TY - JOUR
T1 - A pilot study of physical activity and sedentary behavior distribution patterns in older women
AU - Fortune, Emma
AU - Mundell, Benjamin
AU - Amin, Shreyasee
AU - Kaufman, Kenton
N1 - Funding Information:
Funding was provided by DOD DM090896 and NIH R01 AR027065. The body-worn motion detection and recording units were provided by Dr. Barry Gilbert, James Bublitz, Kevin Buchs, Charles Burfield, Christopher Felton, Dr. Clifton Haider, Michael Lorsung, Shaun Schreiber, Steven Schuster, and Daniel Schwab from the Mayo Clinic Special Purpose Processor Development Group. The information or content and conclusions do not necessarily represent the official position of, nor should any official endorsement be inferred by the National Institutes of Health, the United States Navy, the Department of Defense, or the U.S. Government.
Publisher Copyright:
© 2017 Elsevier B.V.
PY - 2017/9
Y1 - 2017/9
N2 - 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 (±16 g, 100 Hz), 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 20 min 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.
AB - 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 (±16 g, 100 Hz), 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 20 min 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.
KW - Accelerometer
KW - Body mass index
KW - Metabolic syndrome
KW - Older adults
KW - Wearable sensors
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U2 - 10.1016/j.gaitpost.2017.05.014
DO - 10.1016/j.gaitpost.2017.05.014
M3 - Article
C2 - 28578137
AN - SCOPUS:85019999095
SN - 0966-6362
VL - 57
SP - 74
EP - 79
JO - Gait and Posture
JF - Gait and Posture
ER -