Abstract Introduction This analysis used data from the Assessing Daily Activity Patterns Through Occupational Transitions (ADAPT) study to compare differences in employment status on activity variability, as an indicator of circadian fragmentation and stability. Circadian fragmentation refers to frequency of alterations between rest and activity relative to the daily rhythm and stability refers to day-to-day similarity. High fragmentation and low stability have been linked to a number of negative health outcomes including depression, obesity, and heightened mortality risk. Methods The sample consisted of 155 participants that included 702 total cases (n = 434 employed, n = 268 unemployed) assessed over 18 months. Participants were required to have involuntarily lost their jobs in the last 90 days. Employment status was determined for all participants at each visit based on demographic surveys. Daily activity patterns were assessed via actigraphy (Actiwatch-Spectrum) at 30 second epochs for 14 days. The nonparametric measures of intradaily variability (IV) and interdaily stability (IS) were used as measures of circadian fragmentation and stability. Several subsampling intervals were considered for IV, ranging from 5 minutes to 4 hours. Results Unemployment was associated with higher IV (for 1 hour subsampling intervals, t=5.23, p < .001) and lower IS than employment (t=2.38, p <.05). The same is true with changes in the subsampling interval for IV, with highest significance at 45 minutes to 1.5 hours. Significant findings remained even for 5 minute (t=2.15, p < .05) and 4 hour (t = 4.07, p<.001) intervals. Conclusion In a sample of adults with variable employment status, employment was associated with less circadian fragmentation and more stability than unemployment. These findings suggest that circadian fragmentation and instability may be two mechanisms by which job loss increases negative health risk. Future planned studies examining prospective changes in circadian fragmentation/stability during employment transitions will help answer this question. Support (if any) NIH #1R01HL117995-01A1, NSF DMS 1937229, NSF CCF 1740858