Literature DB >> 31002287

Day-level sedentary pattern estimates derived from hip-worn accelerometer cut-points in 8-12-year-olds: Do they reflect postural transitions?

Jordan A Carlson1, John Bellettiere2,3, Jacqueline Kerr2, Jo Salmon4, Anna Timperio4, Simone J J M Verswijveren4, Nicola D Ridgers4.   

Abstract

Improving sedentary measurement is critical to understanding sedentary-health associations in youth. This study assessed agreement between the thigh-worn activPAL and commonly used hip-worn ActiGraph accelerometer methods for assessing sedentary patterns in children. Both devices were worn by 8-12-year-olds (N = 195) for 4.6 ± 1.9 days. Two ActiGraph cut-points were applied to two epoch durations: ≤25 counts (c)/15 s, ≤75c/15s, ≤100c/60s, and ≤300c/60s. Bias, mean absolute deviation (MAD), and intraclass correlation coefficients (ICCs) tested agreement between devices for total sedentary time and 11 sedentary pattern variables (usual bout duration, sedentary time accumulated in various bout durations, breaks/day, break rate, and alpha). For most sedentary pattern variables, ActiGraph 25c/15s, 75c/15s, and 100c/60s had poor ICCs, with bias and MAD >20%. ActiGraph 300c/60s had a better agreement than the other cut-points, but all ICCs were <0.587. ActiGraph underestimated sedentary time in longer bouts and usual bout duration, and overestimated sedentary time in shorter bouts, breaks/day, and alpha. For total sedentary time, ActiGraph 25c/15s, 300c/60s, and 75c/15s had good/fair ICCs, with bias and MAD <20%. Sedentary patterns derived from two commonly used ActiGraph cut-points did not appear to reflect postural changes. These differences between measurement devices should be considered when interpreting findings from sedentary pattern studies.

Entities:  

Keywords:  Accelerometry; children; sitting; validity

Mesh:

Year:  2019        PMID: 31002287      PMCID: PMC6594870          DOI: 10.1080/02640414.2019.1605646

Source DB:  PubMed          Journal:  J Sports Sci        ISSN: 0264-0414            Impact factor:   3.337


  9 in total

1.  Application of Convolutional Neural Network Algorithms for Advancing Sedentary and Activity Bout Classification.

Authors:  Supun Nakandala; Marta M Jankowska; Fatima Tuz-Zahra; John Bellettiere; Jordan A Carlson; Andrea Z LaCroix; Sheri J Hartman; Dori E Rosenberg; Jingjing Zou; Arun Kumar; Loki Natarajan
Journal:  J Meas Phys Behav       Date:  2021-02-25

2.  Agreement of sedentary behaviour metrics derived from hip-worn and thigh-worn accelerometers among older adults: with implications for studying physical and cognitive health.

Authors:  John Bellettiere; Fatima Tuz-Zahra; Jordan A Carlson; Nicola D Ridgers; Sandy Liles; Mikael Anne Greenwood-Hickman; Rod L Walker; Andrea Z LaCroix; Marta M Jankowska; Dori E Rosenberg; Loki Natarajan
Journal:  J Meas Phys Behav       Date:  2021-02-16

3.  Exploring Differences in Older Adult Accelerometer-Measured Sedentary Behavior and Resting Blood Pressure Before and During the COVID-19 Pandemic.

Authors:  Mikael Anne Greenwood-Hickman; Jing Zhou; Andrea Cook; Kayne D Mettert; Bev Green; Jennifer McClure; David Arterburn; Stefani Florez-Acevedo; Dori E Rosenberg
Journal:  Gerontol Geriatr Med       Date:  2022-04-27

4.  Assessment of 24-hour physical behaviour in children and adolescents via wearables: a systematic review of free-living validation studies.

Authors:  Marco Giurgiu; Simon Kolb; Carina Nigg; Alexander Burchartz; Irina Timm; Marlissa Becker; Ellen Rulf; Ann-Kathrin Doster; Elena Koch; Johannes B J Bussmann; Claudio Nigg; Ulrich W Ebner-Priemer; Alexander Woll
Journal:  BMJ Open Sport Exerc Med       Date:  2022-05-12

5.  Associations Between Perceived Neighborhood Walkability and Device-Based Physical Activity and Sedentary Behavior Patterns in Older Adults.

Authors:  Mikael Anne Greenwood-Hickman; Rod Walker; John Bellettiere; Andrea Z LaCroix; Boeun Kim; David Wing; KatieRose Richmire; Paul K Crane; Eric B Larson; Dori E Rosenberg
Journal:  J Aging Phys Act       Date:  2021-08-13       Impact factor: 1.961

6.  The CNN Hip Accelerometer Posture (CHAP) Method for Classifying Sitting Patterns from Hip Accelerometers: A Validation Study.

Authors:  Mikael Anne Greenwood-Hickman; Supun Nakandala; Marta M Jankowska; Dori E Rosenberg; Fatima Tuz-Zahra; John Bellettiere; Jordan Carlson; Paul R Hibbing; Jingjing Zou; Andrea Z Lacroix; Arun Kumar; Loki Natarajan
Journal:  Med Sci Sports Exerc       Date:  2021-11-01

7.  Using compositional data analysis to explore accumulation of sedentary behavior, physical activity and youth health.

Authors:  Simone J J M Verswijveren; Karen E Lamb; Josep A Martín-Fernández; Elisabeth Winkler; Rebecca M Leech; Anna Timperio; Jo Salmon; Robin M Daly; Ester Cerin; David W Dunstan; Rohan M Telford; Richard D Telford; Lisa S Olive; Nicola D Ridgers
Journal:  J Sport Health Sci       Date:  2021-03-15       Impact factor: 13.077

8.  CHAP-child: an open source method for estimating sit-to-stand transitions and sedentary bout patterns from hip accelerometers among children.

Authors:  Jordan A Carlson; Nicola D Ridgers; Supun Nakandala; Rong Zablocki; Fatima Tuz-Zahra; John Bellettiere; Paul R Hibbing; Chelsea Steel; Marta M Jankowska; Dori E Rosenberg; Mikael Anne Greenwood-Hickman; Jingjing Zou; Andrea Z LaCroix; Arun Kumar; Loki Natarajan
Journal:  Int J Behav Nutr Phys Act       Date:  2022-08-26       Impact factor: 8.915

9.  Patterns of Sedentary Time in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) Youth.

Authors:  Carolina M Bejarano; Linda C Gallo; Sheila F Castañeda; Melawhy L Garcia; Daniela Sotres-Alvarez; Krista M Perreira; Carmen R Isasi; Martha Daviglus; Linda Van Horn; Alan M Delamater; Kimberly L Savin; Jianwen Cai; Jordan A Carlson
Journal:  J Phys Act Health       Date:  2020-12-22
  9 in total

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