Device-measured physical activity and cardiometabolic health: the Prospective Physical Activity, Sitting, and Sleep (ProPASS) consortium

Joanna M Blodgett; Matthew N Ahmadi; Andrew J Atkin; Sebastien Chastin; Hsiu-Wen Chan; Kristin Suorsa; Esmee A Bakker; Pasan Hettiarcachchi; Peter J Johansson; Lauren B Sherar; Vegar Rangul; Richard M Pulsford; Gita Mishra; Thijs M H Eijsvogels; Sari Stenholm; Alun D Hughes; Armando M Teixeira-Pinto; Ulf Ekelund; I-Min Lee; Andreas Holtermann; Annemarie Koster; Emmanuel Stamatakis; Mark Hamer; ProPASS Collaboration

doi:10.1093/eurheartj/ehad717

Device-measured physical activity and cardiometabolic health: the Prospective Physical Activity, Sitting, and Sleep (ProPASS) consortium

Eur Heart J. 2024 Feb 7;45(6):458-471. doi: 10.1093/eurheartj/ehad717.

Authors

Joanna M Blodgett¹, Matthew N Ahmadi^{2

3}, Andrew J Atkin⁴, Sebastien Chastin^{5

6}, Hsiu-Wen Chan⁷, Kristin Suorsa^{8

9}, Esmee A Bakker^{10

11}, Pasan Hettiarcachchi¹², Peter J Johansson^{12

13}, Lauren B Sherar¹⁴, Vegar Rangul¹⁵, Richard M Pulsford¹⁶, Gita Mishra⁷, Thijs M H Eijsvogels¹¹, Sari Stenholm^{7

8

17}, Alun D Hughes^{18

19

20}, Armando M Teixeira-Pinto²¹, Ulf Ekelund^{22

23}, I-Min Lee^{24

25}, Andreas Holtermann²⁶, Annemarie Koster²⁷, Emmanuel Stamatakis^{2

3}, Mark Hamer^{1

20}; ProPASS Collaboration

Collaborators

ProPASS Collaboration:
Nidhi Gupta, Coen Stehouwer, Hans Savelberg, Bastiaan de Galan, Carla van de Kallen, Dick H J Thijssen

Affiliations

¹ Institute of Sport Exercise and Health, Division of Surgery and Interventional Sciences, University College London, London , UK.
² Mackenzie Wearables Research Hub, Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia.
³ School of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.
⁴ School of Health Sciences and Norwich Epidemiology Centre, University of East Anglia, Norwich, UK.
⁵ School of Health and Life Science Glasgow Caledonian University, Glasgow, UK.
⁶ Department of Movement and Sport Sciences, Ghent University, Ghent, Belgium.
⁷ School of Public Health, The University of Queensland, Brisbane, Queensland, Australia.
⁸ Department of Public Health, University of Turku and Turku University Hospital, Turku, Finland.
⁹ Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland.
¹⁰ Department of Physical Education and Sports, Faculty of Sport Sciences, Sport and Health University Research Institute (iMUDS), University of Granada, Granada, Spain.
¹¹ Department of Medical BioSciences, Exercise Physiology ResearchGroup, Radboud University Medical Center, Nijmegen, The Netherlands.
¹² Occupational and Environmental Medicine, Department of Medical Sciences, Uppsala University, Sweden.
¹³ Occupational and Environmental Medicine, Uppsala University Hospital, Uppsala, Sweden.
¹⁴ School of Sport, Exercise and Health Sciences, Loughborough University, UK.
¹⁵ HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Norway.
¹⁶ Faculty of Health and Life Sciences, University of Exeter, UK.
¹⁷ Research Services, Turku University Hospital and University of Turku, Finland.
¹⁸ MRC Unit for Lifelong Health and Ageing, UCL Institute of Cardiovascular Science, UCL, UK.
¹⁹ UCL BHF Research Accelerator, University College London, London, UK.
²⁰ University College London Hospitals NIHR Biomedical Research Centre, London, UK.
²¹ School of Public Health, Faculty of Medicine and Health, University of Sydney, Australia.
²² Department of Sport Medicine, Norwegian School of Sport Sciences, Oslo, Norway.
²³ Departmentof Chronic Diseases, Norwegian Public Health Institute, Oslo, Norway.
²⁴ Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
²⁵ Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA.
²⁶ National Research Centre for the Working Environment, Copenhagen, Denmark.
²⁷ Department of Social Medicine, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands.

Abstract

Background and aims: Physical inactivity, sedentary behaviour (SB), and inadequate sleep are key behavioural risk factors of cardiometabolic diseases. Each behaviour is mainly considered in isolation, despite clear behavioural and biological interdependencies. The aim of this study was to investigate associations of five-part movement compositions with adiposity and cardiometabolic biomarkers.

Methods: Cross-sectional data from six studies (n = 15 253 participants; five countries) from the Prospective Physical Activity, Sitting and Sleep consortium were analysed. Device-measured time spent in sleep, SB, standing, light-intensity physical activity (LIPA), and moderate-vigorous physical activity (MVPA) made up the composition. Outcomes included body mass index (BMI), waist circumference, HDL cholesterol, total:HDL cholesterol ratio, triglycerides, and glycated haemoglobin (HbA1c). Compositional linear regression examined associations between compositions and outcomes, including modelling time reallocation between behaviours.

Results: The average daily composition of the sample (age: 53.7 ± 9.7 years; 54.7% female) was 7.7 h sleeping, 10.4 h sedentary, 3.1 h standing, 1.5 h LIPA, and 1.3 h MVPA. A greater MVPA proportion and smaller SB proportion were associated with better outcomes. Reallocating time from SB, standing, LIPA, or sleep into MVPA resulted in better scores across all outcomes. For example, replacing 30 min of SB, sleep, standing, or LIPA with MVPA was associated with -0.63 (95% confidence interval -0.48, -0.79), -0.43 (-0.25, -0.59), -0.40 (-0.25, -0.56), and -0.15 (0.05, -0.34) kg/m2 lower BMI, respectively. Greater relative standing time was beneficial, whereas sleep had a detrimental association when replacing LIPA/MVPA and positive association when replacing SB. The minimal displacement of any behaviour into MVPA for improved cardiometabolic health ranged from 3.8 (HbA1c) to 12.7 (triglycerides) min/day.

Conclusions: Compositional data analyses revealed a distinct hierarchy of behaviours. Moderate-vigorous physical activity demonstrated the strongest, most time-efficient protective associations with cardiometabolic outcomes. Theoretical benefits from reallocating SB into sleep, standing, or LIPA required substantial changes in daily activity.

Keywords: Cardiometabolic outcomes; Cohort consortium; Compositional data analysis; Physical activity; Sedentary behaviour; Sleep; Standing.

MeSH terms

Adult
Cardiovascular Diseases* / epidemiology
Cardiovascular Diseases* / prevention & control
Cholesterol, HDL
Cross-Sectional Studies
Exercise
Female
Glycated Hemoglobin
Humans
Male
Middle Aged
Prospective Studies
Sitting Position*
Sleep
Triglycerides

Substances

Cholesterol, HDL
Glycated Hemoglobin
Triglycerides

Abstract

MeSH terms

Substances

Grants and funding