Vaping nicotine is associated with increased medically-attended COVID-19 in women of reproductive age in an integrated health system

Introduction

Vapes are electronic devices that heat liquids typically containing either nicotine or tetrahydrocannabinol (THC), which is the psychoactive component of cannabis, along with other flavorings, additives, and compounds (1,2). It is becoming more common for younger adults to vape nicotine and/or cannabis, even though the original intended use for vaping was to help reduce chronic tobacco cigarette smoking in adults (3-5). It is a well-known phenomenon that vaping THC, particularly with vitamin E acetate as an additive, can lead to e-cigarette, or vaping, product use associated lung injury (EVALI), an acute lung injury syndrome that presents clinically similar to coronavirus disease 2019 (COVID-19) (6). Around the same time period during EVALI outbreaks, in early 2020, the first documented cases of COVID-19 were seen in the US (7,8).

The relationship between vaping of cannabis and/or nicotine and the risk of medically-attended COVID-19 episodes remains unclear. While some studies have reported a positive association between e-cigarette use and COVID-19 (9,10), recent research on human bronchial epithelial tissue exposed to e-cigarette chemicals suggests that certain compounds may offer protective effects against COVID-19 (11), and some studies have found no association between nicotine vaping and risk of COVID-19 (12). A 2024 meta-analysis found inconclusive evidence linking e-cigarette use to severe COVID-19 outcomes (8). To our knowledge, no prior studies have examined the relation of cannabis vaping and COVID-19, but initial studies on cannabis use (regardless of mode of administration) and risk of getting COVID-19 and disease severity have mixed results (13-16).

Prior studies have been mostly limited to self-reported survey data on vaping and COVID-19 that may not accurately reflect true COVID-19 prevalence. This study aimed to address this gap in the literature by analyzing data from a large sample of pregnant patients universally screened for nicotine and cannabis vaping during the year before pregnancy during standard prenatal care in Kaiser Permanente Northern California (KPNC). We investigated whether nicotine and/or cannabis vaping during the year before pregnancy was associated with an increased prevalence of medically-attended COVID-19 during the year before pregnancy. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-580/rc).

Methods

Setting

KPNC is an integrated healthcare delivery system with a membership of approximately 4.6 million patients who are similar to the insured Northern California population (17). KPNC has universal screening for substance use in the year before pregnancy via a self-report prenatal screening questionnaire (PSQ), which is administered at entrance to prenatal care. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This was a data only study and ethical approval was waived by the ethics committee. Informed consent was waived in this retrospective study.

Study design & sample

We implemented a retrospective cross-sectional study. Patients were included in the cohort based on the following criteria: (I) pregnancy onset between September 1, 2021, and March 31, 2023; (II) one or more KPNC prenatal visits; (III) KPNC membership for at least 9 months in the year before pregnancy; (IV) a non-missing response to the question about cannabis and tobacco use during the year before pregnancy, and; (V) a non-missing response to the question about modes of cannabis use among those who endorsed using during the year before pregnancy. Index date was defined as the onset of the first pregnancy during the study period and index period was defined as 1-year prior to pregnancy onset. For those with more than one pregnancy during the study period, we only included the first pregnancy. All variables, including exposure (vaping status), outcome (medically-attended COVID-19 episode), and covariates were obtained during the index period. The only exception was prior medically-attended COVID-19 episodes, which were identified during the 6-month prior to the beginning of the index period.

Exposures

Vaping during the year before pregnancy was established using responses to substance-use questions from the PSQ. Women were asked to indicate whether they used cannabis during the year before pregnancy, and those who endorsed cannabis use were asked to indicate their modes of cannabis administration (e.g., vaped, smoked, edible/oral, dabbed, lotion/ointment). Women were also asked to indicate whether they vaped nicotine during the year before pregnancy. Using these responses, we created non-mutually exclusive vaping exposure groups of vaped nicotine (yes/no) and vaped cannabis (yes/no), and one mutually exclusive vaping exposure group: vaped nicotine only, vaped cannabis only, vaped both nicotine and cannabis, and vaped neither.

Outcome—medically-attended COVID-19 episode

A medically-attended COVID-19 episode was defined as having at least one ICD 10 diagnosis indicative of COVID-19 in the electronic health record (EHR) (Table S1) or at least one positive antigen or nucleic acid amplification test (NAAT) laboratory test result in the 6 months prior to index date.

Covariates

Covariates included age at the time of pregnancy onset, self-reported race/ethnicity [Asian/Native Hawaiian/Other Pacific Islander (ANOPI), Black, Hispanic, White, multiracial/unknown], Elixhauser comorbidity score (18), and neighborhood deprivation index (NDI) (19), a validated census-based socioeconomic status measure, were obtained from the KPNC Virtual Data Warehouse (VDW) (20). Parity and body mass index (BMI) were obtained from the KPNC Perinatal Research Unit Obstetrics Database (POD). Cannabis smoking during the year before pregnancy was obtained from the PSQ. Tobacco smoking status is routinely assessed and documented during KPNC primary and specialty care visits. Five-year history of tobacco smoking status was defined as any documented record of current or former tobacco smoking in the EHR during the 5 years before pregnancy or self-report of tobacco smoking during the year before pregnancy on the PSQ.

COVID vaccination records during the index period were obtained from the KPNC VDW. The KPNC VDW sources COVID vaccination data from the EHR for vaccine administrations at KPNC, and from claims data, the state immunization registry, and self-reports for vaccine administrations outside of KPNC.

The time of the first valid COVID vaccination a patient received was classified into quartiles (Q1, Q2, Q3, Q4). We also collected prior medically-attended COVID-19 episodes within 6 months prior to the start of the index period, using the same definition as the medically-attended COVID-19 episode.

Statistical analyses

Differences in socio-demographic characteristics were examined across the non-mutually exclusive vaping groups and the four-level mutually exclusive groups using chi-square tests for categorical variables, and two-sample t-tests or analysis of variance (ANOVA) for continuous variables, depending on levels of exposure.

We used Targeted Maximum Likelihood Estimation (TMLE) (21) to examine whether vaping was associated with medically-attended COVID-19 episodes. We computed point estimates for prevalence ratios (PR) and the associated 95% confidence intervals (CIs). TMLE is a general framework for constructing efficient, multiply-robust, asymptotically linear estimators for a given target parameter (21). In our case, the target parameter was the probability of a medically-attended COVID-19 episode, adjusted for covariates, under the presence/absence of different exposure levels for all participants in our target population.

Unless otherwise specified, all models used in TMLE were adjusted for continuous covariates (age at pregnancy onset, pre-pregnancy BMI, NDI, Elixhauser comorbidity score, parity) and categorical covariates (race/ethnicity, 5-year history of tobacco smoking status, cannabis smoking during the index period, medically-attended COVID-19 episodes that occurred up to 6 months prior to the index date, and the quarter in which a patient received a COVID vaccination, if at all, during the index period). Race/ethnicity and quarter in which a patient received a COVID vaccination were coded as multi-level factors that were then transformed into dummy variables for modeling.

For non-mutually exclusive models in which the exposure of interest was vaping cannabis, we additionally adjusted for vaping nicotine and for models in which the exposure of interest was vaping nicotine, we additionally adjusted for vaping cannabis. For the non-mutually exclusive exposure groups, we contrasted the presence/absence of vaping nicotine (adjusting additionally for cannabis vaping), vaping cannabis (adjusting additionally for nicotine vaping), and vaping nicotine or cannabis. For the mutually exclusive exposures, we contrasted (I) vaping nicotine only; (II) vaping cannabis only; and (III) vaping both to the reference group of vaping neither.

For these target parameters, TMLE uses the factorization of the observed data distribution into an outcome regression E[Y|A,W] for a given outcome Y, exposure A, and covariates W, and a propensity score P[A|W]. Initial estimates from the outcome regression are updated by a fluctuation parameter that is a function of the propensity score. If either the outcome regression or propensity score are estimated consistently, the TMLE will be consistent, and if both are estimated consistently at appropriate convergence rates, the TMLE will be asymptotically efficient, achieving the lowest possible variance among a large class of estimators (21). Further, TMLE enables the leveraging of machine learning algorithms (in our case, the ensemble method Super Learner) in the estimation of the outcome regression and propensity score while still maintaining valid statistical inference (22). Super Learner uses cross-validation to create the optimal weighted combination of a library of pre-defined candidate machine learning algorithms (and/or traditional statistical models). Our Super Learner ensemble included generalized linear models, extreme gradient boosted decision trees, multivariate adaptive regression splines, elastic net regressions (e.g., ridge and least absolute shrinkage and selection operator), and a simple mean.

Statistical software

All data extractions and analyses used SAS 9.4 or R version 4.3.1. Specifically, data extractions used the tidyverse, dbplyr, and dorplyr (a proprietary package created for use at the KPNC Division of Research). Analyses were performed using lmtp, ltmle, and SuperLearner packages.

Results

Baseline characteristics of the overall cohort

The sample of 71,508 reproductive-aged women who met the study eligibility criteria (Figure 1) had a mean [standard deviation (SD)] aged of 31.7 (5.2) years, 27.7% were ANOPI, 5.9% were Black, 29.3% were Hispanic, 32.4% were White, and 4.7% were of Multiracial/Unknown race. The mean (SD) Elixhauser score was 0.5 (SD 1.0), indicating an overall healthy population (Table 1).

Figure 1 Consort diagram of inclusion and exclusion criteria. KPNC, Kaiser Permanente Northern California; PSQ, prenatal screening questionnaire.

Baseline characteristics—non-mutually exclusive exposure groups

Overall, 4.9% (n=3,505) reported vaping cannabis and 3.3% (n=2,347) reported vaping nicotine (Table 1). Those who vaped cannabis vs. did not vape cannabis were younger, more likely to be white, currently smoke tobacco, have a 5-year history of tobacco smoking, and nulliparous, and less likely to be ANOPI or receive a COVID-19 vaccination during the index period. Those who vaped nicotine vs. did not vape nicotine were younger, more likely to be white, have a 1- and 5-year history of tobacco smoking, nulliparous, and have no vaccination for COVID-19 during the index period. They were less likely to be ANOPI. When comparing those who vaped nicotine to those who vaped cannabis, those who vaped nicotine were younger, with greater neighborhood deprivation, and were more likely to have a history of tobacco smoking (Table 1).

Baseline characteristics—mutually exclusive exposure groups

When classifying vaping into four mutually exclusive categories, 4.1% (n=2,926) reported vaping cannabis only, 2.5% (n=1,768) vaping nicotine only, and 0.8% (n=579) vaping both (Table 2). Women who vaped both were notably younger, had slightly higher Elixhauser comorbidity score, and were more likely to use tobacco. Compared to the vaping neither group, ANOPI were less likely to vape overall; however, they were more likely to vape nicotine only (18.9%), as opposed to cannabis (14.3%) or both (13.0%). In contrast, there were higher proportions of Black, White, and Hispanic reported vaping cannabis or nicotine with White and Black most likely to vape nicotine only (White 40.7%, Black 8.9%), while Hispanic most likely to vape cannabis only (35.1%). Vaping nicotine only and vaping both group were equally likely to live in the most deprived neighborhood and had not vaccinated during the index period, compared to the other two groups.

Associations with medically-attended COVID-19 episode outcomes across vaping status

During the index period, 14.2% of the cohort had a medically-attended COVID-19 episode. The prevalence of having a medically-attended COVID-19 episode was higher among those who vaped vs. did not vape nicotine (16.9% vs. 14.1%) and among those who vaped nicotine only (17.0%) or nicotine and cannabis (16.8%) vs. neither (14.1%). In TMLE adjusted models, those who vaped nicotine (vs. did not vape nicotine) had a higher prevalence of a medically-attended COVID-19 episode [adjusted prevalence ratio (aPR) =1.33, 95% CI: 1.16–1.53]. Those who vaped nicotine only (aPR =1.32 95% CI: 1.14–1.52), or both nicotine and cannabis (aPR =1.40, 95% CI: 1.28–1.54) had a higher prevalence of medically attended COVID-19 episode than those who did not vape either substance. Vaping cannabis vs. not vaping cannabis, and vaping cannabis only vs. vaping neither cannabis or nicotine were not associated with a medically-attended COVID-19 episode (Table 3).

Discussion

Using data from a large healthcare system with universal screening for cannabis and nicotine vaping, our study found that 7.4% of pregnant individuals self-reported vaping nicotine and/or cannabis during the year before pregnancy. It has previously been shown in a self-reported cross-sectional survey of young adults in the United States that participants were more likely to report vaping cannabis if they were female and if they perceived that vaping is safer than smoking cigarettes (23). It is well known that smoking cigarettes before or during pregnancy results in increased adverse outcomes such as low fetal birth weight, perinatal morbidity and mortality, stillbirth, miscarriage, and negative infant behavioral patterns (24-26). However, in a recent systematic review of 5 large academic databases, out of 23 relevant studies examined there was insufficient evidence to draw any conclusions on the prevalence and effects of vaping in pregnant women and that vaping during pregnancy may have little to no effect on birthweight (27). On the contrary, it was recently shown that pregnant women vaping with mint/menthol flavors were more likely to experience fetal death (OR =3.27, 95% CI: 1.17–9.19) (28). In addition, there are multiple studies showing the overall deleterious effects of vaping nicotine and/or cannabis in women regardless of pregnancy including increased cardiac and lung inflammation, increased airway resistance, and respiratory conditions (1,29-31). In fact the biggest known risk factor for the deleterious acute lung injury associated with vaping inhaled vitamin E acetate, which caused an epidemic of nearly 3000 EVALI cases as of 2020 in the United States (32,33).

During a similar time period to the outbreak of EVALI, in early 2020, the COVID-19 pandemic hit the United States (34). As of December 2024, according to the World Health Organization (WHO), nearly 777 million individuals have been infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with over 7 million deaths worldwide (35). Further complicating things is the fact that both EVALI and SARS-COV-2 presented clinically and radiographically nearly identically (36,37). Therefore, appropriately defining whether individuals have a history of vaping nicotine and/or cannabis is imperative for accurate diagnosis and treatment. Our findings of increased medically-attended COVID-19 episode prevalence in young women who vaped nicotine are highly significant due to the severity of both immediate and long term morbidity and mortality associated with COVID-19, most recently including the increased association with long COVID-19 syndrome in particular (38,39).

Previous literature has been mixed on whether there is an increased association between vaping nicotine and/or cannabis and medically-attended COVID-19 episode (40-42). In a cross-sectional online survey of 2,791 United Kingdom adults in 2020, the authors concluded there was no association between a diagnosis of COVID-19 and vaping nicotine and/or cannabis (40). Two other large studies from the Mayo Clinic and Northern California whenevaluating adults who vaped, found no association between COVID-19 and vaping (12,43). In contrast, another study found that young adults who used e-cigarettes were five times more likely to be diagnosed with COVID-19 than non-users, suggesting the need for better education and screening about the potential harms of e-cigarette use and COVID-19 infection (10). Furthermore, a study of patients with COVID-19 found that those who vaped nicotine had more frequent COVID-19 related symptoms compared to matched control who did not vape nicotine (44). Potential mechanisms behind the association of vaping nicotine and increased COVID-19 infection have been hypothesized including the direct deleterious effects of vaping on the mucociliary epihelium, increased oxidative stress and inflammation, and immune system alterations Our findings of greater and increased prevalence of medically-attended COVID-associated with nicotine vaping add further insights to the literature that reproductive aged women should be counseled on the potentially deleterious effects that vaping has on lung inflammation especially as it relates to COVID-19 susceptibility.

Notably, vaping cannabis on its own during the year before pregnancy was not associated with medically-attended COVID-19. To our knowledge, no prior studies have examined the association between cannabis vaping and COVID-19. Prior research on vaping cannabis intensity and COVID-19 associations are lacking. Some studies have found an inverse association between cannabis use and COVID-19 risk (14,16), or COVID-19 mortality (15), while other studies have found an association with greater COVID-19-related complications and mortality (13,14). In general, more research is needed to better understand the relation between cannabis and/or nictotine vaping intensity and COVID-19 risk.

Strengths and limitations

Our study took place in a large, diverse, integrated healthcare delivery system with universal screening for preconception nicotine and cannabis vaping and little loss of short and long term follow up (45,46). However, our cross-sectional, observational study was limited to individuals seeking prenatal care in California and results may not be generalizable to other populations (e.g., elderly or male patients) and causal inferences cannot be made. Further, while initial case studies indicate an association between vaping and risk of pneumonia, pneumothorax and pneumomediastinum (47-49), we could not evaluate these lung or respiratory-related complications in our study due to the small number of outcomes in the sample. Further, our study was limited to medically-attended COVID-19 episodes using diagnosis and laboratory data from the EHR, which could underestimate the true prevalence of our outcome and bias results to the null. However, to our knowledge, this is the first and largest study to examine preconception cannabis and nicotine vaping status based on universal screening in relation to COVID-19, providing valuable insight to the field.

Conclusions

Our findings of the positive association between nicotine vaping and medically-attended COVID-19 episode among women during the year prior to their pregnancy adds to the growing evidence of negative health outcomes associated with vaping. Additional research is needed to determine whether there is a causal association between vaping and medically-attended COVID-19 among this population. Healthcare providers and community organizations can provide targeted patient educational outreach material on the association between vaping and medically-attended COVID-19 episode during regular women’s health wellness visits.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-580/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-580/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-580/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-580/coif). J.B.V. serves as an unpaid editorial board member of Journal of Thoracic Disease from September 2024 to August 2026. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This was a data only study and ethical approval was waived by the ethics committee. Informed consent was waived in this retrospective study.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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