The objective of this study is to examine the temporal and bidirectional relationships between accelerometer-derived physical activity estimates and actigraphy-assessed sleep characteristics among older women.
A subgroup of participants (N = 143, mean age = 73 yr) enrolled in the Healthy Women Study wore an ActiGraph accelerometer on their waist and an Actiwatch sleep monitor on their wrist concurrently for seven consecutive days. Multilevel models examined whether ActiGraph-assessed daily activity counts (ct·min−1·d−1) and moderate- to vigorous-intensity physical activity (MVPA; min·d−1) predicted Actiwatch-assessed sleep onset latency, total sleep time, sleep efficiency, and sleep fragmentation. Similar models were used to determine whether nighttime sleep characteristics predicted physical activity the following day.
In unadjusted models, greater daily activity counts (B = −0.05, P = 0.005) and more minutes of MVPA (B = −0.03, P = 0.01) were temporally associated with less total sleep time across the week. Greater sleep efficiency was associated with greater daily activity counts (B = 0.37, P = 0.01) and more minutes of MVPA (B = 0.64, P = 0.009) the following day. Less sleep fragmentation was also associated with greater daily activity counts and more MVPA the following day. Findings were similar after adjustment for age, education, body mass index, depressive symptoms, arthritis, and accelerometer wear time.
Few studies have used objective measures to examine the temporal relationships between physical activity and sleep. Notably, these findings suggest that nightly variations in sleep efficiency influence physical activity the following day. Thus, improving overall sleep quality in addition to reducing nightly fluctuations in sleep may be important for encouraging a physically active lifestyle in older women.
1Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA; 2Division of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Austin, TX; and 3Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA
Address for correspondence: Maya J. Lambiase, Ph.D., Department of Psychiatry, University of Pittsburgh, 3811 O’Hara Street, Pittsburgh, PA 14215; E-mail: firstname.lastname@example.org.
Submitted for publication March 2013.
Accepted for publication May 2013.