Decoding the gut-sleep Nexus: a bibliometric mapping of gut microbiota and sleep disorders

解码肠-睡眠关系:肠道菌群与睡眠障碍的文献计量学分析

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Abstract

BACKGROUND: An increasing number of studies have focused on the interaction between gut microbiota and sleep disorders. However, there is currently no bibliometric analysis of the literature on gut microbiota and sleep disorders. This study employs bibliometric methods to analyze the current research status and hotspots in the field of gut microbiota and sleep disorders, providing a reference for future research in this area. METHODS: Articles related to gut microbiota and sleep disorders were retrieved from the WOS core database, covering the period from the database's inception to December 31, 2024. After rigorous screening, VOSviewer and CiteSpace were used to conduct analyses on quantity, collaboration networks, clustering, and citation bursts. RESULTS: The number of articles on gut microbiota and sleep disorders has increased annually, with a significant surge after 2022. China has the highest number of publications, while the United States has the highest citation count. The institution with the most publications is Shanghai Jiao Tong University, and the institution with the most citations is Deakin University. The top 10 journals by publication volume are all ranked above Q2 in the JCR. The most cited article is "Gut microbiome diversity is associated with sleep physiology in humans" by Smith et al., published in PLOS ONE in 2019. The top 10 most frequent keywords are gut microbiota, sleep, depression, inflammation, chain fatty acids, anxiety, brain, oxidative stress, obesity, and health. The keyword cluster "obstructive sleep apnea" is a focal research direction, while fecal microbiota transplantation is a current research hotspot. CONCLUSION: This study reveals the publication trends, collaboration relationships among countries, regions, and authors, and recent research hotspots in the field of gut microbiota and sleep disorders through bibliometric methods, providing an objective data reference for scientific research in this domain.

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