Exploring the U-shaped nonlinear relationship of CHG index with metabolic syndrome and mortality risks in metabolic syndrome patients.

backgroundMetabolic syndrome (MetS) is a worldwide condition that markedly elevates the risk of chronic conditions. The cholesterol, high-density lipoprotein, and glucose (CHG) indices simultaneously reflect various metabolic parameters, including lipid metabolism, cardiovascular function, and insulin sensitivity, providing considerable clinical value. This study aimed to investigate the association between the CHG index and MetS, along with their connections with all-cause death and cardiovascular disease (CVD) death in individuals with MetS.

methodsThe NHANES dataset (2001-2018) was used to assess the relationship between the CHG index and MetS via cross-sectional research and weighted logistic regression analysis. Cohort studies and a weighted Cox proportional hazards model were employed to investigate the relationships of CHG with all-cause mortality and cardiovascular mortality in individuals with MetS. A possible nonlinear association between the CHG score and MetS, along with all-cause and CVD mortality in MetS patients, was assessed via general additive models and smooth fitting of curves. Kaplan‒Meier (K‒M) survival curves were generated to illustrate prognostic variations across CHG index quartiles. Subgroup analyses were performed to investigate discrepancies in these associations across different populations. Finally, the consistency and dependability of the outcomes were verified through repeated analysis via multiple imputation of the data and external validation with CHARLS.

resultsAfter adjusting for relevant confounding factors, the CHG index was positively correlated with all-cause Mortality and CVD Mortality among individuals with MetS. Further analysis revealed a U-shaped nonlinear relationship for these associations, with inflection points at 46.12, 52.67, and 50.82, respectively. K‒M survival curve analysis indicated that the prognosis for the middle quartile of the CHG index was better than that for both the lower and upper quartiles. Subgroup analyses further highlighted differences in these associations across various populations. Ultimately, the sensitivity analysis demonstrated the robustness of the findings.

conclusionThe CHG index has a substantial U-shaped nonlinear association with the incidence of MetS and the risk of all-cause and cardiovascular death in patients with MetS. Previous interventions have focused primarily on high-risk extremes, but the findings of this study suggest that patients with low CHG levels should also be included in monitoring. Future prospective studies are needed to validate these findings and explore their potential clinical applications in managing MetS patients.