Latent class analysis of intrinsic capacity among rural older adults in China and its influencing factors

Background The decline of intrinsic capacity (IC) is especially pronounced among rural older adults and significantly impacts their health outcomes. However, the heterogeneity of IC profiles in this population and its associations with factors like self-care ability are not well understood. Objective This study aimed to identify latent classes of IC among rural older adults in China and examine their influencing factors. Methods Using convenience sampling method, 607 rural older adults in Guizhou Province were recruited between January to June, 2025. Data were collected through questionnaires including a general information survey, self-care ability scale, frailty assessment tool, and intrinsic capacity evaluation instrument. Latent class analysis was performed to identify patterns of intrinsic capacity, followed by multivariate logistic regression to determine influencing factors. Results The intrinsic capacity of rural older adults was classified into three latent classes: “Physically Weak and Lacking Vitality Group” (38.71%), “Balanced and Stable Group” (22.41%), and “Cognitive-Motor Impairment Group” (38.88%). Multivariate logistic regression analysis revealed that living alone, low monthly household income, advanced age, frailty status, self-care ability, current work participation, rural residence, and multiple medication use were significant influencing factors for the latent classes of intrinsic capacity ( p < 0.05). Conclusion The deterioration of intrinsic capacity among rural older adult populations exhibits distinct categorical patterns. Healthcare providers should implement tailored and individualized nursing interventions based on these differential influencing factors to enhance the intrinsic capacity levels of rural older adults.