Association of triglyceride-glucose index with the prevalence of cardiovascular disease in malnourished/non-malnourished patients: a large cross-sectional study - Jiang, Xiaobo; Tu, Jiabin; Chen, Sicong; Zhang, Yanbin; Qiu, Weilong; Chen, Kaihong; Chen, Liling; Wu, Bo (Frontiers in Cardiovascular Medicine, 2023)
Background Numerous investigations have demonstrated a strong association between the TyG (triglyceride-glucose) index, which is derived from lipid and glucose levels in the bloodstream, and the onset and progression of cardiovascular diseases (CVD). Blood glucose and blood lipids are affected by nutritional status, and few studies have explored whether the correlation between TyG index and the risk of CVD is affected by nutritional status. Aims To investigate the connection between TyG index and the risk of CVD among individuals with varying nutritional statuses. Method A total of 19,847 were included in the analysis, of which 15,955 participants were non-malnourished and 3,892 patients were malnourished. According to the TyG index quartile, the patients were categorized into four groups. Logistic regression analysis and restricted cubic spline was used to study the relationship between TyG index and the risk of CVD in normal and malnourished populations. Results The results of the restricted cubic spline showed that the TyG index was positively associated with the risk of CVD in the non-malnourished population. The TyG index showed a U-shaped association with the risk of CVD in malnourished people. The result is consistent with that of logistic regression (Malnutrition: Group 2: OR: 1.14; 95% CI: 0.85–1.53; Group 3: OR: 1.36; 95% CI: 1.03–1.79; Group 4: OR: 1.72; 95% CI:1.31–2.25, P for trend <0.001; Non-malnutrition: Group 2: OR: 0.82; 95% CI: 0.46–1.48; Group 3: OR: 0.88; 95% CI: 0.49–1.57; Group 4: OR: 1.45; 95% CI:0.83–2.52, P for trend =0.067). Conclusions The association between the TyG index and the risk of CVD varied depending on the nutritional states. When using TyG index to assess the risk of CVD, stratification combined with nutritional status helps to more accurately screen patients at high risk of CVD.