Abstract
Background
The estimated effect of cigarette graphic warning labels (GWLs) on smoking rates is a key input to FDA's regulatory impact analysis (RIA), required by law as part of its rulemaking process. However, evidence on the impact of GWLs on smoking prevalence is scarce.
Objective
The goal of this paper is to critically analyze FDA's approach to estimating the impact of GWLs on smoking rates in its RIA, and to suggest a path forward to estimating the impact of the adoption of GWLs in Canada on Canadian national adult smoking prevalence.
Methods
A quasi-experimental methodology was employed to examine the impact of adoption of GWLs in Canada in 2000, using the U.S. as a control.
Findings
We found a statistically significant reduction in smoking rates after the adoption of GWLs in Canada in comparison to the U.S. Our analyses show that implementation of GWLs in Canada reduced smoking rates by 2.87 to 4.68 percentage points, a relative reduction of 12.1 to 19.6% — 33 to 53 times larger than FDA's estimates of a 0.088 percentage point reduction. We also demonstrated that FDA's estimate of the impact was flawed because it is highly sensitive to the changes in variable selection, model specification, and the time period analyzed.
Conclusions
Adopting GWLs on cigarette packages reduces smoking prevalence. Applying our analysis of the Canadian GWLs, we estimate that if the U.S. had adopted GWLs in 2012, the number of adult smokers in the U.S. would have decreased by 5.3 to 8.6 million in 2013. Our analysis demonstrates that FDA's approach to estimating the impact of GWLs on smoking rates is flawed. Rectifying these problems before this approach becomes the norm is critical for FDA's effective regulation of tobacco products.
Background
The 2009 Family Smoking Prevention and Tobacco Control Act (FSPTCA) gave the U.S. Food and Drug Administration (FDA) authority to regulate the manufacture, distribution, and marketing of tobacco products. One key provision of the FSPTCA mandates more prominent warning labels for cigarettes and smokeless tobacco products. Specifically, FSPTCA requires pictorial or graphic warning labels (GWLs) covering the top 50 percent (the minimum percent recommended by the Article 11 of the World Health Organization's Framework Convention on Tobacco Control) of the front and rear panels of cigarette packages (Pub L No. 111-31 §201(a), 123 Stat 1776, 1842-45. 2009).
In June 2011, two years after FSPTCA became the law, FDA issued its first GWL regulations, which were later challenged by tobacco industry and subsequently struck down by the U.S. Court of Appeals (See Figure 1 for a timeline summarizing the events related to FDA's GWL regulations). One of the major reasons that the Court ruled against FDA was because FDA did not provide any “shred of evidence” that graphic warning images would “reduc[e] the number of Americans who smoke” (RJ Reynolds Tobacco Co v FDA, 696 F3d 1205, 1219, DC Cir 2012).
Figure 1.
Timeline of FDA Graphic Warning Label Regulations and Relevant Court Decisions
Despite the court ruling, the beneficial impact of warning labels, particularly large and prominent GWLs, has been well-documented.1,2 Studies have shown that large GWLs on cigarette packages are an important source of health information for smokers and non-smokers.3 Exposure to GWLs reduce cigarette packet appeal,4 increase health knowledge, awareness and perception of risks associated with smoking,5–11 strengthen intentions to quit,5 encourage quit attempts,4,7–9,12 increase use of quitlines,13 prevent relapse,14 discourage smoking initiation,4,7,8 and decrease the odds of being a smoker.12
While the literature on the effectiveness of GWLs is substantial, the evidence to date is focused more on individual level impact than population impact, and the outcomes examined have been more distal indicators of smoking behavior than proximal indicators. And there is limited evidence on the impact of GWLs on smoking prevalence. The limited evidence for prevalence has critical implications for the ongoing legal and policy debates related to the proposed GWLs by FDA, particularly in light of recent failure by the Appeals Court in recognizing a large body of evidence on individual-level outcomes, and putting undue weight on population-level impact provided by FDA, which was not adequately prepared.
As part of its rulemaking process, FDA is required by law to assess all costs and benefits associated with its proposed regulations (known as the Regulatory Impact Analysis (RIA)), and to select the approach that maximizes net benefits when regulation is necessary. Accurately assessing the impact of adopting GWLs on smoking prevalence is a key input to FDA's RIA. In the economic analysis conducted for its graphic warning label regulations, FDA relied on the Canadian experience to estimate the effect of GWLs on U.S. smoking rates. FDA first compared trends in actual and estimated smoking prevalence in Canada and the U.S. from 1991 through 2009, projecting prevalence based on changes in inflation-adjusted cigarette taxes in the two countries in the period before Canada adopted GWLs in 2000. The difference between the projected prevalence rates and the actual prevalence rates for the two countries between 2001 and 2009 was then assumed to be the result of Canada's GWLs. FDA estimated that the reduction in smoking rates attributable to GWLs to be 0.088 percentage points, equivalent to a relative reduction of 0.4% of the U.S. smoking rate.
There are several major problems inherent in FDA's approach (See Table 1 for a summary of those problems). First, FDA used cigarette excise taxes rather than actual prices paid by smokers to quantify the changes in smoking rates attributable to cigarette prices. Cigarette excise taxes, official cigarette price indices, and actual prices paid by smokers may move in different directions. Controlling for cigarette taxes may attribute too much (little) of the differential decline in smoking rates to tax changes, and reduce (increase) the estimated impact of GWLs. Additionally, FDA's approach does not permit testing the statistical significance of changes in smoking rates resulting from the adoption of GWLs; as a result, it is impossible to ascertain whether the estimated impact of GWLs is statistically different from zero. More importantly, FDA's approach does not allow causal interpretations of the effect of GWLs.
Table 1.
Flaws in FDA's Regulatory Impact Analysis on Graphic Warning Labels (GWL)
| 1 | FDA used cigarette excise taxes rather than actual prices paid by smokers, which reduced the estimated impact of GWLs on smoking prevalence. | ||
| Canada | USA | ||
| Inflation-adjusted average cigarette taxes (2001-2009) | increased by 123% | increased by 117% | |
| Average inflation-adjusted official cigarette price indices (2001-2009) | increased by 64% | increased by 42% | |
| Average cigarette prices actually paid by smokers (2002-2011) | decreased by 4% | increased by 25% | |
| 2 | FDA did not utilize all available data points in the entire study period (1991-2009) in projecting smoking prevalence in the U.S. and Canada. | ||
| 3 | It is impossible to ascertain whether the estimated impact of GWLs on smoking prevalence from FDA's approach is statistically different from zero. | ||
| 4 | FDA's approach does not allow causal interpretations of the effect of GWLs on smoking prevalence. | ||
Since those problems in FDA's approach may have profound impact on the estimates of the impact of GWLs on smoking prevalence, it warrants a careful and thoughtful reexamination. In this paper, we critically analyze FDA's approach to estimating the impact of GWLs on smoking rates in its RIA of the required graphic warnings. Employing a quasi-experimental methodology, this paper adds to the growing evidence on the impact of GWLs by examining the change in smoking rates in Canada after it implemented GWLs, compared to the U.S., where GWLs have not been implemented.
Methods
Difference-in-difference Model
To examine the impact of the implementation of GWLs on national adult smoking prevalence, we followed FDA's approach and used adult smoking prevalence data from the U.S. and Canada for 1991 - 2009, a period of 9 years before and after GWLs were introduced in 2000 in Canada. Comparing Canada as the treatment group (subject to GWLs after 2000) and the U.S. as the control group is an example of quasi-experimental methods that are widely used by economists and other policy researchers to estimate the causal impact of policy changes.15 The validity of these methods and their advantages over randomization have been well-documented.16–18, Quasi-experimental methods are particularly appropriate in this case in that it is impractical to randomize persons or jurisdictions to GWLs before they are adopted.
The reason that FDA focused on Canadian GWL experiences lie in three aspects: first, culturally and geographically, Canada provides a closer comparison for the U.S. than any other country; second, Canada is one of the first countries to adopt GWLs, thus provides more data points for examination; last, Canada's GWL policy is much more similar to what was proposed in FDA's GWL regulations than similar policies adopted in other countries and regions (see FDA Final Rule 36712). To analyze FDA's approach, we also focus on analyzing Canadian's smoking prevalence data, as compared to that in the U.S.
In this paper, we use a specific quasi-experimental design, the difference-in-difference (DD) model, to assess, estimate, and test the impact of GWLs on national adult smoking prevalence. The general DD model has the following specification:
(1) Outcomes = β1TreatmentGroup + β2PostPolicyChange + β3TreatmentGroup*PostPolicyChange + β4X + e
“TreatmentGroup” is a dummy variable with a value of 1 for jurisdictions or individuals subject to the policy being examined (in this case GWLs). The estimated coefficient β1 represents the difference between the treatment group (Canada) and the control group (the U.S.), which is not subject to the policy. “PostPolicyChange” is a dichotomous variable with a value of 1 for data observed after policy implementation. The estimated coefficient β2 shows the difference between the pre- and post-policy periods. The key parameter is β3, the interaction between the treatment group and the post policy change indicator, which reflects the estimated impact of the policy on the treatment group after implementation. Finally, X is a vector of control variables (cigarette prices in this case) and e is an idiosyncratic error term.
One of the advantages of DD model is that the existence of fixed differences in un-measured characteristics between the treatment and control groups does not affect the estimates. This is relevant to our analysis because the U.S. and Canada, despite their similarities, still have major differences.
Model Specification
To illustrate the differences between our approach and FDA's approach, we estimated the following equation based on the general DD model outlined above, using the same smoking prevalence data for the same time period used by FDA.
(2) ln(SmokingRate) = Intercept + β1Canada + β2PostGWL +β3Canada*PostGWL + β4ln(ExciseTax/PriceIndex) +β5ln(Trend) + error
The dependent variable in equation (2) is the national smoking rate in log form. Canada's smoking rates came from Health Canada's multiple surveys (including General Social Survey, Survey on Smoking in Canada, National Population Health Survey, and Canadian Tobacco Use Monitoring Survey), for years 1991 to 2009, and for the population aged 15 and above. U.S. smoking rates were for the population aged 18 and above, for years 1994 to 2009, obtained from the National Health Interview Surveys. The smoking rates used in our analysis were obtained from Table 4 in FDA's Final Rule.
In equation (2), “Canada” is a dichotomous variable with the value of 1 indicating Canada, the treatment group, and the value of 0 for the U.S., the control group. “PostGWL” is a dichotomous variable with the value of 1 indicating the post-2000 time period and the value of 0 otherwise. “Canada*PostGWL” is the interaction between the treatment group (Canada) and the post-GWL time period. β3 represents the impact of GWLs on the treatment group (Canada) after GWLs were implemented. “Trend” is a monthly trend variable used to capture the time trends in smoking rates, constructed based on the specific months in which key surveys were conducted in each country. This variable starts at 1 for January 1991, and increases by 1 each month. Data used in the analyses were presented in Appendix 1.
Controlling for Cigarette Tax/Price
Cigarette taxes/prices are one of the most important factors influencing smoking rates;19,20 it is thus important to control for their impact on smoking rates when assessing the impact of GWLs. In our analysis, we use three alternative measures to capture the influence of cigarette taxes/prices. The first is the inflation-adjusted cigarette excise tax rate in Canada and the U.S. This variable is a population weighted average of the sum of federal and provincial/territory cigarette tax rates for Canada, and the sum of the federal and population weighted state cigarette excise tax rates for the U.S. It covers the entire study period 1991-2009.
Controlling for cigarette excise taxes rather than prices ignores the complex relationship between tax rates, retail prices, and the prices actually paid by consumers, and may bias estimates of GWLs. To account for these relationships, we use two alternative price measures. First, the official cigarette price index was used. The official U.S. cigarette price index was based on the monthly tobacco and smoking products price index compiled by the Bureau of Labor Statistics, adjusted by the overall consumer price index to account for general inflation, and constructed as the average tobacco price index over the months specific to the U.S. smoking surveys. Canada's official price index was constructed based on Canadian monthly consumer price index component for cigarettes, adjusted by Canada's general consumer price index, and averaged over the months covered by the Canadian smoking surveys. The official price indices also cover the entire study period 1991-2009. The tax and official price indices were both normalized and indexed to 1 in November 2002. The U.S. tax and price variables were normalized to a Canadian scale using the exchange rate between U.S. dollar and Canadian dollar.
Official statistics on cigarette prices may not reflect the actual prices paid by smokers given opportunities to obtain untaxed cigarettes and opportunities for substitution to discount brands. To address this, we modified the official price index to incorporate actual prices paid by smokers, constructed from the self-reported prices collected in multiple waves of the International Tobacco Control Policy Evaluation Project (ITC) surveys in Canada and U.S. for the 2002-2009 period. The ITC prices were adjusted for inflation, and constructed as the average price in the months specific to surveys of smoking rates in each country. Similar to the other two measures, it was also normalized and indexed to 1 in November 2002. In our analyses, the last price measure was constructed by combining office price indices (1991-2001) and the ITC prices (2002-2009).
One of the key underlying assumptions of our DD models is that the decline in Canadian smoking rates relative to the decline in the U.S. is due to the GWLs since we do not control for changes in other tobacco control policies and other time-variant factors that may influence smoking rates in both countries. Equation (2) also assumes that both countries had the same underlying trend in smoking, which may not be true. To relax this assumption, we re-estimated equation (2), adding an interaction between the trend and the “Canada” variable, allowing for differential trends in the two countries.
Results
Table 1 presents the estimated impact of GWLs on smoking prevalence. Model 1 controls for cigarette taxes, Model 2 controls for official cigarette prices, and Model 3 controls for actual prices paid by smokers. Models 4, 5, 6 are similar to Model 1, 2, 3, respectively, but allow for different trends in the two countries.
The first row of Table 1 shows estimates of β3, the impact of GWLs implemented in Canada in 2000. They are statistically significant in all models, and range from −0.13 to −0.22. These estimates imply that GWLs reduced Canadian smoking prevalence between 12.1% (exp(−0.13)-1) and 19.6% (exp(−0.22)-1). These estimates imply that if US had adopted similar GWLs as did in Canada, the smoking rates in the U.S. would have declined by 2.87 to 4.68 percentage points, using the average pre-2001 smoking rates in the U.S. as the benchmark, which was 23.9 percentage points. Our estimated reduction in smoking rates in the U.S. is 33 to 53 times larger than the 0.088 percentage-point reduction estimated by FDA. Our estimates imply that if GWLs had been implemented in the U.S. in 2012, this would have led to a reduction of 5.3 to 8.6 million adult smokers in the U.S. in 2013, based on the number of adult smokers in the U.S. in 2011, which was 43.8 million.21
The weaknesses in FDA's approach and sensitivity of its estimates are illustrated in Table 2. Starting with the replication of FDA's approach (Model A), subsequent models modify FDA's approach by substituting the official price index for the cigarette tax (Model B), substituting the actual price paid by smokers for the tax (Model C), and by using data from the entire 1991-2009 period for both countries (Models D-F), rather than using only pre-2001 data, as done by FDA. Results in Table 2 show that estimates based on FDA's approach vary considerably across models. Not only does the magnitude of the effect vary, but the direction also changes from model to model. More importantly, because FDA's approach does not permit statistical testing, it is impossible to ascertain whether the estimated impact of GWLs is statistically different from zero, let alone to make causal interpretations. There are some minor differences between our replication of FDA's analysis (Model A) and the estimates in FDA's analysis, which may be attributed to three factors. First, Canadian federal excise tax rates differ across different provinces/territories, FDA did not specify how they constructed Canadian federal tax rates. We used the province/territory-population-weighted average as Canadian's federal tax rate. Second, when constructing the annual tax rates, we took into account the effective dates of tax rates. FDA's final rule did not provide information on how annual tax rates were constructed. Third, there was no information in the final rule on how the trend variable was constructed for observations from surveys that span 2 years. We used the mid-point method. Despite these minor differences, the magnitude of the estimated parameters and their standard errors from our replication (Model A) is very close to FDA's estimates (see Appendix 2 and 3).
Table 2.
Estimated Impact of Graphic Health Warning Labels Using Difference-in-difference Models
| Ln(Smoking Rate) | Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 |
|---|---|---|---|---|---|---|
| Canada & PostGWL | ||||||
| Interaction | −0.145*** (0.0367) | −0.163*** (0.0425) | −0.181*** (0.0455) | −0.129* (0.0644) | −0.181** (0.0722) | −0.219*** (0.0750) |
| Canada dummy | 0.229*** (0.0389) | 0.137*** (0.0320) | 0.128*** (0.0343) | 0.319 (0.290) | 0.0405 (0.317) | −0.0833 (0.332) |
| Post GWL dummy | 0.00610 (0.0332) | −0.0257 (0.0366) | −0.0478 (0.0385) | −0.00430 (0.0474) | −0.0133 (0.0550) | −0.0194 (0.0590) |
| ln(Monthly Trend) | −0.114*** (0.0175) | −0.101*** (0.0196) | −0.0994*** (0.0216) | −0.0972 (0.0578) | −0.120* (0.0667) | −0.142* (0.0701) |
| ln(Index ExciseTax) | −0.172*** (0.0450) | −0.178*** (0.0491) | ||||
| ln(PriceIndex w/o ITC Price) | −0.135** (0.0612) | −0.130* (0.0649) | ||||
| ln(PriceIndex w ITC Price) | −0.0715 (0.0709) | −0.0623 (0.0732) | ||||
| Canada & trend interaction | −0.0197 (0.0628) | 0.0218 (0.0711) | 0.0479 (0.0746) | |||
| Constant | 3.511*** (0.0789) | 3.540*** (0.0913) | 3.573*** (0.0967) | 3.429*** (0.274) | 3.631*** (0.308) | 3.769*** (0.320) |
| Observations | 29 | 29 | 29 | 29 | 29 | 29 |
| R-squared | 0.942 | 0.921 | 0.909 | 0.942 | 0.922 | 0.910 |
| Estimated Relative Reduction in Smoking Rate in Canada | 13.5% | 15.0% | 16.6% | 12.1% | 16.6% | 19.6% |
| Estimated Percentage Point Reduction in U.S. Smoking Rate (Pre-2001 Benchmark = 23.9%) | 3.11 | 3.59 | 3.97 | 2.87 | 3.97 | 4.68 |
Standard errors in parentheses
p<0.01
p<0.05
p<0.10.
Conclusion and Discussion
Since Canada adopted GWLs on cigarette packs in 2000, more than 40 countries have implemented similar prominent graphic health warning messages.22 A growing body of research has demonstrated the impact of GWLs on a number of outcomes, including health knowledge, risk perceptions, intentions to quit, quit attempts, use of quitlines, cigarette consumption and smoking relapse.1,2 This study adds to the growing body of evidence on the effectiveness of GWLs by examining their impact on smoking prevalence.
More importantly, our analyses exposed several serious methodological flaws in FDA's GWL RIA. Our analyses show that the GWLs adopted in Canada decreased adult smoking prevalence by 12 to 20%, 33 to 53 times larger than FDA's estimates. In addition, our estimates imply that if similar GWLs had been implemented in the U.S. in 2012, this would have led to a reduction of 5.3 to 8.6 million adult smokers in the U.S. in 2013. Our estimates are comparable to those found in recent studies that used individual level population survey data,12 as well as simulation models that project the impact of GWLs.23 Compared to studies that looked at intermediate outcomes such as risk perceptions or quit intentions, directly examining the impact of GWLs on smoking prevalence allows us to quantify the impact of GWLs on the number of smokers in a country, something that is critically important to policy-makers. More importantly, the quasi-experimental methodology used in this paper allows stronger inferences to be made on the possible causal impact of GWLs on smoking rates.
Our study has several limitations. First, we did not control for differences between Canada and the U.S. in other tobacco control measures, such as smoke-free air policies, marketing restrictions, and anti-smoking media campaigns. The impact of these other tobacco control policies on our estimates will depend on the strength and implementation of these policies in the two countries. If these policies were similar in Canada and the U.S. during our study period, our estimates of GWLs would not be affected. If policies were becoming stronger in one country relative to the other, our analysis could either overestimate, if policies were becoming stronger in Canada, or underestimate, if the opposite, the impact of GWLs. As a result, the estimated impact of GWLs from our DD models should be interpreted with caution.
Having said that, we believe the strength and implementation of these other policies in the U.S. were as strong as, if not stronger than, those in Canada during post-2000 period. For example, while Canada's Tobacco Act's prohibitions on advertising and promotion came into full effect after the introduction of the graphic cigarette labels, at least 41 states, plus the District of Columbia, enacted or substantially strengthened legislation regarding tobacco advertising and promotion, youth access or sampling and distribution between 2001 to 2008.24 Similarly, while Canada launched a public education, outreach, and mass media campaign that had a goal of reducing tobacco-related death and disease among Canadians in 2001, the American Legacy Foundation launched the ‘‘Truth’’ Campaign, a nationwide advertising effort aimed at discouraging youth smoking, in 2000 and continued into the 2000s. Canada made significant progress with respect to second-hand smoke protection in the past decade, by 2009 all Canadian provinces and territories had legislated protection from second-hand smoke in enclosed public places and workplaces, up from five percent of Canadians at the beginning of 2000s. Meanwhile in the U.S., 26 states and more than 500 localities in the U.S. have adopted comprehensive smoke-free policies at bars, restaurants, and workplaces since early 1990s. Second, our estimated impact of GWLs on smoking rates is the average impact over the 2001-2009 period. The impact of GWLs may erode over time as smokers become inured to the labels and the novelty of the GWLs wear off.25 Future studies could improve our analyses by accounting for other tobacco control policies and other factors that could influence smoking rates in Canada and the U.S., as well as by allowing the impact of GWLs to vary over time.
Despite these limitations, our study demonstrates that adopting large GWLs on cigarette packages reduces smoking prevalence. Our findings have direct relevance to and implications for the recent regulatory impact assessment conducted by FDA related to GWLs. The importance of these findings lies in their relevance to the status of GWLs in the U.S., where tobacco industry's challenges to implementation of GWLs have been upheld by the courts. In part, the courts' support of the industry's position derived from a lack of evidence that GWLs would reduce smoking prevalence. That conclusion was based in part on the FDA's own inadequate analysis of the impact of the GWLs in Canada.
Our analyses show that FDA's approach to estimating the impact of GWLs on smoking rates is flawed. FDA's estimates are highly sensitive to the changes in variable selection, model specifications, and time period used, and does not permit statistical testing of the impact of GWLs. This study demonstrates the inadequacy of the FDA's analysis and further shows that a more appropriate analysis indicates that the GWLs have had a statistically significant and practically important effect on actual adult smoking rates.
Compared to our estimates, and estimates from recent studies using individual level data and simulation methods, FDA's regulatory impact analysis significantly underestimate the likely impact of GWLs in reducing smoking rates in the U.S. To the extent that the assumptions and approach employed in FDA's analysis of GWLs becomes the agency's standard, continued use of this approach in FDA's economic analysis may lead to an underestimation of the impact of future proposed rules on tobacco products promulgated by FDA.
In addition, the fact that we were unable to replicate FDA's estimates indicates a significant problem with transparency and inadequacy of FDA's methods and rule-making process, which need better documentation, including more detailed descriptions of data sources, variable construction, and analytical models that are employed. Rectifying these problems before this approach becomes the norm is critical for FDA's effective regulation of tobacco products.
Supplementary Material
What the paper adds:
While the literature on the effectiveness of cigarette graphic warning label (GWLs) is substantial, there is limited evidence for their impact on smoking prevalence. This study adds to the growing body of evidence on the effectiveness of GWLs by examining their impact on smoking prevalence.
This study demonstrates that adopting large GWLs on cigarette packages reduces smoking prevalence. In addition, our analyses show FDA's approach to estimating the impact of GWLs on smoking rates is inadequate.
Table 3.
Estimated Impact of Graphic Health Warning Labels: Analyzing FDA's Approach
| Unexplained Smoking Rates in Canada | |||||||
|---|---|---|---|---|---|---|---|
| Canada1 | FDA's Approach | Model A Replication with cig taxes | Model B Replication with official price index | Model C Replication with actual paid price | Model D Using all obs with cig taxes | Model E Using all obs with official price index | Model F Using all obs with actual paid price |
| Mean pre-2001 period | 0.129 | 0.079 | 0.050 | 0.050 | 0.072 | 0.041 | 0.136 |
| Mean post-2001 period | −0.501 | −0.253 | −0.116 | −0.812 | −1.777 | −1.194 | −1.574 |
| Difference (Post - Pre) | −0.630 | −0.332 | −0.165 | −0.861 | −1.849 | −1.234 | −1.711 |
|
Unexplained Smoking Rates in the U.S. | |||||||
| United States2 | FDA | Model A | Model B | Model C | Model D | Model E | Model F |
| Mean pre-2001 period | −0.010 | 0.001 | 0.000 | 0.000 | 0.085 | 0.112 | 0.125 |
| Mean post-2001 period | −0.552 | −0.475 | −1.485 | −1.686 | −0.044 | −0.061 | −0.069 |
| Difference (Post - Pre) | −0.541 | −0.476 | −1.485 | −1.686 | −0.130 | −0.173 | −0.194 |
|
Estimated Impact of Graphic Health Warning Label on Smoking Rate | |||||||
| (Canada Difference – US Difference) | FDA | Model A | Model B | Model C | Model D | Model E | Model F |
| −0.089 | 0.144 | 1.320 | 0.825 | −1.719 | −1.061 | −1.516 | |
The estimated/predicted smoking rates in Canada were presented in Appendix 4.
The estimated/predicted smoking rates in the U.S. were presented in Appendix 5.
Acknowledgements
The authors would like to thank Dr. Timothy McAfee of the Centers for Disease Control and Prevention for his helpful comments on an early draft of this paper. We thank Cezary T.Gwarnicki and Yawen Liu of the University of Illinois at Chicago for their excellent research assistance, and Camille Gourdet and Serj Mooradian of the University of Illinois at Chicago for their legal editorial help.
Funding:
The ITC Surveys in the United States and Canada were supported by grants from the U.S. National Cancer Institute (R01 CA100362, P50 CA111236, and P01 CA138389), the Canadian Institutes of Health Research (57897, 79551, and 115216), and the Robert Wood Johnson Foundation (045734). Geoffrey T. Fong was supported by a Senior Investigator Award from the Ontario Institute for Cancer Research and by a Prevention Scientist Award from the Canadian Cancer Society Research Institute. None of the funding agencies played any role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication. The opinions expressed here are those of the authors, and do not necessarily reflect those of the sponsors.
Footnotes
Contributor statement:
FJC, GTF and JH designed the study; GTF and JH collected data; JH conducted data analysis; FJC, GTF, and JH contributed to data interpretation; JH, FJC and GTF wrote the first draft; the final version of this paper has been reviewed and approved by all coauthors.
Competing Interest: None
Patient consent: Obtained
Ethics Approval: The ITC Surveys in the United States and Canada were cleared for ethics by Research Ethics Boards or International Review Boards at the University of Waterloo (Canada) and Roswell Park Cancer Institute (US).
Provenance and Peer Review:
Not commissioned; externally peer reviewed.
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