ArticleFrontiers in aging neuroscience2024
Dementia and metabolic syndrome: a bibliometric analysis.
Article in Frontiers in aging neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Artificial intelligence in immune checkpoint inhibitor research: A bibliometric analysis of the landscape.Human vaccines & immunotherapeutics · 2026Article
- Metabolic Syndrome and Dementia Risk in Older Adults: A Narrative Review.The Kaohsiung journal of medical sciences · 2026Review
- GLP-1 receptor agonists, metabolic syndrome, and Alzheimer's disease: Lessons and opportunities from the EVOKE trials.Journal of neuroendocrinology · 2026Review
- The front-page filter in bibliometric research: implications for retrieval precision and methodological attribution.Frontiers in aging neuroscience · 2026Article
- Association between baseline cardio-kidney-metabolic syndrome, its transition and cognitive impairment: result from CHARLS study.Diabetology & metabolic syndrome · 2025Article
- From obesity to inflammation: emerging frontiers in prostate cancer and metabolic syndrome studies.Translational andrology and urology · 2025Article
- Glucose Metabolic Abnormality: A Crosstalk between Depression and Alzheimer's Disease.Current neuropharmacology · 2025Review
- A bibliometric and visualization analysis of electrochemical biosensors for early diagnosis of eye diseases.Frontiers in medicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Dementia is a progressive neurodegenerative condition, while metabolic syndrome (MetS) is characterized by a combination of metabolic abnormalities such as hypertension, high blood sugar, and obesity. There exists a connection and overlap between the two conditions in certain aspects, and both are influenced to varying degrees by the process of aging. This study presents an overview of the current research landscape regarding dementia and MetS through bibliometric analysis. Methods: A systematic search was conducted to retrieve relevant literature on dementia and MetS published between 1 January 2000, and 30 November 2023, from the Web of Science Core Collection database. Various bibliometric tools, including VOSviewer, CiteSpace, and the R software package "bibliometrix," were utilized for analysis. Results: A total of 717 articles were identified, showing an upward trend in annual publications. Leading contributors included the United States, Italy, and China, with institutions such as the University of California System at the forefront. The Conclusion: This bibliometric analysis summarizes the foundational knowledge structure in the realm of dementia and MetS from 2000 to 2023. By highlighting current research frontiers and trending topics, this analysis serves as a valuable reference for researchers in the field.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.