Abstract
Osteoarthritis (OA) is a prevalent chronic joint disease, metabolic abnormalities may play a key role in its development and progression. The metabolic score for insulin resistance (METS-IR) is an emerging index used to assess insulin resistance and metabolic dysfunction, but its relationship with OA remains unclear. This study utilized the National Health and Nutrition Examination Survey 2011 to 2018 database, including 6079 participants aged ≥20 years, to investigate the association between METS-IR and OA. OA was defined based on self-reported physician diagnoses. METS-IR was calculated using fasting glucose, triglycerides, HDL cholesterol, and body mass index (BMI). Multivariate logistic regression was employed to analyze the relationship between METS-IR and OA, while receiver operating characteristic (ROC) curves were used to evaluate the predictive efficacy of METS-IR for OA risk. Nonlinear associations were explored through smoothed curve fitting, and subgroup analyses were performed to assess potential interactions. Elevated METS-IR levels were significantly associated with an increased risk of OA. After adjusting for potential confounders, METS-IR was independently associated with OA (odds ratio (OR) = 1.026, 95% confidence interval (CI) = 1.020-1.033, P <.0001). Quartile analysis revealed that individuals in the highest METS-IR quartile had a significantly higher risk of OA compared to those in the lowest quartile (OR = 2.068, 95% CI = 1.617-2.644, P <.0001). Nonlinear analysis indicated a threshold effect, with METS-IR levels exceeding 42.153 significantly increasing OA risk (OR = 1.031, 95% CI = 1.022-1.040, P <.0001). ROC analysis showed that METS-IR had moderate predictive ability, with an AUC of 0.829 after full adjustment. Elevated METS-IR levels are significantly associated with increased OA risk, with a nonlinear relationship identified. METS-IR may serve as a potential predictor for OA, providing new insights into the "metabolic phenotype" hypothesis of OA and offering a basis for early screening and intervention. However, due to the cross-sectional design and reliance on self-reported OA diagnosis, causality cannot be established, and further longitudinal studies are warranted.