Preferred Name
Almothana Matarneh
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
ORCID
https://orcid.org/0009-0005-7452-6309
Date of Graduation
8-15-2025
Semester of Graduation
Summer
Degree Name
Master of Science (MS)
Department
Department of Kinesiology
First Advisor
Trent Hargens
Abstract
THE ASSOCIATION OF WALKING CADENCE WITH SLEEP QUALITY IN ADULTS 18 – 65
Almothana Matarneh, Emma Morrow, Trent A. Hargens FACSM, FCEPA
ABSTRACT
Sleep quality is essential to physical and mental health, influencing physiological functions including muscle recovery, hormonal balance, immune response, and cognition. Poor sleep may impact physical activity (PA) and sedentary behavior (SB), potentially contributing to reduced overall well-being. Walking cadence, the number of steps per minute, is an accessible proxy for PA intensity, but its relationship with sleep quality remains unclear. Objective: This study examined the relationship between PA, SB, and sleep quality, as measured by step cadence, among adults aged 18–65 years. Methods: participants wore an ActiGraph GT3X accelerometer on the hip during waking hours and on the non‑dominant wrist during sleep for 7 consecutive days. Sleep logs were documented in‑bed and out-of-bed times. Sleep efficiency (SE) was classified as “normal” (sleep efficiency ≥ 85%) or “poor” (sleep efficiency < 85%). Results: Participants classified as having normal SE accumulated more daily steps (8,975 ± 2,901 vs 6,518 ± 2,657; p < .001), spent less time at zero cadence (p < .05), and accumulated more time in low- (1–19 steps/min) and moderate-intensity (20–39 steps/min) cadence ranges (p < .05) compared to those with poor SE. Time at zero cadence was negatively associated with SE, while time in the 1–39 steps/min range was positively associated with sleep quality. Conclusions: Findings suggest that low-to-moderate cadence stepping is positively associated with sleep efficiency. Cadence-based metrics may offer an accessible tool for identifying movement patterns linked to better sleep quality and may inform public health strategies aimed at improving sleep through achievable activity targets.
