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Toward a context-aware geroscience: integrating structural and social context into aging biology.

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Τίτλος: Toward a context-aware geroscience: integrating structural and social context into aging biology.
Συγγραφείς: Bellizzi KM; Department of Human Development and Family Sciences, University of Connecticut, Storrs, Connecticut, United States., Kuchel GA; UConn Center on Aging, University of Connecticut Health Center, Farmington, Connecticut, United States., Redeker NS; Elisabeth DeLuca School of Nursing, University of Connecticut, Storrs, Connecticut, United States., Nwakasi C; Department of Human Development and Family Sciences, University of Connecticut, Storrs, Connecticut, United States.
Πηγή: The Gerontologist [Gerontologist] 2026 Aug 05; Vol. 66 (9).
Τύπος έκδοσης: Journal Article
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Oxford University Press Country of Publication: United States NLM ID: 0375327 Publication Model: Print Cited Medium: Internet ISSN: 1758-5341 (Electronic) Linking ISSN: 00169013 NLM ISO Abbreviation: Gerontologist Subsets: MEDLINE
Imprint Name(s): Publication: 2009- : Cary, NC : Oxford University Press
Original Publication: St. Louis, Gerontological Society.
Ιατρικοί όροι (MeSH): Aging*/physiology , Geroscience* , Social Environment*, Humans ; Biomarkers
Περίληψη: Biological hallmarks of aging are increasingly treated as modifiable targets, yet these processes are unevenly distributed across populations due to cumulative, socially patterned exposures. Chronic stress, environmental conditions, and differential access to health-promoting resources systematically influence inflammatory, metabolic, and epigenetic pathways, contributing to heterogeneity in biological aging trajectories. When geroscience models treat aging biology as context-neutral, biological variation may be interpreted without adequate consideration of the social and environmental conditions that shape it, introducing bias into inference. We distinguish three related forms of bias: mechanistic misattribution in causal inference, biased biomarker construction in measurement, and inequitable translational of interventions across heterogeneous exposure contexts. This reflects not only omitted-variable bias but also the possibility that exposure-patterned biological variation becomes embedded in how aging is measured, interpreted, and translated. For example, elevated inflammatory markers may reflect differing contributions of senescent cell burden, chronic psychosocial stress, environmental exposures, or related processes, illustrating how similar biological signals can arise through different exposure histories and biological mechanisms. We propose a multilevel, life-course framework that models structural, environmental, and behavioral influences as determinants of biological state and treatment response, providing a basis for improving inference, measurement validity, and equitable translation in geroscience.
(© The Author(s) 2026. Published by Oxford University Press on behalf of the Gerontological Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)
Contributed Indexing: Keywords: Biological aging; Geroscience; Health disparities; Social determinants
Substance Nomenclature: 0 (Biomarkers)
Entry Date(s): Date Created: 20260808 Date Completed: 20260826 Latest Revision: 20260908
Update Code: 20260909
DOI: 10.1093/geront/gnag179
PMID: 42568191
Βάση Δεδομένων: MEDLINE
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  Data: Biological hallmarks of aging are increasingly treated as modifiable targets, yet these processes are unevenly distributed across populations due to cumulative, socially patterned exposures. Chronic stress, environmental conditions, and differential access to health-promoting resources systematically influence inflammatory, metabolic, and epigenetic pathways, contributing to heterogeneity in biological aging trajectories. When geroscience models treat aging biology as context-neutral, biological variation may be interpreted without adequate consideration of the social and environmental conditions that shape it, introducing bias into inference. We distinguish three related forms of bias: mechanistic misattribution in causal inference, biased biomarker construction in measurement, and inequitable translational of interventions across heterogeneous exposure contexts. This reflects not only omitted-variable bias but also the possibility that exposure-patterned biological variation becomes embedded in how aging is measured, interpreted, and translated. For example, elevated inflammatory markers may reflect differing contributions of senescent cell burden, chronic psychosocial stress, environmental exposures, or related processes, illustrating how similar biological signals can arise through different exposure histories and biological mechanisms. We propose a multilevel, life-course framework that models structural, environmental, and behavioral influences as determinants of biological state and treatment response, providing a basis for improving inference, measurement validity, and equitable translation in geroscience.<br /> (© The Author(s) 2026. Published by Oxford University Press on behalf of the Gerontological Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)
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