title: Understanding the metabolic syndrome: a modeling perspective.
abstract: The prevalence of obesity is growing at an alarming rate, placing many at risk for developing diabetes, hypertension, sleep apnea, or a combination of disorders known as "metabolic syndrome". The evidence to date suggests that metabolic syndrome results from an imbalance in the mechanisms that link diet, physical activity, glucose-insulin control, and autonomic cardiovascular control. There is also growing recognition that sleep-disordered breathing and other forms of sleep disruption can contribute significantly to autonomic dysfunction and insulin resistance. Chronic sleep deprivation resulting from sleep-disordered breathing or behavioral causes can lead to excessive daytime sleepiness and lethargy, which in turn contribute to increasing obesity. Analysis of this complex dynamic system using a model-based approach can facilitate the delineation of the causal pathways that lead to the emergence of the metabolic syndrome. In this paper, we provide an overview of the main physiological mechanisms associated with obesity and sleep-disordered breathing that are believed to result in metabolic and autonomic dysfunction, and review the models and modeling approaches that are relevant in characterizing the interplay among the multiple factors that underlie the development of the metabolic syndrome.
authors.affiliation: Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA. khoo@ bmsr.usc.edu
authors.forename: Michael C K
authors.initials: MC
authors.lastname: Khoo
authors.forename: Flavia M G S
authors.initials: FM
authors.lastname: Oliveira
authors.forename: Limei
authors.initials: L
authors.lastname: Cheng
mesh_terms: D006801:Humans; D024821:Metabolic Syndrome / Q000503:physiopathology*; D008954:Models, Biological; D008991:Monitoring, Physiologic; D009765:Obesity / Q000503:physiopathology*; D012891:Sleep Apnea Syndromes / Q000503:physiopathology*