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Building a system dynamics model of body weight regulation and obesity

Building a system dynamics model of body weight regulation and obesity. Özge Karanfil PhD student Department of Biomedical Physiology and Kinesiology, SFU ozgekaranfil@gmail.com 19th MIT-UAlbany-WPI System Dynamics PhD Colloquium October 30, 2009. Outline. Introduction Methodology

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Building a system dynamics model of body weight regulation and obesity

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  1. Building a system dynamics model of body weight regulation and obesity Özge Karanfil PhD student Department of Biomedical Physiology and Kinesiology, SFU ozgekaranfil@gmail.com 19th MIT-UAlbany-WPI System Dynamics PhD Colloquium October 30, 2009

  2. Outline • Introduction • Methodology • Problem Description and Research Objectives • Data • Weight cycling, or “yo-yo dieting”, as a common feature

  3. Introduction • Obesity is a problem.. • Factors influencing obesity and the regulation of body weight have been under intensive investigation • Growing interest has culminated in the growth of simulation models: • as a tool to investigate this complex system • as a means for evaluating hypotheses concerning the underlying pathology • Obesity is a“dynamically complex” problem.. • A dynamic problem is one that necessitates continuous monitoring and action (“management”). “Chronic” problems. • Internal structure is the main cause of dynamic behavior

  4. Introduction • Body weight regulation constitutes a suitable area for simulation modeling: • Feedback complexity of the underlying structure • Different levels of factors involved (genetic, dietary, life-style ..) • Time delays, interplay of factors make it difficult to make quantitative predictions of dynamic patterns • System dynamics is appropriate for quantitative analysis of chronic problems

  5. Methodology- Steps of System Dynamics methodology • Problem identification (a dynamic feedback problem is selected) • Model conceptualization (causal loop diagramming) • Model construction (mathematical, numeric) • Simulation & verification testing • Validation (is my model appropriate for real life?) • Analysis and results • Implementation

  6. Problem Description and Research Objectives • Most adults maintain a stable body weight and composition, in spite substantial deviations in their daily food intakes, physical activity levels, resulting energy balances.. (Flatt, 1995) • Energy In and Energy Out tend to remain adjusted, and protein, carbohydrate, fat balances are achieved • As long as this is not the case, body composition keeps changing • Deviations from energy balance trigger body’s homeostatic mechanisms: • 1-Regulating food intake • 2-Altering rate of energy expenditure • 3-Altering the composition of fuel mix used for energy generation

  7. Some of core physiological mechanisms Energy Intake-Expenditure adapted from Abdel-Hamid TK. 2002. “Modeling the dynamics of human energy regulation and its implications for obesity treatment”. System Dynamics Review 18:431-71

  8. Some of core physiological mechanisms Energy Intake-Expenditure Adapted from Abdel-Hamid TK. 2002. “Modeling the dynamics of human energy regulation and its implications for obesity treatment”. System Dynamics Review 18:431-71

  9. Carbohydrate-fat interactions and obesity examined by a two-compartment computer model Adapted from Flatt JP. 2004. “Carbohydrate-fat interactions and obesity examined by a two-compartment computer model”. Obesity Research 12:2013-22

  10. Carbohydrate–Fat Interactions and Obesity Examined by a Two-Compartment Model- J. P. Flatt • A systems dynamics computer model to examine how interactions between CHO and Fat metabolism influence BW regulation • Environmental factors such as food palatability, and availability can be expected to raise the range within which glycogen levels are habitually maintained. • This restrains fat oxidation, until expansion of the fat mass is sufficient to promote fat oxidation to a rate commensurate with dietary fat intake. This metabolic leverage can explain why increased food offerings tend to raise the prevalence of obesity. • Flatt JP. 2004. “Carbohydrate-fat interactions and obesity examined • by a two-compartment computer model”. Obesity Research 12:2013-22

  11. Two-compartment model showing the impact of circumstantial, lifestyle & genetic factors on glycogen levels and fat stores • Reflects operation of a 2 reservoir-system: representing the body’s limited glycogen, and its large fat reserves. Outflows from reservoirs correspond to oxidation of glucose and fat, whose relative contributions are affected by size of prevailing glycogen and fat reserves. • Flow through the small turbine reflects the exclusive use of glucose by the brain • Flow through large turbine represents EE in the rest of the body to which 2 reservoirs contribute in proportion to levels of fuel they contain at a given time The conduit from the small to the large reservoir: lipogenesis Flatt JP. 1995. McCollum Award Lecture, 1995: diet, lifestyle, and weight maintenance. Am. J. Clin. Nutr. 62:820-36

  12. The two main issues for body weight maintenance in obesity Well known and less well known variables affecting adiposity and their potential role in explaining the increased incidence of obesity revealed by the (NHANES Ill) data. Flatt JP. 1995. McCollum Award Lecture, 1995: diet, lifestyle, and weight maintenance. Am. J. Clin. Nutr. 62:820-36

  13. Computational model of in vivo human energy metabolism during semistarvation and refeeding • A general simulation model for body weight change based on the Minnesota Starvation Experiment (1940). • Model consists of 3 macronutrient compartments (stocks) : fat, glycogen and protein, and fluxes (flows) between them. • Energy intake of fat, carbohydrate and protein are external inputs. Hall KD. 2006. Computational model of in vivo human energy metabolism during semistarvation and refeeding. Am. J. Physiol Endocrinol. Metab 291:E23-E37

  14. Hall Model- Stock-Flow diagram Adapted from Hall KD. 2006. Computational model of in vivo human energy metabolism during semistarvation and refeeding. Am. J. Physiol Endocrinol. Metab 291:E23-E37

  15. Hall Model- Stock-Flow diagram Body Composition Fat Metabolism Protein Metabolism Physical Activity Expenditure Resting Metabolic Rate Macronutrient Oxidation Rates Adapted from Hall KD. 2006. Computational model of in vivo human energy metabolism during semistarvation and refeeding. Am. J. Physiol Endocrinol. Metab 291:E23-E37

  16. Why to model food intake regulation? • Diet induced changes in “energy expenditure” help to slightly attenuate the gap between energy intake & expenditure, but does not have power to offset energy imbalances. (Flatt, 1978) • Regulation of “energy intake” appears to be a more important phenomenon to help achieving a steady-state body weight. • Less well explored by previous models, also less is known • We aim to explore interactions between food intake regulation and body composition.

  17. Different “levels” • “Human energy and weight regulation is a complex of nested feedback processes at multiple levels”. • 1- Physiological aspects • 2- Aspects between the physiology and thebehaviour – Combination of voluntary and involuntary effects • 3- Environmental, cognitive aspects

  18. Research Questions • How does food intake- dietcomposition effect the effort of losing weight? • How does our body composition change when we lose and gain weight, and what are the implications of this for further attempts of weight loss? • Can we simulate this model to examine a common feature: “weight cycling”?

  19. Weight cycling, or “yo-yo dieting” • Unintended consequences of dieting: Detrimental effects on body composition? Both supportive and counter-arguments can be found • Cannon G, Einzig H. 1983. Dieting makes you fat. London: Century Publishing. • We believe that drivers for “natural” weight cycles and today’s “yo-yo dieting” and consequent body weight trajectories are different in nature. • First dynamic behavior is mainly driven by an “externally” imposed function. • We cannot observe a similar external data source for the latter. Fig. Seasonal fluctuations in body weight in rural Gambian women. Plot derived from over 20 000 measurements in women of child-bearing age. (Prentice et. al, 1992)

  20. When does weight cycling become more interesting for us? • We see a pattern in the real data, but cannot observe any externally imposed functions to explain this cyclic behavior . • No simple, straight answers, no straight-line-thinking! • Endogenous (structural) explanation for weight cycles • Without having external data force, peoples weights are oscillating, i.e. problem “structural”. • “Structure”: Complex interactions between our physiology, psychology, behavior & social factors • Problem is quantitative and dynamic: well suited to computer simulation. • Iteratively develop models of varying size & scope along with the development of hypotheses & supporting evidence.

  21. A model for the dynamics of human weight cycling Adapted from Goldbeter A. 2006. “A model for the dynamics of human weight cycling”. Journal of Biosciences 31:129-36

  22. Summary • Previous models on body weight regulation are explored in detail, reproduced and simulated when possible • The application of system dynamics is appropriate because of the central role homeostatic (feedback) processes play in human energy regulation. • Regulation of food intake behavior appears to be an important phenomenon to help achieving a steady-state body weight, needs to be further explored • Investigating the weight cycling phenomenon would be a good application of SD modeling.

  23. References • Abbott, WGH, Howard BV, Christin L. et al. 1988. Short-term energy balance: relationship with protein, carbohydrate, and fat balances A. J. Physiology. 255: E 332-7. • Abdel-Hamid TK. 2002. Modeling the dynamics of human energy regulation and its implications for obesity treatment. System Dynamics Review 18:431-71 • Abdel-Hamid TK. 2003. Exercise and diet in obesity treatment: an integrative system dynamics perspective. Med. Sci. Sports Exerc. 35:400-13 • Bjöntorp P, Sjöström L. 1978. Carbohydrate storage in man: speculations and some quantitative considerations. Metabolism. 27:1853- 65. • Cannon G, Einzig H. 1983. Dieting makes you fat. London: Century Publishing. • Chow CC, Hall KD. 2008. The dynamics of human body weight change. PLoS. Comput. Biol. 4:e1000045 • Christakis NA, Fowler JH. 2007. The spread of obesity in a large social network over 32 years. N. Engl. J. Med. 357:370-9 • Christiansen E, Swann A, Sorensen TIA. 2008. Feedback models allowing estimation of thresholds for self-promoting body weight gain. Journal of Theoretical Biology 254:731-6 • Flatt, JP. 1978. The biochemistry of energy expenditure. In: Bray GA, ed. Recent advances in obesity research. Vol 2. London: Newman, 1978:211-28. • Flatt, JP. 1987. Dietary fat, carbohydrate balance, and weight maintenance: effects of exercise. Am J Clin Nutr. 45: 296-306 • Flatt JP. 1995. McCollum Award Lecture, 1995: diet, lifestyle, and weight maintenance. Am. J. Clin. Nutr. 62:820-36 • Flatt JP. 2004. Carbohydrate-fat interactions and obesity examined by a two-compartment computer model. Obes. Res. 12:2013-22 • Goldbeter A. 2006. A model for the dynamics of human weight cycling. Journal of Biosciences 31:129-36 • Hall KD. 2006. Computational model of in vivo human energy metabolism during semistarvation and refeeding. Am. J. Physiol Endocrinol. Metab 291:E23-E37 • Homer J, Milstein B, Dietz W, Buchner D, Majestic D. 2006. Obesity population dynamics: exploring historical growth and plausible futures in the U.S. 24th International System Dynamics Conference; Nijmegen,The Netherlands. • Keys A, Brozek J, Henschel A, Mickelsen 0, Taylor HL. 1950. The biology of human starvation. Minneapolis; University of Minnesota Press. • Mayer J, Thomas DW. 1967. Regulation of food intake and obesity. Science.156:328-37. • Oga H, Uehara T. 2003. An Application of System Dynamics to an Obesity Prevention Program: Simulation of the Risk Reduction of Cardiovascular Disease and the Savable Medical Expenses. Proceedings of the 21st International Conference of the System Dynamics Society. • Prentice AM, Jebb SA, Goldberg GR, Coward WA, Murgatroyd PR, Poppitt SD, Cole TJ. 1992. Effects of weight cycling on body composition, American Journal of Clinical Nutrition. 56: 209S-216S

  24. (My) Questions • One shortcoming of the second part of this proposal: • It may be hard to find empirical data in these areas, so that we can test our theories (i.e models). • Do you know any good datasets to study.. • How dieting affects body composition, and vice versa? • Weight cycling/ yo-yo dieting, its effect on further attempts of losing weight? • Contact: ozgekaranfil@gmail.com

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