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Large-scale assessment of physical activity in a population using high-resolution hip-worn accelerometry: the German National Cohort (NAKO).

Authors :
Weber A
van Hees VT
Stein MJ
Gastell S
Steindorf K
Herbolsheimer F
Ostrzinski S
Pischon T
Brandes M
Krist L
Marschollek M
Greiser KH
Nimptsch K
Brandes B
Jochem C
Sedlmeier AM
Berger K
Brenner H
Buck C
Castell S
Dörr M
Emmel C
Fischer B
Flexeder C
Harth V
Hebestreit A
Heise JK
Holleczek B
Keil T
Koch-Gallenkamp L
Lieb W
Meinke-Franze C
Michels KB
Mikolajczyk R
Kluttig A
Obi N
Peters A
Schmidt B
Schipf S
Schulze MB
Teismann H
Waniek S
Willich SN
Leitzmann MF
Baurecht H
Source :
Scientific reports [Sci Rep] 2024 Apr 04; Vol. 14 (1), pp. 7927. Date of Electronic Publication: 2024 Apr 04.
Publication Year :
2024

Abstract

Large population-based cohort studies utilizing device-based measures of physical activity are crucial to close important research gaps regarding the potential protective effects of physical activity on chronic diseases. The present study details the quality control processes and the derivation of physical activity metrics from 100 Hz accelerometer data collected in the German National Cohort (NAKO). During the 2014 to 2019 baseline assessment, a subsample of NAKO participants wore a triaxial ActiGraph accelerometer on their right hip for seven consecutive days. Auto-calibration, signal feature calculations including Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD), identification of non-wear time, and imputation, were conducted using the R package GGIR version 2.10-3. A total of 73,334 participants contributed data for accelerometry analysis, of whom 63,236 provided valid data. The average ENMO was 11.7 ± 3.7 mg (milli gravitational acceleration) and the average MAD was 19.9 ± 6.1 mg. Notably, acceleration summary metrics were higher in men than women and diminished with increasing age. Work generated in the present study will facilitate harmonized analysis, reproducibility, and utilization of NAKO accelerometry data. The NAKO accelerometry dataset represents a valuable asset for physical activity research and will be accessible through a specified application process.<br /> (© 2024. The Author(s).)

Details

Language :
English
ISSN :
2045-2322
Volume :
14
Issue :
1
Database :
MEDLINE
Journal :
Scientific reports
Publication Type :
Academic Journal
Accession number :
38575636
Full Text :
https://doi.org/10.1038/s41598-024-58461-5