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Tryptophan and Brain Disorders · Journal article
Journal of Pharmaceutical and Sciences · August 15, 2026
Raises a question worth testing. It does not answer one.
This bibliometric analysis maps trends in published research on tea (Camellia sinensis) and obesity from 2005–2024, showing a 3.8-fold increase from 21 to 80 articles annually and identifying four major research themes. The analysis is descriptive and does not evaluate the efficacy or safety of tea for weight management; it documents the scientific landscape and research directions but does not provide evidence of clinical benefit.
Bibliometric analysis using systematic retrieval and network analysis. Published research articles indexed in Scopus on Camellia sinensis (tea) and obesity-related outcomes; no human or animal subjects.. n = 897. Global; publications identified from Scopus; China was the leading producer of publications (n = 182)..
Annual output increased from 21 articles in 2005 to a peak of 80 in 2020 China produced the most publications (n = 182) 897 original research articles were analysed
Safety was not reported in the material analysed. Check the source before drawing any conclusion about harm.
Clinicians should note that this analysis describes the research landscape rather than providing clinical evidence. It identifies emerging methodologies (multi-omics, microbiota work, precision nutrition) but explicitly states that standardised clinical trials are needed and cautious translation into clinical and policy settings is warranted.
This is a bibliometric mapping of 20 years of published research on tea and obesity, not a primary clinical or experimental study, and does not test efficacy or safety itself.
As stated by the source record.
Quoted from the source exactly as published.
Clinicians should note that this analysis describes the research landscape rather than providing clinical evidence. It identifies emerging methodologies (multi-omics, microbiota work, precision nutrition) but explicitly states that standardised clinical trials are needed and cautious translation into clinical and policy settings is warranted.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
Camellia sinensis (tea) is widely consumed and has been extensively investigated for its potential to support weight management, particularly because of the bioactive catechin epigallocatechin-3-gallate (EGCG). We conducted a bibliometric analysis to map the scope, productivity, collaboration patterns, citation impact, and thematic evolution of research on Camellia sinensis and obesity-related outcomes. We retrieved records indexed in Scopus for 2005–2024 using terms for Camellia sinensis, major tea types, and obesity. After excluding non-original publications, we analysed 897 original research articles with VOSviewer (version 1.6.20) and the Biblioshiny R package, including co-occurrence, collaboration, and citation networks. Annual output increased from 21 articles in 2005 to a peak of 80 in 2020. China produced the most publications (n = 182), while the United States achieved the greatest total citation impact. The leading sources were Nutrients, Journal of Nutritional Biochemistry, and Food & Function; the most prolific authors were Wang Y, Liu Z, and Zhang Y; and Anhui Agricultural University was the most productive institution. Keyword analysis identified four interconnected themes: green tea catechins and lipid metabolism, oxidative stress and polyphenols, gut microbiota and thermogenesis, and obesity-related metabolic syndrome. Recent research increasingly emphasises multi-omics, microbiota interactions, and precision nutrition. These bibliometric findings indicate expanding scientific interest in the potential contribution of Camellia sinensis to weight management and obesity-related metabolic health, while underscoring the need for standardised clinical trials, improved EGCG bioavailability, and cautious translation into clinical and policy settings
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