Daniel Eduardo da Cunha Leme1, Erika Valeska da Costa Alves2, André Fattori2. 1. Graduate Program in Gerontology, School of Medical Sciences, UNICAMP, Campinas, São Paulo, Brazil. Electronic address: daniel.eduardo.7@hotmail.com. 2. Graduate Program in Gerontology, School of Medical Sciences, UNICAMP, Campinas, São Paulo, Brazil.
Abstract
OBJECTIVE: Frailty is a multifactorial syndrome characterized by social, physical, and psychological stressors. Network analysis is a graphical statistical technique that can contribute to the understanding of this complex, multifactorial phenomenon. The aim of this study was to investigate the relationships between social, physical, and psychological factors and frailty in older persons. DESIGN: A cross-sectional study. SETTINGS AND PARTICIPANTS: A total of 2588 community-dwelling older persons from the FIBRA (Frailty in Brazilian Older Persons) 2008 to 2009 study. MEASURES: Participants were assessed for sociodemographic variables, physical and mental health, and the frailty phenotype. Partial correlation network analysis with the Graphical Least Absolute Shrinkage and Selection Operator (glasso) estimator was performed to determine the relationships between social, physical, and psychological factors and frailty. RESULTS: Mean participant age was 72.31 years, 7.0% were frail, and 50.6% were prefrail. In the network structure, frailty correlated most strongly with physical and psychological factors such as diabetes and depression and exhibited greater proximity to physical factors such as disability, urinary incontinence, and cardiovascular risk as measured by waist-to-hip ratio. CONCLUSIONS AND IMPLICATIONS: The analytical strategy used can provide information for specific subpopulations of interest and here confirmed that frailty is not uniformly determined but associated with different psychological and physical health factors, thereby allowing better understanding and management of this condition.
OBJECTIVE: Frailty is a multifactorial syndrome characterized by social, physical, and psychological stressors. Network analysis is a graphical statistical technique that can contribute to the understanding of this complex, multifactorial phenomenon. The aim of this study was to investigate the relationships between social, physical, and psychological factors and frailty in older persons. DESIGN: A cross-sectional study. SETTINGS AND PARTICIPANTS: A total of 2588 community-dwelling older persons from the FIBRA (Frailty in Brazilian Older Persons) 2008 to 2009 study. MEASURES: Participants were assessed for sociodemographic variables, physical and mental health, and the frailty phenotype. Partial correlation network analysis with the Graphical Least Absolute Shrinkage and Selection Operator (glasso) estimator was performed to determine the relationships between social, physical, and psychological factors and frailty. RESULTS: Mean participant age was 72.31 years, 7.0% were frail, and 50.6% were prefrail. In the network structure, frailty correlated most strongly with physical and psychological factors such as diabetes and depression and exhibited greater proximity to physical factors such as disability, urinary incontinence, and cardiovascular risk as measured by waist-to-hip ratio. CONCLUSIONS AND IMPLICATIONS: The analytical strategy used can provide information for specific subpopulations of interest and here confirmed that frailty is not uniformly determined but associated with different psychological and physical health factors, thereby allowing better understanding and management of this condition.