Purpose/Significance To classify the elderly according to their heterogeneous health status, and to explore the potential categories and influencing factors status, so as to promote the precision of health information services for the elderly. Method/Process Based on the data of the China health and retirement longitudinal study (CHARLS) database in 2018, the elderly are classified according to their health status by the method of latent class analysis, and the main influencing factors are identified by regression analysis. Result/Conclusion The elderly could be divided into 4 categories according to their health status. Age, sex, education level and retirement status are significant factors affecting the health grouping of the elderly. According to the heterogeneous health characteristics of the elderly, the service optimization strategy should be provided to promote the physical and mental health of the elderly.