This document discusses body image and eating disorders behaviors and the effects of personal networks. It summarizes research on how personal networks can influence individuals' perceptions of their own body image. The study uses survey data from 284 individuals with eating disorders to analyze their ego-centric networks and relate network features to discrepancies between self-perceived, ideal, and perceived-by-others body images. The results suggest that network structure, composition, and relational proximity influence body image distortions, especially for overweight individuals. Characteristics like gender heterogeneity, medical treatment, age, and sports activity were also found to impact body image gaps.

1. Body image and eating
disorders behaviors.
The effects of personal
networks
Paola Tubaro!
University of Greenwich, London &
CNRS, Paris!
Francesca Pallotti!
University of Greenwich, London!
Antonio A. Casilli!
Telecom ParisTech & EHESS, Paris!
Thomas W. Valente!
University of Southern California, Los
Angeles!

2. INTRODUCTION
Eating disorders and body image
• Eating disorders are characterized by abnormal eating behaviors
with either insufficient or excessive food intake and exercising to
the detriment of physical and mental health.
• Eating disorders are accompanied by distorted perceived body
image.

3. Body image and behavior
Self-perceived image affects individuals’ behavior
Source: A Brazilian campaign against anorexia

4. Body image and peer effects
Networks, peer effects and body image
• Peer pressure is know to be a significant contributor to body image
concerns and eating attitudes (Costa-Font and Jofre-Bonetpeer, 2011).
• "Teen girls' concerns about their own weight, about how they appear to
others and their perceptions that their peers want them to be thin are
significantly related to weight-control behavior“ (Mackey and La Greca,
2008)
• We use a network perspective to look more closely at the social
environment to establish the extent to which interpersonal relationships
affect the perception of individuals with respect to their body image

5. Our approach
A personal networks approach
• We use ego-centric network data collected through a web survey
of 284 English- and French-speaking respondents with eating
disorders (Research project: Anamia).
• Network data include information on their broadly defined
personal networks including face-to face and Internet-based
networks.

6. The online questionnaire
Questionnaire interface

7. General personal networks: using a visual sociogram
• In the online questionnaire, a
graphical ego network applet
enabled participants to draw
their personal networks!
• Two graphical networks each!
– general personal network
(school, family, workplace
etc.)!
– online personal network
(forums, blogs etc.)!
The ANAMIA study

8. Network structure and composition
• Each graphical interface
enabled participants to:!
– Add alters, specifying name,
gender, and qualification
(friend, family member etc.)!
– Position emotionally closest
alters next to ego, and less
close alters further away!
– Draw ties between alters;!
– Group alters in social circles
(schoolmates, member of a
sports team, participants in a
forum etc.)!
The ANAMIA study

9. Personal networks as drawn by respondents
Some examples of personal networks
Personal network data

10. Data
Ego-networks
• We reconstructed 265 ego-networks
• Two types of network variables:
1. Structural :
– Adjusted density – taking into account social circles
– Size – the number of all alters
2. Compositional:
–
–
–
–
Online and offline alters (multiplexity) (Blau index)
Level of intimacy (proportion)
Gender (proportion and variance)
Qualification (Blau index)

11. Egos’ characteristics
•
Social, demographic and economic
characteristics!
–
•
age, gender, geographic location,
employment, qualifications, income, family
structure, profession of parents, etc.;!
Body and health !
–
–
–
–
Body image (how they see themselves, how
others see them, how they would like to look);!
Body characteristics (current weight;
minimum and maximum weight achieved;
desired weight; weight believed to be healthy
for them; height; BMI); !
Exercise and sports practice; !
Health (what eating disorder, if any; whether
currently or previously under treatment and if
yes, for what diagnosis, with which
professionals, and since when; the
importance of health for them, for their
families, and for their friends);!
Some basic descriptive statistics:!
• 36 FR; 148 UK!
1
• ender: 95% women;!
G
• ge: Average 21.7 (both FR and UK);!
A
• tudents: Average FR 66%, UK 69%;!
S
• orkers: Average FR 34%, UK 41%;!
W
• MI is normal for 53.96% of participants;
B
underweight for 27.55, overweight for 18.49%;!
• ating disorders: EDNOS (FR 47%, UK 45%);
E
Anorexia nervosa (FR 17%, UK 34%); bulimia
nervosa (FR 28%, UK 16%); Binge eating (FR
8%, UK 5%);!
• reatment: over 50% of the participants who
T
reported an eating disorder are being treated
now!

12. Self-perception & Body image
Figure Rating Scale
1
2
3
4
5
6
7
8
9
1. If I had to describe myself, I would say that I look like (perceived body image - D)
2. If I could choose, I would like to look as (ideal body image - C)
3. People usually say that I look like (mediated body image - O)
Each of these variables is measured on a scale ranging from 1 – very thin silhouette – to
9 – corpulent silhouette.

13. Data
Dependent variables
•
•
D – C: Difference between self-description and how one would choose to look;
D – O: Difference between self-description and how people think others see them.
A positive difference would indicate that the respondent’s current body image is
heavier than his/her ideal or mediated body image. A negative difference would
indicate the opposite.

14. MODEL
Analysis
• Two-stages econometric analysis. As a first step, discrepancies in the two
forms of body image are modeled for the whole sample. Secondly, we
evaluate the determinants of discrepancies in body image for individuals in
different BMI categories.
• Model: bivariate ordered probit model to account for the joint distribution of
the two forms of body image distortions, as a function of both individual
attributes and personal network characteristics.
• For the analysis we used the bioprobit Stata program written by Sajaia (2008).
• As our sub-samples consist of a limited number of observations, we check for
the robustness of our models by applying a simple stochastic re-sampling
procedure based on bootstrapping techniques.

15. Results:
• djusted density has an effect on D-C.
A
This result is also confirmed for the
normal weight and overweight subsamples.
• ize is significant only for over- and
S
under-weight individuals.
• elational proximity matters for D-C,
R
for overweight only.
• eterogeneity in sex also matters for
H
over- and under-weight individuals.
• roportion of females: negative effect
P
for the underweight, positive effect for
normal weight

16. Also:
• ositive effect of BMI (difference
P
between individual BMI and country-level
average BMI): The more corpulent I am
relative to my general social
environment, the more dissatisfied I am
with my body image.
• ositive effect of medical treatment on
P
both D – C and D – O.
• egative effect of age: older people
N
seem to have narrower gaps.
• ositive effect of doing sports on both D
P
– C and D – O.

17. Conclusions
Effects of network structure and composition
• ffects of individual variables confirm findings from the literature (peer effects
E
from social environment broadly interpreted)
• n addition, we find evidence of network effects on body image distortions
I

18. THANKS!
For more information: www.anamia.fr/en
Contact: coordination@anamia.fr, p.tubaro@gre.ac.uk, f.pallotti@gre.ac.uk
Twitter: @anamia