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Short Daily-Life Walking Bouts and Poor Self-Reported Health Predict the Onset of Depression in Community-Dwelling Older People: A 2-Year Longitudinal Cohort Study

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  • معلومة اضافية
    • بيانات النشر:
      Elsevier
    • الموضوع:
      2022
    • Collection:
      UNSW Sydney (The University of New South Wales): UNSWorks
    • نبذة مختصرة :
      Objectives: This study aimed to assess whether the amount and quality of daily-life walking obtained using wearable technology can predict depression onset over a 2-year period, independently of self-reported health status. Design: Longitudinal cohort study. Setting and Participants: Three-hundred twenty-two community-dwelling older people recruited in Sydney, Australia. Methods: Participants were assessed at baseline on (1) depressive symptoms using the Patient Health Questionnaire–9; (2) average weekly physical activity levels over the past month using the Incidental and Planned Activity Questionnaire, (3) clinical mobility tests (ie, short physical performance battery, timed up-and-go test, 6-m walk test); and (4) amount and quality of daily-life walking assessed with a trunk accelerometer (MoveMonitor, McRoberts) for 1 week. Participants were followed up for onset of depressive symptoms for 2 years at 6-monthly intervals. Results: Daily-life walking (ie, gait intensity in the mediolateral axis, daily step counts, duration of longest walk) and self-rated health predicted the new onset of depressive symptoms at 2 years in univariable logistic regression models. In multivariable models containing a self-rated health measure, clinical mobility tests were not predictive of the onset of depressive symptoms. In contrast, a measure of daily-life walking (duration of longest walking bout) was identified as a significant predictor of depressive symptom onset [standardized odds ratio (SOR) 2.44, 95% CI 1.62-3.76] independent of self-rated health (SOR 1.51, 95% CI 1.16-1.96), with these 2 measures achieving a satisfactory prediction accuracy (area under the curve = 0.67, sensitivity: 0.78, specificity: 0.52). Conclusions and Implications: A risk algorithm based on daily-life walking bouts and self-reported health demonstrated good accuracy for the prediction of depression onset in older people over 2 years. Wearable sensor data compared favorably with clinical mobility screens and may add important independent ...
    • File Description:
      application/pdf
    • Relation:
      http://hdl.handle.net/1959.4/102405; https://unsworks.unsw.edu.au/bitstreams/b368e5ba-c22e-4756-af9b-7cb2e566730c/download; https://doi.org/10.1016/j.jamda.2021.12.042
    • الرقم المعرف:
      10.1016/j.jamda.2021.12.042
    • Rights:
      open access ; https://purl.org/coar/access_right/c_abf2 ; CC-BY-NC-ND ; https://creativecommons.org/licenses/by-nc-nd/4.0/ ; free_to_read
    • الرقم المعرف:
      edsbas.5F59D47B