Literature DB >> 27878845

Evaluation of raw acceleration sedentary thresholds in children and adults.

Maria Hildebrand1, Bjørge H Hansen1, Vincent T van Hees2, Ulf Ekelund1.   

Abstract

The aim was to develop sedentary (sitting/lying) thresholds from hip and wrist worn raw tri-axial acceleration data from the ActiGraph and GENEActiv, and to examine the agreement between free-living time spent below these thresholds with sedentary time estimated by the activPAL. Sixty children and adults wore an ActiGraph and GENEActiv on the hip and wrist while performing six structured activities, before wearing the monitors, in addition to an activPAL, for 24 h. Receiver operating characteristic (ROC) curves were used to determine sedentary thresholds based on activities in the laboratory. Agreement between developed sedentary thresholds during free-living and activPAL were assessed by Bland-Altman plots and by calculating sensitivity and specificity. Using laboratory data and ROC-curves showed similar classification accuracy for wrist and hip thresholds (Area under the curve = 0.84-0.92). Greatest sensitivity (97-98%) and specificity (74-78%) were observed for the wrist thresholds, with no large differences between brands. During free-living, Bland-Altman plots showed large mean individual biases and 95% limits of agreement compared with activPAL, with smallest difference for the ActiGraph wrist threshold in children (+30 min, P = 0.3). Sensitivity and specificity for the developed thresholds during free-living were low for both age groups and for wrist (Sensitivity, 68-88%, Specificity, 46-59%) and hip placements (Sensitivity, 89-97%, Specificity, 26-34%). Laboratory derived sedentary thresholds generally overestimate free-living sedentary time compared with activPAL. Wrist thresholds appear to perform better than hip thresholds for estimating free-living sedentary time in children and adults relative to activPAL, however, specificity for all the developed thresholds are low.
© 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  zzm321990ENMOzzm321990; Measurement; accelerometer; raw data; sedentary time

Mesh:

Year:  2016        PMID: 27878845     DOI: 10.1111/sms.12795

Source DB:  PubMed          Journal:  Scand J Med Sci Sports        ISSN: 0905-7188            Impact factor:   4.221


  62 in total

1.  Association between sociodemographic, dietary, and substance use factors and accelerometer-measured 24-hour movement behaviours in Brazilian adolescents.

Authors:  Bruno Gonçalves Galdino da Costa; Jean-Philippe Chaput; Marcus Vinicius Veber Lopes; Anelise Reis Gaya; Diego Augusto Santos Silva; Kelly Samara Silva
Journal:  Eur J Pediatr       Date:  2021-05-15       Impact factor: 3.183

2.  Estimated Physical Activity in Adolescents by Wrist-Worn GENEActiv Accelerometers.

Authors:  Sarah G Sanders; Elizabeth Yakes Jimenez; Natalie H Cole; Alena Kuhlemeier; Grace L McCauley; M Lee Van Horn; Alberta S Kong
Journal:  J Phys Act Health       Date:  2019-07-17

3.  Inpatient care utilisation and expenditure associated with objective physical activity: econometric analysis of the UK Biobank.

Authors:  Leonie Heron; Mark A Tully; Frank Kee; Ciaran O'Neill
Journal:  Eur J Health Econ       Date:  2022-06-24

4.  A randomized controlled trial of a community-based obesity intervention utilizing motivational interviewing and community resource mobilization for low-income families: Study protocol and baseline characteristics.

Authors:  Jessica Andino; Jennifer Park-Mroch; Shelby L Francis; Amy M J O'Shea; Bery Engebretsen; Sarai Rice; Helena H Laroche
Journal:  Contemp Clin Trials       Date:  2021-11-18       Impact factor: 2.226

5.  Leading by Example: Association Between Mother and Child Objectively Measured Physical Activity and Sedentary Behavior.

Authors:  Brad R Julius; Amy M J O'Shea; Shelby L Francis; Kathleen F Janz; Helena Laroche
Journal:  Pediatr Exerc Sci       Date:  2021-04-05       Impact factor: 2.333

6.  The Validity of MotionSense HRV in Estimating Sedentary Behavior and Physical Activity under Free-Living and Simulated Activity Settings.

Authors:  Sunku Kwon; Neng Wan; Ryan D Burns; Timothy A Brusseau; Youngwon Kim; Santosh Kumar; Emre Ertin; David W Wetter; Cho Y Lam; Ming Wen; Wonwoo Byun
Journal:  Sensors (Basel)       Date:  2021-02-18       Impact factor: 3.576

Review 7.  Assessment of Physical Activity in Adults Using Wrist Accelerometers.

Authors:  Fangyu Liu; Amal A Wanigatunga; Jennifer A Schrack
Journal:  Epidemiol Rev       Date:  2022-01-14       Impact factor: 4.280

8.  Reliability of GENEActiv accelerometers to estimate sleep, physical activity, and sedentary time in children.

Authors:  Devan Antczak; Chris Lonsdale; Borja Del Pozo Cruz; Philip Parker; Taren Sanders
Journal:  Int J Behav Nutr Phys Act       Date:  2021-06-06       Impact factor: 6.457

9.  Association of daily composition of physical activity and sedentary behaviour with incidence of cardiovascular disease in older adults.

Authors:  Manasa S Yerramalla; Duncan E McGregor; Vincent T van Hees; Aurore Fayosse; Aline Dugravot; Adam G Tabak; Mathilde Chen; Sebastien F M Chastin; Séverine Sabia
Journal:  Int J Behav Nutr Phys Act       Date:  2021-07-12       Impact factor: 6.457

10.  Objective and subjective measurement of sedentary behavior in human adults: A toolkit.

Authors:  Justin Aunger; Janelle Wagnild
Journal:  Am J Hum Biol       Date:  2020-12-05       Impact factor: 2.947

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