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应激负荷与心理健康:生理失调的潜在类别分析。

Allostatic load and mental health: a latent class analysis of physiological dysregulation.

机构信息

School of Social Work, Integrative Biosciences (IBio) Center, Wayne State University, Detroit, MI, USA.

出版信息

Stress. 2021 Jul;24(4):394-403. doi: 10.1080/10253890.2020.1813711. Epub 2020 Sep 4.

DOI:10.1080/10253890.2020.1813711
PMID:32835575
Abstract

This study explored the associations between specific profiles of biological dysregulation and mental health outcomes in a national, community sample of healthy adults in the United States. A latent class analysis of data from the Midlife Development in the United States study ( = 1,757) was conducted to determine classes of biological dysregulation. Multinomial logistic regressions of class membership were employed to determine associations with measures related to depression, including whether or not individuals had sought treatment, Center for Epidemiological Studies Depression Scale, and both the generalized distress and anhedonia subscales of the Mood and Anxiety Symptoms Questionnaire. Four classes of dysregulation emerged: baseline/low dysregulation, metabolic and inflammatory dysregulation, parasympathetic dysregulation, and SAM pathway dysregulation. Individuals who met the criteria for depression measures were more likely to be in the metabolic and immune dysregulation and parasympathetic dysregulation groups as compared to the baseline group. The results suggest that mental health outcomes, such as depression, are differentially associated with specific profiles of biological dysregulation. A more nuanced approach to profiles of dysregulation could better inform treatment decisions.Lay summaryHigher levels of allostatic load, which represents the cumulative wear and tear of exposure to stress, are associated with increased rates of depression and anhedonia. Specifically, parasympathetic dysregulation and immunometabolic dysregulation are associated with negative mental health outcomes.

摘要

本研究旨在探讨美国全国性社区健康成年人样本中生物失调特定模式与心理健康结果之间的关联。采用潜在类别分析方法对来自美国中年发展研究( = 1757)的数据进行分析,以确定生物失调的类别。采用多项逻辑回归分析来确定与抑郁相关的措施与类别成员之间的关联,包括个体是否寻求治疗、流行病学研究中心抑郁量表、心境与焦虑症状问卷的一般困扰和快感缺失子量表。共出现 4 种失调类别:基线/低度失调、代谢和炎症失调、副交感神经失调以及 SAM 通路失调。与基线组相比,符合抑郁测量标准的个体更有可能处于代谢和免疫失调以及副交感神经失调组。研究结果表明,心理健康结果(如抑郁)与特定的生物失调模式存在差异关联。更细致的失调模式方法可以更好地为治疗决策提供信息。

非专业人士请谨慎参考译文,译文可能存在错误。

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