Physical Activity Assessed by Wrist and Thigh Worn Accelerometry and Associations with Cardiometabolic Health

Author:

Maylor Benjamin D.123ORCID,Edwardson Charlotte L.123,Clarke-Cornwell Alexandra M.4ORCID,Davies Melanie J.13ORCID,Dawkins Nathan P.135ORCID,Dunstan David W.67,Khunti Kamlesh138,Yates Tom13,Rowlands Alex V.123ORCID

Affiliation:

1. Diabetes Research Centre, Population Health Sciences, College of Life Sciences, University of Leicester, Leicester LE1 7RH, UK

2. Assessment of Movement Behaviours Group (AMBer), Leicester Lifestyle and Health Research Group, Diabetes Research Centre, University of Leicester, Leicester LE1 7RH, UK

3. Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK

4. School of Health and Society, University of Salford, Greater Manchester M5 4WT, UK

5. School of Sport and Wellbeing, Leeds Trinity University, Leeds LS18 5HD, UK

6. Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia

7. Institute for Physical Activity and Nutrition, Faculty of Health, Deakin University, Geelong, VIC 3220, Australia

8. NIHR Applied Research Collaboration East Midlands, Diabetes Research Centre, University of Leicester, Leicester LE1 7RH, UK

Abstract

Physical activity is increasingly being captured by accelerometers worn on different body locations. The aim of this study was to examine the associations between physical activity volume (average acceleration), intensity (intensity gradient) and cardiometabolic health when assessed by a thigh-worn and wrist-worn accelerometer. A sample of 659 office workers wore an Axivity AX3 on the non-dominant wrist and an activPAL3 micro on the right thigh concurrently for 24 h a day for 8 days. An average acceleration (proxy for physical activity volume) and intensity gradient (intensity distribution) were calculated from both devices using the open-source raw accelerometer processing software GGIR. Clustered cardiometabolic risk (CMR) was calculated using markers of cardiometabolic health, including waist circumference, triglycerides, HDL-cholesterol, mean arterial pressure and fasting glucose. Linear regression analysis assessed the associations between physical activity volume and intensity gradient with cardiometabolic health. Physical activity volume derived from the thigh-worn activPAL and the wrist-worn Axivity were beneficially associated with CMR and the majority of individual health markers, but associations only remained significant after adjusting for physical activity intensity in the thigh-worn activPAL. Physical activity intensity was associated with CMR score and individual health markers when derived from the wrist-worn Axivity, and these associations were independent of volume. Associations between cardiometabolic health and physical activity volume were similarly captured by the thigh-worn activPAL and the wrist-worn Axivity. However, only the wrist-worn Axivity captured aspects of the intensity distribution associated with cardiometabolic health. This may relate to the reduced range of accelerations detected by the thigh-worn activPAL.

Funder

National Institute for Health Research

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

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