Networks and Obesity
Stanley Ulijaszek
Institute of Social and Cultural
Anthropology
University of Oxford
Networks and Obesity
• Introduction
• Potential to apply network thinking
–Obesity systems
–Social networks
–Biological networks
• UK Government Foresight launch of ‘Tackling
Obesities: Future Challenges: October 2007
– Huge potential for population obesity to
expand
– energy balance discourse is sterile (neither
can be measured precisely enough to tell)
– the imbalance is clearly there, but is
socially and culturally embedded in ways
not understood
– effective action taken now will take ten
years or more to take effect (like stopping
an oil tanker heading toward a collision)
Unit for Biocultural
Variation and Obesity
School of Anthropology
University of Oxford
www.oxfordobesity.org
Models of population obesity (Ulijaszek 2007)
• Obesity/thrifty genotypes (Neel 1962)
• Classical nutrition transition (Popkin and Doak 1998)
• Developmental programming (Barker 1988)
• Obesogenic environment (Swinburn et al 1999)
• Food behaviour (Rolls 2003)
• Political economic (Foresight 2008)
A need for meta-models of obesity
Toward meta-models of obesity
• Biocultural
• Systems
• Text mining of obesity literature
• Medical
• Social
• Biosocial
Networks and Obesity
• Introduction
• Potential to apply network thinking
–Obesity systems
–Social networks
–Biological networks
Foresight obesity systems map (FOSM) (UK government)
• Conditional success in capturing the United
Kingdom obesity system at the present
• Not intuitive
• No obvious pathways to energy imbalance
• Dealing with novel factors and changing
strength of evidence
• Without continuous updating, it is at risk of
becoming obsolete within a few years
Towards a data model
Structural
representation
Search
algorithm
Software outputs
Scoring
function
• Powerful instrument for understanding
of population obesity, and for
intervention and policy
– Identification of major obesity pathways
–
– Responsive to new evidence
– Determination of whether novel factors
influence or change obesity pathways
identified
Networks and Obesity
• Introduction
• Potential to apply network thinking
–Obesity systems
–Social networks
–Biological networks
The Spread of Obesity in a Large Social Network over 32 Years
Christakis and Fowler 2007
Each circle (node) represents one person in the data set. Circles with red borders denote women,
and circles with blue borders denote men. The size of each circle is proportional to the person’s
body-mass index. The interior color of the circles indicates the person’s obesity status:yellow
denotes an obese person (body-mass index, ≥30) and green denotes a nonobese person. The
colors of the ties between the circlesindicate the relationship between them: purple denotes a
friendship or a marital tie and orange denotes a familial tie. The disappearanceof a circle from one
year to another indicates the person’s death, and the disappearance of a tie between the circles
indicates that the relationshipbetween the two persons no longer exists. Dynamic network.
Social networks and obesity
Geographically extended
Construction of social environments
Social selection
Importance of communication
Networks and Obesity
• Introduction
• Potential to apply network thinking
–Obesity systems
–Social networks
–Biological networks
Obesity involves a combination of
environmental and genetic factors
Most obesity genes regulate one or
more of:
appetite
energy metabolism
fat storage
Neuroendocrine regulation of appetite, energy expenditure
and fat storage in overfeeding (Ulijaszek and Lofink 2006)
Adipose
tissue
Brain
leptin
leptin
receptor
catabolism
alpha
MSH
POMC
neuron
Pancreas
insulin
GLP1
insulin
receptor
grhelin
PYY3-36
Neurons
expressing
MC4R
NPY
NPY/AGRP
neuron
AGRP
energy
expenditure
reproduction
Gut
Appetite genes best understood
appetite &
energy intake
Reorganising energy balance as network
satiety
IN
Fat storage
GSC
OUT
IN2
OUT2
IS
The bow-tie structure of the human metabolic network (giant
strong component: metabolic interchangeability)
Decomposition of the metabolic network for E.coli (Zhao
et al 2006)
Relationships among
metabolic reactions and
genes reanalysed as
hierarchical clustering
tree for GSC; modules
represent strong links
between reactions
Each circle represents a module and is coloured according to the Kyoto Encyclopedia of Genes and
Genomes pathway classification of the reactions belonging to it, while the arcs reflect the connection
between clusters. The area of each colour in one circle is proportional to the number of reactions that
belong to the corresponding metabolism. The width of an arc is proportional to the number of reactions
between the two corresponding modules. For simplicity, bi-directed arcs are presented by grey edges.
Obesity and metabolic networks
Bow tie modules as building blocks of
metabolic networks
Evolution of systems that can predispose
to obesity which fall into three
components, based on genetic
understandings:
Energy metabolism
Appetite
Fat storage