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Annu Rev Sociol. 2018 Jul;44(1):319-340. doi: 10.1146/annurev-soc-060116-053403. Epub 2018 May 16.
2
Allostatic Load and Its Impact on Health: A Systematic Review.应激适应负荷及其对健康的影响:系统评价。
Psychother Psychosom. 2021;90(1):11-27. doi: 10.1159/000510696. Epub 2020 Aug 14.
3
Sex Differences and Gender Diversity in Stress Responses and Allostatic Load Among Workers and LGBT People.应激反应和压力负荷中的性别差异和性别多样性:工人和 LGBT 人群的比较
Curr Psychiatry Rep. 2019 Oct 19;21(11):110. doi: 10.1007/s11920-019-1104-2.
4
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5
Social stratification and allostatic load: shapes of health differences in the MIDUS study in the United States.社会分层与应激负荷:美国 MIDUS 研究中的健康差异形态。
J Biosoc Sci. 2019 Sep;51(5):627-644. doi: 10.1017/S0021932018000378. Epub 2019 Jan 28.
6
Allostatic Load: Importance, Markers, and Score Determination in Minority and Disparity Populations.应激激素负荷:少数民族和差异人群中的重要性、标志物和评分确定。
J Urban Health. 2019 Mar;96(Suppl 1):3-11. doi: 10.1007/s11524-019-00345-5.
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Early life predictors of midlife allostatic load: A prospective cohort study.中年时期压力负荷的早期生活预测因素:一项前瞻性队列研究。
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比较中年时期测量的应激负荷的不同操作性定义及其与种族和累积生活经历社会经济地位的模式。

Comparing different operationalizations of allostatic load measured in mid-life and their patterning by race and cumulative life course socioeconomic status.

机构信息

Department of Epidemiology, Mailman School of Public Health, New York, NY, USA.

Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA.

出版信息

Psychoneuroendocrinology. 2022 May;139:105689. doi: 10.1016/j.psyneuen.2022.105689. Epub 2022 Feb 12.

DOI:10.1016/j.psyneuen.2022.105689
PMID:35202971
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8977239/
Abstract

Since its conceptualization, there has been a lack of consensus on the best way to operationalize allostatic load (AL). As a marker of the cumulative, physiological wear and tear on the body resulting from chronic exposure to stressors, it follows that AL should be higher among people who have faced more stressful life experiences. Thus, the purpose of this study was to construct AL scores using different operationalizations and, as a measure of construct validity, compare whether each construction produced expected disparities in AL by race and a composite socioeconomic status (SES) variable which accounts for measures over the life course; we also explored differences by sex. We conducted the study in a sample of 45-52-year-old offspring from the Child Health and Development Studies, a longitudinal birth cohort established in the early 1960s. AL scores were constructed in 6 different ways and included 10 biomarkers from inflammatory, neuroendocrine, cardiovascular, and metabolic systems. Our main approach to constructing AL was to sum across high-risk biomarker quartiles, correct for medication use, and use sex-specific high-risk quartiles for specific biomarkers. Alternative constructions did not use sex-specific quartiles and/or weighted biomarkers within subsystems and/or did not correct for medication use. We estimated differences in AL scores by race, SES, sex and their pairwise interactions. All constructions of AL, including the main approach, produced expected disparities by race (higher scores for Black vs. non-Black participants) and life course SES (higher scores for low vs. high SES participants). However, disparities by sex only emerged when the AL score was constructed via approaches that did not use sex-specific high-risk quartiles; for these alternative constructions, overall, female participants had higher AL scores than male participants and Black female participants had the highest AL scores in the sample. For most constructions, the pairwise interaction between sex and SES, showed a stronger disparity in AL scores between low and high-SES female compared with low- and high-SES male participants; this suggests that, in terms of lowering AL, high life course SES may be more important for female than male participants. In conclusion, our results suggest that the basic AL concept is consistently expressed in different operationalizations, making it an especially useful and robust tool for understanding disparities by race and SES.

摘要

自概念提出以来,对于如何操作化应激负荷(allostatic load,AL)一直缺乏共识。作为一种标记,它反映了人体在长期暴露于压力源下所经历的生理磨损。因此,我们假设,经历过更多压力生活经历的人,其 AL 水平应该更高。因此,本研究的目的是使用不同的操作化方法构建 AL 分数,并将其作为结构有效性的一种衡量标准,比较每种构建方法是否会因种族和综合社会经济地位(socioeconomic status,SES)变量而产生预期的 AL 差异,该变量涵盖了整个生命过程中的衡量标准;我们还探讨了性别差异。我们在儿童健康与发展研究的样本中进行了这项研究,该研究是一个 20 世纪 60 年代初建立的纵向出生队列。AL 分数通过 6 种不同的方式构建,包括来自炎症、神经内分泌、心血管和代谢系统的 10 种生物标志物。我们构建 AL 的主要方法是将高风险生物标志物四分位数相加,校正药物使用情况,并为特定生物标志物使用性别特异性的高风险四分位数。替代构建方法不使用性别特异性四分位数和/或加权生物标志物在子系统内,也不校正药物使用情况。我们估计了 AL 分数在种族、SES、性别及其两两交互作用上的差异。所有的 AL 构建方法,包括主要方法,都产生了预期的种族差异(黑人参与者的分数高于非黑人参与者)和生命过程 SES 差异(低 SES 参与者的分数高于高 SES 参与者)。然而,只有当 AL 分数是通过不使用性别特异性高风险四分位数的方法构建时,性别差异才会出现;对于这些替代构建方法,总体而言,女性参与者的 AL 分数高于男性参与者,而黑人女性参与者的 AL 分数在样本中最高。对于大多数构建方法,性别和 SES 的两两交互作用显示,低 SES 和高 SES 的女性参与者之间的 AL 分数差异比低 SES 和高 SES 的男性参与者更大;这表明,就降低 AL 而言,高生命过程 SES 对女性参与者可能比男性参与者更重要。总之,我们的研究结果表明,基本的 AL 概念在不同的操作化方法中得到了一致的表达,这使其成为理解种族和 SES 差异的一种特别有用和稳健的工具。