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Correlates of change in accelerometer-assessed total sedentary time and prolonged sedentary bouts among older English adults: results from five-year follow-up in the EPIC-Norfolk cohort

Background: Development of effective strategies to reduce sedentary time among older adults necessitates understanding of its determinants but longitudinal studies of this utilising objective measures are scarce. Methods: Among 1536 older adults (≥60 years) in the EPIC-Norfolk study, sedentary time...

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Detalles Bibliográficos
Autores principales: Yerrakalva, Dharani, Hajna, Samantha, Wijndaele, Katrien, Westgate, Kate, Khaw, Kay-Tee, Wareham, Nick, Griffin, Simon J, Brage, Soren
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7835006/
https://www.ncbi.nlm.nih.gov/pubmed/33431710
http://dx.doi.org/10.18632/aging.202497
Descripción
Sumario:Background: Development of effective strategies to reduce sedentary time among older adults necessitates understanding of its determinants but longitudinal studies of this utilising objective measures are scarce. Methods: Among 1536 older adults (≥60 years) in the EPIC-Norfolk study, sedentary time was assessed for seven days at two time-points using accelerometers. We assessed associations of change in total and prolonged bouts of sedentary time (≥ 30 minutes) with change in demographic and behavioural factors using multi-level regression. Results: Over follow-up (5.3±1.9 years), greater increases in total sedentary time were associated with older age, being male, higher rate of increase in BMI, lower rate of increase in gardening (0.5 min/day/yr greater sedentary time per hour/week/yr less gardening, 95% CI 0.1, 1.0), a lower rate of increase in walking (0.2 min/day/yr greater sedentary time per hour/week/yr less walking, 95% CI 0.1, 0.3) and a higher rate of increase in television viewing. Correlates of change in prolonged sedentary bouts were similar. Conclusion: Individuals in specific sub-groups (older, male, higher BMI) and who differentially participate in certain behaviours (less gardening, less walking and more television viewing) but not others increase their sedentary time at a higher rate than others; utilising this information could inform successful intervention content and targeting.