Association Rule Analysis of Cognitive Frailty Subtypes in Community-Dwelling Older Adults

In order to provide a foundation for identification and intervention strategies, this study intends to investigate the influencing factors and associative patterns of two subtypes of reversible cognitive frailty (RCF) and potential reversible cognitive frailty (PRCF) in older adults with cognitive frailty (CF) who live in the community.

From July to December 2023, we conducted a cross-sectional study in a Beijing community to recruit older adults with CF using convenience sampling. We conducted the survey using the General Information Questionnaire, the Montreal Cognitive Assessment, the Clinical Dementia Rating, the Fried Frailty Phenotype, the Geriatric Depression Scale-15, the Generalized Anxiety Disorder-7, the Athens Insomnia Scale, the Barthel index, the Tinetti Performance Oriented Mobility Assessment, and the Lubben social network scale. The participants were separated into two categories: RCF and PRCF, based on frailty and cognitive assessment. After screening variables with a random forest algorithm, we applied association rule analysis to examine the factors influencing CF and the strength of their interactions.

The survey was completed by 529 older adults with CF who lived in the community. Among them, 145 participants (27.4%) were classified as PRCF and 384 (72.6%) as RCF. 24 association rules, 12 for each subtype, were developed using the Apriori algorithm and clinical practice experience. These rules identified polypharmacy, multimorbidity, low educational attainment, and high fall risk as significant factors. Furthermore, the association pattern for PRCF is more complex.

The influencing factors associative patterns of the two categories of CF differ. In order to better manage elderly individuals with CF in the community, improve the cognitive health of the elderly, and encourage healthy aging, medical professionals should upgrade the community evaluation system for CF.