Mukhopadhyay iems leanwashing 02 march2017

Lay Theories of Obesity:
Corporate Leanwashing and the Obesity
Crisis as Market Failure
Anirban Mukhopadhyay
HKUST Institute for Emerging Market Studies (IEMS)
Academic Seminar Series

3
Lay Theories
• “Implicit assumptions that ordinary people hold about
themselves and their world” (Dweck 1996)
– Help give meaning to ones environment (Wyer 2004)
– Have systematic and predictable influences on behavior
• Everyone holds lay theories in numerous domains, e.g.,
– Lay theories about the causes of failure – whether it is attributed to
intelligence or effort – predict helplessness, drops in self-esteem,
and eventually, grades (Robins and Pals 2002)

Today’s focus: Lay theories of obesity
What, do you believe, is the main cause of obesity?
• Poor diet
…or…
insufficient exercise?
McFerran and Mukhopadhyay, Psych. Science 2013
Karnani, McFerran and Mukhopadhyay, CMR 2014, JACR 2016
… and ongoing

This talk in one slide
• The more someone believes that insufficient exercise [poor
diet] causes obesity, the heavier [lighter] they are actually likely
to be.
– Controlling for a lot of things…
– …Because exercise theorists eat more
• Some of this is attributable to Marketing
– In an indirect way that had not been realized till recently
• There is an urgent need for decisive action

Marketers Love Food (and Vice Versa)
• The food industry is among the top advertisers in the U.S.
media market(Story et al. 2002).
– Over $4.2 billion on fast food alone
• One third of the advertising in children’s TV programs (Desrochers
and Holt 2007).
– 72% for candy, cereal, and fast food (Mellow et al. 2006).

• Very effective (Wilkie and Moore 2003; Dhar and Baylis 2011).
• “The message communicated … is that unhealthy eating (e.g., frequent
snacking on calorie-dense and nutrient-poor food) is normal, fun, and
socially rewarding.” (Chandon and Wansink 2011)

10
• Food quality is emerging as a major issue worldwide
– Adulteration
– Factory farming
• Safety issues: Monocultures
• Nutritional issues: Loss of nutrient diversity
• Environmental issues: Land usage
• Ethical issues: CAFO (Concentrated Animal Feeding Operations)
– GMOs
– Labeling
• Do people notice the labels? Do they read the labels? Do they
understand the information? How do they use it?
– Additives
People Love Food (but Vice Versa?)

Portion Sizes = More of the Bad Stuff

Inflation at McDonald’s
6.5
12
16
21
32
0
5
10
15
20
25
30
35
1955 2000s
Ounces
McDonald's Soda Portion Sizes
Child's (110 cal)
Small (150 cal)
Medium (210 cal)
Large (310 cal)
2.0
2.5
4.1
5.4
0
1
2
3
4
5
6
1955 2000s
Ounces
McDonald's Fries Portion Sizes
Small (230 cal)
Medium (380 cal)
Large (500 cal)

Consequently, people are becoming heavier
• 66% US adults, 1/3 of preschoolers overweight or obese (NHANES 2004)
– Doubled over the last 20 years
• More people overweight than starving in the world (UN)
• Huge economic cost, ~$2 trillion/ yr. (McKinsey 2014)

The estimated cost of the obesity problem
McKinsey Global Institute, Discussion Paper November 2014
15

This is a major problem worldwide
Wall Street Journal, April 12, 2013

Obesity Trends* Among U.S. Adults
BRFSS, 1990
(*BMI ≥30, or ~ 30 lbs. overweight for 5’ 4” person)
No Data <10% 10%–14%

BRFSS, 1991
No Data <10% 10%–14% 15%–19%

BRFSS, 1992
No Data <10% 10%–14% 15%–19%

BRFSS, 1993
No Data <10% 10%–14% 15%–19%

BRFSS, 1994
No Data <10% 10%–14% 15%–19%

BRFSS, 1995
No Data <10% 10%–14% 15%–19%

BRFSS, 1996
No Data <10% 10%–14% 15%–19%

BRFSS, 1997
No Data <10% 10%–14% 15%–19% ≥20%

BRFSS, 1998
No Data <10% 10%–14% 15%–19% ≥20%

BRFSS, 1999
No Data <10% 10%–14% 15%–19% ≥20%

BRFSS, 2000
No Data <10% 10%–14% 15%–19% ≥20%

BRFSS, 2001
No Data <10% 10%–14% 15%–19% 20%–24% ≥25%

BRFSS, 2002
No Data <10% 10%–14% 15%–19% 20%–24% ≥25%

BRFSS, 2003
No Data <10% 10%–14% 15%–19% 20%–24% ≥25%

BRFSS, 2004
No Data <10% 10%–14% 15%–19% 20%–24% ≥25%

BRFSS, 2005
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

BRFSS, 2006
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

BRFSS, 2007
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

BRFSS, 2008
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

BRFSS, 2009
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

BRFSS, 2010
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

2000
BRFSS, 1990, 2000, 2010
(*BMI 30, or about 30 lbs. overweight for 5’4” person)
2010
1990
No Data <10% 10%–14% 15%–19% 20%–24% 25%–29% ≥30%

…But people are trying to lose weight
• 59% trying to lose weight (Gallup)
• How?
• Diet market size - $40 billion
• Exercise market size - $18 billion

And there’s no shortage of advice

The tabloids are all over it
• “Exercise holds key to keeping weight off” Medicinenet
• “Exercise key to fighting flab: Diet takes second place in fitness stakes”
Suite101.com
• “Obesity epidemic simply caused by eating too much, claims
academic” Telegraph (UK)
• “Diet, not exercise, plays role in weight loss” MSNBC
• “Why exercise won’t make you thin” Time
• “Fat gene found by scientists” Times (UK)
• “The myth of the fat gene” Live Science
• “Fat gene can be trumped by exercise” Health News

So what’s a poor girl to think?
Diet… exercise… genes… Everyone arrives at
some conclusion for themselves.
 Their own “lay theory of obesity”
Weight gain comes from too much
food…I should watch what I eat!
Weight gain comes from not enough
exercise…I should go to the gym!

Which lay theories would most people hold?
• People believe that individuals can control their own weight
• People can make vast and relatively rapid changes to their diet and
exercise patterns, but do nothing to alter their genetic code.
• Other factors related to obesity (e.g., sleep patterns, smoking,
geographical location, etc.) influence people’s food choice or exercise
patterns, but are not primary causes in themselves.
 The two most commonly-held lay theories of obesity are:
(1) overconsumption of food and (2) lack of exercise.

…And how does this matter?
So either she skips the cake altogether, or she lets
herself eat it with a promise to burn it off with an extra
workout later…
Nope, bad news!
Umm, well I just went
to the gymI’ll hit the gym later…

Problem is, we’re biased
• We underestimate the calories we intake and also overestimate what we
burn while exercising (Lichtman et al 1992).
• Calories?
– 1110, 28g fat
• Hours of walking?
– ~7
• We “reward” our exercise with additional consumption, often ingesting
more calories than the exercise burned (Church et al. 2009).

And what “really” causes obesity?
• Sedentary lifestyle?
• Genetics?
• Eating too much?
– Americans eat 200 more calories a day than they did in 1980 (Chandon & Wansink
2007; NHANES 2004)
– Exercise rates are stagnant over this period and cannot explain obesity rate
change (Westerterp and Speakman 2008)
– Gym memberships have nearly doubled 23M (1993) to 45M (2009)
– 47% “regularly exercise” 1980 to 57% in 2000 (MN Heart study)
– The human genome cannot have morphed that much in only 20 years
• Eliminating one 591 ml soft drink cuts 250 calories
– But…250 calories would take an hour of cycling to burn.
– 250 calories a day = ~30 pounds in a year (Wansink 2006)

The American Medical Association is pretty definitive
• “Clearly, environmental causes for obesity are far more influential than
genes. […]
• Obesity results from overnutrition and the primary therapeutic target is
preventing or reversing overeating […]
• Exercise is associated with weight loss but its duration or intensity has
minor effects on weight loss relative to diet.”
Livingston & Zylke, JAMA editorial 2012

So… our two predictions:
• Poor diet and insufficient exercise are the two predominant lay
theories about the causes of obesity.
• Those who believe that poor diet causes obesity should have a lower
body mass index (BMI) than those who implicate insufficient exercise.

Study 1 – These beliefs exist, and matter
• South Korean nationally representative sample
(N = 254, 54% female, mean age = 32.61, range 15-68)
• Asked to indicate (in Korean) what they believed to be the primary cause
of obesity:
– Eating too much,
– Not exercising enough, or
– Genetic factors.
• Also reported their age, gender, and height and weight (converted to
BMI)

Study 1 - Results
50.4%
41.3%
8.30%
0%
10%
20%
30%
40%
50%
60%
Poor diet Insufficient exercise Genetic factors
Primary cause of obesity

Study 1 - Results
• Diet theorists had lower BMI than exercise theorists
• Of the overweight people (BMI > 25), 30 (of 110) were exercise theorists,
and only 17 (of 128) were diet theorists
21.55
23.10
22.21
21
22
23
24
Poor diet Insufficient exercise Genetic factors
BMI

Study 2 – Replicated with controls….in France
• French sample (N=290)
• Controls (Gutiérrez-Fisac et al 2002; NIH 2011)
– Education level (1-8)
– Hours of sleep per night
– Self-reported stress, anxiety, and depression (each 1=very low, 5=very high)
– Underactive thyroid (hypothyroidism), Cushing's syndrome, or polycystic ovarian
syndrome (1 = yes, 2 = no)
– Weight-affecting medications (corticosteroids, antidepressants, or seizure medicines;
1 = yes, 2 = no)
– Current SES
– Childhood SES
– Home location (1=urban, 2=suburban, 3=smaller city or town, 4=rural)
– Current pregnancy
– Employed outside of the home
– Smoker or not
– Self-reported overall health (1=poor, 5=excellent)
– Interest in nutrition (1=very low, 5=very high)
– Self esteem

Study 2 – Continued
• Rated strength of lay theory by allocating 100 points among
– Diet
– Exercise
– Genetics
• And an additional item “Obesity is caused more by…?”
– 1 = eating too much, 7 = not exercising enough
• Uncorrelated with:
– appearance self esteem
– restrained eating orientation
– body esteem
– hyperopia
– self-efficacy
– impulsivity
– lay theories of self control
– gender

Study 2 - Results
Step 1 Step 2 Step 3
Age .103 .103 .116*
Gender1 -.232*** -.232*** -.206***
Education -.188*** -.188*** -.174***
Medical conditions2 -.031 -.031 -.026
Medications3 .021 .021 .026
Hours of sleep per night .020 .020 .027
Stress4 .032 .032 .055
Socio-Economic Status (Current) -.096 -.096 -.091
Socio-Economic Status (Childhood) .062 .062 .059
Home location .043 .043 .054
Current pregnancy5 .065 .065 .060
Employed outside home5 -.025 -.025 -.021
Smoker5 .145** .145** .148***
Overall health -.199*** -.199** -.221***
Interest in nutrition .011 .011 -.028
Self-esteem .096* .096* .106*
Genetics Lay Theory -.001 -.120
Diet Lay Theory -.184**
R2 .23 .23 .25
DR2 .00 .02**

55
Study 2 – Results
Obese
Overweight

The effect is robust
• Seven other studies controlled for alternative possibilities
– Different ways of measuring lay theories, including open-ended protocols
– Priming lay theories
– Introducing competing cognitions
– Measuring eating behaviors
– Data collected in Canada, France, HK, South Korea, and USA
– And yes, doctors’ do hold the right “lay” theories
• Novel predictor of obesity – a new way of thinking about the problem

Findings regarding the existence and effects of lay
theories of obesity
• People have naïve beliefs about what causes obesity
– Largely implicating diet and exercise
– These often diverge from science
• These beliefs guide behavior
– Exercise-theorists have a higher BMI than diet-theorists
– Robust to measurement
• Mere beliefs explain previously undocumented variance in BMI
• Effects comparable in magnitude to many known correlates of BMI
• Persist as well as explain additional variance even after these other factors
are controlled for

(Big) Food For Thought: Where Do These Beliefs Come
From?
FAREED ZAKARIA (CNN): We have three times the rate of obesity as Europe.
They say it is because of the snacks and fast food and high calorie drinks.
INDRA NOOYI (CEO, PEPSICO): I wish the solution was that simple. ... When I
was a kid, I would come home from school, throw my bag, go out to play. My
daughter comes home from school, throws her bag, goes to play, but sitting in
front of the computer because their definition of play has changed. They
don't go out to play. ... Lifestyles have changed.
CNN, April 17, 2011

Food companies actively promote the exercise theory
Four major ways:
• Public statements
• Lobbying
• Exercise philanthropy
• Sports sponsorships
Karnani, McFerran, and Mukhopadhyay, CMR 2014

Public statements indicting exercise and “lifestyle”
• “Balanced lifestyle” in most interviews and communications
– ‘active balanced lifestyle’: Coca Cola
‘balanced active lifestyle’: McDonald’s
‘balanced and healthy lifestyle’: General Mills
‘balanced diet and lifestyle’: Unilever
‘well-balanced lifestyle’: Mars
‘a balanced lifestyle’: Nestle, PepsiCo
• Directly implicating exercise and “personal choice”
– “If all consumers exercised, did what they had to do, the problem of obesity
wouldn't exist.” – Indra Nooyi, Fortune, April 27, 2010
– “This is an important complicated societal issue that we all have to work together
to provide a solution. That's why we are working with government, business and
civil society to have active lifestyle programs in every country we operate by
2015.” – Muhtar Kent, CEO, Coca-Cola, 2012
– “We cannot escape the role of personal responsibility we each have…. [the growth
in the number of overweight people is] “mirrored by a decline in physical
activity”– John Sutherland, CEO, Cadbury-Schweppes, 2004

Lobbying
• US Food industry spent $175 million on lobbying during 2009-12
• Industry-funded groups that distort research findings
• e.g., The Center for Consumer Freedom (CCF) – a nonprofit “lobbying front for the
restaurant, food, beverage, and alcohol industries”:
“A hefty number of studies has shown that the trend of rising obesity rates can be
attributed not to increased intake of food in general (or any particular food) or to the
influence of restaurants, but rather to less physical activity compounded by a variety of
other factors that are constantly being explored.”
• “Of 76 industry-funded studies (March-October 2015), 70 reported results that were
favorable to the sponsor’s interest” (Marion Nestle, JAMA 2016)
• Influence on guidelines, standards, and initiatives
– Michelle Obama’s “Let’s Move” campaign (NYT op-ed, May 28, 2014)
– US “Inter-Agency Working Group” (FDA, FTC, CDC, & Dept of Agriculture)
recommendation for voluntary standards for children’s food marketing.

Exercise philanthropy
• In-school programs, joint programs with local governments
• Helping to fund and build parks, playgrounds, and gyms
• Examples:
• Kelloggs’ “Get in Step” initiative encouraged people to walk an extra 2,000 steps a day
and then eat a bowl of cereal
• PepsiCo’s “Smart Choices” built playgrounds in cities across the US
• Kraft Foods Foundation invested more than US$ 7 million across Europe, targeting
elementary schools, sports facilities, parks and community centers.
• Coca-Cola funded sports and physical activity programs in China, Brazil, Singapore, and
the Netherlands, among many others
• Unilever sponsored the Flora London Marathon, the Flora Women’s 5km challenge,
and the Danish Handball Summer School.
• “If a 50-pound kid plays soccer for 45 minutes, she burns ~120 calories. But a
typical post-game snack chosen from Pepsi's 'good for you' brand list – a 15.2-
ounce bottle of Dole Strawberry-Kiwi juice and a reduced calorie Quaker granola
bar – adds up to 320 calories.” -- WSJ

Sports sponsorships
• Coke and McDonald’s: Olympics, FIFA World Cup, UEFA soccer,
multiple NBA teams
• Pepsico: NFL, Major League Baseball, Major League Soccer, ICC
Cricket World Cup, Indian Premier League
• And hundreds of others

More recent data: Back to the Center for Consumer
Freedom
• “A hefty number of studies has shown that the trend of rising obesity rates
can be attributed not to increased intake of food in general (or any
particular food) or to the influence of restaurants, but rather to less physical
activity compounded by a variety of other factors that are constantly being
explored.”
• Also insist: “A calorie is a calorie”
– Paper titled: “An Epidemic of Obesity Myths”
64

65
Study 3: New data replicates
Obese
Overweight

66
And extends: Are all calories indeed the same?
Obese
Overweight
Strongly
disagree
Strongly
agree

67
In fact, if BOTH your beliefs are wrong, you’re really
screwed
23.0
24.0
25.0
26.0
27.0
28.0
29.0
30.0
Believe in diet lay
theory
Do NOT believe in
diet lay theory
All calories are the
same
All calories are NOT
the same

We call it “Leanwashing”
• Food marketing tries to influence people’s lay theories of
obesity
• Tries to make them exercise theorists
 Dual effect of “Big Food” on obesity

Policy implications: What should be done?
• “Regulate food like tobacco”? (BBC News May 2014)
• The obesity crisis is a case of market failure
– Evidence of irrational behavior (Thaler and Sunstein 2015)
– Breakdown of the revealed-preference model: “Free markets… will not only
provide us with what we want, as long as we can pay for it; they will also tempt
us into buying things that are bad for us, whatever the costs.” (Akerlof and Shiller
2015)
• Causes of market failure
– Monopoly power or lack of competition (Vickers 1995)
– Asymmetric information (Akerlof 1970)
• Children; Imperfect information (leanwashing)
– Externalities (Scitovsky 1954; Greenwald and Stiglitz 1986)
• Social costs of obesity; social contagion
• Therefore, need for corrective mechanisms (Datta-Chaudhuri 1990; Lerner 1972)
Karnani, McFerran, and Mukhopadhyay, JACR 2016

70
Monopoly
Power
Asymmetric
Information
• Marketing to children
• Problems with
information disclosure
• Leanwashing
Externalities
•Public health
expenditures
•Social contagion
MARKET
FAILURE
CORRECTIVE
MECHANISMS
Corporate Social
Responsibility
• Not incentive
compatible
• Often irrelevant
Industry Self-
Regulation
• Not happening
• Possible
opportunity
Consumer
Activism
• Sporadic
• Ineffective
for many
reasons
Government Intervention
• Unreliable (due to lobbying)
• May be the best option
• But how? Taxes? Bans?
Need for
Analyzing Obesity as Market
Failure

Summary of Government Intervention Remedies to
Address Obesity
Policy Tool Market Failure Addressed Upside Downside
Taxes Externalities (Public health
expenditures)
Taxes at high levels could be
effective (as with tobacco).
Unlikely to get political support, especially at
high levels. Potentially regressive. Difficult to
implement properly. Never tried at levels
most likely to significantly change behavior.
Restrictions on
marketing to adults
Asymmetric Information (Complexity,
motivation to process, ability to
comprehend)
Could have significant impact (as
with tobacco).
Strong political opposition. Untested - not
tried anywhere yet.
Restrictions on
marketing to
children
Asymmetric Information (Children as
vulnerable consumers)
Demonstrable benefits. Somewhat
less political opposition.
Political opposition. Patchwork of
regulations.
Restrictions on
distribution
Asymmetric Information (Children as
vulnerable consumers)
Evidence of effectiveness. Political opposition. Hard to implement,
impossible in some cases.
Product bans Asymmetric information Might work for clearly harmful
ingredients.
Very unlikely to get political support unless
clear evidence of harm.
Nudging Human biases in information
processing and decision making
Less coercive. Possibly less political
opposition. Demonstrably effective
at individual level.
Difficult to scale up. Cross-context
generalizability unclear.
Labeling Rules Asymmetric Information (Complex and
possibly deceptive information)
Less political opposition. Unlikely to have large impact. Potentially
long lag before impact.
Education Asymmetric Information Non-controversial. Very mixed results. Tried before. Costly.
71

So... going forward
Policy implications: Firm side
• Review of recent interest in sugar taxes (with Karnani & McFerran)
• Possible mechanism design problem: How to align food company incentives with the
public interest?
Consumer psychology side
• Attitudes to food “constituents” (with Karnani, McFerran & Das)
• What happened to those who believe equally in diet and exercise?
• Does exercise really have no effect? “Diet : Weight :: Exercise : Health”?
• Exercise self-reports are not accurate – need physiological data
• Scope for large-scale intervention studies.
• The evolution of children’s beliefs and the effect of parents’ beliefs (with Briers & Huh)
• The effects of beliefs on BMI: Dutch LISSpanel data (with Briers & Chan)
• Lay beliefs about sleep, effects on BMI (with Weihrauch & Dewitte)

73
Sugar taxes
• Pre-2016
• Hungary (salt, sugar, and high caffeine tax), France (soft drink tax), Mexico (soda tax),
Denmark (fat tax), Finland (soft drink tax)
• Import / excise taxes on sugary beverages in Norway and several Polynesian countries
• Berkeley: first American city to tax high-calorie sugary drinks (2015)
• 2016
• WHO study: “reasonable and increasing evidence that appropriately designed taxes on
sugar-sweetened beverages would result in proportional reductions in consumption,
especially if aimed at raising the retail price by 20% or more”
• Soda taxes approved in San Francisco, Oakland, Albany, CA, Boulder, CO, and Cook County,
IL, which includes Chicago
• Expected introduction of taxes in Portugal, Spain, Estonia, UK, and Ireland
• Ongoing debate in Australia, NZ, Brazil, Colombia, Philippines, Indonesia, India, and others
• Effectiveness
• Berkeley soda tax: 21% drop in consumption of sugar-sweetened beverages; consumption
increased by 4% in comparison cities (Falbe et al. AJPH 2016)
• Mexico: 6% decrease in purchases of taxed beverages; effect most pronounced for
households of low socioeconomic status (Colchero et al. BMJ 2016)
• Pushback: American Beverage Association; Michael Bloomberg and John Arnold
Karnani, McFerran and Mukhopadhyay (invited article)

74
Study 4: Attitudes to GMOs and organic foods predict
healthiness
2.8
2.9
3
3.1
3.2
3.3
Dislike organic food Like organic food
Dislike GMOs
Like GMOs
• N = 13,910 (Australia, HK, India, South Africa, UK, USA)
• DV: Self-reported health (5-point scale)
Karnani, McFerran, Mukhopadhyay, and Das (in process)

75
Attitudes to GMOs and organic foods predict
healthiness across countries
Australia (N=2365) Hong Kong (N=928) India (N=3786)
South Africa (N=1832) UK (N=2679) USA (N=2320)
Karnani, McFerran, Mukhopadhyay, and Das (in process)

76
Study 5: Attitudes to GMOs and organic foods predict
BMI
• Mall intercepts in North India, N = 221, 65% male, Mean age = 28, 95% at least
college educated

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Mukhopadhyay iems leanwashing 02 march2017