Step-Count Distribution as an Indicator of Walking Reserve in People with Gait Vulnerabilities

Abstract

Background

Steps per day can provide a lot of information about the activity of the average person whose main source of activity is derived from walking. This study looks at the distribution of step count data to identify different subgroups of people which could be used to indicate walking reserve.

Methods

A time series design of a secondary data analysis was conducted to track the variability of daily step count for 44 seniors post-fracture. The mean age was 75.8 years (SD: 9.75). The full percentile distribution was used in a cluster analysis and group-based trajectory analysis was used for the longitudinal data. Ordinal regression was used to identify factors associated with cluster membership.

Results

Four clusters best represented the distribution of reserve in this sample, hypothesized to be defined as the difference between the median and 90th percentile of the step-count distribution. Cluster 1, with the lowest reserve would also be classified as sedentary based on median step count (1,555 step count; 1,314 reserve). Cluster 2 represented people with limited activity with low reserve (4,081 step count; 2,439 reserve). Cluster 3 represented active people with high reserve (7,197 step count; 4,370 reserve). Cluster 4, was very active with very high reserve (9,202 step count, 6,964 reserve).The factors associated with cluster membership were gait speed, sit-to-stand, and depression.

Conclusions

The median and 90th percentile over a longer period indicates the potential “reserve” for participating in activities that demand additional walking.