Electronic Cigarette Prevalence and Patterns of Use in Adults with a History of Cardiovascular Disease in the United States.

Andrew Stokes, Jason M Collins, Kaitlyn M Berry, Lindsay M Reynolds, Jessica L Fetterman, Carlos J Rodriguez, Michael B Siegel, Emelia J Benjamin
Author Information
  1. Andrew Stokes: Department of Global Health, Boston University School of Public Health, Boston, MA acstokes@bu.edu.
  2. Jason M Collins: Department of Global Health, Boston University School of Public Health, Boston, MA.
  3. Kaitlyn M Berry: Department of Global Health, Boston University School of Public Health, Boston, MA.
  4. Lindsay M Reynolds: Department of Epidemiology & Prevention, Wake Forest School of Medicine, Winston-Salem, NC.
  5. Jessica L Fetterman: Department of Medicine, Boston University School of Medicine, Boston, MA.
  6. Carlos J Rodriguez: Department of Epidemiology & Prevention, Wake Forest School of Medicine, Winston-Salem, NC.
  7. Michael B Siegel: Department of Community Health Sciences, Boston University School of Public Health, Boston, MA.
  8. Emelia J Benjamin: Department of Medicine, Boston University School of Medicine, Boston, MA.

Abstract

BACKGROUND: Characterizing electronic cigarette (e-cigarette) use patterns is important for guiding tobacco regulatory policy and projecting the future burden of tobacco-related diseases. Few studies have examined patterns of e-cigarette use in individuals with cardiovascular disease (CVD).
METHODS AND RESULTS: We examined e-cigarette use in adults aged 18 to 89 years with a history of CVD, using data from the 2014 National Health Interview Survey. We investigated associations between ever and current e-cigarette use and smoking with multivariable logistic regression. In a secondary analysis, we modeled the association between e-cigarette use and a quit attempt over the past year. Former smokers with CVD who quit smoking within the past year showed 1.85 (95% confidence interval, 1.03, 3.33) times the odds of having ever used e-cigarettes as compared with those who reported being "some days" current smokers. Current smokers who attempted to quit smoking within the past year showed significantly increased odds of ever having used e-cigarettes (odds ratio, 1.70; 95% confidence interval, 1.25, 2.30) and currently using e-cigarettes (odds ratio, 1.97; 95% confidence interval, 1.32, 2.95) as compared with smokers who had not attempted to quit over the past year.
CONCLUSIONS: Individuals with CVD who recently quit smoking or reported a recent quit attempt were significantly more likely to use e-cigarettes than current smokers and those who did not report a quit attempt. Our findings may indicate that this population is using e-cigarettes as an aid to smoking cessation. Characterizing emerging e-cigarette use behaviors in adults with CVD may help to inform outreach activities aimed at this high-risk population.

Keywords

References

  1. Tob Control. 2013 Jan;22(1):19-23 [PMID: 22034071]
  2. Lancet. 2013 Nov 16;382(9905):1614-6 [PMID: 24029168]
  3. Atherosclerosis. 2016 Dec;255:179-185 [PMID: 27693003]
  4. Circ Res. 2016 Jun 10;118(12):1872-5 [PMID: 27283531]
  5. J Am Coll Cardiol. 2009 Dec 15;54(25):2382-7 [PMID: 20082928]
  6. Circulation. 2013 Jan 1;127(1):e6-e245 [PMID: 23239837]
  7. Int J Public Health. 2016 Mar;61(2):177-88 [PMID: 26560309]
  8. Lancet. 2006 Aug 19;368(9536):647-58 [PMID: 16920470]
  9. Tob Control. 2017 Dec;26(e2):e117-e126 [PMID: 28624763]
  10. Natl Vital Stat Rep. 2015 Jul 27;63(3):1-120 [PMID: 26222597]
  11. Nat Rev Cardiol. 2017 Aug;14(8):447-456 [PMID: 28332500]
  12. JAMA. 2013 Aug 14;310(6):591-608 [PMID: 23842577]
  13. J Public Health Policy. 2011 Feb;32(1):16-31 [PMID: 21150942]
  14. BMJ. 2017 Jul 26;358:j3262 [PMID: 28747333]
  15. Am J Med Sci. 2016 Oct;352(4):420-426 [PMID: 27776725]
  16. Am J Prev Med. 2017 Mar;52(3):385-390 [PMID: 27988090]
  17. Chest. 2016 Sep;150(3):606-12 [PMID: 27108682]
  18. Lancet. 2013 Nov 16;382(9905):1629-37 [PMID: 24029165]
  19. Ann Intern Med. 2002 Sep 17;137(6):494-500 [PMID: 12230350]
  20. J Am Heart Assoc. 2017 Aug 30;6(9): [PMID: 28855171]
  21. JAMA. 2003 Jul 2;290(1):86-97 [PMID: 12837716]
  22. Circulation. 2011 Nov 29;124(22):2458-73 [PMID: 22052934]
  23. Nicotine Tob Res. 2015 Oct;17(10):1195-202 [PMID: 25381306]
  24. Environ Pollut. 2015 Mar;198:100-7 [PMID: 25577651]
  25. NCHS Data Brief. 2015 Oct;(217):1-8 [PMID: 26555932]
  26. Am J Prev Med. 2017 Feb;52(2):e33-e66 [PMID: 27914771]
  27. Circulation. 2014 Oct 14;130(16):1418-36 [PMID: 25156991]
  28. Cochrane Database Syst Rev. 2016 Sep 14;9:CD010216 [PMID: 27622384]
  29. Prev Med. 2014 Dec;69:248-60 [PMID: 25456810]
  30. JAMA Cardiol. 2017 Mar 1;2(3):278-284 [PMID: 28146259]
  31. BMC Cardiovasc Disord. 2014 Jun 23;14:78 [PMID: 24958250]
  32. Am J Cardiol. 2010 Oct 1;106(7):911-6 [PMID: 20854949]
  33. BMC Geriatr. 2017 Feb 8;17(1):48 [PMID: 28178927]
  34. Vital Health Stat 2. 2014 Apr;(165):1-53 [PMID: 24775908]
  35. BMJ. 2015 Jun 24;350:h3317 [PMID: 26109314]
  36. MMWR Morb Mortal Wkly Rep. 2016 Jun 10;65(22):557-61 [PMID: 27281058]
  37. Nicotine Tob Res. 2016 May;18(5):715-9 [PMID: 26525063]
  38. Regul Toxicol Pharmacol. 2015 Feb;71(1):24-34 [PMID: 25460033]

Grants

  1. P50 HL120163/NHLBI NIH HHS
  2. U54 HL120163/NHLBI NIH HHS

MeSH Term

Adolescent
Adult
Aged
Aged, 80 and over
Cardiovascular Diseases
Cross-Sectional Studies
Electronic Nicotine Delivery Systems
Female
Health Surveys
Humans
Male
Middle Aged
Prevalence
Risk Assessment
Risk Factors
Risk Reduction Behavior
Smokers
Smoking Cessation
Time Factors
Tobacco Smoking
United States
Vaping
Young Adult

Word Cloud

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