Background: Previous studies has shown a significant relationship between baseline triglyceride-glucose (TyG) index and cardiovascular disease (CVD). However, the long-term effect of TyG index and incident CVD remains uncertain. This study aimed to investigate the association between cumulative TyG index and the risk of CVD. Method: In this study, we recruited individuals participating in Kailuan Study from 2006 to 2013 without stroke, myocardial infarction, and cancer in the four consecutive examinations. Cumulative TyG index was calculated by multiplying the average TyG index and the time between the two consecutive examinations. Cumulative TyG index levels were categorized into four quartile groups: Q1 group, ≤ 50.65 (as reference group), Q2 group, 50.65–53.86, Q3 group, 53.86–57.44, Q4 group, > 57.44. The association between cumulative TyG index and the risk of CVD was estimated by multivariable Cox proportional hazard models. Result: A total of 44,064 individuals participated in the final analysis. After a mean follow-up of 6.52 ± 1.14 years, incident CVD, MI and stroke occurred in 2057, 395 and 1695, respectively. The risk of developing CVD increased with the quartile of cumulative in TyG index, after adjustment for multiple potential confounders, the HR for CVD events were 1.25 (1.08–1.44) in Q2, 1.22 (1.05–1.40) in Q3 and 1.39 (1.21–1.61) in Q4, compared to Q1 group. The longer duration of higher TyG index exposure was significantly associated with increased CVD risk. Similar results were obtained in the subgroup and sensitivity analysis. Conclusion: Cumulative TyG index was associated with increased risk of CVD. Maintaining an appropriate level of TG and FBG within the desirable range and better control of cumulative TyG index are important for prevention of CVD.
Keywords: Triglyceride-glucose index; Cardiovascular disease; Cumulative exposure; Cohort study; Prevention
Haozhe Cui and Qian Liu contributed equally to this work
According to epidemiological studies, cardiovascular disease (CVD) is still the leading cause of morbidity and mortality among chronic non-communicable diseases globally. Despite improvement in CVD outcomes following the progress of living standards and medical levels, the high incidence of CVD remains a major health concern [[
Epidemiological and pathophysiological studies suggest that insulin resistance (IR) may be largely responsible for vascular endothelial dysfunction and CVD [[
Therefore, in the present study, we investigated to determine the impact of cumulative TyG index, a measure which incorporates both the levels of TyG index and the duration of the exposure elevated TyG index, on the risk of developing CVD by using a large community-based prospective cohort from Kailuan Study.
The Kailuan Study is an ongoing prospective community-based cohort study conducted in Tangshan, China. All participants in the Kailuan Study are employees and retirees of the Kailuan Group. Details of the study design and procedure have been described elsewhere [[
Graph: Fig. 1 Flowchart of the study population
The study was conducted in accordance with the guidelines of the Declaration of Helsinki and was approved by the Kailuan General Hospital Ethics Committee. All the participants agreed to take part in the study and provided written informed consent.
Information on demographic and clinical characteristics (age, sex, lifestyle, and past medical history, etc.) were collected using a self-reported questionnaire, as detailed elsewhere [[
Elbow venous blood samples of 5 mL were collected into an anticoagulant tube containing EDTA between 7:00–9:00 am after overnight fasting for at least 8 h, and the serum was collected after centrifugation at 3000 × g for 10 min. The supernatant was measured within 4 h. All biochemical measurement including TG, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), high-sensitive C-reactive protein (Hs-CRP), FBG, and Uric acid (UA), and etc. was measured on the Hitachi 747 autoanalyzer (Hitachi, Tokyo, Japan).
Hypertension was defined as SBP ≥ 140 mmHg or DBP ≥ 90 mmHg, a self-reported history of hypertension, or any use of antihypertensive medication. Diabetes was defined as FBG ≥ 7.0 mmol/L, a self-reported history of diabetes, or use of antidiabetic medication.
The TyG index was calculated as ln (fasting TG [mg/dL] × FBG [mg/dL]/2), as previously reported [[
Graph
where TyG index
According to previous studies, adults with a higher TyG index experience an increased risk of CVD, in the current analysis, participants with a fourth quartile of TyG index (> 9.02) at each examination were identified to be in the higher TyG index exposure group [[
Follow-up ended at the first record of CVD event, all-cause death or at the end of follow-up on 31 December 2019, whichever came first. The types of CVD included MI and stroke. We used ICD-10th revision codes to identify CVD cases (I21 for MI, I6 for stroke) [[
Continuous variables were compared using analysis of variance or the Kruskal–Wallis test according to distribution, and categorical variables were compared with the chi-square test.
Kaplan–Meier method was used to compute cumulative incidence of CVD and subgroup of CVD. Cox proportional hazard models were used with age as the time scale to estimate the hazard ratios (HRs) for incident CVD by cumulative TyG index, and were adjusted for baseline confounders, including sex, income (categories of high, intermediate, and low), educational level, drinking (yes or no), smoking (yes or no), physical exercise (active or inactive), diabetes, hypertension, lipid‐lowering medication, BMI, resting heart rate(RHR), HDL-C, LDL-C, UA, Hs-CRP. Missing covariates were imputed by multiple imputation using the fully conditional specification method SAS MI procedure. The results were consistent from analyses that excluded participants with missing covariates. The proportional hazard assumption was examined by Schoenfeld residuals.
To examine the robustness of our results, we performed several sensitivity analyses. First, we excluded events occurring in the first 2 years of follow-up to minimize potential reverse causation. Second, we excluded participants with diabetes or received treatment with lipid lowering medication and repeated analysis. Third, additional adjustment for TyG index at baseline. All analyses were done with SAS 9.4 (SAS Institute, Cary, NC), at a two-tailed alpha level of 0.05.
A total of 44,064 eligible participants were included in present analysis, their mean age was 54.30 ± 11.65 years, and 74.80% were men. The average cumulative TyG index was 54.12 ± 5.13. To baseline characteristics of participants according to the quartile of cumulative TyG index are shown in Table 1. When compared to the Q1 group, participants in the other groups were more likely to be older, men, less well educated, more current smokers and drinkers, a higher prevalence of hypertension, diabetes, and lipid‐lowering medication, more likely to take antihypertensive agents and antidiabetic agents, had a higher BMI, RHR, LDL-C, UA and Hs-CRP level, and a lower HDL-C level.
Table 1 Baseline characteristics of participants by cumulative TyG index quartiles (n = 44064)
Q1 group Q2 group Q3 group Q4 group N 11,016 11,017 11,017 11,014 < 0.001 Age, mean ± SD, years 49.92 ± 10.69 52.78 ± 11.43 56.25 ± 11.47 58.22 ± 11.21 < 0.001 Male, % 7670 (69.63) 8431 (76.53) 8527 (77.40) 8328 (75.61) < 0.001 BMI, mean ± SD, kg/m2 24.15 ± 3.19 24.77 ± 3.24 25.28 ± 3.24 25.87 ± 3.18 < 0.001 RHR, mean ± SD, beats/min 71.66 ± 9.73 72.83 ± 10.54 73.78 ± 10.56 75.16 ± 10.67 < 0.001 HDL-C, mmol/L 1.43 (1.21–1.69) 1.38 (1.19–1.60) 1.32 (1.11–1.55) 1.20 (0.99–1.44) < 0.001 LDL-C, mmol/L 2.24 (1.68–2.84) 2.50 (2.01–2.97) 2.50 (2.00–3.05) 2.59 (2.07–3.13) < 0.001 UA, mean ± SD, μmol/L 307.27 ± 91.66 296.64 ± 92.90 309.76 ± 89.45 326.33 ± 89.92 < 0.001 Hs-CRP, mg/dL 1.12 (0.39–2.97) 0.90 (0.20–2.19) 1.23 (0.51–2.63) 1.59 (0.83–3.00) < 0.001 High income, % 754 (23.20) 746 (22.95) 837 (25.75) 913 (28.09) < 0.001 High school or above, % 1061 (28.85) 939 (25.53) 871 (23.68) 807 (21.94) < 0.001 Drinking, % 1625 (21.12) 1774 (23.06) 2035 (26.45) 2260 (29.37) < 0.001 Smoking, % 3168 (23.85) 3085 (23.22) 3485 (26.23) 3546 (26.69) < 0.001 Physical exercise, % 1066 (17.32) 1327 (21.56) 1821 (29.59) 1940 (31.52) < 0.001 Diabetes, % 225 (6.78) 496 (14.94) 812 (24.46) 1787 (53.83) < 0.001 Hypertension, % 2742 (16.49) 4180 (25.14) 4485 (26.97) 5220 (31.39) < 0.001 Lipid‐lowering medication, % 245 (16.20) 288 (19.05) 415 (27.45) 564 (37.30) < 0.001 TyG index2006, mean ± SD 8.18 ± 0.53 8.50 ± 0.57 8.71 ± 0.59 9.15 ± 0.67 < 0.001 TyG index2008, mean ± SD, 8.17 ± 0.51 8.52 ± 0.51 8.72 ± 0.54 9.24 ± 0.69 < 0.001 TyG index2010, mean ± SD 8.24 ± 0.50 8.52 ± 0.52 8.74 ± 0.54 9.27 ± 0.67 < 0.001 TyG index2012, mean ± SD 8.29 ± 0.53 8.52 ± 0.55 8.74 ± 0.60 9.22 ± 0.71 < 0.001
BMI body mass index, RHR resting heart rate, HDL high-density lipoprotein, LDL low-density lipoprotein, UA uric acid, Hs-CRP high-sensitivity C-reactive protein, TG triglyceride, FBG fasting blood glucose, TyG triglyceride glucose
After a mean follow-up of 6.52 ± 1.14 years starting after the fourth examination, incident CVD, MI and stroke occurred in 2057, 395 and 1695, respectively. The Kaplan–Meier curve indicates a stepwise increase in the incidence of CVD across the patterns of cumulative TyG index (χ
Table 2 Association of cumulative TyG index with CVD from 2013 to 2019 (n = 44,064)
Case Cumulative incidence, % Sex-adjusted Multiple-adjusted Q1 307 3.13 Ref Ref Q2 474 4.97 1.36 (1.18–1.57) 1.25 (1.08–1.44) Q3 544 5.89 1.39 (1.20–1.60) 1.22 (1.05–1.40) Q4 709 7.51 1.78 (1.55–2.04) 1.39 (1.21–1.61) P for trend < 0.001 Per SD 1.10 (1.05–1.16) 0 year 819 4.22 Ref Ref 2 years 428 6.01 1.44 (1.28–1.62) 1.28 (1.14–1.44) 4 years 283 6.06 1.52 (1.33–1.74) 1.24 (1.08–1.43) 6 years 228 6.24 1.55 (1.34–1.80) 1.21 (1.04–1.42) 8 years 276 8.01 1.94 (1.69–2.22) 1.42 (1.22–1.66) P for trend < 0.001
Multivariable model adjusted for sex, income, educational level, drinking, smoking, diabetes, hypertension, lipid‐lowering medication, BMI, RHR, HDL-C, LDL-C, UA, Hs-CRP Culumative TyG index SD = 5.13
Table 3 Association of cumulative TyG index with subgroup of CVD from 2013 to 2019 (n = 44,064)
MI Stroke Case Cumulative incidence, % Multiple-adjusted Case Cumulative incidence, % Multiple-adjusted Q1 51 0.50 Ref 259 2.70 Ref Q2 93 0.92 1.49 (1.05–2.10) 388 4.14 1.20 (1.02–1.40) Q3 95 0.95 1.25 (0.89–1.78 455 5.01 1.19 (1.02–1.40) Q4 138 1.40 1.53 (1.09–2.16) 584 6.26 1.35 (1.16–1.58) P for trend < 0.001 < 0.001 Per SD 1.08 (0.97–1.21) 1.10 (1.05–1.16) 0 year 132 0.67 Ref 696 3.61 Ref 2 years 86 1.10 1.57 (1.19–2.07) 351 5.11 1.23 (1.08–1.40) 4 years 50 1.00 1.31 (0.94–1.84) 238 5.17 1.22 (1.05–1.43) 6 years 46 1.20 1.47 (1.03–2.10) 183 5.07 1.14 (0.96–1.36) 8 years 63 1.78 1.89 (1.34–2.65) 218 6.40 1.32 (1.12–1.57) P for trend < 0.001 < 0.001
Multivariable model adjusted for sex, income, educational level, drinking, smoking, diabetes, hypertension, lipid‐lowering medication, BMI, RHR, HDL-C, LDL-C, UA, Hs-CRP
Figure 2b shows the Kaplan–Meier incidence rate stratified by the times of examinations with a higher TyG index. There was a progressively increasing risk of incidence with the times of examinations with a higher TyG index (P < 0.001). After adjustment for potential confounders, compared with the unexposed group (0 years), risk of CVD was significantly higher in those with 2 years group (HR 1.29; 95% CI 1.15, 1.46), 4 years group (HR 1.25; 95% CI 1.09, 1.44), 6 years group (HR 1.21; 95% CI 1.04, 1.42), and 8 years group (HR 1.42; 95% CI 1.22, 1.66) (Table 2).
Graph: Fig. 2 Kaplan–Meier incidence rate of CVD by TyG index. a Quartiles of cumulative TyG index. b Exposure duration with a higher TyG index
In the sensitivity analyses, the associations of cumulative TyG index with risk of incident CVD were not materially changed after excluding participants with CVD occurring within the first two years of the follow-up, or excluding participants who received treatment with lipid-lowering medications, or excluding participants with diabetes, or additional adjustment for TyG index at baseline (Table 4).
Table 4 Association of cumulative TyG index with CVD-sensitivity analysis
Analysis 1 Analysis 2 Analysis 3 Analysis 4 CVD MI Stoke CVD MI Stoke CVD MI Stoke CVD MI Stoke Q1 Ref Ref Ref Ref Ref Ref Ref Ref Ref Ref Ref Ref Q2 1.26 (1.07–1.49) 1.49 (0.99–2.23) 1.23 (1.02–1.47) 1.29 (1.11–1.50) 1.53 (1.07–2.19) 1.22 (1.03–1.43) 1.30 (1.12–1.52) 1.35 (0.95–1.92) 1.24 (1.05–1.47) 1.20 (1.04–1.40) 1.38 (0.98–1.96) 1.16 (0.99–1.36) Q3 1.20 (1.02–1.42) 1.19 (0.79–1.80) 1.21 (1.01–1.44) 1.27 (1.09–1.47) 1.31 (0.91–1.88) 1.21 (1.03–1.42) 1.27 (1.09–1.48) 1.07 (0.74–1.54) 1.23 (1.04–1.45) 1.14 (0.99–1.33) 1.12 (0.78–1.60) 1.14 (0.94–1.34) Q4 1.35 (1.15–1.59) 1.34 (0.89–2.02) 1.36 (1.14–1.63) 1.43 (1.23–1.66) 1.60 (1.11–2.29) 1.33 (1.13–1.57) 1.52 (1.31–1.77) 1.34 (0.94–1.91) 1.40 (1.19–1.66) 1.25 (1.06–1.46) 1.24 (0.85–1.80) 1.24 (1.04–1.47) 0 year Ref Ref Ref Ref Ref Ref Ref Ref Ref – – – 2 years 1.28 (1.12–1.47) 1.46 (1.04–2.04) 1.26 (1.09–1.45) 1.22 (1.07–1.38) 1.51 (1.13–2.01) 1.16 (1.01–1.33) 1.24 (1.09–1.41) 1.51 (1.13–2.02) 1.20 (1.05–1.38) – – – 4 years 1.26 (1.08–1.48) 1.22 (0.81–1.85) 1.27 (1.06–1.51) 1.23 (1.06–1.43) 1.24 (0.86–1.79) 1.23 (1.01–1.45) 1.19 (1.02–1.39) 1.21 (0.84–1.74) 1.19 (1.01–1.40) – – – 6 years 1.24 (1.04–1.48) 1.54 (1.01–2.34) 1.18 (0.96–1.43) 1.10 (0.92–1.31) 1.32 (0.88–1.97) 1.05 (0.86–1.28) 1.18 (0.99–1.39) 1.26 (0.85–1.87) 1.15 (0.95–1.38) – – – 8 years 1.51 (1.26–1.79) 2.08 (1.39–3.10) 1.42 (1.17–1.72) 1.42 (1.20–1.69) 2.11 (1.46–3.03) 1.29 (1.06–1.57) 1.46 (1.24–1.71) 1.78 (1.23–2.57) 1.37 (1.15–1.65) – – –
Multivariable model adjusted for sex, income, educational level, drinking, smoking, diabetes, hypertension, lipid‐lowering medication, BMI, RHR, HDL-C, LDL-C, UA, Hs-CRP Analysis1 excluded participants events occurring in the first 2 years of follow-up (n = 884); Analysis2 excluded participants with diabetes at baseline (n = 3320); Analysis3 excluded received treatment with lipid lowering medication at baseline and follow-up (n = 5866); Analysis4 additional adjustment for TyG index at baseline
In this prospective cohort study of 44,064 individuals from Kailuan study, we found an association between cumulative TyG index and the risk of CVD. In particular, higher exposure to cumulative TyG index was associated with CVD and subgroup of CVD in a period of mean 6.52 years. We also found that longer time of higher TyG index exposure could increase risk for CVD and subgroup. Additionally, this result was also validated in non-diabetes and not taking lipid-lowering medication populations.
Previous studies have found that participants with a higher TyG index were at a higher risk of developing CVD compared to low-level group [[
Another important finding was derived from our subgroup analysis. Our findings indicate that cumulative TyG index seems to significantly increase the risk of developing MI and stroke, and the risk of cumulative TyG index developing in MI is slightly higher than that in stroke. Epidemiological survey showed that the prevalence of stroke patients are significantly more than patients with MI [[
To the best of our knowledge, few cohort studies have explored TyG index by repeated measurements analysis. Wang et al. found that higher levels of TyG index were associated with an increased risk of future stroke and ischemic stroke by updated cumulative average exposure [[
The increased risks of CVD and subgroup is possibly explained by persistent, low-degree inflammation, arterial stiffness and endothelial dysfunction caused by cumulative TyG index [[
Our study has important implications for CVD prevention. The cumulative TyG index might help identify individuals at high risk for developing CVD in a large and long-term follow-up cohort. For the general populations, maintaining an appropriate level of TG and FBG within the desirable range and better control of cumulative TyG index is important for controlling the chronic diseases. For patients with diabetes and hyperlipidemia, motivating patients to adhere to glucose-lowering, and lipid-lowering medications and treatment monitoring for a long time for actively controlling FBG and TG levels [[
In the present study, we observed that cumulative TyG index was associated with increased risk of CVD. Hence, clinicians should consider the risk of incident CVD in people with abnormal FBG and TG and counsel them about metabolic fitness.
The authors thank all the members of the Kailuan Study Team for their contributions and the participants who contributed their data. Hey, Liu, I love you.
Haozhe Cui and Liu Qian wrote the main manuscript text and conceived and designed the study. Haozhe Cui analyzed the data. Liu Qian carried out literature search. Yuntao Wu and Liying Cao performed the manuscript review. All authors have read and approved the final manuscript.
None.
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
The study was performed according to the guidelines of the Helsinki Declaration and was approved by the Ethics Committee of Kailuan General Hospital (approval number: 2006-05). All participants were agreed to take part in the study and provided informed written consent.
Not applicable.
The authors declare no potential conflict of interest.
Graph: Additional file 1: Fig. S1. Kaplan-Meier incidence rate of stroke and MI by TyG index. a quartiles of cumulative TyG index for stroke. b quartiles of cumulative TyG index for MI. c exposure duration with a higher TyG index for stroke. d exposure duration with a higher TyG index for MI.
• BMI
- Body mass index
• CI
- Confidence interval
• CVD
- Cardiovascular disease
• FBG
- Fasting blood glucose
• HR
- Hazard ratio
• Hs-CRP
- High-sensitivity C-reactive protein
• LDL-C
- Low-density lipoprotein cholesterol
• SD
- Standard deviation
• TG
- Triglyceride
• TyG
- Triglyceride-glucose
• UA
- Uric acid
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By Haozhe Cui; Qian Liu; Yuntao Wu and Liying Cao
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