Restricted access

Purchase article

USD $24.95

Student 1 year subscription

USD $37.00

1 year subscription

USD $50.00

Student 2 year subscription

USD $71.00

2 year subscription

USD $93.00

The purpose of this study was to conduct a comprehensive evaluation of the ActiGraph GT3X+ (AG) and activPAL (AP) for assessing time spent in sedentary behaviors (SB) in youth using structured and free-living activities. Forty-four participants (M age, 12.7±0.8 yrs) completed up to eight structured activities and approximately 2 hrs of free-living activity while wearing an AG (right hip) and AP (right thigh). A Cosmed K4b2 was used for measured energy expenditure (METy; activity VO2 ÷ resting VO2). Direct observation was used during the structured activities. SB time was estimated using the inclinometer function of the AP and AG, and count thresholds with AG (<75 vector magnitude [VM] counts/10-s; <25 vertical axis [VA] counts/10-s; and <50, 100, 150, and 200 VA counts/min). For the structured activities, the AG inclinometer and AP correctly classified supine rest about 45% of the time, seated activities 54.6% and 65.1% of the time, respectively, and walking and running >96% of the time. For the free-living measurement, the VA <25 counts/10-s had the lowest RMSE (20.6 min), while the VM <75 counts/10-s had the lowest MAPE (69.2%). The AG inclinometer was within 0.2 minutes of measured time, but had the highest MAPE (107.1%). The AP was within 1.6 minutes of measured time, but had the highest RMSE (28.5 minutes). Compared to measured SB time, the VA <25 counts/10-s and VM <75 counts/10-s provided the most precise estimates of SB during free-living activity. Further refinement is needed to improve the AP and AG posture estimates.

Crouter, Hibbing, and LaMunion are with the Dept. of Kinesiology, Recreation, and Sport Studies, College of Education, Health, and Human Sciences, The University of Tennessee, Knoxville, TN.

Crouter (scrouter@utk.edu) is corresponding author.
Journal for the Measurement of Physical Behaviour
Article Sections
References
  • ActiGraph Corp. (2016). How Does the ActiGraph Device Determine Inclination (for Waist Wear Locations)? Retrieved from https://actigraph.desk.com/customer/en/portal/articles/2515819-how-does-the-actigraph-device-determine-inclination-for-waist-wear-locations

    • Export Citation
  • AminianS. & HincksonE.A. (2012). Examining the validity of the ActivPAL monitor in measuring posture and ambulatory movement in children. International Journal of Behavioral Nutrition and Physical Activity 9119. PubMed ID: 23031188 doi:10.1186/1479-5868-9-119

    • Crossref
    • Search Google Scholar
    • Export Citation
  • AtkinA.J.GorelyT.ClemesS.A.YatesT.EdwardsonC.BrageS.BiddleS.J. (2012). Methods of Measurement in epidemiology: Sedentary Behaviour. International Journal of Epidemiology 41(5) 14601471. PubMed ID: 23045206 doi:10.1093/ije/dys118

    • Crossref
    • Search Google Scholar
    • Export Citation
  • BassettD.R.Jr.JohnD.CongerS.A.RiderB.C.PassmoreR.M. & ClarkJ.M. (2014). Detection of lying down, sitting, standing, and stepping using two activPAL monitors. Medicine & Science in Sports & Exercise 46(10) 20252029. PubMed ID: 24598698 doi:10.1249/MSS.0000000000000326

    • Crossref
    • Search Google Scholar
    • Export Citation
  • ChowdhuryA.K.TjondronegoroD.ChandranV. & TrostS.G. (2017). Ensemble Methods for Classification of Physical Activities from Wrist Accelerometry. Medicine & Science in Sports & Exercise 49(9) 19651973. doi:10.1249/MSS.0000000000001291

    • Crossref
    • Search Google Scholar
    • Export Citation
  • CrouterS.E.FlynnJ.I. & BassettD.R.Jr. (2015). Estimating physical activity in youth using a wrist accelerometer. Medicine & Science in Sports & Exercise 47(5) 944951. doi:10.1249/MSS.0000000000000502

    • Crossref
    • Search Google Scholar
    • Export Citation
  • CrouterS.E.HortonM. & BassettD.R.Jr. (2012). Use of a two-regression model for estimating energy expenditure in children. Medicine & Science in Sports & Exercise 44(6) 11771185. PubMed ID: 22143114 doi:10.1249/MSS.0b013e3182447825

    • Crossref
    • Search Google Scholar
    • Export Citation
  • CrouterS.E.HortonM. & BassettD.R.Jr. (2013). Validity of actigraph child-specific equations during various physical activities. Medicine & Science in Sports & Exercise 45(7) 14031409. doi:10.1249/MSS.0b013e318285f03b

    • Crossref
    • Search Google Scholar
    • Export Citation
  • DaviesG.ReillyJ.J.McGowanA.J.DallP.M.GranatM.H. & PatonJ.Y. (2012). Validity, practical utility, and reliability of the activPAL in preschool children. Medicine & Science in Sports & Exercise 44(4) 761768. doi:10.1249/MSS.0b013e31823b1dc7

    • Crossref
    • Search Google Scholar
    • Export Citation
  • DowdK.P.HarringtonD.M. & DonnellyA.E. (2012). Criterion and concurrent validity of the activPAL professional physical activity monitor in adolescent females. PLoS ONE 7(10) 47633. PubMed ID: 23094069 doi:10.1371/journal.pone.0047633

    • Crossref
    • Search Google Scholar
    • Export Citation
  • FischerC.YildirimM.SalmonJ. & ChinapawM.J. (2012). Comparing different accelerometer cut-points for sedentary time in children. Pediatric Exercise Science 24(2) 220228. PubMed ID: 22728414 doi:10.1123/pes.24.2.220

    • Crossref
    • Search Google Scholar
    • Export Citation
  • FreedsonP.PoberD. & JanzK.F. (2005). Calibration of accelerometer output for children. Medicine & Science in Sports & Exercise 37(Suppl. 11) S523530. doi:10.1249/01.mss.0000185658.28284.ba

    • Crossref
    • Search Google Scholar
    • Export Citation
  • GibbsB.B.HergenroederA.L.KatzmarzykP.T.LeeI.M. & JakicicJ.M. (2015). Definition, measurement, and health risks associated with sedentary behavior. Medicine & Science in Sports & Exercise 47(6) 12951300. doi:10.1249/MSS.0000000000000517

    • Crossref
    • Search Google Scholar
    • Export Citation
  • HänggiJ.M.PhillipsL.R. & RowlandsA.V. (2013). Validation of the GT3X ActiGraph in children and comparison with the GT1M ActiGraph. Journal of Science and Medicine in Sport 16(1) 4044. doi:10.1016/j.jsams.2012.05.012

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kozey-KeadleS.LibertineA.LydenK.StaudenmayerJ. & FreedsonP. (2011). Validation of wearable monitors for assessing sedentary behavior. Medicine & Science in Sports & Exercise 43(8) 15611567. doi:10.1249/MSS.0b013e31820ce174

    • Crossref
    • Search Google Scholar
    • Export Citation
  • MatthewsC.E.ChenK.Y.FreedsonP.S.BuchowskiM.S.BeechB.M.PateR.R. & TroianoR.P. (2008). Amount of time spent in sedentary behaviors in the United States, 2003-2004. American Journal of Epidemiology 167(7) 875881. PubMed ID: 18303006 doi:10.1093/aje/kwm390

    • Crossref
    • Search Google Scholar
    • Export Citation
  • PaveyT.G.GilsonN.D.GomersallS.R.ClarkB. & TrostS.G. (2017). Field evaluation of a random forest activity classifier for wrist-worn accelerometer data. Journal of Science and Medicine in Sport 20(1) 7580. PubMed ID: 27372275 doi:10.1016/j.jsams.2016.06.003

    • Crossref
    • Search Google Scholar
    • Export Citation
  • RidgersN.D.SalmonJ.RidleyK.O’ConnellE.ArundellL. & TimperioA. (2012). Agreement between activPAL and ActiGraph for assessing children’s sedentary time. International Journal of Behavioral Nutrition and Physical Activity 915. PubMed ID: 22340137 doi:10.1186/1479-5868-9-15

    • Crossref
    • Search Google Scholar
    • Export Citation
  • RidleyK.RidgersN.D. & SalmonJ. (2016). Criterion validity of the activPAL and ActiGraph for assessing children’s sitting and standing time in a school classroom setting. International Journal of Behavioral Nutrition and Physical Activity 1375. PubMed ID: 27387031 doi:10.1186/s12966-016-0402-x

    • Crossref
    • Search Google Scholar
    • Export Citation
  • TremblayM.S.AubertS.BarnesJ.D.SaundersT.J.CarsonV.Latimer-CheungA.E.SBRN Terminology Consensus Project Participants. (2017). Sedentary Behavior Research Network (SBRN) - Terminology Consensus Project process and outcome. International Journal of Behavioral Nutrition and Physical Activity 14(1) 75. PubMed ID: 28599680 doi:10.1186/s12966-017-0525-8

    • Crossref
    • Search Google Scholar
    • Export Citation
  • TreuthM.S.SchmitzK.CatellierD.J.McMurrayR.G.MurrayD.M.AlmeidaM.J.PateR. (2004). Defining accelerometer thresholds for activity intensities in adolescent girls. Medicine & Science in Sports & Exercise 36(7) 12591266.

    • Search Google Scholar
    • Export Citation
  • TrostS.G.ZhengY. & WongW.K. (2014). Machine learning for activity recognition: Hip versus wrist data. Physiological Measurement 35(11) 21832189. PubMed ID: 25340887 doi:10.1088/0967-3334/35/11/2183

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Van CauwenbergheE.WoollerL.MackayL.CardonG. & OliverM. (2012). Comparison of Actical and activPAL measures of sedentary behaviour in preschool children. Journal of Science and Medicine in Sport 15(6) 526531. PubMed ID: 22658858 doi:10.1016/j.jsams.2012.03.014

    • Crossref
    • Search Google Scholar
    • Export Citation
Article Metrics
All Time Past Year Past 30 Days
Abstract Views 31 31 9
Full Text Views 1 1 0
PDF Downloads 1 1 0
Altmetric Badge
PubMed
Google Scholar