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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Issues in characterizing resting energy expenditure in obesity and after weight loss
|
|---|---|
| Published in |
Frontiers in Physiology, January 2013
|
| DOI | 10.3389/fphys.2013.00047 |
| Pubmed ID | |
| Authors |
Anja Bosy-Westphal, Wiebke Braun, Britta Schautz, Manfred J. Müller |
| Abstract |
Limitations of current methods: Normalization of resting energy expenditure (REE) for body composition using the 2-compartment model fat mass (FM), and fat-free mass (FFM) has inherent limitations for the interpretation of REE and may lead to erroneous conclusions when comparing people with a wide range of adiposity as well as before and after substantial weight loss. Experimental objectives: We compared different methods of REE normalization: (1) for FFM and FM (2) by the inclusion of %FM as a measure of adiposity and (3) based on organ and tissue masses. Results were compared between healthy subjects with different degrees of adiposity as well as within subject before and after weight loss. Results: Normalizing REE from an "REE vs. FFM and FM equation" that (1) was derived in obese participants and applied to lean people or (2) was derived before weight loss and applied after weight loss leads to the erroneous conclusion of a lower metabolic rate (i) in lean persons and (ii) after weight loss. This is revealed by the normalization of REE for organ and tissue masses that was not significantly different between lean and obese or between baseline and after weight loss. There is evidence for an increasing specific metabolic rate of FFM with increasing %FM that could be explained by a higher contribution of liver, kidney and heart mass to FFM in obesity. Using "REE vs. FFM and FM equations" specific for different levels of adiposity (%FM) eliminated differences in REE before and after weight loss in women. Conclusion: The most established method for normalization of REE based on FFM and FM may lead to spurious conclusions about metabolic rate in obesity and the phenomenon of weight loss-associated adaptive thermogenesis. Using %FM-specific REE prediction from FFM and FM in kg may improve the normalization of REE when subjects with wide differences in %FM are investigated. |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 14% |
| United States | 1 | 14% |
| United Kingdom | 1 | 14% |
| Switzerland | 1 | 14% |
| Unknown | 3 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 86% |
| Scientists | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 1% |
| Unknown | 70 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 18% |
| Student > Ph. D. Student | 8 | 11% |
| Student > Master | 7 | 10% |
| Other | 6 | 8% |
| Student > Doctoral Student | 5 | 7% |
| Other | 17 | 24% |
| Unknown | 15 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 20% |
| Sports and Recreations | 9 | 13% |
| Agricultural and Biological Sciences | 9 | 13% |
| Social Sciences | 5 | 7% |
| Biochemistry, Genetics and Molecular Biology | 4 | 6% |
| Other | 11 | 15% |
| Unknown | 19 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 04 January 2022.
All research outputs
#3,034,759
of 25,223,158 outputs
Outputs from Frontiers in Physiology
#1,623
of 15,509 outputs
Outputs of similar age
#29,795
of 293,113 outputs
Outputs of similar age from Frontiers in Physiology
#50
of 399 outputs
Altmetric has tracked 25,223,158 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 15,509 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one has done well, scoring higher than 89% 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 293,113 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 399 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.