| Title |
A mathematical model of the effects of resistance exercise-induced muscle hypertrophy on body composition
|
|---|---|
| Published in |
European Journal of Applied Physiology, December 2017
|
| DOI | 10.1007/s00421-017-3787-6 |
| Pubmed ID | |
| Authors |
Marcella Torres, Eric T. Trexler, Abbie E. Smith-Ryan, Angela Reynolds |
| Abstract |
Current diet and exercise methods used to maintain or improve body composition often have poor long-term outcomes. We hypothesize that resistance exercise (RE) should aid in the maintenance of a healthy body composition by preserving lean mass (LM) and metabolic rate. We extended a previously developed energy balance model of human metabolism to include muscle hypertrophy in response to RE. We first fit model parameters to a hypothetical individual to simulate an RE program and then compared the effects of a hypocaloric diet only to the diet with either cardiovascular exercise (CE) or RE. We then simulated a cohort of individuals with different responses to RE by varying the parameters controlling it using Latin Hypercube Sampling (LHS). Finally, we fit the model to mean data from an elderly population on an RE program. The model is able to reproduce the time course of change in LM in response to RE and can be used to generate a simulated cohort for in silico clinical studies. Simulations suggest that the additional LM generated by RE may shift the body composition to a healthier state. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 50% |
| Japan | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
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 | 12 | 18% |
| Student > Master | 7 | 10% |
| Student > Doctoral Student | 6 | 9% |
| Researcher | 6 | 9% |
| Student > Ph. D. Student | 6 | 9% |
| Other | 10 | 15% |
| Unknown | 20 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Sports and Recreations | 19 | 28% |
| Nursing and Health Professions | 6 | 9% |
| Engineering | 4 | 6% |
| Mathematics | 3 | 4% |
| Medicine and Dentistry | 3 | 4% |
| Other | 7 | 10% |
| Unknown | 25 | 37% |
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 30 March 2020.
All research outputs
#17,292,294
of 25,382,440 outputs
Outputs from European Journal of Applied Physiology
#3,318
of 4,345 outputs
Outputs of similar age
#280,966
of 446,012 outputs
Outputs of similar age from European Journal of Applied Physiology
#46
of 60 outputs
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