Worldwide trends in prediabetes from 1985 to 2022: A bibliometric analysis using bibliometrix R-tool

Front Public Health. 2023 Feb 13:11:1072521. doi: 10.3389/fpubh.2023.1072521. eCollection 2023.

Abstract

Background: Prediabetes is a widespread condition that represents the state between normal serum glucose and diabetes. Older individuals and individuals with obesity experience a higher rate of prediabetes. Prediabetes is not only a risk factor for type 2 diabetes mellitus (t2dm) but is also closely related to microvascular and macrovascular complications. Despite its importance, a bibliometric analysis of prediabetes is missing. The purpose of this study is to provide a comprehensive and visually appealing overview of prediabetes research.

Methods: First, the Web of Science (WOS) database was searched to collect all articles related to prediabetes that were published from 1985 to 2022. Second, R language was used to analyze the year of publication, author, country/region, institution, keywords, and citations. Finally, network analysis was conducted using the R package bibliometrix to evaluate the hotspots and development trends of prediabetes.

Results: A total of 9,714 research articles published from 1985 to 2022 were retrieved from WOS. The number of articles showed sustained growth. Rathmann W was the most prolific author with 71 articles. Diabetes Care was the journal that published the highest number of articles on prediabetes (234 articles), and Harvard University (290 articles) was the most active institution in this field. The United States contributed the most articles (2,962 articles), followed by China (893 articles). The top five clusters of the keyword co-appearance network were "prediabetes", "diabetes mellitus", "glucose", "insulin exercise", and "oxidative stress". The top three clusters of the reference co-citation network were "Knowler. WC 2002", "Tabak AG 2012", and "Matthews DR1985".

Conclusions: The combined use of WOS and the R package bibliometrix enabled a robust bibliometric analysis of prediabetes papers, including evaluation of emerging trends, hotspots, and collaboration. This study also allowed us to validate our methodology, which can be used to better understand the field of prediabetes and promote international collaboration.

Keywords: R language; bibliometrics; bibliometrix; diabetes; prediabetes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bibliometrics
  • China
  • Databases, Factual
  • Diabetes Mellitus, Type 2*
  • Humans
  • Prediabetic State*

Grants and funding

This work was supported by Scientific and technological innovation project of China Academy of Chinese Medical Sciences (CI2021A01606); Beijing Natural Science Foundation and Beijing-Tianjin-Hebei Project (J200019); The National Natural Science Foundation of China (81973837).