Department of Social Medicine, CAPHRI School for Public Health and Primary Care, Maastricht University, Maastricht, The Netherlands.
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Comparison of Sedentary Estimates between activPAL and Hip- and Wrist-Worn ActiGraph.
- Published on Aug 2016
Purpose: Sedentary behavior is an emerging independent health risk factor. The accuracy of measuring sedentary time using accelerometers may depend on the wear location. This study in older adults evaluated the accuracy of various hip- and wrist-worn ActiGraph accelerometer cutoff points to define sedentary time using the activPAL as the reference method.
Methods: Data from 62 adults (mean age, 78.4 yr) of the Aging Research Evaluating Accelerometry study were used. Participants simultaneously wore an activPAL accelerometer on the thigh and ActiGraph accelerometers on the hip, dominant, and nondominant wrist for 7 d in a free-living environment. Using the activPAL as the reference criteria, we compared classification of sedentary time to hip-worn and wrist-worn ActiGraph accelerometers over a range of cutoff points for both 60-s and 15-s epochs.
Results: The optimal cutoff point for the hip vertical axis was <22 counts per minute with an area under the curve (AUC) of 0.85; the optimal hip vector magnitude cutoff point was <174 counts per minute with an AUC of 0.89. For the dominant wrist, the optimal vector magnitude cutoff point to define sedentary time was <2303 counts per minute (AUC, 0.86) and for the nondominant wrist <1853 counts per minute (AUC, 0.86). The optimal 15-s cutoff points resulted in lower agreements compared with activPAL.
Conclusions: Hip- and wrist-worn ActiGraph data may be used to define sedentary time with a moderate to high accuracy when compared with activPAL. The observed optimal cutoff point for hip vertical axis <22 counts per minute is substantially lower than the standard <100 counts per minute. It is unknown how these optimal cutoff points perform in different populations. Results on an individual basis should therefore be interpreted with caution.
- Koster A 1
- Shiroma EJ 2
- Caserotti P 3
- Metthews CE 4
- Chen KY 5
- Glynn NW 6
Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Bethesda, MD.
Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Denmark.
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD.
National Institute of Diabetes and Digestive and Kidney Diseases, Diabetes, Endocrinology, and Obesity Branch, Bethesda, MD.
University of Pittsburgh, Graduate School of Public Health, Center for Aging and Population Health, Pittsburgh, PA.
Medicine & Science in Sports & Exercise