  Background. Wearable accelerometry devices allow collection of high-density
activity data in large epidemiological studies both in-the-lab as well as
in-the-wild (free-living). Such data can be used to detect and identify periods
of sustained harmonic walking. This report aims to establish whether the micro-
and macro-features of walking identified in the laboratory and free-living
environments are associated with measures of physical function, mobility,
fatigability, and fitness.
  Methods. Fifty-one older adults (median age 77.5) enrolled in the
Developmental Epidemiologic Cohort Study in Pittsburgh, Pennsylvania were
included in the analyses. The study included an in-the-lab component as well as
7 days of monitoring in-the-wild. Participants were equipped with hip-worn
Actigraph GT3X+ activity monitors, which collect high-density raw accelerometry
data. We applied a walking identification algorithm to the data and defined
features of walking, such as participant-specific walking acceleration and
cadence. The association between these walking features and physical function,
mobility, fatigability, and fitness was quantified using linear regression
analysis.
  Results. Micro-scale features of walking (acceleration and cadence) estimated
from in-the-lab and in-the-wild data were associated with measures of physical
function, mobility, fatigability, and fitness. In-the-lab median walking
acceleration was strongly inversely associated with physical function,
mobility, fatigability and fitness. Additionally, in-the-wild daily walking
time was inversely associated with usual- and fast-paced 400m walking time.
  Conclusions. The proposed accelerometry-derived walking features are
significantly associated with measures of physical function, mobility,
fatigability, and fitness, which provides evidence of convergent validity.

Quantitative Methods