Nonlinear Association Between the C-Reactive Protein-Triglyceride-Glucose Index and Rheumatoid Arthritis Risk: The
Haiping Xie1, Qinwen Liu2, Xuefeng Xu3
1Department of Rheumatology and Immunology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou 350001, China.
Background:
Rheumatoid arthritis (RA) is a growing public health concern with rising incidence worldwide. The C-reactive protein-triglyceride-glucose index (CTI), a composite marker of inflammation and insulin resistance, has been linked to various metabolic disorders, but its role in RA remains unclear. This study aimed to examine the association between CTI and RA risk and assess whether body mass index (BMI) mediates this relationship.
Methods:
We analyzed data from 4292 participants using the 2005-2010 National Health and Nutrition Examination Survey (NHANES). CTI was computed and stratified into quartiles. Multivariable logistic regression models assessed the association between CTI and RA after adjusting for demographic, socioeconomic, lifestyle, and clinical confounders. Restricted cubic spline (RCS) functions were employed to test for nonlinear patterns. Additionally, subgroup analyses examined effect modification, and mediation analysis quantified the indirect effect through BMI.
Results:
Elevated CTI values were independently linked to higher odds of RA. After full adjustment, each one-unit rise in CTI corresponded to a 45% increase in RA odds (OR = 1.45, 95% CI: 1.22-1.73, p < 0.001). The RCS analysis demonstrated a significant nonlinear association (p for nonlinearity = 0.048). Stratified analyses indicated consistent patterns across sex, ethnicity, and other variables, with a more pronounced effect among individuals without diabetes (p for interaction = 0.036). Mediation findings showed that BMI accounted for 32.31% of the total CTI-RA effect (p < 0.001).
Conclusions:
CTI is nonlinearly and independently associated with RA risk, partly through BMI, highlighting its potential as a biomarker linking metabolic and inflammatory pathways.
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