Health Policy 80 (2007) 378–391
Limiting youth access to tobacco: Comparing the long-term
health impacts of increasing cigarette excise taxes and
raising the legal smoking age to 21 in the United States
Sajjad Ahmad a,∗ , John Billimek b,1
a
Department of Civil, Architectural and Environmental Engineering, University of Miami,
1251 Memorial Drive, Coral Gables, FL 33146-0630, United States
b Department of Psychology and Social Behavior, University of California, Irvine,
3340 Social Ecology II, Irvine, CA 92697, United States
Abstract
Although many states in the US have raised cigarette excise taxes in recent years, the size of these increases have been fairly
modest (resulting in a 15% increase in the per pack purchase price), and their impact on adult smoking prevalence is likely
insufficient to meet Healthy People 2010 objectives. This paper presents the results of a 75-year dynamic simulation model
comparing the long-term health benefits to society of various levels of tax increase to a viable alternative: limiting youth access
to cigarettes by raising the legal purchase age to 21. If youth smoking initiation is delayed as assumed in the model, increasing
the smoking age would have a minimal immediate effect on adult smoking prevalence and population health, but would affect a
large drop in youth smoking prevalence from 22% to under 9% for the 15–17-year-old age group in 7 years (by 2010)—better
than the result of raising taxes to increase the purchase price of cigarettes by 100%. Reducing youth initiation by enforcing a
higher smoking age would reduce adult smoking prevalence in the long-term (75 years in the future) to 13.6% (comparable to
a 40% tax-induced price increase), and would produce a cumulative gain of 109 million QALYs (comparable to a 20% price
increase). If the political climate continues to favor only moderate cigarette excise tax increases, raising the smoking age should
be considered to reduce the health burden of smoking on society. The health benefits of large tax increases, however, would be
greater and would accrue faster than raising the minimum legal purchase age for cigarettes.
© 2006 Elsevier Ireland Ltd. All rights reserved.
Keywords: Legal smoking age; Tobacco taxes; Youth smoking; System dynamics; Simulation; QALYs; Smoking prevalence; Policy
∗ Corresponding author. Present address: Department of Civil and
Environmental Engineering, University of Nevada, 4505 Maryland
Parkway, Las Vegas, NV 89154-4015, United States.
Tel.: +1 702 895 5456; fax: +1 702 895 3936.
E-mail addresses: [email protected] (S. Ahmad),
[email protected] (J. Billimek).
1 Tel.: +1 949 295 7126; fax: +1 949 824 3002.
1. Introduction
Although the United States has seen considerable
declines in tobacco use in recent years, adult smoking
prevalence at the end of this decade is likely to remain
significantly above the target established with Healthy
0168-8510/$ – see front matter © 2006 Elsevier Ireland Ltd. All rights reserved.
doi:10.1016/j.healthpol.2006.04.001
S. Ahmad, J. Billimek / Health Policy 80 (2007) 378–391
People 2010 [1,2]. To meet this objective target, adult
prevalence (which has fallen from 25% in 1995 to
23% in 2001 [3] must drop to 12% [4]. Considering
the effects of tobacco use on mortality, productivity,
birth outcomes and quality of life, delayed attainment
of smoking rate targets carries significant public health
consequences.
Among the best-supported interventions to reduce
smoking in the population are increased cigarette
excise taxes [5–9]. Popular because they are believed
to simultaneously discourage smoking initiation and
encourage cessation while increasing state revenues
[5,9], new excise tax increases have been passed in 35
states and the District of Columbia since the beginning
of 2002. Because the smoking behavior of teenagers,
who are the most vulnerable to initiate smoking, is particularly sensitive to price increases, the incremental
annual benefit of raising taxes grows with every year
for decades [9,10].
In spite of strong evidence for the effectiveness of
cigarette taxes to reduce smoking, there may be limits to
how high a tax rate will be politically viable. Recent tax
increases, although frequent, have been modest in most
states, resulting in an average per pack price increase
of only about 15%, and in several cases are only temporary [11]. Resistance from tobacco companies and
smokers [5] coupled with concerns about the possible
emergence of black markets [12] and an unfair burden on poor smokers who may lack the resources to
quit [13] may discourage lawmakers from setting tax
rates high enough to derive maximum benefit to the
population.
Keeping in mind the political costs of additional tax
increases, policymakers may want to consider other
interventions to improve the population’s progress
toward healthy people smoking prevalence goals.
Already, many states have implemented programs
including education and advertising campaigns, clean
indoor air laws and telephone support hotlines, but a
weakness in current efforts to reduce smoking is the
relative ease of youth access to tobacco, which persists even with stricter enforcement of the current legal
smoking age [14].
Teenagers obtain cigarettes from two primary types
of sources: commercial sources (direct retail purchase),
and social sources (buying or being given cigarettes
from friends, acquaintances and relatives). With more
rigorous enforcement of the minimum legal purchase
379
age for tobacco of 18 years, the proportion of underage smokers who usually buy their own cigarettes in
stores has been cut in half (from 38.7% to 18.8%) from
1995 to 2003. This reduction in reliance on commercial sources of cigarettes, however, has been offset in
part by increased use of social sources over the same
time span. The proportion of teen smokers who usually
obtain cigarettes by giving someone else money to buy
them has nearly doubled (from 16% in 1995 to 30% in
2003) and 9% of underage smokers are usually simply
given cigarettes by adults [15].
Gaps in youth access restrictions are problematic
because they undermine the potentially large health
benefits of reduced youth prevalence. By one estimate,
the long-term population health benefits of a given
decrease in youth smoking initiation probability are
seven times greater than those resulting from comparable improvements in adult cessation probability [16].
Ninety percent of current adult smokers took up the
habit before their 18th birthday [17], and more than half
of those who initiate smoking in their teens continue
to smoke for 16 years or longer [18]. If youth access to
tobacco can be restricted, it will provide direct health
benefits to those who will not initiate smoking. It will
also benefit those for whom initiation will be simply
delayed because of the increased probability of cessation associated with a later age of onset [19].
Effectiveness of youth access tobacco programs,
however, has been debated in literature. Rigotti et al.
[20] reporting on an evaluation of the effectiveness
of enforcing laws that ban tobacco sales to minors as
a strategy to reduce tobacco use by adolescents conclude, “we found no meaningful difference in smoking behavior between communities that implemented
enforcement programs and those that did not.” Later,
in response to comments by Moskowitz et al. [21]
the authors acknowledge [22] “nonetheless, we remain
optimistic that vigorous enforcement of the law is
possible and can stop the illegal sale of tobacco to
children.”
In a meta-analysis study, Fichtenberg and Glantz
[22] argue that youth access tobacco programs do not
affect teen smoking prevalence because as fewer merchants sell tobacco to minors, teens will use social
sources to obtain tobacco. In an editorial, based on
results from Fichtenberg and Glantz study, Ling et al.
[23] conclude that it is time to abandon youth access
tobacco programs. This resulted in additional discus-
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S. Ahmad, J. Billimek / Health Policy 80 (2007) 378–391
sion [24] and a rebuttal from authors [25]. In the discussion, DiFranza raised questions about the method
used in the Fichtenberg and Glantz study, and noted
that the meta-analysis improperly combined studies of
different cohort, cross section, and controlled and noncontrolled interventions from three different countries.
In a letter to editor, Jason et al. [26] review their position and admit that it is premature to abandon youth
access to tobacco programs.
In their discussion of flaws in current youth access
restrictions, DiFranza and Coleman [14] suggest that a
key step to improving the system would be to raise the
minimum legal purchase age (MPLA) for tobacco to
21. Ahmad [27,28] has presented a cost-effectiveness
analysis of raising the legal smoking age to 21 in
California and the US.
The legal smoking age in most of the States in USA
is 18. Alaska, Alabama and Utah have minimum smoking age of 19; Illinois [29] and Massachusetts [30] are
increasing the age to 19. Several states including Maine
[31], California [32], Connecticut [33], New Jersey
[34], New York [35], North Dakota [36], Oregon [37],
South Carolina [38], Texas [39], and Vermont [40] have
considered (through legislative bills in State assembly)
increasing the legal smoking age. The measure carries
a significant popular support across party lines in opinion polls [41,42].
The greatest benefit of a higher MLPA, given
the increased importance of non-retail sources of
cigarettes, might be the reduction of youth access
through social sources. DiFranza and Coleman [14]
cite a previously unpublished survey by Radeki indicating that 90% of adults approached by minors to
buy cigarettes are under 21. Although minors routinely
encounter 18-year olds at school and elsewhere, they
typically have much less contact with 21-year olds in
their social circles. There is no direct evidence to indicate raising the smoking age will impact smoking rates
at all, but it is plausible such a policy change might
significantly reduce minors’ access to individuals who
can legally purchase tobacco.
Combined with rigorous vendor compliance checks,
raising the smoking age has the potential to further
limit teens’ commercial access to cigarettes by reducing cashiers’ ambiguity in determining if a customer
is of legal age to buy tobacco. As it is, teenagers who
appear older than 16 have a significantly greater success
rate in purchase attempts compared to younger-looking
individuals. Even if many 19- and 20-year olds who
resemble 21-year olds succeed in buying cigarettes
following the enactment of an MLPA of 21, more individuals under 18 may be clearly recognized as being
underage and, therefore, may have their access better controlled. Given the high risk for adult smoking
associated with initiation before age 18 [17,18], delaying access in this way may carry a significant impact
on future smoking behavior. If this is true, as predicted for tax increases, the benefits of improved youth
access restriction would grow with each passing year
as more adolescents enter adulthood as non-smokers
[9,10]. The tobacco industry, restricted from overtly
targeting adolescents, appears to be focusing on young
adults [43]. Raising the MPLA could also curb some
of these tobacco company efforts with this age group
and may help offset the recent rise in initiation rates
among young adults.
This paper provides a comparison of the health benefits that would accumulate for the U.S. population
following the enactment of age 21 as the new MLPA,
and compares them to the predicted short- and longterm impacts of various levels of excise tax increases.
First, we provide an overview of the development and
calibration of the dynamic simulation model used to
estimate the short- and long-term outcomes of the indicated policy changes. Second, we describe the key
outcomes estimated in the simulation, and discuss our
assumptions of how the various policy interventions
will affect initiation and cessation rates in the population in terms of price elasticity for tax increases, and
youth initiation rates for raising the smoking age. Next,
we present estimates from the model of the cumulative health impacts, i.e., quality-adjusted life years of
each intervention in both short term (2010) and long
term (2078, i.e., after 75 years), and finally we discuss
the results and present some caveats to consider when
interpreting them.
2. Methods
Levy et al. [44–46] have done extensive work on
estimating the effects of policies directed at youth
access, using a simulation modeling approach. We
developed a dynamic simulation model using Vensim
[47] to estimate the population health outcomes resulting from raising taxes on cigarettes and raising the
S. Ahmad, J. Billimek / Health Policy 80 (2007) 378–391
legal smoking age to 21. This model has been widely
use to explore several tobacco control policies and is
described in more detail elsewhere [9,27,28,48–50].
2.1. Model overview
The simulated population is initialized to reflect
the size and smoking status distribution of every age
cohort by gender for the 2003 United States population [15,51–53]. Then, using change probabilities
derived from external sources, the simulation uses a
state-transition model with a time step of 1 year to predict births, deaths, aging, net migration and changes
in smoking status over the next 75 years. A period of
75 years was selected to ensure that the full cumulative lifetime impact of each simulated policy scenario
is captured in the output.
Change probabilities vary based on the characteristics of members of the population for any given year.
The number of live births for a given year in the simulation is computed by multiplying the number of women
in each age cohort by its respective age-specific fertility
rate [54]. Similarly, the number of deaths is computed
by multiplying the number of people of each combination of age, gender and smoking status by that group’s
respective mortality probability [54,55], and taking the
sum across all groups for each year. Net migration rates
reflect age and gender specific changes due to people
moving in an out of the population [54,56].
Participation in smoking behavior is captured
in three smoking status categories: never smokers
(smoked less than 100 cigarettes in lifetime), current
smokers (smoked 100 or more cigarettes in lifetime
and has smoked in past 30 days), and former smokers
(smoked 100 or more cigarettes in lifetime, but none
in the past 30 days). The initial population is divided
into these three smoking status categories according
to external prevalence estimates [15,53,57]. In each
subsequent year, the current number of never smokers within each age by gender group is multiplied
by age- and gender-specific initiation probabilities to
determine how many people leave the never smoker
category to join the current smoker category. The number of current smokers (by age and gender group) are
multiplied by group-specific cessation probabilities to
give the number of individuals subtracted from the current smoker group and added to the former smoker
group. Similarly, the number of former smokers (by
381
age and gender group) is multiplied by group-specific
relapse probability to indicate how many former smokers will become current smokers again. Age- and
gender-specific initiation, cessation and relapse probabilities were derived from multiple sources [52,58,59].
Cessation probability estimates were adjusted based
on age of smoking initiation to reflect the increased
likelihood of cessation that accompanies a later age of
smoking onset.
2.2. Model calibration
The model’s accuracy was improved through an iterative calibration process for which the model is initiated
with actual 1995 population values and run to a future
time point. The output is then compared to external estimates of (i) total population size (by age and gender)
[51], (ii) current adult smoker prevalence [2], and (iii)
life expectancy (by age, gender and smoking status)
[60,61]. Between iterations, some change probabilities
were adjusted until the model produced results very
similar to external estimates of total population in year
2025, 2050 and 2075 (within 1% for all groups). Model
estimates also closely matched externally computed
values of adult smoking prevalence for 2003 (22.3%
from the model compared to 22.5% from external estimate) and life expectancies (for example, in the model,
a 45-year-old female current smoker would live an
average of 33.94 additional years—very close to the
external life expectancy estimate of 33.89 years from
actuarial data).
2.3. Key outcomes
Smoking prevalence for adults (18 years and older)
is calculated for every year of the simulation run as the
ratio of the number of current smokers aged 18 or older
and the total population of that age group. Because
no estimates of price elasticity for smoking participation were available for youths aged 14 and younger,
our annual estimates of youth smoking prevalence only
include the ratio of the number of smokers aged 15–17
and the total number of people in that age group.
Health outcomes are quantified both in terms of total
accumulated life years (the cumulative sum across the
simulation period of the total number of living members
of the population at the end of each year) and, as recommended by the US Task Force on Cost-Effectiveness in
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S. Ahmad, J. Billimek / Health Policy 80 (2007) 378–391
Health and Medicine [62], quality-adjusted life years
(QALYs).
The QALY combines improvements in length of life
and health-related quality of life into a single measure
by adjusting each life year that accrues according to
a quality of life (QOL) score. For example, 10 years
of life at 85% quality would result in 8.5 QALYs. In
our model, each year of life represented was adjusted
by assigning a QOL score based on the individual’s
age, gender and smoking status. These QOL scores
were summed for the whole population for every year
of the model to determine the number of QALYs that
accumulated that year, and these annual totals were
summed across the entire simulation period. We used
QOL scores derived from Quality of Well Being scale
data provided by a 1999 personal communication from
Kaplan. Because we are not comparing present day
costs to future benefits, we did not apply a discount
rate to any outcome values.
2.4. Scenarios simulated
To determine the public health benefit resulting from
each of the proposed policy interventions, we first ran
the simulation assuming no policy change (that is, no
change in smoking prevalence across the model run)
to produce results for a status quo base case. Then,
we completed additional simulation runs incorporating
assumptions about how each proposed policy change
would effect initiation, cessation and relapse probabilities across the population, and compared those results
to the status quo case to determine the incremental
health benefit of each intervention.
2.4.1. Raising cigarette taxes
Modeling the impacts of tax increases on smoking
behavior required us to estimate price elasticity (that
is, the amount of change in behavior predicted per unit
change in price). Consistent with other work [7,63] and
building on our previous work [9], we estimated age
group-specific price elasticity of smoking participation
with a weighted ordinary least squares model using a
standard model of consumption.
The elasticity estimation model takes smoking
behavior and demographic data for over 1 million
observations from the Centers for Disease Control and
Prevention Behavioral Risk Factor Surveillance Systems (BRFSS) [53] from all 50 states from 1993 to
2000 (except 1993 when Wyoming did not participate)
and merges it with state-specific cigarette tax and price
data [64]. A dichotomous dependent variable indicating whether each individual is a current smoker was
then regressed against state-specific cigarette price,
various socioeconomic and demographic covariates
(including gender, health status, age, race, education,
marital status, and income), and dummy variables for
state and year to determine age-specific price elasticity for adults. Because the BRFSS does not include
minors, we used price elasticity estimates for the 15–17
age group from other studies. Harris and Chan [7] and
Tauras and Chaloupka [65] have estimated overall price
elasticity for youth as −0.831 and −0.79, respectively.
Unlike our price elasticity estimates, these estimates
capture both participation changes and reduced consumption. Because our model only addresses participation changes, based on evidence from literature, we
estimated that 50% of the adolescent price elasticity
was due to reduced prevalence, which resulted in a participation elasticity estimate of −0.4155 from Harris
and Chan [7]. Our estimate is comparable to participation price elasticity for young adults (−0.35) estimated
by Tauras [66] and (−0.416) by Ross and Chaloupka
[67].
These elasticity estimates, summarized in Table 1,
reflect the change in probability of being a current
smoker that would accompany a given change in
Table 1
Price effects on smoking in the US
Dependent variable
15–17
Status as a “current smoker”
Elasticity for “current smoker”
status
– (–)
−0.0320 (0.010)
−0.4155 −0.3565
18–23
24–29
30–39
40–65
65 and over
−0.0265 (0.008)
−0.2957
−0.0175 (0.005)
−0.1809
−0.0171 (0.004)
−0.1979
−0.0124 (0.004)
−0.3286
This table presents weighted ordinary least squares estimates from the BRFSS data, 1993–2000. There are 1,000,013 observations. All regressions
estimate controls for gender, age, race, education, income, martial status, health status and region effects although not reported. Standard Errors
are in parentheses.
S. Ahmad, J. Billimek / Health Policy 80 (2007) 378–391
cigarette purchase price. For example, if the price elasticity for smoking participation were −0.3 for a given
population, raising the purchase price of cigarettes by
50% would result in a 15% (0.3 times 50%) decline
in smoking prevalence. The simulation model incorporates these elasticities to predict the impact of increased
cigarette taxes on smoking participation in the population. We ran scenarios assuming tax increases that raise
cigarette prices from as little as 10% above status quo
to as much as 100% (a doubling in price), and for all
levels of tax-induced price increase at 10% intervals in
between.
2.4.2. Raising the smoking age to 21
Although the true impacts of raising the smoking
age are unknown, it is plausible that an increase in
the minimum purchase age for cigarettes coupled with
more rigorous enforcement may reduce youth access to
cigarettes. To estimate the potential effect of increasing
the MLPA for cigarettes to 21, we made the assumption that its primary impact on smoking behavior would
be to reduce or delay adolescent smoking initiation
[19]. Specifically, we assume that age-specific initiation rates would shift by 3 years so that an 18-year old in
this scenario would have the same likelihood of becoming a current smoker as a 15-year old in the status quo
(as depicted in Fig. 1). A 17-year old in this scenario
would have the initiation rate of a 14-year old, and so
on. Adults aged 21 or older would maintain their current rate for smoking initiation. We acknowledge that
there are no empirical data to support this assumption,
largely because no state in the US has ever increased the
Fig. 1. Smoking initiation rate in the US assuming a 3-year shift after
increasing the legal smoking age from 18 to 21.
383
legal smoking age to 21. We varied this assumption in
sensitivity analysis and estimated outcomes assuming
2-year and 1-year shifts in youth initiation rates.
Over time, this reduction in youth initiation would
reduce adult smoking prevalence because fewer teens
would enter adulthood as current smokers and delaying the age of initiation for those who smoke as adults
would increase the subsequent probability of cessation
[19].
2.5. Sensitivity analysis
To evaluate the sensitivity of outcomes to changes in
important parameter values we carried out a sensitivity
analysis. For cigarette excise tax increase scenario we
varied price elasticity estimates and for increasing the
legal smoking age scenario we varied the youth cohort
that will be influence by the legislation.
2.5.1. Tobacco taxes
We varied the price elasticity of tobacco excise taxes
for sensitivity analysis between −50% and +50%. We
carried out five simulation by changing elasticity by
−50%, −25%, 0%, +25%, and +50%, where −50%
change means reducing the elasticity by 50%, for example, the price elasticity for 24–29-year-old smokers will
reduce from −0.2957 to (−0.2957 × 0.5) −0.1478.
Similarly, a change of +50% will result in increase
in price elasticity to (−0.2957 × 1.5) −0.4435 for the
same age group. A 0% change means price elasticity
values reported in Table 1 are used without any change
(base case).
2.5.2. Age 21
For base case we assumed that age specific initiation
rates for 18-, 19- and 20-year olds will change following the enactment of law raising the legal purchase age
to 21. Through sensitivity analysis we explored two
more conservative alternatives assuming that legislation will result in: (i) change in initiation rates for 18and 19-year olds, i.e., initiation rates for 20-year olds
will not be affected) and (ii) change in initiation rates
for 18-year olds only, i.e., initiation rates for 19- and
20-year olds will not be affected. For a scenario where
raising the legal purchase age will not reduce smoking
at all, results of status quo run (model run without any
policy change) will hold.
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S. Ahmad, J. Billimek / Health Policy 80 (2007) 378–391
Table 2
75-Year health impacts of selected anti-smoking interventions in the US
Intervention
Smoking prevalence in 2078
Cumulative life years
15–17-year olds
>18-year olds
Total accrued
(millions)
Status quo
22.1
22.3
28853
–
24905
–
Tax increase (%)
10
20
30
40
50
60
70
80
90
100
21.0
20.1
19.2
18.3
17.3
16.4
15.5
14.6
13.7
12.8
18.9
16.6
14.8
13.5
12.3
11.4
10.6
10.0
9.4
8.9
28905
28943
28971
28994
29012
29026
29038
29049
29057
29065
52
90
119
141
159
174
186
196
205
212
24966
25012
25046
25074
25096
25115
25130
25144
25155
25165
61
106
141
169
191
209
225
238
250
260
7.5
13.6
28919
67
25014
109
Age 21
3. Results
Table 2 summarizes smoking prevalence and cumulative health outcomes for the U.S. population at the
end of the 75-year simulation. The first row presents the
status quo scenario, assuming that there is no change
in smoking behavior throughout the simulation period.
Without intervention, the model predicts that smoking
prevalence for 15–17-year olds will be 22.1% in the
year 2078, and adult prevalence (for ages 18 and older)
will be 22.3%. A total of 28,853 million life years and
24,905 QALYs would accumulate for the population
across the 75 years.
The next 10 rows in the column present results
assuming various rates of excise tax increases. The
first of these rows lists the outcomes assuming that
taxes increase nationwide to produce an average 10%
price increase for a pack of cigarettes. In this scenario,
the estimate smoking prevalence for 15–17-year olds
in the year 2078 falls to 21% and adult prevalence
to 18.9%. The population accrues 28,905 million life
years over the course of the simulation period—52 million more than was estimated for the status quo—and
24,966 million QALYs for a cumulative gain of 61
million. Subsequent rows can be interpreted similarly.
For example, if taxes are increased to produce a 20%
increase in average per pack cigarette prices, prevalence for 15–17-year olds would fall to 20.1%, adult
prevalence would be 16.6%, and a total of 28,943 mil-
Cumulative QALYs
Cumulative
gain (millions)
Total accrued
(millions)
Cumulative
gain (millions)
lion life years (for net gain of 90 million above the
status quo) and 25,012 million QALYs (an additional
106 million above status quo) would accumulate.
The final row of the table presents outcomes after
75 years the MLPA is raised to 21, and this policy
change, in fact, reduces youth access to tobacco and
delays smoking initiation as assumed. In this scenario,
smoking prevalence drops from status quo levels to
7.5% for 15–17-year olds and to 13.6% for individuals
18 and older. A total of 28,919 million life years (67
million above status quo) and 25,014 million QALYs
(109 million above status quo) would accrue over the
75-year period.
The intermediate-term effects of increased taxes
versus raising the smoking age on 15–17-year-olds’
smoking prevalence are compared in Fig. 2. The horizontal line marked “Status quo” indicates the estimated smoking prevalence in the year 2010 for this
age group assuming no changes in initiation, cessation
and relapse rates. As a reference point, a line representing the Healthy People 2010 objective of 16% for
all high school students (not just 15–17-year olds) is
also presented. The 10 bars in solid black represent
2010 prevalence estimates assuming tax-induced prices
increases of 10–100%. For example, if taxes are raised
to the point that the average per pack purchase price of
cigarettes increases by 10%, the smoking prevalence
for this age group in 2010 would be approximately
21%. For a 20% price increase, prevalence would be
S. Ahmad, J. Billimek / Health Policy 80 (2007) 378–391
385
Fig. 2. Youth (15–17-year olds) smoking prevalence in the US in 2010.
just over 20%. The final hashed bar represents the
2010 smoking prevalence for 15–17-year olds assuming the smoking age is raised to 21, but taxes do not
increase—just under 9%. Comparing the results of tax
increases and raising the MLPA, even doubling the
price of cigarettes (the 100% increase scenario) would
fall well short of the reduction in 15–17-year-old smoking prevalence by 2010 predicted for raising the MLPA
to 21. Fig. 3 makes a similar comparison for 2010 adult
smoking prevalence. Again, reference lines marking
the status quo adult prevalence of just over 22% and
the Healthy People 2010 objective of 12% are included.
The solid bars represent prevalence estimates assuming
tax-induced price increases ranging from 10% (resulting in a smoking prevalence of approximately 21%)
to 100% (producing over 16% prevalence). Under the
model’s assumptions, raising the smoking age would
produce only a very small decline in adult prevalence to
21.7% (shown in the hashed bar) by 2010. Adult prevalence does not reach the Healthy People 2010 target in
any scenario.
Figs. 4–6 compare the long-term effectiveness of
setting the MLPA to 21 and raising taxes to various
levels. Base case estimates and results from sensitivity analyses of price elasticity and initiation rate shifts
are also included. In each figure, horizontal reference
Fig. 3. Adult smoking prevalence in the US in 2010.
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S. Ahmad, J. Billimek / Health Policy 80 (2007) 378–391
Fig. 4. Youth (15- to 17-year olds) smoking prevalence in the US in 2078.
lines indicate the outcome of raising the smoking age
to 21 assuming initiation rate shifts of 3 years (the base
case), 2 years and 1 year, but assuming no tax increase.
The curves plotted in each figure represent outcomes
for levels of taxation causing per pack purchase price to
increase from 0% (the status quo condition) to 100%. In
addition to the base case plots, the results of sensitivity
analyses assuming price elasticities 50% lower, 25%
lower, 25% higher and 50% higher are plotted for each
figure. Any point at which a plotted curve intersects
with a horizontal reference line indicates a taxation
scenario that produces an effect equivalent to that of
raising the smoking age to 21 assuming the indicated
shift in initiation rate.
For example, the base case plot in Fig. 4 indicates
that smoking prevalence for 15–17-year olds in the year
2078 would range from 22% assuming the status quo
(0% tax increase) to under 13% assuming a doubling of
cigarette prices (100% tax-induced price increase). No
tax increase scenario would produce a youth prevalence
reduction equivalent to that predicted for MLPA of 21
scenario (with no tax increase) in the base case (3-year
Fig. 5. Adult smoking prevalence in the US in 2078.
S. Ahmad, J. Billimek / Health Policy 80 (2007) 378–391
387
Fig. 6. Cumulative QALYs gained in the US in 2078.
shift) or assuming a 2-year shift in initiation rate. If
initiation rate only shifts by 1 year, however, raising
the MLPA to 21 would produce a decline in prevalence
comparable to a approximately 68% price increase.
Fig. 5 shows adult smoking prevalence after 75
years. Comparing base case scenarios for both interventions it can be noted that a tax-induced price increase
of approximately 40% will result in comparable reduction in adult smoking prevalence offered by MLPA,
i.e., smoking prevalence will be just over 13% at the
end of the 75-year period for both interventions. If,
however, the resulting shift in initiation rate following MLPA is 2 years or 1 year (contrary to 3 years
assumed in base case) the level of tax required to
achieve comparable reduction in smoking prevalence
will be approximately 25% or 12%, respectively. Similarly, an increase or decrease of 25% in price elasticity
will shift the breakeven taxation point to 32% or 52%,
respectively.
Fig. 6 shows a cumulative gain in QALYs ranging
from zero (in the status quo) to 260 million (with 100%
tax-induced price increase), and approximately 110
million cumulative QALYs saved assuming a higher
smoking age—equivalent to the result of increasing
taxes to raise prices by 20%. The equivalent taxation
levels are approximately 13% and 7% if shift in age
is assumed to be 2 years or 1 year, respectively. An
increase or decrease of 25% in price elasticity will
shift the breakeven taxation point to 17% or 28%,
respectively.
4. Discussion
Adult cigarette smoking prevalence in US is declining as expected but not as desired [68]. In this work,
we compare two policy options for their potential
to reduce smoking prevalence and estimate resulting
health impacts. If youth smoking initiation is delayed
as assumed in the model, raising the smoking age to
21 would have little immediate effect on adult smoking, but would bring about a rapid reduction in youth
prevalence by reducing initiation. Over time, as more
adolescents enter adulthood as never smokers, lower
lifetime initiation rates and higher cessation probabilities will produce an overall decline in adult prevalence equivalent to an aggressive excise tax increase
(producing a 40% rise in cigarette price). Across a
75-year period, the higher smoking age would yield
an increased accumulation of QALYs comparable to
what would be observed following a 20% tax-induced
price increase—comparable to the average size of
all state tax increases enacted since the beginning of
2002.
Although slower to affect youth initiation rates,
moderate to high excise tax increases produce an immediate decline in adult prevalence and rapid accumulation of population health benefits by impacting all age
groups simultaneously. Plus, even a relatively modest
impact on youth smoking translates into lower adult
prevalence and adds to the cumulative long-term benefit of the policy.
388
S. Ahmad, J. Billimek / Health Policy 80 (2007) 378–391
Modeling outcomes over a 75-year time span allows
us to capture the slowly accumulating benefits of a
policy change, but requires that caveats be considered
when interpreting the results. For example, all intervention scenarios are compared against a status quo
condition in which smoking behaviors do not change,
even though smoking prevalence has declined in recent
years. Although we could have included a modest
decline in baseline smoking rates, we presumed that the
same forces that would produce such a decline in the
status quo would also be present in the intervention scenarios. Rather than introducing one more assumption
into the model about rate of decline in smoking prevalence for 75 years into the future without improving the
results, we opted to keep the status quo prevalence rate
constant. Because the same assumptions are used in all
scenarios, the results presented can, at a minimum, be
compared to each other.
The impacts of raising the smoking age to 21 require
making assumptions in the model. We assume that
by increasing the age gap between high school students and legal buyers, coupled with increased enforcement, teen access to cigarettes by commercial and
social means will drop, and initiation rates will shift
accordingly. We varied this assuming during sensitivity analysis and also considered more conservative
changes in initiation rates. Estimates of the potential
impacts of the policy change, however, could change
using a different assumption, and certainly there is no
direct evidence that youth initiation would be impacted
at all.
With respect to the tax increase, numerous estimates
of price elasticity for smoking participation exist in the
literature. For example, price elasticity for adolescents’
overall demand for cigarettes has been estimated anywhere from −0.8 to −1.4 [10]. The overall demand
elasticity figure from which we computed adolescent
participation elasticity was 0.831 [7], which is on the
low end of this range. If the actual elasticity is, in fact,
greater than this, smoking prevalence would be lower,
and health benefits would be greater than the values
reported in this paper. Inflation is not included in the
model because we assume that even though cigarette
prices will increase in absolute terms over time, they
will not change relative to the price of other goods.
Both of the proposed interventions carry with them
practical considerations. Raising the MLPA to 21 must
be accompanied by strict vendor compliance checks,
educating law enforcement, retailer and the public
about the policy and more thorough id checking by
cashiers—all of which carry costs. Given that each of
the hundreds of millions of packs sold nationwide costs
society US$ 8.61 in medical care and lost productivity,
however, some or all of the policy’s costs will be offset
by the savings and benefits it generates [27,28,69].
Additionally, efforts to control youth access to
tobacco are typically met with increased “leakage”
of cigarettes into the teen population through social
means [70]. Even with a higher purchase age and rigorous enforcement, minors will still be able to access
cigarettes through social channels, but not easily in a
quantity large enough to support a regular smoking
habit. Because the policy change would reduce teens’
access to legal buyers in their daily routines and limit
their success in buying cigarettes from stores, fewer
teens would be likely to obtain enough cigarettes to sustain a high level of consumption. Other sources such as
internet vendors with weak age verification procedures
would also have to be more tightly regulated to ensure
maximum benefit of the policy change [71].
Similarly, tax increases may motivate leakage in the
form of smuggling. Black market activity can dilute the
effects of tax increases by making cheaper cigarettes
available to motivated smokers. Vendors on Native
American reservations open additional opportunities to
purchase cigarettes in person or over the internet at low
prices with little or no tax [72]. Because the proposed
policy change is nationwide, it does not create any new
incentive for interstate smuggling, but may result in
increased smuggling from other countries. Although
the exact magnitude of this effect is unknown, research
suggests that the impact of smuggling is not large, and
smuggling may reduce but will not eliminate the benefits of excise tax increases [73,74].
Another concern surrounding cigarette excise taxes
is their potential recessivity [13]. In general, as a proportion of disposable income, excise taxes represent
a larger burden to poor people than to more affluent
individuals. Because price elasticities for smoking are
higher for people with lower incomes, however, raising
excise taxes may actually reduce the relative tax burden
for poorer individuals as their total cigarette consumption (and expenditure) drops by a greater amount than
for more wealthy smokers [75]. Even if this is true in the
aggregate, however, policy-makers should be sensitive
to the burden high excise taxes may place on individu-
S. Ahmad, J. Billimek / Health Policy 80 (2007) 378–391
als who do not quit—particularly if a lack of resources
is an impediment to cessation.
Both types of anti-smoking interventions discussed
here have their own advantages and obstacles which
policymakers must balance in pursuing a health promotion agenda. Estimates from our simulation model
suggest that impacts of raising the smoking age to
21 may be comparable to the effects predicted for
the typical moderate level of tax increases passed
in recent years throughout the U.S. Although large
excise tax increases would have the largest and most
immediate effects on smoking prevalence and population health, if the political climate does not support
such a policy, alternatives such as strengthening youth
access restrictions by raising the MLPA should be
considered.
Acknowledgement
The National Institute of Drug Abuse supported this
work through a grant (PHS GrantDA13332) to the University of California Irvine Transdisciplinary Tobacco
Use Research Center (http://www.tturc.uci.edu/).
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