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Research Article: Observational Study

An association between electronic nicotine delivery systems use and a history of stroke using the 2016 behavioral risk factor surveillance system

Bricknell, Ryan A.T. MDa,∗; Ducaud, Christobal MDb; Figueroa, Alejandra MDc; Schwarzman, Logan S. MDa; Rodriguez, Pura MPHd; Castro, Grettel MPHd; Zevallos, Juan Carlos MDe; Barengo, Noël C. MD, PhD, MPHd,f,g

Editor(s): Khoshnood., Ardavan

Author Information
doi: 10.1097/MD.0000000000027180
  • Open


1 Introduction

Electronic nicotine delivery systems (ENDS) have grown in popularity as an alternative to the known harmful effects of traditional cigarettes (TC). ENDS are especially growing amongst teenagers, with one study finding that from 2011 to 2018 ENDS use had grown from 1.5% to 20.8% of teenagers.[1–4] Yet, little is known about long term health effects of ENDS, including effects on cerebrovascular disease. In 2018, there were 147,810 fatal strokes in the United States, and stroke was the fifth most common cause of death.[5] Per the American Heart Association 2021 Update on heart disease and stroke statistics, “the cardiovascular disease (CVD) risks associated with e-cigarette use are not known.”[5]

Several theoretical frameworks exist that could make ENDS a possible risk factor for stroke. First, TCs have been found to be major risk factor for stroke with many studies demonstrating a 2 to 4 times increased risk.[6–8] While considered by some studies to be less toxic than TCs, ENDS share some similarities to them including nicotine, inhalation at high temperatures, and some overlap in ingested chemicals.[9,10] Substances such as acrolein and formaldehyde, emitted in both TCs and ENDS, have been associated with cardiotoxicity in rodents ranging from bradycardia to cardiomyopathy.[11,12] Second, numerous studies have evaluated possible biochemical mechanisms which may link ENDS to CVD and neural disease.[13–15] For example, ENDS may have transient effects on increasing heart rate.[16] Its aerosol contents may cause reactive damage and inflammation or impair platelet function.[17,18] Albeit less than TCs, one study found ENDS to increase unfavorable markers of vascular function including oxidative stress and flow-mediated dilation.[18] Its use may impair glucose uptake in the ischemic brain.[19]

Some population based cross-sectional studies have looked into ENDS use and cardiovascular diseases. At least 2 studies have found an association between ENDS use and myocardial infarction.[20,21] However, the data for ENDS use and stroke are particularly limited with 1 study in young adults thus far not showing an overall association.[22] Thus, using a large US population-based survey, the objective of this study (Study) is to investigate if there is a statistical association between ENDS use and stroke history.

2 Methods

2.1 Study design and population

This cross-sectional study was a secondary data analysis using the 2016 Centers for Disease Control (CDC)'s behavioral risk factor surveillance system (BRFSS). The CDC conducts the BRFSS surveys annually in the general American population. Throughout 2016, CDC interviewers collected data through a series of randomized phone calls to landlines and cellular phones across all 50 states, Puerto Rico, District of Columbia, and the US Virgin Islands.[23] In a standardized script, interviewers asked interviewees a series of questions. Interviews took an average of 27 minutes.[23] The sampled population interviewed was designed and statistically weighted by the BRFSS to have similar baseline characteristics to the general American population. This Study's authors downloaded the publicly available data in 2018 from the BRFSS section within the CDCs website.

This study includes patients only if they answered all of the following questions from the 2016 BRFSS questionnaire.[24] For Question 6.3, participants were asked: “Were you ever told that you had a stroke?” Participants must have answered “yes” or “no.” For Question 10.1, they were asked, have you ever used an electronic cigarette product. For Question 10.2, they were also asked: “Do you now use electronic cigarette or other electronic ‘vaping’ products every day, some days, or not at all?” Participants must have answered “yes” or “no” to 10.1. If participants answered “yes” to 10.1, they must have answered “every day,” “some days,” or “not at all” to 10.2. Participants were excluded from the study if they answered “don’t know/not sure” or “refuse to answer” to any of the above questions regarding ENDS use or stroke. A participant was still included in the study if they answered appropriately to ENDS use and stroke but answered “don’t know/not sure” or “refuse to answer” to any of the 9 covariates: sex, age, race, body mass index (BMI), coronary artery disease (CAD), chronic kidney disease (CKD), diabetes mellitus (DM), smokeless tobacco use, and TC use. Missing data points from unanswered covariate data were excluded from this Study's multivariate analysis.

2.2 Criteria for assessing data

The main independent variable of this study was self-reported ENDS use, defined as electronic cigarettes and other electronic “vaping” products including electronic hookas, vape pens, e-cigars, and others. ENDS use was categorized as “current every-day use (EDU),” “nondaily or some-days use (SDU),” “former use (FU),” and “never use (NU).” FU was defined as having used ENDS in the past but not currently using. The dependent variable, and main outcome variable, is a self-reported history of stroke, reported as “yes” or “no.”

This study evaluated the 9 covariates (sex, age, race, BMI, CAD, CKD, DM, smokeless tobacco use, and TC use) as follows. Sex was defined as “male” or “female.” Age was categorized as “18–24,” “25–34,” “35–44,” “45–54,” “55–64,” and “65+.” Race was categorized as “non-Hispanic white” and “other,” which included African American, Asian American, Hispanic, or other. Self-reported BMI was categorized as “<25” or non-overweight, and “≥25” or overweight in accordance with CDC guidelines.[25] Self-reported diagnoses of CAD, CKD, and DM were categorized as “yes” or “no.” Smokeless tobacco was differentiated as “current use” versus “not current use.” “Current use” encompassed participants who answered “every day” and “some day” use. TC use was categorized into the following categories: “current-every day,” “some-days,” “former,” and “never.” “Former” TC use encompassed having smoked at least 100 cigarettes in one's life, but none currently. If <100 lifetime TCs were used, and not currently using, they were categorized as “never.”

This study analyzed the BRFSS data using STATA 3D.[26] Initially, a descriptive analysis was performed to assess baseline characteristics of ENDS use with covariates and stroke. Then, analysis of variance testing was used to obtain P-values across each category. Next, collinearity diagnostics were done to ensure that none of the independent variables or covariates were correlated with each other (r > 0.6 or r < –0.6). Finally, logistic regression analyses were performed to calculate unadjusted and adjusted odds ratios (AOR) and their corresponding 95% confidence intervals (CI).

2.3 Ethical considerations

This study used de-identified data and was classified by the Florida International University Internal Review Board as non-human subject research. The authors have no conflicts of interest to disclose. The research was performed without any funding.

3 Results

This study's population included 465,594 (95.7%) of the 2016 BRFSS survey of 486,303 participants. It excluded 20,709 (4.3%) participants due to missing data on history of stroke or ENDS usage. Within this study's population, 5010 (1.5%) participants reported EDU, 10,169 (3.0%) reported SDU, 58,834 (17.1%) reported FU, and 391,581 (78.4%) reported NU. 20,045 (3.2%) reported a history of stroke, and 445,549 (96.8%) denied a history of stroke.

Table 1 outlines the baseline characteristics of ENDS use in this study. Participants with stroke histories represented 3.5% of total EDU versus 3.3% of total SDU versus 2.8% of total FU versus 3.3% of total NU (P = .02). Demographically, EDU was more associated with male sex, non-Hispanic white race, and younger age compared with NU. Men accounted for 64.5% of EDU versus 46.5% of NU (P < .01). Eighteen to 24-year-olds accounted for 21.2% of EDU versus 9.6% of NU, while 65+ participants made up just 5.3% of EDU versus 24.1% of NU (P < .01). Non-Hispanic Whites represented 79.1% of EDU but only 63.0% of NU. Participants with EDU were less likely than with NU to suffer from comorbidities including BMI ≥ 25 kg/m2, CAD, and DM. BMI ≥ 25 was seen in 63.4% of EDU versus 66.1% of NU (P < .01). CAD accounted for 5.4% of EDU versus 7% of NU (P < .01). Likewise, DM was with 7.5% of EDU versus 11.9% of NU (P < .01). CKD, however, was recorded with 3.5% of EDU, 2.3% of SDU, 2.2% of FU, and 3.1% of NU (P < .01). Regarding tobacco, current daily TC use was seen with 18% of EDU versus 4.8% of NU (P < .01). Of note, the 55.9% of EDU was seen with former TC use. Currently smokeless tobacco use was seen in 6.4% of EDU versus 2.8% of NU (P < .01).

Table 1 - Baseline characteristics of 2016 BRFSS participants according to electronic nicotine delivery system use.
Electronic nicotine delivery system use
Characteristic Current every day Current some day Former Never P value
N % N % N % N %
Sex <.01
 Male 2778 64.5 5018 57.8 29014 55.6 164605 46.5
 Female 2229 35.5 5151 42.2 29815 44.4 226937 53.5
Race <.01
 Non-Hispanic White 4109 79.1 7658 68.2 44074 66.3 298948 63
 Othera 818 20.9 2357 31.8 13791 33.7 86135 37
Age, y <.01
 18–24 640 21.2 1681 28.3 7972 23.6 15029 9.6
 25–34 1030 28.3 1897 23.4 12373 27.5 30815 14.6
 35–44 873 17.9 1536 17.5 9235 17.2 40707 15.9
 45–54 900 15.9 1873 15 10281 14.7 60616 17.7
 55–64 953 11.5 2050 11.3 11259 11.3 88737 18.3
 65+ 614 5.3 1132 4.5 7714 5.8 155677 24.1
Body mass index, kg/m2 <.01
 >25 3113 63.4 5957 58.6 35341 60.9 245605 66.1
 <25 1710 36.6 3817 41.4 20733 39.1 119420 33.9
Kidney disease <.01
 Yes 177 3.5 342 2.3 1828 2.2 15306 3.1
 No 4812 96.5 9789 97.7 56833 97.8 375153 96.9
Coronary artery disease <.01
 Yes 416 5.4 872 5.4 4877 5.4 37152 7
 No 4561 94.6 9214 94.6 53529 94.6 351482 93
Diabetes <.01
 Yes 473 7.5 1019 7 5759 6.8 56145 11.9
 No 4528 92.5 9128 93 52978 93.2 334941 88.1
Traditional cigarette <.01
 Current every day 1031 18 4849 41.3 23533 34 19342 4.8
 Current some days 705 16.2 2158 20.9 7348 12.4 9331 2.8
 Former 2878 55.9 1612 15.2 13970 22.5 115336 24.5
 Never 375 9.8 1497 22.5 13698 31 245427 67.9
Smokeless tobacco <.01
 Yes 271 6.4 751 8.1 3646 6.3 10498 2.8
 No 4732 93.6 9400 91.9 55113 93.7 380506 97.2
aHispanic White, African American, Asian American, and other.
P value: performed by chi-squared test.

Table 2 shows the adjusted odds ratios (AOR) between the covariates and a history of stroke. Among demographic covariates, female sex was positively associated with a history of stroke versus men (AOR: 1.2, [95% CI: 1.1–1.3]). “Other” race was also positively associated versus non-Hispanic white (1.2, [1.1–1.3]). With age 25 to 34 chosen as the reference, age >65 was strongly associated with stroke (7.3, [5.7–9.3]). Among demographic covariates, BMI ≥ 25 was not significantly associated with stroke versus a normal BMI (0.98, [0.90–1.05]). However, reporting a history of CKD (2.1, [1.8–2.3]), CAD (4.3, [3.9–4.6]), and DM (1.8, [1.6–1.9]) were all associated with a stroke history. Within tobacco covariates, current every-day TC use (2.1, [1.9–2.4]), current someday TC use (1.8, [1.6–2.1]), and former TC use (1.3, [1.2–1.4]) were associated with stroke versus never TC use. In this sample, current smokeless tobacco use was not statistically associated with stroke versus non-current use (1.2, [0.997–1.5]).

Table 2 - Unadjusted and adjusted odds ratios between covariates and a history of stroke using the 2016 BRFSS survey.
History of stroke
Covariate Unadjusted Adjusted
OR (95% CI) P-value OR (95% CI) P-value
 Male Reference Reference
 Female 1.03 (0.97–1.09) .37 1.2 (1.1–1.3) <.01
 Non-Hispanic White Reference Reference
 Othera 0.8 (0.76–0.88) <.01 1.2 (1.1–1.3) <.01
 25–34 Reference Reference
 18–24 0.4 (0.2–0.7) .04 0.5 (0.3–0.95) .03
 35–44 1.9 (1.5–2.5) <.01 2.0 (1.5–2.6) <.01
 45–54 3.6 (2.9–4.5) <.01 3.2 (2.5–4.1) <.01
 55–64 6.0 (4.9–7.5) <.01 4.7 (3.7–6.0) <.01
 65+ 10.4 (8.4–12.8) <.01 7.3 (5.7–9.3) <.01
Body mass index, kg/m2
 <25 Reference Reference
 ≥25 1.3 (1.2–1.4) <.01 0.98 (0.90–1.05) .52
Kidney disease
 No Reference Reference
 Yes 5.1 (4.6–5.6) <.01 2.1 (1.8–2.3) <.01
Coronary artery disease
 No Reference Reference
 Yes 9.1 (8.5–9.7) <.01 4.3 (3.9–4.6) <.01
 No Reference Reference
 Yes 4.1 (3.8–4.3) <.01 1.8 (1.6–1.9) <.01
Traditional cigarette
 Never Reference Reference
 Current every day 2.4 (2.2–2.6) <.01 2.1 (1.9–2.4) <.01
 Current some days 1.8 (1.6–2.0) <.01 1.8 (1.6–2.1) <.01
 Former 2.2 (2.0–2.3) <.01 1.3 (1.2–1.4) <.01
Smokeless tobacco
 No Reference Reference
 Yes 1.07 (0.8–1.3) .49 1.2 (0.997–1.5) .053
aOther: Hispanic White, African American, Asian American, and other.

Table 3 demonstrates the primary endpoint, the association between ENDS use and stroke history. After adjusting for the 9 covariates above, EDU use was independently, positively associated with stroke versus NU (1.62, [1.18–2.31]). SDU use was also positively associated (1.28, [1.02–1.61]). FU was not significantly associated with stroke (AOR 1.09, [0.98–1.23]).

Table 3 - Unadjusted and adjusted odds ratios of electronic nicotine delivery system (ENDS) use and a history of stroke using the 2016 BRFSS survey.
ENDS use Unadjusted Adjusted
OR (95% CI) P-value OR (95% CI) P-value
Never Reference Reference
Current everyday 1.08 (0.80–1.47) .61 1.62 (1.18–2.31) .01
Current some days 1.02 (0.84–1.24) .84 1.28 (1.02–1.61) .03
Former 0.86 (0.79–0.94) <.01 1.09 (0.98–1.23) .11

4 Discussion

The data from this study revealed a positive association between ENDS use and a history of stroke. EDU and SDU were both associated with an increased likelihood compared with NU of reporting stroke. The association with EDU was greater than with SDU consistent with a dose dependent relationship.

Overall, this study's associations between covariates and stroke aligned relatively closely to those found in other large population-based studies with differences sometimes in the magnitude of the AORs. Female sex, old age, non-Caucasian race, DM, CKD, and TC use have all been accepted as risk factors for stroke.[5] This study's female sex association is very similar to the Framingham study which noted a 1 in 5 lifelong risk of stroke for women versus 1 in 6 for men.[27] For race, this study echoes other studies with non-Caucasian race as a risk factor.[28–30] However, this study's strength of association was less than in the REGARDS cohort, which compared stroke to black versus white ethnicity.[28] This study found that diabetes nearly doubled the risk of reporting stroke, similar to a prior study consisting of 775,385 people.[31] Most studies showed that reduced glomerular filtration rate was associated with an increased odds of reporting stroke, however this study's associations were stronger than in some other studies.[32–34] A meta analysis with 280,000 pooled patients found a lower risk ratio.[32] This study did not account for hypertension which may overestimate this AOR compared with the other studies which were able to account for it. Finally, this study found daily TC use to double the odds of reporting stroke, in line with previous research.[6–8] Overall, the similarity of this study's multifactorial analysis of covariates to stroke compared with those reported in other large studies adds validity to this study's key finding of a statistically significant association between ENDS use and stroke.

Furthermore, several cross-sectional based studies have looked at the association between ENDS and myocardial infarction. One 2018 study of 70,000 participants using the National Health Interview Surveys found that current ENDS users had a statistically significant increased odds of reporting an MI compared with NUs (AOR = 1.8; 95% CI 1.2–2.7).[20] A second study published in 2019, looking at about 60,000 participants in the 2016 to 2017 National Health Interview Surveys, found no statistically significant association between daily ENDS use and MI (AOR 1.35, 95% CI: 0.80–2.27).[21] While their study did not find statistical significance, only 714 participants reported EDU, compared with this Study of which 5010 reported EDU. It is possible that if a larger sample was used, statistical significance would have been found. This study found a large association between MI and stroke. The positive associations found between ENDS and MI bolster the possibility of a true association between ENDS and stroke due to overlaps in pathogenesis between MI and stroke.

Finally, one recently published study using pooled data from the 2016 to 2017 BRFSS sought to examine the risk of stroke with ENDS use in young adults.[22] Amongst 150,000 participants aged 18 to 44, their results found that dual use of ENDS and TCs was associated with a 2.91 AOR (1.62–5.25) of stroke versus nonusers, and a 1.83 AOR (1.06–3.17) of stroke with dual use versus only TCs. Compared with nonsmokers, ENDS use did not show significantly different odds of stroke versus non ENDS or TC users (AOR 0.69, 0.34–1.32).[22] Parekh et al's findings differs from this study's as their study examined at a younger subset and utilized subgroup analyses to look at single ENDS use and dual ENDS use with TC use. Meanwhile this study had a different focus, to find a global independent association between ENDS use and stroke, across all age groups. It included participants of any adult age, including participants older than 65, who are far more likely to report a stroke.

Naturally, this study has some limitations. First, ENDS were initially introduced around 2007 and this study's data were collected in 2016.[35] Hence, there is a relatively short time period in which a person could have ingested enough ENDS doses for ENDS to be a risk factor. Second, while this study accounted for 9 important covariates, it missed valuable modifiable risk factors including hypertension, hyperlipidemia, and alcohol use. The BRFSS did not include these variables in their 2016 questionaire.[24] Third, this study lacked the resolution to further differentiate levels of ENDS use beyond the categories of “EDU,” “SDU,” and “FU.” “SDU” is a potentially vague classification and might not precisely reflect ENDS use. Fourth these data were self-reported which is subject its own inaccuracies.

Lastly, this study's most important limitation is its cross-sectional design. This study could not determine the temporality of the association between ENDS use and a history of stroke. Rather than ENDS use being the exposure variable, and a history of stroke as the outcome variable as intended, it could be that a history of stroke is a risk factor for a participant starting ENDS. This Study found that most every day ENDS users are former TC users and over 90% of every day ENDS users have smoked at least 100 lifetime cigarettes. In other studies, such as the National Center for Health Statistics data brief, among former TC users who quit within the last year, 25.2% of them were current ENDS users. Meanwhile, among current TC users, only 9.7% of them were current ENDS users.[36] Similarly, current TC users with a history of CVD who attempted to quit TC use in the past year had 1.97 times the odds of current ENDS use compared with all TC smokers (including the non-CVD population), who did not attempt to quit TC use within the past year.[37] Some evidence has suggested that TC users may be more prone to stop smoking TCs after a major adverse cardiac event (MACE).[38,39]

However, whether TC users after MACE actually switch to ENDS in a greater frequency than patients without MACE remains to be proven. One study, using 2013 to 2015 Population Assessment of Tobacco and Health data, determined that post MI patients who smoked TCs were not significantly more likely to adopt non-combustible cigarettes than those without an MI.[40] Nevertheless, even if stroke and other MACE were found to be independent risk factors for ENDS, this would still have important healthcare implications. The FDA has yet to approve ENDS for smoking cessation, let alone in those with MACE. The CDC and American Heart Association lack clear statements on ENDS use in patients after MACE, such as stroke.

This study's positive association could be due to either ENDS use as the exposure with stroke as the outcome, or stroke as the exposure with ENDS use as the outcome—both scenarios with important public health implications. The validity of this study's positive association is supported by the similarity of this study's covariates to stroke AORs versus the AORs found in other large studies. It is further supported by the existence of reported positive associations between ENDS use and CAD found in a recent study. Thus, this study's statistical association cannot be ignored and its existence compels the need for future cohort studies to best analyze a relationship between ENDS use and stroke.

5 Conclusion

This study, consisting of over 450,000 people responding to the 2016 BRFSS survey, found an independent positive association between ENDS use and stroke. It is among the first population-based studies to assess for this association. Further research, particularly cohort studies, is needed to assess the reproducibility and temporality of the positive association found in this study.

Author contributions

Conceptualization: Ryan Aziz Thomas Bricknell, Christobal Ducaud, Alejandra Figueroa, Juan Carlos Zevallos, Noël C. Barengo.

Data curation: Ryan Aziz Thomas Bricknell, Christobal Ducaud, Alejandra Figueroa, Pura Rodriguez, Grettel Castro.

Formal analysis: Ryan Aziz Thomas Bricknell, Christobal Ducaud, Alejandra Figueroa, Pura Rodriguez, Grettel Castro.

Investigation: Ryan Aziz Thomas Bricknell, Christobal Ducaud, Alejandra Figueroa, Logan S. Schwarzman, Juan Carlos Zevallos, Noël C. Barengo.

Methodology: Ryan Aziz Thomas Bricknell, Christobal Ducaud, Alejandra Figueroa, Pura Rodriguez, Grettel Castro, Juan Carlos Zevallos, Noël C. Barengo.

Project administration: Ryan Aziz Thomas Bricknell, Christobal Ducaud, Juan Carlos Zevallos, Noël C. Barengo.

Resources: Ryan Aziz Thomas Bricknell, Alejandra Figueroa, Noël C. Barengo.

Software: Ryan Aziz Thomas Bricknell, Christobal Ducaud, Alejandra Figueroa, Pura Rodriguez, Grettel Castro.

Supervision: Juan Carlos Zevallos, Noël C. Barengo.

Validation: Ryan Aziz Thomas Bricknell.

Visualization: Ryan Aziz Thomas Bricknell, Noël C. Barengo.

Writing – original draft: Ryan Aziz Thomas Bricknell, Logan S. Schwarzman.

Writing – review & editing: Ryan Aziz Thomas Bricknell, Logan S. Schwarzman, Noël C. Barengo.


[1]. Cullen KA, Ambrose BK, Gentzke AS, Apelberg BJ, Jamal A, King BA. Notes from the field: use of electronic cigarettes and any tobacco product among middle and high school students—United States, 2011–2018. Morb Mortal Wkly Rep 2018;67:1276.
[2]. Murthy VH. E-cigarette use among youth and young adults: a major public health concern. JAMA Pediatr 2017;171:209–10.
[3]. Walley SC, Wilson KM, Winickoff JP, Groner J. A public health crisis: electronic cigarettes, vape, and JUUL. Pediatrics 2019;143:e20182741.
[4]. Glasser AM, Collins L, Pearson JL, et al. Overview of electronic nicotine delivery systems: a systematic review. Am J Prev Med 2017;52:e33–66.
[5]. Virani SS, Alonso A, Aparicio HJ, et al. Heart Disease and Stroke Statistics—2021 update: a report from the American Heart Association. Circulation 2021;143:e254–743.
[6]. Thun MJ, Carter BD, Feskanich D, et al. 50-year trends in smoking-related mortality in the United States. N Engl J Med 2013;368:351–64.
[7]. Ohira T, Shahar E, Chambless LE, Rosamond WD, Mosley TH Jr, Folsom AR. Risk factors for ischemic stroke subtypes: the Atherosclerosis Risk in Communities study. Stroke 2006;37:2493–8.
[8]. Frishman W. Tobacco use and risk of myocardial infarction in 52 countries in the INTERHEART study: a case-control study. Yearb Med 2007;2007:313–5.
[9]. Cheng T. Chemical evaluation of electronic cigarettes. Tob Control 2014;23: (suppl): ii11–7.
[10]. Margham J, McAdam K, Forster M, et al. Chemical composition of aerosol from an e-cigarette: a quantitative comparison with cigarette smoke. Chem Res Toxicol 2016;29:1662–78.
[11]. Horiguchi TT. Effects of formaldehyde on cardiac function. Jpn J Pharmacol 1990;52:563–72.
[12]. Henning RJ, Johnson GT, Coyle JP, Harbison RD. Acrolein can cause cardiovascular disease: a review. Cardiovasc Toxicol 2017;17:227–36.
[13]. Bhatnagar A. Cardiovascular perspective of the promises and perils of e-cigarettes. Circ Res 2016;118:1872–5.
[14]. Qasim H, Karim ZA, Rivera JO, Khasawneh FT, Alshbool FZ. Impact of electronic cigarettes on the cardiovascular system. J Am Heart Assoc 2017;6:e006353.
[15]. MacDonald A, Middlekauff HR. Electronic cigarettes and cardiovascular health: what do we know so far? Vasc Health Risk Manag 2019;15:159–74.
[16]. Vansickel AR, Eissenberg T. Electronic cigarettes: effective nicotine delivery after acute administration. Nicotine Tob Res 2012;15:267–70.
[17]. Hom S, Chen L, Wang T, Ghebrehiwet B, Yin W, Rubenstein DA. Platelet activation, adhesion, inflammation, and aggregation potential are altered in the presence of electronic cigarette extracts of variable nicotine concentrations. Platelets 2016;27:694–702.
[18]. Carnevale R, Sciarretta S, Violi F, et al. Acute impact of tobacco vs electronic cigarette smoking on oxidative stress and vascular function. Chest 2016;150:606–12.
[19]. Sifat AE, Vaidya B, Kaisar MA, Cucullo L, Abbruscato TJ. Nicotine and electronic cigarette (E-Cig) exposure decreases brain glucose utilization in ischemic stroke. J Neurochem 2018;147:204–21.
[20]. Alzahrani T, Pena I, Temesgen N, Glantz SA. Association between electronic cigarette use and myocardial infarction. Am J Prev Med 2018;55:455–61.
[21]. Farsalinos KE, Polosa R, Cibella F, Niaura R. Is e-cigarette use associated with coronary heart disease and myocardial infarction? Insights from the 2016 and 2017 National Health Interview Surveys. Therap Adv Chronic Dis 2019;10:2040622319877741.
[22]. Parekh T, Pemmasani S, Desai R. Risk of stroke with e-cigarette and combustible cigarette use in young adults. Am J Prev Med 2020;58:446–52.
[23]. Behavioral Risk Factor Surveillance System OVERVIEW: BRFSS 2016. Center for Disease Control; 2017.
[24]. Behavioral Risk Factor Surveillance System Questionnaire: BRFSS 2016. Center for Disease Control; 2015.
[25]. Defining Adult Overweight and Obesity. Center for Disease Control and Prevention; 2017.
[26]. Behavioral Risk Factor Surveillance System LLCP 2016 Codebook Report: BRFSS 2016. Center for Disease Control; 2017.
[27]. Seshadri S, Beiser A, Kelly-Hayes M, et al. The lifetime risk of stroke: estimates from the Framingham Study. Stroke 2006;37:345–50.
[28]. Howard VJ, Kleindorfer DO, Judd SE, et al. Disparities in stroke incidence contributing to disparities in stroke mortality. Ann Neurol 2011;69:619–27.
[29]. Morgenstern LB, Smith MA, Lisabeth LD, et al. Excess stroke in Mexican Americans compared with non-Hispanic whites: the brain attack surveillance in Corpus Christi project. Am J Epidemiol 2004;160:376–83.
[30]. White H, Boden-Albala B, Wang C, et al. Ischemic stroke subtype incidence among whites, blacks, and Hispanics: the Northern Manhattan Study. Circulation 2005;111:1327–31.
[31]. Peters SA, Huxley RR, Woodward M. Diabetes as risk factor for incident coronary heart disease in women compared with men: a systematic review and meta-analysis of 64 cohorts including 858,507 individuals and 28,203 coronary events. Diabetologia 2014;57:1542–51.
[32]. Lee M, Saver JL, Chang KH, Liao HW, Chang SC, Ovbiagele B. Low glomerular filtration rate and risk of stroke: meta-analysis. BMJ 2010;341:c4249.
[33]. Mahmoodi BK, Yatsuya H, Matsushita K, et al. Association of kidney disease measures with ischemic versus hemorrhagic strokes: pooled analyses of 4 prospective community-based cohorts. Stroke 2014;45:1925–31.
[34]. Wang X, Wang Y, Patel UD, et al. Comparison of associations of reduced estimated glomerular filtration rate with stroke outcomes between hypertension and no hypertension. Stroke 2017;48:1691–4.
[35]. Romeh F, Diaz M, Vallone D. E-cigarette Unit Sales, by Product and Flavor Type - United States, 2014–2020. Centers for Disease Control and Prevention; 2020.
[36]. Villarroel MA, Cha AE, Vahratian A. Electronic cigarette use among U.S. adults, 2018. NCHS Data Brief, no 365. Hyattsville, MD: National Center for Health Statistics; 2020.
[37]. Stokes A, Collins JM, Berry KM, et al. Electronic cigarette prevalence and patterns of use in adults with a history of cardiovascular disease in the United States. J Am Heart Assoc 2018;7:e007602.
[38]. Streck JM, Chang Y, Tindle HA, et al. Smoking cessation after hospital discharge: factors associated with abstinence. J Hosp Med 2018;13:774.
[39]. Holm M, Schiöler L, Andersson E, et al. Predictors of smoking cessation: a longitudinal study in a large cohort of smokers. Respir Med 2017;132:164–9.
[40]. Gaalema DE, Pericot-Valverde I, Bunn JY, et al. Tobacco use in cardiac patients: Perceptions, use, and changes after a recent myocardial infarction among US adults in the PATH study (2013-2015). Prev Med 2018;117:76–82.

association; behavioral risk factor surveillance system; cerebrovascular; electronic cigarette; electronic nicotine delivery systems; stroke

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