社会关系对中风风险和中风后死亡率的影响:系统回顾和荟萃分析。

IF 3.5 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Mingxian Meng, Zheng Ma, Hangning Zhou, Yanming Xie, Rui Lan, Shirui Zhu, Deyu Miao, Xiaoming Shen
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引用次数: 0

摘要

背景:不良社会关系与脑卒中后死亡率之间的关系仍不确定,有关不良社会关系与脑卒中风险之间关系的证据也不一致。在这项荟萃分析中,我们旨在阐明与社会关系不良(包括社会隔离、有限的社会网络、缺乏社会支持和孤独)的人的卒中风险和卒中后死亡率有关的证据:方法: 对 PubMed、Embase 和 Cochrane 图书馆数据库进行全面检索,系统地确定相关研究。数据提取由两名研究人员独立完成。采用随机效应或固定效应模型计算汇总的几率比(OR)及 95% 的置信区间(CI)。为评估结果的可靠性,还进行了敏感性分析。进行了随机效应元回归,以探索不同研究之间卒中风险估计值异质性的来源。使用 Egger 检验和 Begg 检验对潜在的发表偏倚进行了评估:结果:共纳入 19 项研究,分别来自全球 4 大洲和 12 个国家。共有 1,675,707 名参与者参与了此次荟萃分析。随机效应模型下的汇总分析表明,不良社会关系与中风风险之间存在显著关联(OR = 1.30;95%CI:1.17-1.44),并增加了中风后死亡的风险(OR = 1.36;95%CI:1.07-1.73)。分组分析表明,有限的社会网络(OR = 1.52;95%CI = 1.04-2.21)、孤独(OR = 1.31;95%CI = 1.13-1.51)和缺乏社会支持(OR = 1.66;95%CI = 1.04-2.63)与中风风险之间存在关联。元回归解释了不同研究间中风风险报告差异的 75.21%。随机效应元回归结果表明,中风风险估计值的异质性可能源于所纳入研究的大陆和发表年份:结论:社会隔离、有限的社会网络、缺乏社会支持和孤独感已成为导致中风发病和随后死亡的独特风险因素。公共卫生政策必须优先考虑社会关系和孤独感对中风预防和中风后护理的多方面影响:该方案于2024年5月1日在Prospero国际前瞻性系统上注册,注册号为CRD42024531036。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The impact of social relationships on the risk of stroke and post-stroke mortality: a systematic review and meta-analysis.

Background: The association between poor social relationships and post-stroke mortality remains uncertain, and the evidence regarding the relationship between poor social relationships and the risk of stroke is inconsistent. In this meta-analysis, we aim to elucidate the evidence concerning the risk of stroke and post-stroke mortality among individuals experiencing a poor social relationships, including social isolation, limited social networks, lack of social support, and loneliness.

Methods: A thorough search of PubMed, Embase, and the Cochrane Library databases to systematically identify pertinent studies. Data extraction was independently performed by two researchers. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using either a random-effects or fixed-effects model. Sensitivity analyses were conducted to evaluate the reliability of the results. Random-effects meta-regression was performed to explore the sources of heterogeneity in stroke risk estimates between studies. Assessment for potential publication bias was carried out using Egger's and Begg's tests.

Results: Nineteen studies were included, originating from 4 continents and 12 countries worldwide. A total of 1,675,707 participants contributed to this meta-analysis. Pooled analyses under the random effect model revealed a significant association between poor social relationships and the risk of stroke (OR = 1.30; 95%CI: 1.17-1.44), as well as increased risks for post-stroke mortality (OR = 1.36; 95%CI: 1.07-1.73). Subgroup analyses demonstrated associations between limited social network (OR = 1.52; 95%CI = 1.04-2.21), loneliness (OR = 1.31; 95%CI = 1.13-1.51), and lack of social support (OR = 1.66; 95%CI = 1.04-2.63) with stroke risk. The meta-regression explained 75.21% of the differences in reported stroke risk between studies. Random-effect meta-regression results indicate that the heterogeneity in the estimated risk of stroke may originate from the continent and publication year of the included studies.

Conclusion: Social isolation, limited social networks, lack of social support, and feelings of loneliness have emerged as distinct risk factors contributing to both the onset and subsequent mortality following a stroke. It is imperative for public health policies to prioritize the multifaceted influence of social relationships and loneliness in stroke prevention and post-stroke care.

Trial registration: The protocol was registered on May 1, 2024, on the Prospero International Prospective System with registration number CRD42024531036.

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来源期刊
BMC Public Health
BMC Public Health 医学-公共卫生、环境卫生与职业卫生
CiteScore
6.50
自引率
4.40%
发文量
2108
审稿时长
1 months
期刊介绍: BMC Public Health is an open access, peer-reviewed journal that considers articles on the epidemiology of disease and the understanding of all aspects of public health. The journal has a special focus on the social determinants of health, the environmental, behavioral, and occupational correlates of health and disease, and the impact of health policies, practices and interventions on the community.
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