2026/01/01 by Erin E. Dooley, J F Winkles, J.F. Winkles +12
Medicine · Psychology · #Dietary Effects on Health #Physical Activity and Health #Sleep and related disorders
paper · doi:10.1123/japa.2025-0082
openalex publication_date 2026/01/01 · openalex created_date 2026/01/23 · openalex updated_date 2026/06/11
BACKGROUND: The 24-hr movement cycle is associated with health, but less is known about factors associated with differences in cycle composition. METHODS: Data from 1,297 Study of Women's Health Across the Nation participants (ages 60-72 years; Mage = 65.4 ± 2.6 years) who concurrently wore hip (waking) and wrist (sleep) accelerometers at Visit 15 (2015-2017) to quantify differences in sleep, sedentary, and physical activity across sociodemographic and health factors are used, including age, race and ethnicity, educational attainment, body mass index, financial strain, self-rated health, body pain, vasomotor symptoms, depression symptoms, anxiety, obstructive sleep apnea, and multimorbidity. We used compositional data analysis to characterize movement cycles and multivariate analysis of variance to examine the difference in the proportion of the day spent in cycle components by subgroup, controlling for Study of Women's Health Across the Nation site, age, race and ethnicity, and body mass index. RESULTS: On average, women spent 34.6% (8.3 hr) in sleep and 31.4% (7.5 hr), 30.5% (7.3 hr), and 3.5% (50 min) in sedentary, light-intensity, or moderate- or vigorous-intensity physical activities (MVPA), respectively. Black and Hispanic women; smokers; and those who reported moderate/severe financial strain, moderate/severe bodily pain, poor health, or living with multimorbidity spent 19%-34% less time in MVPA relative to the overall mean composition. Women with depression and anxiety symptoms spent 10%-19% less time in MVPA relative to the mean composition. CONCLUSION: Variations in compositions were driven by differences in the proportion of time spent in MVPA. Significance/Implications: Identifying persons with inadequate movement profiles could help inform targeted strategies for intervention and policies.