Author:
Kityo Anthony,Lee Sang-Ah
Abstract
Abstract
Background
Simple biochemical and anthropometric measurements such as fasting blood glucose (FBG), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), waist circumference (WC), and body mass index (BMI) are used to formulate insulin resistance (IR) indices. Whether these indices provide new predictive information for mortality remains unknown. This study examined the relationships of biochemical, anthropometric, and IR indices with mortality risk, as well as their predictive performance.
Methods
The data source was the Korean Genome and Epidemiology Study (2004–2020) involving 114,957 participants whose data were linked to death records. The IR indices- triglyceride-glucose index (TyG), TyG-BMI, TyG-WC, visceral adiposity index (VAI), lipid accumulation product (LAP), and metabolic score for insulin resistance (METS-IR) were computed using standard formulae. The associations were examined using restricted cubic splines. The predictive performance was compared using the log-likelihood ratio chi-square test.
Results
Body mass index was U-shaped, HDL-C was reverse J-shaped, and FBG and TG levels were J-shaped associated with all-cause mortality. Results showed U-shaped (TyG), J-shaped (TyG-BMI, VAI, LAP, and METS-IR), and reverse J-shaped (TyG-WC) associations with all-cause mortality. The percentages of new predictive information for all-cause mortality explained by the FBG level, BMI, TyG-BMI, and METIR were 3.34%, 2.33%, 1.47%, and 1.37%, respectively. Other IR indices and biochemical and anthropometric measurements provided < 1.0% of new predictive information. For cardiovascular disease mortality, the FBG, BMI, METIR, TyG-BMI, and HDL-C levels explained 2.57%, 2.12%, 1.59%, 1.30%, and 1.27% of new predictive information respectively. Moreover, the risks of cancer mortality explained by FBG level, VAI, and HDL-C level were 2.05%, 1.49%, and 1.28%, respectively.
Conclusions
Fasting blood glucose level is a superior predictor of mortality risk and may be used as a simple predictive and preventative factor.
Publisher
Springer Science and Business Media LLC
Subject
Biochemistry (medical),Clinical Biochemistry,Endocrinology,Endocrinology, Diabetes and Metabolism