Cigarette consumption in adult dual users of cigarettes and e- cigarettes: a review of the evidence, including new results from the PATH study [version 1; peer review: 1 approved with reservations]

Background:  Modelling disease risk from e-cigarette use requires knowing how much e-cigarette uptake affects a smoker’s cigarette consumption.  From Waves 1-3 of the US PATH study and other evidence, we sought answers to three questions: (Q1) Does consumption differ between dual users and exclusive smokers?  (Q2) Does initiating e-cigarettes affect cigarette consumption?  (Q3) Is baseline consumption related to later initiation of e-cigarettes? Methods:  Consumption data from PATH were corrected for clear recording errors, with e-cigarette use classified as established or every day, and adjustment made for demographics, use of alcohol, drugs and other tobacco products, and age of starting smoking.  Searches identified other studies published since 2008, with Q1 answered from cross-sectional studies, and Q2 and Q3 also from prospective studies. Results: (Q1) In PATH, consumption in current every day e-cigarette users was 2-3 cigarettes per day lower in dual users, with no difference seen in established users.  From 31 published studies, consumption was no lower in dual users for current or ever ecigarette users.  (Q2) In PATH study consistent decreases in consumption occurred in those becoming every day dual users with increases seen in those reverting to exclusive smoking.  Thirteen published studies consistently showed reduced consumption in those becoming dual users.  (Q3) Three studies consistently showed greater consumption in smokers subsequently initiating e-cigarettes, but no significant difference was seen for PATH. Open Peer Review


Introduction
Various population health impact models have been developed to estimate the extent to which mortality is reduced following the introduction of a reduced-risk tobacco product (RRTP). In many applications of one approach (Lee et al., 2017) it is assumed that adult dual users of cigarettes and RRTPs have a mean cigarette consumption (CC) per day that is half that of cigarette smokers who do not use RRTPs. A substantial reduction in CC in dual users is also assumed in another similar modelling exercise (Poland & Teischinger, 2017). However, other approaches (e.g. (Bachand et al., 2018;Hill & Camacho, 2017;Vugrin et al., 2015)) have assumed that dual users and cigarette-only smokers have the same or a very similar CC. While conclusions regarding CC in dual users may depend on the specific type of RRTP, there is very little evidence available on very recently introduced types, such as heated tobacco products. However, as we demonstrate, a considerable number of papers have published evidence relating to e-cigarettes.
The objective of the work described here is to review and summarize evidence in adults comparing CC by dual users of cigarettes and e-cigarettes with CC by cigarette-only smokers. More specifically, this study attempts to answer three interrelated questions.
Q1. Does CC differ between dual users and exclusive smokers?
Q2. Does take-up of e-cigarettes change CC?
Q3. Does baseline CC differ by subsequent take-up of e-cigarettes?
Answers to Q1 may be obtained from cross-sectional studies carried out at one point in time, or from prospective studies at separate follow-ups. Answers to Q2 and Q3 will usually require information from prospective studies, though cross-sectional studies asking questions on the history of tobacco use might also provide relevant results.
We derive answers to the three questions from Waves 1, 2 and 3 of the publicly available adult data from the Population Assessment of Tobacco and Health (PATH) study (Hyland et al., 2017), a longitudinal cohort study in the U.S. supported by Federal funds, some previous publications (Berry et al., 2019;Buu et al., 2018) having only considered data from Waves 1 and 2. We also derive results from a detailed review of other published literature. We restrict attention to adults as they are most relevant to the estimation of the impact on mortality of RRTP introduction, and as the level of CC in cigarette smoking youths is less firmly established.

Methods
Analysis of adult data from waves 1, 2 and 3 of the PATH study To be included in the analyses, individuals had to satisfy four criteria: 1. Be aged 18 to 54 years at Wave 1 (as e-cigarette use proved to be very uncommon in those aged 55+ years).
2. Be current every day cigarette smokers at each Wave with data available on CC.
3. Have data available on current and former established e-cigarette use at each Wave.
In the PATH dataset, the data on CC were recorded by two variables, a number and a unit (cigarettes per day or packs per day), the intention being to derive daily consumption directly from the number variable if the unit was cigarettes per day and by multiplying the number by 20 if the unit was packs per day. However, for some individuals the consumption data recorded in this way was highly implausible. For example, one individual had a recorded CC of 15 packs per day at Wave 1, 10 cigarettes per day at Wave 2 and 15 cigarettes per day at Wave 3. Here the implied consumption of 300 cigarettes per day is highly implausible and it seems much more likely that the Wave 1 consumption was actually 15 cigarettes per day. Accordingly, as described more fully in Extended data, Additional File 1 (Lee, 2020), a detailed investigation of the CC data at each Wave was carried out, and corrections were made for 84 individuals. There were 75 corrections relating to individuals where the consumption at one Wave was seven or more times the average consumption at the other two Waves. However, there were nine individuals where corrections were applied for other reasons, as described in the Additional File (see Extended data; Lee, 2020). All the analyses reported are based on the corrected CC data.
Analyses were carried out relating to current and ever established e-cigarette use, based on data for a current established e-cigarette user (one who has ever used, has used fairly regularly, and uses every day or some days) and a former established e-cigarette user (one who has ever used, has used fairly regularly, and currently does not use at all), with ever users being those who were either current or former users. Analyses were also carried out relating to current every day e-cigarette use. Note that for Wave 3, the data used were for e-product use (which also includes e-cigars, e-pipes and e-hookahs) rather than e-cigarette use, data for e-cigarette use not being available for this Wave.
All the analyses were weighted, based on the weighting factors for Wave 1, and used weighted linear regression analyses. Analyses were carried out with no adjustment for other variables and with adjustment for the other nine predictor variables selected, using a forward stepwise approach, including variables significant at p<0.05.
To answer Q1, the corrected CC was compared in exclusive cigarette smokers and in dual users, separately at each Wave.
To answer Q2 (and to provide some additional information), the change in corrected CC between two Waves was compared in four groups -exclusive cigarette smokers at both Waves, dual users at both Waves, dual users only at the second Wave, and dual users only at the first Wave. Separate analyses were carried out for each pair of Waves.
To answer Q3, the corrected CC at the first of two Waves in those who were then exclusive cigarette smokers was compared in those who did or did not become dual users. Separate analyses were carried out for each pair of Waves.
Software used to analyse data from the PATH study Relevant data were transferred for analysis to a ROELEE database, and analysed using the ROELEE program (Release 59, Build 49). All these analyses could be run using the R-program (https:/www.r-project.org), using the "lm" function including the "weights=" option for weighted linear regression, and for stepwise regression using the "step" function specifying "method=forward" and test="F".

Literature searches
The search was limited to publications from 2008 onwards, e-cigarette usage not being widely established before then (Barrington-Trimis et al., 2015;Bauld et al., 2014;Bell & Keane, 2014 Subsequently, on 26th July 2019, the search was repeated, using the same keywords as before, but restricted to papers published since 1st January 2018.
An initial trial was undertaken on the first 100 papers for which free copies were available via PubMed, with PNL screening using the abstract only, and BAF independently screening using the full paper. Based on the high level of agreement between the two methods, it was decided that initial screening on the abstract was satisfactory, but that where there was any doubt the papers would need to be obtained and examined in full. In particular, any paper apparently reporting an epidemiological survey in a general adult population which had enquired about both cigarettes and e-cigarettes should be obtained, even if there was no mention in the abstract of dual use or of the number of cigarettes smoked.
All papers were then screened by BAF or AJT, with the full paper obtained wherever necessary. Papers were accepted as having data, or as being relevant reviews. No restriction was made as to the type of device referred to by the original papers, whether e-cigarettes, ENDS, ANDS, cigalike or other terminology, or whether containing nicotine or not, except that results specifically referring to heated tobacco products were excluded.
For each paper, rejected papers were marked in two ways. First, whether they were rejected on the basis of the full paper, abstract or title, this final option only being used where no abstract was available through PubMed and the title and publication type clearly indicated it was not relevant. Papers which were at all debatable or borderline for acceptance were also examined by KJC and PNL before being finally rejected.
Second, the reason for rejection was coded as follows: 11. Report on the PATH study.
Only one reason was recorded per paper, usually (but not necessarily) the first from the list above. A note on the reason for rejection was also usually recorded.
The papers identified as review papers from the PubMed search were examined, looking for references to papers apparently describing an epidemiological survey which had enquired about both cigarettes and e-cigarettes. Except where either the context of the review paper or the title of the secondary paper indicated that the survey was in an ineligible population (corresponding to rejection codes 2-7), new papers were added to the list of candidate papers and at least the abstract was examined. As previously, unless the abstract made clear that the study population was ineligible, the full paper was obtained, regardless of whether dual use or amount smoked were mentioned in the abstract. Further review papers cited in the original set of reviews were also considered, but only if the context in the original review indicated that they referred to amount smoked.
Extraction and analysis of information from the accepted papers For each publication, information was collected on the study location, title and type (prospective or cross-sectional), the period when the study was conducted, the age of the population considered, the number of smokers, the definition of e-cigarette use (and whether it contained nicotine) and which of the three questions it could provide answers to. For Q1, the data extracted (separately for current and ever e-cigarette use) included the numbers of dual users of cigarettes and e-cigarettes, and of exclusive cigarette smokers, the CC for each group and the difference, with its statistical significance, where possible. Where distributions were given by grouped amount smoked, the estimates of CC were derived using assumed midpoints. For studies where differences could be estimated, comparisons were made, again separately for current and ever e-cigarette use, of the number showing positive and negative differences, with unweighted means and standard errors estimated overall, and separately for US and European studies. For Q2, data were extracted for studies comparing changes in CC in those becoming or not becoming current e-cigarette users, with the number showing significant differences in each direction summarized. Data were also extracted for studies reporting changes in CC only in those becoming current dual users, with the numbers showing reductions or increases summarized. For Q3, evidence was summarised comparing CC in exclusive cigarette smokers according to whether they later used e-cigarettes, there being too few studies to allow more than a description of the results.

Results
Results from the PATH study A total of 3,543 adults were eligible for the analysis. Table 1 summarizes the results relating to Q1. They show no significant tendency for CC to be associated with current or ever established e-cigarette use, with six of the differences being positive and six negative. In contrast, though based on much smaller numbers of dual users, current every day e-cigarette use is associated with a consistently lower CC, with five of the six estimates significant at p<0.05, and the estimated difference ranging from 1.50 to 2.92 cigarettes per day. Table 2 summarizes the results relating to changes in e-cigarette status between Waves, with those who are exclusive cigarette smokers at each Wave ("No No") used as the base for comparisons. The analyses comparing the "No Yes" with the "No No" group are directly relevant to Q2 as defined, while those comparing "Yes No" with "No No" provide information on the reverse association.
The results relating to established e-cigarette use, with one marginal exception, show no significant tendency for changes in CC to be associated with changes in e-cigarette use. The results for every day e-cigarette use show more evidence of a d In Waves 1 and 3 the differences in cigarette consumption are adjusted for sex, age range, school grade, race, Hispanic origin, ever used other tobacco products, and age at starting to smoke. In Wave 2 the differences are adjusted for the same list of factors except ever used other tobacco products. Significance codes are as for unadjusted differences.
relationship. While they show no consistent tendency for changes to differ between those who are exclusive cigarette smokers at each Wave ("No No"), and those who are dual users at each Wave ("Yes Yes"), there is a consistent decrease in CC in those who became dual users at the second Wave ("No Yes"), and a consistent increase in those who switch from dual use to exclusive smoking ("Yes No"). While none of the decreases are significant (at p<0.05), four of the increases are highly significant (p<0.001). However, the numbers becoming or ceasing to be dual users are small.   (Al Delaimy et al., 2015) which only compared smokers who either reported they have used e-cigarettes or will never use e-cigarettes at both surveys. Table 4 summarizes the characteristics of the 46 studies considered, in order of country within continent. Of the 46 studies, 22 were conducted in the US, five in multiple countries, three in the United Kingdom, three in Italy, two in France and one in each of 11 other countries. Of these, 16 studies involved an element of follow-up, the remaining 30 being of cross-sectional design, with three of these involving multiple cross-sectional studies. The studies mainly covered the whole adult population though some were restricted to younger adults. The number of smokers included varied considerably between studies with 10 involving more than 4,000 and seven less than 250. As will become evident, the studies varied in how e-cigarette use was defined and the questions they could answer. All the papers described the product as e-cigarettes, and it has been  assumed that all the products contained nicotine, no study stating otherwise, though many did not give details.  Nelson et al., 2015), and study 27 (Shi et al., 2015). Table 5 summarizes the results from the 39 studies that presented evidence comparing CC in dual users with that in exclusive cigarette smokers. Of these studies, the evidence related to current e-cigarette use in 25, to ever e-cigarette use in eight and to both current and ever use in six. In some studies, results were presented in terms of the distribution of the subjects by broad categories of cigarette consumption and (as described in the footnotes to The 14 studies providing estimates relating to ever e-cigarette use were equally inconsistent, with four of the ten estimated differences showing a reduction, and six an increase.

Results related to Q2
Our searches revealed 17 studies that presented evidence on whether cigarette-only smokers who become dual users change their CC. The top half of Table 6 summarizes results for five studies, all of prospective design, where dual use refers to current use and where changes are compared in those who remain exclusive cigarette smokers ("No No") and those who become dual users ("No Yes"). All these studies present evidence that reductions in CC are significantly greater in dual users. The bottom half of Table 6 also presented evidence from a further eight studies (one prospective and seven cross-sectional), where changes were only recorded in those who became dual users. Of these, seven showed large reductions, which seem likely to be substantially greater than in those remaining exclusive cigarette smokers, although lack of the relevant data prevents this from being tested, while the other (study 41 (Seto et al., 2016)) showed a smaller reduction. The evidence from these 13 studies clearly indicates that becoming a current e-cigarette user leads to a reduction in CC.
The other four studies provided less useful results. Study 22 (Choi & Forster, 2014a) reported that changes in CC were almost identical between those who had never used e-cigarettes and those who had used e-cigarettes for at least one day in the past 30 days at baseline, after adjustment for demographics and baseline CC. These results neither relate to a proper definition of current e-cigarette use, nor to taking up e-cigarettes between baseline and follow-up. Study 27 (Shi et al., 2016) concluded that "among early adopters, ever-use of first generation e-cigarettes to aid quitting cigarette smoking was not associated with improved cessation or with reduced CC, even among heavier smokers" but the basis for this conclusion is most unclear, with no formal statistical analysis described and it being unclear when the e-cigarette use occurred, and whether those who quit during follow-up were excluded. Study 37 (Grana et al., 2014) reported that "e-cigarette use at baseline was not associated with a change in cigarette consumption, controlled for baseline cigarette consumption". In study 43 (Wu et al., 2015), no difference was seen between exclusive cigarette smokers and dual users at six months follow-up in individuals who continued to smoke. These analyses related to ever rather than current use of e-cigarettes.
It can also be noted that, as studies restricted to dual users were excluded (see Literature searches, rejection reason 7), the results shown in the bottom half of Table 6 may not be comprehensive.

Results related to Q3
Our searches revealed only three published studies that presented evidence relevant to whether CC in exclusive cigarette smokers differed according to whether they later used e-cigarettes. Study 5 (Andler et al., 2016), a cross-sectional study which involved 4,752 current smokers of whom 759 also currently used e-cigarettes, noted that, before they started to vape, these individuals smoked 21 cigarettes per day as compared to 11.3 in those who continued to smoke. Though the results presented did not allow precise estimation of the difference in CC between smokers according to whether they later used e-cigarettes, the results clearly suggested that heavier smokers were more likely to start vaping. Study 35 (English et al., 2018), a cross-sectional study involving 245 current smokers, of whom 103 also currently used e-cigarettes, reported that, for each additional cigarette smoked per day prior to using e-cigarettes, individuals were 4.0% (p = 0.001) more likely to use e-cigarettes. Study 45 (Chan et al., 2019), a prospective study, presented results from a logistic regression predicting uptake of vaping in 3,797 smokers. After adjustment for a range of smoking-related and demographic variables, they reported an increasing likelihood of uptake with increasing cigarette consumption, with ORs of 1.13 (95%

Discussion
Based on the analyses of the PATH study, there was no evidence from the analysis of Q1 (Table 1) that cigarette smokers who were also current or ever established e-cigarette users had a lower CC than exclusive cigarette smokers. However, cigarette smokers who were also current every day e-cigarette users did have a lower CC by about two to three cigarettes per day. This is consistent with CC in dual users being more likely to be affected in adults who use e-cigarettes more often, occasional e-cigarette use being less likely to affect cigarette smoking habits. These results, based on cross-sectional analysis, are less relevant to the effect that e-cigarette use might have on CC than those based on changes over time (Q2). Here again the results for every day e-cigarette use (Table 2) showed more evidence of an effect, with those becoming dual users consistently decreasing CC and those switching from dual use to exclusive smoking consistently increasing their CC, although only the second result was statistically significant. It is possible that those who decided  -up (Manzoli et al., 2015) d Numbers include those who quit during follow-up e Estimated from data provided f The 82% who reduced had a mean reduction of 8.9 cigarettes per day, so, assuming the remaining 18% had no reduction, the mean reduction would be 7.3 cigarettes per day g The terms "drastically" and "slightly" were undefined h The terms "substantially" and "slightly" were undefined to take up e-cigarettes might have had a different baseline CC than those who continued to smoke cigarettes exclusively (Q3), but our analyses (Table 3) showed no evidence of this.
Two limitations of our analyses should be noted. One is the small number of cigarette smokers who were also current every day e-cigarette users, ranging from about 50 to 70 in the relevant analyses. The other is the weakness of the CC data itself. While we have made our best attempt to correct obvious errors in the data, some doubts must remain about the validity of our correction.
Two previous publications (Berry et al., 2019;Buu et al., 2018) have presented results from the PATH study using data from Waves 1 and 2, neither making any mention of correcting the clearly erroneous CC data. Buu et al. (2018) restricted attention to those who, at Wave 1, had in the past 12 months smoked cigarettes and not used e-cigarettes, and who at Waves 1 and 2 had not used tobacco products other than cigarettes or e-cigarettes. Comparisons were made between those who had or had not used e-cigarettes some day or every day in the past 30 days. The authors reported that a higher frequency of e-cigarette use was associated with a lower CC after controlling for baseline CC and other confounding variables. This finding, though based on different statistical procedures, seems consistent with our finding for Q2.
Based on current cigarette smokers aged 25+ years who were not current e-cigarette users at Wave 1, Berry et al. (2019) presented odds ratios (ORs) and 95% confidence intervals (CIs), adjusted for 12 potential confounding variables, relating at least a 50% reduction in CC between Waves 1 and 2 to new e-cigarette use at Wave 2. While no material difference was noted for experimental e-cigarette use (OR 1.08, 95% CI 0.78 to 1.48) or for some day e-cigarette use (OR 1.00, 95% CI 0.58 to 1.74), a highly significant (p<0.001) effect was noted for every day ecigarette use (OR 5.70, 95% CI 3.47 to 9.35). Their analyses defined current smokers as smoking every day or some days, whereas ours restricted attention to every day smokers. Nevertheless, though differently expressed, their analyses support our findings for Q2, with those switching to every day e-cigarette use reducing their cigarette consumption.
As regards Q1, the other published studies identified by the literature search (see Table 5) provide no clear evidence of a relationship of current or ever e-cigarette use to CC. The lack of consistent association seen in the literature aligns with the findings from the PATH study shown in Table 1 for current and ever established e-cigarette use, but not with the results for current every day use. A problem is that very few of the reviewed studies provided results for current regular e-cigarette use, which may be considered comparable to the results for every day e-cigarette use from the PATH study. Also many of the studies only presented results for grouped cigarette consumption, making it difficult to accurately quantify CC.
The results from the other published studies regarding Q2 shown in Table 6 clearly demonstrate that becoming a current e-cigarette user is associated with a reduction in CC. While this conclusion is consistent with that from the PATH study, the actual decrease in CC associated with uptake of e-cigarettes cannot be directly compared, as few of the 13 studies actually presented estimates of the mean reduction, with others simply giving the numbers reducing (or increasing) consumption, or presenting odds ratios for the probability of reducing cigarette consumption by 50% or more, and only five allowing the reduction to be tested against a suitable control group of continuing exclusive smokers.
As noted above, only three of the other published studies provided evidence relating to Q3. While these results are all consistent with those who choose to start using e-cigarettes being heavier smokers than those who do not choose to do so, our analyses of the PATH study data found no clear relationship.
Given the limited number of studies, more evidence is clearly needed to answer Q3.
Assessment of the overall evidence is unclear, partly due to the between-study differences in how e-cigarette use is quantified, and how the results are presented. Given the quite clear evidence from the analyses addressing Q2 that those taking up e-cigarettes and becoming dual users do reduce their CC, the failure to find any very clear difference in CC between current dual users and exclusive cigarette smokers from the analyses of Q1 would suggest that smokers who subsequently take up e-cigarettes had somewhat higher CC to start with. While the analyses at Q3 are rather limited they do tend to support this view.
Although the overall evidence is somewhat difficult to interpret, it appears that exclusive cigarette smokers who become dual users tend to decrease their CC, especially if they use e-cigarettes regularly. The level of reduction in CC is generally fairly modest, and seemingly inconsistent with the assumption that those becoming dual users replace half their cigarettes with e-cigarettes. However, given the much lower claimed disease risks of e-cigarettes relative to cigarettes (Nutt et al., 2014), it seems quite possible that smokers who become dual users will reduce their disease risk to some extent.
Overall, it can be concluded that there is clear evidence that exclusive cigarette smokers who become dual users of cigarettes and e-cigarettes reduce their daily CC. The reduction seen is quite modest in most studies (e.g. two or three cigarettes per day), though some studies show greater reductions. The fact that cross-sectional analyses show little difference in CC between dual users and exclusive cigarette smokers may be due to those who take up e-cigarettes tending to be somewhat heavier cigarette smokers to start with, though more evidence is needed to confirm this. Obtaining accurate overall estimates is made difficult by the different way that studies present their results.
Harmonization in the way data on patterns of use of different tobacco products are collected and analysed across studies is warranted. This project contains the following extended data file:

Data availability
• CC in dual users -additional file (DOCX).
Extended data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).
achieve the optimum outcome of reducing smoking related diseases, adult smokers must switch completely from cigarettes to e-cigs. We recommend that the authors either delete or modify the statement with appropriate caveats.
There are several points for consideration to refine the methodology used in this manuscript: In the method section, the authors describe that the analysis is limited to every day cigarette smokers. The authors described "all the analyses were weighted, based on weighting factors for Wave 1". In PATH user guide (Section 5), there are various types of weights. It is not clear whether the cross-sectional analysis (Q1) was conducted separately using cross-sectional weights of each wave to ensure the representativeness of the results. Longitudinal analysis should be conducted using longitudinal weights. In this case, wave 3 weights should be applied to answer research questions 2 and 3. The authors must clearly specify which weight was used for each analysis (Q1-Q3). 1.
The data is limited to 'current everyday cigarette smokers at each Wave with data available on CC'. As reported by Borland et. al. (2019)[ref-3] and Smith et al. (2021)[ref-1] cigarette consumption differs significantly between every day and some day cigarette smokers and different segment of dual users. To obtain a complete picture of the current cigarette smoker population, the authors should consider including some day smokers in the analysis. This group more likely represents a larger proportion of dual users and provides a more comprehensive view of the cigarette consumption data for dual users. We note that indeed, there are cigarette consumption data in PATH for some day smokers. 2.
To answer Q3, the cigarette consumption was "compared in those who did or did not become dual users". However, since Q3 is asking "is baseline consumption related to later initiation of e-cigarettes". A logistic regression model with e-cigarette initiation as the outcome measure and cigarette consumption being the covariate would be more appropriate to answer Q3.

3.
Based on the current analysis description for Q3, the analysis will compare exclusive cigarette smokers who did or did not become dual users. A clearer description of 'dual user' needs to be given as it is shown in Table 3 there are three types of 'Definition of Use'. Does the heading 'Became users' in the 'Ever Established' row mean exclusive daily smokers who became ever established users of e-cigarette? Please clarify.

4.
The authors should clearly describe if R survey package is used in the analysis. While the R-program is appropriate to conduct statistical analysis, R survey package allows the researcher to utilize the full-sample weight, variance estimation method, BRR-Fay replicate weights, and that Fay's factor are correctly specified (See PATH User Guide, Appendix B for example R program code). The authors must specify whether replicate weights and Fay's correction factor were used in current analyses.

5.
Authors state that "nine predictor variables [were] selected, using a forward stepwise approach, including variables significant at p<0.05". It is not clear what variables were considered and the rationale for selection of the variables... The age range category "55+ years" for the variable 'age range when first started smoking cigarettes every day' should not be included as the data analysis is limited to 18 to 54 years.

6.
Authors only included respondents "aged 18 to 54 years at Wave 1 (as e-cigarette use proved to be very uncommon in those aged 55+ years". A quick analysis revealed that 7.

4.
by excluding individuals aged 55 or older, around 14% of the sample size is excluded among both current established and former established e-cigarette users at Wave 1. This phrase "(as e-cigarette use proved to be very uncommon in those aged 55+ years)" should be deleted since the data does not appear to support the statement. In the result section, the table captions should include more detail descriptions and definitions. For all result tables, the phrase 'among every day smokers' should be added if the analysis is only conducted among every day smokers. Does the table footnote 'NS' mean 'not significant'? If yes, the corresponding footnote should be 'p>0.05' instead of 'p<=0.05'. The 'dual use' term becomes very confusing when it is corresponding to three meanings (i.e., current establish e-cigarette use, ever established e-cigarette use and current every day e-cigarette use). The authors should be more precise. To answer Q3, the cigarette consumption was "compared in those who did or did not become dual users". However, since Q3 is asking "is baseline consumption related to later initiation of e-cigarettes". A logistic regression model with e-cigarette initiation as the outcome measure and cigarette consumption being the covariate would be more appropriate to answer Q3.

○
In response to this point, we ran analyses equivalent to those used to answer Q3, but using weighted logistic regression as suggested by the reviewers rather than weighted linear regression as we had done. The unadjusted results were identical, and the adjusted results gave such similar results that it seems unnecessary to revise our results. Based on the current analysis description for Q3, the analysis will compare exclusive cigarette smokers who did or did not become dual users. A clearer description of 'dual user' needs to be given as it is shown in Table 3  We have changed this sentence to read "Analyses were carried out with no adjustment for other variables and with adjustment for those of the nine predictor variables described above which were selected using a forward stepwise approach to include variables significant at p<0.05." The age range category "55+ years" for the variable 'age range when first started smoking cigarettes every day' should not be included as the data analysis is limited to 18 to 54 years.

○
In fact the analyses included those aged 18 to 64 years, as we now make clear in the revised version of the paper. Authors only included respondents "aged 18 to 54 years at Wave 1 (as e-cigarette use proved to be very uncommon in those aged 55+ years". A quick analysis revealed that by excluding individuals aged 55 or older, around 14% of the sample size is excluded among both current established and former established e-cigarette users at Wave 1. This phrase "(as e-cigarette use proved to be very uncommon in those aged 55+ years)" should be deleted since the data does not appear to support the statement.

○
We have amended the sentence for point 1 of paragraph 1 of the methods to read "Be aged 18 to 64 years at Wave 1, as preliminary analysis showed e-cigarette use to be rare at older ages. In the literature review section, some of the findings were drawn from studies with adolescent data. Five out of 13 studies (Table 6) referenced in the results include adolescent data. The authors should be consistent with the literature search criteria and either exclude studies on youth as that was considered out of scope for the review, modify their search criteria or provide a rationale regarding inclusion of only select publications with adolescent data. 1.

○
In the methods section, we have clarified the second reason for rejection as "Study only of adolescents, young adults (age 25 or under), or students". We did not want to exclude studies that included adolescents as well as adults.
Results related to Q3. Based on Andler et al. 2016, the authors state that 'heavier smokers were more likely to start vaping'. However, this does not accurately represent the results from the publication. Andler et al. 2016, state that "82 % of dual users reported that vaping had enabled them to reduce their cigarette consumption, with a mean reduction of 8.9 cigarettes per day. These individuals were initially heavy smokers, smoking 21 cigarettes per day on average (the mean overall among smokers was 11.3 in 2014." Just because the participants in the study were heavy smokers that does not establish causality. Furthermore, Andler et al. 2016, included adolescents (age 15+) in their study. The authors should consider providing more context around the statement on heavy smokers.

○
We have amended the statement "the results clearly suggested that heavier smokers were more likely to start vaping" to read "the results clearly suggested that vapers were more likely to be heavier smokers.
Competing Interests: No competing interests were disclosed.