Diverse Daily Activity Patterns - Examining Daily Activity Sequences and Activity Diversity in Older Adults - Abstract

Q: How were daily activity patterns measured in older adults?

Older adults completed an experience sampling study embedded in the Berlin Aging Study II, reporting activities six times per day over seven consecutive days.

Q: What method was used to identify common activity sequence patterns?

Sequence analysis combined with distance metrics compared how dissimilar each day’s sequence was, followed by cluster analysis to identify eight common patterns.

Q: Which activity pattern was most associated with better quality sleep?

Days dominated by physical and domestic work predicted better quality sleep compared with days dominated by leisure, self-care, social, or mental activities.

Sep 29, 2026

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Daily activity diversity is linked to healthy aging outcomes, but daily activity sequences may reveal which time-use patterns are most beneficial. This study used experience sampling within the Berlin Aging Study II (N=140, mean age 77.09, seven days; 879 daily sequences) with self-reported social, mental, leisure, physical, self-care, domestic, and productive activities sampled six times per day. Sequence analysis and distance-based clustering identified eight common sequence patterns. Patterns dominated by physical and domestic work predicted better quality sleep than patterns dominated by leisure, self-care, social, and mental activities.

LanguageEnglish

CategoryExam

FormatPDF

Pages1

Reading Time3 min

AccessFree to download

Abstract

Study design and data collection

Sequence analysis and clustering

Key sleep outcomes

Innovation in Aging, 2025, Vol. 9, No. S2 469 Abstract citation ID: igaf122.1603 DIVERSE DAILY ACTIVITY PATTERNS: EXAMINING DAILY ACTIVITY SEQUENCES AND ACTIVITY DIVERSITY IN OLDER ADULTS Rachel Koffer1, Sandra Duezel2, Denis Gerstorf3, Ilja Demuth2, Ulman Lindenberger4, Soomi Lee5, and Johanna Drewelies3, 1. Arizona State University, Phoenix, Arizona, United States, 2. Charité - Universitätsmedizin Berlin, Berlin, Berlin, Germany, 3. Humboldt University Berlin, Humboldt University Berlin, Berlin, Germany, 4. Max Planck Institute for Human Development, Berlin, Berlin, Germany, 5. The Pennsylvania State University, University Park, Pennsylvania, United States While daily activity diversity has been widely associated with healthy aging outcomes, further examination of daily activity patterns can uncover daily time use that is most beneficial for older adults. This study identified distinct daily activity sequencesand examined whether they were associated with better quality sleep that night. Using a sample of older adults who participated in an experience sampling study embedded into the Berlin Aging Study II (N = 140, Mage = 77.09, range: 67–88 years), we applied sequence analysis to self-reported activity data (social, mental, leisure, physical, self-care, domestic, and productive activities) collected six times per day over seven consecutive days (N = 879 daily sequences) . Distance metrics identified how dissimilar each day’s sequence was from each other day. Using cluster analysis of the distance metrics, we identified 8 common sequence patterns. Days with activity patterns dominated by physical and domestic work predicted better quality sleep than days with patterns dominated by leisure (B = -2.10, p = .004), self-care (B = -5.33, p < .001), social (B = -3.65, p < .001), and mental activities (B = -2.91, p = .01) . Findings controlled for comorbidities, age, gender, education, and weekday. Further, the likelihood of each sequence pattern differed across age and traditional measures of activity diversity. Daily activities in later life vary not just in diversity of types but also in the sequential patterns in which they occur throughout the day. Findings highlight the benefit of examining daily activity sequences in addition to activity diversity.

FAQs

How were daily activity patterns measured in older adults?

Older adults completed an experience sampling study embedded in the Berlin Aging Study II, reporting activities six times per day over seven consecutive days.

What method was used to identify common activity sequence patterns?

Sequence analysis combined with distance metrics compared how dissimilar each day’s sequence was, followed by cluster analysis to identify eight common patterns.

Which activity pattern was most associated with better quality sleep?

Days dominated by physical and domestic work predicted better quality sleep compared with days dominated by leisure, self-care, social, or mental activities.

Sep 29, 2026

Upload by Bintang