Association between triglyceride-glucose related indices and all-cause and cardiovascular mortality among the population with cardiovascular-kidney-metabolic syndrome stage 0-3: a cohort study

Abstract

Background: Cardiovascular-Kidney-Metabolic (CKM) syndrome typically commences with the interaction of insulin resistance (IR), excessive or dysfunctional obesity, and the consequent systemic inflammatory response and oxidative stress. The relationship between the triglyceride-glucose (TyG) index and TyG-related indices that may simply assess IR and obesity, as well as the mortality risk in the CKM syndrome population, remains ambiguous.

Methods: This study included 6,383 participants from the National Health and Nutrition Examination Survey (NHANES) 2009-2018. The TyG index, TyG-waist-to-height ratio (TyG-WHtR), TyG-waist circumference (TyG-WC), and TyG-body mass index (TyG-BMI) were developed. Cox proportional hazards models, smooth curve fitting, and two-stage Cox proportional hazards models were employed to examine the association of TyG and TyG-related indices with all-cause and cardiovascular mortality in the CKM syndrome population. Subgroup analyses and interaction tests were conducted to evaluate the risk within various demographics.

Results: In survey-weighted multifactorial regression analyses, a significant positive association existed between TyG, TyG-related indices, and both all-cause mortality and cardiovascular mortality, except for the TyG index, which did not demonstrate a significant link with all-cause mortality. Of these indices, the TyG-WC index exhibited the strongest correlation with all-cause mortality, with a hazard ratio (HR) of 1.50 and a 95% confidence interval (CI) of 1.18-1.92, followed by the TyG-WHtR index (HR: 1.45, 95%CI 1.13-1.85). The TyG-WHtR index demonstrated the strongest correlation with cardiovascular mortality (HR: 1.85, 95% CI 1.19-2.86), followed by the TyG-WC index(HR: 1.83, 95%CI 1.21-2.78). An L-shaped association was identified between TyG-WHtR, TyG-BMI, and all-cause mortality in CKM syndrome during the examination of nonlinear relationships (both P for log-likelihood ratio < 0.05). The TyG-WHtR, TyG-WC, and TyG-BMI indices exhibited a more pronounced correlation with all-cause mortality in those with CKM syndrome stages 1 and 3 (P value < 0.05, P for interaction < 0.05).

Conclusion: Our study emphasizes the association between TyG and TyG-related indices and mortality in individuals with CKM syndrome stages 0-3. Individuals with CKM syndrome stages 1 and 3 should be more vigilant to abnormal alterations in TyG-related indices.

Keywords: All-cause mortality; Body mass index; Cardiovascular mortality; Cardiovascular-kidney-metabolic syndrome; Triglyceride-glucose index; Waist circumference; Waist-to-height ratio.

Fig. 1

Flowchart of the study population

Fig. 2

Cox proportional hazards regression analysis of TyG and TyG-related indices concerning all-cause and cardiovascular mortality in a CKM syndrome stage 0–3 population, weighted for representativeness. Abbreviations: HR, hazard ratio; CI, confidence interval; SD, standard deviation; CKM syndrome, Cardiovascular-Kidney-Metabolic syndrome; TyG, triglyceride-glucose index; WHtR, waist-to-height ratio; WC, waist circumference; BMI, body mass index. The model was adjusted for age, gender, race, poverty income ratio, eGFR, UACR, uric acid, SBP, DBP, HDL-C, LDL-C, HbA1c, smoking, drinking, statin use, antihypertensive use, antihyperglycemic agent use, insulin use, liver disease, cancer, hypertension, diabetes, MeTS, CKD, and CKM syndrome.

Fig. 3

Smooth curve fitting of the association between TyG and TyG-related indices and all-cause and cardiovascular mortality in a group with CKM syndrome stage 0–3. Abbreviations: CKM syndrome, Cardiovascular-Kidney-Metabolic syndrome; TyG, triglyceride-glucose index; WHtR, waist-to-height ratio; WC, waist circumference; BMI, body mass index. The solid red line at the center represents a smooth curve fit, while the blue-shaded regions on either side show 95% confidence intervals. The model was adjusted for age, gender, race, poverty income ratio, eGFR, UACR, uric acid, SBP, DBP, HDL-C, LDL-C, HbA1c, smoking, drinking, statin use, antihypertensive use, antihyperglycemic agent use, insulin use, liver disease, cancer, hypertension, diabetes, MeTS, CKD, and CKM syndrome.