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
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Introduction
Methodology
Problem Description and Research Objectives
Data
Weight cycling, or “yo-yo dieting”, as a common feature
2
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..

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A dynamic problem is one that necessitates continuous monitoring
and action (“management”). “Chronic” problems.
Internal structure is the main cause of dynamic behavior
3
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
4
MethodologySteps 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
5
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)
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
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:
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1-Regulating food intake
2-Altering rate of energy expenditure
3-Altering the composition of fuel mix used for energy generation
energy intake (EI)
Total energy
stored in body
energy
expenditure (EE)
6
Some of core physiological mechanisms
Energy Intake-Expenditure
thermogenesis
+ daily energy+
expenditure (EE)
+
-
-
daily energy
intake (EI)
-
food intake
-
+ daily energy
surplus
-
resting energy
expenditure (REE)
+
-
endocrine factors
e.g. leptin
-
+
+
size and number of
fat cells
+
Body fat
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
7
Some of core physiological mechanisms
Energy Intake-Expenditure
thermogenesis
+ daily energy+
expenditure (EE)
+
-
-
daily energy
intake (EI)
-
food intake
-
+ daily energy
surplus
-
resting energy
expenditure (REE)
+
-
endocrine factors
e.g. leptin
-
+
+
size and number of
fat cells
+
Body fat
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
Carbohydrate-fat interactions and obesity examined
by a two-compartment computer model
+
effect of insulin
Insulin
+
-
+
+
CHO oxidation
by body
+
-
total energy need
+
-
+
TG oxidation by
body
+
Total Body CHOGlycogen (GLY)
-
-
-
-
Total Body FatTrigycerides (TG)
CHO-fat ratio
+
-
-
basal metabolic
rate (BMR)
+
CHO oxid by
+
brain
Adapted from Flatt JP. 2004. “Carbohydrate-fat interactions and obesity examined
by a two-compartment computer model”. Obesity Research 12:2013-22
9
Carbohydrate–Fat Interactions and Obesity
Examined by a Two-Compartment Model- J. P. Flatt
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A systems dynamics computer model to
examine how interactions between CHO and
Fat metabolism influence BW regulation
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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
10
Two-compartment model showing the impact of circumstantial,
lifestyle & genetic factors on glycogen levels and fat stores
The conduit from the small to the large
reservoir: lipogenesis
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Reflects operation of a 2 reservoirsystem: 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
Flatt JP. 1995. McCollum Award Lecture, 1995: diet, lifestyle, and weight maintenance.
Am. J. Clin. Nutr. 62:820-36
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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
12
Computational model of in vivo human energy
metabolism during semistarvation and refeeding
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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 13
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
14
Hall Model- Stock-Flow diagram
Body
Composition
Fat
Metabolism
Physical Activity
Expenditure
Protein
Metabolism
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
15
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.
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Different “levels”

“Human energy and weight regulation is a complex of
nested feedback processes at multiple levels”.
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1- Physiological aspects
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2- Aspects between the physiology and the behaviour –
Combination of voluntary and involuntary effects
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3- Environmental, cognitive aspects
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Research Questions

How does food intake- diet composition effect the effort
of losing weight?
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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”?
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Weight cycling, or “yo-yo dieting”
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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 “yoyo 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)
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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!
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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.

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Iteratively develop models of varying size & scope along with the
development of hypotheses & supporting evidence.
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A model for the dynamics of human
weight cycling
+
expenditure
-
dietary intake undergoes a sharp
decrease once restraint exceeds
a threshold level
Body Weight
threshold value for
action
+
+
extra weight -
+
craving
+
-
Dietary
Intake
-
+
+
the stronger the restriction, the
stronger the "craving" to increase
dietary intake
Cognitive
Restraint
-
-
+
eff of limit on
restraint
max limit of
restraint
Adapted from Goldbeter A. 2006. “A model for the dynamics
of human weight cycling”. Journal of Biosciences 31:129-36
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Summary
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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.
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References
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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
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(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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