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Association of e-cigarette and cigarette use with self-reported chronic obstructive pulmonary disease (COPD): a multivariable analysis of a large United States data set

Respiratory Research volume 26, Article number: 49 (2025) Cite this article

Abstract

Background

Prior research has linked e-cigarette use with chronic obstructive pulmonary disease (COPD). We examined the relationship between e-cigarette use and COPD prevalence in older adults with varying cigarette use status.

Methods

Data from the 2020 National Health Interview Survey were used to estimate the association between each of 9 exposure categories based on cigarette use (never, former, current) and e-cigarette use (never, former, current), with respondent-reported physician-diagnosed COPD prevalence in individuals 40 years and older (N = 22,997). Weighted multivariable analysis accounted for cigarette pack years, age of cigarette smoking onset, race, income-to-poverty ratio, rurality, gender, age, and medical comorbidities. Sensitivity of results was tested in 3 separate models with addition of years since quit cigarettes, smoking intensity and duration.

Results

39.7% of individuals reported ever smoking cigarettes and 10.2% reported ever using e-cigarettes. Among individuals with ever e-cigarette use, 88.5% also reported current or former cigarette smoking. The weighted prevalence of COPD was 7.2%; Among those who reported former cigarette smoking, the highest risk of COPD prevalence compared to never cigarette/never e-cigarette use was in those currently using e-cigarettes (adjusted risk ratio (ARR) 2.82, 95% confidence interval (CI) [1.5, 5.3]). The ARR for former cigarette/current e-cigarette use was significantly larger than the ARR for former cigarette/never e-cigarette use (p < 0.002) in 3 out of 4 models; however, one model had the ARR attenuated to 1.35 (0.67, 2.76) when years since quitting smoking was added to the model. Other cigarette/e-cigarette combinations were also sensitive to how cigarette smoking history was modeled. For example, ARR for former cigarette/former e-cigarette (1.68 [1.00, 2.80] and current cigarette/former e-cigarette (2.50 [1.56,4.02]) were reduced to 1.05 (0.62, 1.77) and 1.04 (0.62, 1.75) respectively, when cigarette smoking duration was substituted for pack-years.

Conclusions

Current e-cigarette use among former cigarette smokers was associated with significantly higher COPD prevalence compared to never e-cigarette use. However, COPD risk for most cigarette/e-cigarette combinations could be greatly attenuated by how cigarette smoking history was modeled, raising questions about the robustness of these associations in prior research and the possibility of reverse causality in prior cross-sectional research.

Introduction

Chronic obstructive pulmonary disease (COPD) is a progressive disease characterized by airflow obstruction and is a leading cause of mortality worldwide, accounting for at least 3 million deaths annually [1, 2]. Tobacco smoking is the major cause of COPD in high-income countries and accounts for up to 80% of COPD-related deaths in the United States (U.S.) [3, 4]. Thus, efforts directed toward smoking cessation are critically important for population health related to COPD.

Less than 10% of all adults who smoke in the U.S. successfully quit smoking cigarettes each year [5,6,7], and most adults that attempt to quit smoking try multiple different methods [8]. Electronic-cigarettes (e-cigarettes), which are devices that heat a liquid to produce an aerosol with nicotine and other chemicals, have been proposed as a new strategy for smoking cessation [8, 9]. Since becoming commercially available in the United States in 2007, e-cigarette use has grown rapidly among adolescents and adults [9, 10]. Although no e-cigarette products are currently approved by the U.S. Food and Drug Association for smoking cessation, some adults who smoke have used e-cigarettes for this purpose [8, 11].

Several studies have demonstrated that chemicals in e-cigarette aerosols cause harm to the respiratory tract [12,13,14,15,16,17]. In addition, multiple studies have suggested that e-cigarette use may be a risk factor for COPD [18,19,20,21,22,23,24,25]. Due to the rapid growth in popularity of e-cigarettes and their utilization in smoking cessation, further investigation into their health impacts in individuals with history of former cigarette use is critical [26]. It is currently unclear whether e-cigarette use represents differential risk for COPD prevalence among adults who have never smoked, formerly smoked, or currently smoke. This is particularly important to study given the rapid growth in popularity of e-cigarettes and their utilization as a smoking cessation aid. This study aimed to analyze the relationships between e-cigarette use, cigarette use, and COPD prevalence in a large national U.S. data set.

Methods

Study participants

Data from the 2020 National Center for Health Statistics, National Health Interview Survey (NHIS) [27], which utilizes probability sampling and clustering to obtain information in a nationally representative civilian population, were used for analysis. We selected adults aged 40 and over because in the U.S. COPD is most diagnosed in individuals over the age of 40 [1].

Outcome measure

The diagnosis of lifetime COPD was determined by the question “Have you EVER been told by a doctor or other health professional that you had chronic obstructive pulmonary disease, COPD, emphysema, or chronic bronchitis.” This study qualified as exempt per guidelines of the Westat Institutional Review Board and the Dartmouth Health Human Research Protection Program.

Tobacco use

The exposures of interest were lifetime use of cigarettes and/or e-cigarettes. For cigarettes, never use was defined as smoking < 100 lifetime cigarettes; former use was defined as smoking > 100 lifetime cigarettes but no use within the last 30 days; and current use was defined as smoking > 100 lifetime cigarettes and use within the last 30 days. For e-cigarettes, current use was defined by use of e-cigarettes in the last 30 days; former use was defined by ever use of e-cigarettes but not in the last 30 days; and never use was defined by responding “no” to a question about ever use of e-cigarettes. Nine mutually exclusive categories of cigarette and e-cigarette use were defined by discrete combinations of never use, former use, or current use of each product.

Smoking-related covariates

Cigarette smoking covariates among those who had ever smoked (former or current) included cigarette pack years and age of smoking onset [28, 29]. Age of smoking onset was determined by the question “How old were you when you FIRST started to smoke fairly regularly?”. For those with former cigarette use, cigarette pack years were determined by the duration of cigarette use (calculated from time since quit and age of smoking onset) and number of cigarettes per day (“What is the average number of cigarettes that you smoked daily during the longest period that you smoked?” and “when you last smoked FAIRLY REGULARLY, how many cigarettes did you usually smoke per day?”). To determine years since quitting, those with former cigarette use were asked, “How long has it been since you quit smoking cigarettes?” For those with current cigarette use, pack years were determined by the duration of cigarette use (calculated using current age and age of onset) and number of cigarettes smoked per day.

Sociodemographic covariates

Sociodemographic covariates associated with COPD [1, 30,31,32] included the following: gender (male or female); race (white, Black/African American or other race/multiple); age (40–49, 50–59, 60–69, 70–79, or 80+); geographic location (large central metro, large fringe metro, medium and small metro, or non-metropolitan); a comorbidity score (range 0–12) [33], and income-to-poverty ratio (IPR) [34]. For the IPR, total family income was divided by the poverty threshold; ratios < 1 indicates that the total family income is below the poverty threshold [34]. The comorbidity score included ever diagnosis (coded as no = 0 and yes = 1) of coronary heart disease, diabetes, stroke, hypertension, high cholesterol, obesity, angina, heart attack, cancer, arthritis, weak/failing kidneys, and cirrhosis/liver condition.

Statistical analysis

Weighted comparisons of means or proportions, as appropriate, were used to evaluate associations between categories of cigarette/e-cigarette use and COPD prevalence. Adjusted risk ratios (ARRs) of the discrete cigarette/e-cigarette use categories compared to never cigarette/never e-cigarette were estimated with a weighted multivariable Poisson regression, controlling for both sociodemographic and smoking-related covariates. Post-hoc contrast following multivariable regression determined whether the ARRs for e-cigarette use were significantly different from the ARRs for never e-cigarette use within each cigarette smoking category. All analyses were performed using Stata version 17.0.

Sensitivity analysis

Sensitivity models were conducted to explore how additional smoking history impacted results. In one sensitivity analysis, an additional weighted Poisson regression was conducted with years since quitting added in as an additional covariate. For this analysis, years since quitting was entered as a categorical variable coded as 0 (never smoking), 1 (current smoking), 2 (former smoking quit for 0–20 years), 3 (former smoking quit for 21–40 years), and 3 (former smoking quit for > 40 years).

In a second sensitivity analyses, we examined whether the inclusion of cigarette smoking intensity as a covariate would impact results. For this analysis, smoking intensity was entered as a categorical variable coded as 0 (never smoking), 1 (former smoking < 10 cigarettes/day), 2 (former smoking 10–20 cigarettes/day), 3 (former smoking > 20 cigarettes/day), 4 (current smoking < 10 cigarettes/day), 5 (currently smoking 10–20 cigarettes/day), and 6 (current smoking > 20 cigarettes/day) into the multivariable model.

Finally, in a third sensitivity analysis, we examined whether replacing cigarettes pack-years with smoking duration, or the number of years an individual used cigarettes, in the primary multivariable model would impact results given that some work has shown smoking duration to have a stronger association with COPD prevalence than cigarette pack-years [35].

Results

Sample description

Among adults aged 40 years and older (N = 22,997), the weighted prevalence of lifetime COPD was 7.2%, among whom mean age was 65.1 years (Table 1). Of those with a lifetime COPD diagnosis (N = 1,760), 42.6% were male, 83.3% were of white race, 26.5% lived in a non-metropolitan area, and the weighted mean of income to poverty ratio (IPR) was 2.9 (Table 1).

Table 1 Demographics of individuals in 2020 NHIS (aged 40 years and older; N = 22,997)
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Out of all adults, 10.2% reported ever using e-cigarettes and 88.5% of those who used e-cigarettes reported current or former smoking. In former and current cigarette users, the weighted mean pack years was 22.7, the weighted percent of adults who started smoking in childhood (< 15 years old) was 7.0%, and, among former smokers, the weighted mean years since smoking cessation was 22.3 years.

Among those with COPD, 75.4% reported ever cigarette use and 20.3% ever using e-cigarettes. Weighted lifetime COPD prevalence for nine cigarette/e-cigarette categories (shown in Table 2) were as follows: 2.6% never cigarette/never e-cigarette (n = 12,777); 0.6% never cigarette/former e-cigarette (n = 220); 11.7% never cigarette/current e-cigarette (n = 25); 11.0% former cigarette/never e-cigarette (n = 6,037); 13.8% former cigarette/former e-cigarette (n = 657); 15.6% former cigarette/current e-cigarette (n = 217); 15.9% current cigarette/never e-cigarette (n = 1,640); 22.1% current cigarette/former e-cigarette (n = 893); and 16.0% current cigarette/current e-cigarette (n = 121). Among adults who had ever smoked (current or former), the cigarette pack years was highest for former cigarette/current e-cigarette (32.6) and lowest for former cigarette/never e-cigarettes (19.4). The years since quit cigarettes was greatest in former smokers with no e-cigarette use (24.6 years) and lowest in those with former cigarette use/current e-cigarette use (7.3 years). Also shown in Table 2, among former smokers, the number of cigarettes smoked per day was highest in those with current e-cigarette use compared to those with never or former e-cigarette use, the percent with age of childhood onset cigarette use (< 15 years old) was highest in current cigarette/current e-cigarette use and lowest in former cigarette/never e-cigarette use. Finally, the mean comorbidity score was highest for former cigarette/never e-cigarette and lowest for never cigarette/current e-cigarette (Table 2).

Table 2 Cigarette and E-Cigarette Status, Tobacco Associated Variables, and Lifetime COPD Diagnosis in Adults 40 Years and Older1
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Multivariable analyses

Compared to the reference category of never cigarette/never e-cigarette use, the following categories were all associated with higher risk of COPD prevalence: never cigarette/current e-cigarette ARR = 9.16, CI [1.84, 45.73]), former cigarette/former e-cigarette ARR = 1.68, 95% Confidence Interval (CI) [1.00, 2.80]; former cigarettes/current e-cigarette ARR = 2.82, CI [1.50, 5.30]; current cigarette/never e-cigarette ARR = 2.46, CI [1.54, 3.95]; current cigarettes/former e-cigarette ARR = 2.50, CI [1.56, 4.02] (Table 3). The weighted ARR for COPD of the other variables included in these models are shown in Supplementary Table 1.

Table 3 Risk of COPD based on cigarette and E-Cigarette use Status
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Post-hoc contrasts revealed that the ARR for COPD diagnosis for former cigarette/current e-cigarette was significantly larger than the ARR for former cigarette/never e-cigarette use (p < 0.002). Post-hoc contrasts also showed no significant differences in the ARR for COPD diagnosis for different categories of e-cigarette use among those who currently smoked cigarettes (p values all > 0.05).

Sensitivity analyses

Results from all three sensitivity analyses are shown in Supplemental Table 2: Model B included years since quit smoking as an additional variable, Model C included smoking intensity as an additional variable, and Model D substituted smoking duration for cigarette pack years. Adding additional smoking covariates changed the size and significance of many of the cigarette/e-cigarette combinations (Table 4). When years since quitting was added, the ARRs for former cigarette/former e-cigarette and former cigarette/current e-cigarette were greatly attenuated and became nonsignificant. When smoking intensity was added, ARRs for current cigarette/never e-cigarette and current cigarette/former e-cigarette were greatly attenuated and became nonsignificant. The most profound effect on e-cigarette associations occurred when cigarette pack-years was replaced with smoking duration (total years of cigarette use), ARRs for former cigarette/former e-cigarette, current cigarette/never e-cigarette and current cigarette/former e-cigarette were greatly attenuated and became nonsignificant; this was especially true for estimates of risk associated with former e-cigarette use. In all three sensitivity analyses, the post hoc comparison showing higher risk for former cigarette/current e-cigarette users compared to former cigarette/never users remained statistically significant.

Table 4 Risk of Chronic Obstructive Pulmonary Disease based on cigarette and E-Cigarette use Status in three separate sensitivity Analyses1
Full size table

Discussion

In a nationally representative U.S. sample of adults aged 40 + years, we found that e-cigarette use was associated with a higher risk of COPD compared to those with no cigarette use, even after accounting for sociodemographic factors, medical comorbidities, lifetime smoking pack year exposure, and age of smoking onset. Much of the added risk in the categories seemed to be driven by cigarette use, but the ARR for COPD diagnosis for former cigarette/current e-cigarette was significantly larger than the ARR for former cigarette/never e-cigarette use. Finally, a large, significant association was found for a very small sample of never cigarette smokers who use e-cigarettes, an association we consider very preliminary and subject to verification in larger samples of older adults.

The sensitivity analysis demonstrated that some of the observed associations between products and COPD were dependent on how past cigarette smoking was modeled. Further adjustments not only had implications for the statistical significance of the results but also attenuated estimates for the associations. Adjusting for current cigarette smoking intensity (average number of cigarettes per day) attenuated the association for the current cigarette/never e-cigarette category. Substituting smoking duration for cigarette pack years attenuated the association between cigarette use and COPD for the current cigarette/never e-cigarette category, as was found in a previous study [35] which emphasized that cigarette smoking duration was the most important risk factor for COPD. Among two categories with current e-cigarette use (never cigarette/current e-cigarette and former cigarettes/current e-cigarette) the risk ratios mostly remain significant across all models although the risk ratios attenuate in models with alternative smoking history variables. Our findings raise an important question about many previous studies that have reported e-cigarette associations. These results from previous studies are summarized in a recent metanalysis; the pooled adjusted odds ratio for COPD comparing e-cigarette use to no use was 1.46 (1.31–1.61) [36]. Our findings raise the question of how much this pooled estimate would be attenuated if the individual studies had included key variables describing smoking history in their multivariable models. Importantly, pooled estimates can be biased if the estimates from the individual studies included are biased. For example, a prospective study of PATH Study data waves 1–5 by Cook et al. 2023 [37] found that e-cigarette use was not associated with increased incidence of COPD after controlling for cigarette pack years and cigarette use status. This difference highlights the importance of adequately controlling for cigarette associated variables, which we do in our study’s models.

E-cigarette aerosols contain chemicals that are known to be harmful to the respiratory tract. These include toxic metals (nickel, tin, lead), humectants (propylene glycol, glycerin) and their thermal degradation products (aldehydes) [16, 17, 38]. In vivo and in vitro studies have shown short-term adverse pulmonary effects such as oxidative stress, inflammatory changes, impaired endothelial function, and reduction in mucous clearance [12, 14, 16, 17]. Although the long-term respiratory complications of e-cigarettes is not known, these short-term impacts raise concern that chronic e-cigarette use may convey risk for chronic pulmonary disease.

It is unclear if the relationship between e-cigarettes and COPD prevalence identified in this study is due to an inherent characteristic of e-cigarettes (known chemical exposures as described), if there is residual confounding of cigarette exposure not captured in the tobacco associated variables (such as secondhand smoke or smoking behavior that is underreported), or if e-cigarette use itself is driven by quit attempts due to respiratory symptoms. COPD is a disease that develops over decades and the e-cigarette market is less than 20 years old [1, 38]. Our results suggest that those who have successfully quit cigarettes and turned to e-cigarettes tend to be those who may be the most resistant to quitting (e.g. higher pack years, less time since quit cigarette, and higher cigarettes per day when smoking). Thus, the association between e-cigarette use and COPD among people who formerly smoked cigarettes may tell us more about additional circumstances and risk factors they experience than truly about risk from e-cigarettes. Confounding unmeasured variables may include respondents’ living environment, exposures, behavior patterns, or social factors. This includes the possibility that a new diagnosis of COPD may increase e-cigarette use as people attempt to quit smoking. As a cross-sectional study, the direction of effects and causality cannot be discerned. In this analysis, the ARR for individuals with current dual use of cigarettes and e-cigarettes was lower than those with former cigarette/current e-cigarette use. However, the confidence intervals for risk of COPD prevalence for dual use overlapped with the category of former cigarette/current e-cigarette. In subsequent sensitivity analyses, the ARR for former cigarette/current e-cigarette is higher than the ARR for current cigarette/current e-cigarette when adjusting for smoking duration and smoking intensity, but not for years since quit. This highlights the possibility that those that have a new diagnosis of COPD or a high burden of medical comorbidities may be more likely to transition exclusively to e-cigarettes.

This study has strengths. First, it is an analysis of a representative population in which COPD would manifest (age 40 years and older) from a large national data set. Second, this analysis controlled for multiple variables that describe smoking history and variables that are known to be associated with increased risk for COPD such as cigarette pack years and age of smoking onset [26]. Third, in addition to controlling for socioeconomic, demographic, and cigarette-associated factors, this analysis controlled for common medical co-morbidities to ensure those with e-cigarette use did not have an overall worse health status compared to their counterparts. Fourth, our findings reflect several ways of capturing an individual’s cigarette smoking history, something that to our knowledge has not been done to date.

There are limitations to this study. First, the NHIS relies on patient reported physician-diagnosed COPD rather than spirometry. This raises concern that the number of individuals with COPD may be misreported and thus misrepresented. The 2020 Behavioral Risk Factor Surveillance System (BRFSS) found that 5.6% of individuals reported physician diagnosed COPD, which is slightly lower than the percentage identified in the 2020 NHIS [39]. However, it is known that COPD is both commonly underdiagnosed and misdiagnosed thus spirometry diagnosis in a large analysis may not accurately represent population disease burden [40]. Second, the NHIS is unable to distinguish nuanced patterns of e-cigarette use between individuals. This includes, but is not limited to, considerations for frequency of use during the day, number of cartridges used per week, type of e-cigarette product used, and the content of each e-cigarette solution. Part of this difficulty lies in the wide range of e-cigarette products and variable e-cigarette solutions that exist in the market [38]. The NHIS does not ask about what e-cigarette device(s) were/are used by participants and there are nuances in regards to nicotine delivery and exposure to respiratory toxicants between device types [38] and thus is limited in its ability to evaluate the net exposure to the user or of different e-cigarette devices and usage patterns. Indeed, this is a major limitation in current scientific understanding of e-cigarette use, with poorly defined estimates of usual exposure, or unclear comparisons between device types. Third, there is no measure of second-hand smoke exposure in the NHIS which limits information about a potential confounding exposure. Fourth, the NHIS does not include timing of COPD diagnosis nor timing of e-cigarette exposure initiation which limits the ability to determine causality. Our findings may raise concern of potential reverse causality. First, there is the potential that sicker patients may switch products due to symptoms that make it difficult to inhale cigarettes. This analysis attempted to control for this with a comorbidity score to account for individual burden of illness, however there may be variables that contribute to overall burden of disease not captured in this score. Further, although former cigarette/current e-cigarette use was associated with higher risk of COPD compared to their counterparts with no e-cigarette exposure, this group had the least number of years since quit cigarettes compared to these counterparts who quit decades prior. This might reflect a higher proportion of individuals with an established COPD diagnosis that may have transitioned from cigarettes to e-cigarettes in an attempt to quit smoking with the perception that these products are less harmful. The importance of timing of exposure is demonstrated by Rodu and Plurphanswat, who in 2022 analyzed PATH Study Wave 1 data that included age of disease diagnosis and initiation of nicotine products to assess the reliability of cross-sectional studies regarding e-cigarette use and COPD [41]. They found that nearly all cases of COPD and emphysema were diagnosed after cigarette initiation and rarely after e-cigarette initiation [41]. The interpretation of the ARR for COPD in never cigarette users with current or former e-cigarette use in our analysis is substantially limited because of small sample sizes and N = 2 for COPD diagnosis in each group. This is likely a reflection of the novelty of the e-cigarette market and the fact that COPD develops over decades. Given the fact that most people who use e-cigarettes are adolescents and young adults, the implications of exclusive e-cigarette use on COPD risk will likely become more obvious over time [42, 43]. Finally, there is no standardized definition of e-cigarette use comparable to cigarette “pack years” in a way that would quantify overall chemical exposure and the NHIS 2020 did not include questions regarding e-cigarette frequency or intensity. Thus, there may be a way in which adults who formerly smoked and who use e-cigarette products are utilizing them in a way that conveys higher risk for COPD that cannot be fully captured.

This analysis highlights the need for further investigation into the safety of e-cigarettes even when used as a tool for smoking cessation. It also highlights the need for standardization of e-cigarette products and definitions of patterns of use in order to gain further insight into their impact on chronic lung disease and population health. Finally, investigators who study the association between e-cigarettes and COPD should test the robustness of their findings against additional multivariable models that capture cigarette smoking intensity, age of onset of cigarette smoking, years since quitting smoking, and smoking duration.

Conclusions

Current e-cigarette use in respondents reporting former cigarette smoking was associated with a higher risk of COPD prevalence compared to never e-cigarette use in the same population even after accounting for sociodemographic variables, medical comorbidities, and important smoking variables including cigarette pack years, cigarette smoking age of onset, and time since quit for cigarettes. These findings depended in part on how cigarette smoking history was modeled. This finding raises questions about previous studies that reported association but included only current or former cigarette smoking status as covariates. Future longitudinal studies could provide more robust insights into these associations, better controlling for confounders, and establishing clearer causal relationships. As such, more longitudinal investigation into the long-term health effects of e-cigarette products is needed, and randomized trials may be necessary to advise individuals about respiratory risks associated with e-cigarettes as a means for smoking cessation.

Data availability

All data generated or analyzed during this study are publicly available through the National Health Interview Survey (https://www.cdc.gov/nchs/nhis/documentation/?CDC_AAref_Val=https://www.cdc.gov/nchs/nhis/data-questionnaires-documentation.htm).

Abbreviations

COPD:

Chronic obstructive pulmonary disease

NHIS:

National health interview survey

BRFSS:

Behavioral risk factor surveillance system

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Funding

National Institutes of Health Grant R21HL161758. Dr. Paulin received support from the National Institute of General Medical Sciences of the National Institutes of Health under Award Number P20GM148278.

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Authors and Affiliations

  1. Department of Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA

    Alicia J. Burns & Laura M. Paulin

  2. Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA

    Alexander W. Steinberg

  3. Departments of Pediatrics and Biomedical Data Sciences, Geisel School of Medicine, Hanover, NH, USA

    James D. Sargent

  4. Behavioral Health & Health Policy, Westat, Rockville, MD, USA

    Jenny E. Ozga, Zhiqun Tang & Cassandra A. Stanton

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Contributions

Conception and design: J. D. S., L. M. P., C. A. S.; Data analysis: J. E. O., Z. T.; Data interpretation: all authors; Initial manuscript draft: A. J. B.; Manuscript editing and final approval: all authors.

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Correspondence to Alicia J. Burns.

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Burns, A.J., Steinberg, A.W., Sargent, J.D. et al. Association of e-cigarette and cigarette use with self-reported chronic obstructive pulmonary disease (COPD): a multivariable analysis of a large United States data set. Respir Res 26, 49 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12931-024-03087-4

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Keywords

Respiratory Research

ISSN: 1465-993X

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