Abstract
BACKGROUND: Rheumatoid arthritis (RA) is a chronic inflammatory joint disease with increasing mortality worldwide. Traditional obesity indicators inadequately predict the mortality risk in this population. Thus, the research aimed to evaluate new obesity indicators to explore their close association with RA mortality. METHODS: This study analyzed 101,316 National Health and Nutrition Examination Survey participants (1999-2018) to evaluate alternative adiposity indices for RA mortality prediction. Missing data were imputed using the random forest method. Key covariates were selected using the Boruta algorithm and weighted univariate Cox regression. Multivariable-adjusted models generated hazard ratios (95% confidence interval), validated by time-dependent receiver operating characteristic curves and Harrell's C-index. Survival patterns were assessed with restricted cubic splines (RCS) and Kaplan-Meier curves. Threshold effects and robustness were analyzed via segmented Cox models and sensitivity analyses. Extreme gradient boosting (XGBoost) identified A Body Shape Index (ABSI) as the strongest predictor. RESULTS: Among the 1,266 individuals, 299 deaths occurred during follow-up (190 all-cause, 59 cardiovascular, 50 cancer). ABSI predicted the 5-, 10-, and 20-year mortality (area under the curve: 0.823, 0.801, 0.752, respectively) and outperformed other indices in the Harrell's C-index. Weighted multivariable Cox regression linked higher ABSI × 100 values with increased mortality; Kaplan-Meier curves confirmed reduced survival in the highest quartile (P < 0.001). RCS revealed a U-curve association linking ABSI × 100 to mortality. Moreover, the mediating effects analysis indicated the Monocyte-to-High-Density Lipoprotein Cholesterol Ratio, Neutrophil-to-Lymphocyte Ratio, Advanced Lung Cancer Inflammation Index, and Systemic Immune-Inflammation Index played significant roles as mediators, with mediation ratios of 4.9%, 5.1%, 8.5%, and 4.5%, respectively. Additional sensitivity analyses validated these results. Quartile stratification revealed a pronounced risk amplification in the highest quartile (Q4), particularly in the fully adjusted specification (Hazard ratio = 3.43, 1.45-8.14; P = 0.005). Furthermore, XGBoost results indicate that ABSI is the best obesity metric for predicting the prognosis of patients with RA. CONCLUSIONS: This study revealed a potential clinical value of a new obesity index, specifically the ABSI, in predicting the survival rates among individuals with RA. Inflammatory markers appear to play a partial mediating role in this relationship.