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Updated: Jun 23, 2025

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
24-hour movement behaviors time allocation and depression among Chinese community-dwelling older adults: A latent
Yan Jiang1, Ye Lu2, Jingping Cui3
1Department of Nursing, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, PR China; Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of USTC,Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, PR China.
Abstract:
This study explored the combination characteristics of physical activity, sedentary behavior, and sleep among older adults during a 24-hour time allocation and analyzed the correlations between different combinations and depression. We recruited 648 older adults (mean age 72.65±7.03) from three communities in urban areas of central China and measured their physical activity, sedentary behavior, sleep quality, and depression. We used latent profile analysis to classify the time allocation of 24 h of movement behavior and binary logistic regression to analyze associations between different subgroups and depression. We found four classes of 24-hour movement behavior: moderately active-moderate sleepers (32.9 %), active-sedentary-short sleepers (17.8 %), sedentary-long sleepers (8.6 %), and active-short sleepers (40.7 %). Compared with moderately active-moderate sleepers, active-sedentary-short and sedentary-long sleepers were 2.953 and 4.813 times more likely to have depression, respectively. There was no statistically significant difference between active-short and moderately active-moderate sleepers. The results can inform preventive measures for depression in older adults.
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