Abstract Introduction: Rest-activity patterns provide an indication of circadian rhythmicity in the free-living setting. We aimed to describe the distributions of rest-activity patterns in a convenience sample of adults and children across demographic variables using parametric and non-parametric analytical methods. Methods: A sample of adults (N=590) and children (N=58) wore an actigraph on their non-dominant wrist for 7 days and nights. Cosinor regression methods were applied to the accelerometer count data to calculate MESOR, acrophase and amplitude. Non-parametric methods were used to calculate the intra-daily stability, inter-daily variability, most active 10 hour period, least active 5 hour period, and relative amplitude. Demographic variables examined included age, sex, race, education, marital status, and household income. Linear mixed effects models were used to test for demographic differences in rest-activity patterns. Results: Adolescents, compared to younger children, had later timing of peak activity (β=1.1 hours 95%CI: 0.4, 1.2 and peak inactivity (β=1.6 hours 95%CI: 0.9, 2.3), lower activity levels during their least and most active periods (β=0.4 ln counts 95%CI: 0.1, 0.6 and β=-709 counts 95%CI: -1003, -416), and less regular rest-activity patterns. Adults (i.e. ages 40 to 49 years), compared to younger adults (ages 18 to 29 years), had earlier timings of peak activity and peak inactivity (β=-1.0 hours 95%CI: -1.6, -0.4 and β=-0.7 hours 95%CI: -1.2, -0.2), and their rest-activity patterns were more regular. Adult females and whites had more stable rest-activity patterns compared to African Americans and adult males. Higher educated adults had a later timing of their peak activities (β= 0.8 hours 95%CI: 0.4, 1.2) and also showed less stable rest-activity patterns. Conclusion: Rest-activity patterns vary across the lifespan, and differ by race, sex and education. Understanding population variation in these patterns provides a foundation for further elucidating the health implications of rest-activity patterns across the lifespan. Support (If Any): This work was supported by NIH grants U01-CA116850, U54-CA155496, U54-CA155626, U54-CA155435 and U54-CA155850 and 1R01-CA164993. JM, CRM, PJ were supported by NIH grants K01-HL123612, 1F31-CA183125 and K99-CA201542, respectively. MQ was supported by a scholarship from the Tuebinger Program for the Advancement of Women in Science.