Evidence map›Paper›PMID 42010472›Full record

ArticleEuropean review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity2026

Not just how much, but how it's done: movement activity bout distributions and everyday cognition in older adults with elevated dementia risk.

Chih-Hsiang Yang, Jonathan George Hakun, Sunwoo Emma Cho, Jongwon Lee, Halle Prine, Donna Coffman, Rahul Ghosal

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Article in European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Chih-Hsiang YangUniversity of South Carolina, Columbia, USA. cy11@mailbox.sc.edu.
Jonathan George HakunThe Pennsylvania State University, Hershey, USA.
Sunwoo Emma ChoUniversity of South Carolina, Columbia, USA.
Jongwon LeeUniversity of South Carolina, Columbia, USA.
Halle PrineUniversity of South Carolina, Columbia, USA.
Donna CoffmanUniversity of South Carolina, Columbia, USA.
Rahul GhosalUniversity of South Carolina, Columbia, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPhysical activity (PA) is a protective factor of brain health. Existing literature has predominately examined total PA volume or sedentary time in relation to cognitive health, with limited attention to the distributional features of the movement activity bouts. Variability in the duration of daily movement activity bouts may influence cognitive function beyond total exposure to PA or sedentary time. This study investigates whether daily PA and sedentary bout distributions are associated with daily cognitive function in older adults, and further explores whether these associations differ across the days of the week.

methodsOlder adults (n = 87, age = 68.5 ± 7.0 years, 38% male, 21% non-White) with elevated dementia risk completed 14 days of ecological momentary assessment (EMA). Participants wore an accelerometer (activPAL) and completed smartphone-based cognitive assessments of processing speed four times each day. The number and duration of sedentary, light (LPA), or moderate-to-vigorous physical activity (MVPA) bouts (≥ 1 min) were calculated from the activPAL data. Median response time (RT) and number of correct trials from the symbol search task were aggregated at the day level. Two distributional indicators (alpha and Gini) were each calculated for daily sedentary, LPA, and MVPA bouts to investigate their associations with the symbol search outcomes. Functional regression models examined the associations between the distributional indicators and cognitive outcomes by each day of the week (Sunday-Saturday).

resultsOn most weekdays, higher Gini (greater variations) in daily MVPA bout length was associated with faster RT (p<.001, R2=0.138); higher Gini of daily LPA bout length was also associated with more accurate trials (p<.05, R2=0.022). Conversely, higher Gini in daily sedentary bout length was associated with slower RT (p<.05, R2=0.164).

conclusionsThis study provides proof-of-concept that the distribution of daily movement behavior bouts is associated with variations in daily cognition. It also illustrates how integrating accelerometry with repeated ambulatory cognitive measures can capture within-person dynamics. The findings can support future research to examine whether specific daily movement patterns may represent appropriate targets for interventions aimed at promoting cognitive health in older adults.

Indexed as

Activity pattern metricsAmbulatory cognitive assessmentBrain healthFunctional regression modelTime-varying associationsWeekday-weekend contexts

Identifiers

PMID42010472
PMCPMC13227851

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.