Differences in Life Space Activity Patterns Between Older Adults With Mild Cognitive Impairment Living Alone or as a Couple: Cohort Study Using Passive Activity Sensing.

2-person home activities of daily living activity pattern aging at home cognition cognitive impairment daily activities digital health elder geriatric gerontology in-home sensor life space activity mild cognitive impairment old age older adult passive monitoring sensor technology

Journal

JMIR aging
ISSN: 2561-7605
Titre abrégé: JMIR Aging
Pays: Canada
ID NLM: 101740387

Informations de publication

Date de publication:
11 Oct 2023
Historique:
received: 23 01 2023
accepted: 12 09 2023
revised: 18 08 2023
medline: 11 10 2023
pubmed: 11 10 2023
entrez: 11 10 2023
Statut: epublish

Résumé

Measuring function with passive in-home sensors has the advantages of real-world, objective, continuous, and unobtrusive measurement. However, previous studies have focused on 1-person homes only, which limits their generalizability. This study aimed to compare the life space activity patterns of participants living alone with those of participants living as a couple and to compare people with mild cognitive impairment (MCI) with cognitively normal participants in both 1- and 2-person homes. Passive infrared motion sensors and door contact sensors were installed in 1- and 2-person homes with cognitively normal residents or residents with MCI. A home was classified as an MCI home if at least 1 person in the home had MCI. Time out of home (TOOH), independent life space activity (ILSA), and use of the living room, kitchen, bathroom, and bedroom were calculated. Data were analyzed using the following methods: (1) daily averages over 4 weeks, (2) hourly averages (time of day) over 4 weeks, or (3) longitudinal day-to-day changes. In total, 129 homes with people living alone (n=27, 20.9%, MCI and n=102, 79.1%, no-MCI homes) and 52 homes with people living as a couple (n=24, 46.2%, MCI and n=28, 53.8%, no-MCI homes) were included with a mean follow-up of 719 (SD 308) days. Using all 3 analysis methods, we found that 2-person homes showed a shorter TOOH, a longer ILSA, and shorter living room and kitchen use. In MCI homes, ILSA was higher in 2-person homes but lower in 1-person homes. The effects of MCI status on other outcomes were only found when using the hourly averages or longitudinal day-to-day changes over time, and they depended on the household type (alone vs residing as a couple). This study shows that in-home behavior is different when a participant is living alone compared to when they are living as a couple, meaning that the household type should be considered when studying in-home behavior. The effects of MCI status can be detected with in-home sensors, even in 2-person homes, but data should be analyzed on an hour-to-hour basis or longitudinally.

Sections du résumé

BACKGROUND BACKGROUND
Measuring function with passive in-home sensors has the advantages of real-world, objective, continuous, and unobtrusive measurement. However, previous studies have focused on 1-person homes only, which limits their generalizability.
OBJECTIVE OBJECTIVE
This study aimed to compare the life space activity patterns of participants living alone with those of participants living as a couple and to compare people with mild cognitive impairment (MCI) with cognitively normal participants in both 1- and 2-person homes.
METHODS METHODS
Passive infrared motion sensors and door contact sensors were installed in 1- and 2-person homes with cognitively normal residents or residents with MCI. A home was classified as an MCI home if at least 1 person in the home had MCI. Time out of home (TOOH), independent life space activity (ILSA), and use of the living room, kitchen, bathroom, and bedroom were calculated. Data were analyzed using the following methods: (1) daily averages over 4 weeks, (2) hourly averages (time of day) over 4 weeks, or (3) longitudinal day-to-day changes.
RESULTS RESULTS
In total, 129 homes with people living alone (n=27, 20.9%, MCI and n=102, 79.1%, no-MCI homes) and 52 homes with people living as a couple (n=24, 46.2%, MCI and n=28, 53.8%, no-MCI homes) were included with a mean follow-up of 719 (SD 308) days. Using all 3 analysis methods, we found that 2-person homes showed a shorter TOOH, a longer ILSA, and shorter living room and kitchen use. In MCI homes, ILSA was higher in 2-person homes but lower in 1-person homes. The effects of MCI status on other outcomes were only found when using the hourly averages or longitudinal day-to-day changes over time, and they depended on the household type (alone vs residing as a couple).
CONCLUSIONS CONCLUSIONS
This study shows that in-home behavior is different when a participant is living alone compared to when they are living as a couple, meaning that the household type should be considered when studying in-home behavior. The effects of MCI status can be detected with in-home sensors, even in 2-person homes, but data should be analyzed on an hour-to-hour basis or longitudinally.

Identifiants

pubmed: 37819694
pii: v6i1e45876
doi: 10.2196/45876
pmc: PMC10600648
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e45876

Subventions

Organisme : NIA NIH HHS
ID : P30 AG066518
Pays : United States
Organisme : NIA NIH HHS
ID : P30 AG008017
Pays : United States
Organisme : NIA NIH HHS
ID : RF1 AG022018
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG017917
Pays : United States
Organisme : NIA NIH HHS
ID : U2C AG054397
Pays : United States

Informations de copyright

©Marijn Muurling, Wan-Tai M Au-Yeung, Zachary Beattie, Chao-Yi Wu, Hiroko Dodge, Nathaniel K Rodrigues, Sarah Gothard, Lisa C Silbert, Lisa L Barnes, Joel S Steele, Jeffrey Kaye. Originally published in JMIR Aging (https://aging.jmir.org), 11.10.2023.

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Auteurs

Marijn Muurling (M)

Department of Neurology, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC locatie VUmc, Amsterdam, Netherlands.
Amsterdam Neuroscience - Neurodegeneration, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.

Wan-Tai M Au-Yeung (WM)

Oregon Center for Aging & Technology, Oregon Health & Science University, Portland, OR, United States.
Layton Aging & Alzheimer's Disease Research Center, Oregon Health & Science University, Portland, OR, United States.
Department of Neurology, Oregon Health & Science University, Portland, OR, United States.

Zachary Beattie (Z)

Oregon Center for Aging & Technology, Oregon Health & Science University, Portland, OR, United States.
Layton Aging & Alzheimer's Disease Research Center, Oregon Health & Science University, Portland, OR, United States.
Department of Neurology, Oregon Health & Science University, Portland, OR, United States.

Chao-Yi Wu (CY)

Oregon Center for Aging & Technology, Oregon Health & Science University, Portland, OR, United States.
Layton Aging & Alzheimer's Disease Research Center, Oregon Health & Science University, Portland, OR, United States.
Department of Neurology, Oregon Health & Science University, Portland, OR, United States.
Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.

Hiroko Dodge (H)

Oregon Center for Aging & Technology, Oregon Health & Science University, Portland, OR, United States.
Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.

Nathaniel K Rodrigues (NK)

Oregon Center for Aging & Technology, Oregon Health & Science University, Portland, OR, United States.
Layton Aging & Alzheimer's Disease Research Center, Oregon Health & Science University, Portland, OR, United States.
Department of Neurology, Oregon Health & Science University, Portland, OR, United States.

Sarah Gothard (S)

Oregon Center for Aging & Technology, Oregon Health & Science University, Portland, OR, United States.
Layton Aging & Alzheimer's Disease Research Center, Oregon Health & Science University, Portland, OR, United States.
Department of Neurology, Oregon Health & Science University, Portland, OR, United States.

Lisa C Silbert (LC)

Oregon Center for Aging & Technology, Oregon Health & Science University, Portland, OR, United States.
Layton Aging & Alzheimer's Disease Research Center, Oregon Health & Science University, Portland, OR, United States.
Department of Neurology, Oregon Health & Science University, Portland, OR, United States.
Department of Neurology, Portland Veterans Affairs Medical Center, Portland, OR, United States.

Lisa L Barnes (LL)

Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, United States.

Joel S Steele (JS)

Oregon Center for Aging & Technology, Oregon Health & Science University, Portland, OR, United States.
Layton Aging & Alzheimer's Disease Research Center, Oregon Health & Science University, Portland, OR, United States.
Department of Neurology, Oregon Health & Science University, Portland, OR, United States.
Indigenous Health Department, University of North Dakota, Grand Forks, ND, United States.

Jeffrey Kaye (J)

Oregon Center for Aging & Technology, Oregon Health & Science University, Portland, OR, United States.
Layton Aging & Alzheimer's Disease Research Center, Oregon Health & Science University, Portland, OR, United States.
Department of Neurology, Oregon Health & Science University, Portland, OR, United States.

Classifications MeSH