Diabetes and sarcopenia: A bibliometric exploration of mechanisms, comorbidities, and therapeutic frontiers—an evidence mapping study

Background

The increasing global prevalence of diabetes has highlighted sarcopenia as a significant emerging complication. While numerous studies have explored the association between diabetes and sarcopenia, a comprehensive synthesis of the research landscape and its evolving trends remains limited. This study employs bibliometric analysis to provide an objective overview, identify key contributors, and uncover emerging research frontiers.

Methods

We systematically retrieved articles on diabetes and sarcopenia published over the past two decades from the Web of Science Core Collection. Using advanced bibliometric tools (VOSviewer, CiteSpace, and R software), we analyzed publication trends, collaboration networks, and thematic clusters. Visualization techniques were applied to map the distribution of research outputs by country, institution, journal, and author, as well as to identify high-impact keywords and references.

Results

A total of 1608 articles were sourced from 75 countries and 561 institutions. China had the highest publication output, while the most productive institution was from Yonsei University in South Korea. The most prolific author was Fukui M from Japan. Among high-yield journals, the Journal of Cachexia, Sarcopenia and Muscle from Germany had the highest Impact Factor (IF). The hot keywords of strong citation burst strength were “sarcopenia”, “insulin resistance”, “skeletal muscle”, “older adults” and “metabolic syndrome”. Furthermore, frontier topics in recent years included “hepatocellular carcinoma” and “non-alcoholic fatty liver disease”.

Conclusion

This study provides a comprehensive bibliometric analysis of the relationship between diabetes and sarcopenia, offering insights into the evolution of research themes and identifying potential areas for future investigation. The findings underscore the importance of early intervention and multidisciplinary approaches to improve diagnosis, treatment, and patient outcomes. By mapping the current landscape, this work aims to guide future studies and address critical knowledge gaps.