Physical activity fragmentation and functional decline among older adults: Findings from the National Health and Aging Trends Study.

Authors

Nicholas R Lamoureux, Joey M Saavedra, Brian Downer, Jennifer A Schrack, Amal A Wanigatunga

Published in

The journals of gerontology. Series A, Biological sciences and medical sciences. Jul 09, 2026. Epub Jul 09, 2026.

Abstract

Physical activity fragmentation is associated with poor physical function in older adulthood, but the relationship between changes in physical activity fragmentation with concurrent and future changes in physical function are unclear, and this information is important for guiding clinical decision making. We therefore characterized this relationship in a nationally representative sample of older adults.
Data were drawn from a subset of the National Health and Aging Trends Study. Activity fragmentation was defined as the probability of transitioning from an active to a sedentary bout, captured using wrist-worn actigraphy, while function was assessed using the Short Physical Performance Battery (SPPB). The association between physical activity fragmentation with any instance of longitudinal decline in SPPB was evaluated using multivariable logistic regression.
The sample included 531 participants aged ≥70 years (55.4% female). Among those with baseline SPPB ≤ 6, higher baseline activity fragmentation was associated with lower baseline function overall, and with a 1-year future decline in function (adjusted OR: 1.32; 95% CI: 1.01-1.72 per 10% higher baseline fragmentation). A 1-year increase in fragmentation was associated with a greater likelihood of experiencing a concurrent decline in SPPB, particularly among those with baseline SPPB = 7-10 (OR: 2.21; 95% CI: 1.17-4.17). The 1-year change in activity fragmentation was not associated with declines in SPPB the following year.
Physical activity fragmentation may represent a digital biomarker, rather than an antecedent, of changes in physical function, highlighting the potential utility of accelerometry for identifying at-risk phenotypes likely to benefit from early interventions.

PMID:
42423287
Bibliographic data and abstract were imported from PubMed on 09 Jul 2026.

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