Development of a personalized fall rate prediction model in community-dwelling older adults: a negative binomial regression modelling approach.

ABSTRACT:

Background

Around a third of adults aged 65 and older fall every year, resulting in unintentional injuries in 30% of the cases. Fractures are a frequent consequence of falls, primarily caused in individuals with decreased bone strength who are unable to cushion their falls. Accordingly, an individual's number of experienced falls has a direct influence on fracture risk. The aim of this study was the development of a statistical model to predict future fall rates using personalized risk predictors.

Methods

In the prospective cohort GERICO, several fall risk factor variables were collected in community-dwelling older adults at two time-points four years apart (T1 and T2). Participants were asked how many falls they experienced during 12 months prior to the examinations. Rate r

SUBMITTER: Wapp C 

PROVIDER: S-EPMC10064572 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature