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Cross-Sectional Comparison of Physical Activity, Sedentary Behavior, and Sleep in Shift and Nonshift Workers Using
Matthew J Fenwick1, Stina Oftedal, Tracy Kolbe-Alexander
1From the School of Medicine & Public Health, College of Health, Medicine, and Wellbeing (M.J.F., M.J.D.), and Centre for Active Living and Learning (M.J.F., M.J.D.), University of Newcastle, Callaghan; and Active Living Research Program, Hunter Medical Research Institute, New Lambton Heights (M.J.F., M.J.D.), New South Wales; and Queensland Cerebral Palsy and Rehabilitation Research Centre, Child Health Research Centre, The University of Queensland, South Brisbane (S.O.); and School of Health and Medical Sciences, and Centre for Health Research, University of Southern Queensland (T.K.-A.), Queensland, Australia; Centre for Health through Physical Activity, Lifestyle and Sport (HPALS), Division of Research Unit for Exercise Science and Sports Medicine, University of Cape Town, South Africa (T.K.-A.); and Alliance for Research in Exercise Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia (D.D.).
Objective:
Investigate differences in device-measured physical activity, sedentary behavior, and sleep between shift and nonshift workers, focusing on variations during work and leisure periods.
Methods:
Full-time employed adult participants from Newcastle, Australia, wore thigh and wrist accelerometers for 14 days to assess activity and sleep. Activity was classified into sedentary, standing, light-intensity physical activity, and moderate to vigorous physical activity. Linear mixed models and compositional data analysis were used to assess behavioral time allocation.
Results:
Forty-nine participants (shift = 33, nonshift = 16) completed the study. During work periods, shift workers were less sedentary (-79.40 minutes, P = 0.031) and engaged more in light-intensity physical activity (+39.95 minutes, P = 0.044), but were more sedentary during leisure (+93.59 minutes, P = 0.019).
Conclusions:
Distinct differences during work and leisure highlight the need for domain-specific analysis.
