The paper by Asfar et al (1) had a noble objective, which was to inform ENDS health risk communications by updating the 2018 evidence review by the US. National Academies of Sciences, Engineering and Medicine (NASEM) (2). The need for improved risk communications about ENDS is reinforced by a recent study which found that only 17.4% of US smokers believe that nicotine vaping is safer than smoking (3). While ENDS use is not safe, the evidence from toxicant exposure studies does show that ENDS use is far safer than smoking cigarettes and may benefit public health by assisting those who smoke to quit smoking (4, 5).
An important limitation of the umbrella review method utilized by the authors is that it does not directly attempt to systematically characterize new research. This is a concern because the marketplace of ENDS products used by consumers has evolved since the 2018 NASEM report (4, 5). Furthermore, the authors have included some meta-analyses of selected reviews for some domains, but these meta-analyses were not in the Prospero pre-registration (6), nor explained in the paper. It’s thus unclear how or why certain reviews were selected for meta-analysis, and also whether the comparators are the same for these reviews. More importantly, these meta-analyses risk single studies contributing multiple times to the same pooled estimate. The authors noted this as a limitation commenting inaccurately that ‘it was impossible to identify articles that were included in multiple reviews’. In our view this serious methodological flaw merits removal of all pooled estimates from their analyses. Additionally in several places, association is conflated with causality (e.g. “ENDS use impedes smoking cessation”) when based on observational data. The classification of evidence is also not transparent, cannot be found in the source the authors cited, and in places does not follow from the evidence presented (e.g. gateway evidence classified as high when based on observational studies).
The review also excludes research reviews supported by ENDS manufacturers. While we recognize and agree with the authors’ concerns about possible bias in industry publishing, we also believe that the exclusion of such research without any analysis of the scientific merits of the research itself precludes a comprehensive assessment of the scientific literature regarding the health risks of ENDS. Also, excluding industry publications necessarily eliminates from consideration evidence that the Center for Tobacco Products may be asked to consider when it is reviewing product applications for product marketing authorizations and modified risk claims.
The paper falls short, as well, in addressing the risk communication implications of the findings since the authors’ recommendations often do not match the evidence of what is known and not known about the risks of using ENDS. A careful analysis of suggested risk messages contained in supplementary material to the paper finds messages that do not appear to be supported by the evidence reviewed in the paper. For example, the suggested risk messages that "nicotine in vapes can harm memory, concentration, and learning in young people," "vaping nicotine can harm learning ability in young people," and "exposure to nicotine during adolescence can interfere with brain development" do not appear to be derived from a comprehensive review of scientific evidence. The evidence of nicotine having adverse effects on brain development or learning in adolescents comes primarily from rodent studies where dosing of nicotine is not necessarily analogous to exposure from ENDS.
For most of the topics reviewed, the umbrella review reveals that the health risks of ENDS remain unsettled at this time. Whilst biomarker exposure data clearly indicate reduced risk compared to tobacco cigarettes (4), we would suggest restraint is needed in communicating absolute risk information to the public (7). Also we would go one step further in noting that whatever the health risks of ENDS may be, they are going to be most observable in those persons using ENDS on a persistent basis for months or years at a minimum. For example, the health risks of cigarette smoking do not reliably emerge until after smokers exceed 10 pack-years or more of exposure (87). Few studies of ENDS health risks have actually focused on the likely higher risk group of persistent ENDS users (4).
We also take issue with the paper’s main conclusion that direct comparison between the harms of cigarettes and ENDS should be avoided (1). In fact, such comparisons are likely unavoidable and necessary since the group most likely to use ENDS on a persistent basis are those who have a history of cigarette use. Moreover, ENDS were originally developed as a cessation aid and evaluations of cessation aids almost always incorporate evidence on the relative harms compared to continuing to smoke. We do recognize that accounting for a person’s smoking history complicates evaluations of the health risks of ENDS, but dismissing such comparisons simply ignores the fact that ENDS are existing or potential cigarette substitutes for many smokers (4, 5). A recent review of biomarker studies found that compared to smoking, using ENDS leads to a substantial reduction in biomarkers of toxicant exposure associated with cigarette smoking, while also acknowledging that the degree of any residual risk from smoking remains unclear because of the lack of comparisons between long-term former smokers, and with those who have never smoked or used ENDS (4).
Communicating health risk information about ENDS has to have some context to be meaningful to consumers. A common misconception about tobacco use is that the most dangerous component of the product is nicotine (9-14). However, while nicotine can be addictive, it is the other toxicants in tobacco, especially burned tobacco, that are the true culprits of tobacco-related diseases (2, 4). Thus, when communicating information about the health risks of tobacco products, it makes sense to provide consumers with information about the relative health dangers from burned compared to unburned tobacco products. The example risk messages included in the supplementary materials to the paper appear to be developed with a goal of discouraging anyone from using a vaping product rather than to inform potential users about risks.
Public health authorities can reduce the risk of misinforming or confusing the public by acknowledging when evidence is incomplete or based on statistical association rather than clear evidence of causality, and by updating any statements or recommendations quickly when plausibly causal evidence becomes available (7).

 
References
1. Asfar T, Jebai R, Li W, et al. Risk and safety profile of electronic nicotine delivery systems (ENDS): an umbrella review to inform ENDS health communication strategies. Tob Control Epub ahead of print: [please include Day Month Year]. doi:10.1136/ tobaccocontrol-2022-057495
2. National Academies of Sciences, Engineering, and Medicine; Health and Medicine Division; Board on Population Health and Public Health Practice; Committee on the Review of the Health Effects of Electronic Nicotine Delivery Systems. Public Health Consequences of E-Cigarettes. Eaton DL, Kwan LY, Stratton K, editors. Washington (DC): National Academies Press (US); 2018 Jan 23.
3. Kim S, Shiffman S, Sembower MA. US adult smokers' perceived relative risk on ENDS and its effects on their transitions between cigarettes and ENDS. BMC Public Health. 2022 Sep 19;22(1):1771. doi: 10.1186/s12889-022-14168-8.
4. McNeill, A, Simonavičius, E, Brose, LS, Taylor, E, East, K, Zuikova, E, Calder, R and Robson, D (2022). Nicotine vaping in England: an evidence update including health risks and perceptions, September 2022. A report commissioned by the Office for Health Improvement and Disparities. London: Office for Health Improvement and Disparities.
5. Balfour DJK, Benowitz NL, Colby SM, Hatsukami DK, Lando HA, Leischow SJ, Lerman C, Mermelstein RJ, Niaura R, Perkins KA, Pomerleau OF, Rigotti NA, Swan GE, Warner KE, West R. Balancing Consideration of the Risks and Benefits of E-Cigarettes. Am J Public Health. 2021 Sep;111(9):1661-1672.
6. Rime Jebai, Wei Li, Oluwole Olusanya Joshua, Beck Graefe, Celia Rubio. Systematic Review of Reviews on the Harmful Effects of Electronic Nicotine Delivery Systems: Building Evidence for Health Communication Messaging. PROSPERO 2021 CRD42021241630 Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021241630
7. United States Surgeon General. Confronting Health Misinformation: The U.S. Surgeon General’ s Advisory on Building a Healthy Information Environment [Internet]. 2021 [cited 2022 Aug 9]. Available from: https://www.hhs.gov/sites/default/files/surgeon-general-misinformation-a...
8. Doll R, Peto R, Boreham J, Sutherland I. Mortality from cancer in relation to smoking: 50 years observations on British doctors. Br J Cancer. 2005 Feb 14;92(3):426-9. doi: 10.1038/sj.bjc.6602359.
9. O’Brien EK, Nguyen AB, Persoskie A, Hoffman AC. U.S. adults’ addiction and harm beliefs about nicotine and low nicotine cigarettes. Prev Med. 2017;96:94-100.
10. Steinberg MB, Bover-Manderski MT, Wackowski OA, Singh B, Strasser AA, Delnevo CD. Nicotine Risk Misperception Among US Physicians. J Gen Intern Med. 2021, 36(12):3888-3890.
11. Elton-Marshall T, Driezen P, Fong GT, et al. Adult perceptions of the relative harm of tobacco products and subsequent tobacco product use: Longitudinal findings from waves 1 and 2 of the population assessment of tobacco and health (PATH) study. Addict Behav. doi:10.1016/j.addbeh.2020.106337.
12. Parker MA, Villanti AC, Quisenberry AJ, Stanton CA, et al. Tobacco Product Harm Perceptions and New Use. Pediatrics. 2018 Dec;142(6):e20181505. doi: 10.1542/peds.2018-1505.
13. Yong HH, Gravely S, Borland R, Gartner C, et al. Perceptions of the Harmfulness of Nicotine Replacement Therapy and Nicotine Vaping Products as Compared to Cigarettes Influence Their Use as an Aid for Smoking Cessation? Findings from the ITC Four Country Smoking and Vaping Surveys. Nicotine Tob Res. 2022 Aug 6;24(9):1413-1421. doi: 10.1093/ntr/ntac087.
14. National Cancer Institute. Health Information National Trends Survey. HINTS 5 cycle 3, 2019. Available at: https://hints.cancer.gov/view-questions-topics/question-details.aspx?PK_...

NOT PEER REVIEWED
These arguments by Pesko and Friedman cannot undo the central flaw in the Friedman paper. We are surprised that Pesko and Friedman continue to argue that Friedman’s analysis of the YRBSS fall data as “after” data is valid despite the Friedman paper defining the exposure variable as follows: “A binary exposure variable captured whether a complete ban on flavoured tobacco product sales was in effect in the respondent’s district on January 1 of the survey year.”[1] If Friedman had intended to treat the period immediately after July 21 2018 as the “after” period, why had she not selected July 21 of each year as the cut-off date for indicating exposure to the policy effects? It seems apparent that Friedman chose the January 1, 2019 as the cut-off for “after” data because she knew this was the enforcement date and she assumed wrongly that the YRBSS data were collected after January 1, 2019. This is evident in her own response[2] to a critique[3] of her paper as we already noted in our previous response.[4]
Friedman states that “the official/legislated effective date are used to ensure that resulting estimates capture unconfounded responses to the policy change.” Again, if this approach made sense in the specific San Francisco case, why did Friedman use January 1, 2019 in her paper? Perhaps because it simply doesn’t make sense to attribute a policy’s effects before the policy is actually implemented. Similarly, the use of enforcement date rather than effective date is not at all as unusual as Pesko claims. Pesko and Friedman’s suggestion to use effective date post hoc simply does not make any logical sense in the San Francisco case, where there was an explicit and highly publicised period of non-enforcement as well as documented non-compliance with the policy through the period of survey administration. In fact, all the existing papers on the San Francisco flavour ban,[5–8] including the Friedman paper,[1] have used the January 1, 2019 enforcement date as the cut-off date for evaluating the policy implementation effects.
Friedman rightly points out that the San Francisco Department of Public Health didn’t even begin compliance inspections until December 3rd, 2018. The YRBSS survey was already nearly complete (fielded between November 5th and December 14th, 2018) at that time. In addition, the current smoking question assesses smoking in the past 30 days, meaning that all of the survey respondents would be reporting on their smoking behaviour for a preceding period that encompasses a time before compliance checks began. When compliance checks began in December, only 17% of retailers were found to be compliant with the flavour ban, likely because they were explicitly instructed that there would be no penalties until January 1, 2019. These facts mean that youths’ retail purchase access would not have changed appreciably at that time. Her conclusion in her paper that “reducing access to flavoured electronic nicotine delivery systems may motivate youths who would otherwise vape to substitute smoking”[1] is inconsistent with the fact that e-cigarettes were still widely available in San Francisco in the fall of 2018.
Pesko and Friedman cite Gammon et al. (2021) showing reduced e-cigarette sales[5] to argue that Friedman’s analysis is still valid because the law may have led to a decrease in youth’s demand for e-cigarettes before the enforcement date. In truth, the vaping rate went from 7.1% to 16% in San Francisco between 2017 and 2019. We note that the Friedman paper omitted reporting youth vaping prevalence,[1] stating that “Recent vaping was not considered because of likely confounding. California legalised recreational marijuana use the same year San Francisco’s flavour ban went into effect; in addition, the YRBSS’s vaping questions did not distinguish vaping nicotine vs marijuana.” The decision to not control for vaping in the Friedman analysis is not justified. Friedman wrote in her response[2] to three critiques[3,9,10] of the original paper that the reason was potential misclassification of marijuana vaping due to California’s legalisation of recreational marijuana because the YRBSS questions do not specify the substance being vaped. Marijuana exclusive vapers account for only about 1% of the youth population, making this an inappropriate reason to not control for significant differential changes in vaping over time in different cities.[11–13] For example, vaping rates went down in Oakland after the flavour restriction but were up significantly in the 2018 pre-enforcement period in San Francisco. Initiation of vaping nicotine has been associated with higher rates of subsequent use of cigarettes among adolescents.[14,15] Higher rates of vaping nicotine e-cigarettes may also have been the impetus for passage of the San Francisco flavour ban, making vaping an important confounder. Taken together, these facts make uncontrolled confounders a likely explanation to cigarette use differences across locations and therefore decreases the possibility that the cigarette smoking rate went up due to an unenforced flavour ban.
Pesko and Friedman did not mention that Gammon et al. (2021) reported the predicted flavoured nicotine e-cigarette sales in San Francisco increased from 3439 units per week pre-policy (July 2015-July 2018) to 5906 units per week in the effective period (July-December 2018) and only declined after the enforcement period (January-December 2019) to 16 units per week (Table 1 in their article).[5] Clearly, flavoured e-cigarettes were still widely available in the marketplace during the effective but non-enforced period and in fact, more flavoured e-cigarettes were sold during the effective period than prior to the policy. Furthermore, Friedman also did not mention that Gammon et al. (2021) reported that cigarette sales declined post flavour ban.[5] Predicted total cigarette sales in San Francisco declined from 83424 units per week pre-policy (July 2015-July 2018) to 77370 units per week in the effective period (July-December 2018) and further declined after the enforcement period (January-December 2019) to 64220 units per week (Table 1). [5] This pattern is therefore inconsistent with Friedman’s 2021 paper conclusion that “reducing access to flavoured electronic nicotine delivery systems may motivate youths who would otherwise vape to substitute smoking” in the fall of 2018. The fact is average weekly flavoured e-cigarette sales increased while total cigarette sales decreased in San Francisco between July-December 2018 compared to pre-policy period. [5] The substitution explanation falls apart. Pesko and Friedman cannot selectively use data to have it both ways.
As we described in our paper, after Oakland implemented a convenience store flavoured tobacco sales restriction in July 2018, high school youth vaping declined from 11.2% to 8.0% (p=0.04)[16] and smoking declined from 4.4% to 2.4% (p=0.02)[17] between 2017 and 2019. Our description that vaping and cigarette use prevalence declined was accurate. Upon reviewing the YRBSS data from the CDC, the Oakland data does in fact represent a statistically significant drop in vaping and smoking rate from 2017 to 2019. Friedman objects to our use of the Oakland (neighboring city to San Francisco) data as a comparison because Oakland’s law was less comprehensive than San Francisco’s. We respectfully disagree with Friedman’s objection. The Oakland law that drastically limited youth access to flavoured tobacco products in that city certainly informs the San Francisco case. The idea that the decline in cigarette smoking prevalence after the flavour ban in Oakland was less than the decline of cigarette smoking elsewhere is disproven by the fact that there was a greater drop in current smoking rate in Oakland from 2017 to 2019 (46% decline from 4.4% to 2.4%) compared to the average decrease nationally across the United States (32% decline from 8.8% to 6.0%) based on YRBSS data.[18]
Friedman offered several post hoc explanations for why youth cigarette smoking might increase following a flavour ban. She offers no data from San Francisco to support market responses following the SF flavour ban, nor does she provide data that SF youth had switched to using flavour accessories. These scenarios also assume that flavoured tobacco products were no longer available at the time of the SF YRBSS data collection, but we know products were still largely available as of December 2018 in 83% of the retailers. It is historically inaccurate for Friedman to suggest that the outbreak of EVALI had any bearing on potentially reducing people’s willingness to buy vaping products from informal sellers in 2018 because this outbreak occurred in the fall of 2019, one year after the SF YRBSS data were collected.
Our description about receiving the YRBSS survey collection date through an inquiry from the CDC was accurate.[19] The CDC informed us that the YRBSS in San Francisco was conducted in the fall of 2018 and we used this information in our paper. We wrote to the San Francisco School District to confirm these dates as did Dr. Friedman.
Liber’s points about partial compliance rates are refuted by the availability of flavoured products during the survey administration period and are addressed by our above response. We thank him for agreeing that this case highlights the need for including more precise date of data collection identifiers in publicly available data sets. Given the significance and potential impact of these analyses for public health policy, it behooves all users of publicly available data to pay close attention to dates of data collection in relation to policy effective/enforcement dates when analyzing this information, to seek confirmation if there is any doubt, and not make assumptions about the dates. In this case the dates of the 2019 YRBSS administration ranged widely from fall of 2018 (SF) to fall of 2019 (NYC).[19]
An important benefit of flavour ban legislation is that flavoured combustible tobacco use goes down.[7] The use rates of flavoured combustible little cigars and cigarillos are similar or exceed the combustible cigarette use rate among youth in San Francisco, [11] making flavour bans an important tool in decreasing overall youth combustible tobacco rates.
The results of the 2019-2020 California Student Tobacco Survey, which was conducted after the enforcement of the flavour ban showed that the prevalence of cigarette smoking among San Francisco high schoolers was 1.6% (compared with 4.7% based on the San Francisco 2017 pre-ban YRBSS data).[11] After the enforcement of the flavour ban, we now see historically low smoking rates in San Francisco. This data from the time after the flavour ban was actually implemented by retailers further calls into question the conclusion of the Friedman paper.
References
1 Friedman AS. A Difference-in-Differences Analysis of Youth Smoking and a Ban on Sales of Flavoured Tobacco Products in San Francisco, California. JAMA Pediatr 2021;175:863–5. doi:10.1001/jamapediatrics.2021.0922
2 Friedman AS. Further Considerations on the Association Between Flavoured Tobacco Legislation and High School Student Smoking Rates—Reply. JAMA Pediatr 2021;175:1291–2. doi:10.1001/jamapediatrics.2021.3293
3 Maa J, Gardiner P. Further Considerations on the Association Between Flavoured Tobacco Legislation and High School Student Smoking Rates. JAMA Pediatr 2021;175:1289–90. doi:10.1001/jamapediatrics.2021.3284
4 Liu J, Hartman L, Tan ASL, et al. In reply: Youth tobacco use before and after flavoured tobacco sales restrictions in Oakland, California and San Francisco, California. Tob Control Published Online First: 16 March 2022. doi:10.1136/tobaccocontrol-2021-057135
5 Gammon DG, Rogers T, Gaber J, et al. Implementation of a comprehensive flavoured tobacco product sales restriction and retail tobacco sales. Tob Control Published Online First: 4 June 2021. doi:10.1136/tobaccocontrol-2021-056494
6 Guydish JR, Straus ER, Le T, et al. Menthol cigarette use in substance use disorder treatment before and after implementation of a county-wide flavoured tobacco ban. Tob Control 2021;30:616–22. doi:10.1136/tobaccocontrol-2020-056000
7 Yang Y, Lindblom EN, Salloum RG, et al. The impact of a comprehensive tobacco product flavour ban in San Francisco among young adults. Addict Behav Rep 2020;11:100273. doi:10.1016/j.abrep.2020.100273
8 Holmes LM, Lempert LK, Ling PM. Flavoured Tobacco Sales Restrictions Reduce Tobacco Product Availability and Retailer Advertising. Int J Environ Res Public Health 2022;19:3455. doi:10.3390/ijerph19063455
9 Mantey DS, Kelder SH. Further Considerations on the Association Between Flavoured Tobacco Legislation and High School Student Smoking Rates. JAMA Pediatr 2021;175:1290. doi:10.1001/jamapediatrics.2021.3287
10 Leas EC. Further Considerations on the Association Between Flavoured Tobacco Legislation and High School Student Smoking Rates. JAMA Pediatr 2021;175:1290–1. doi:10.1001/jamapediatrics.2021.3290
11 Zhu S-H, Braden K, Zhuang Y-L, et al. Results of the Statewide 2019-2020 California Student Tobacco Survey. https://www.cdph.ca.gov/Programs/CCDPHP/DCDIC/CTCB/CDPH%20Document%20Lib...
12 Zhu S-H, Zhuang Y-L, Braden K, et al. Results of the Statewide 2017-2018 California Student Tobacco Survey. https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUK...
13 Monitoring the Future (MTF) Public-Use Cross-Sectional Datasets. https://www.icpsr.umich.edu/web/NAHDAP/series/35 (accessed 1 Jul 2022).
14 Chan GCK, Stjepanović D, Lim C, et al. Gateway or common liability? A systematic review and meta-analysis of studies of adolescent e-cigarette use and future smoking initiation. Addiction 2021;116:743–56. doi:10.1111/add.15246
15 Soneji S, Barrington-Trimis JL, Wills TA, et al. Association Between Initial Use of e-Cigarettes and Subsequent Cigarette Smoking Among Adolescents and Young Adults: A Systematic Review and Meta-analysis. JAMA Pediatr 2017;171:788–97. doi:10.1001/jamapediatrics.2017.1488
16 Centers for Disease Control and Prevention. Youth Online: High School YRBS - Oakland, CA 2017 and 2019 Results Current Electronic Vapor Product Use. https://nccd.cdc.gov/Youthonline/App/Results.aspx?TT=A&OUT=0&SID=HS&QID=... (accessed 1 Jul 2022).
17 Centers for Disease Control and Prevention. Youth Online: High School YRBS - Oakland, CA 2017 and 2019 Results Current Cigarette Smoking. https://nccd.cdc.gov/Youthonline/App/Results.aspx?TT=A&OUT=0&SID=HS&QID=... (accessed 1 Jul 2022).
18 Centers for Disease Control and Prevention. Trends in the Prevalence of Tobacco Use National YRBS: 1991—2019. 2021.https://www.cdc.gov/healthyyouth/data/yrbs/factsheets/2019_tobacco_trend... (accessed 20 Jun 2022).
19 Centers for Disease Control and Prevention. Data Request and Contact Form- YRBSS. 2021.https://www.cdc.gov/healthyyouth/data/yrbs/contact.htm (accessed 1 Jul 2022).

NOT PEER REVIEWED
In their response to my reply, the authors appear to not address mistakes in their analysis. It's important that any inaccurate statements be corrected for the benefit of other researchers trying to learn from this conversation. 1) The authors say in their response (and the paper) that there is no "after" period in the Friedman study. However, as reported by Gammon et al. (2022), there was an immediate decline in e-cigarette sales in San Francisco at the effective date. The authors need to explain how they can say there is no "post" period if other research clearly shows that e-cigarette sales declined starting July 2018. This is a central part of their argument and the paper unravels if there actually is a reduction in July 2018 as has been documented previously. The authors mention in their reply that they are aware of changes beginning in July 2018 ("merchant education and issuing implementing regulations"). The press may also have widely covered the effective date, which led to changes in youth's demand for e-cigarettes. Many retailers may have wished to become compliant immediately rather than wait until enforcement. All of these are valid potential mechanisms explaining why e-cigarette sales declined starting July 2018. So for the authors to say that Friedman doesn't have a "post" period is ignorant of both the literature and many valid reasons explaining why e-cigarette sales declined at the effective date. 1a) The authors state in their abstract: "We also found that 2019 YRBSS data from San Francisco, California cannot be used to evaluate the effect of the sales restriction on all flavoured tobacco products in San Francisco as the YRBSS data for this city were collected prior to enforcement of the sales restriction." This is undercut by the above finding that the policy effective date led to declines in e-cigarette sales. Additionally, for other researchers in this space, I highly recommend the use of effective date in these types of policy evaluation efforts. Only one thing can change the effective date: legislation. In contrast, any number of things can change enforcement dates including government resources and willpower to enforce the laws. Further, enforcement intensity can change over time for many reasons. For these reasons, enforcement is a messy source of variation subject to all kinds of endogeneity concerns. For this reason, the vast majority of quasi-experimental research uses effective date, and I recommend that continue. However, it's reasonable to consider alternative timing points (such as enactment date and/or enforcement date) as sensitivity analyses. 2) The authors state: "Following the sales restriction, high school youth vaping and cigarette use declined between 2017 and 2019 in Oakland. These observations of patterns are purely descriptive and observational and are not statistically significant changes." The authors cannot say that cigarette use 'declined' between 2017 and 2019 if this change is not statistically significant. 3) The authors say in their paper that they received the YRBSS survey collection date from the CDC. In their reply, they appear to acknowledge that this was false and they actually received the data from the San Francisco School District. The reference should be corrected so that people know where to go for this type of information in the future. 4) This statement is not completely accurate: "If youth smoking rates increased similarly in Oakland following that city’s sales restriction, this would lend credence to the call for caution against flavoured tobacco sales restrictions. However, if the patterns differ, we should identify alternate explanations for the rise in San Francisco’s youth smoking prevalence." It's entirely possible smoking rates could continue to fall, just by less than in control groups as a result of flavor bans. That would still be evidence that flavor bans are increasing smoking (by reducing smoking cessation). The loose language the authors use here could lead people to make the wrong conclusion in other contexts.

¶ 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 population health (not just to youth tobacco use). This study provides evidence from a single state that may not be generalizable to other states without preemption policies. Other studies have found unintended negative effects of flavor policies, and these studies should be referenced to balance the discussion section.

¶ I applaud the authors for providing an early data point on the effect of these policies, but certainly more work in this space is needed before policy recommendations can be made. The authors may also wish to consider for future difference-in-difference papers whether there is evidence in support of the parallel trends assumption , which is a crucial assumption underpinning the reliability of the model.
¶ References:

¶ Friedman, Abigail S. "A difference-in-differences analysis of youth smoking and a ban on sales of flavored tobacco products in San Francisco, California." JAMA pediatrics 175, no. 8 (2021): 863-865.

¶ Xu, Yingying, Lanxin Jiang, Shivaani Prakash, and Tengjiao Chen. "The Impact of Banning Electronic Nicotine Delivery Systems on Combustible Cigarette Sales: Evidence From US State-Level Policies." Value in Health (2022).