SwePub
Sök i LIBRIS databas

  Extended search

onr:"swepub:oai:DiVA.org:umu-57438"
 

Search: onr:"swepub:oai:DiVA.org:umu-57438" > A Network-Based App...

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

A Network-Based Approach to Visualize Prevalence and Progression of Metabolic Syndrome Components

Haring, Robin (author)
Rosvall, Martin (author)
Umeå universitet,Institutionen för fysik
Völker, Uwe (author)
show more...
Völzke, Henry (author)
Kroemer, Heyo (author)
Nauck, Matthias (author)
Wallaschofski, Henri (author)
show less...
 (creator_code:org_t)
2012-06-19
2012
English.
In: PLOS ONE. - San Francisco : Public Library of Science. - 1932-6203. ; 7:6, s. e39461-
  • Journal article (peer-reviewed)
Abstract Subject headings
Close  
  • Background: The additional clinical value of clustering cardiovascular risk factors to define the metabolic syndrome (MetS) is still under debate. However, it is unclear which cardiovascular risk factors tend to cluster predominately and how individual risk factor states change over time. Methods & Results: We used data from 3,187 individuals aged 20-79 years from the population-based Study of Health in Pomerania for a network-based approach to visualize clustered MetS risk factor states and their change over a five-year follow-up period. MetS was defined by harmonized Adult Treatment Panel III criteria, and each individual's risk factor burden was classified according to the five MetS components at baseline and follow-up. We used the map generator to depict 32 (2(5)) different states and highlight the most important transitions between the 1,024 (32(2)) possible states in the weighted directed network. At baseline, we found the largest fraction (19.3%) of all individuals free of any MetS risk factors and identified hypertension (15.4%) and central obesity (6.3%), as well as their combination (19.0%), as the most common MetS risk factors. Analyzing risk factor flow over the five-year follow-up, we found that most individuals remained in their risk factor state and that low high-density lipoprotein cholesterol (HDL) (6.3%) was the most prominent additional risk factor beyond hypertension and central obesity. Also among individuals without any MetS risk factor at baseline, low HDL (3.5%), hypertension (2.1%), and central obesity (1.6%) were the first risk factors to manifest during follow-up. Conclusions: We identified hypertension and central obesity as the predominant MetS risk factor cluster and low HDL concentrations as the most prominent new onset risk factor.

Subject headings

NATURVETENSKAP  -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
NATURAL SCIENCES  -- Mathematics -- Probability Theory and Statistics (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Hälsovetenskap (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Health Sciences (hsv//eng)

Publication and Content Type

ref (subject category)
art (subject category)

Find in a library

  • PLOS ONE (Search for host publication in LIBRIS)

To the university's database

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Search outside SwePub

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view