Journal of inflammation research · 2026
Association of Triglyceride-to-HDL Cholesterol Ratio with Osteoarthritis: Multicenter Evidence and Application of an Interactive Risk Visualization Tool.
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Chen Junrui, Hong Weishi, Tian Xue, Wang Wei, Sun Yu
Аннотация
BACKGROUND: Osteoarthritis (OA) is a degenerative joint disease increasingly recognized to be closely associated with lipid metabolism dysregulation. The triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio, a composite marker of metabolic abnormalities, is widely used to predict the risk of metabolic diseases, yet its link with OA risk remains unclear.
OBJECTIVE: This study aimed to evaluate the association between TG/HDL-C and OA risk, explore potential nonlinear dose-response relationships and subgroup heterogeneity, and develop an interactive visualization tool for clinical application.
METHODS: A total of 6,570 participants were included in this multicenter cross-sectional study. Multivariable logistic regression, random forest modeling, and restricted cubic spline (RCS) analyses were conducted to assess independent associations, variable importance, and nonlinear trends. Stratified analyses by sex and diabetes status identified subgroup-specific thresholds. An interactive risk visualization tool was created using the R Shiny platform.
RESULTS: Each unit increase in TG/HDL-C was associated with an 11% higher OA risk (OR = 1.11; 95% CI: 1.077-1.144). RCS analysis revealed a nonlinear association, with lower inflection points and steeper risk curves in females and diabetic individuals, indicating greater sensitivity to TG/HDL-C elevation. In the random forest model, TG/HDL-C ranked second only to age in importance; moreover, the random forest model outperformed logistic regression in predictive accuracy. The visualization tool illustrated higher OA risk among older women and diabetic participants with elevated TG/HDL-C ratios.
CONCLUSION: TG/HDL-C is an independent metabolic predictor of OA, showing nonlinear and subgroup-specific effects. The proposed model and visualization tool may aid early identification and individualized risk stratification.
OBJECTIVE: This study aimed to evaluate the association between TG/HDL-C and OA risk, explore potential nonlinear dose-response relationships and subgroup heterogeneity, and develop an interactive visualization tool for clinical application.
METHODS: A total of 6,570 participants were included in this multicenter cross-sectional study. Multivariable logistic regression, random forest modeling, and restricted cubic spline (RCS) analyses were conducted to assess independent associations, variable importance, and nonlinear trends. Stratified analyses by sex and diabetes status identified subgroup-specific thresholds. An interactive risk visualization tool was created using the R Shiny platform.
RESULTS: Each unit increase in TG/HDL-C was associated with an 11% higher OA risk (OR = 1.11; 95% CI: 1.077-1.144). RCS analysis revealed a nonlinear association, with lower inflection points and steeper risk curves in females and diabetic individuals, indicating greater sensitivity to TG/HDL-C elevation. In the random forest model, TG/HDL-C ranked second only to age in importance; moreover, the random forest model outperformed logistic regression in predictive accuracy. The visualization tool illustrated higher OA risk among older women and diabetic participants with elevated TG/HDL-C ratios.
CONCLUSION: TG/HDL-C is an independent metabolic predictor of OA, showing nonlinear and subgroup-specific effects. The proposed model and visualization tool may aid early identification and individualized risk stratification.