FARRAHI, VAHID1,2; ROSTAMI, MEHRDAD2; DUMUID, DOT3; CHASTIN, SEBASTIEN F. M.4,5; NIEMELÄ, MAISA1,6,7; KORPELAINEN, RAIJA6,7,8; JÄMSÄ, TIMO1,6; OUSSALAH, MOURAD1,2. Joint Profiles of Sedentary Time and Physical Activity in Adults and Their Associations with Cardiometabolic Health. Medicine & Science in Sports & Exercise 54(12):p 2118-2128, December 2022. | DOI: 10.1249/MSS.0000000000003008
Joint profiles of sedentary time and physical activity in adults and their associations with cardiometabolic health
|Author:||Farrahi, Vahid1,2; Rostami, Mehrdad2; Dumuid, Dot3;|
1Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, FINLAND
2Centre of Machine Vision and Signal Analysis, Faculty of Information Technology, University of Oulu, Oulu, FINLAND
3Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, AUSTRALIA
4School of Health and Life Sciences, Glasgow Caledonian University, Glasgow, UNITED KINGDOM
5Department of Movement and Sports Science, Ghent University, Ghent, BELGIUM
6Medical Research Center, Oulu University Hospital and University of Oulu, Oulu, FINLAND
7Department of Sports and Exercise Medicine, Oulu Deaconess Institute Foundation sr., FINLAND
8Center for Life Course Health Research, University of Oulu, Oulu, FINLAND
|Online Access:||PDF Full Text (PDF, 0.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2023053049541
|Publish Date:|| 2023-05-30
Purpose: This study aimed to identify and characterize joint profiles of sedentary time and physical activity among adults and to investigate how these profiles are associated with markers of cardiometabolic health.
Methods: The participants included 3702 of the Northern Finland Birth Cohort 1966 at age 46 yr, who wore a hip-worn accelerometer during waking hours and provided seven consecutive days of valid data. Sedentary time, light-intensity physical activity, and moderate- to vigorous-intensity physical activity on each valid day were obtained, and a data-driven clustering approach (“KmL3D”) was used to characterize distinct joint profiles of sedentary time and physical activity intensities. Participants self-reported their sleep duration and performed a submaximal step test with continuous heart rate measurement to estimate their cardiorespiratory fitness (peak heart rate). Linear regression was used to determine the association between joint profiles of sedentary time and physical activities with cardiometabolic health markers, including adiposity markers and blood lipid, glucose, and insulin levels.
Results: Four distinct groups were identified: “active couch potatoes” (n = 1173), “sedentary light movers” (n = 1199), “sedentary exercisers” (n = 694), and “movers” (n = 636). Although sufficiently active, active couch potatoes had the highest daily sedentary time (>10 h) and lowest light-intensity physical activity. Compared with active couch potatoes, sedentary light movers, sedentary exercisers, and movers spent less time in sedentary by performing more physical activity at light-intensity upward and had favorable differences in their cardiometabolic health markers after accounting for potential confounders (1.1%–25.0% lower values depending on the health marker and profile).
Conclusions: After accounting for sleep duration and cardiorespiratory fitness, waking activity profiles characterized by performing more physical activity at light-intensity upward, resulting in less time spent in sedentary, were associated with better cardiometabolic health.
Medicine & science in sports & exercise
|Pages:||2118 - 2128|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
217 Medical engineering
315 Sport and fitness sciences
3121 General medicine, internal medicine and other clinical medicine
The present study is connected to the DigiHealth-project, a strategic profiling project at the University of Oulu. The project is supported by the Academy of Finland (project number 326291) and the University of Oulu. NFBC1966 received financial support from University of Oulu Grant no. 24000692, Oulu University Hospital Grant no. 24301140, ERDF European Regional Development Fund Grant no. 539/2010 A31592. This study has also received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 713645, and the Ministry of Education and Culture in Finland [grant numbers OKM/20/626/2022, OKM/86/626/2014, OKM/43/626/2015, OKM/17/626/2016, OKM 47/626/2017, OKM/78/626/2018, OKM/54/626/2019, OKM/85/626/2019, OKM/88/626/2019, OKM/1096/626/2020]. DD is supported by the Australian National Health and Medical Research Council (NHMRC) Early Career Fellowship APP1162166 and by the Centre of Research Excellence in Driving Global Investment in Adolescent Health funded by NHMRC APP1171981.
|EU Grant Number:||
(713645) BioMEP - Biomedical Engineering and Medical Physics
© 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American College of Sports Medicine. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and
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