Identifying and describing segments of office workers by activity patterns: Associations with demographic characteristics and objectively measured physical activity

Published

Journal Article

© 2018 Emerald Publishing Limited. Purpose - The purpose of this paper is to identify and characterize patterns of physical activity among office workers employed in largely sedentary occupations at a major health insurer located in the Southeastern USA. Design/methodology/approach - The authors used latent class analysis to identify segments of office workers (n=239) based on their self-reported activities of daily living and exercise behaviors. The authors examined the association of demographic characteristics with segment membership, and differences in accelerometer-measured weekly minutes of light and moderate-vigorous physical activity across segments. Findings - The authors identified two segments and labeled them "exerciser" and "non-exerciser." Being female was associated with lower odds of membership in the "exerciser" segment (OR=0.18; 95% CI=0.06, 0.52), while those with at least a bachelor's degree were more likely to be in the "exerciser" segment (OR=2.12; 95% CI=1.02, 4.40). Mean minutes of moderate-vigorous physical activity per week were greater for the "exerciser" segment than the "non-exerciser" segment. Practical implications - Based on this sample, the authors found that office workers in sedentary occupations were roughly equally divided and distinguished by their engagement in exercise-type behaviors. The findings underscore the need for innovative workplace programming that enhances activity opportunities particularly for those that are not likely to exercise. Originality/value - A scarcity of research on activity patterns among office workers inhibits development of targeted worksite activity programming. The present research reveals two segments of workers with regard to their activity patterns and suggests ways for worksites to meet their unique needs.

Full Text

Duke Authors

Cited Authors

  • Close, MA; Lytle, LA; Viera, AJ; Chen, DG; Linnan, LA; Valle, CG

Published Date

  • January 1, 2018

Published In

Volume / Issue

  • 11 / 1

Start / End Page

  • 16 - 30

Electronic International Standard Serial Number (EISSN)

  • 1753-836X

International Standard Serial Number (ISSN)

  • 1753-8351

Digital Object Identifier (DOI)

  • 10.1108/IJWHM-07-2017-0053

Citation Source

  • Scopus