Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
The Rotterdam Study: objectives and design update
20071.0k citationsAlbert Hofman, Monique M.B. Breteler et al.European Journal of Epidemiologyprofile →
Dietary fat intake and the risk of incident dementia in the Rotterdam study
1997673 citationsLenore J. Launer, Jacqueline C.M. Witteman et al.Annals of Neurologyprofile →
Prolonged QTc Interval and Risk of Sudden Cardiac Death in a Population of Older Adults
2006639 citationsJan A. Kors, Albert Hofman et al.Journal of the American College of Cardiologyprofile →
High Serum Uric Acid as a Novel Risk Factor for Type 2 Diabetes
2008510 citationsAlbert Hofman, Jacqueline C.M. Witteman et al.Diabetes Careprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Jacqueline C.M. Witteman
Since
Specialization
Citations
This map shows the geographic impact of Jacqueline C.M. Witteman'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 Jacqueline C.M. Witteman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jacqueline C.M. Witteman more than expected).
Fields of papers citing papers by Jacqueline C.M. Witteman
This network shows the impact of papers produced by Jacqueline C.M. Witteman. 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 Jacqueline C.M. Witteman. The network helps show where Jacqueline C.M. Witteman may publish in the future.
Co-authorship network of co-authors of Jacqueline C.M. Witteman
This figure shows the co-authorship network connecting the top 25 collaborators of Jacqueline C.M. Witteman.
A scholar is included among the top collaborators of Jacqueline C.M. Witteman 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 Jacqueline C.M. Witteman. Jacqueline C.M. Witteman is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Leening, Maarten J.G., Bart S. Ferket, Maryam Kavousi, et al.. (2014). Abstract 12068: Sex Differences in Lifetime Risk and First Manifestation of Cardiovascular Disease: An Evidence Gap in Preventive Cardiology. Circulation. 130.1 indexed citations
2.
Leening, Maarten J.G., Maryam Kavousi, Ewout W. Steyerberg, et al.. (2013). Evaluation of newer risk markers for coronary heart disease: The Rotterdam study. Nederlandsch tijdschrift voor geneeskunde/Nederlands tijdschrift voor geneeskunde/NTvG-databank. 157(30).1 indexed citations
Woudenbergh, Geertruida J. van, Rozemarijn Vliegenthart, Frank J.A. van Rooij, et al.. (2008). Coffee Consumption and Coronary Calcification. Arteriosclerosis Thrombosis and Vascular Biology. 28(5). 1018–1023.32 indexed citations
Brugts, Jasper J., Moniek P.M. de Maat, Eric Boersma, et al.. (2008). Abstract 2456: Strong and Independent Association between Angiotensinogen Gene Polymorphisms and Hypertension in 10060 Patients with Stable Coronary Artery Disease. Circulation. 118.1 indexed citations
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.