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Correlation between body composition and risk factors for cardiovascular disease and metabolic syndrome

Overview of attention for article published in Biofactors, June 2012
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Title
Correlation between body composition and risk factors for cardiovascular disease and metabolic syndrome
Published in
Biofactors, June 2012
DOI 10.1002/biof.1027
Pubmed ID
Authors

Hai‐Hua Chuang, Wen‐Cheng Li, Bor‐Fuh Sheu, Shu‐Chen Liao, Jau‐Yuan Chen, Ko‐Chen Chang, Yi‐Wen Tsai

Abstract

Body mass index (BMI) is an important diagnostic tool for determining obesity; however, while BMI reflects the influence of body height over body weight, it does not reveal body fat percentage (BF%). We explored whether BF% correlated with risk factors for cardiovascular disease and metabolic syndrome and whether metabolically obese, normal weight people were at risk for these diseases. A total of 2,867 healthy volunteers participated in this study. Blood pressure, height, weight, waist circumference, BMI, BF%, lipid profile, fasting glucose, uric acid, and lifestyle factors were collected from healthy subjects during their annual health examinations. In both males and females, BF% correlated positively with BMI and waist circumference. Participants were divided into three groups according to BF% and data were compared between groups. The results suggest that BF% correlates with risk factors for cardiovascular disease and metabolic syndrome for both men and women, and that BF% may be a useful predictor of risk, particularly in metabolically obese, normal weight individuals.

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

Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 15 22%
Student > Master 11 16%
Student > Ph. D. Student 6 9%
Researcher 5 7%
Other 3 4%
Other 5 7%
Unknown 22 33%
Readers by discipline Count As %
Medicine and Dentistry 18 27%
Nursing and Health Professions 9 13%
Biochemistry, Genetics and Molecular Biology 4 6%
Sports and Recreations 3 4%
Engineering 2 3%
Other 8 12%
Unknown 23 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 12 June 2012.
All research outputs
#20,657,128
of 25,374,917 outputs
Outputs from Biofactors
#688
of 937 outputs
Outputs of similar age
#141,676
of 181,000 outputs
Outputs of similar age from Biofactors
#4
of 10 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 937 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
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 181,000 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.