Zhang Xiaoyan, Krobath Danielle M, Tembo Penias, Cuevas Adolfo G
Department of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, USA.
Department of Epidemiology & Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, USA.
SSM Popul Health. 2025 Apr 26;30:101812. doi: 10.1016/j.ssmph.2025.101812. eCollection 2025 Jun.
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.
应激负荷是慢性应激导致的生理磨损的累积指标，是疾病和死亡风险的有力预测指标。虽然先前的研究记录了应激负荷在种族/族裔和性别方面的差异，通常是通过对极端水平的生物标志物进行计数来评估，但很少有研究使用潜在类别分析（LCA）来检查多系统生理失调，或测试这些模式在种族/族裔和性别的交叉点上是否不同。本研究分析了健康与退休研究中5743名50岁及以上黑人和白人成年人的数据，以填补这一空白。基于代表代谢、心血管和炎症系统的八种生物标志物，LCA确定了四种不同的失调模式，这些模式在种族和性别上有显著差异。这四个类别包括：（1）一个在所有群体中都有发现但在黑人男性中最为普遍的类别；（2）一个专门在黑人男性和白人女性中发现的类别；（3）一个在黑人女性和白人女性中都观察到的类别；（4）一个在黑人女性和白人男性中观察到的类别。关联分析显示，除黑人男性外，在所有群体中，较高的教育程度与代谢相关失调几率的降低显著相关，这突出了仅靠教育在减轻该群体健康风险方面的局限性。这些发现强调了交叉性框架对于理解种族和性别如何共同塑造生理失调模式的价值，并强调了制定针对不同人群亚组所面临的特定健康风险的公共卫生策略的必要性。
