Non-linear associations between blood glucose, blood lipids and inflammatory markers and new-onset arthritis in the middle-aged and older population

Objective: The arthritis burden increases with aging, while blood glucose, lipid profiles and inflammatory markers may affect the development of arthritis. This study aims to determine the associations between blood markers and rheumatoid arthritis (RA) and osteoarthritis (OA) for better arthritis management. Method: Data from the 6th and 9th wave of the Survey of Health, Ageing, and Retirement in Europe (SHARE) were used. Logistic regression and Cox proportional hazards regression models were used to examine the associations between blood markers and arthritis. Generalized additive models and restricted cubic splines (RCS) were employed to assess non-linear associations. Results: This study included a total of 14,276 participants. The incidence was 5.80% for OA, and 13.92% for RA. The participants with new-onset OA and RA were more likely to be older, female, and with higher body mass index. The generalized additive model detected nonlinear associations between the incidence of OA and glycated hemoglobin A (HbA1c), and between the incidence of RA and high-density lipoprotein (HDL) and triglycerides (TRG). RCS curves (P-nonlinear < 0.05) showed an increased risk of new-onset OA for HbA1c levels between 4.75% and 5.91% in individuals aged ≤ 65. For those aged>65, HDL levels between 44.99 and 67.42 mg/dL and TRG levels between 265.37 and 1125.06 mg/dL were associated with an increased risks of new-onset RA. Furthermore, total cholesterol, HbA1c, HDL and TRG were associated with the prevalence of arthritis. Conclusion: Monitoring lipid profiles and HbA1c levels in middle-aged and older adults may help to manage arthritis.