International Journal of Behavioral Nutrition and Physical Activity (Nov 2023)

Device-measured movement behaviours in over 20,000 China Kadoorie Biobank participants

  • Yuanyuan Chen,
  • Shing Chan,
  • Derrick Bennett,
  • Xiaofang Chen,
  • Xianping Wu,
  • Yalei Ke,
  • Jun Lv,
  • Dianjianyi Sun,
  • Lang Pan,
  • Pei Pei,
  • Ling Yang,
  • Yiping Chen,
  • Junshi Chen,
  • Zhengming Chen,
  • Liming Li,
  • Huaidong Du,
  • Canqing Yu,
  • Aiden Doherty,
  • on behalf of the China Kadoorie Biobank Collaborative Group

DOI
https://doi.org/10.1186/s12966-023-01537-8
Journal volume & issue
Vol. 20, no. 1
pp. 1 – 11

Abstract

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Abstract Background Movement behaviours, including physical activity, sedentary behaviour, and sleep have been shown to be associated with several chronic diseases. However, they have not been objectively measured in large-scale prospective cohort studies in low-and middle-income countries. We aim to describe the patterns of device-measured movement behaviours collected in the China Kadoorie Biobank (CKB) study. Methods During 2020 and 2021, a random subset of 25,087 surviving CKB individuals participated in the 3rd resurvey of the CKB. Among them, 22,511 (89.7%) agreed to wear an Axivity AX3 wrist-worn triaxial accelerometer for seven consecutive days to assess their habitual movement behaviours. We developed a machine-learning model to infer time spent in four movement behaviours [i.e. sleep, sedentary behaviour, light intensity physical activity (LIPA), and moderate-to-vigorous physical activity (MVPA)]. Descriptive analyses were performed for wear-time compliance and patterns of movement behaviours by different participant characteristics. Results Data from 21,897 participants (aged 65.4 ± 9.1 years; 35.4% men) were received for demographic and wear-time analysis, with a median wear-time of 6.9 days (IQR: 6.1–7.0). Among them, 20,370 eligible participants were included in movement behavior analyses. On average, they had 31.1 mg/day (total acceleration) overall activity level, accumulated 7.7 h/day (32.3%) of sleep time, 8.8 h/day (36.6%) sedentary, 5.7 h/day (23.9%) in light physical activity, and 104.4 min/day (7.2%) in moderate-to-vigorous physical activity. There was an inverse relationship between age and overall acceleration with an observed decline of 5.4 mg/day (17.4%) per additional decade. Women showed a higher activity level than men (32.3 vs 28.8 mg/day) and there was a marked geographical disparity in the overall activity level and time allocation. Conclusions This is the first large-scale accelerometer data collected among Chinese adults, which provides rich and comprehensive information about device-measured movement behaviour patterns. This resource will enhance our knowledge about the potential relevance of different movement behaviours for chronic disease in Chinese adults.

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