Principal Component Analysis to Examine Fall-predictive Screening Tests for use during Locomotive Health Checkups

Abstract

Objectives: The purpose of this study was to determine which components of screening tests are important for assessing locomotive dysfunction during locomotive health checkups and best predict falls in a prospective cohort study.

Methods: Four hundred and sixty-eight residents were assessed for locomotive syndrome, frailty, knee and back pain, bone mass, muscle mass, grip strength, gait speed, gait variability, and kyphosis at a baseline locomotive health checkup. Residents were followed up after 1 year and surveyed about their incidence of falls.

Results: A total of 379 residents were analyzed in the study. Principal component analysis was used to divide components using all screening tests for locomotive dysfunction. The primary variable making up the first principal component was “mobility function,” the second was “muscle function,” and the third was related to “spinal alignment.” The tests that showed the highest principal component loadings in each component were the five-question Geriatric Locomotive Function Scale, muscle mass index, and kyphosis index. Binary regression analyses, adjusted for age and past fall history, showed that the five-question Geriatric Locomotive Function Scale was independently related with the incidence of falling (odds ratio=2.04; 95% confidence interval: 1.04–3.99).

Conclusions: We propose that during a locomotive health checkup, mobility function, muscle function, and spinal alignment are important components for the assessment of locomotive dysfunction. Notably, the five-question Geriatric Locomotive Function Scale is a simple and convenient screening test that can predict the future incidence falls.