Literature DB >> 28578137

A pilot study of physical activity and sedentary behavior distribution patterns in older women.

Emma Fortune1, Benjamin Mundell2, Shreyasee Amin3, Kenton Kaufman4.   

Abstract

The study aims were to investigate free-living physical activity and sedentary behavior distribution patterns in a group of older women, and assess the cross-sectional associations with body mass index (BMI). Eleven older women (mean (SD) age: 77 (9) yrs) wore custom-built activity monitors, each containing a tri-axial accelerometer (±16g, 100Hz), on the waist and ankle for lab-based walking trials and 4 days in free-living. Daily active time, step counts, cadence, and sedentary break number were estimated from acceleration data. The sedentary bout length distribution and sedentary time accumulation pattern, using the Gini index, were investigated. Associations of the parameters' total daily values and coefficients of variation (CVs) of their hourly values with BMI were assessed using linear regression. The algorithm demonstrated median sensitivity, positive predictive value, and agreement values >98% and <1% mean error in cadence calculations with video identification during lab trials. Participants' sedentary bouts were found to be power law distributed with 56% of their sedentary time occurring in 20min bouts or longer. Meaningful associations were detectable in the relationships of total active time, step count, sedentary break number and their CVs with BMI. Active time and step counts had moderate negative associations with BMI while sedentary break number had a strong negative association. Active time, step count and sedentary break number CVs also had strong positive associations with BMI. The results highlight the importance of measuring sedentary behavior and suggest a more even distribution of physical activity throughout the day is associated with lower BMI.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Accelerometer; Body mass index; Metabolic syndrome; Older adults; Wearable sensors

Mesh:

Year:  2017        PMID: 28578137      PMCID: PMC5865394          DOI: 10.1016/j.gaitpost.2017.05.014

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


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