Barry M. Popkin SPECIAL EVENT 28th Annual Martin J. Forman Memorial Lecture Confronting the New Face of Malnutrition: Regulatory and Fiscal Approaches to Improving Diets OCT 29, 2018 - 12:15 PM TO 01:45 PM EDT

1. The changing face of malnutrition and regulatory
and fiscal efforts to address the rapid food system
changes and growth in obesity while also improving
overall diet quality
Barry Popkin
W. R. Kenan, Jr. Distinguished University Professor
Department of Nutrition
Gillings School of Global Public Health
School of Medicine
Department of Economics
The University of North Carolina at Chapel Hill
THE W RLD IS FAT

2. Outline: The whys and consequences
1.Setting the stage: dynamics of under and overnutrition,
the double burden and the global obesity situation facing
LMICs
2. Major Global Driver: Dietary shifts and food system
changes driving future increases and the rapidly shifting
dynamics
3. Early stages of global large-scale public health
efforts: methodological challenges for evaluations.
4. Future strategies and major gaps

3. 1. State of adult obesity across LMIC’s with most
complete data on women
• Large shift from undernutrition to overweight across all regions,
with some critical exceptions
– Accelerated increase in annualized prevalence of rural overweight status
• BMI distribution shifting rightward, increasing significantly
– Age-period-cohort work in China showed 8-10 kg increase in weight over a decade.
• Waist circumferences increasing along with BMI
• Mysterious challenge: WC/BMI ratio increasing in many countries for
men and women
• Adolescents: Not presented but much more complex picture with
more undernutrition — fear of intergenerational transmission of
stunting/undernutrition for large set of adolescent girls of reproductive
age in both South Asia and subSaharan Africa

4. -1.75
-1.25
-0.75
-0.25
0.25
0.75
1.25
1.75
Annualizedchangeinprevalence
Wasted Stunted Overweight or Obese
Supplemental Figure 2. Annualized changes in malnutrition prevalence among children ages 0–4 from earliest to latest survey years in selected countries*
* Countries presented here had earliest-to-latest-year data spanning 15 or more years, latest-year data after 2010, and a population greater than ≈15 million (with the exception
of Jordan and Kyrgyz Republic, which both had smaller populations but were included for regional representation). The data presented is from years spanning 1988 to 2016,
but exact years vary by country. The span of earliest-to-latest years collected ranges from 15 years to 24 years. All data are from the Demographic and Health Surveys (DHS,
https://dhsprogram.com/) with the exceptions of China (China Health and Nutrition Survey), Indonesia (Indonesian Family Life Survey), Mexico (Mexico National Survey of
Health and Nutrition), Brazil (Brazil National Health Survey), and Vietnam (Vietnam Living Standards Survey).

5. Cambodia
China
Indonesia
Vietnam
Armenia
Kazakhstan
KyrgyzRepublic
Turkey
Bolivia
Brazil
Colombia
DominicanRepublic
Guatemala
Haiti
Honduras
Mexico
Nicaragua
Peru
Egypt,ArabRep.
Jordan
Morocco
Bangladesh
India
Nepal
BurkinaFaso
Cameroon
Chad
Comoros
Congo,Dem.Rep.
Congo,Rep.
Coted'Ivoire
Ethiopia
Gabon
Ghana
Guinea
Kenya
Lesotho
Liberia
Madagascar
Malawi
Mali
Mozambique
Namibia
Niger
Nigeria
Rwanda
Senegal
SierraLeone
Tanzania
Togo
Uganda
Zambia
Zimbabwe
Annualizeddifference
EastAsia
andPacific
Europeand
CentralAsia
Latin
America
&the
Caribbean
MiddleEast
&NorthAfrica
Sub-Saharan
Africa
SouthAsia
Annualized difference in growth rate of women aged 15-49 overweight/obese prevalence for lowest- vs. highest-
wealth groups between first and last survey waves (positive is where poor wealth groups growth rates are increasing
more than high wealth groups)
* Countries presented here had earliest-to-latest-year data spanning 15 or more years, latest-year data after 2010, and a population greater than ≈15 million (with the exception
of Jordan and Kyrgyz Republic, which both had smaller populations but were included for regional representation). The data presented is from years spanning 1988 to 2016,
but exact years vary by country. The span of earliest-to-latest years collected ranges from 15 years to 24 years. All data are from the Demographic and Health Surveys (DHS,
https://dhsprogram.com/) with the exceptions of China (China Health and Nutrition Survey), Indonesia (Indonesian Family Life Survey), Mexico (Mexico National Survey of
Health and Nutrition), Brazil (Brazil National Health Survey), and Vietnam (Vietnam Living Standards Survey).

6. 82.8 82.5
82.0
78.6
76.6
78.7
86.7
86.3
84.6
80.6
83.2 83.3
70
72
74
76
78
80
82
84
86
88
90
USA
Mex*
USA
White*
USA
Black*
England* Mexico* China*
WaistCircumference(cm)
Year 1 Year 2
86.8
88.6
84.4
88.2
82.6
88.2
89.3
84.2
88.2
87.3
USA
Mex*
USA
White
USA
Black
England China*
A. Women B. Men
*Bonferroni Corrected t-test significant at <.05 level.
Figure Predicted mean WC (cm) for BMI=25 kg/m2 in Year 2
compared to Year 1 for women and men aged 20-29 years
in the US (by race/ethnicity), England, Mexico, and China.

7. The Consequences Vary by Race-Ethnicity:
Body Fat Composition in the East Vs the West
(Yajnik & Yudkin 2004)

8. The global double burden of malnutrition based on two alternate measures for all countries
using the most recent data for low- and middle-income countries
(based on UNICEF, WHO, World Bank, and Institute for Health Metrics and Evaluation estimates)
40% overweight prevalence
30% overweight prevalence
20% overweight prevalence No double burden
High-income
countries
Double burden at:
Criteria, any two: child with wasting ≥15%, stunting ≥30%, wasting and stunting both ≥35%,
or overweight ≥15%; woman with overweight ≥40% or thinness ≥20%,
Criteria, any 2: Child with wasting ≥15%, stunting ≥30%, wasting and stunting both
≥35%, overweight ≥15%, and/or severe anemia ≥40%; woman with overweight ≥40%,
thinness ≥20%, and/or severe anemia ≥40%.
a. Current Double burden countries according to weight/height
data: at least 1 wasted/stunted/thin and 1 overweight/obese child,
adolescent, or adult in household
b. Double burden countries (anemic/wasted/stunted and
overweight/obese in household) in most recent survey year,
based on 20%, 30%, and 40% overweight/obesity cutoffs
Not for use or quotation until published Popkin et al Lancet 2019

9. Predicted double burden of overweight & wasting or stunting
Double burden of overweight & wasting or stunting
a. Earliest measure of double burden
regressed on 1990 GDP (PPP)
b. Most recent measure of double burden
regressed on 2010 GDP (PPP)
Sources: The data are from the Demographic and Health Surveys (DHS, https://dhsprogram.com/), with the exceptions of China (China Health and Nutrition
Survey), Indonesia (Indonesian Family Life Survey), Mexico (Mexico National Survey of Health and Nutrition), Brazil (Brazil National Health Survey), and
Vietnam (Vietnam Living Standards Survey)
Note: the regressions control for population size and look at GNP (quadratic or second-degree polynomial form)
1990GDP/capita
10,000
8,000
6,000
4,000
2,000
Prevalence of double burden
2010GDP/capita
10,000
8,000
6,000
4,000
2,000
Prevalence of double burden
Regressions relating GDP per capita to household double burden
Azerbaijan
Egypt
Kazakhstan
Comoros
Guatemala
Lesotho
EgyptMyanmar

10. Major direct drivers: Role of our history
Core biochemical and
physiologic processes
have been preserved
from those who
appeared in Africa
between 100,000 and
50,000 years ago.
Biology Evolved Over
100,000 Years
Modern Technology has taken
advantage of this biology
Sweet preferences Cheap caloric sweeteners, food processing create
habituation to sweetness
Thirst, hunger/satiety
mechanisms not linked
Caloric beverage revolution
Fatty food preference Edible oil revolution — high yield oilseeds,
cheap removal of oils, modern processed
food/restaurant sector
Desire to
eliminate exertion
Technology in all phases of work and movement
reduce energy expenditure,
enhance sedentarianism
Snacking Behavior Modern food marketing; modern accessibility
everywhere of unhealthy nonessential convenient
ready-to-eat snack foods
Mismatch: Biology, which has evolved over the
millennia, clashes with modern technology

11. 0
5
10
15
20
25
30
100
150
200
250
300
350
400
450
1991 1994 1997 2000 2003 2006 2009 2012 2015 2018 2021 2024 2027 2030
Averagehoursperweekbringsedentary
AverageMET-hoursperweek
Year
Active Leisure PA
Travel PA
Domestic PA
Occupational PA
Sedentary Time (hrs/week)
by 2030: 188
MET-hr/week
2009: 213
MET-hr/week
by 2020: 200
MET-hr/week
1991: 399
MET-hr/week
Source: Ng S.W. & Popkin B.M. Obesity Reviews 13 (8):659-80
Chinese adults: Met-hours per week of physical activity & hours/week of time in
sedentary behavior; measured for 1991-2009 and forecasted for 2010-2030

12. From Jean-Claude Moubarac
Evolution of Human Experience with Food
• Old and accumulative process
• Increase penetration of the matter
• From domestic & artisanal to industrial
Butchering,
smoking &
drying
of meats
Pounding,
grinding,
roasting,
wetting,
boiling,
fermenting
of seeds
and acorns
Granaries,
agriculture,
husbandry,
pottery
Large
granaries
Mass
production
of oil, salt
& sugar
Pasteurization,
canning,
roller mills
Cooking
Ultra-processing
Industrial
ingredients,
biochemicals,
genetics
By Jean-Claude Moubarac
Paleolithic
2 mya
300,000 BC
Neolithic
12,000 - 2000 BC
First
States
Post-war/global
1950-2013
Industrial
1780

13. Sources of major global dietary shifts:
All significant in most Low and Middle Income
Countries
Global increases in:
↑ Use of added caloric sweeteners, especially beverages,
but increasingly all packaged foods consumed
↑ Animal source foods
↑ Refined carbohydrates, ultra-(highly) processed foods
↑ Convenience foods for snacking, away-from-home eating,
precooked/uncooked ready-to-heat food
↑ Large increase in edible oil used to fry foods (unique to LMICs)
Global decreases in:
↓ Legumes, vegetables, fruits in most countries
↓ Food preparation time

14. From traditional to modern meals

15. From traditional to modern snacking

16. From traditional to modern marketing of food

17. First major global shift:
Sweetness, added sugars
Always loved sweetness and as fruit,
provided unique source of nutrients.

18. A unique factor: Beverage-thirst
and food-hunger mechanisms are not linked
General Properties
Food Water
Hunger – Feeding
Sensations that promote
attainment of minimal
food energy needs
Thirst – Drinking
Sensations that promote
attainment of minimal
hydration needs
Energy Excess
Stored
Water Excess
Excreted
Energy Deficit: Die in 1-2 months Water Deficit: Die in 3-7 days

19. Mourao, .. (2007). "Effects of food form..." IJO:31(11): 1688-95.
0
500
1000
1500
2000
2500
3000
3500
4000
Kcalsperdayconsumed
Liquid
Solid
Liquid
Solid
Liquid
Solid
Carbohydrate
(Watermelon)
Fat
(Coconut)
Protein
(Dairy)
*
*
*
Comparison of consumption of a beverage and a solid food on
total energy intake shows beverage consumption in any macronutrient
form significantly increases dairy energy intake

20. Mexican SSB distribution by age group
(per-capita kcal/day from Quantile regressions), Ensanut 2012
58
99
175
133
178
108120
197
323
263
296
230
200
298
506
401
482
357
0
100
200
300
400
500
600
Preschool
children
School-aged
children
Adolescent
males
Adolescent
females
Adult males Adults females
Energyintake(kcal/d)
50th percentile
75th percentile
90th percentile
Source: Aburto, Poti, Popkin in press Pub Health Nutr.

21. Remarkably short history for caloric beverages:
Might the absence of compensation relate to this historical evolution?
AD
BCE
10000BCE
200000BCE
Beginning
ofTime
100000 BCE
200000 BCE
Homo Sapiens
Pre-HomoSapiens
200,000BCE-10,000BCE
OriginofHumans
ModernBeverageEra
10,000BCE-present
0
Earliest possible date
Definite date
Water, Breast Milk
2000 BCE
Milk (9000 BCE)
Beer (4000 BCE)
Wine (5400 BCE)Wine, Beer, Juice
(8000 BCE)
(206 AD)
Tea (500 BCE)
Brandy Distilled (1000-1500)
Coffee (1300-1500)
Lemonade (1500-1600)
Liquor (1700-1800)
Carbonation (1760-70)
Pasteurization (1860-64)
Coca Cola (1886)
US Milk Intake 45 gal/capita
(1945)
Juice Concentrates (1945)
US Coffee Intake 46 gal/capita
(1946)
US Soda Intake 52/gal/capita
(2004)

22. a. Annualized change in SSB sales, 2004–2017
* Sugar-sweetened beverages (SSBs) include regular cola carbonates, noncola carbonates (e.g., lemon/lime and orange carbonates, ginger ale, mixers), liquid and powder
concentrates, juice drinks (up to 24% juice), nectars (25–99% juice), ready-to-drink coffees and teas, sports and energy drinks, and Asian specialty drinks.
** Includes low- and middle-income countries for which Euromonitor had data for the majority of SSB categories. Countries with modeled data were excluded.
Data source: Euromonitor International Limited 2018 © All rights reserved
Regressions of global trends in total sugar-sweetened beverage*
(SSB) sales in low- and middle-income countries**
Annualized change prediction (grams/capita/day)
2010GDP(PPP)
-4.0 0.0 2.0 4.0-2.0 6.0
b. 2017 SSB sales
SSB sales prediction (grams/capita/day)
2010GDP(PPP)
-100 3001000 200

23. Sweeteners in Our Food Supply
Key word searches in the ingredient list of each product:
• Low-calorie sweeteners: artificial sweetener, aspartame, saccharin,
sucralose, cyclamate, acesulfame K, stevia, sugar alcohols (i.e. xylitol) and
brand name versions of each sweetener (i.e. Splenda)
• Caloric sweeteners: fruit juice concentrate (not reconstituted), cane
sugar, beet sugar, sucrose, glucose, corn syrup, high fructose corn syrup,
agave-based sweeteners, honey, molasses, maple, sorghum/malt/maltose,
rice syrup, fructose, lactose, inverted sugars
Caloric Sweetener Low-calorie Sweetener

24. * excluding lemon/lime and when reconstituted)
Source: Popkin,Hawkes Lancet Diab: 2016
30 29 32 31 31 34
28 26 28
3 6
5
0 0
0 9 14 12
63 60 55 66 66
63 58 51
45
3 5 7
2 2 2 4
9
15
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2000(N=40,562)
2006(N=76,971)
2013(N=129,527)
2000(N=35,896)
2006(N=67,600)
2013(N=113,015)
2000(N=4,666)
2006(N=9,371)
2013(N=16,512)
All CPG Foods & Beverages Foods only Beverages only
%uniqueformulationscontainingsweetenersbyweight
Any fruit juice
concentrate*
Both nutritive and non-
nutritive sweetener
Nutritive/caloric
sweetener only
Non-nutritive/non-
caloric sweetener only
No added sweeteners
Proportion of CPG products with unique formulations
by weight containing any sweeteners

25. Second major global concern: Snacking
• Snacking is a norm created by the food industry
• The history of snacking — very rare until the mid-1900s
except for festivals, royalty, war
• When did snacking become a norm?
– In the United States really began post-WWII
• Today a different issue:
– Brazil, Mexico, and the United States are three countries where
our studies show >22% of kcal come from snacks, increasingly
highly processed foods and beverages
– China tripling each year from 2002,2004. 2006, 2009, 2011
but still small except for selected groups.
• Increasingly refined carbohydrate and sugary snacks

26. a. Annualized change in junk food sales, 2004–2017
* “Junk” foods include cakes, pastries, chocolate & sugar confectioneries, chilled and shelf-stable desserts, frozen baked goods, frozen desserts, ice cream, sweet biscuits,
snack bars, processed fruit snacks, salty snacks, savory biscuits, popcorn, pretzels, and other savory snacks.
** Includes low- and middle-income countries for which Euromonitor had data for the majority of junk food categories. Countries with modeled data were excluded.
Data source: Euromonitor International Limited 2018 © All rights reserved
Annualized change prediction (grams/capita/day)
2010GDP(PPP)
Regressions of global trends in total junk food* sales
in low- and middle-income countries**
0 0.5 1.0 1.5
b. 2017 junk food sales
Junk food sales prediction (grams/capita/day)
2010GDP(PPP)
-20 80400 20 60

27. Source: Euromonitor International Limited 2018 © All rights reserved
Trends in per capita daily packaged junk food sales by category
in select Asian countries, 2005-2017
0
5
10
15
20
25
30
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
China Malaysia Philippines Thailand India
Gramspercapitaperday
Sweet Biscuits, Snack Bars and Fruit Snacks
Salty Snacks
Confectionery
Cakes & pastries
China Malaysia Philippines Thailand India

28. Trends in total banner sales from quick-service, café, and full-service*
restaurant retailers in select Asian countries, 2006–2017
× = No full-service restaurant data available.
Source: Authors’ analysis of data from www.Planetretail.net. The sales figures are for the food retail chains
PlanetRetail followed per country. PlanetRetail follows the leading national chains, not smaller chains, independents, or
regional chains in a country. The total sales for a given country are thus an underestimate of all modern food retail sales
but the trends are meaningful.
× × × × ×
×
×
× × × ×
×
× × × × × × × ×
× × × × × × ×
× × ×
× ×
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
16.00
18.00
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
China India Malaysia Philippines Thailand
BillionsUSD
Full Service Restaurants
Cafes
Quick Service Restaurants
China Malaysia Philippines ThailandIndia

29. Third major shift: Fatty foods and edible oils —
unsure of weight and health effects
• Fatty foods: smoother, affects taste in many ways
• Shifts largest in Africa, Middle East, and Asia but
also in the Americas
• Oils have faced and will continue to face many challenges
regarding trans fat content and unhealthy saturated fatty acid
components, particularly palm oil whose consumption is
growing very rapidly in LMICs.
• Possibly the biggest early caloric drivers in the developing
world other than SSB’s have been:
– higher-fat junk foods,
– other ultra processed foods with high saturated fats, and
– ready-to-eat, ready-to-heat products.

30. Other Critical Eating Behavior Changes
• Reduced healthy cooking
• Increased away-from-home intake
• Reduced home cooking are the major shifts

31. Major food system changes
Occurred different times, similar now
Four big players drive food
and agricultural systems in
LMICs and the US:
(agricultural economists have documented)
Source: Popkin BM. Nutrition, Agriculture, global food systems in LMIC’s Food Policy (2014) 14;47:91-96; Zhou et al
(2015). The food retail revolution in China and its association with diet and health. Food Policy 55:92-100.
• Trend in disappearing fresh markets being replaced by small stalls, convenience
stores and supermarkets  all selling ultra-processed foods and beverages
• Mexico and China: packaged foods with bar codes based on nationally
representative 24-hour recalls surveys with questions probing this issue
– 58% of kcal Mexico in 2012 and 29% in China in 2011 (growing by 50%/year)
– $72 billion in 2016 ($350/cap) on retail sales in Brazil; $22 billion in 2016 in Mexico
• Latin America/Gulf states: first major growth, now Asia and urban Africa;
high penetration into all African and Middle East communities now
• Major shifts in types of foods and integrated marketing strategies used by
food industry sectors across global regions with Latin America being penetrated
most completely and earlier than Africa and Asia
• Global agribusinesses
• Retailers
• Food manufacturers
• Large restaurant chains

32. Stage 1
1800’s mainly
scientific underpinnings
Stage 3
Post WWII massive investments
modern system
Stage 4
Systematically
transmitted globally
(1955-2008)
Stage 5
Commercial sector shifts
major drivers of system
change (present)
Stage 2
1900-1944
Stage 6
Healthier food
supply
Reduced
noncommunicable
diseases, reduced
climate footprint,
achieve total
sustainability, fewer
animal source foods
consumed
Production linked to
the needs of food
manufacturers and
retailers, ignoring
climate, sustainability,
and health concerns
Green revolution,
irrigation, credit, farm
extension, and
agricultural institutions
mirror those of the
west; modernizing of
food processing
High income countries see
rapid mechanization;
development of new food
processing technologies (e.g.
extraction of edible
oils from oilseeds); and
investment in transportation/
irrigation/electrification/
modernization of agriculture
Farming systems
developed;
underpinnings post
WWII revolution
added modernization
of agricultural
production inputs
and machinery
Farming remains
the major source of
the food supply;
industrial/large-
scale monoculture
initiated
Investments in
infrastructure
and training
Food industry
farm links drive
production and
marketing
decisions,
incentives and
economic
drivers change
Investment training,
institutions, infrastructure,
CGIARC (Consortium
Global International
Agricultural Research)
Extensive funding for
major infrastructure,
systems, input and
enhanced seeds,
and major technology
development
Expansion of
science; develop
reaper; many
other technologies
Fossil energy,
modern genetics,
fertilizer, beginning
agricultural science
and experimental
work, & land
grant/agricultural
universities
Price incentives, taxation,
other regulatory controls
(e.g. marketing healthy
food only) and system
investments
Retailers, agricultural
input & processing,
businesses, and food
manufacturers
dominate farm-level
decision-making
Farm research,
extension systems,
and education mirror
those of the West
Create the modern
food system focused
on staples, animal
source foods, and
cash crops
Expansion
technologies;
science
Stages of modern global agricultural system’s development
Science and
institution building
Scientific and technological change, economic change, urbanization, globalization
Source: © (copyright) Barry M. Popkin, 2015
See Anand,Hawkes et al, J Am College Card (2015) 66; Popkin (2017) Nutr Reviews

33. 3. National Regulations
• Counter-factual option: look at shift in existing trends using
historical trends, modeled and adjusted fully.
– Look at shifts in trend line
• Controls: No true controls for a country intervention so use other
methods to understand changes linked to the law.
• Differences when discussing US cities where groups we advise are
using other cities (e.g. Baltimore for Philly) but we have our concerns
with such options and areas around municipalities for leakages
a. Evaluation Design: Taxes

34. Mexico: Modeling
Used household food purchase
data pre-tax (2012-13) and
post-tax (2014-2015)
Conducted pre-post comparisons
of purchases using observational
data, accounting for:
• Seasonality in prices & purchases
• Concurrent SSB and
junk food taxes
• Other concurrent changes
(e.g., economic climate,
consumer preferences)
volumepurchased
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
Month-Year
2012 20142013
pre-tax trend
post-tax trend
observed
Modeling
post-tax trend
counterfactual
Colchero et al BMJ. 2016;352:h6704; Colchero et al, Health Affairs. 2017;36:564-571

35. Mexico: SSB tax
Findings:
• On average, SSB purchases
were 6% lower (-12ml/cap/d)
while purchases of untaxed
beverages (mainly water)
were 4% higher compared
to counterfactual in 2014
• Larger decline (9%; -19ml/cap/d)
among low SES households
• Decline in SSB consumption from
SSB tax (-12ml) is small relative
to growth in earlier years
Colchero et al BMJ. 2016;352:h6704; Colchero et al, Health Affairs. 2017;36:564-571

36. Mexico: SSB tax
Findings:
• On average, SSB purchases
were 6% lower (-12ml/cap/d)
while purchases of untaxed
beverages (mainly water)
were 4% higher compared
to counterfactual in 2014
• Larger decline (9%; -19ml/cap/d)
among low SES households
• Decline in SSB consumption from
SSB tax (-12ml) is small relative
to growth in earlier years
Colchero et al BMJ. 2016;352:h6704;
Colchero et al, Health Affairs. 2017;36:564-571

37. Mexico: Junk food tax —
bigger reach, potentially larger impact
8% tax on non-basic foods (subject if >275kcal/100g)
– salty snacks
– confectionary
– chocolates
– flans
– sweetened fruit or vegetables
– peanut or hazelnut butter
– milk candies
– ice-cream if energy dense
– grain-based foods
(all except: tortilla, pasta,
plain bread, flour, baby cereals)
Missing foods
• Not collected in Nielsen:
– Most of unpackaged items
– Confectionary and candies
• Not collected consistently in Nielsen:
– Bread from bakery
– Tortillas
– Chocolates
Batis et al PLOS Medicine. 2016;13:e1002057;
Taillie et al Preventive Medicine. 2017;105:S37-S42

38. Mexico: junk food tax
Findings:
• Mean volume of taxed foods
purchased in 2014 declined
by 5.1% (25 g/cap/mo) beyond what
would have been expected based on
pre-tax trends (2012-2013)
– no corresponding change in
purchases of untaxed foods.
• Low SES households showed
greater response to the tax,
purchasing on average 10.2% less
taxed foods than expected.
– Middle- and high-SES households
purchased 5.8% and 2.3% less taxed
foods than expected, respectively.
Batis et al PLOS Medicine. 2016;13:e1002057;
Taillie et al Preventive Medicine. 2017;105:S37-S42

39. Sugary drink taxes around the world
Western
Pacific:
Philippines
Brunei
Cook Islands
Fiji
Palau
French
Polynesia
Kiribati
Nauru
Samoa
Tonga
Vanuatu
Updated July 2, 2018
Copyright 2018 Global Food Research Program UNC
Americas:
USA (8 local)
Mexico
Dominica
Barbados
Peru
Chile
Bermuda
Europe:
United Kingdom
Ireland
Norway
Finland
Estonia
Belgium
France
Hungary
Spain (Catalonia)
Portugal
St Helena
Africa, Eastern
Mediterranean and
Southeast Asia:
Saudi Arabia
Bahrain
United Arab Emirates
India
Sri Lanka
Thailand
Maldives
Mauritius
South Africa
IMPLEMENTED
PASSED

40. SAMOA: 0.40 WST per L ($0.15)
on carbonated beverages. Implemented 1984
FR. POLYNESIA: 40 CFP/L local
($0.39); 60 CFP/L import tax ($0.58)
on sweetened drinks. Implemented 2002
PALAU: $0.28175/L import tax
on carbonated soft drinks. Implemented 2003
FIJI: 0.35 FJD per L local ($0.17);
15% import duty on sweetened drinks.
Updated 2016. 10% import duty on
concentrates. Implemented 2007, updated 2017
NAURU: 30% import duty
on all products with added sugars
(+ removal of bottled water levy).
Implemented 2007
COOK ISLANDS: 15% import duty
(with 2% rise per year) on sweetened drinks.
Implemented 2013
TONGA: 1 Pa’anga per L ($0.44)
on carbonated beverages. Implemented 2013
KIRIBATI: 40% excise tax
on drinks containing added sugar and fruit
concentrates, 100% juices exempt.
Implemented 2014
VANUATU: 50 vatu/L excise
($0.45) on carbonated beverages containing
added sugar or other sweeteners.
Implemented February 2015
INDIA: 12% goods and services tax on all processed
packaged beverages and foods; additional 28% GST
on aerated beverages and lemonades.
Implemented Jul. 2017
UNITED ARAB EMIRATES:
100% excise tax
on energy drinks; 50% tax on all
carbonated drinks except sparkling water.
Implemented Oct. 2017
BAHRAIN: 100% excise tax
on energy drinks, 50% excise tax
on aerated soft drinks. Implemented Dec. 2017
SAUDI ARABIA: 100% excise
on energy drinks, 50% tax on
carbonated drinks.
Implemented Jun. 2017
MAURITIUS: MUR 0.03
per g sugar ($0.0009)
on sodas, syrups, and fruity drinks with added sugar.
Implemented Jan. 2013, updated Oct. 2016
SOUTH AFRICA: ZAR 0.021
per g sugar ($0.002)
on sugary drinks and concentrates (4g per 100mL
exempt). If sugar not labeled, default tax based
on 20 g sugar/100mL; exempts dairy drinks and
fruit, vegetable juices. Implemented Apr. 2018
MALDIVES: MVR 33.64 per L ($2.18)
import tariff on all energy drinks; MVR 4.60/L ($0.30)
tariff on soft drinks (incl. sweetened and unsweetened
carbonated sodas, sports drinks) Implemented Mar. 2017
SRI LANKA: LKR 0.50 per g sugar
($0.003) on sweetened drinks, or Rs 12 per L ($0.08)
— whichever is higher. Implemented Nov. 2017
BRUNEI: BND 4.00 per 10 L ($ 0.37/L) excise
on all drinks with >6 g sugar per 100mL. Implemented Apr. 2017
IMPLEMENTED
Sugary drink taxes:
Africa, Middle East, Asia, and Pacific
Updated July 2, 2018
Copyright 2018 Global Food
Research Program UNC
PHILIPPINES: 6 pesos per L ($0.12)
on drinks using sugar and artificial sweeteners;
P12 per L ($0.23) on drinks using HFCS;
exempts dairy drinks, sweetened instant coffee, drinks
sweetened using coco sugar or stevia,
and 100% juices. Implemented January 2018
THAILAND: 3-tiered ad valorem and excise
on all drinks with >6 g sugar per 100mL. Ad valorem
rate will decrease over time as excise increases. Drinks
with >6g sugar per 100mL will face higher tax rates, up
to 5 baht/L ($0.16) for drinks with >10g sugar per
100mL from 2023 onwards. Implemented Sept. 2017

41. b. Evaluation Design: Chile, with multiple interventions and layers of
timed changes focused on negative front-of-package labels
• October 2014: 5% tax on SSBs relative to other beverages, incomplete,
dropped some prices several % (will not show results—minimal impact, leakages into
some sugary untaxed beverages, low price pass through)
• July 1, 2016: foods and beverages with added sugars, sodium, saturated fats or
calories that exceed set of thresholds (increasingly stringent over time) are subject to:
• Front-of-package warning labels (on packaged products)
• Marketing restrictions on children (≤14y)
• 2018: Advertising ban extended to all TV and cinema from 6am – 10pm;
warning message on regulated foods and beverages other hours of the day

42. Chile’s marketing restrictions
First law June 2016
✓ Applies to all foods and beverages
✓ Uses uniform nutrition criteria across categories
✓ Restricts all characters on packages for foods deemed unhealthy
✓ Adds warning logos to packaged foods high in added sodium/sat fat/sugar
✓ No advertising of unhealthy foods when 20%+ of audience is <14y
✓ Includes comprehensive in-school restrictions
New June 2018 law and implementation guidelines
✓ Adds total ban on advertising from 6am to 10pm
✓ Adds warning message to any ads for foods and beverages
with warning logos outside this time frame

43. Labeling unhealthy foods
• 10% of front surface of the package
• One for each high “critical nutrient”
(sugar, saturated fat, sodium, or calories)

44. Focus groups
Purpose: to explore how mothers perceive the food environment
before and after the law and to investigate their understanding,
attitudes, discourses, buying decisions and eating behaviors
after introduction of the food regulation (including warning labels).
• Nine focus groups of 7-10 mothers
of children aged 2 to 14 (84 in total)
• Different SES backgrounds
• July 2017 Santiago, Chile

45. Changes in social norms
Mother of a 9-year-old child explained:
“My son eats at school. He, by his own,
started to decide what he can eat and
what not, this is because of these black
logos that are in the package.”
“Because of this new law, my daughter has been taught a lot about
these black logos. ‘No mom, you can’t buy me that, my teacher
won’t accept it because it has those labels.’And she requests me
salads, she doesn’t accept snacks that have black labels.”
— Gina, who has a 5-year-old daughter

46. Chilean results
Not yet published, but will have publications on:
• the first year of marketing and character bans
• impacts on kids’ knowledge, attitudes, and
exposure, and
• effects on food purchasing. (astounding
unprecedented impact in shift from regulated to
unregulated beverages)
SSB purchasing changes will be first to come out.

47. Last updated July 5, 2018 | © Copyright 2018 Global Food Research Program UNC
Mandatory regulation of broadcast food advertising to children*
Last updated 10/10/2017
© Copyright 2018 Global Food
Research Program UNC
National or regional
statutory regulation
* Not showing countries
with regulations that
apply to only specific/
limited products

48. Last updated July 5, 2018 | © Copyright 2018 Global Food Research Program UNC
Countries with voluntary industry self-regulatory schemes
Not shown: IFBA’s Global Policy
provides minimum criteria for
marketing directed to children <12y
that is paid for/controlled by IFBA
companies in every country where
they market their products.
Companies include:
Ferrero
General Mills
Grupo Bimbo
Kellogg Company
McDonald's
Mondelēz International
Mars, Incorporated
Nestlé S.A.
PepsiCo, Inc.
Unilever
National or regional
industry self regulation
Last updated 10/10/2017
© Copyright 2017 Global Food
Research Program UNC

49. Future strategies and major gaps
• Fiscal policies focused on unhealthy products with minimal
discussions to date on ways to use tax funds to encourage
healthy food purchases (i.e. subsidizing foods)
• Focused solely on retail sales and have ignored major dietary
components: food service, street vendors/stalls
• Food service: portion control via calorie labeling and then
calorie pricing controls

50. Effectivenesspotential(populationlevel)
Spectrum of approaches for changing behaviorsGov’t
led
Indiv
driven
Fiscal
Measures
(e.g., tax)
Marketing/
advertising
controls/FOP
Industry’s
voluntary
efforts
Food service &
other regulations
Modify
choice
architecture
Cultural/ societal
norms for healthy eating
Individuals, communities, food manufacturers, retailers, food service,
policymakers, regulatory agencies all have roles to play but to date
little evidence they will without regulatory efforts
Labeling &
claims regs;
Menu,
Package
Behaviors
(measureable) as
proxies for norms
(non-measurable)
Social marketing/
nutrition education
5. Our ultimate goal: How to use multiple approaches
to change BOTH supply and demand?
Slide derived from Shu Wen Ng

51. The Struggle Over the Millenia to
Eliminate Arduous Effort Could Not
Foresee Modern Technology