Bibliometric Analysis of Depression and Type 2 Diabetes Comorbidity Research, 2016-2025

A review combining macro bibliometric analysis and micro content interpretation of literature on the comorbidity between depression and type 2 diabetes mellitus. The analysis is based on 3,986 papers from the Web of Science Core Collection and 238 clinical trials from PubMed published between 2016 and 2025. The study was authored by Donghai Wu and published on figshare in April 2026.

Use Cases

• Analyzing research trends and growth in depression-T2DM comorbidity studies based on the bibliometric analysis of 3,986 papers
• Identifying key contributing institutions and authors in the field based on the mapped research entities
• Exploring potential future research hotspots such as links to Parkinson's disease and obesity mentioned in the results
• Investigating proposed comorbidity mechanisms like the HPA axis and BDNF through the micro-interpretation content
• Evaluating integrated treatment strategies for depression and T2DM discussed in the conclusion

Strengths

• Analysis is based on a substantial corpus of 3,986 papers and 238 clinical trials
• Provides a defined temporal coverage of research published between 2016 and 2025
• Combines macro bibliometric mapping with micro content interpretation for deeper insights

Limitations

• The dataset is a 47.9 KB DOCX file, suggesting limited scope and likely being a summary document rather than raw data
• Column-level documentation and sample data are unavailable, making data structure and content uncertain
• The description focuses on the study's conclusions; the actual downloadable data content is not specified

Provenance

Source

Web of Science Core Collection and PubMed

Collection Method

Bibliometric analysis using VOSviewer, Citespace, and Bibliometrix, combined with micro content interpretation

Time Range

2016 to 2025

Freshness

Last updated 2026-04-10 06:03:28