绿地与人类健康证据的可信度:采用证据分级方法进行的元分析综述。

IF 9.7 1区 医学 Q1 MEDICINE, RESEARCH & EXPERIMENTAL EBioMedicine Pub Date : 2024-08-01 Epub Date: 2024-07-29 DOI:10.1016/j.ebiom.2024.105261
Yuting Xie, Shujun Fan, Yana Luo, Jiaxin Li, Yidan Zhang, Lixin Hu, Huiling Qiu, Ganglong Zhou, Joachim Heinrich, Tianyu Zhao, Zhengtu Li, Li Li, Aimin Xu, John S Ji, Zhoubin Zhang, Yuanzhong Zhou, Sam S S Lau, Xiaoguang Zou, Guanghui Dong, Payam Dadvand, Boyi Yang
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引用次数: 0

摘要

背景:绿地是人类生活环境的重要组成部分,许多流行病学研究估计了绿地对人类健康的影响。然而,没有任何研究对现有证据的可信度进行过量化评估,这阻碍了这些证据转化为政策决策,也妨碍了研究人员发现新的研究缺口。本综述旨在对此类证据的可信度进行评估和排序:按照 PRISMA 指南,我们系统地检索了 PubMed、Web of Science 和 Embase 数据库中截至 2024 年 1 月 15 日发表的有关绿地和健康结果的系统综述和荟萃分析。我们采用 "推荐、评估、发展和评价分级 "框架,根据偏倚风险、不一致性、间接性、不精确性和发表偏倚等五个方面,将来自干预性研究的荟萃分析证据的可信度分为四级(即高、中、低和极低)。此外,我们还重新计算了所有观察性研究的荟萃分析,并通过考虑 P 值、样本大小、稳健性、异质性和偏倚检测的严格阈值,将证据分为五个等级(即令人信服、高度提示、提示、弱和非显著):共有 154 项荟萃分析(干预性分析 = 44 项,观察性分析 = 110 项)对绿地与健康结果之间的联系进行了分级。在干预性研究的荟萃分析中,绿地与健康结果之间的关联被评为高、中、低和极低可信度证据的分别为0、4(幸福感、收缩压、消极情绪和积极情绪)、20和20项。在观察性研究的荟萃分析中,有1项(心血管疾病死亡率)、4项(糖尿病、早产和胎龄小婴儿的患病率/发生率以及全因死亡率)、12项、22项和71项关联分别被归类为令人信服、高度提示、提示、弱和非显著证据:目前的证据在很大程度上证实了绿地与人类健康之间的有益联系。然而,这些关联中只有一小部分具有较高或令人信服的可信度。因此,未来仍需要设计更好的初级研究和荟萃分析,以提供更高质量的证据,为健康促进策略提供依据:国家自然科学基金、广州市科技计划、广东省医学科技研究基金、香港特别行政区研究资助局、中德人员流动项目。
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Credibility of the evidence on green space and human health: an overview of meta-analyses using evidence grading approaches.

Background: Green space is an important part of the human living environment, with many epidemiological studies estimating its impact on human health. However, no study has quantitatively assessed the credibility of the existing evidence, impeding their translations into policy decisions and hindering researchers from identifying new research gaps. This overview aims to evaluate and rank such evidence credibility.

Methods: Following the PRISMA guideline, we systematically searched PubMed, Web of Science, and Embase databases for systematic reviews with meta-analyses concerning green spaces and health outcomes published up to January 15, 2024. We categorized the credibility of meta-analytical evidence from interventional studies into four levels (i.e., high, moderate, low, and very low) using the Grading of Recommendation, Assessment, Development and Evaluations framework, based on five domains including risk of bias, inconsistency, indirectness, imprecision, and publication bias. Further, we recalculated all the meta-analyses from observational studies and classified evidence into five levels (i.e., convincing, highly suggestive, suggestive, weak, and non-significant) by considering stringent thresholds for P-values, sample size, robustness, heterogeneity, and testing for biases.

Findings: In total, 154 meta-analysed associations (interventional = 44, observational = 110) between green spaces and health outcomes were graded. Among meta-analyses from interventional studies, zero, four (wellbeing, systolic blood pressure, negative affect, and positive affect), 20, and 20 associations between green spaces and health outcomes were graded as high, moderate, low, and very low credibility evidence, respectively. Among meta-analyses from observational studies, one (cardiovascular disease mortality), four (prevalence/incidence of diabetes mellitus, preterm birth, and small for gestational age infant, and all-cause mortality), 12, 22, and 71 associations were categorized as convincing, highly suggestive, suggestive, weak, and non-significant evidence, respectively.

Interpretation: The current evidence largely confirms beneficial associations between green spaces and human health. However, only a small subset of these associations can be deemed to have a high or convincing credibility. Hence, future better designed primary studies and meta-analyses are still needed to provide higher quality evidence for informing health promotion strategies.

Funding: The National Natural Science Foundation of China of China; the Guangzhou Science and Technology Program; the Guangdong Medical Science and Technology Research Fund; the Research Grant Council of the Hong Kong SAR; and Sino-German mobility program.

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来源期刊
EBioMedicine
EBioMedicine Biochemistry, Genetics and Molecular Biology-General Biochemistry,Genetics and Molecular Biology
CiteScore
17.70
自引率
0.90%
发文量
579
审稿时长
5 weeks
期刊介绍: eBioMedicine is a comprehensive biomedical research journal that covers a wide range of studies that are relevant to human health. Our focus is on original research that explores the fundamental factors influencing human health and disease, including the discovery of new therapeutic targets and treatments, the identification of biomarkers and diagnostic tools, and the investigation and modification of disease pathways and mechanisms. We welcome studies from any biomedical discipline that contribute to our understanding of disease and aim to improve human health.
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