Examining differences in cigarette smoking prevalence among young adults across national surveillance surveys

Autoři: Peter Messeri aff001;  Jennifer Cantrell aff002;  Paul Mowery aff003;  Morgane Bennett aff004;  Elizabeth Hair aff004;  Donna Vallone aff002
Působiště autorů: Mailman School of Public Health, Columbia University, New York, NY, United States of America aff001;  College of Global Public Health, New York University, New York, NY, United States of America aff002;  Biostatistics, Inc., Atlanta, GA, United States of America aff003;  The Schroeder Institute at Truth Initiative, Washington, DC, United States of America aff004;  Department of Prevention and Community Health, Milken Institute School of Public Health, The George Washington University, Washington, DC, United States of America aff005;  Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America aff006
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0225312


Accurate smoking prevalence data is critical for monitoring, surveillance, and evaluation. However, estimates of prevalence vary across surveys due to various factors. This study examines smoking prevalence estimates for 18–21 year olds across six U.S. national telephone, online and in-person surveys for the years 2013 and 2014. Estimates of ever smoking ranged from 35% to 55%. Current smoking ranged from 16% to 30%. Across the three modalities, household surveys were found to yield the highest estimates of smoking prevalence among 18 to 21 year olds while online surveys yielded the lowest estimates, and this was consistent when stratifying by gender and race/ethnicity. Assessments of the joint effect of gender, race/ethnicity, educational attainment and survey mode indicated that the relative differences in the likelihood of smoking were consistent across modes for gender and education groups. However, the relative likelihood of smoking among minority groups compared with non-Hispanic Whites varied across modes. Gender and racial/ethnic distributions for most surveys significantly differed from the U.S. Census. Over and underrepresentation of certain demographic subpopulations, variations in survey question wording, and social desirability effects may explain modality differences in smoking estimates observed in this study. Further research is needed to evaluate the effect of survey mode on variation in smoking prevalence estimates across national surveys, particularly for young adult populations.

Klíčová slova:

Census – Hispanic people – Semantics – Smoking habits – Surveys – Telephones – Thin-layer chromatography – Young adults


1. American Association for Public Opinion Research (AAPOR). Evaluating Survey Quality in Today's Complex Envrionment. 2016.

2. Cantrell J, Hair EC, Smith A, Bennett M, Rath JM, Thomas RK, et al. Recruiting and retaining youth and young adults: challenges and opportunities in survey research for tobacco control. Tob Control. 2018;27(2):147–54. Epub 2017/04/23. doi: 10.1136/tobaccocontrol-2016-053504 28432211.

3. Rath JM, Villanti AC, Abrams DB, Vallone DM. Patterns of tobacco use and dual use in US young adults: the missing link between youth prevention and adult cessation. J Environ Public Health. 2012;2012:679134. Epub 2012/06/06. doi: 10.1155/2012/679134 22666279; PubMed Central PMCID: PMC3361253.

4. Scherpenzeel A. Data collection in a probability-based internet panel: how the LISS panel was built and how it can be used. Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique. 2011;109(1):56–61.

5. Yeager DS, Krosnick JA, Chang L, Javitz HS, Levendusky MS, Simpser A, et al. Comparing the accuracy of RDD telephone surveys and internet surveys conducted with probability and non-probability samples. Public Opinion Quarterly. 2011;75(4):709–47. doi: 10.1093/poq/nfr020

6. Tourangeau R, Conrad FG, Couper MP. The science of web surveys. Oxford; New York: Oxford University Press; 2013. viii, 198 p. p.

7. Hammond D. Smoking behaviour among young adults: beyond youth prevention. Tob Control. 2005;14(3):181–5. Epub 2005/06/01. doi: 10.1136/tc.2004.009621 15923468; PubMed Central PMCID: PMC1748046.

8. Ling PM, Glantz SA. Why and how the tobacco industry sells cigarettes to young adults: evidence from industry documents. Am J Public Health. 2002;92(6):908–16. Epub 2002/05/31. doi: 10.2105/ajph.92.6.908 12036776; PubMed Central PMCID: PMC1447481.

9. Arnett JJ. Emerging adulthood: A theory of development from the late teens through the twenties. American Psychologist. 2000;55(5):469–80. doi: 10.1037/0003-066X.55.5.469 10842426

10. Cantrell J, Bennett M, Mowery P, Xiao H, Rath J, Hair E, et al. Patterns in first and daily cigarette initiation among youth and young adults from 2002 to 2015. PLoS One. 2018;13(8):e0200827. Epub 2018/08/11. doi: 10.1371/journal.pone.0200827 30096141; PubMed Central PMCID: PMC6086419 There are no patents, products in development or marketed products to declare. This does not alter our adherence to all the PLOS ONE policies on sharing data and materials, as detailed online in the guide for authors.

11. Ribisl KM, Mills SD. Explaining the rapid adoption of Tobacco 21 policies in the United States. Am J Public Health. 2019;109(11):1483–5. Epub 2019/10/03. doi: 10.2105/AJPH.2019.305269 31577495.

12. Kaplan S. Senator McConnell, a Tobacco Ally, Supports Raising Age to Buy Cigarettes New York New York Times; April 18, 2019 [cited 2019 September 25]. Available from: https://www.nytimes.com/2019/04/18/health/mcconnell-tobacco-vaping-21.html

13. Kreuter F, Presser S, Tourangeau R. Social desirability bias in CATI, IVR, and web surveys: the effects of mode and question sensitivity. Public Opinion Quarterly. 2008;72(5):847–65. doi: 10.1093/poq/nfn063

14. Tourangeau R, Rips LJ, Rasinski KA. The psychology of survey response. Cambridge, U.K.; New York: Cambridge University Press; 2000. xiii, 401 p. p.

15. Rath JM, Teplitskaya L, Williams VF, Pearson JL, Vallone DM, Villanti AC. Correlates of e-cigarette ad awareness and likeability in U.S. young adults. Tob Induc Dis. 2017;15:22. Epub 2017/04/12. doi: 10.1186/s12971-017-0125-z 28396620; PubMed Central PMCID: PMC5379699.

16. Link MW, Battaglia MP, Frankel MR, Osborn L, Mokdad AH. A comparison of address-based sampling (ABS) versus random-digit dialing (RDD) for general population surveys. Public Opinion Quarterly. 2008;72(1):6–27. doi: 10.1093/poq/nfn003

17. McMillen RC, Winickoff JP, Wilson K, Tanski S, Klein JD. A dual-frame sampling methodology to address landline replacement in tobacco control research. Tob Control. 2015;24(1):7–10. Epub 2013/04/19. doi: 10.1136/tobaccocontrol-2012-050727 23596199.

18. McCabe SE, Boyd CJ, Couper MP, Crawford S, D'Arcy H. Mode effects for collecting alcohol and other drug use data: Web and U.S. mail. J Stud Alcohol. 2002;63(6):755–61. Epub 2003/01/17. doi: 10.15288/jsa.2002.63.755 12529076.

19. Rodu B, Cole P. Smoking prevalence: a comparison of two American surveys. Public Health. 2009;123(9):598–601. Epub 2009/09/08. doi: 10.1016/j.puhe.2009.07.014 19733373.

20. Johnson AL, Villanti AC, Glasser AM, Pearson JL, Delnevo CD. Impact of question type and question order on tobacco prevalence estimates in U.S. young adults: a randomized experiment. Nicotine Tob Res. 2018. Epub 2018/03/30. doi: 10.1093/ntr/nty058 29596662.

21. Delnevo CD, Gundersen DA, Manderski MTB, Giovenco DP, Giovino GA. Importance of survey design for studying the epidemiology of emerging tobacco product use among youth. Am J Epidemiol. 2017;186(4):405–10. Epub 2017/04/04. doi: 10.1093/aje/kwx031 28369184.

22. Velicer WF, Prochaska JO, Rossi JS, Snow MG. Assessing outcome in smoking cessation studies. Psychol Bull. 1992;111(1):23–41. Epub 1992/01/01. doi: 10.1037/0033-2909.111.1.23 1539088.

23. Glasgow RE, Mullooly JP, Vogt TM, Stevens VJ, Lichtenstein E, Hollis JF, et al. Biochemical validation of smoking status: pros, cons, and data from four low-intensity intervention trials. Addict Behav. 1993;18(5):511–27. Epub 1993/09/01. doi: 10.1016/0306-4603(93)90068-k 8310871.

24. Patrick DL, Cheadle A, Thompson DC, Diehr P, Koepsell T, Kinne S. The validity of self-reported smoking: a review and meta-analysis. Am J Public Health. 1994;84(7):1086–93. Epub 1994/07/01. doi: 10.2105/ajph.84.7.1086 8017530; PubMed Central PMCID: PMC1614767.

25. Connor Gorber S, Schofield-Hurwitz S, Hardt J, Levasseur G, Tremblay M. The accuracy of self-reported smoking: a systematic review of the relationship between self-reported and cotinine-assessed smoking status. Nicotine Tob Res. 2009;11(1):12–24. Epub 2009/02/28. doi: 10.1093/ntr/ntn010 19246437.

26. Holbrook AL, Green MC, Krosnick JA. Telephone versus face-to-face interviewing of national probability samples with long questionnaires: comparisons of respondent satisficing and social desirability response bias. Public Opinion Quarterly. 2003;67(1):79–125. doi: 10.1086/346010

27. Simile CM, Stussman B, Dahlhamer JM, editors. Exploring the impact of mode on key health estimates in the national health interview survey Proceedings of Statistics Canada Symposium 2006: Methodological Issues in Measuring Population Health; 2006.

28. Soulakova J, Davis WW, Hartman A, Gibson J. The Iipact of survey and response modes on current smoking prevalence estimates using TUS-CPS: 1992–2003. Surv Res Methods. 2009;3(3):123–37. Epub 2009/01/01. 21841957; PubMed Central PMCID: PMC3153871.

29. Link MW, Mokdad AH. Alternative modes for health surveillance surveys: an experiment with web, mail, and telephone. Epidemiology. 2005;16(5):701–4. Epub 2005/09/02. doi: 10.1097/01.ede.0000172138.67080.7f 16135951.

30. Aquilino WS, Sciuto LA. Effects of interview mode on self-reported drug use. Public Opinion Quarterly. 1990;54(3):362–93. doi: 10.1086/269212

31. Falck R, Siegal HA, Forney MA, Wang J, Carlson RG. The validity of injection drug users self-reported use of opiates and cocaine. Journal of Drug Issues. 1992;22(4):823–32. doi: 10.1177/002204269202200402

32. Aquilino WS. Interview Mode Effects in Surveys of Drug and Alcohol Use: A Field Experiment. Public Opinion Quarterly. 1994;58(2):210–40. doi: 10.1086/269419

33. Fendrich M, Johnson TP, Wislar JS, Hubbell A, Spiehler V. The utility of drug testing in epidemiological research: results from a general population survey. Addiction. 2004;99(2):197–208. Epub 2004/02/06. doi: 10.1111/j.1360-0443.2003.00632.x 14756712.

34. Johnson TP, Bowman PJ. Cross-cultural sources of measurement error in substance use surveys. Subst Use Misuse. 2003;38(10):1447–90. Epub 2003/09/26. doi: 10.1081/ja-120023394 14509547.

35. Jamal A, Phillips E, Gentzke AS, Homa DM, Babb SD, King BA, et al. Current cigarette smoking among adults—United States, 2016. MMWR Morb Mortal Wkly Rep. 2018;67(2):53–9. Epub 2018/01/19. doi: 10.15585/mmwr.mm6702a1 29346338; PubMed Central PMCID: PMC5772802.

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