Abstract P422: Accelerometer-Determined Sedentary Time and Physical Activity Across Employment Status Categories in CARDIA

Abstract

Prolonged sedentary behavior and insufficient physical activity is a common activity profile, especially in modern workplaces. Describing activity profiles by employment status groups could identify target populations for sedentary and activity intervention. Methods: This cross-sectional analysis of Year 20 CARDIA data (2005-6), included participants who had valid accelerometry data (≥4 days with ≥10 hours), reported occupational status, and were not currently a student (n=2,068). Uniaxial accelerometry data (ActiGraph 7164) were expressed in 60 second epochs and summarized as: average counts per minute (cpm) and time spent (min/day) in prolonged sedentary behavior (≥30 continuous minutes, SED ≥30 ), less than 30-minute bouts of sedentary behavior of (SED <30 ), light physical activity (LPA), less than 10-minute bouts of moderate-to-vigorous physical activity of (MVPA <10 ), and bouted MVPA (≥10 minutes, MVPA ≥10 ) using Freedson cutpoints. Employment status was self-reported as full-time, part-time, unemployed/looking for work, keeping house, or raising children. Omnibus group differences were analyzed using ANCOVA adjusted for sex, race, age, education, wear time, center, and BMI. Least square means of activity time across groups were calculated and standardized to population average wear time (14.8 hours). Results: Figure 1 shows activity profiles of employment groups rank ordered by cpm. Cpm and most types of activity differed modestly but significantly across employment groups, except for MVPA ≥10 . Unemployed participants had the highest cpm, the most MVPA ≥10 and SED ≥30 , but the least SED <30 . Participants working part-time had the most MVPA <10 . Full-time workers had the least LPA. Those raising children had the least SED ≥30 and MVPA ≥10 , but the most LPA. Participants keeping house had the least cpm and MVPA <10 . Conclusions: Public health intervention programing could consider differences in activity profiles across employment status groups.