Heterogeneity of frailty and psychosocial factors among community-dwelling older adults in Shijiazhuang city of China: A cross-sectional study based on conservation of resources theory

Background Frailty, as a common geriatric health syndrome, has attracted extensive attention due to its association with multiple adverse health outcomes. However, the heterogeneity of frailty and its related psychosocial factors among community-dwelling older adults requires additional exploration. Objective To identify the latent classes of frailty among community-dwelling older adults and explore the associations between resource loss/gain factors and these frailty profiles based on the Conservation of Resources (COR) theory. Methods From May to October 2024, we recruited 480 community-dwelling older adults in Shijiazhuang City (one of provincial cities of China), using multistage stratified sampling. Frailty was assessed using the Tilburg Frailty Indicator (TFI). Anxiety, depression, loneliness, and social support were evaluated using the Generalized Anxiety Disorder-7 (GAD-7), the 15-item Geriatric Depression Scale (GDS-15), the ULS-6 Loneliness Scale, and the Social Support Rating Scale (SSRS), respectively. Latent Profile Analysis (LPA) was used to identify frailty profiles, and Generalized Structural Equation Models (GSEM) were constructed to examine the associations between resource loss/gain factors and these frailty profiles. Results We included 479 valid responses (response rate, 99.79%). LPA identified three latent frailty profiles. The "high physical-social frailty" profile (13.15%) comprised mostly women, unmarried individuals, and those living alone; this group exhibited low social support and high depression and loneliness. The "moderate-stable frailty" profile (59.71%) is the largest group, comprising mostly married individuals with the highest social support and relatively stable overall function. The "low psychological-social frailty" profile (27.14%) comprised mostly men with better economic status, social support, and psychological well-being. GSEM revealed significantly different associations between resource factors and frailty classes. The "high physical-social frailty" profile was positively associated with resource loss factors ( β =0.246, P <0.001) and negatively associated with resource gain factors ( β =-0.404, P <0.001). The "moderate-stable frailty" profile was positively associated only with resource gain factors ( β =0.605, P <0.001). Social support did not significantly moderate the association between resource loss factors and frailty profiles ( P >0.05). These findings support the "independent dual-pathway model of resource loss and gain." Conclusion Frailty among community-dwelling older adults is heterogeneous, and different frailty profiles exhibit distinct associations with resource loss and resource gain factors. Community health management strategies should be tailored to specific frailty profiles, focusing on enhancing resource gains and reducing resource losses to improve health outcomes and quality of life among older adults.