Leveraging network analysis to determine sex differences in factors associated with frailty among older adults living alone

Abstract

BackgroundFrailty is a complex geriatric syndrome typically characterized by multiple underlying etiological factors. We determined the contributing factors, by sex, using a network analysis.MethodsThe study sample consisted of a cross-sectional cohort of community-dwelling older adults aged >= 65 years living alone in a Korean city (N = 1,037). Frailty was assessed via the Korean Frailty Index. Participants were assessed for sociodemographic, health-related, mental and cognitive, and social characteristics. Mixed graphical models including all variables were estimated using the R-package mgm discretely by sex. We also used the Walktrap cluster algorithm to identify differences in the network structure in terms of connectivity around frailty between the sex groups for further insights.ResultsIn both the networks for males and females, frailty correlated most strongly with nutritional status, presence of complex chronic disease, and self-efficacy, and exhibited proximity to decreased sleep quality and loneliness. However, frailty showed an association with suicidal ideation and the number of falls per year only in males, whereas it showed an association with functional disabilities only in females. The overall network connectivity around frailty was stronger with dense interactions (more edges) in the network for females than for males.ConclusionsThe results signify the need for sex-group customized multi-domain assessments and interventions for the prevention and improvement of frailty among community-dwelling older adults.