Can you help me identify the research question? Do you agree with the statistical methods and conclusion? What are the advantages and disadvantages of the statistical analysis used in the study? Do you think are the limitations presented by the study population and sample size? Do you think there is additional research that would help in further analysis of this topic? Introduction E-cigarettes deliver an aerosol of nicotine by heating a liquid and are promoted as an alternative to combustible tobacco. This study determines the longitudinal associations between e-cigarette use and respiratory disease controlling for combustible tobacco use. Methods This was a longitudinal analysis of the adult Population Assessment of Tobacco and Health Waves 1, 2, and 3. Multivariable logistic regression was performed to determine the associations between e-cigarette use and respiratory disease, controlling for combustible tobacco smoking, demographic, and clinical variables. Data were collected in 2013-2016 and analyzed in 2018-2019. METHODS Data were collected in 2013-2016 and analyzed in 2018-2019. Study Population This study used the adult (aged 18 years) sample in PATH Waves 1 (September 2013 to December 2014), 2 (October 2014 to October 2015), and 3 (October 2015 to October 2016), a nationally representative, population-based, longitudinal study (Appendix Figure 1, available online). The weighted response rate at Wave 1 household screener was 54.0%; among screened households, the overall weighted response rate at Wave 1 adult interview was 74.0%. The weighted adult retention rates at Waves 2 and 3 were 83.2% and 78.4%, respectively. The University of California San Francisco Committee on Human Research ruled this study exempt. Statistical Analysis Logistic regression was used to quantify cross-sectional association between e-cigarette use (former and current) and respiratory disease at Wave 1, controlling for combustible tobacco smoking (former and current), age, BMI, sex, poverty level, race/ethnicity, and clinical variables. The reference condition was people who had never used e-cigarettes or smoked combusted tobacco products (cigarettes in the subsidiary analysis). Among respondents who did not report any respiratory disease at Wave 1, logistic regression was used to quantify the longitudinal association between e-cigarette use at Wave 1 and incident respiratory disease at either Wave 2 or Wave 3 combined, controlling for combustible tobacco smoking (former and current), age, BMI, sex, poverty level, race/ethnicity, and clinical variables at Wave 1. Waves 2 and 3 were combined to increase the number of events and the power of the study, essentially treating the study as a 2-year longitudinal follow up from baseline when e-cigarette use was assessed. A separate analysis was performed on the effect of e-cigarette use on respiratory disease after controlling for cigarette smoking only, demographic, and clinical variables. The PATH-provided different weights for the cross-sectional and follow up data sets were used as specified in the PATH Study user guide.26 Survey package, version 3.33-2 in R was used for statistical analyses accounting for the complex survey design. There are very little missing data in PATH. The number of dropped cases was only 1,028 (respiratory disease, n=127; e-cigarette users, n=42; any combustible tobacco smokers, n=774; conventional cigarette smokers, n=85), 5.3% of the sample. Given the very low level of missing data, list-wise deletion was used. Results Among people who did not report respiratory disease (chronic obstructive pulmonary disease, chronic bronchitis, emphysema, or asthma) at Wave 1, the longitudinal analysis revealed statistically significant associations between former e-cigarette use (AOR=1.31, 95% CI=1.07, 1.60) and current e-cigarette use (AOR=1.29, 95% CI=1.03, 1.61) at Wave 1 and having incident respiratory disease at Waves 2 or 3, controlling for combustible tobacco smoking, demographic, and clinical variables. Current combustible tobacco smoking (AOR=2.56, 95% CI=1.92, 3.41) was also significantly associated with having respiratory disease at Waves 2 or 3. Odds of developing respiratory disease for a current dual user (e-cigarette and all combustible tobacco) were 3.30 compared with a never smoker who never used e-cigarettes. Analysis controlling for cigarette smoking alone yielded similar results. Limitations Several respiratory conditions were combined to obtain enough events to achieve adequate power. For the same reason, this study did not distinguish between daily and nondaily product use and included both established (smoked >100 cigarettes) and experimenters in the former smoker group. There is a possibility of recall bias because use of e-cigarettes, conventional cigarettes, and other combustible tobacco products were self-reported as were clinical conditions. Participants with respiratory diseases might over-report e-cigarette, conventional cigarette, and other combustible tobacco use. There is also possibility of recall bias because doctor diagnoses of lung or respiratory diseases is reported by respondents rather than being based on actual hospital records but the questions. However, the question Has a doctor or other health professional ever told you that you had any of the following lung or respiratory conditions: COPD, chronic bronchitis, emphysema, and asthma? is used widely in epidemiologic studies, including other federal surveys such as the National Health Interview Survey. This question has been validated against direct clinical observation in at least 2 studies; one reported that 98% of patients had clinically or spirometrically validated among self-reported diagnosis of COPD31 and another found clinical validation in 83%, 84%, and 90% of nurses self-reporting diagnoses of COPD.32 Research to validate analogous questions about myocardial infarction also found high agreement (81%-98%) with medical records.33,34 The longitudinal follow-up was only 2 years, but COPD has been detected in people after 1-9 years of smoking.35 In addition, this study examined incident cases, which may have been developing for some time before symptoms were manifest. The similarity of the cross-sectional and longitudinal estimates supports this idea. As noted above, this study found p<0.001 for reverse causality, which could be consistent with a hypothesis that some individuals with respiratory disease try e-cigarettes believing they might be therapeutic. This study limited to control for intensity and type of e-cigarette use, which could affect the respiratory outcome. There is also always the possibility that other important confounders were not measured in the PATH study. CONCLUSIONS Current use of e-cigarettes appears to be an independent risk factor for respiratory disease in addition to all combustible tobacco smoking. Although switching from combustible tobacco, including cigarettes, to e-cigarettes theoretically could reduce the risk of developing respiratory disease, current evidence indicates a high prevalence of dual use, which is associated with increased risk beyond combustible tobacco use. In addition, for most smokers, using an e-cigarette is associated with lower odds of successfully quitting smoking.4,36 E-cigarettes should not be recommended