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Sports Medicine

, Volume 35, Issue 5, pp 393–412 | Cite as

Interactions of Metabolic Hormones, Adipose Tissue and Exercise

  • Robert G. McMurrayEmail author
  • Anthony C. Hackney
Review Article

Abstract

Physiological and psychological systems work together to determine energy intake and output, and thus maintain adipose tissue. In addition, adipose tissue secretes leptin and cytokines, which induces satiety and has been linked to catecholamines, cortisol, insulin, human growth hormone, thyroid hormones, gonadotropin and lipolysis. Thus, adipose tissue is acted upon by a number of physiological stimuli, including hormones, and simultaneously, is an active component in the regulation of its own lipid content. All of the hormones mentioned above are associated with each other and respond to exercise and exercise training. Thus, exercise is one of the major links between the hormonal modulators of energy intake and output. It appears that the sympathetic nervous system and the catecholamines are key components facilitating the lipolytic activity during exercise. These two neuroendocrine factors directly affect adipose metabolism and metabolic hormones that influence adipose metabolism. Acute low- and moderate-intensity exercise causes hormonal changes that facilitate lipolytic activity. Exercise training reduces these hormonal responses, but the sensitivity to these hormones increases so that lipolysis may be facilitated. Large amounts of adipose tissue blunt the metabolic hormonal responses to exercise, but the sensitivity of these hormones is increased; thus maintaining normal lipolytic activity. Although the physiological role of the endocrine system during exercise and training is significant, other training effects may have as great, or greater influence on lipolytic activity in adipose tissue.

Keywords

Cortisol Adipose Tissue Testosterone Thyroid Hormone Sympathetic Nervous System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The authors have provided no information on sources of funding or on conflicts of interest directly relevant to the content of this review.

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© Adis Data Information BV 2005

Authors and Affiliations

  1. 1.CB#8700, Fetzer GymUniversity of North Carolina at Chapel HillChapel HillUSA

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