Objectives: To identify latent rest-activity behavior profiles of objectively measured total sleep time, sleep efficiency, physical activity, and sedentary time in a diverse sample of U.S. women. Methods: 372 women (mean age 55.4 + 10.2) were recruited from studies conducted across four US universities. Participants wore ActiGraph GT3X+ accelerometers on the hip and wrist for a week. Total daily minutes in moderate-to-vigorous physical activity (MVPA) and percentage of wear-time spent sedentary was estimated from the hip device. Total sleep time and sleep efficiency were estimated from the wrist device. Latent profile analyses were performed with these four rest-activity variables, and adjusted ANOVAs were conducted to compare behaviors, demographics, and health conditions across resulting behavior profiles. Results: Participants achieved an average of 21.1 (SD=18.9) minutes of daily MVPA, and 62.1 (SD=8.7) percent of their daily time was spent sedentary. Mean nightly sleep time was 408.9 (SD=55.7) minutes, with an average sleep efficiency of 85.6 (7.5). These rest-activity variables clustered to form five behavior profiles including: 1) fairly active poor sleepers, 2) inactive average sleepers, 3) fairly active average sleepers, 4) active average sleepers, and 5) very active average sleepers & low sitters. Sleep was comparable across four of five behavior profiles (n=345, 92.5%). The behavior profile with the poorest sleep had the lowest proportion of whites (35% vs 78-91%, p < .001) and college graduates (28% vs 68-90%, p = .004). The largest profile (n=151, 40.6%) engaged in 7 min of MVPA per day. BMI and physical functioning varied across behavior profiles. Other health variables did not vary statistically, but trended in hypothesized directions. Conclusions: Daily rest-activity behaviors do cluster in women to form distinct behavior profiles. These identified behavior profiles can inform population targeting or intervention goals of multiple health behavior interventions.

Physical activity and time spent outdoors may be important non-pharmacological approaches to improve sleep quality and duration (or sleep patterns) but there is little empirical research evaluating the two simultaneously. The current study assesses the role of physical activity and time outdoors in predicting sleep health by using objective measurement of the three variables. A convenience sample of 360 adult women (mean age = 55.38 ±9.89 years; mean body mass index = 27.74 ±6.12) was recruited from different regions of the U.S. Participants wore a Global Positioning System device and ActiGraph GT3X+ accelerometers on the hip for 7 days and on the wrist for 7 days and 7 nights to assess total time and time of day spent outdoors, total minutes in moderate-to-vigorous physical activity per day, and 4 measures of sleep health, respectively. A generalized mixed-effects model was used to assess temporal associations between moderate-to-vigorous physical activity, outdoor time, and sleep at the daily level (days = 1931) within individuals. There was a significant interaction (p = 0.04) between moderate-to-vigorous physical activity and time spent outdoors in predicting total sleep time but not for predicting sleep efficiency. Increasing time outdoors in the afternoon (versus morning) predicted lower sleep efficiency, but had no effect on total sleep time. Time spent outdoors and the time of day spent outdoors may be important moderators in assessing the relation between physical activity and sleep. More research is needed in larger populations using experimental designs.