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Record W4409518111 · doi:10.3389/fnut.2025.1539587

Obesity and psychology: a bibliometric analysis of half a century

2025· article· en· W4409518111 on OpenAlexaboutno aff
Shan Liu, Zixuan Xiao, Saiqiong Yin, Boyan Fan, Guixiang Sun

Bibliographic record

VenueFrontiers in Nutrition · 2025
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsnot available
FundersNatural Science Foundation of Hunan ProvinceHunan University of Chinese MedicineHunan University
KeywordsObesityPsychologyApplied psychologyMedicine

Abstract

fetched live from OpenAlex

Background: The interaction mechanisms between obesity and psychological factors are intricate and bidirectional. Psychological issues can prompt unhealthy eating behaviors, impede weight management efforts, and elevate the risk of obesity. This study employs bibliometric approaches to conduct a comprehensive analysis of the knowledge structure, research hotspots, and development trends in the field of obesity and psychology, offering valuable references for future research in this area. Methods: This study draws on the Web of Science Core Collection (WoSCC) database, with "obesity" and "psychology" serving as the primary search terms. Leveraging CiteSpace (version 6.3.R1) and VOSviewer (version 1.6.20) software, bibliometric analyses were conducted on various indicators, including the number of publications, publication volume, authors, journals, references, countries, institutions, and keywords. Through co-citation analysis and keyword co-occurrence analysis, the research hotspots and developmental trajectories in this field were revealed. Results: Based on the inclusion and exclusion criteria, a total of 2,753 relevant articles were ultimately included in this study. The results indicate that since the 21st century, there has been a significant surge in the number of publications in the field of obesity and psychology. Developed countries like the United States, Canada, the United Kingdom, and Australia are at the forefront of this field. Leading research institutions include Yale University, University College London, and the University of Pennsylvania. Among the authors, GRILO CM has the highest publication output. Research hotspot keywords primarily include "depression," "stress," "emotional eating," "bariatric surgery," "intervention," "weight stigma," and "self-regulation." Current research trends reveal a marked regional imbalance in international collaboration in the field of obesity and psychology. In particular, there exists a notable absence of substantive cooperation between developed and developing countries. Research hotspots mainly center around the following aspects: Firstly, it focuses on the prevalence of common psychological distress symptoms, including depression, anxiety, and stress, within the obese population and the implications these symptoms have for health. Secondly, mental health issues like binge eating and emotional eating play a pivotal role in the onset and maintenance of obesity. Thirdly, psychosocial factors like health-related quality of life and weight stigma are at the core of obesity intervention and have potential impacts on behavioral change. Meanwhile, researchers are increasingly concentrating on the individualized mental health requirements of obese populations, emphasizing the importance of evidence-based psychological interventions in the management of obesity. These research hotspots not only enhance our understanding of the complex relationship between obesity and mental health but also provide crucial theoretical foundations and practical insights for future research directions. Conclusion: This study employs bibliometric approaches to conduct a comprehensive and in-depth analysis of research trends and developments in the field of obesity and psychology. The research reveals the current status and characteristics of this field from multiple perspectives, offering scientific backing for researchers to identify potential collaborators, pinpoint hotspot issues, and keep abreast of the latest developments. Looking forward to the future, related research can further expand data sources, diversify research viewpoints, and delve more profoundly into the complex relationship between obesity and mental health.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0650.086
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.447
Teacher spread0.409 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2025
Admission routes1
Has abstractyes

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