A Bibliometric Analysis of Global Trends and Research Hotspots in Medicine Food Homology
Xiaolin Li, Minna Liu, Shengguang Wang, Yi Ding, Rong Wang, Wenbin Li, Xiaowei Zhou, Tianlong LiuBackground
Medicine Food Homology (MFH) represents a fundamental concept in traditional health systems, describing natural substances with dual nutritional and therapeutic value. Despite growing global interest in MFH as a complementary health approach, a comprehensive analysis of its research landscape remains underdeveloped. This study provides a systematic bibliometric analysis to map the evolution and current state of MFH research.
Methods
We analyzed publications from Web of Science (1976-2026) using standard bibliometric methods. After rigorous screening, 509 articles were examined through CiteSpace and VOSviewer to identify publication trends, collaboration patterns, and research fronts.
Results
The analysis reveals exponential growth in MFH research since 2020, with China dominating the field (93.9% of publications). Keyword burst analysis identifies “network pharmacology” (strength: 4.08) and “machine learning” as dominant frontiers, signaling a shift toward artificial intelligence-driven precision nutrition. However, the output is heavily skewed toward narrative reviews and compositional studies, with a notable lack of high-quality mechanistic original research.
Conclusion
While MFH research is rapidly expanding, bridging the gap between traditional theory and international standards requires prioritizing multidisciplinary collaboration and rigorous randomized controlled trials. Integrating artificial intelligence with multi-omics data is essential to transition MFH into a cornerstone of evidence-based, personalized medicine.