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Examining the Health Risk Pathways Between Discrimination and Accelerated Biological Aging Among a Population-Based
Francisco Rios Casas1,2, Christy L Erving1,2, Mateo P Farina2,3
1Department of Sociology, The University of Texas at Austin, Austin, Texas, USA.
Objective:
Discrimination is a prominent stressor among older adults tied to a greater risk of disability, morbidity, and mortality. However, the underlying biological mechanisms by which discrimination impacts health outcomes are not clear. We investigated the relationship between discrimination and accelerated biological aging. We also evaluated the sensitivity of that association to the inclusion of potential health risk pathways, which link discrimination to accelerated biological aging.
Methods:
Data on frequency and attributions for everyday discrimination came from the Health and Retirement Study (2012-2014). Biological age was estimated using 22 blood-based biomarkers collected in the 2016 Venous Blood Study. We used linear regression models to examine the association between discrimination and accelerated biological age. We used the Karlson, Holm, and Breen decomposition method to investigate what portion of the association was explained by key health risk pathways (depression, sleep, physical activity, body mass index, and smoking).
Results:
Sixty-three percent of participants reported discrimination, attributing it mostly to their age (27%), gender (13%), or financial status (12%). Respondents reporting higher frequency of discrimination had a biological age 0.66 years older than their chronological age (p < .001). Respondents with more attributions for discrimination had an accelerated biological age of 0.61 years (p < .001). Adjustment for health risk pathways explained a statistically significant (p < .001) portion of the association for both aspects of discrimination: ~94% for frequency and ~55% for attributions.
Discussion:
Discrimination attributed to various social characteristics can accelerate aging and, in turn, undermine health, but the association is highly modifiable, pointing to the potential importance of interventions to reduce health inequalities.
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