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. 2025 Apr 3:12:1528366.
doi: 10.3389/fnut.2025.1528366. eCollection 2025.

Global research trends in obesity-related asthma (2004-2023): a bibliometric analysis

Affiliations

Global research trends in obesity-related asthma (2004-2023): a bibliometric analysis

Liye Lang et al. Front Nutr. .

Abstract

Background: In recent years, an increasing body of evidence has revealed a complex interplay between obesity and asthma, prompting academic and medical communities to intensify their focus on this area of research. The objective of this study is to undertake a comprehensive bibliometric analysis of the research literature pertaining to obesity-related asthma from 2004 to 2023. This analysis aims to provide precise and valuable insights, as well as to systematically reflect upon the current status and emerging trends within the field.

Methods: Literature data on obesity and asthma research was sourced from the Web of Science Core Collection database. CiteSpace and VOSviewer were utilized to visually analyze bibliometric indicators such as co-authorship, citation networks, and publication frequency of the data to facilitate the identification of patterns and trends.

Results: A total of 3,118 papers were included in the analysis, encompassing 2,539 articles and 579 reviews. Throughout the last 20 years, the volume of publications has shown a consistent upward trend. The United States and Harvard University are at the forefront of this research field. Professor Dixon Anne E. is recognized as a pioneer and leading figure in the cultivation of obesity-related asthma research. Keyword analysis identified topics such as "childhood asthma," "bariatric surgery," "physical activity," "gut microbiota," "COVID-19," "food allergy," "asthma control," "nutrition examination," and "severe asthma."

Conclusion: The research domain of obesity-related asthma has experienced a substantial growth, with the United States, the United Kingdom, and China leading the global landscape. The focus on asthma in obese adolescents and children, the role of bariatric surgery, and lifestyle interventions remains a consistent area of interest, with considerable potential for further study. These findings provide a scientific basis for the development of personalized treatment programs for obese asthma patients. In addition, this study highlights the importance of further research in the fields of gut microbiota, COVID-19, and food allergy, providing directions for future policymaking.

Keywords: asthma; bibliometrics; hotspots; obesity; visualization.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart of screening process.
Figure 2
Figure 2
Annual publications on obesity-related asthma by years.
Figure 3
Figure 3
(A) Geographical distribution of studies on obesity-related asthma. (B) A visual map of cooperation among the top 50 countries/regions by publication count. Each node in the diagram symbolizes a country/region, with its size reflecting the number of articles. The thickness of lines indicates the strength of collaboration between countries.
Figure 4
Figure 4
(A) Author cooperation network diagram. Each node represents an author. Different colors represent different author clusters. The thickness of lines reflects the level of collaboration. (B) Institutional cooperation network diagram. Each node symbolizes an institution, with its size reflecting the number of publications. The thickness of lines indicates the level of collaboration. (C) The top 10 institutions.
Figure 5
Figure 5
(A) The density distribution map of cited journal. The darker the color, the higher the density, indicating more citations. (B) Overlap diagram of journal citations. A node represents a journal, and the size of the node represents the amount of citation. Color represents the time change of journal citation. (C) The dual-map overlay of journals.
Figure 6
Figure 6
(A) Keyword co-occurrence network. Each node signifies a keyword, with its size indicating the frequency of occurrence. Connections between nodes represent the co-occurrence of two keywords. (B) Network overlap of co-occurrence keywords. Different colors represent time changes. (C) The map of top 30 keywords with the strongest citations bursts. (D) Top 30 references with the strongest citation bursts. (E) Keyword clustering of cited articles. (F) The density distribution map of article citations. The darker the color, the greater the density, indicating more citations.

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