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The metabolic syndrome: useful concept or clinical tool? Report of a WHO Expert Consultation

Overview of attention for article published in Diabetologia, December 2009
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
1 tweeter
patent
1 patent
f1000
1 research highlight platform

Citations

dimensions_citation
254 Dimensions

Readers on

mendeley
253 Mendeley
citeulike
5 CiteULike
Title
The metabolic syndrome: useful concept or clinical tool? Report of a WHO Expert Consultation
Published in
Diabetologia, December 2009
DOI 10.1007/s00125-009-1620-4
Pubmed ID
Authors

R. K. Simmons, K. G. M. M. Alberti, E. A. M. Gale, S. Colagiuri, J. Tuomilehto, Q. Qiao, A. Ramachandran, N. Tajima, I. Brajkovich Mirchov, A. Ben-Nakhi, G. Reaven, B. Hama Sambo, S. Mendis, G. Roglic

Abstract

This article presents the conclusions of a WHO Expert Consultation that evaluated the utility of the 'metabolic syndrome' concept in relation to four key areas: pathophysiology, epidemiology, clinical work and public health. The metabolic syndrome is a concept that focuses attention on complex multifactorial health problems. While it may be considered useful as an educational concept, it has limited practical utility as a diagnostic or management tool. Further efforts to redefine it are inappropriate in the light of current knowledge and understanding, and there is limited utility in epidemiological studies in which different definitions of the metabolic syndrome are compared. Metabolic syndrome is a pre-morbid condition rather than a clinical diagnosis, and should thus exclude individuals with established diabetes or known cardiovascular disease (CVD). Future research should focus on: (1) further elucidation of common metabolic pathways underlying the development of diabetes and CVD, including those clustering within the metabolic syndrome; (2) early-life determinants of metabolic risk; (3) developing and evaluating context-specific strategies for identifying and reducing CVD and diabetes risk, based on available resources; and (4) developing and evaluating population-based prevention strategies.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 253 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 1%
Spain 3 1%
New Zealand 2 <1%
France 2 <1%
Mexico 2 <1%
Brazil 2 <1%
Canada 1 <1%
Denmark 1 <1%
Cuba 1 <1%
Other 6 2%
Unknown 230 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 43 17%
Student > Ph. D. Student 41 16%
Student > Master 34 13%
Student > Bachelor 25 10%
Student > Postgraduate 24 9%
Other 85 34%
Unknown 1 <1%
Readers by discipline Count As %
Medicine and Dentistry 123 49%
Unspecified 33 13%
Agricultural and Biological Sciences 32 13%
Nursing and Health Professions 14 6%
Biochemistry, Genetics and Molecular Biology 10 4%
Other 40 16%
Unknown 1 <1%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 May 2018.
All research outputs
#942,863
of 13,017,042 outputs
Outputs from Diabetologia
#557
of 3,779 outputs
Outputs of similar age
#13,004
of 213,784 outputs
Outputs of similar age from Diabetologia
#6
of 53 outputs
Altmetric has tracked 13,017,042 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,779 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.5. This one has done well, scoring higher than 85% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 213,784 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 53 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.