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Behavioral Choice Theory and
Obesity: From Molecular
Genetics to Public Policy
Leonard H. Epstein, Ph.D.
Distinguished Professor of Pediatrics and
Social and Preventive Medicine
University at Buffalo School of Medicine
and Biomedical Sciences
1
Behavioral Choice Theory
 Behavioral
choice theory, or
behavioral economics, involves
understanding factors that influence
choice between two or more
alternatives
2
Choice and behavioral interventions

Task of intervention or treatment is to shift
choice from an unhealthy, highly
reinforcing behavior to less reinforcing, but
more healthy alternatives
– Choosing to be more active rather than
sedentary
– Choosing to eat healthier, rather than less
healthy eating
– Choosing to play sports rather than use drugs
3
Choice: now or later?

Concurrent choices
– Eating junk food or healthy food now
– Being sedentary or active now
– Relative reinforcing value; substitutes or
complements

Delayed choices
– Eating healthy now to lose weight later
– Being active now to be stronger and faster later
– Delay discounting or behavioral impulsivity
4
Topics to be addressed from perspective
of behavioral economic theory
Basic science of choice, using drug selfadministration and eating as examples
 What happens to energy balance (the
relationship between energy intake and energy
expenditure) or body composition when you
modify sedentary behaviors?
 What is the role of food pricing on choice?

5
Experimental Design: Alcohol
Dependence




Rats randomized to control, intermittent free choice (once
per week), continuous free choice, or forced intake of
ethanol
Became dependent on ethanol over 32 weeks of drug
administration
Animals kept ethanol-abstinent for 3 months, during which
time they showed withdrawal (change in pain threshold,
hyperthermia, inactivity)
Animals then provided self-administration test
Wolffgramm, J., Heyne, A. (1995). From controlled drug intake to loss of control: the
irreversible development of drug addiction in the rat. Behavioural Brain Research,
6
70, 77-94.
3
2.5
2
g/kg/day ethanol
1.5
1
0.5
0
Controls
Forced
Intermittent
Free Choice
Continuous
Free Choice
Wolffgramm, J., Heyne, A. (1995). From controlled drug intake to
loss of control: the irreversible development of drug addiction in
the rat Behavioural Brain Research, 70, 77-94.
7
Experimental Design : Opiate
Dependence




Rats randomized to control, choice or forced
intake of etonitazene
Became dependent on opiate over 30 weeks of
drug administration
Animals kept opiate-abstinent for 19 weeks,
during which time they showed withdrawal
(change in pain threshold)
Animals then provided self-administration test
Wolffgramm, J., Heyne, A. (1995). From controlled drug intake to loss of control: the
irreversible development of drug addiction in the rat. Behavioural Brain Research,
8
70, 77-94.
90
80
70
60
50
ug/kg/day Etonitazene
40
30
20
10
0
Controls
Forced
Free Choice
Wolffgramm, J., Heyne, A. (1995). From controlled drug intake to loss
of control: the irreversible development of drug addiction in the rat
Behavioural Brain Research, 70, 77-94.
9
Choices for cocaine or
placebo
10
9
8
7
6
Choices 5
4
3
2
1
0
Drug
Placebo
Higgins, Bickel & Hughes. (1994). Influence of an alternative reinforcer on
human cocaine self-administration. Life Sciences, 55, 179-187.
10
Choices for cocaine or placebo
12
10
8
First Exposure
Second Exposure
6
4
2
0
$0.00
$0.50
$1.00
$2.00
Higgins, Bickel & Hughes. (1994). Influence of an alternative reinforcer on
human cocaine self-administration. Life Sciences, 55, 179-187.
11
Fulton, Woodside & Shizgal (2000). Modulation of brain reward circuitry by
leptin. Science, 287, 125-128.
12
13
14
Do genetic factors influence choice
of food as a reinforcer?
Food reinforcement is mediated in part by
dopaminergic activity in the brain
 Dopamine has multiple functions in the brain,
including:
– Locomotor activity
– Feeding and drinking
– Reinforcement
– Appetitive motivation

15
Dopamine, Eating, and Obesity

Dopamine is released in the striatum during eating in
rodents (Heffner et al., 1980; Hernandez & Hoebel, 1988) and
humans (Small et al., 2003)

In genetically obese mice (ob/ob), administration of
dopamine normalizes body weight (Bina & Cincotta, 2000)

In obese humans, dopamine agonists reduce energy
intake (Leddy, et al, 2004)

Chronic treatment with antipsychotic drugs, which block
the dopamine receptors, increases obesity risk (American
Diabetes Association, 2004)
16
Dopamine D2 Receptor

DRD2 may be a common neurobiological substrate
underlying drug addiction and obesity (Volkow & Wise, 2005)

Imaging studies show that obese individuals have
reduced expression of DRD2 similar in magnitude to
reductions reported in drug-addicted subjects (Wang et al.,
2001)
Density of the D2 receptor is related to polymorphisms
of the A1 and A2 alleles, with 3 genotypes: A1/A1,
A1/A2, A2/A2.

17
Taq 1 Al Allele of the DRD2

D2 genotype provides an estimate of DRD2 density and,
thus, an estimate of dopaminergic system activity
– The presence of at least one copy of the Taq 1 A1 allele of the
DRD2 is associated with a 30-40% reduction in the density of
DRD2 (Noble et al., 1994; Jonsson et al., 1999).

A current hypothesis is that reduced sensitivity to dopamine
in individuals with the Taq 1 A1 leads to a need for excess
dopamine in the synapse (Bowirrat & Oscar-Berman, 2005).
18
DRD2 genotypes, food reinforcement,
obesity and energy intake
18 – 40 year olds (n=45 non-obese and
n=29 obese)
 Not currently on a diet
 Not currently on medications that affect
appetite or eating (methylphenidate, etc)
 No eating disorders
 Must like study foods

Epstein, Temple, Neaderhiser, Salis, Erbe, & Leddy, (2007). Food reinforcement, the dopamine D2 receptor
genotype and energy intake in obese and non-obese humans. Behavioral Neuroscience, 121, 877-886.
19
Study Design

Two visits to the laboratory – separated by 1 week

First visit = “taste test”
– Measure energy intake of snack foods
– Take DNA sample

Second visit = food reinforcement
– Participants complete reinforcement task
– Height/weight obtained
Epstein, Temple, Neaderhiser, Salis, Erbe, & Leddy, (2007). Food reinforcement, the dopamine D2 receptor
genotype and energy intake in obese and non-obese humans. Behavioral Neuroscience, 121, 877-886.
20
0
Non-Obese
Obese
Individuals with the Taq 1 A1
allele have a higher BMI
35
Body Mass Index (kg/m2)
30
*
25
20
15
10
5
0
A2/A2
A1/A1 or A1/A2
Epstein, Temple, Neaderhiser, Salis, Erbe, & Leddy, (2007). Food reinforcement, the dopamine D2 receptor
genotype and energy intake in obese and non-obese humans. Behavioral Neuroscience, 121, 877-886.
21
Obese Individuals Find Food More
Reinforcing than Non-Obese
500
400
300
200
100
*
2000
Non-obese (n=45)
Obese (n=29)
Total Button Presses
Number of Button Presses
600
1500
1000
500
0
0
4
8
16
32
64 128 256 512 1024
Non-Obese
Obese
Epstein, Temple, Neaderhiser, Salis, Erbe, & Leddy, (2007). Food reinforcement, the dopamine D2 receptor
genotype and energy intake in obese and non-obese humans. Behavioral Neuroscience, 121, 877-886.
22
Obese Individuals with the Taq 1 A1 Allele
Have the Highest Levels of Food
Reinforcement
Non-Obese/A2/A2 (n=25)
Non-Obese/A1/A1 or A1/A2 (n=20)
Obese/A2/A2 (n=12)
Obese/A1/A1 or A1/A2 (n=17)
600
3000
*
*
*
400
200
Total Button Presses
Number of Button Presses
800
2500
A2/A2
A1/A1 or A1/A2
*
2000
1500
1000
500
0
0
4
8
16
32
64 128 256 512 1024
Non-Obese
Obese
Epstein, Temple, Neaderhiser, Salis, Erbe, & Leddy, (2007). Food reinforcement, the dopamine D2 receptor
genotype and energy intake in obese and non-obese humans. Behavioral Neuroscience, 121, 877-886.
23
Taq 1 A1 Interacts with Food Reinforcement to
Increase Energy Intake
A2/A2
A1/A2 or A1/A1
Energy Consumed (KCal)
1000
800
600
400
200
0
Low
High
Food Reinforcement Level
Epstein, Temple, Neaderhiser, Salis, Erbe, & Leddy, (2007). Food reinforcement, the dopamine D2 receptor
genotype and energy intake in obese and non-obese humans. Behavioral Neuroscience, 121, 877-886.
24
Summary of basic science studies
Choice is important to establish drugs as
rewards
 Relative reinforcing value depends on
behavioral cost and alternatives
 There are genetic and neurobiological
factors that influence choice

25
26
Reinforcing value of physical activity:
Design


Children in three categories:
– Non-obese (<20% overweight)
– Moderately obese (20-80% overweight)
– Very obese (>80% overweight)
Provided access to a moderately liked vigorous
activity at a constant variable ratio (VR2)
reinforcement schedule versus a highly liked
sedentary activity with the schedule varied from VR2
to VR32.
Epstein, Smith, Vara, & Rodefer. (1991). Behavioral economic analysis of
activity choice in obese children. Health Psychology, 10, 311-316.
27
200
Active Time (sec)
175
150
Non-obese
Moderately Obese
Very Obese
125
100
75
50
25
0
2/8
2/32
2/16
2/2
2/4
Vigorous/Sedentary VR Schedules of Reinforcement
Epstein, Smith, Vara, & Rodefer. (1991). Behavioral economic analysis of activity
choice in obese children. Health Psychology, 10, 311-316.
28
How can reducing sedentary
behavior influence energy balance?

Sedentary behaviors can reduce the
opportunity to be physically active
– Reducing sedentary behaviors may increase
physical activity

Sedentary behaviors can increase the
opportunities to eat
– Reducing sedentary behaviors can reduce
energy intake and dietary fat intake
29
30
31
32
33
Effects of decreasing sedentary behavior
versus increasing activity on weight
change in obese children

Obese 8-12 year-old children from 61
families randomized to groups that targeted:
– Increased physical activity
– Decreased sedentary behavior
– Combined increased physical activity,
decreased sedentary behavior

Provided 4 month intensive treatment,
followed at 12 month post randomization
34
Effects of decreasing sedentary behavior
versus increasing activity on weight
change in obese children


Traffic light diet used for reducing calories,
increasing nutrient density and balancing nutrient
intake
Increase activity goals from 30-150 points/week
– 300-1500 kcal/week for a 150 lb person

Decrease sedentary from 35 hours/week to goal of
15 hours/week
– decreases in 5 hour increments
35
Epstein et al. (1995). Effects of decreasing sedentary behavior and increasing
physical activity on weight change in obese children. Health Psychology, 14,
109-115.
36
Epstein et al. (1995). Effects of decreasing sedentary behavior and
increasing physical activity on weight change in obese children. Health
Psychology, 14, 109-115.
50
45
40
35
30
Exercise
Combined
Reduce sedentary
25
20
15
10
5
0
Change in liking for physical activity
37
What happens to eating and activity when
you change sedentary behavior?

58 families with non-obese and obese 12-15 year-old
children
– Participated in a 9 week experiment
» Baseline: maintain usual pattern of sedentary behavior, physical
activity and energy intake.
» Increase sedentary behavior by 25% to 50% of baseline
» Decrease sedentary behavior by 25% to 50% of baseline



– Targeted sedentary behaviors were watching TV or VCR,
playing computer games, or using the internet.
Activity measured using tri-axial accelerometer
Dietary intake from repeated 24-hour phone dietary recalls
Epstein LH, Paluch RA, Consalvi A, Riordan K, Scholl T. Effects of manipulating38
sedentary behavior on physical activity and food intake. J Pediatr. 2002; 140:334-339.
Changes in targeted sedentary behaviors from
baseline during increase and decrease phases
Change in minutes of targeted sedentary
behavior/ day from baseline
150
***
100
50
0
- 50
- 100
***
- 150
Increase
Decrease
Epstein, L. H., Roemmich, J. N., Paluch, R. A., & Raynor, H. A. (2005). Physical activity as a substitute
for sedentary behavior in youth. Annals of Behavioral Medicine, 29, 200-209.
39
a
600
a
500
400
b
300
200
100
Diet ar y f at int ak e in associat ion wit h
t ar get ed sed ent ar y b ehavior
Ener gy int ak e (k cal/ d ay) associat ed wit h
t ar get ed sed ent ar y b ehavior s
Energy intake in association with watching television influenced
more by reducing than increasing sedentary behaviors
240
a
220
200
a
180
160
140
b
120
100
80
60
Design:
16 of the nonoverweight
12-16 year-old
youth who did not
underreport
energy Intake
were studied
in the same 3phase within
subjects design
40
Baseline Increase Decrease
Baseline Increase Decrease
Phases
Phases
Epstein, L. H., Roemmich, J. N., Paluch, R. A., & Raynor, H. A. (2005). The
influence of changes in sedentary behavior on energy and macronutrient intake in
40
youth. American Journal of Clinical Nutrition, 81, 361-366.
41
Can reducing television watching
modify z-BMI in 4-7 year-old youth?

Most programs to change body weight
involve combinations of programs to
decrease energy intake and increase
physical activity
– Reducing television watching may have an
impact on body weight since the effects on
reducing energy intake are potentially so strong
– Even if the effects on physical activity are more
limited
42
Can reducing television watching
modify z-BMI in 4-7 year-old youth?

70 4-7 year-old children at the 75th BMI percentile or
greater were randomized to:
– A TV and computer game reduction group
» Goal of reducing these targeted sedentary behaviors by 50%
» Provided TV Allowance monitors as well as monthly newsletters.

Newsletter provided ideas for substitutes for watching television and
ideas for parenting
– Monitoring control group
» TV Allowance devices but no reduction goals
» Received newsletter without ideas for substitutes or parenting
– Activity measured using accelerometers
– Dietary intake measured using food frequency questionnaire
(Rockett)
43
Hours of television and computer garmes/week
30
Control group
TV reduction group
25
20
15
10
5
-6
0
6
12
18
24
Months
Epstein, L.H., Roemmich, J.N., Robinson, J.L., Paluch, R.A., Winiewicz, D.D., Fuerch, J.H. &
Robinson, T.N. (2008). A randomized trial on the effects of reducing television on BMI in
young children. Archives of Pediatrics and Adolescent Medicine, 162, 239-245.
44
1.70
Control group
TV reduction group
1.65
1.60
zBMI
1.55
1.50
1.45
1.40
1.35
1.30
-6
0
6
12
18
24
X Data
Epstein, L.H., Roemmich, J.N., Robinson, J.L., Paluch, R.A., Winiewicz, D.D., Fuerch, J.H. &
Robinson, T.N. (2008). A randomized trial on the effects of reducing television on BMI in
young children. Archives of Pediatrics and Adolescent Medicine, 162, 239-245.
45
1600
Control group
TV reduction group
Energy intake/day
1500
1400
1300
1200
1100
-6
0
6
12
18
24
Months
Epstein, L.H., Roemmich, J.N., Robinson, J.L., Paluch, R.A., Winiewicz, D.D., Fuerch, J.H. &
Robinson, T.N. (2008). A randomized trial on the effects of reducing television on BMI in
young children. Archives of Pediatrics and Adolescent Medicine, 2008, 239-245.
46
Background on pricing research

The first step in consuming food is purchasing
food
• Over the past three decades less healthy foods have
become much cheaper in comparison to healthier
alternatives.
– Increases in energy intake are due in part to
purchasing increased energy.

Pricing interventions are powerful ways to
modify purchasing and thus consumption
Own-price elasticity

Price of A is negatively related to purchases of A
– Price of coffee increases, demand for coffee decreases

Experimental studies have shown increases in
purchases of healthier foods as their price is
reduced (subsides) and reductions in purchases of
less healthy foods as their price is increased (taxes)
–
–
–
–
French et. al. (1997) Pricing strategy to promote fruit and vegetable purchases in high school cafeteria.
Journal of American Dietetic Association, 97, 1008-10.
Horgen K., Brownell, K. (2002). Comparison of price change interventions in promoting healthy food
choices. Health Psychology, 21, 505-12.
Epstein, LH, Handley, EA, Dearing, KK, Cho, DD, Roemmich, JN, Paluch, RA et. al (2006). Purchases
of food in youth: Influence of price and income. Psychological Science, 17,82-89.
Epstein, LH, Dearing, KK, Paluch, RA, Roemmich, JN & Cho, D (2007). Price and maternal obesity
influence purchasing of low and high energy dense foods. American Journal of Clinical Nutrition, 86,
914-922.
Cross-price elasticity

Price of A is positively related to purchases of B
– Price of coffee increases, purchases of tea increase


Experimental studies have shown increases in
purchases of healthier foods as the price of less
healthy foods is increased
Individual differences may moderate cross-price
elasticity
– Moderated by amount of money available
» Epstein, LH, Handley, EA, Dearing, KK, Cho, DD, Roemmich, JN, Paluch, RA et. al (2006).
Purchases of food in youth: Influence of price and income. Psychological Science, 17,82-89.

Children with less money are more likely to substitute healthy foods for less healthy foods when the price of less healthy
foods increase
– Moderated by maternal weight
» Epstein, LH, Dearing, KK, Paluch, RA, Roemmich, JN & Cho, D (2007). Price and maternal
obesity influence purchasing of low and high energy dense foods. American Journal of Clinical
Nutrition, 86, 914-922.

Lean mothers were more likely to substitute healthy foods for less healthy foods when the price of less healthy foods
increase
Effect of Weight on Effectiveness of
Pricing Interventions
BMI=20
BMI=40
BMI=20
BMI=40
9.0
Purchases of Low Energy Dense Foods
Purchases of High Energy Dense Foods
7
6
5
4
3
8.5
8.0
7.5
7.0
6.5
6.0
2
50
75
100
125
Percentage of HED Reference Price
Figure 1: Number of Purchases of HED foods
when the price of HED foods was changing in
individuals with high and low BMI.
150
50
75
100
125
Percentage of HED Reference Price
Figure 2: Number of Purchases of LED foods
when the price of HED foods was changing in
individuals with high and low BMI.
Epstein, LH, Dearing, KK, Paluch, RA, Roemmich, JN & Cho, D (2007). Price and maternal obesity influence
purchasing of low and high energy dense foods. American Journal of Clinical Nutrition, 86, 914-922.
150
Taxes or Subsides?


Is it better to subsidize the cost of healthy
foods or tax unhealthy foods?
Using an experimental analog food purchasing
task, we examined the effects of increasing the
prices of high calorie for nutrient foods
(HCFN) by 12.5% and 25% (TAX) or reducing
the prices of low calorie for nutrient foods
(LCFN) by 12.5% and 25% (SUBSIDY) on
mother’s purchases of 68 common foods and
beverages.
Methods



Participants were 42 mothers, 20 were lower income (<
$50,000) and 22 were higher income(≥ $50,000). 45%
were obese (BMI ≥ 30)
Each participant was given a study income of
$22.50/family member for each of 5 purchasing trials
In addition to number of items purchased, we also
analyzed changes in calories and macronutrients
purchased, as we thought this would provide a better
index of how price changes influence health
– A family could buy more fruits and vegetables, but still
purchase the same amount of high-energy density, low
nutrient density foods. If they do not substitute healthier for
less healthy foods, buying more fruits and vegetables may
have limited effects on weight and health.
Data Analysis

Mixed effects regression models were used to
assess the effects of price change on calories
and macronutrients purchased as well as the
number of HCFN and LCFN foods purchased
– Log values of the prices and the number of calories
purchased after adjusting for family size were used
– Covariates such as age, BMI, family income and
hunger were added to the models and they were
tested to examine whether they moderated the
influence of price on purchases
Total calories purchased in relationship to taxes and subsidies
11000
Epstein, Dearing , Roba & Finkelstein. In press.
The influence of taxes and subsidies
on energy purchased in an experimental
purchasing study. Psychological
Science.
10000
Total calories purchased
Fig.1. Total calories purchased (A), changes in
macronutrients (B) and proportion of calories as
macronutrents (C) purchased. Mixed regression models
showed subsidies increased calories purchased, due to
increases in fat, carbohydrates and protein purchased.
Taxes reduced calories purchased, with significant
reductions in fat and carbohydrates. Subsides resulted
in no changes in the quality of the diet as calories increased,
while taxes resulted in reductions in fat and increases
in protein.
9000
8000
7000
6000
-25.0
-12.5
0.0
12.5
25.0
Price Changes
Reduction in price from reference price - Subsidies
Increase in price from reference price - Taxes
Macronutrients purchased in relationship to taxes and
subsidies
Fig.1. Total calories purchased (A), changes in
macronutrients (B) and proportion of calories as
macronutrents (C) purchased. Mixed regression models
showed subsidies increased calories purchased, due to
increases in fat, carbohydrates and protein purchased.
Taxes reduced calories purchased, with significant
reductions in fat and carbohydrates. Subsides resulted
in no changes in the quality of the diet as calories increased,
while taxes resulted in reductions in fat and increases
in protein.
Epstein, Dearing , Roba & Finkelstein.
In press. The influence of taxes and subsidies
on energy purchased in an experimental
purchasing study. Psychological
Science.
Change in macronutrients from reference price
1200
1000
800
600
Fat
Carbohydrates
Protein
400
200
0
-200
-400
-25% -12.5%
0%
12.5% 25%
Price Changes
Epstein, Dearing , Roba & Finkelstein. In press.
The influence of taxes and subsidies
on energy purchased in an experimental
purchasing study. Psychological
Science.
20
18
16
Proportion of calories as fat
Fig.1. Total calories purchased (A), changes in
macronutrients (B) and proportion of calories as
macronutrents (C) purchased. Mixed regression models
showed subsidies increased calories purchased, due to
increases in fat, carbohydrates and protein purchased.
Taxes reduced calories purchased, with significant
reductions in fat and carbohydrates. Subsides resulted
in no changes in the quality of the diet as calories increased,
while taxes resulted in reductions in fat and increases
in protein.
22
32
Proportion of calories as carbohydrates
Proportion of macronutrients purchased in
relationship to taxes and subsidies
Proportion of calories as protein
C
58
30
28
26
56
54
52
50
-25.0
-12.5
0.0
12.5
Price changes
25.0
57
58
59
60
61
62
Summary



Behavioral economics is a theoretical approach that can be
used to study how people make choices about health
behaviors
Behavioral economics can be studied at the genetic,
physiological, environmental or behavioral levels
Choice is important to understand factors that influence the
motivation to engage in healthier behaviors
63
Acknowledgements
Brian Saelens, Ph.D.
 Holly Raynor, Ph.D.
 James Roemmich, Ph.D.
 Rocco Paluch, M.S.
 Jenn Temple, Ph.D.
 John Leddy, M.D.
 Tom Robinson, M.D.

64