Evidence map›Paper›PMID 42268661›Full record

ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2026

Associations of accelerometry-derived time in major activity intensities with cognitive outcomes: a compositional data analysis approach.

Daniel Callow, Jill A Rabinowitz, Xinkai Zhou, Xiaowen Chen, Ryan Dougherty, Ciprian Crainiceanu, Lacey Etzkorn, Amal A Wanigatunga, Sarah K Wanigatunga, Adam P Spira and 2 more

Abstract read
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Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Daniel CallowDepartment of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States.
Jill A RabinowitzDepartment of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey, United States.ORCID 0000-0002-3674-8032
Xinkai ZhouDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States.
Xiaowen ChenDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States.
Ryan DoughertyDepartment of Kinesiology and Health, Rutgers University, New Brunswick, New Jersey, United States.
Ciprian CrainiceanuDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States.
Lacey EtzkornDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States.
Amal A WanigatungaDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States.ORCID 0000-0002-5763-5184
Sarah K WanigatungaDepartment of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States.
Adam P SpiraDepartment of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States.ORCID 0000-0003-1507-0995
Jennifer A SchrackCenter on Aging & Health, Johns Hopkins University, Baltimore, Maryland, United States.ORCID 0000-0001-9244-9267
Vadim ZipunnikovDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States.

Funding

Research Education ComponentP30AG066507 · NIA · JOHNS HOPKINS UNIVERSITY · PI Corinne Pettigrew · 2020 to 2026
$29.3M
NIA NIH HHS P30 AG066507
6 · The paper itself

Abstract

backgroundPhysical activity (PA), sedentary behavior (SB), and sleep are modifiable lifestyle factors linked to cognitive health. Prior research has largely relied on self-report to measure these constructs or ignored the compositional nature of these data. We applied compositional data analysis (CoDA) to quantify the association between accelerometry-derived measures of time in major activity domains and cognitive outcomes among older adults.

methodsParticipants were 927 older adults (Mage = 82.71 years, SD = 3.99, range = 76-95) from the Atherosclerosis Risk in Communities (ARIC) study who wore wrist-worn accelerometers and completed cognitive assessments. Major activity domains were time in bed and time out of bed, which were divided into 4 categories: SB, low-light (low-LIPA), high-light (high-LIPA), and moderate-to-vigorous physical activity (MVPA). Cognitive outcomes included global cognition, memory, executive function, and language performance.

resultsAcross all cognitive domains, greater time spent in MVPA relative to other activity domains, including out-of-bed time, SB, and low-LIPA, was associated with better cognitive performance. In contrast, greater time spent in low-LIPA relative to other activity domains was consistently associated with poorer performance across all cognitive domains, and these associations were attenuated, but remained statistically significant, after adjustment for gait speed. Sedentary behavior was negatively associated with executive function only.

conclusionsThe trade-off between time spent in MVPA and in low-LIPA is the objectively measured PA that was most strongly associated with cognitive abilities. Time spent in low-LIPA may be an important biomarker of physical health and cognitive impairment.

Indexed as

AccelerometryCognitionExerciseLightingTime FactorsAgedAged, 80 and overData AnalysisFemaleGeriatric AssessmentHumansMaleMental Status and Dementia TestsPhysical ExertionSedentary BehaviorSleepCognitionOlder adultsPhysical activitySedentary behavior

Identifiers

PMID42268661
PMCPMC13316422

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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 OpenQuestion graph.