Growth curve models to detect walking impairment: The case of InCHIANTI study

Abstract

This work is motivated by a study on aging based on a representative population living in the Chianti geographic area (Tuscany, Italy). Multiple factors may influence the ability to walk, and no standard criteria are currently available to establish whether these factors are functioning within the “normal” range. Our work exploits data collected during the performance of an indoor mobility test to discriminate individuals at high risk of mobility disability and/or falls. A large number of outcomes were collected during the test. We explore the application of growth curve models to detect walking impairment. The model is extended to include non-ignorable missing data. Our findings suggest that subjects aggregate into distinct behavioral profiles, characterized by age and other demographic and anthropometric factors.