Intersecting race/ethnicity and gender in physiological dysregulation profiles and associations with socioeconomic status among older adults in the United States.
| Year of Publication |
2025
|
|---|---|
| Author | |
| Journal |
SSM Popul Health
|
| Volume |
30
|
| Number of Pages |
101812
|
| ISSN Number |
2352-8273
|
| Abstract |
Allostatic load, a cumulative indicator of physiological wear and tear resulting from chronic stress, is a robust predictor of disease and mortality risk. While prior research has documented racial/ethnic and gender variations in allostatic load, typically assessed by counting biomarkers at extreme levels, few studies have used latent class analysis (LCA) to examine multi-system physiological dysregulation or tested whether these patterns differ across the intersection of race/ethnicity and gender. This study analyzed data from 5743 Black and White adults aged 50 and older in the Health and Retirement Study to address this gap. Based on eight biomarkers representing metabolic, cardiovascular, and inflammatory systems, LCA identified four distinct dysregulation patterns that varied significantly by race and gender. The four classes included: (1) a class, identified across all groups but most prevalent among Black men; (2) a class, identified specifically among Black men and White women; (3) a class, observed in both Black and White women; and (4) a class, observed among Black women and White men. Association analyses revealed that higher educational attainment was significantly linked to reduced odds of metabolic-related dysregulation in all groups except Black men, underscoring the limitations of education alone in mitigating health risks for this group. These findings emphasize the value of an intersectionality framework for understanding how race and gender jointly shape physiological dysregulation patterns and highlight the need for tailored public health strategies that address the specific health risks faced by different population subgroups. |
| DOI |
10.1016/j.ssmph.2025.101812
|
| PMID |
40469922
|
| PMCID |
PMC12135385
|
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