Literature DB >> 18671981

Feedback models allowing estimation of thresholds for self-promoting body weight gain.

Edmund Christiansen1, Andrew Swann, Thorkild I A Sørensen.   

Abstract

OBJECTIVE: Most people maintain almost constant body weight over long time with varying physical activity and food intake. This indicates the existence of a regulation that works well for most individuals. Yet some people develop obesity, indicating that this regulation sometimes fails. The difference between the two situations is typically an energy imbalance of about 1% over a long period of time. THEORY: Weight gain increases basal metabolic rate. Weight gain is often associated with a decrease in physical activity, although not to such an extent that it prevents an increase in total energy expenditure and energy intake. Dependent on the precise balance between these effects of weight gain, they may make the body weight unstable and tend to further promote weight gain. With the aim of identifying the thresholds beyond which such self-promoting weight gain may take place, we develop a simple mathematical model of the body as an energy-consuming machine in which the changes in physical activity and food intake are described as feedback effects in addition to the effect of the weight gain on basal metabolic rate. The feedback parameters of the model may differ between individuals and only in some cases do they take values that make weight gain self-promoting.
RESULTS: We determine the quantitative conditions under which body weight gain becomes self-promoting. We find that these conditions can easily be met, and that they are so small that they are not observable with currently available techniques. This phenomenon encourages emphasis on even minor changes in food intake and physical activity to abate or stop weight gain.

Entities:  

Mesh:

Year:  2008        PMID: 18671981     DOI: 10.1016/j.jtbi.2008.07.004

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  6 in total

1.  Rate of weight gain predicts change in physical activity levels: a longitudinal analysis of the EPIC-Norfolk cohort.

Authors:  R Golubic; U Ekelund; K Wijndaele; R Luben; K-T Khaw; N J Wareham; S Brage
Journal:  Int J Obes (Lond)       Date:  2012-04-24       Impact factor: 5.095

Review 2.  Simulation models of obesity: a review of the literature and implications for research and policy.

Authors:  D T Levy; P L Mabry; Y C Wang; S Gortmaker; T T-K Huang; T Marsh; M Moodie; B Swinburn
Journal:  Obes Rev       Date:  2010-10-26       Impact factor: 9.213

Review 3.  Gene-nutrient interactions and susceptibility to human obesity.

Authors:  Joseph J Castillo; Robert A Orlando; William S Garver
Journal:  Genes Nutr       Date:  2017-10-30       Impact factor: 5.523

4.  The FTO genetic variants are associated with dietary intake and body mass index amongst Emirati population.

Authors:  Maha Saber-Ayad; Shaista Manzoor; Hadia Radwan; Sarah Hammoudeh; Rahaf Wardeh; Ahmed Ashraf; Hussein Jabbar; Rifat Hamoudi
Journal:  PLoS One       Date:  2019-10-17       Impact factor: 3.240

5.  Assessing causality in the association between child adiposity and physical activity levels: a Mendelian randomization analysis.

Authors:  Rebecca C Richmond; George Davey Smith; Andy R Ness; Marcel den Hoed; George McMahon; Nicholas J Timpson
Journal:  PLoS Med       Date:  2014-03-18       Impact factor: 11.069

6.  Physical activity, sedentary time and gain in overall and central body fat: 7-year follow-up of the ProActive trial cohort.

Authors:  R Golubic; K Wijndaele; S J Sharp; R K Simmons; S J Griffin; N J Wareham; U Ekelund; S Brage
Journal:  Int J Obes (Lond)       Date:  2014-04-15       Impact factor: 5.095

  6 in total

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