Background: Insulin resistance (IR) and arthritis are strongly associated, and the triglyceride-glucose (TyG) index combinations with obesity indicators [including TyG-BMI (glucose triglyceride-body mass index), TyG-WC (glucose triglyceride-waist circumference), and TyG-WHtR (glucose triglyceride-waist height ratio)] has recently been recognized as a more effective indicator for assessing IR. However, there is a lack of research on its association with arthritis, and it is also important to assess in different populations.

Methods: The analysis utilized data from the China Health and Retirement Longitudinal Study (CHARLS) and the National Health and Nutrition Examination Survey (NHANES). Arthritis diagnosis relied on self-reporting confirmed by physicians. The association of TyG-BMI, TyG-WC, and TyG-WHtR with arthritis was analyzed through weighted logistic regression models, and exploring nonlinear effects with restricted cubic spline (RCS) models. Secondary and sensitivity analyses included receiver operating characteristic curve (ROC) analysis, comparisons of z score-related odds ratios, subgroup analyses, and multiple imputation.

Results: The study involved 6141 CHARLS participants and 17,091 NHANES participants. Adjusting for confounding variables, TyG-BMI and TyG-WHtR demonstrate a positive correlation with arthritis prevalence in both CHARLS (TyG-BMI: OR = 1.02, 95% CI 1.00-1.04; TyG-WHtR: OR = 1.13, 95% CI 1.03-1.24) and NHANES (TyG-BMI: OR = 1.07, 95% CI 1.06-1.08; TyG-WHtR: OR = 1.50, 95% CI 1.40-1.60). RCS regression analysis demonstrated a significant nonlinear association. ROC analysis indicated that TyG-BMI and TyG-WHtR were superior to TyG for the diagnosis of arthritis in both CHARLS and NHANES.

Conclusions: TyG-BMI and TyG-WHtR demonstrate a positive correlation with arthritis prevalence in both Chinese and the U.S. populations, displaying superior diagnostic relevance compared to TyG.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11282701PMC
http://dx.doi.org/10.1186/s40001-024-01992-4DOI Listing

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