Quantifying Circadian Aspects of Mobility-Related Behavior in Older Adults by Body-Worn Sensors—An “Active Period Analysis”
Disruptions of circadian motor behavior cause a significant burden for older adults as well as their caregivers and often lead to institutionalization. This cross-sectional study investigates the association between mobility-related behavior and subjectively rated circadian chronotypes in healthy ol...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/6/2121 |
| _version_ | 1797540928543522816 |
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| author | Tim Fleiner Rieke Trumpf Anna Hollinger Peter Haussermann Wiebren Zijlstra |
| author_facet | Tim Fleiner Rieke Trumpf Anna Hollinger Peter Haussermann Wiebren Zijlstra |
| author_sort | Tim Fleiner |
| collection | DOAJ |
| description | Disruptions of circadian motor behavior cause a significant burden for older adults as well as their caregivers and often lead to institutionalization. This cross-sectional study investigates the association between mobility-related behavior and subjectively rated circadian chronotypes in healthy older adults. The physical activity of 81 community-dwelling older adults was measured over seven consecutive days and nights using lower-back-worn hybrid motion sensors (MM+) and wrist-worn actigraphs (MW8). A 30-min and 120-min active period for the highest number of steps (MM+) and activity counts (MW8) was derived for each day, respectively. Subjective chronotypes were classified by the Morningness-Eveningness Questionnaire into 40 (50%) morning types, 35 (43%) intermediate and six (7%) evening types. Analysis revealed significantly earlier starts for the 30-min active period (steps) in the morning types compared to the intermediate types (<i>p</i> ≤ 0.01) and the evening types (<i>p</i> ≤ 0.01). The 120-min active period (steps) showed significantly earlier starts in the morning types compared to the intermediate types (<i>p</i> ≤ 0.01) and the evening types (<i>p</i> = 0.02). The starting times of active periods determined from wrist-activity counts (MW8) did not reveal differences between the three chronotypes (<i>p</i> = 0.36 for the 30-min and <i>p</i> = 0.12 for the 120-min active period). The timing of mobility-related activity, i.e., periods with the highest number of steps measured by hybrid motion sensors, is associated to subjectively rated chronotypes in healthy older adults. The analysis of individual active periods may provide an innovative approach for early detecting and individually tailoring the treatment of circadian disruptions in aging and geriatric healthcare. |
| first_indexed | 2024-03-10T13:08:55Z |
| format | Article |
| id | doaj.art-b1721037888145ca883c93dacad9f00d |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T13:08:55Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-b1721037888145ca883c93dacad9f00d2023-11-21T10:57:13ZengMDPI AGSensors1424-82202021-03-01216212110.3390/s21062121Quantifying Circadian Aspects of Mobility-Related Behavior in Older Adults by Body-Worn Sensors—An “Active Period Analysis”Tim Fleiner0Rieke Trumpf1Anna Hollinger2Peter Haussermann3Wiebren Zijlstra4Institute of Movement and Sport Gerontology, German Sport University Cologne, 50933 Cologne, GermanyInstitute of Movement and Sport Gerontology, German Sport University Cologne, 50933 Cologne, GermanyInstitute of Movement and Sport Gerontology, German Sport University Cologne, 50933 Cologne, GermanyDepartment of Geriatric Psychiatry & Psychotherapy, LVR Hospital Cologne, 51109 Cologne, GermanyInstitute of Movement and Sport Gerontology, German Sport University Cologne, 50933 Cologne, GermanyDisruptions of circadian motor behavior cause a significant burden for older adults as well as their caregivers and often lead to institutionalization. This cross-sectional study investigates the association between mobility-related behavior and subjectively rated circadian chronotypes in healthy older adults. The physical activity of 81 community-dwelling older adults was measured over seven consecutive days and nights using lower-back-worn hybrid motion sensors (MM+) and wrist-worn actigraphs (MW8). A 30-min and 120-min active period for the highest number of steps (MM+) and activity counts (MW8) was derived for each day, respectively. Subjective chronotypes were classified by the Morningness-Eveningness Questionnaire into 40 (50%) morning types, 35 (43%) intermediate and six (7%) evening types. Analysis revealed significantly earlier starts for the 30-min active period (steps) in the morning types compared to the intermediate types (<i>p</i> ≤ 0.01) and the evening types (<i>p</i> ≤ 0.01). The 120-min active period (steps) showed significantly earlier starts in the morning types compared to the intermediate types (<i>p</i> ≤ 0.01) and the evening types (<i>p</i> = 0.02). The starting times of active periods determined from wrist-activity counts (MW8) did not reveal differences between the three chronotypes (<i>p</i> = 0.36 for the 30-min and <i>p</i> = 0.12 for the 120-min active period). The timing of mobility-related activity, i.e., periods with the highest number of steps measured by hybrid motion sensors, is associated to subjectively rated chronotypes in healthy older adults. The analysis of individual active periods may provide an innovative approach for early detecting and individually tailoring the treatment of circadian disruptions in aging and geriatric healthcare.https://www.mdpi.com/1424-8220/21/6/2121circadian motor behaviorbody-worn sensorsolder adults |
| spellingShingle | Tim Fleiner Rieke Trumpf Anna Hollinger Peter Haussermann Wiebren Zijlstra Quantifying Circadian Aspects of Mobility-Related Behavior in Older Adults by Body-Worn Sensors—An “Active Period Analysis” Sensors circadian motor behavior body-worn sensors older adults |
| title | Quantifying Circadian Aspects of Mobility-Related Behavior in Older Adults by Body-Worn Sensors—An “Active Period Analysis” |
| title_full | Quantifying Circadian Aspects of Mobility-Related Behavior in Older Adults by Body-Worn Sensors—An “Active Period Analysis” |
| title_fullStr | Quantifying Circadian Aspects of Mobility-Related Behavior in Older Adults by Body-Worn Sensors—An “Active Period Analysis” |
| title_full_unstemmed | Quantifying Circadian Aspects of Mobility-Related Behavior in Older Adults by Body-Worn Sensors—An “Active Period Analysis” |
| title_short | Quantifying Circadian Aspects of Mobility-Related Behavior in Older Adults by Body-Worn Sensors—An “Active Period Analysis” |
| title_sort | quantifying circadian aspects of mobility related behavior in older adults by body worn sensors an active period analysis |
| topic | circadian motor behavior body-worn sensors older adults |
| url | https://www.mdpi.com/1424-8220/21/6/2121 |
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