG index and TyG-BMI. Kaplan-Meier survival curves revealed significant associations of higher TyG index and TyG-BMI levels with increased survival time. (A)The median survival time was significantly shorter in centenarians with the low group of TyG index than in those with the high group of TyG index. (29 months vs. 31 months, P < 0.020). (B)The median survival time was significantly shorter in centenarians with the low group of TyG-BMI than in those with the high group of TyG-BMI. (28 months vs. 36 months, P < 0.001)

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Subgroup analysis

Moreover, we conducted a stratification analysis of TyG index and TyG-BMI with all-cause mortality in multiple subgroups after adjusting confounders included age, sex, ethnicity, marital status, education, smoking and alcohol status, history of hypertension, diabetes, and CHD, HDL-C, LDL-C (Fig. 4). TyG index displayed a significant association with a decreased risk of death in subgroups defined by female (HR 0.79, 95% CI 0.67–0.94), 102 ≤ age ≤ 116 years (HR 0.77, 95% CI 0.64–0.93), never smoking (HR 0.81, 95% CI 0.69–0.95), never drinking (HR 0.84, 95% CI 0.71–0.99), absence of diabetes (HR 0.82, 95% CI 0.70–0.96), presence of hypertension (HR 0.76, 95% CI 0.63–0.92) and absence of CHD (HR 0.81, 95% CI 0.70–0.95) (all P < 0.05). Additionally, no significant interactions were observed in all strata (Fig. 4A).

Fig. 4
figure 4

Subgroup analysis for the associations between the TyG index and TyG-BMI with the risk of all-cause death. Multivariate-adjusted analyses adjusted for age, sex, ethnicity, marital state, education, smoking status, alcohol status, diabetes mellitus (DM), hypertension, coronary artery disease (CHD), HDL-C and LDL-C. (A) Subgroup analysis for the association between the TyG index and the risk of all-cause death. (B) Subgroup analysis for the association between the TyG-BMI and the risk of all-cause death

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As for TyG-BMI, a significant association was found with a decreased risk of death in subgroups defined by female (HR 0.93, 95% CI 0.91–0.96), 102 ≤ age ≤ 116 years (HR 0.93, 95% CI 0.90–0.96), never smoking (HR 0.94, 95% CI 0.92–0.97), never drinking (HR 0.94, 95% CI 0.92–0.97), drinking in the past or quit (HR 0.89, 95% CI 0.80–0.98), absence of diabetes (HR 0.95, 95% CI 0.92–0.97), presence of diabetes (HR 0.89, 95% CI 0.81–0.98), presence of hypertension (HR 0.93, 95% CI 0.90–0.96), and absence of CHD (HR 0.94, 95% CI 0.92–0.97) (all P < 0.05). Additionally, interaction tests revealed a significant difference only in hypertension (P for interaction = 0.043), suggesting that the linear negative correlation between TyG-BMI and all-cause mortality could be influenced by blood pressure (Fig. 4B).

Discussion

The main findings of this large, prospective cohort study on centenarians were as follows: (1) Centenarians generally demonstrated low insulin resistance and a low TyG index, with a median of 8.35. (2) The TyG index and TyG–BMI were both negatively correlated with all-cause mortality in centenarians. (3) Centenarians in the lowest quartile of the TyG index and TyG–BMI had 1.27-fold and 1.60-fold increased risks for all-cause mortality, respectively, compared with those in the highest quartile. The TyG–BMI was superior to the TyG index in identifying the risk of death in centenarians. (4) Blood pressure could influence the linear negative correlation between the TyG–BMI and all-cause mortality. To the best of our knowledge, this is the first large-sample-size investigation to explore the associations of the TyG index and TyG–BMI with all-cause mortality in Chinese centenarians. The identification of these specific biomarkers for longevity could provide a foundation for identifying regulatory mechanisms against aging-related diseases.

Aging, oxidative stress and insulin resistance are closely related [16]. In animal experiments, blocking insulin/insulin-like growth factor-1 (IGF-1) signaling prolonged the lifespan of Caenorhabditis elegans by up to 10-fold [17]. A large-sample European study on healthy Caucasians verified that there was a significant decline in insulin with aging from the age of 50 to 75 years [18]. The Leiden Longevity Study also revealed a significant reduction in the incidence of type 2 diabetes among centenarians and their offspring [19]. These findings revealed an important causal relationship between aging and insulin. Preserved insulin sensitivity and a low prevalence of metabolic syndrome have been shown to be metabolic features of centenarians, and adipokine homeostasis could play a role in health and longevity [11, 19]. In the Tokyo Centenarian Study, only 6.0% of 304 centenarians living in the Tokyo metropolitan area had diabetes [20]. The TyG index and TyG–BMI have been widely used in clinical practice as reliable and simple surrogate indicators of insulin resistance. For the general population in China, insulin resistance is defined as a TyG index greater than 8.87 in men and 8.50 in women [21]. Similarly, our study revealed that the 75th percentile of the TyG index was 8.67, while the prevalence rates of diabetes and CHD were 9.7% and 3.9%, respectively. These findings suggest that most centenarians in our cohort had low insulin resistance and a low prevalence of metabolic syndrome, which is consistent with the findings of previous studies.

Previous studies have reported that an elevated TyG index and TyG–BMI are both positively associated with increased incidence rates of diabetes, stroke and all-cause mortality [22,23,24]. In contrast, our study revealed that both the TyG index and TyG–BMI were negatively associated with increased all-cause mortality in centenarians. To the best of our knowledge, this negative link could not be considered “the lower the better” and could be explained in the following aspects. First, the TyG index and TyG–BMI of our subjects lay in the low and narrow parts of the TyG index and TyG–BMI of the general population. Second, insulin resistance is believed to be a defense response to avoid hypoglycemia in centenarians. Third, moderate insulin levels could balance the metabolic homeostasis of carbohydrates, fat and protein in the body to better adapt to adverse environments [25, 26]. Additionally, high-normal blood glucose and lipid levels are beneficial for reducing the risk of death in centenarians. Many studies have shown that both high and low blood glucose are related to an increased risk of cardiovascular and cerebrovascular events and death and can damage the kidney, cardiovascular and nervous systems [27, 28]. This goes with lipids as well. Hyperlipidemia can lead to vascular atherosclerosis, whereas hypolipidemia is associated with increased capillary fragility, both of which can eventually cause cardiovascular and cerebrovascular diseases [29, 30].

Our results suggested that the TyG–BMI was superior to the TyG index for identifying the risk of death in centenarians. The TyG–BMI could be used to evaluate the risk of all-cause mortality in centenarians more comprehensively from the perspectives of blood glucose, lipids and BMI. An appropriately high BMI could play a protective role in centenarians despite its association with the presence of many chronic diseases. First, obesity may represent a greater physiological reserve in the context of exogenous stress [31]. A meta-analysis of 250,000 patients with CHD revealed that overweight/obese patients with CHD had lower all-cause mortality and CVD mortality than underweight and normal weight patients with CHD [32]. Second, “muscular obese” centenarians have more muscle mass, which can strengthen cardiopulmonary function and benefit metabolism [33]. Finally, adipokines and anti-inflammatory factors produced by adipose tissue, such as adiponectin and omentin, have been shown to have beneficial effects on the cardiovascular system [34, 35]. Consequently, the TyG–BMI is an easily available parameter to guide the elderly population to achieve successful aging and healthy longevity.

The interaction test in this study revealed that the linear negative correlation between the TyG–BMI and all-cause mortality could be influenced in centenarians with normal blood pressure. These findings suggested that the beneficial effect of normal blood pressure was stronger than the detrimental effects of hypoglycemia, hypolipidemia and low BMI. An animal experiment revealed that hypotension could augment the vasopressin (AVP) and adrenocorticotropic hormone (ACTH) responses to insulin-induced hypoglycemia in conscious dogs [36]. Marker et al. reported that catecholamines could prevent hypoglycemia during exercise in humans [37]. Therefore, the neuroendocrine system may be one of the pathways by which blood pressure affects the relationship between the TyG–BMI and all-cause mortality.

However, our study has several limitations. First, blood samples taken in a nonfasting state were used in this study. Second, the waist-to-hip ratio could not be obtained from all the subjects. Nevertheless, we believe that BMI can replace the waist‒to-hip ratio to some extent in this study. Third, the associations between the TyG index and TyG–BMI and cause-specific mortality, such as cardiovascular and cerebrovascular disorders, were not analyzed. Finally, all the centenarians were from Hainan Province, China, and the relationships of the TyG index and TyG–BMI with all-cause mortality in different countries and different races remain to be further investigated.

Conclusions

In conclusion, the results of the China-Hainan Centenarian Longevity Cohort Study (CHCCS) revealed that both the TyG index and TyG–BMI were significantly associated with all-cause mortality in Chinese Hainan centenarians and that the TyG–BMI was more efficient than the TyG index. Our findings should be taken into consideration to improve the management of blood glucose, blood lipids and BMI to achieve healthy aging in centenarians.

Data availability

The raw data supporting the conclusions of this article will be made available from the corresponding author upon request and without undue reservation.

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Acknowledgements

We thank all patients for making this study possible.

Funding

This study was supported by the National Key Research and Development Program of China (No. 2022YFC3602900, 2022YFC3602902 and 2022YFC3602903), the National Natural Science Foundation of China (No. 82270769, No. 32141005), the Specialized Project of Military Logistics Scientific Research and Health Care (No. 21BJZ37), Sanya science and technology innovation special project (No. 2022KJCX02), the Specific research fund of the Innovation Platform for Academicians of Hainan Province, Beijing Natural Science Foundation (No.7242033), Capital’s Funds for Health Improvement and Research (No. CFH 2024-1-5021), Science & Technology Project of Beijing (No. Z221100007422121).

Author information

Author notes

  1. Shiju Yan, Wenjing Dong and Yue Niu contributed equally to this work and share first authorship.

Authors and Affiliations

  1. Department of Orthopedics, Hainan Hospital of Chinese PLA General Hospital, Hainan, Sanya, 572013, China

    Shiju Yan

  2. Department of Endocrinology, Hainan Hospital of Chinese PLA General Hospital, Hainan, Sanya, 572013, China

    Wenjing Dong, Lingyun Song, Ping Pang, Di Sun, Yue Zhang, Wei Wang & Guoqing Yang

  3. Chinese PLA Medical College, Beijing, 100039, China

    Wenjing Dong

  4. Senior Department of Nephrology, State Key Laboratory of Kidney Diseases, Beijing Key Laboratory of Medical Devices and Integrated Traditional Chinese and Western Drug Development for Severe Kidney Diseases, Beijing Key Laboratory of Digital Intelligent TCM for the Prevention and Treatment of Pan-vascular Diseases, First Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Kidney Diseases, Key Disciplines of National Administration of Traditional Chinese Medicine(zyyzdxk-2023310), Beijing, 100853, China

    Yue Niu, Bin Wang, Xiangmei Chen & Yizhi Chen

  5. Department of Laboratory Medicine, Hainan Hospital of Chinese PLA General Hospital, Sanya, 572013, China

    Hongyan Hu

  6. Department of Nephrology, Hainan Hospital of Chinese PLA General Hospital, Academician Chen Xiangmei of Hainan Province Kidney Diseases Research Team Innovation Center, Sanya, 572013, China

    Xinye Jin, Jie Zhang, Qing Luo, Ding Sun, Hao Li, Zehao Zhang, Zeyu Qu & Yizhi Chen

  7. Central Laboratory, Hainan Hospital of Chinese PLA General Hospital, Sanya, 572013, China

    Qiao Zhu, Yujian Chen, Chaoxue Ning & Yali Zhao

  8. Department of Cardiology, Hainan Hospital of Chinese PLA General Hospital, Sanya, 572013, China

    Shihui Fu

  9. Department of Disease Prevention and Control, First Medical Center, Chinese PLA General Hospital, Beijing, 100853, China

    Shanshan Yang

  10. Institute of Geriatrics, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Second Medical Center, State Key Laboratory of Kidney Diseases, Chinese PLA General Hospital, Beijing, 100853, China

    Shengshu Wang, Yao He & Miao Liu

  11. The Second School of Clinical Medicine, Southern Medical University, Guangzhou, 510515, China

    Yizhi Chen

  12. Sanya Nephrology Medical Quality Control Center, Sanya, 572013, China

    Yizhi Chen

Authors
  1. Shiju Yan
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  2. Wenjing Dong
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Contributions

CY, LM, CX and DW designed the concept of the study. CY, NY, SL, WB, ZQ, YS, CY, NC and DW collected and analyzed the data. YS, PP, ZY, SD, WW, YG, HY, ZJ, HH and YS critically revised the analysis. YS, DW, WS, FS, SD, LH, QZ, ZZ, LQ, JX and DW wrote the draft manuscript. All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

Corresponding authors

Correspondence to Xiangmei Chen, Miao Liu or Yizhi Chen.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the Ethics Committee of the Hainan Hospital of Chinese PLA General Hospital (No. 301HNLL-2016-01) and was conducted in accordance with the World Medical Association Declaration of Helsinki and its subsequent revisions. Written informed consent was obtained from each patient in accordance with institutional guidelines.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

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Yan, S., Dong, W., Niu, Y. et al. Associations of the triglyceride–glucose index and triglyceride–glucose/body mass index with all-cause mortality in Chinese centenarians. BMC Geriatr 25, 266 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12877-025-05894-w

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Keywords

BMC Geriatrics

ISSN: 1471-2318

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