Objective: Recent studies suggest that simple biomarkers derived from routine laboratory parameters may capture long-term risk beyond traditional clinical factors. The objective of this study was to evaluate the prognostic value of two novel biomarkers: the triglyceride–glucose index (TyG) and triglyceride–glucose body mass index (TyG-BMI), for the prediction of fatal and non-fatal cardiovascular (CV), cerebrovascular, and kidney outcomes. Design and method: This prospective cohort included 784 adults (mean age 52.5 years, 34.9% men, 59.2% had hypertension, and 13.9% had diabetes) from the ENAH rural study with available baseline biomarker data. Biomarkers were analysed as standardized z-scores and by tertiles. Median follow-up was 117 months (IQR 87–141). Outcomes included all-cause and CV mortality, and a composite non-fatal outcome. Associations were assessed using Cox proportional hazards models. Kaplan–Meier survival curves with log-rank testing were used to compare outcomes across tertiles. Results: During follow-up, 192 participants (24.5%) died and 99 (12.6%) experienced a non-fatal composite outcome. In univariable Cox regression analyses, higher TyG z-scores were associated with increased all-cause mortality (HR=1.39, 95%CI 1.24–1.57, p<0.001) and CV mortality (HR=1.49, 95%CI 1.24–1.81, p<0.001). Similar associations were observed for TyG-BMI with all-cause (HR=1.23, 95%CI 1.07–1.41, p=0.003) and CV mortality (HR=1.32, 95%CI 1.06–1.65, p=0.015). In Kaplan–Meier analyses, higher TyG tertiles were associated with increased all-cause and CV mortality (log-rank p<0.00 and p=0.002), with participants in the highest tertile showing more than a two-fold higher of all-cause (HR=2.22, 95%CI 1.58–3.12) and a three-fold higher risk of CV mortality (HR=3.03, 95%CI 1.69–5.42) compared with the lowest tertile. Similar trends were observed for TyG-BMI tertiles (log-rank p=0.025 for all-cause and p=0.041 for CV mortality). After multivariable adjustment, TyG and TyG-BMI were no longer independently associated with mortality. Neither biomarker predicted non-fatal outcomes. Conclusions: TyG and TyG-BMI showed strong unadjusted and tertile based associations with all-cause and CV mortality, but in fully adjusted models were not independently linked to mortality. Our findings indicate these biomarkers do not enhance long-term risk assessment beyond traditional factors in general adult rural populations.
Štimac et al. (Fri,) studied this question.