Do you agree with the statistical methods used and the conclusion? What do you think are the advantages and disadvantages of the type of statistical analysis used in this study? 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 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. Measures Lung or respiratory disease at Wave 1 was assessed with the question: Has a doctor or other health professional ever told you that you had any of the following lung or respiratory conditions? (yes or no): COPD, chronic bronchitis, emphysema, and asthma. Respondents who answered yes to any of these questions were coded as having lung or respiratory disease at Wave 1. Lung or respiratory disease at Waves 2 and 3 was assessed with the question: In the past 12 months, has a doctor, nurse, or other health professional told you that you had any of the following lung or respiratory conditions? (yes or no): COPD, chronic bronchitis, emphysema, and asthma. Respondents who answered yes to any of these questions were coded as having lung or respiratory disease at Wave 2 or 3. Respondents who ever used an e-cigarette, ever used fairly regularly, and currently used every day or some days were considered current users. Respondents who reported that they ever used e-cigarettes but do not currently use e-cigarettes were considered former users. Respondents who reported that they have never used e-cigarettes, even once or twice, were considered never users. Respondents who currently smoked cigarettes, traditional cigars, filtered cigars, cigarillos, pipe tobacco, or hookah every day or some days (regardless of whether they have smoked 100 cigarettes in their lifetime) were considered current combustible tobacco smokers. Respondents who ever smoked and currently do not smoke at all were classified as former smokers. Respondents who reported that they have never smoked, even 1 or 2 puffs, were classified as never smokers. The same definitions were used to define conventional cigarette smoking status. Demographic variables assessed at Wave 1 were age, BMI, sex (male or female), race/ethnicity (white, black, and other), and poverty level (below or above 100% of the poverty line). In Wave 1, respondents who answered yes to Has a doctor, nurse, or other health professional ever told you that you had high blood pressure? were coded as having high blood pressure. Respondents who answered yes to Has a doctor, nurse, or other health professional ever told you that you had high cholesterol? were coded as having high cholesterol. Respondents who answered yes to Has a doctor, nurse, or other health professional ever told you that you had diabetes, sugar diabetes, high blood sugar, or borderline diabetes? were coded as having diabetes mellitus. 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. 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