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

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.