Identifying Heterogeneity in Older Adults’ Community Care demand: A Latent Class Analysis with Implications for the Dual-Factor Model of Mental Health

Background A consequence of population aging acceleration and traditional family care decline is the increasing diversity in care services. Community care is a feasible solution for promoting active aging in developing countries. However, the current care services passively rely on standardized supply and fail to accommodate the diverse demands among older adults. Methods This cross-sectional study collected data from 857 individuals aged 60–95 years across 12 communities in an urban–rural integrated city in eastern China, using a multi-stage stratified sampling. Data was collected between July 2024 to August 2024, analyzed from October 2024 to December 2024.Conducting a Latent Class Analysis (LCA), we systematically examined and categorized the demand characteristics for care of older adults. We employed linear regression and Dual-Factor Model of Mental Health (DFM) to assess the mental health of older adults, as well as to grasp the mental health variations across latent classes. Results Based on the LCA findings, the participants were categorized into five latent classes based on their demand for care. Participants in the Comprehensive Demand group exhibited low levels of psychological distress and high social well-being compared to their counterparts. On the contrary, the Low Demand group reported high psychological distress and low social well-being. Furthermore, the mental health of classes appeared unaffected by demographic characteristics, community and care utilization. Conclusions The study provides a novel perspective on understanding the diverse care demands of Chinese adults using the people-centered approach. Given the demographic structure of the study sample, the findings may apply to other areas with comparable urban-rural population ratios. Developing the diverse demands of older adults, as well as tailoring precise and extensive service offerings to meet the varied demands, is essential.