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This study demonstrates a novel data-driven method of summarising accelerometer data to profile physical activity in three diverse groups, compared with cut-point determined moderate-to-vigorous physical activity (MVPA). GGIR was used to generate average daily acceleration, intensity gradient, time in MVPA and MX metrics (acceleration above which the most active X-minutes accumulate) from wrist-worn accelerometer data from three datasets: office-workers (OW, N = 697), women with a history of post-gestational diabetes (PGD, N = 267) and adults with ≥1 chronic disease (CD, N = 1,325). Average acceleration and MVPA were lower in CD, but not PGD, relative to OW (-5.2 mg and -30.7 minutes, respectively, P Abbreviations: CD: Adults with ≥1 chronic disease; mg: Milli-gravitational unit; MVPA: Moderate-to-vigorous physical activity; OW: Office workers; PGD: Women with a history of post-gestational diabetes; VPA: Vigorous physical activity.

Original publication

DOI

10.1080/02640414.2020.1812202

Type

Journal article

Journal

Journal of sports sciences

Publication Date

01/2021

Volume

39

Pages

219 - 226

Addresses

Diabetes Research Centre, University of Leicester, Leicester General Hospital , Leicester, UK.

Keywords

Humans, Diabetes, Gestational, Chronic Disease, Exercise, Pregnancy, Adult, Aged, Middle Aged, Occupations, Female, Accelerometry, Fitness Trackers, Sedentary Behavior