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Physiological models of body composition and human obesity

Overview of attention for article published in Nutrition & Metabolism, September 2007
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

wikipedia
1 Wikipedia page

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
39 Mendeley
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Title
Physiological models of body composition and human obesity
Published in
Nutrition & Metabolism, September 2007
DOI 10.1186/1743-7075-4-19
Pubmed ID
Authors

David G Levitt, Steven B Heymsfield, Richard N Pierson, Sue A Shapses, John G Kral

Abstract

The body mass index (BMI) is the standard parameter for predicting body fat fraction and for classifying degrees of obesity. Currently available regression equations between BMI and fat are based on 2 or 3 parameter empirical fits and have not been validated for highly obese subjects. We attempt to develop regression relations that are based on realistic models of body composition changes in obesity. These models, if valid, can then be extrapolated to the high fat fraction of the morbidly obese.

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Belgium 1 3%
Unknown 37 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 21%
Student > Bachelor 7 18%
Student > Master 5 13%
Student > Ph. D. Student 4 10%
Professor 3 8%
Other 9 23%
Unknown 3 8%
Readers by discipline Count As %
Medicine and Dentistry 10 26%
Agricultural and Biological Sciences 5 13%
Social Sciences 4 10%
Nursing and Health Professions 3 8%
Engineering 2 5%
Other 9 23%
Unknown 6 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 20 October 2013.
All research outputs
#1,161,556
of 4,785,233 outputs
Outputs from Nutrition & Metabolism
#222
of 395 outputs
Outputs of similar age
#49,402
of 170,039 outputs
Outputs of similar age from Nutrition & Metabolism
#9
of 23 outputs
Altmetric has tracked 4,785,233 research outputs across all sources so far. This one has received more attention than most of these and is in the 63rd percentile.
So far Altmetric has tracked 395 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one is in the 42nd percentile – i.e., 42% 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 170,039 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.