The identification and prediction of frailty based on Bayesian network analysis in a community-dwelling older population.

ABSTRACT:

Background

We have witnessed frailty, which characterized by a decline in physiological reserves, become a major public health issue in older adults. Understanding the influential factors associated with frailty may help prevent or if possible reverse frailty. The present study aimed to investigate factors associated with frailty status and frailty transition in a community-dwelling older population.

Methods

A prospective cohort study on community-dwelling subjects aged ≥ 60 years was conducted, which was registered beforehand (ChiCTR 2,000,032,949). Participants who had completed two visits during 2020-2021 were included. Frailty status was evaluated using the Fried frailty phenotype. The least absolute shrinkage and selection operator (LASSO) regression was applied for var

SUBMITTER: Yuan Y 

PROVIDER: S-EPMC9652858 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature