eLetters

493 e-Letters

  • In Reply: Youth tobacco use before and after flavoured tobacco sales restrictions in Oakland, California and San Francisco, California

    Pesko’s central argument is that it does not matter that Friedman’s assessment of the effect of San Francisco’s ban on the sale of flavored tobacco products is not based on any data collected after the ban actually went into force. In particular, Friedman’s “after” data were collected in fall 2018, before the ordinance was enforced on January 1, 2019.[1] Pesko incredibly argues that Friedman’s “before-after” difference-in-difference analysis is valid despite the fact that she does not have any “after” data.

    Pesko justifies this position on the grounds that the effective date of the San Francisco ordinance was July, 2018. While this is true, it is a matter of public record that the ordinance was not enforced until January 1, 2019 because of the need for time for merchant education and issuing implementing regulations.[2]

    Friedman is aware of the fact that the enforcement of the ordinance started on January 1, 2019 and used that date in her analysis. In her response[3] to critiques[4] of her paper, she stated “retailer compliance jumped from 17% in December 2018 to 77% in January 2019 when the ban went into effect.” Friedman thought the YRBSS data was collected in Spring 2019; she only learned that the “2019” San Francisco YRBSS data she used were in fact collected in fall 2018 from our paper.[1]

    Rather than simply accepting this as an honest error and suggesting Friedman withdraw her paper, Pesko is offering an after-the-fact justification for the cl...

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  • Methods question / comment on the discussion

    ¶ I enjoyed reading this paper. I appreciate the author's use of difference-in-difference (DD) methodology. There were some things I found unclear that I would like to ask the authors to comment on.

    ¶ First, could the authors provide greater clarity on the model for column 1 of Table 1? Is the dependent variable here a yes/no for current cigarette use? The authors write, "Adolescents reported lifetime and prior month use of cigarettes, which we combined into a count variable of days smoked in the past month (0–30)." How does lifetime cigarette use help the authors to code the current number of cigarette days? The authors later state that they show that "increasing implementation of flavoured tobacco product restrictions was associated not with a reduction in the likelihood of cigarette use, but with a decrease in the level of cigarette use among users." Do the authors mean lifetime cigarette use here, or current cigarette use? The authors estimate this equation with an "inflation model," which I am not aware of. Could the authors provide more information on this modelling technique? This is not discussed in the "Analysis" section.

    ¶ Second, I felt like this statement is too strong. "Our findings suggest that[...] municipalities should enact stricter tobacco-control policies when not pre-empted by state law." Municipalities need to weigh many factors in making these decisions, including the effects of popu...

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  • Scientific concerns

    ¶ The authors make some points in their article that are reasonable: 1) the generalizability of San Francisco's flavor ban compared to other places is an open question, and 2) the original study uses the San Francisco ban effective date rather than enforcement date. The original author (Friedman), who does not accept tobacco industry funding and is a well-respected scientist in the field, had pointed to both facts in her original article. So that information isn’t new.
    ¶ The current authors appear to construct a straw man argument claiming that Friedman argued that she was studying the effect of San Francisco enforcing its flavor ban policy. Friedman specifically wrote in her original article that she was studying, “a binary exposure variable [that] captured whether a complete ban on flavored tobacco product sales was in effect in the respondent’s district on January 1 of the survey year.” She specifically uses effect in the above sentence, so there is no ambiguity that she is studying effective date. San Francisco’s flavor ban effective date was July 2018 (Gammon et al. 2021).
    ¶ The authors found new information that the San Francisco YRBSS survey was collected between November to December of 2018. Gammon et al. 2021 (Appendix Figure 1) shows that flavored e-cigarette sales declined in San Francisco between the effective date and the end of August 2018 (compensating for a 30-day look-back period for the YRBSS question wording), even though the flavor ban...

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  • Response to Wang, 'Some discrepancies and limitations'

    NOT PEER REVIEWED

    We would like to thank Mr. Wang for his feedback on our paper, Indicators of dependence and efforts to quit vaping and smoking among youth in Canada, England and the USA.

    With regards to the ‘discrepancies’ in vaping and smoking prevalence between those reported in Table 1 and an earlier publication [1], we have previously published these same estimates [2], along with a description of the survey weighting procedures—which were modified since the first estimates were published (as outlined in a published erratum to the cited publication [3]). Briefly, since 2019, we have been able to incorporate the smoking trends from national ‘gold standard’ surveys in Canada and the US into the post-stratification sampling weights. A full description is provided in the study’s Technical Report [4], which is publicly available (see http://davidhammond.ca/projects/e-cigarettes/itc-youth-tobacco-ecig/).

    Mr. Wang has also noted a change in the threshold used for a measure of frequent vaping/smoking: ≥20 days in past 30 days rather than ≥15 days, as previously reported [1]. We have adopted the convention of reporting using ≥20 days in past 30 days to align with the threshold commonly used by the US Centers for Disease Control for reporting data from the National Youth Tobacco Survey (NYTS), as well as the Population Assessment of Tobacco and Health (PATH) Study and the Mo...

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  • Some discrepancies and limitations

    NOT PEER REVIEWED

    There’s a published paper by Hammond and colleagues in 2019[1] using the same survey results, but there are some discrepancies.

    1. The Table 2 of the 2019 paper, prevalence of vaping in 2018 for ever, past 30 days are 37.0% (1425), 14.6% (562) in Canada, 32.7% (1276), 8.9% (346) in England and 33.6% (1360), 16.2% (655) in the US, respectively. However, in this article’s Table 1, for vaping in the same year 2018 for ever, past 30 days are 33.2% (1275), 12.1% (463) in Canada, 33.1% (1283), 9.0% (351) in England and 33.1%(1336), 15.7% (635) in the US. More discrepancies can be found on cigarette smoking section as well. These numbers warrant further explanation particularly why numbers in Canada and the US decreased while numbers in England increased? Considering previous correction of numbers to the 2019 paper has raised serious concern among some readers[1], such timely clarification in this article will be very necessary.

    2. The 2019 paper use the criteria of ≥15 days in past 30 days but the current paper adopts different criteria of ≥20 days in past 30 days, for both vaping and cigarette smoking. Further explanation is needed for such change.

    Additionally, a few considerations on possible limitations of the paper’s findings:

    1. Since the invitations were sent to nearly twice more parents than youth themselves according to the technical report[2], responds to survey questions might be biased because study has shown many...

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  • Our primary assertion is not impacted by the limitations in our statistical analyses

    NOT PEER REVIEWED
    We thank Mr. Clive Bates (1) and Dr. Moira Gilchrist (2) for their reconsideration of our work (3) and previous response where we corrected some errors (4). We also reiterate that all data informing our Industry Watch are publicly available at Tobacco Watcher (https://tobaccowatcher.globaltobaccocontrol.org/) for anyone to analyze. As with any analyses of observational data, there are limitations and we do not disagree with some of the limitations that Gilchrist and Bates point out in our analyses (as we addressed nearly all of these in our previous response (4)). However, we remain unchanged in our conclusion that, as the title of our initial article stated, “Philip Morris International used the e-cigarette, or vaping, product use associated lung injury (EVALI) outbreak to market IQOS heated tobacco” (3).

    While statistical analysis indicated a correlation between (a) PMI’s public statements regarding EVALI and their IQOS brand of heated tobacco posted to their corporate “media center” (5) and (b) trends in news coverage of EVALI and IQOS, our primary assertion is that PMI used EVALI to market IQOS. The necessary and sufficient analysis to substantiate this assertion is reporting what PMI publicly claimed, which we did by analyzing the statement made by PMI which promoted IQOS through mentioning, contrasting or describing it along with EVALI and/or vaping.

    The full text...

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  • Hagen's response to the authors

    NOT PEER REVIEWED

    Thank you for the corrections and for acknowledging the omission. The additional analysis performed by ITC is greatly appreciated and provides further insight into the impact of both interventions. Although unstated, Canada’s regional characterizing flavour bans contributed significantly to the development of a national menthol additive ban as chronicled by the U.S. Tobacco Control Legal Consortium[1] . I look forward to reading the full analysis when published.

    1. Kerry Cork, Tobacco Control Legal Consortium, Leading from Up North: How Canada Is Solving the Menthol Tobacco Problem (2017). https://www.publichealthlawcenter.org/sites/default/files/resources/tclc...

  • Increasing quitting in older smokers should be top priority in rich countries

    NOT PEER REVIEWED
    Reducing smoking rates in older smokers will achieve a far greater reduction in deaths & disease and do this much earlier than reducing already much lower smoking rates in teens & young populations. Tobacco harm reduction (THR) options, such as vaping, Heated Tobacco Products (HTP), snus & nicotine pouches, all avoid inhalation of smoke from tobacco combustion and are less risky than smoking cigarettes which are responsible for the death of more than 50% of long term smokers. Cigarette sales in Japan declined by over 40% in five years after HTPs entered the Japanese market in 2016. There are now many other examples of other THR options substituting for deadly cigarettes in other countries.
    New drug harm reduction interventions usually face fierce opposition for many years after their introduction. Needle syringe programs to reduce HIV spread among and from people who inject drugs were still strongly resisted long after the evidence for their effectiveness, safety and cost effectiveness was incontrovertible. It is not surprising to me therefore, as a veteran of many battles over new drug harm reduction interventions, to observe the acrimonious debate over THR.
    If it is made easy for older smokers to switch to THR options, the benefits will not only be an acceleration in the decline of smoking related deaths and disease, but also a more rapid decline in cigarette sales.

  • Authors’ response to L Hagen

    NOT PEER REVIEWED
    In his comment, Les Hagen brings up an important distinction between two types of restrictions on menthol: a menthol additive ban, and a menthol characterizing flavour ban. Canada's menthol ban across the provinces did indeed involve both types. Between May 2015 and July 2017, Nova Scotia, Alberta, Quebec, Ontario, Prince Edward Island, and Newfoundland & Labrador implemented characterizing flavour bans, whereas New Brunswick implemented a menthol additive ban [1]. When the Federal Government implemented a menthol additive ban in October 2017 [2] , it applied only to the remaining provinces—British Columbia, Saskatchewan, Manitoba—as well as Nunavut, Yukon, and the Northwest Territories. Thus, the "menthol cigarette ban" in Canada is a mixture of the two types.

    Our article [3] evaluated the impact of menthol bans implemented between the 2016 and 2018 waves of the Canadian arm of the ITC Four Country Smoking and Vaping Surveys. Hagen incorrectly stated that "the analysis was performed exclusively on provincial characterizing flavour bans." In fact, the provinces evaluated in our study included both those that implemented characterizing flavour bans (Quebec, Ontario, Prince Edward Island, Newfoundland & Labrador) and those that implemented the Federal menthol additive ban (British Columbia, Saskatchewan, Manitoba).

    In our original study, we did not test for differences between the two kinds of bans, beca...

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  • In Response to Michael Pesko's Comments "Scientific Concerns"

    NOT PEER REVIEWED
    We thank Pesko for his comments and the opportunity for us to respond and clarify.

    First, we appreciate Pesko’s clarification that Cotti et al. (2020) clustered standard errors to account for clustering. In the present study, we used multilevel analysis not only to account for clustering of respondents (i.e., design effects) but also to incorporate different error terms for different levels of the data hierarchy which yields more accurate Type I error rates than nonhierarchical methods where all unmodeled contextual information ends up pooled into a single error term of the model.

    Second, we understand that Cotti et al. (2020) evaluated the magnitude of e-cigarette tax values, which does not contradict to our statement because our study focused on the effects of e-cigarette excise tax policies on individual e-cigarette use and prevalence rather than aggregated sales at state or county levels. We also clearly described the reason why we examined the e-cigarette excise tax policy implementation indicator rather than its magnitude in our paper’s discussion section.

    Third, our study used a nationally representative sample of young adults (rather than a nationally representative sample of general adult population). While we understand Pesko’s concern that a sample’s representativeness might be lost when subgroups are explored, we believe our use of sampling weights in analysis has reduced such a concern.

    Fourth, in Table 3,...

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