Literature DB >> 31479008

activPAL and ActiGraph Assessed Sedentary Behavior and Cardiometabolic Health Markers.

Charlotte L Edwardson1,2, Joseph Henson1,2, Stuart J H Biddle3, Melanie J Davies1,2,4, Kamlesh Khunti1,4,5, Benjamin Maylor1, Thomas Yates1,2.   

Abstract

PURPOSE: To establish whether associations between sedentary behavior and cardiometabolic health differ when assessed by thigh-worn and waist-worn accelerometry.
METHODS: Participants were recruited from several areas in the United Kingdom. Sedentary behavior was assessed using the activPAL worn on the thigh and ActiGraph worn on the waist. Average total (TST), prolonged (bouts ≥30 min; PST) and breaks (BST) in sedentary time were calculated. Cardiometabolic health markers included: adiposity (body fat) and surrogate markers of adiposity ((waist circumference, body mass index [BMI]), lipids (total, low density lipoprotein, and high-density lipoprotein [HDL] cholesterol, triglycerides), blood pressure, and glucose (fasting, 2 h and glycated hemoglobin A1c). A clustered cardiometabolic risk score was calculated. Linear regression analysis examined the associations with cardiometabolic health.
RESULTS: There were 1457 participants (mean age [± standard deviation], 59.38 ± 11.85 yr; 51.7% male; mean BMI, 30.19 ± 5.59 kg·m) included in the analyses. ActivPAL and ActiGraph sedentary variables were moderately correlated (0.416-0.511, P < 0.01); however, all variables were significantly different from each other (P < 0.05). Consistency was observed across devices in the direction and magnitude of associations of TST and PST with adiposity, surrogate markers of adiposity, HDL, triglycerides, and cardiometabolic risk score and for BST with adiposity, surrogate markers of adiposity, and cardiometabolic risk. Differences across devices were observed in associations of TST and PST with diastolic blood pressure, for TST with 2-h glucose and for BST with HDL. No other associations were observed for any other health marker for either device.
CONCLUSIONS: Results suggest that associations with cardiometabolic health are largely comparable across the two common assessments of sedentary behavior but some small differences may exist for certain health markers.

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Year:  2020        PMID: 31479008     DOI: 10.1249/MSS.0000000000002138

Source DB:  PubMed          Journal:  Med Sci Sports Exerc        ISSN: 0195-9131            Impact factor:   5.411


  10 in total

Review 1.  Thigh-worn accelerometry for measuring movement and posture across the 24-hour cycle: a scoping review and expert statement.

Authors:  Matthew L Stevens; Nidhi Gupta; Elif Inan Eroglu; Patrick Joseph Crowley; Barbaros Eroglu; Adrian Bauman; Malcolm Granat; Leon Straker; Peter Palm; Sari Stenholm; Mette Aadahl; Paul Mork; Sebastien Chastin; Vegar Rangul; Mark Hamer; Annemarie Koster; Andreas Holtermann; Emmanuel Stamatakis
Journal:  BMJ Open Sport Exerc Med       Date:  2020-12-24

2.  Concurrent and discriminant validity of ActiGraph waist and wrist cut-points to measure sedentary behaviour, activity level, and posture in office work.

Authors:  Roman P Kuster; Maria Hagströmer; Daniel Baumgartner; Wilhelmus J A Grooten
Journal:  BMC Public Health       Date:  2021-02-12       Impact factor: 3.295

3.  Is Sitting Always Inactive and Standing Always Active? A Simultaneous Free-Living activPal and ActiGraph Analysis.

Authors:  Roman P Kuster; Wilhelmus J A Grooten; Victoria Blom; Daniel Baumgartner; Maria Hagströmer; Örjan Ekblom
Journal:  Int J Environ Res Public Health       Date:  2020-11-28       Impact factor: 3.390

4.  Patterns and correlates of sedentary behaviour among people with multiple sclerosis: a cross-sectional study.

Authors:  Jennifer Fortune; Meriel Norris; Andrea Stennett; Cherry Kilbride; Grace Lavelle; Wendy Hendrie; Christina Victor; Jennifer Mary Ryan
Journal:  Sci Rep       Date:  2021-10-13       Impact factor: 4.379

5.  A Standardised Core Outcome Set for Measurement and Reporting Sedentary Behaviour Interventional Research: The CROSBI Consensus Study.

Authors:  Fiona Curran; Kieran P Dowd; Casey L Peiris; Hidde P van der Ploeg; Mark S Tremblay; Grainne O'Donoghue
Journal:  Int J Environ Res Public Health       Date:  2022-08-05       Impact factor: 4.614

6.  Associations between sedentary behavior and negative emotions in adolescents during home confinement: Mediating role of social support and sleep quality.

Authors:  Liye Zou; Ting Wang; Fabian Herold; Sebastian Ludyga; Weina Liu; Yanjie Zhang; Sean Healy; Zhihao Zhang; Jin Kuang; Alyx Taylor; Arthur F Kramer; Sitong Chen; Mark S Tremblay; M Mahbub Hossain
Journal:  Int J Clin Health Psychol       Date:  2022-09-22

7.  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

8.  Differences in Habitual Physical Activity Behavior between Students from Different Vocational Education Tracks and the Association with Cognitive Performance.

Authors:  Rianne H J Golsteijn; Hieronymus J M Gijselaers; Hans H C M Savelberg; Amika S Singh; Renate H M de Groot
Journal:  Int J Environ Res Public Health       Date:  2021-03-16       Impact factor: 3.390

9.  Cross-Sectional Associations of Sedentary Behavior and Sitting with Serum Lipid Biomarkers in Midlife.

Authors:  Petra Tjurin; Maisa Niemelä; Maarit Kangas; Laura Nauha; Henri Vähä-Ypyä; Harri Sievänen; Raija Korpelainen; Vahid Farrahi; Timo Jämsä
Journal:  Med Sci Sports Exerc       Date:  2022-03-22

10.  Associations of Sedentary Patterns with Cardiometabolic Biomarkers in Physically Active Young Males.

Authors:  Chen Zheng; Xiao Yu Tian; Feng Hua Sun; Wendy Yajun Huang; Sinead Sheridan; Yalan Wu; Stephen Heung-Sang Wong
Journal:  Med Sci Sports Exerc       Date:  2021-04-01
  10 in total

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