Analysing the Potential Impact of a Proposed Sugar-Sweetened Beverage Tax in the

State of Hawaii

By

Scheherazade R. Husain

B.A, University College London, 2016

Thesis

Submitted in partial fulfilment of the requirements for the Degree of Master of Public

Health in the Brown University School of Public Health

Providence, Rhode Island

May 2018

ii

This thesis by Scheherazade R. Husain is accepted in its present form by the Brown

University School of Public Health as satisfying the thesis requirements for the degree

of Master of Public Health.

Date___________ ______________________________

Omar Galarraga, PhD, Advisor

Date___________ ______________________________

Patricia A. Nolan, MD, MPH, Reader

Date ___________ ______________________________

Patrick M. Vivier, MD, PhD

Director, Master of Public Health Program

Approved by the Graduate Council

Date ___________ ______________________________

Andrew G. Campbell

Dean of the Graduate School

iii

Vita

Ms. Husain was born in Islamabad, Pakistan to parents Maliha Hussein and Tariq

Husain. She attended the International School of Islamabad in Islamabad, Pakistan

and University College London in London, England where she received a B.A

(Honours) in Politics and East European Studies. During her undergraduate studies,

Ms. Husain’s primary research interests were in health economics and the impact of

politic systems on healthcare; this was reflected in her undergraduate dissertation

titled, Post Communism and the Transition into Poor Health: A comparative study of

the impact of the political system on healthcare provision in Kyrgyzstan, Poland, and

Russia. Scheherazade’s work experience extends from Pakistan & Central Asia to

Europe and the United States, giving her a unique insight into a range of diverse

healthcare systems. Her experiences have taken her from hospitals and community

health clinics to rural development organizations and multinational firms. Upon

completion of her MPH, Ms. Husain aims to apply her skills in international public

health policy and health promotion.

iv

Acknowledgements

This thesis would not have been possible without the guidance and support of my

advisors/readers Dr. Omar Galarraga and Dr. Patricia Nolan. Thank you for providing

me with the right balance of strength, space and encouragement to mould this thesis

as my own.

I would also like to thank Dr. Annie Gjelsvik and Dr. Crystal Linkletter for

introducing me to Mathemagics and the wonders of STATA. There are few professors

who can enthusiastically engage a classroom of 50 graduate students between the

hours of 6 and 8pm.

I would like to thank my mother, without whom my journey would not have been

possible. Thank you for all that you do.

I would like to thank my friends and my family for their unwavering support,

accompanying me to many study spots around Providence, always being a phone call

away, and helping me maintain peace.

“All models are wrong, but some are useful”- George E.P Box

“My Lord, increase me in Knowledge” (20:114)

v

Table of Contents

Part 1—Literature Review: “A Sugar Tax or a Sugar-Coated Tax? Analyzing

Modeling Techniques used to Assess the Impact of the Sugar-Sweetened Beverage

Tax on Soda Consumption and Health Outcomes”

Introduction……………………………………………………………………............1

Inclusion Criteria for Studies and Modeling Parameters……………………………...3

Modeling………………………………………………………………………............4

The Impact of SSB Taxation on Consumption………………………………………..4

Associations between SSB Taxation and Health Outcomes……………………..........6

The Economics of SSB Taxation……………………………………………………...9

Conclusion…………………………………………………………………………....11

Figure 1-Inclusion Criteria for Studies used to Determine Modeling Parameters…...13

Table 1: Description of Studies Using Demand Elasticities to Model the Impact on

Consumption of SSBs based on a Proposed 20% SSB Tax, 2008-2018…………….13

References…………………………………………………………………………....16

Part 2—Policy in Practice: Analyzing a Proposed Sugar-Sweetened Beverage

Tax in Hawaii

Abstract……………………………………………………………………………....21

Introduction…………………………………………………………………………..22

Statement of Purpose………………………………………………………………....25

Methods……………………………………………………………………………....26

Results…………..........................................................................................................29

Discussion……………………………………………………………………………30

Conclusion…………………………………………………………………………...32

References…………………………………………………………………………....34

Tables…………………………………………………………………………..........40

vi

List of Tables

Table 1. Characteristics of adults aged 18 and over living in Hawaii between 2011-

2012 by sugared-beverage consumptiona, BRFSS 2011 and 2012 weighted

percentages with 95% Confidence Intervals and p-values 40

Table 2. Adjusted & survey weighted odds of being overweight or obese without a

proposed 20% SSB tax, for adults aged 18 and over in Hawaii from logistic

regression, BRFSS 2011 and 2012 43

Table 3. Adjusted & survey weighted odds of being overweight or obese after a

proposed 20% SSB tax, for adults aged 18 and over in Hawaii from logistic

regression, BRFSS 2011 and 2012 45

1

Part 1: A Sugar Tax or a Sugar-Coated Tax? Using the Sugar-Sweetened

Beverage Tax to Improve Health Outcomes

Introduction

The consumption of sugar-sweetened beverages (SSBs) significantly impacts

health outcomes among adults, adolescents and children, and contributes to the

prevalence of overweight and obesity, and the development of chronic diseases such

as type II diabetes, gout, and heart disease among others. There is increasing evidence

between the link of SSBs and obesity, which has led to SSB taxes becoming the target

of anti-obesity initiatives. SSBs are defined as “any beverage with added sugar or

other caloric sweeteners, such as high-fructose corn syrup”.1 An increased intake of

SSBs is associated with weight gain and obesity, which in turn are associated with

increased health, economic, and social costs.2 Research by Powell and Chaloupka,

and by Smith et al. has indicated that price has a profound impact on diet and weight

outcomes, particularly among youth, lower income populations, and those who are at

an increased risk for obesity.3,4

Evidence from tobacco taxation indicates that price changes affect purchasing

behavior and public health. Literature surrounding the use of taxation as an essential

tool to discourage smoking has contributed to a growing body of empirical evidence

on the increasing interest in modeling the demand for addictive products.5

Experimental studies suggest that sugar can lead to a natural form of addictive

behavior and is noteworthy as a substance that releases opioids and dopamine, thus

leading to its addictive potential.6 The evidence on sugar dependence is particularly

interesting when comparing taxation models for tobacco and SSBs, as both can be

classified as demand models for the taxation of addictive products.5 For the purpose

of economic analyses, a behavior is termed as addictive when an increase in past

consumption of a good results in an increase in future consumption. The activation of

2

the brain’s reward system resulting from the intake of sugar can lead to the

classification of SSBs as addictive goods. Empirical studies indicate that consumption

of addictive goods is more sensitive to changing price than was previously estimated.7

To decrease the demand for SSBs, several states across the United States of America,

as well as some countries around the globe, have adopted taxation policies to increase

price.

One of the pioneering efforts to reduce soda consumption via taxation took

place in Berkeley, California. Initiated in March 2015, the first substantial US excise

tax on soda resulted in a decline in consumption of taxed sweetened beverages,

measured by an observational study a year after the implementation of the tax. The

tax was implemented as 1-cent-per-ounce of sugar in each beverage. According to the

study, sales of taxed SSBs fell by 9.6% as compared to non-tax predictions, and the

sale of untaxed beverages (especially water) rose by 3.5% as compared to non-tax

predictions.8

Globally, a frequently cited example of the success of the SSB tax comes from

Mexico. In January 2014, the government of Mexico implemented an excise tax on all

non-alcoholic beverages with added sugars. Findings indicate a decrease of 7.3% in

per capita sales of SSBs and an increase in 5.2% of per capita sales of water during

the 2014-2015 period, as compared to a pre-tax period between 2007 and 2013.9

The far-reaching scope and low cost of this intervention has facilitated the

discussion on SSB taxes across the United States. Despite gaining traction, the SSB

tax still warrants debate as many remain unconvinced about the potential health

improvements based on the tax; those that oppose the tax believe that it is regressive

in nature.10 It is important to develop objective measures to analyze the impact of

wide-scale policies, and facilitate the debate with meaningful data. Economic

3

analyses of the SSB tax and its impact can provide useful assessments for

governments and organizations during, both, the pre-implementation and post-

implementation phases.

This review paper aims to critically examine, summarize, and discuss the

existing literature on the association between a sugar-sweetened beverage tax and

improved health outcomes. The paper will focus specifically on modeling techniques

and economic analyses that employ price-elasticity of demand and sensitivity

measurements to understand the implementation and implications of an SSB tax. A

literature search was conducted using the databases PubMed, Web of Science, Google

Scholar, Brown University Library Services, EconLit, and National Bureau of

Economic Research (NBER) Working Papers.

Inclusion Criteria for Studies and Modeling Parameters

A comprehensive review of the literature existing around the SSB Tax was

conducted. The search terms included, but are not limited to: SSB Taxation, Soda Tax,

Sugar-Sweetened Beverage Tax, Economic Analysis of SSB Tax/Soda Tax, SSB Tax

and Health Outcomes, SSB Tax and Demand Elasticities. The literature on the topic is

vast as it spans across continents and timeframes. The second step was to divide the

studies based on the following categories: studies pertaining to adolescents and

children, international studies, studies employing rigorous econometric analysis or

modeling techniques, studies based on public opinion and surveys to measure the

effectiveness of the tax, news articles, and grey literature such as previous

dissertations and theses. This search was restricted to studies ranging in time from the

year 1998-2018. These studies have been used as the basis of the literature review;

they provide a foundation for future research as well as highlight key considerations

and limitations for study design. The final step of the review process was to identify

4

published modeling studies in the US and Latin America that have specifically used

the price elasticity of demand for SSBs, with or without the added evaluation of

substitute goods (cross-price elasticities), to estimate the effects of a proposed SSB

tax. This set of articles was further restricted to studies ranging in time from the year

2008-2018 (Figure 1).

It is also important to note that the literature on SSBs and SSB taxes includes

studies that declare financial conflicts of interest (FCOI) due to funding received from

the soda and beverage industry. Some estimates from systematic reviews indicate that

industry funded research has been 5 times more likely to declare that there is no

relationship between SSB consumption and obesity.33 This review did not include any

studies that declared an FCOI in the form of industry funding.

Modeling

The literature reviewed in this paper will examine modeling techniques

pertaining to country-level data, state-level data, survey data and public opinion data,

adolescent health, international health, changes in prevalence of obesity and BMI

outcomes, and econometric techniques. The literature presented in this paper will be

organized thematically.

Existing models and meta-analyses will be used to define parameters for a

modeling study of the impact of the tax in Hawaii. Some of these parameters include:

population demographics and stratification by gender, income, and race, price

elasticities, tax effects on the average SSB price, taxation recommendations for SSBs,

and the prevalence of diseases associated with an increased intake of SSBs.

The Impact of SSB Taxation on Consumption

The precautionary public health measures to prevent overweight and obesity

include the avoidance of an excessive intake of added-sugars and SSBs. SSB taxation

5

has been suggested as one of the public health policy tools to decrease the intake of

added sugar and combat obesity. Although data on the relationship between food

taxes and consumption is limited, an emerging body of evidence suggests that a

relationship does exist. While sugar can also be viewed as an addictive good, like

tobacco and alcohol, it is important to keep in mind that food is a necessity. One of

the key drivers behind food choices and consumption patterns is price; as an item

becomes more expensive consumers may search for alternatives. Research suggests

that to influence consumption patterns there needs to be a price increase of at least 20

percent.11,12

Increasing evidence indicates that taxes on sodas and snacks have a marked

impact on health improvements, particularly among groups with a lower

socioeconomic status where the price elasticity tends to be higher.3,4,11,13 Price

elasticity of demand is a function of how consumption changes in response to the

change in price; it can be defined as the percentage change in consumption for one

percentage change in price.14

Previous studies have assessed the values of the price elasticity of demand for

SSBs after the initiation of a tax in various circumstances. A 2013 meta-analysis on

the impact of SSB taxes on obesity rates indicated that for each 10% increase in price

there would be a 12.9% decrease (-1.29; 95% CI -1.09 to -1.51) in the consumption of

SSBs. This can be expressed as a negative own-price elasticity, where higher prices of

a good result in decreased consumption of that same good.14 A 2015 analysis of the

SSB tax in Mexico estimated own and cross-price elasticities, and found that a 10%

increase in price was associated with an 11.6% (p<0.01) decrease in consumption.

This study, conducted by Colchero et al., found that households with a lower

socioeconomic status have higher price elasticities for the demand of SSBs. A

6

particularly interesting study finding was that an increase in SSB price was associated

with a decrease in the consumption of snacks.15

There are many factors in addition to the price of a beverage that impact its

consumption, which makes it necessary to account for some important externalities

when making assumptions regarding demand. While many models are based only on

own-price elasticities to measure demand, more robust studies account for cross-price

elasticities and the reallocation of consumption choices.

Associations between SSB Taxation and Health Outcomes

There is extensive literature that posits a strong association between soda

consumption and an increased risk of obesity and Type II diabetes. While this

association has been assumed for decades, more recently, large epidemiological

studies have quantified the relationship between SSB consumption and long-term

weight gain, type II diabetes, and cardiovascular disease.16 Despite a strong evidence

base to suggest that sodas and other such beverages are strongly associated with

increased health risks, more research is required to estimate the impact of SSB

taxation on health outcomes. While it is estimated that the impact of obesity on health

and health costs is greater than that of both drinking and smoking21 there is far more

research on the impact of alcohol and tobacco taxes on health outcomes as compared

to similar effects of the soda tax.17 However, there are some studies that have

evaluated the possible health effects of the SSB tax.

While 33 states currently use some form of taxation for sodas, there are only 9

major cities among 9 states that have implemented a targeted SSB taxation policy

aimed at reducing consumption levels.17,18 There are also an estimated 26 countries

aside from the US that have considered or have implemented soda taxes, including:

7

Mexico (as previously mentioned), Canada, Australia, and the United Kingdom,

Colombia, Portugal, France, South Africa, India, Sri Lanka, and the UAE.17, 22, 23

A study by Fletcher et al., provides an empirical examination of the

effectiveness of soda taxes to improve adult weight outcomes. The study uses

repeated cross-sectional BRFSS data from 1990-2006 to assess the changes to BMI in

states based on their tax status over the specified timeframe. In order to estimate the

effect of state soft drink prices on various weight outcomes, this study uses an

ordinary least-squares (OLS) framework to evaluate the impact of changes in state

soft drink taxes on body mass index (BMI), obesity, and overweight. The authors

follow methodology used in the tobacco taxation literature36, 37, which enables them to

capture the effect of state soft drink taxes on weight by comparing individuals in the

same state who face differing sugared-beverage taxes over time. The results indicate

that an increase in one percentage points of the state soda tax rate leads to a 0.003-

point decrease in BMI. Additionally, the study found that soda taxes have a greater

impact on BMI and obesity among low income adults and Hispanics. The authors

note that taxation rates in states was low during the study period, and thus only

modest effects can be seen; they predict that an increase in taxation by 20 percentage

points can lead to a decrease in BMI of 0.06 points, with some demographic groups

benefiting more than others.17

A systematic review on the effectiveness of taxes on non-alcoholic beverages

as a strategy to prevent obesity was conducted in 2013; while an initial 3,700 papers

were identified, only 55 papers were selected for the review based on inclusion

criteria. While 40 selected studies were conducted based on data from the US, there

were no geographical restrictions and studies from Mexico, Brazil, Taiwan,

Singapore, Australia and Europe were also included. The authors noted that existing

8

literature fails to draw consistent and undisputed evidence on the effectiveness of

pricing and tax policies to reduce the burden of obesity. Based on the studies included

in this review, the authors concluded that the elasticities of demand were low and in

some cases not significant. They also commented on the heterogeneity of results, with

a specific emphasis on the dependence of the results on income, weight, sex, and age

group. In conclusion, the review argues that for taxes to have a significant impact on

BMI they must be of a large monetary value, which may lend to the regressive nature

of the tax.24

A modelling study from Mexico assessed the projected impact of the SSB tax

policy on type II diabetes and cardiovascular disease (CVD), and found that while the

long-term impact of the tax remains unknown, it is possible to witness a substantial

decrease in morbidity and mortality attributable to diabetes and CVD over 10 years.

The study employed an established mathematical model—the Cardiovascular Disease

Policy Model-Mexico—and accounted for calorie compensation. Based on a

computer-simulation Markov model to predict the impact of a 10% SSB tax, the

results from this study suggested that the effect of decreasing SSB intake on diabetes

incidence and associated costs would be greater for men as compared to women. The

study was restricted to adults aged 35 and over.25

While the discussion surrounding taxation of SSBs is steadily spreading in the

developed world, it is also emerging as a revenue-generating public health strategy in

middle-income countries. A study conducted in 2014 shed light on the potential

impact of an SSB tax in India; the evidence contributed to the larger discussion on

soda taxes as a viable option for India’s public health problems. A sin tax on SSBs,

which are alternatively referred to as sweetened carbonated beverages (SCBs), was

9

imposed in the country on July 1, 2017.26 While it is early to assess the real outcomes

of this tax, the 2014 study presents a robust assessment of what might ensue.

Basu et al., conducted a novel study that separates itself from previous work,

as their economic-epidemiologic modeling study examines the SSB taxation policy in

a low/middle-country where the population is relatively heterogeneous in its

consumption of SSBs. The study used demand elasticities and a household survey

with a nationally representative sample size of 100,855 Indian households to estimate

the effects of a 20% SSB tax on caloric consumption, glycemic data, the prevalence

of overweight and obesity, and the incidence of type II diabetes. The authors

calculated own and cross-price elasticities based on survey data, which were then

used to calculate per capita kilocalorie and glycemic load changes expected from a

20% SSB excise tax. The study used a discrete-time microsimulation model to

simulate tax-based predicted changes in overweight and obesity, and type II diabetes

prevalence and incidence. Results from this model estimate that a proposed 20% SSB

tax would lead to a 3% reduction in overweight and obesity prevalence and a 1.6%

reduction in type II diabetes incidence in India between 2014 and 2023, as compared

to no-tax conditions.27 The study contributes to the literature on the use of fiscal

strategies to mitigate obesity and type II diabetes, and adds to the research by

predicting the effects in a middle-income setting.

The Economics of SSB Taxation

Economic analyses support policy interventions that aim to change

consumption patterns by changing price. Price has been estimated as a key

determinant of food choice in several studies3,4,11,28, and thus the World Health

Organization (WHO) has suggested that fiscal measures are an appropriate strategy to

overcome the burden of disease.29 However, for a soda tax to be effective it must do

10

more than simply influence consumer behavior. One of the primary reasons that

makes the taxation of SSBs appropriate is the negative externalities associated with

the consumption of SSBs. The clearest manifestation of the negative externalities of

soda consumption is the increased healthcare costs associated with obesity and

obesity-induced problems. In general, negative externalities arise when an individual

does not have to pay the full cost of their decision. These costs may result in higher

insurance premiums for individuals, as well as increased healthcare costs for the

government or others. Another consideration for the associated costs is the loss of

productivity. Those suffering from obesity and related diseases may experience

productivity losses, which in turn could result in decreased wages.30 It is evident that

obesity imposes both medical and nonmedical costs on society.

A tax that may be placed on a good that creates negative externalities is

known as a Pigouvian tax.31 In order for a Pigouvian tax to produce the desired

results, however, the tax must equal the external cost (the cost passed on from the

decision-maker to an individual disengaged from the good or activity being taxed).32

There is strong evidence to suggest that the soda tax can be classified as

Pigouvian. A Pigouvian tax necessitates that the individual engaging in the activity on

which the tax is being applied, perceives the total cost of the activity to be lower than

it is. For instance, an individual who consumes soda may only consider the price of

the soda and disregard the additional health costs and the cost to society. Thus, by

raising the price of the good or the activity, it is possible to change the consumer’s

behavior as they may no longer view the good or activity as worthwhile.34 This

classification has important implications for the analysis and implementation of the

SSB tax, as it strengthens the notion that the tax will result in reduced consumption.

11

The purpose of the SSB tax is to motivate consumers to reduce their

consumption of sugary beverages; to analyze this shift in consumption it is important

to understand the elasticity of SSBs. As mentioned previously, elasticity is a measure

of the extent to which consumers will change their consumption of a good when the

price of that good changes. In general, it is calculated as the percent change in the

quantity of a good demanded divided by the percent change in the price of that good.

It is also important to note that most studies report elasticities as absolute values to

avoid the redundancy of using the term negative own-price elasticity of demand, as

price and demand are assumed to have an inverse relationship.2,32

When assessing the elasticity of a good, it is important to recognize some

additional factors that contribute to the definition of the term. (i) Elasticity is also

related to substitutability, whereby the more substitutes a good has the greater its

elasticity. (ii) The magnitude of the definition of the good plays a significant role on

the substitutability of the good; a more broadly defined term such as SSBs may

present a smaller elasticity of demand as compared to a more narrowly defined term

such as soda.32,35

As price elasticity of demand is an important concept when analyzing the

change in consumption for SSBs, this review presents 5 studies that use elasticities of

demand to estimate the change in consumption based on a proposed 20% SSB tax.

The findings and modeling methodologies of these studies can be found in Table 1.

Conclusion

There is strong evidence to suggest that a tax on sugar-sweetened beverages

will result in reduced consumption of these beverages, which in turn will lower the

prevalence of associated chronic conditions such as obesity and type II diabetes.

Current literature is divided in its use of terms for analyzing the tax; while some

12

studies define taxable beverages as SSBs, others use the term soda. Such differences

lead to discrepancies in overall findings, especially when considering elasticity of

demand.

Additionally, some studies employ cross-price elasticities that account for

substitution while other research does not present results on the substitution effects.

Furthermore, research suggests that there are differences in study findings when

accounting for diet soda versus regular soda. While all studies may not be able to

make this distinction due to unavailability of data, it is an important difference to

note.

Finally, there are few studies that differentiate study findings for adults versus

children. This may be an important consideration for future research as the negative

health outcomes associated with both populations may vary.

The findings from this literature review serve as a fundamental basis for future

research on SSB taxation. They will provide background and context for our research

study that will model the predicted impact of a proposed SSB tax in Hawaii.

13

Figure 1-Inclusion Criteria for Studies used to Determine Modeling Parameters

Table 1: Description of Studies Using Demand Elasticities to Model the Impact on

Consumption of SSBs based on a Proposed SSB Tax, 2008-2018

Studies Identified:

n=60

•Excluded all studies outside the timeframe of 1998-2018

Studies Reviewed:

n=50

•Excluded studies not employing econometric techniques or modeling

Studies used to determine modeling

parameters:

n=5

•Excluded all studies not eligible based on final inclusion criteria1

Reference Study Design Population/

Location

Modeling

Methods

Modeling

Parameters

Results

Wang Y.C,

2010

Logical

pathways-

model

framework

Children and

Adults, New

York State

Quantitative

evaluation of the

impact of a

hypothetical

penny-per-ounce

tax for NY, using

state-specific

epidemiological

data and

published

literature. Two

sensitivity

analyses were

also performed.

Own-price

elasticity of

-0.8, estimated by

Andreyeva et al.,

2009

Penny-per-ounce

tax estimated at

22%

A proposed 22%

SSB tax is expected

to reduce the

proportion of adults

consuming one or

more drink/day by

2-4 percentage

points and 2-6

percentage points

for those adults

consuming 2 or

more drinks/day. A

higher absolute

value for price

elasticity

corresponds with

greater health and

economic benefits.

1Studies that use demand elasticities to model the effects of a proposed SSB tax on SSB

consumption in the USA and Latin America, between 2008-2018.

14

Andreyeva,

Chaloupka, &

Brownell, 2011

Construction of

a model

projecting

beverage

consumption

and tax

revenues

resulting from

an excise SSB

tax.

U.S Census

Population

projections,

2007-2015

Modeling

projected

consumption and

tax revenues

based on regional

data, historic

trends, and

published

estimates for

price elasticity of

demand for

SSBs. The model

was based on a

penny-per-ounce

tax.

Price elasticity

estimated from

Andreyeva et al.,

-0.8. Price

elasticity when

accounting for

substitution

estimated from

Smith et al., 2010

at -1.2.

If there is no

substitution, a

penny-per-ounce

SSB tax could

result in a 24%

reduction in

consumption of

SSBs, reducing per

capita caloric intake

from SSBs by ~45-

50 calories. A

national penny-per-

ounce SSB tax

could generate new

tax revenue of $79

billon over 2010-2015.

Long et al.,

2015

Modeling a

penny-per-

ounce SSB tax,

as an

intervention

exceeding sales

and excise

taxes.

The model

simulated the

2015 U.S.

population

aged>=2

years at

baseline and

followed

them

for 10 years

until death or

age 100

years.

Modeling

framework

developed by

researchers,

based on

Australian

Assessing Cost-

Effectiveness

(ACE-)Obesity

and ACE-

prevention

framework.

Markov cohort

model

SSB consumption

was based on

estimates by

Powell et al., with

an average soft

drink own-price

elasticity of

-1.21 (range, -0.69

to -3.87).

Probabilistic

sensitivity

analyses were

conducted by

simultaneously

sampling all

parameter values

from

predetermined

distributions

using Monte Carlo

simulations.

The implementation

of a national excise

tax was estimated

to cause a 20%

reduction in

baseline

consumption. For

every dollar

invested, the

intervention would

result in $55 in

healthcare cost

savings.

Colchero,

Salgado, Unar-

Munguía,

Hernández-

Ávila &

Rivera-

Dommarco,

2015

linear

approximate

almost ideal

demand system

(LA/AIDS)

Children and

Adults,

Mexico

Used data

available in

Mexico and

provided price

elasticities of

demand for soft

drinks and SSB

stratified by

income and

marginality level

to explore the

potential

heterogeneous

impact of a tax

Price elasticity for

soft drinks was

-1.06 and

-1.16 for SSBs.

Price elasticities

were estimated

using the 2006,

2008 and 2010

Mexican National

Income and

Household

Expenditure

Surveys

(MNHIES).

A price increase in

soft drinks is

associated with a

higher quantity

consumed for

water, milk, snacks

and sugar and a

decrease in the

quantity consumed

for other SSB,

candies and

traditional snacks.

Higher elasticities

were found among

households living in

rural areas (for soft

15

drinks), in more

marginalized areas

and with lower

income.

Implementation of a

tax to soft drinks or

to SSBs could

decrease

consumption

particularly among

the poor.

16

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17

9. Colchero M, Guerrero-López C, Molina M, Rivera J. Beverages Sales in Mexico

before and after Implementation of a Sugar Sweetened Beverage Tax. PLOS ONE

2016;11(9): e0163463.

10. Soda Tax Proposals Bubbling Up in California - Tax Foundation [Internet]. Tax

Foundation. 2018; Available from: https://taxfoundation.org/soda-tax-proposals-

bubbling-california

11. Sarlio-Lähteenkorva S, Winkler J. Could a sugar tax help combat obesity?. BMJ

2015; h4047.

12. Mytton O, Clarke D, Rayner M. Taxing unhealthy food and drinks to improve

health. BMJ 2012;344(may15 2): e2931-e293.

13. Eyles H, Ni Mhurchu C, Nghiem N, Blakely T. Food Pricing Strategies,

Population Diets, and Non-Communicable Disease: A Systematic Review of

Simulation Studies. PLoS Medicine 2012;9(12): e1001353.

14. Cabrera Escobar M, Veerman J, Tollman S, Bertram M, Hofman K. Evidence that

a tax on sugar sweetened beverages reduces the obesity rate: a meta-analysis. BMC

Public Health 2013;13(1).

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Dommarco J. Price elasticity of the demand for sugar sweetened beverages and soft

drinks in Mexico. Economics & Human Biology 2015; 19:129-137.

16. Hu F, Malik V. Sugar-sweetened beverages and risk of obesity and type 2

diabetes: Epidemiologic evidence. Physiology & Behavior 2010;100(1):47-54.

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17. Fletcher J, Frisvold D, Tefft N. Can Soft Drink Taxes Reduce Population Weight

Gain? Contemporary Economic Policy 2010;28(1):23-35. Available from:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2908024/

18. Sugary drink tax. En.wikipedia.org. 2018; Available from:

https://en.wikipedia.org/wiki/Sugary_drink_tax

19. Long M, Gortmaker S, Ward Z et al., Cost Effectiveness of a Sugar-Sweetened

Beverage Excise Tax in the U.S. American Journal of Preventive Medicine

2015;49(1):112-123.

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State. Columbia.edu. 2015; Available from:

http://www.columbia.edu/~ycw2102/SSB%20tax%20brief%20Wang%202010%2006

%2021%20_Final_.pdf

21. Sturm R. The Effects Of Obesity, Smoking, And Drinking On Medical Problems

And Costs. Health Affairs 2002;21(2):245-253.

22. Sugar taxes: The global picture in 2017. beveragedaily.com. 2018 Available from:

https://www.beveragedaily.com/Article/2017/12/20/Sugar-taxes-The-global-picture-

in-2017

23. Han E. Dozens of countries now tax sugary drinks but sweet-toothed Australia

isn't interested. The Sydney Morning Herald. 2018. Available from:

https://www.smh.com.au/healthcare/dozens-of-countries-now-tax-sugary-drinks-but-

sweettoothed-australia-isnt-interested-20180103-h0cv21.html

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24. Maniadakis N, Kapaki V, Damianidi L, Kourlaba G. A&nbsp; systematic review

of the effectiveness of taxes on nonalcoholic beverages and high-in-fat foods as a

means to prevent obesity trends. ClinicoEconomics and Outcomes Research

2013;519.

25. Sánchez-Romero L, Penko J, Coxson P et al. Projected Impact of Mexico’s Sugar-

Sweetened Beverage Tax Policy on Diabetes and Cardiovascular Disease: A

Modeling Study. PLOS Medicine 2016;13(11): e1002158.

26. India applies sin tax on sweetened carbonated beverages .The Education Post.

2017; Available from: https://educationpostonline.in/2017/08/19/india-applies-sin-

tax-on-sweetened-carbonated-beverages/

27. Basu S, Vellakkal S, Agrawal S, Stuckler D, Popkin B, Ebrahim S. Averting

Obesity and Type 2 Diabetes in India through Sugar-Sweetened Beverage Taxation:

An Economic-Epidemiologic Modeling Study. PLoS Medicine 2014;11(1):

e1001582.

28. Veerman J, Sacks G, Antonopoulos N, Martin J. The Impact of a Tax on Sugar-

Sweetened Beverages on Health and Health Care Costs: A Modelling Study. PLOS

ONE 2016;11(4): e0151460.

29. WHO urges global action to curtail consumption and health impacts of sugary

drinks. World Health Organization. 2016; Available from:

http://www.who.int/mediacentre/news/releases/2016/curtail-sugary-drinks/en/

30. Cawley J. The Impact of Obesity on Wages. The Journal of Human Resources

2004;39(2):451.

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31. Pigouvian taxes. The Economist. 2017; Available from:

https://www.economist.com/news/economics-brief/21726709-what-do-when-

interests-individuals-and-society-do-not-coincide-fourth

32. Pratt E. Stop the Sugar: Policy Considerations for an Effective Soda Tax. Tax

Analysts. 2016; Available from: http://www.taxanalysts.org/content/stop-sugar-

policy-considerations-effective-soda-tax

33. Bes-Rastrollo M, Schulze M, Ruiz-Canela M, Martinez-Gonzalez M. Financial

Conflicts of Interest and Reporting Bias Regarding the Association between Sugar-

Sweetened Beverages and Weight Gain: A Systematic Review of Systematic

Reviews. PLoS Medicine 2013;10(12): e1001578.

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Hill/Irwin; 2007.

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Reduce the Onset of Youth Smoking?. Journal of Political Economy [Internet] 2002

[cited 2018 Apr];110(1):144-169. Available from:

https://www.journals.uchicago.edu/doi/abs/10.1086/324386

37. Carpenter C, Cook P. Cigarette Taxes and Youth Smoking: New Evidence from

National, State, & Local Youth Risk Behavior Surveys. NBER [Internet] 2007 [cited

2018 Apr];Working Paper. Available from: http://www.nber.org/papers/w1304

21

Part II-Policy in Practice: Analyzing the Impact of a Proposed Sugar-Sweetened

Beverage Tax in Hawaii

Abstract

Objectives

Sugar-sweetened beverages (SSBs) have received substantial global attention as a key

contributor to detrimental health outcomes, particularly obesity, type II diabetes, and

heart disease. The aim of this paper is to present a method to estimate the impact of a

proposed SSB tax on sugar-sweetened beverage consumption in the State of Hawaii.

Methods

We construct a model to project beverage consumption based on BRFSS data on

regional beverage consumption and population demographics, and recent estimates of

the price elasticities of demand for SSBs. We used a logistic regression model to

obtain adjusted and survey weighted odds ratios to estimate sugared-beverage

consumption before and after a proposed 20% SSB tax, and predict the effects of the

tax on BMI for individuals in Hawaii with varying demographics, in 2011 and 2012.

Findings

Our results indicate that those who identified as Native Hawaiian or Pacific Islander

had 4.14 times the odds of being overweight or obese as compared to those who

identified as White. Additionally, after the initiation of a 20% SSB tax, the odds of

being overweight or obese decreased from 1.19 to 1.03 for those who drank one or

more SSB in 2011.

Conclusion

Our research indicates that while a 20% SSB tax results in reduced consumption and

BMI, the association is not significant. Future research should consider taxation-based

consumption trends within specific segments of the population, as well as the use of

two-part regression models.

22

Introduction

The taxation of sugar-sweetened beverages (SSBs) has gained traction

throughout the United States, as well as throughout the globe. Recommendations by

the World Health Organization (WHO) suggest that taxation of sugary drinks is one

of the most efficient ways to reduce the burden of the obesity epidemic.1 While 34

U.S states—and Washington D.C—have sales taxes on food and beverages, there are

only a select few that have gone a step further and have implemented specific excise

taxes. Studies indicate that sales taxes are largely ineffective in producing desired

reductions in consumption patterns, as they are of nominal value and are applied after

the purchasing decision has been made.11,12 The pioneering effort to implement an

excise tax on sugared beverages in the United States was made by Berkeley,

California in 2014. Since, several cities across the US have proposed or implemented

a tax on sugary beverages. The cities within the US where a tax has been

implemented are: Berkeley, California; Albany, California; Oakland, California; Cook

County, Illinois (repealed); Philadelphia, Pennsylvania; Seattle, Washington

(effective as of January 1st, 2018); and Boulder, Colorado.2,10

Today, Americans consume approximately 250-300 more calories as

compared to the average daily caloric consumption some decades ago, and nearly half

of this increase is attributable to SSBs.3,4 Between 1999 and 2009, the per capita

intake of calories from sugary beverages increased by an alarming 30%.5 Sugary

beverages and sodas are also extensively advertised to adolescents and children. It is

estimated that for each additional can or glass of sugared beverage consumed per day,

a child’s likelihood of becoming obese increases by 60%.6 Additionally, calories from

sugary drinks are usually representative of extra calories that can be avoided without

significant nutritional losses. Moreover, studies have also found that reduced

23

consumption of SSBs leads to a lower overall caloric consumption, improved weight

management, and a reduced risk of obesity and diabetes.7,8,9 Thus, as a source of non-

essential calories, SSBs are a reasonable target for obesity prevention strategies

through taxation efforts.6

Research from Hawaii suggests that an approximated 1 in 3 children entering

kindergarten are obese, in addition to an estimated 22% obese adults and 13.4% obese

youth. Available evidence indicates that Native Hawaiians and other Pacific Islander

(NHOPI) adults display alarming rates of obesity and other related diseases.

Compared to Caucasians, NHOPI are 30% more likely to be obese, 30% more likely

to be diagnosed with cancer, twice as likely to be diagnosed with diabetes, and three

times more likely to be diagnosed with coronary heart disease.37 Moreover, Hawaii’s

annual medical expenditure attributable to obesity alone amounts to a staggering $470

million.18,23 While studies have not estimated obesity-attributable productivity loss in

Hawaii, national estimates indicate that unhealthy weight gain can have debilitating

consequences and lead to chronic conditions.24,25

NHOPI constitute 1.2 million people and are the second fastest-growing

racial/ethnic group in the United States, increasing 40% from 2000 to 2010.36 Given

the rapid growth of the NHOPI population, the disproportionate burden of obesity in

adults, and high prevalence of overweight and obesity in youth, it is imperative that

evidence-based obesity interventions be developed to meet the needs of this group.

The state of Hawaii presents a compelling case study on the taxation of goods

and services, as it is the only state where a general excise tax (GET) is used in lieu of

a sales tax. In most cases, the GET is 4% throughout the state, with some exceptions

where it is charged at 4.5% or 4.7%, and additional exceptions to certain insurance

and wholesale services.14 Hawaii’s general excise tax is charged directly to producers

24

and business rather than to consumers. However, businesses may choose to pass on a

percentage of this tax to consumers, resulting in higher prices of goods or services

that are taxed.12,13

Despite the unique approach adopted by the state of Hawaii, the GET alone is

insufficient to significantly reduce sugared beverage consumption. In an attempt to

alleviate the burden of obesity in the state, an additional specific excise tax on SSBs

was proposed in the Hawaii Senate in the 2012, 2011 and 2013 legislative sessions.

However, despite gaining significant attention from the press and policymakers, none

of these bills underwent the full legislative process required to be passed.

The first bill, SB 2238, which was introduced by Senator Gary Hooser

proposed an additional general excise tax to be imposed on the beverage or syrup

manufacturer. As outlined in the bill, revenues generated through this GET would

have been used to fund K-12 education programs.15

In 2011, then-governor Neil Abercrombie reintroduced the idea by proposing

a penny-per-ounce tax to the state senate. During the same year, two bills regarding

SSB taxation policies were proposed in Hawaii’s state senate; SB1179 proposed an

SSB tax to generate revenue for a children’s health promotion special fund, and

accompanying bill HB1216 proposed a tiered approach whereby a fee of 10 cents

would be added to SSBs equal to or less than 12 fluid ounces and 25 cents would be

added to SSBs greater than 12 ounces. The revenues generated from HB1216 would

be allocated to the Hawaii State Department of Health. Both bills were deferred to the

2012 session.16,17

Between 2012 and 2013, a total of four new bills were proposed as part of

state tax legislation with none passing through. The bills differed from previous ones

in their suggested taxation methods, as well as their proposed use of the revenue

25

generated. All proposals for revenue allocation suggested that the monies should be

utilized for public health efforts.19,20,21,22 An important component of the 2012 session

was the creation of Hawaii’s Childhood Obesity Prevention Task Force. The taskforce

was created with the intention to address the state’s urgent need to prevent childhood

obesity, as there are concerns that this generation may be the first to live shorter lives

than their parents.18

Obesity trends have remained high in Hawaii and are indicative of disparities

with higher rates presented for boys, certain ethnic groups, and those with a lower

socioeconomic status. When evaluating obesity rates in Hawaii, it is important to

remain cognizant of the fact that there is not a single contributor to the epidemic, but

rather a range of complex factors that facilitate the spread of the problem. As obesity

rates are on the rise, there is also a steady decline in physical activity and

consumption of healthy foods.18 Consequently, an SSB tax should be proposed as a

necessary but insufficient intervention, as part of a comprehensive action plan to

prevent and reduce the burden of obesity.

Statement of Purpose

The objective of this paper is to provide an analysis of the impact of a

proposed tax on sugar-sweetened beverages in Hawaii. The research aims to provide

meaningful information for policymakers, health economists, clinicians, and public

health practitioners who intend on implementing an SSB tax or studying its effects.

To our knowledge, this is the first research paper that examines the associations

between SSB consumption and sociodemographic characteristics among Hawaii

adults, and models the effects of a proposed 20% SSB tax in Hawaii.

26

Methods

Data Sources

SSB consumption and demographic data were sourced from the Behavioral

Risk Factor Surveillance Survey (BRFSS) for Hawaii, for the survey years 2011 and

2012. During these two years, data on SSB consumption was collected for Hawaii

using the BRFSS SSB Module. The BRFSS SSB Module is included as an Optional

Module or as State-Added Questions and can be used to monitor SSB consumption at

the state level. The BRFSS is a telephone survey administered in all 50 states, the

District of Columbia, and 3 U.S. territories with funding and specifications from the

Centers for Disease Control and Prevention (CDC). The BRFSS monitors the

prevalence of behavioral health risks that contribute to the leading causes of disease

and death among adults 18 years and older in the United States.26

Population data was also sourced from BRFSS from the 2011-2012 waves,

and was limited to responses pertaining to the state code for Hawaii. Some of the

advantages of the BRFSS dataset are that the data is nationally representative and has

a large sample size. The population data was used to examine the potential effect of

soda taxes on population weight status as indicated through body mass index (BMI).

BRFSS collects self-reported height and weight data, which are then used to calculate

BMI. Control variables were used for demographics such as gender, age, income,

race, education level, physical activity engagement, and disease status. Reported

values are weighted using the BRFSS survey weights to be representative of the

national adult population.

Sugared-Beverage Variables

Respondents were asked two questions pertaining to their sugared-beverage

consumption. The questions were phrased differently during the 2011 and 2012

27

surveys. In 2011, respondents were asked: 1) “About how often do you drink regular

soda or pop that contains sugar? Do not include diet soda or diet pop” and 2) “About

how often do you drink sweetened fruit drinks, such as Kool-Aid, cranberry juice

cocktail, and lemonade? Include fruit drinks you made at home and added sugar to.”

In 2012, these questions were rephrased, and each started with “During the past 30

days, how often did you…?”

For each question, respondents reported the number of times per day, per

week, or per month that they consumed these drinks. Weekly and monthly

consumption were converted to daily consumption. This was done by dividing all

weekly consumption responses by 7, and monthly consumption responses by 30.

To calculate the overall prevalence of sugared-beverage consumption, the

consumption of regular soda or pop and the consumption of sweetened fruit drinks

were summed to provide an overall total for both years. The responses were then

categorized to reflect those who reported not drinking any SSBs, those who drank less

than once a day, and those who drank one or more times a day. We used weighted

percentages with 95% confidence intervals and Pearson’s chi-square tests to assess

the association between SSB consumption and sociodemographic characteristics for

the years 2011 and 2012(Table 1).

Taxes and Prices

To estimate the potential shift in soda consumption and BMI for a proposed

tax scenario, we estimated consumption data based on price elasticities that have been

established in the literature. Demand elasticities were based on a systematic review by

Andreyeva et al.27, which estimates a demand elasticity of -0.8 for soft drinks. This is

reflective of an 8% decrease in consumption for a 10% increase in price. In order to

indicate this shift in consumption, we multiplied the provided values for SSB

28

consumption by 0.84, to reflect a 16% reduction after a 20% SSB tax has been

imposed.

The price elasticity of demand is often used to measure shift in consumption

based on taxes, and can be found in the literature surrounding SSB taxation and

tobacco taxation. It is a function of how consumption changes in response to the

change in price, and can be defined as the percentage change in consumption for one

percentage change in price.28

Variables

Our main variables of interest were SSB consumption, and BMI. The BRFSS

survey uses self-reported height and weight responses to calculate BMI values. While

there is some data to suggest that BMI varies in validity as an indicator for body fat, it

is still a widely-accepted measure to diagnose obesity.29 In 1993, the WHO divided

BMI values into quintiles and established the following categories: underweight,

normal weight, overweight, and obese. Based on these categories, a BMI of 30-35 or

greater is considered as obese.30 The results in Table 1 represent 2 categories for BMI

as those who were reported as underweight or normal weight were grouped together,

and those who reported as overweight or obese were grouped together. This was done

for the purposes of creating a binary variable for logistic regression.

The results were analyzed using Stata version 14.2.31

Logistic Regression

We performed a multiple logistic regression in order to obtain survey

weighted and adjusted odds of being overweight or obese without the effects of a 20%

SSB tax on consumption for individuals in Hawaii with varying demographics (Table

2). We then used the same logistic regression model to obtain results to reflect the

effects of a 20% SSB tax. In order to predict the change in consumption, individual

29

level consumption data was multiplied by 0.84 in order to adjust for a price elasticity

of demand of 0.16 for a 20% tax. This was based on Andreyeva et al.’s findings that

suggest an elasticity of demand of 0.08 for a 10% tax.27 The individual level

consumption data based on a 20% tax were then used to conduct the logistic

regression (Table 3). We adjusted for gender, age, education, race/ethnicity, income,

diabetes status, coronary heart disease status, and engagement in physical activity

during the past month.

Results

We combined data for 2011 and 2012 that had responses for both sugared-

beverage questions. Our sample size for 2011 was 7,606 and 7,582 for 2012 giving us

a combined sample size of 15,188. We assessed the characteristics of adults in Hawaii

by their sugared-beverage consumption status and found all covariates to be

significantly associated (Table 1). The covariates used were: gender, age, education

status, race/ethnicity, income status, BMI category, diabetes status, presence of

coronary heart disease, and engagement in physical activity during the past month.

We stratified the results by year with separate responses for 2011 and 2012, in order

to account for variability over time. As the literature suggests, gender is significantly

associated with SSB consumption. In 2011, among those who drank SSBs one or

more times a day, 56.4% (52.3, 60.4 C.I) were male. In 2012, this number increased

to 57.7% (53.7, 61.7 C.I). Additionally, in 2012, 17.3% (14.2, 20.8 C.I) of those who

drank SSBs at least once a day were between the ages of 18 and 24 while only 6.2%

(4.7, 8.1 C.I) of those who reported not drinking SSBs belonged to this demographic.

Income was also significantly associated with soda consumption; among those who

reported never drinking soda, in 2011, 53.1% (50.3, 55.8 C.I) were high income while

only 22.7% (20.4, 25.3 C.I) were low income.

30

We used a multiple logistic regression model to obtain adjusted and survey

weighted odds ratios to estimate sugared-beverage consumption before and after a

proposed 20% SSB tax, and predict the effects of the tax on BMI for individuals in

Hawaii with varying demographics, in 2011 and 2012 (Table 2). Our results indicate

that the relationship between SSB consumption and BMI is significantly associated

with race. Prior to the addition of a tax, those who identified as Native Hawaiian or

Pacific Islander had 4.14 (2.25, 7.62 C.I) times the odds of being overweight or obese

as compared to those who identified as White. While income was a significant factor

when assessing soda consumption, it only appears to be statistically significant for

those who are within the high-income category, when examining the relationship

between soda consumption and BMI. Age was also a significant factor, whereby those

between the ages of 35 and 44 had 3.48 (2.28, 5.30 C.I) times the odds of being

overweight or obese as compared to those aged 18-24, even after a 20% SSB tax was

considered for 2011.

To estimate the effect of a soda tax on SSB consumption we modelled a 20%

SSB tax scenario and compared it to the standard of no tax. We assumed a price

elasticity of demand of 0.8 (absolute value), based on a systematic review by

Andreyeva et al., 201127. The results indicate that after the initiation of a 20% SSB

tax, the odds of being overweight or obese decreased from 1.19 to 1.03 for those who

drank one or more SSB in 2011.

Discussion

The state of Hawaii has considered several policy proposals for SSB taxation

but so far none have been implemented. As Hawaii’s state taxation system already

employs an excise tax rather than a sales tax, increasing the current rate of 4% to 20%

for an SSB tax would be beneficial. Additionally, a 20% tax is suggested as it would

31

reflect a penny per ounce tax for most sodas.32 As excise taxes are structured to reflect

a fixed cost per ounce of sugar, they may present a more incentivized mechanism for

consumers to purchase a reduced amount. Excise taxes are imposed on the

distributor/producer and it is their decision to pass an amount of the tax to the

customer. If the producer chooses to pass the tax on to the consumer, the change is

reflected in the price of the good, and thus influences the customer’s decision prior to

making the purchase.

Limitations

The BRFSS survey provides cross-sectional data, which may lead to certain

limitations when assessing the proposed impact of soda consumption on weight

outcomes. Specifically, we cannot make causal inferences due to the nature of the

data. Additionally, the BRFSS data on SSB consumption is self-reported and thus

may be subject to recall and social desirability bias. Furthermore, the SSB modules

used in Hawaii during the 2011 and 2012 waves use two questions to assess the

consumption of sugared-beverages, and neither pertains to consumption of sports or

energy drinks. These questions ask respondents to describe their frequency of SSB

consumption, and as such do not allow us to determine the specific amount of SSBs

consumed. Data on BMI is also self-reported and thus may be subject to similar

limitations.

Interventions to Reduce SSB Consumption

As price has been estimated as one of the greatest drivers of demand, taxation

is suggested as one of the most efficient methods to reduce consumption. It is

important to keep in mind that there are several factors that contribute to obesity, and

while reducing SSB consumption is necessary it is not sufficient. Research from

Fletcher et al., indicates that, while small by order of magnitude, state soft drink taxes

32

have a statistically significant impact on weight. They predict that an increase in

taxation by 20 percentage points can lead to a decrease in BMI of 0.06 points, with

some demographic groups benefiting more than others.34

To contextualize this reduction, it is important to note that exercise-based

interventions to reduce BMI have not produced significant or better results. A meta-

analysis of randomized control trials for the effect of school-based physical activity

interventions on body mass index suggests that while physical activity is an important

part of school programs, the interventions did not produce statistically significant

results.35

Conclusion

The results of this study have several policy implications for the state of

Hawaii. There is substantial evidence to suggest a need for obesity-reduction

interventions, and it is likely that a single intervention will not suffice. As several bills

to implement an SSB tax in Hawaii have already been formulated there is certainly

impetus for implementation. Our findings indicate that an additional excise tax

specifically applied to sugared-beverages will aid in improving growing obesity and

general health concerns in Hawaii. Future research should study the impact of SSB

taxation on specific segments of the population, as our results indicate that certain

demographic factors such as race and gender are significantly associated with the

relationship between soda consumption and BMI.

The direction and magnitude of the effects of an SSB tax may vary based on

several factors such as the size of the tax, the public knowledge of the tax, and the

nature of the tax (excise versus sales). Lastly, a tax implemented for revenue

generation may not produce the same results as a tax implemented for public health

benefits. While it is possible to generate substantial revenue from the SSB tax,

33

policymakers should prioritize public health and ensure mechanisms for SSB tax

revenue to be invested into improved health efforts.

As there is growing evidence to suggest that a sugar-sweetened beverage tax

may produce desirable results for public health, further research should be conducted

to understand state-level impacts. Additionally, surveys designed specifically to

measure SSB consumption, health outcomes and responses to price would contribute

necessary data to the field.

34

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40

Table 1. Characteristics of adults aged 18 and over living in Hawaii between 2011-2012 by sugared-beverage consumptiona, BRFSS

2011 and 2012 weighted percentages with 95% Confidence Intervals and p-values

2011 p-valueb

2012 p-valueb

None

34.8 (33.3, 36.4) % (95%CI)

Drink less than one per day

44.0 (42.3, 45.8)

% 95(%CI)

Drink one or more per day

21.1 (19.7, 22.7)

% 95(%CI)

N/A

None

35.1 (33.5, 36.8)

% 95(%CI)

Drink less than one per day

45.4 (43.6, 47.1)

% 95(%CI)

Drink one or more per day

19.5 (18.2, 21.0)

% 95(%CI)

N/A

Gender Male Female

43.9 (41.3, 46.5) 56.1 (53.5, 58.7)

51.8 (49.1, 54.4) 48.3 (45.6, 51.0)

56.4 (52.3, 60.4) 43.6 (39.6, 47.7)

<.001

46.8 (44, 49.5) 53.3 (50.5, 56.0)

48.5 (45.9, 51.1) 51.5 (48.9, 54.1)

57.7 (53.7, 61.7) 42.3 (38.3, 46.3)

<.001

Age 18-24 25-34 35-44 45-64 >=65

6.14 (4.6, 8.2) 13.4 (11.3, 15.8) 13.4 (11.6, 15.4) 39.0 (36.5, 41.5) 28.1 (26.1, 30.3)

14.3 (12.0, 17.1) 19.2 (17.0, 21.6) 19.3 (17.3, 21.6) 31.9 (29.7, 34.3) 15.2 (13.8, 16.7)

16.2 (12.7, 20.3) 26.7 (23.0, 30.8) 17.6 (14.7, 21.0) 26.2 (23.2, 30.0) 13.3 (11.2, 15.6)

<.001

6.2 (4.7, 8.1) 10.1 (8.6, 11.9) 13.3 (11.4, 15.5) 39.0 (36.6, 41.7) 31.3 (28.9, 33.8)

14.5 (12.5, 16.7) 18.8 (16.8, 21.0) 18.8 (16.8, 21.0) 33.5 (31.1, 36.0) 14.5 (13.0, 16.1)

17.3 (14.2, 20.8) 26.5 (22.9, 30.4) 16.5 (13.5, 20.0) 28.3 (24.9, 31.9) 11.5 (9.5, 14.0)

<.001

Education

<High school graduate High school graduate

10.9 (8.9, 13.2) 26.7 (24.4, 29.1)

8.7 (7.0, 10.8) 28.9 (26.4, 31.5)

11.7 (8.8, 15.4) 39.8 (35.8, 44.0)

<.001

8.6 (6.8, 11.0)

9.6 (7.8, 11.9)

12.9 (9.7, 16.9)

<.001

41

>High school graduate College graduate

31.9 (29.5, 34.5) 30.6 (28.5, 32.8)

33.7 (31.1, 36.4) 28.7 (26.6, 30.8)

32.2 (28.6, 36.1) 16.2 (14.0, 18.8)

27.8 (25.3, 30.4) 34.5 (31.9, 37.3) 29.1 (27.0, 31.3)

26.8 (24.6, 29.2) 33.5 (30.1, 36.1) 30.0 (27.8, 32.2)

41.4 (37.4, 45.6) 30.2 (26.7, 34.0) 15.5 (13.4, 17.8)

Race White Asian Native Hawaiian or Pacific Islander Multiracial Hispanic Other

33.6 (31.2, 36.0) 41.1 (38.5, 43.8) 1.9 (1.3, 2.9) 14.9 (13.2, 16.7) 6.9 (5.5, 8.6) 1.6 (1.1, 2.5)

25.7 (23.4, 28.1) 41.8 (39.1, 44.5) 1.9 (1.4, 2.5) 18.2 (16.4, 20.0) 10.6 (8.8, 12.8) 1.9 (1.3, 2.8)

21.3 (18.2, 24.8) 35.7 (31.8, 39.9) 4.9 (3.4, 7.0) 23.5 (20.4, 27.0) 12.3 (9.5, 15.8) 2.2 (1.1, 4.3)

<.001

27.8 (25.7, 30.1) 44.5 (41.7, 47.4) 2.6 (1.8, 3.6) 16.8 (14.9, 19.0) 6.0 (4.9, 7.2) 2.4 (1.5, 3.7)

25.5 (23.4, 27.7) 41.2 (38.5, 43.9) 2.8 (2.2, 3.5) 21.1 (19.1, 23.2) 7.3 (6.1, 8.9) 2.1 (1.5, 3.0)

22.8 (19.6, 26.4) 30.5 (26.9, 34.3) 6.7 (4.7, 9.6) 26.9 (23.5, 30.6) 11.3 (8.6, 14.7) 1.8 (1.1, 2.9)

<.001

Income Low Income Middle Income High Income

22.7 (20.4, 25.3) 24.2 (22.0, 26.6) 53.1 (50.3, 55.8)

21.3 (19.1, 23.7) 26.0 (23.7, 28.4) 52.7 (49.9, 55.5)

28.0 (24.2, 32.1) 29.7 (25.9, 33.8) 42.3 (38.1, 46.6)

<.001

20.9 (18.7, 23.3) 28.2 (25.6, 30.9) 50.9 (48.0, 53.8)

22.8 (20.5, 25.4) 25.3 (23.0, 27.7) 51.9 (49.1, 54.6)

31.4 (27.5, 35.6) 29.6 (25.8, 33.8) 39.0 (35.0, 43.1)

<.001

BMI Underweight or normal weight

46.4 (43.7, 49.0) 53.7 (51.0, 56.3)

44.8 (42.0, 47.5) 55.3 (52.5, 58.0)

40.2 (36.2, 44.4) 59.8 (55.6, 63.8)

p=0.05

44.6 (41.9, 47.5) 55.3 (52.6, 58.1)

43.8 (41.2, 46.5) 56.2 (53.6, 58.8)

43.4 (39.3, 47.6) 56.6 (52.4, 60.7)

p=0.86

42

Overweight or obese

Diabetes Yes No Pre-diabetes

13.5 (11.9, 15.2) 81.4 (79.4, 83.3) 5.2 (4.1, 6.4)

6.2 (5.2, 7.3) 90.4 (88.9, 91.7) 3.5 (2.7, 4.6)

5.2 (4.0, 6.8) 92.1 (90.1, 93.8) 2.7 (1.7, 4.2)

<.001

11.9 (10.2, 13.9) 81.5 (79.2, 83.6) 6.6 (5.3, 8.1)

6.3 (4.9, 7.9) 89.3 (87.4, 90.9) 4.5 (3.6, 5.6)

3.8 (2.3, 6.2) 93.4 (90.9, 95.3) 2.8 (1.8, 4.2)

<.001

Coronary heart disease Yes No

4.4 (3.5,5.6) 95.6 (94.4, 96.5)

2.4 (1.8, 3.2) 97.6 (96.8, 98.2)

1.7 (1.1, 2.5) 98.3 (97.5, 98.9)

<.001

3.5 (2.7, 4.6) 96.5 (95.4, 97.3)

2.2 (1.6, 3.0) 97.8 (97.0, 98.5)

2.82 (2.3, 3.4) 97.0 (95.4, 98.1)

p=.09

Physical activity during the past month Yes No

78.3 (75.8, 80.6) 21.7 (19.4, 24.2)

81.0 (78.6, 83.1) 19.0 (16.9, 21.4)

74.7 (71.1, 78.0) 25.3 (22.0, 29.)

<0.01

81.0 (78.6, 83.3) 19.0 (16.7, 21.4)

83.3 (81.1, 85.3) 16.7 (14.7, 19.0)

76.9 (73.5, 80.1) 23.1 (19.9, 26.5)

<0.01

Abbreviations: CI, confidence interval; N/A, not applicable; BRFSS, Behavioral Risk Factor Surveillance System a sugared-beverages includes regular variety of soda, and sweetened fruit drinks (lemonade, Kool Aid, etc.) b Determined by Pearson’s Chi-square test

43

Table 2. Adjusted & survey weighted odds of being overweight or obese without a proposed 20% SSB tax, for adults aged 18 and over in

Hawaii from logistic regression, BRFSS 2011 and 2012

2011 2012

Odds Ratio 95% Confidence

Interval

P Value

Odds Ratio 95% Confidence Interval

P Value

Gender Male Female

1.00 0.49

0.41, 0.57

<.001

1.00 0.42

0.36, 0.50

<.001 Age 18-24 25-34 35-44 45-64 >=65

1.00 2.56 3.48 3.10 2.36

1.67, 3.89 2.28, 5.31 2.08, 4.60 1.57, 3.55

<.001

1.00 2.10 2.98 2.76 1.63

1.46, 3.02 2.07, 4.30 1.97, 3.88 1.14, 2.33

{<.001

<0.1 Education <High school graduate High school graduate >High school graduate College graduate

1.00 1.09 0.90 0.70

0.74, 1.59 0.61, 1.30 0.46, 0.99

0.67 0.55 0.05

1.00 1.11 1.03 0.82

0.72, 1.70 0.66, 1.59 0.53, 1.28

0.64 0.90 0.38

Race White Asian Native Hawaiian or Pacific Islander Multiracial Hispanic Other

1.00 0.91 4.14 1.95 1.67 3.23

0.75, 1.10 2.25, 7.62 1.55, 2.46 1.17, 2.40 1.74, 5.99

0.36

{<.01

1.00 0.87 6.66 1.86 1.27 1.46

0.72, 1.06 3.97, 11.17 0.82, 2.61 1.49, 2.33 0.90, 1.78

0.17

{<.001

0.17 0.20

44

Income Low Income Middle Income High Income

1.00 1.02 1.34

0.80, 1.30 1.06, 1.69

0.889 <.05

1.00 1.02 1.15

0.81, 1.30 0.91, 1.44

0.85 0.24

Diabetes Yes No Pre-diabetes

1.00 0.35 0.74

0.26, 0.46 0.47, 1.17

<.001 0.20

1.00 0.29 0.68

0.20, 0.42 0.41, 1.12

<.001 0.13

Coronary heart disease Yes No

1.00 0.57

0.35, 0.93

<.05

1.00 0.81

0.49, 1.33

0.40

Physical activity during the past month Yes No

1.00 1.04

0.84, 1.29

0.69

1.00 1.16

0.92, 1.45

0.21

SSB consumption before a 20% tax Never drink <1 time/day >=1 time/day

1.00 1.15 1.19

0.96, 1.37 0.94, 1.51

0.13 0.15

1.04 1.03

0.88, 1.24 0.82, 1.30

0.64 0.80

Abbreviations: SSB, sugar sweetened beverage; BRFSS, Behavioral Risk Factor Surveillance System P-values obtained from Pearson’s chi-square test

45

Table 3. Adjusted & survey weighted odds of being overweight or obese after a proposed 20% SSB tax, for adults aged 18 and over in

Hawaii from logistic regression, BRFSS 2011 and 2012

2011 2012

Odds Ratio 95% Confidence

Interval

P Value

Odds Ratio 95% Confidence Interval

P Value

Gender Male Female

1.00 0.48

0.41, 0.57

<.001

1.00 0.42

0.36, 0.50

<.001 Age 18-24 25-34 35-44 45-64 >=65

1.00 2.57 3.48 3.08 2.33

1.70, 3.92 2.28, 5.30 2.07, 4.60 1.55, 3.52

<.001

1.00 2.10 2.98 2.76 1.63

1.46, 3.02 2.07, 4.30 1.97, 3.88 1.14, 2.33

{<.001

<0.1 Education <High school graduate High school graduate >High school graduate College graduate

1.00 1.08 0.90 0.70

0.74, 1.58 0.60, 1.28 0.45, 0.96

0.69 0.49 <.05

1.00 1.11 1.03 0.82

0.72, 1.70 0.66, 1.59 0.53, 1.28

0.65 0.91 0.38

Race White Asian Native Hawaiian or Pacific Islander Multiracial Hispanic Other

1.00 0.91 4.24 1.97 1.69 3.24

0.75, 1.10 2.30, 7.81 1.57, 2.48 1.18, 2.43 1.75, 6.00

0.35

{<.01

1.00 0.87 6.66 1.86 1.27 1.46

0.72, 1.06 3.97, 11.17 0.82, 2.61 1.49, 2.33 0.90, 1.78

0.17

{<.001

0.17 0.20

46

Income Low Income Middle Income High Income

1.00 1.01 1.33

0.79, 1.30 1.05, 1.68

0.917 <.05

1.00 1.02 1.15

0.80, 1.30 0.91, 1.44

0.86 0.25

Diabetes Yes No Pre-diabetes

1.00 0.35 0.74

0.26, 0.46 0.47, 1.17

<.001 0.20

1.00 0.29 0.68

0.20, 0.42 0.41, 1.12

<.001 0.13

Coronary heart disease Yes No

1.00 0.57

0.35, 0.93

<.05

1.00 0.81

0.49, 1.33

0.40

Physical activity during the past month Yes No

1.00 1.05

0.85, 1.30

0.65

1.00 1.16

0.92, 1.45

0.21

SSB consumption after a 20% tax Never drink <1 time/day >=1 time/day

1.00 1.18 1.03

0.99, 1.41 0.76, 1.40

0.05 0.85

1.04 1.02

0.88, 1.24 0.74, 1.39

0.62 0.92

Abbreviations: SSB, sugar sweetened beverage; BRFSS, Behavioral Risk Factor Surveillance System P-values obtained from Pearson’s chi-square test