Peter M. Laskarzewski

3.7k citations
83 papers · 3.0k · h-index 29

Impact in

Papers in

Peter M. Laskarzewski

82 papers receiving 2.8k citations

Peers

Peter M. Laskarzewski
Comparison fields: 5 of 112
  • Endocrinology, Diabetes and Metabolism 1.2k
  • Surgery 940
  • Public Health, Environmental and Occupational Health 554
  • Cardiology and Cardiovascular Medicine 401
  • Cancer Research 235
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Norman L. Lasser United States
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Citations per field
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Citations per year

Countries citing papers authored by Peter M. Laskarzewski

Since Specialization
Citations

This map shows the geographic impact of Peter M. Laskarzewski'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 Peter M. Laskarzewski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter M. Laskarzewski more than expected).

Fields of papers citing papers by Peter M. Laskarzewski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter M. Laskarzewski. 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 Peter M. Laskarzewski. The network helps show where Peter M. Laskarzewski may publish in the future.

Co-authors

The 25 scholars most cited alongside Peter M. Laskarzewski, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Peter M. Laskarzewski Line = papers co-authored together Peter M. Laskarzewski links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 83 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998310
2 1993211
3 1999196
4
The Cincinnati Lipid Research Clinic family study: cultural and biological determinants of lipids and lipoprotein concentrations.
1982123
5 1979119
6 1985116
7 1984104
8 1994101
9 198093
10
Common major gene inheritance of extreme overweight.
199088
11 197987
12 199782
13 198072
14 198472
15 198365
16 198156
17 198455
18 200548
19
Frequency and clustering of nonlipid coronary risk factors in dyslipoproteinemia. The Lipid Research Clinics Program Prevalence Study.
198647
20 199144

About Peter M. Laskarzewski

Peter M. Laskarzewski is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery, Genetics, Public Health, Environmental and Occupational Health and Cardiology and Cardiovascular Medicine, having authored 83 papers that have together received 3.0k indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (37 papers), Lipoproteins and Cardiovascular Health (27 papers), Genetic Associations and Epidemiology (15 papers), Obesity, Physical Activity, Diet (11 papers), Hormonal and reproductive studies (9 papers), Cancer, Lipids, and Metabolism (8 papers), Lipid metabolism and disorders (7 papers) and Birth, Development, and Health (6 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (1.2k citations), Surgery (940 citations), Public Health, Environmental and Occupational Health (554 citations), Cardiology and Cardiovascular Medicine (401 citations) and Cancer Research (235 citations). Peter M. Laskarzewski has collaborated with scholars based in United States, Australia and Canada. Frequent co-authors include Charles J. Glueck, Philip R. Khoury, Evan A. Stein, Michael Lane, Margot J. Mellies, John A. Morrison, D. C. Rao, Kathe A. Kelly, J. A. Morrison and Evan A. Stein. Their work appears in journals such as Metabolism, Pediatric Research, Preventive Medicine, American Journal of Epidemiology and Genetic 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.

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