Abstract
OBJECTIVES: Chronic systemic inflammation is increasingly recognized as a key contributor to the development of osteoporosis. This investigation seeks to assess how effectively several inflammation-derived composite indices can diagnose osteoporosis in the elderly population. METHODS: A multicenter cross-sectional study was conducted across four hospitals in China from January 2023 to May 2025, enrolling 3,625 participants aged ≥60 years. Associations between inflammatory markers and osteoporosis were examined with multivariable logistic regression, and potential nonlinear patterns were further investigated using restricted cubic spline (RCS) models. Diagnostic accuracy was assessed through receiver operating characteristic (ROC) curves and decision curve analysis (DCA). RESULTS: Elevated values of several inflammation-related indices were associated with a higher likelihood of osteoporosis in multivariable analyses. RCS analysis demonstrated a nonlinear dose-response pattern (p for nonlinearity <0.001). These findings were consistent across stratified and sensitivity analyses. Among all indices evaluated, the aggregate index of systemic inflammation (AISI) exhibited the strongest association with osteoporosis (OR = 1.63; 95% CI: 1.49-1.78). CONCLUSION: This multicenter study demonstrates that elevated inflammatory indices are independently associated with osteoporosis, with AISI emerged as the superior marker, offering a novel, cost-effective tool for early identification of osteoporosis in clinical practice.