KGMM Alberti
- Endocrinology, Diabetes and Metabolism top 0.5%
- Epidemiology top 2%
- Physiology top 1%
- Public Health, Environmental and Occupational Health top 2%
- Cardiology and Cardiovascular Medicine top 2%
- Co-authors
- Robert H. EckelPaul ZimmetScott M. GrundyNigel UnwinPZ ZimmetTerry AsprayJean Claude MbanyaEugène Sobngwi
- Topics
- Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers)Obesity, Physical Activity, Diet (3 papers)Diabetes Treatment and Management (3 papers)
- Partner nations
- United KingdomAustraliaCameroon
In The Last Decade
KGMM Alberti
22 papers receiving 4.8k citations
Hit Papers
Peers
Comparison fields: 5 of 142
- Endocrinology, Diabetes and Metabolism 1.7k
- Epidemiology 1.4k
- Physiology 1.4k
- Public Health, Environmental and Occupational Health 856
- Cardiology and Cardiovascular Medicine 817
Countries citing papers authored by KGMM Alberti
This map shows the geographic impact of KGMM Alberti's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by KGMM Alberti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites KGMM Alberti more than expected).
Fields of papers citing papers by KGMM Alberti
This network shows the impact of papers produced by KGMM Alberti. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by KGMM Alberti. The network helps show where KGMM Alberti may publish in the future.
Co-authorship network of co-authors of KGMM Alberti
This figure shows the co-authorship network connecting the top 25 collaborators of KGMM Alberti. A scholar is included among the top collaborators of KGMM Alberti based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with KGMM Alberti. KGMM Alberti is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | The metabolic syndromebreakdown → | 3990 |
| 3 | Stroke mortality in urban and rural Tanzania | 115 |
| 4 | 232 | |
| 5 | 77 | |
| 6 | 52 | |
| 7 | 61 | |
| 8 | 24 | |
| 9 | 36 | |
| 10 | 1 | |
| 11 | The diagnosis and classification of diabetes | 3 |
| 12 | 63 | |
| 13 | 110 | |
| 14 | 1 | |
| 15 | 7 | |
| 16 | 128 | |
| 17 | 17 | |
| 18 | 3 | |
| 19 | 0 | |
| 20 | 13 |
About KGMM Alberti
KGMM Alberti is a scholar working on Endocrinology, Diabetes and Metabolism, Clinical Biochemistry and Public Health, Environmental and Occupational Health, having authored 23 papers that have together received 5.0k indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers), Obesity, Physical Activity, Diet (3 papers) and Diabetes Treatment and Management (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (1.7k citations), Physiology (1.4k citations) and Epidemiology (1.4k citations). KGMM Alberti has collaborated with scholars based in United Kingdom, Australia and Cameroon. Frequent co-authors include Robert H. Eckel, Paul Zimmet, Scott M. Grundy, Nigel Unwin, PZ Zimmet, Terry Aspray, Jean Claude Mbanya, Eugène Sobngwi, André Pascal Kengne and EM Minkoulou. Their work appears in journals such as The Lancet, Scientific Reports and International Journal of Epidemiology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.