Multivariate glm regression model constructed.

The number of arthritis samples in China has been increasing. Currently, there is limited research on the relationship between agricultural activities and arthritis. This study aimed to investigate the correlation between agricultural activities and arthritis risk based on the China Health and Retirement Longitudinal Study (CHARLS). A total of 694 participants from the 2015 CHARLS study were included, with 443 samples as controls and 251 samples classified as affected. Baseline characteristics of all participants were compared using the Student t-test and Chi-square test. Subsequently, the association between agricultural activities and arthritis risk was explored through multivariable generalized linear models (GLM) and weighted logistic regression models. Additionally, the diagnostic performance and clinical utility of agricultural activities for arthritis were evaluated using receiver operating characteristic (ROC) curves and decision curve analysis. Finally, the difference in model prediction performance before and after adjusting for covariates was assessed using the net reclassification index (NRI) and integrated discrimination improvement (IDI). Five covariates showed significant associations with arthritis, and agricultural activities had a significant effect (P = 0.026). Furthermore, a significant positive correlation was observed between agricultural activities and arthritis (Model 1: odds ratio (OR)=1.44, 95% confidence interval (95%CI): 1.06–1.97, P = 0.021; Model 2: OR=1.61, 95%CI: 1.17–2.24, P = 0.004; Model 3: OR=1.74, 95%CI: 1.17–2.60, P = 0.007). Risk stratification analysis further indicated that agricultural activities were a risk factor for arthritis (OR=1.736, 95%CI: 1.168–2.597, P