Background: High sedentary time is associated with adverse metabolic health outcomes and mortality in older adults. It has been suggested that breaking up sedentary time may be beneficial for metabolic health; however, population prevalence data are lacking on the patterns of sedentary behaviour which would identify opportunities for intervention. Methods: We used data of adults aged ≥ 60 years (n = 3705) from the population-based EPIC-Norfolk cohort, to characterize the patterns of total sedentary time, breaks in sedentary time and sedentary bouts across the day and assess their associations with participant characteristics, using multi-level regression. Sedentary time was measured objectively by a hip-mounted accelerometer (ActigraphTM GT1M) worn for 7 days during waking time. Results: More than 50% of every waking hour was spent sedentary, increasing to a peak of 83% in the evening. On average fewer breaks were accrued in the evenings compared with earlier in the day. Marginally more sedentary time was accrued on weekend days compared with weekdays (difference 7.4 min, 95% confidence interval 5.0-9.7). Large proportions of this sedentary time appear to be accrued in short bouts (bouts of < 10 min for 32% of the time). Older age, being male, being retired, not being in paid employment and having a higher body mass index were associated with greater sedentary time and fewer breaks. Conclusion: Sedentary time is common throughout the day but peaks in the evenings with fewer breaks and longer bouts. We identified a number of characteristics associated with sedentary time and additionally inversely associated with sedentary breaks, which should inform the development and targeting of strategies to reduce sedentary time among older adults.
Background: High sedentary time is associated with adverse metabolic health outcomes and mortality in older adults. It has been suggested that breaking up sedentary time may be beneficial for metabolic health; however, population prevalence data are lacking on the patterns of sedentary behaviour which would identify opportunities for intervention. Methods: We used data of adults aged ≥ 60 years (n = 3705) from the population-based EPIC-Norfolk cohort, to characterize the patterns of total sedentary time, breaks in sedentary time and sedentary bouts across the day and assess their associations with participant characteristics, using multi-level regression. Sedentary time was measured objectively by a hip-mounted accelerometer (ActigraphTM GT1M) worn for 7 days during waking time. Results: More than 50% of every waking hour was spent sedentary, increasing to a peak of 83% in the evening. On average fewer breaks were accrued in the evenings compared with earlier in the day. Marginally more sedentary time was accrued on weekend days compared with weekdays (difference 7.4 min, 95% confidence interval 5.0-9.7). Large proportions of this sedentary time appear to be accrued in short bouts (bouts of < 10 min for 32% of the time). Older age, being male, being retired, not being in paid employment and having a higher body mass index were associated with greater sedentary time and fewer breaks. Conclusion: Sedentary time is common throughout the day but peaks in the evenings with fewer breaks and longer bouts. We identified a number of characteristics associated with sedentary time and additionally inversely associated with sedentary breaks, which should inform the development and targeting of strategies to reduce sedentary time among older adults.
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