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社会支持、社会融合与炎性细胞因子:一项荟萃分析。

Social support, social integration, and inflammatory cytokines: A meta-analysis.

机构信息

Department of Psychology.

出版信息

Health Psychol. 2018 May;37(5):462-471. doi: 10.1037/hea0000594. Epub 2018 Mar 22.

Abstract

OBJECTIVE

Social support and social integration have been linked to lower rates of morbidity and mortality. However, the biological mechanisms responsible for such links need greater attention to advance theory and unique intervention opportunities. The main aim of this article was to conduct a meta-analytic review of the association between social support-social integration and inflammatory cytokines (e.g., interleukin-6, C-reactive protein) and test several proposed moderators from prior qualitative reviews.

METHOD

A literature search was conducted using the ancestry approach and with databases PsycINFO, Medline, and EMBASE by crossing the exact keywords or with . The review identified 41 studies with a total of 73,037 participants.

RESULTS

The omnibus meta-analysis showed that social support-social integration were significantly related to lower levels of inflammation (Zr = -.073). These results were not moderated by the operationalization of social relationships or the type of population, cytokine, and design.

CONCLUSIONS

These data suggest that inflammation is at least one important biological mechanism linking social support and social integration to the development and course of disease. Future work should continue to build on this review and address next-generation questions regarding antecedent processes, mechanisms, and other potential moderators. (PsycINFO Database Record

摘要

目的

社会支持和社会融合与较低的发病率和死亡率有关。然而,为了推进理论和独特的干预机会,需要更多关注负责这些关联的生物学机制。本文的主要目的是对社会支持-社会融合与炎症细胞因子(例如白细胞介素-6、C 反应蛋白)之间的关联进行荟萃分析综述,并检验之前定性综述中提出的几种调节变量。

方法

采用追溯法进行文献检索,使用 PsycINFO、Medline 和 EMBASE 数据库,通过交叉使用确切的关键词 或 。该综述确定了 41 项研究,共有 73037 名参与者。

结果

总体荟萃分析表明,社会支持-社会融合与较低的炎症水平显著相关(Zr=-.073)。这些结果不受社会关系的操作化或人口、细胞因子和设计类型的影响。

结论

这些数据表明,炎症至少是将社会支持和社会融合与疾病的发生和进程联系起来的一个重要生物学机制。未来的工作应继续在此综述的基础上进行,并解决关于前因过程、机制和其他潜在调节变量的下一代问题。

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