Data Sheet 2_Mapping the research trends and hotspots of exercise and nutrition in diabetes: a bibliometric and visual analysis (2005–2025).csv
Bibliographic record
Abstract
Objectives Despite the growing interest in exercise and nutrition as key strategies for diabetes prevention and management, a comprehensive bibliometric assessment of this field remains lacking. This study aims to map the research landscape, identify research trends and hotspots to inform future academic inquiry and clinical practice. Methods As of July 3, 2025, publications on exercise and nutrition in diabetes from 2005 to 2025 were retrieved from the Web of Science Core Collection and Scopus databases. The bibliometric and visual analysis was conducted using R software, VOSviewer, and CiteSpace. Results Trends in annual publication outputs have shown a consistent upward trajectory from 2005 to 2025. The United States led in both research output and institutional prominence. China, South Korea, Australia, and Canada also emerged as key contributors, and European countries functioned as major collaborative centers. Nutrients and the American Journal of Clinical Nutrition ranked among the most prolific and frequently cited sources in the field. Co-citation, burst detection, keyword frequency, clustering, and thematic evolution collectively revealed three major thematic domains: (1) lifestyle interventions in diabetes focusing on different exercise types, nutritional approaches, and their combinations; (2) management of long-term diabetic complications through physical activity and dietary approaches; and (3) population-specific strategies for older adults, children, and women with and at risk of diabetes. Across these themes, studies have prominently highlighted mechanistic insights, therapeutic efficacy, evidence-based guidelines, risk management, and adherence. Conclusion Over the past two decades, attention to this field has steadily increased, with strong collaboration established among countries, institutions, and journals. Emerging research trends in exercise and nutrition in diabetes are shifting toward a life course–oriented paradigm, personalized self-management support, and more innovative, adaptable intervention formats tailored to accommodate modern lifestyles.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Insufficient payload (model declined to judge) Domain: not available · Genre: Dataset About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
| gpt | Bibliometrics Domain: not available · Genre: Dataset About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.370 | 0.476 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.052 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".