Social well-being is associated with slower multisystem aging estimated from a single brain MRI scan: prospective evidence from MIDUS

The science

Original title

Social well-being is associated with slower multisystem aging estimated from a single brain MRI scan: prospective evidence from MIDUS.

Authors

Lee M, Garza-Gonzalez SM, Schaefer SM et al.

Journal

Research square

Published

Oct 25, 2026

Study type

Study

PMID

42926665 ↗

DOI

10.21203/rs.3.rs-11292832/v1 ↗

Abstract

Subjective well-being is increasingly recognized as critical for health across the adult lifespan. Yet, it is unclear whether separable dimensions of well-being are differentially associated with biological aging. Using data from the Midlife in the United States (MIDUS) study ( N  = 213; age = 56.2 ± 13.6), we modeled the multifaceted structure of subjective well-being (i.e., private/eudaimonic, social, and hedonic well-being) and examined its prospective association with DunedinPACNI, a novel brain MRI-derived biomarker trained to estimate the pace of biological aging. We found that the social dimension of well-being was consistently associated with a slower pace of aging after sequentially controlling for demographic, health, lifestyle, and social covariates. Associations with private/eudaimonic well-being and hedonic well-being were rendered non-significant once health and lifestyle factors were accounted for. Data-driven variable selection further identified social well-being as the most stable predictor of DunedinPACNI among the well-being dimensions. Lastly, using community volunteering as an illustrative example of a modifiable, health-promoting behavior, we found an indirect association with a slower pace of aging via social well-being that was not detected when well-being was modeled as a broader construct. These findings suggest that a fine-grained characterization of subjective well-being may yield novel insights into the psychosocial mechanisms supporting healthy aging. They also provide the first evidence that psychosocial correlates of the pace of aging can be detected from a single structural MRI scan, which may extend the evidence base for aging research to cohorts that lack biospecimens.

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