Measuring Physical Activity in Free-Living Conditions-Comparison of Three Accelerometry-Based Methods

被引:52
|
作者
Leinonen, Anna-Maiju [1 ,2 ,3 ]
Ahola, Riikka [1 ,4 ,5 ]
Kulmala, Janne [6 ]
Hakonen, Harto [6 ]
Vaha-Ypya, Henri [7 ]
Herzig, Karl-Heinz [4 ,5 ,8 ,9 ,10 ]
Auvinen, Juha [4 ,5 ,11 ]
Keinanen-Kiukaanniemi, Sirkka [4 ,5 ,11 ]
Sievanen, Harri
Tammelin, Tuija H. [6 ]
Korpelainen, Raija [3 ,4 ,5 ,11 ]
Jamsa, Timo [1 ,2 ,4 ,5 ,12 ]
机构
[1] Univ Oulu, Res Unit Med Imaging Phys & Technol, Oulu, Finland
[2] Univ Oulu, Infotech Oulu, Oulu, Finland
[3] Oulu Deaconess Inst, Dept Sports & Exercise Med, Oulu, Finland
[4] Oulu Univ Hosp, Med Res Ctr, Oulu, Finland
[5] Univ Oulu, Oulu, Finland
[6] LIKES Res Ctr Sport & Hlth Sci, Jyvaskyla, Finland
[7] UKK Inst Hlth Promot Res, Tampere, Finland
[8] Univ Oulu, Res Unit Biomed, Oulu, Finland
[9] Poznan Univ Med Sci, Dept Gastroenterol & Metab, Poznan, Poland
[10] Univ Oulu, Bioctr Oulu, Oulu, Finland
[11] Univ Oulu, Ctr Life Course Hlth Res, Oulu, Finland
[12] Oulu Univ Hosp, Diagnost Radiol, Oulu, Finland
来源
FRONTIERS IN PHYSIOLOGY | 2017年 / 7卷
关键词
accelerometer; agreement; middle-aged; objective measurement; sedentary time; CUT-POINTS; SEDENTARY BEHAVIOR; RAW ACCELERATION; UNITED-STATES; TIME SPENT; WRIST; HIP; COMPARABILITY; INTENSITY; MORTALITY;
D O I
10.3389/fphys.2016.00681
中图分类号
Q4 [生理学];
学科分类号
071003 ;
摘要
We examined the agreement in time spent on different physical activity (PA) levels using (1) mean amplitude deviation (MAD) of raw acceleration from the hip, (2) wrist-worn Polar Active, and (3) hip-worn Actigraph counts using Freedson's cut-points among adults under free-living conditions. PA was measured in 41 volunteers (mean age 47.6 years) for 14 days. Two MET-based threshold sets were used for MAD and Polar Active for sedentary time (ST) and time spent in light (LPA), moderate (MPA), and vigorous (VPA) PA. Actigraph counts were divided into PA classes, =100 counts/min for ST and Freedson's cut-points for LPA, MPA, and VPA. Analysis criteria were simultaneous use of devices for at least 4 days of >500 min/d. The between-method differences were analyzed using a repeated measures analysis of variance test. Bland-Altman plots and ROC graphs were also employed. Valid data were available from 27 participants. Polar Active produced the highest amount of VPA with both thresholds (=5 and =6 MET; mean difference 17.9-30.9 min/d, P < 0.001). With the threshold 3-6 MET for MPA, Polar Active indicated 19.2 min/d more than MAD (95% CI 5.8-32.6) and 51.0 min/d more than Actigraph (95% CI 36.7-65.2). The results did not differ with 3.5-5 MET for MPA [F(1.44, 37.43) = 1.92, P = 0.170]. MAD and Actigraph were closest to each other for ST with the threshold <1.5 MET (mean difference 22.2 min/d, 95% CI 7.1-37.3). With the threshold < 2 MET, Polar Active and Actigraph provided similar results (mean difference 7.0 min/d, 95% CI -17.8-31.7). Moderate to high agreement (area under the ROC curve 0.8060.963) was found between the methods for the fulfillment of the recommendation for daily moderate-to-vigorous PA of 60 min. In free-living conditions the agreement between MAD, Polar Active, and Actigraph for measuring time spent on different activity levels in adults was dependent on the activity thresholds used and PA intensity. ROC analyses showed moderate to high agreement for the fulfillment of the recommendation for daily MVPA. Without additional statistical adjustment, these methods cannot be used interchangeably when measuring daily PA, but any of the methods can be used to identify persons with insufficient daily amount of MVPA.
引用
收藏
页数:9
相关论文
共 50 条
  • [21] Physical Activity Classification for Elderly People in Free-Living Conditions
    Awais, Muhammad
    Chiari, Lorenzo
    Ihlen, Espen Alexander F.
    Helbostad, Jorunn L.
    Palmerini, Luca
    IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2019, 23 (01) : 197 - 207
  • [22] Assessment of physical activity under free-living conditions in children
    Caputo, JL
    Farley, RS
    Tseh, W
    MEDICINE AND SCIENCE IN SPORTS AND EXERCISE, 2004, 36 (05): : S329 - S329
  • [23] Comparison of Different Physical Activity Measurement Methods in Adults Aged 45 to 64 Years Under Free-Living Conditions
    Lipert, Anna
    Jegier, Anna
    CLINICAL JOURNAL OF SPORT MEDICINE, 2017, 27 (04): : 400 - 408
  • [24] A Review of Accelerometry-Based Wearable Motion Detectors for Physical Activity Monitoring
    Yang, Che-Chang
    Hsu, Yeh-Liang
    SENSORS, 2010, 10 (08) : 7772 - 7788
  • [25] An Accelerometry-Based Approach to Assess Loading Intensity of Physical Activity on Bone
    Kelley, Sarah
    Hopkinson, Georgina
    Strike, Siobhan
    Luo, Jin
    Lee, Raymond
    RESEARCH QUARTERLY FOR EXERCISE AND SPORT, 2014, 85 (02) : 245 - 250
  • [26] Comparison of pedometer and accelerometer measures of free-living physical activity
    Tudor-Locke, C
    Ainsworth, BE
    Thompson, RW
    Matthews, CE
    MEDICINE AND SCIENCE IN SPORTS AND EXERCISE, 2002, 34 (12): : 2045 - 2051
  • [27] Triaxial Accelerometry-Based Moderate to Vigorous Physical Activity in Older Adults Using Four Different Methods
    Hall, Anna
    Hillebrant-Openshaw, Madisen
    Baca-Zeff, Sierra
    van Woerden, Irene
    JOURNAL OF AGING AND PHYSICAL ACTIVITY, 2022, 30 (03) : 473 - 481
  • [28] Validation of the RT3 accelerometer for measuring physical activity of children in simulated free-living conditions
    Sun, David Xiaoqian
    Schmidt, Gordon
    Teo-Koh, Sock Miang
    PEDIATRIC EXERCISE SCIENCE, 2008, 20 (02) : 181 - 197
  • [29] Free-living physical activity in pregnancy
    Landsberger, E
    Zhang, K
    Boozer, C
    OBESITY RESEARCH, 2005, 13 : A56 - A57
  • [30] GPS-Based Exposure to Greenness and Walkability and Accelerometry-Based Physical Activity
    James, Peter
    Hart, Jaime E.
    Hipp, J. Aaron
    Mitchell, Jonathan A.
    Kerr, Jacqueline
    Hurvitz, Philip M.
    Glanz, Karen
    Laden, Francine
    CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION, 2017, 26 (04) : 525 - 532