Skip to main content
Top
Published in: BMC Public Health 1/2022

Open Access 01-12-2022 | Addiction | Research

Developmental trajectories of tobacco use and risk factors from adolescence to emerging young adulthood: a population-based panel study

Authors: Seong Yeon Kim, Sung-il Cho

Published in: BMC Public Health | Issue 1/2022

Login to get access

Abstract

Background

Adolescence to young adulthood is a critical developmental period that determines lifelong patterns of tobacco use. We examined the longitudinal trajectories of tobacco use, and risk factors for its use, and explored the association between the trajectories of mobile phone dependency and smoking throughout the life-course among adolescents and young adults.

Methods

Data of 1,723 subjects (853 boys and 870 girls) were obtained from six waves of the Korean Children and Youth Panel Survey (mean age = 13.9–19.9 years). To identify trajectories of smoking and mobile phone dependency, group-based trajectory modelling (GBTM) was conducted. A multinomial logistic regression analysis was performed to identify the characteristics of the trajectory groups.

Results

GBTM identified four distinct smoking trajectories: never smokers (69.1%), persistent light smokers (8.7%), early established smokers (12.0%), and late escalators (10.3%). Successful school adjustment decreased the risk of being an early established smoker (odds ratio [OR] 0.46, 95% confidence interval [CI] 0.27–0.78). The number of days not supervised by a guardian after school was positively associated with the risk of being an early established smoker (OR 1.96, 95% CI 1.23–3.13). Dependency on mobile phones throughout the life-course was positively associated with the risk of being a persistent light smoker (OR 4.04, 95% CI 1.32–12.34) or early established smoker (OR 8.18, 95% CI 4.04–16.56).

Conclusions

Based on the group-based modeling approach, we identified four distinctive smoking trajectories and highlight the long-term effects of mobile phone dependency, from early adolescence to young adulthood, on smoking patterns.
Appendix
Available only for authorised users
Literature
1.
go back to reference USDHHS. Preventing tobacco use among youth and young adults: a report of the Surgeon General. Atlanta: US Department of Health and Human Services, Centers for Disease; 2012. USDHHS. Preventing tobacco use among youth and young adults: a report of the Surgeon General. Atlanta: US Department of Health and Human Services, Centers for Disease; 2012.
2.
go back to reference White HR, Pandina RJ, Chen PH. Developmental trajectories of cigarette use from early adolescence into young adulthood. Drug Alcohol Depen. 2002;65(2):167–78.CrossRef White HR, Pandina RJ, Chen PH. Developmental trajectories of cigarette use from early adolescence into young adulthood. Drug Alcohol Depen. 2002;65(2):167–78.CrossRef
3.
go back to reference Lee Y, Lee KS. Factors related to smoking status among young adults: an analysis of younger and older young adults in Korea. J Prev Med Public Health. 2019;52(2):92.PubMedPubMedCentralCrossRef Lee Y, Lee KS. Factors related to smoking status among young adults: an analysis of younger and older young adults in Korea. J Prev Med Public Health. 2019;52(2):92.PubMedPubMedCentralCrossRef
4.
go back to reference Dutra LM, Glantz SA, Lisha NE, Song AV. Beyond experimentation: five trajectories of cigarette smoking in a longitudinal sample of youth. PLoS ONE. 2017;12(2):e0171808.PubMedPubMedCentralCrossRef Dutra LM, Glantz SA, Lisha NE, Song AV. Beyond experimentation: five trajectories of cigarette smoking in a longitudinal sample of youth. PLoS ONE. 2017;12(2):e0171808.PubMedPubMedCentralCrossRef
5.
go back to reference Derefinko KJ, Charnigo RJ, Peters JR, Adams ZW, Milich R, Lynam DR. Substance use trajectories from early adolescence through the transition to college. J Stud Alcohol Drugs. 2016;77(6):924–35.PubMedPubMedCentralCrossRef Derefinko KJ, Charnigo RJ, Peters JR, Adams ZW, Milich R, Lynam DR. Substance use trajectories from early adolescence through the transition to college. J Stud Alcohol Drugs. 2016;77(6):924–35.PubMedPubMedCentralCrossRef
6.
go back to reference Nagin DS, Odgers CL. Group-based trajectory modeling in clinical research. Annu Rev Clin Psychol. 2010;6:109–38.PubMedCrossRef Nagin DS, Odgers CL. Group-based trajectory modeling in clinical research. Annu Rev Clin Psychol. 2010;6:109–38.PubMedCrossRef
7.
go back to reference Colder CR, Mehta P, Balanda K, Campbell RT, Mayhew K, Stanton WR, et al. Identifying trajectories of adolescent smoking: an application of latent growth mixture modeling. Health Psychol. 2001;20(2):127.PubMedCrossRef Colder CR, Mehta P, Balanda K, Campbell RT, Mayhew K, Stanton WR, et al. Identifying trajectories of adolescent smoking: an application of latent growth mixture modeling. Health Psychol. 2001;20(2):127.PubMedCrossRef
8.
go back to reference Stanton WR, Flay BR, Colder CR, Mehta P. Identifying and predicting adolescent smokers’ developmental trajectories. Nicotine Tob Res. 2004;6(5):843–52.PubMedCrossRef Stanton WR, Flay BR, Colder CR, Mehta P. Identifying and predicting adolescent smokers’ developmental trajectories. Nicotine Tob Res. 2004;6(5):843–52.PubMedCrossRef
9.
go back to reference Nagin DS. Group-based modeling of development over the life course. Cambridge: Harvard University Press; 2005.CrossRef Nagin DS. Group-based modeling of development over the life course. Cambridge: Harvard University Press; 2005.CrossRef
10.
go back to reference Hautala D, Sittner K, Walls M. Latent trajectories and profiles of commercial cigarette smoking frequency from adolescence to young adulthood among North American Indigenous People. Nicotine Tob Res. 2020;22(11):2066–74.PubMedPubMedCentralCrossRef Hautala D, Sittner K, Walls M. Latent trajectories and profiles of commercial cigarette smoking frequency from adolescence to young adulthood among North American Indigenous People. Nicotine Tob Res. 2020;22(11):2066–74.PubMedPubMedCentralCrossRef
11.
go back to reference van der Nest G, Passos VL, Candel MJ, van Breukelen GJ. An overview of mixture modelling for latent evolutions in longitudinal data: Modelling approaches, fit statistics and software. Adv Life Course Res. 2020;43:100323.CrossRef van der Nest G, Passos VL, Candel MJ, van Breukelen GJ. An overview of mixture modelling for latent evolutions in longitudinal data: Modelling approaches, fit statistics and software. Adv Life Course Res. 2020;43:100323.CrossRef
12.
go back to reference Riggs NR, Chou CP, Li C, Pentz MA. Adolescent to emerging adulthood smoking trajectories: when do smoking trajectories diverge, and do they predict early adulthood nicotine dependence? Nicotine Tob Res. 2007;9(11):1147–54.PubMedCrossRef Riggs NR, Chou CP, Li C, Pentz MA. Adolescent to emerging adulthood smoking trajectories: when do smoking trajectories diverge, and do they predict early adulthood nicotine dependence? Nicotine Tob Res. 2007;9(11):1147–54.PubMedCrossRef
13.
go back to reference Seo DG, Park Y, Kim MK, Park J. Mobile phone dependency and its impacts on adolescents’ social and academic behaviors. Comput Hum Behav. 2016;63:282–92.CrossRef Seo DG, Park Y, Kim MK, Park J. Mobile phone dependency and its impacts on adolescents’ social and academic behaviors. Comput Hum Behav. 2016;63:282–92.CrossRef
14.
go back to reference Kim Y. Analysis of mobile phone ownership and usage among children and adolescents. KISDI STAT Report 18.20. 2018. p. 1–7. Available online: https://www.kisdi.re.kr/. Accessed 15 Aug 2022. Kim Y. Analysis of mobile phone ownership and usage among children and adolescents. KISDI STAT Report 18.20. 2018. p. 1–7. Available online: https://​www.​kisdi.​re.​kr/​. Accessed 15 Aug 2022.
16.
go back to reference Lee KE, Kim SH, Ha TY, Yoo YM, Han JJ, Jung JH, et al. Dependency on smartphone use and its association with anxiety in Korea. Public Health Rep. 2016;131(3):411–9.PubMedPubMedCentralCrossRef Lee KE, Kim SH, Ha TY, Yoo YM, Han JJ, Jung JH, et al. Dependency on smartphone use and its association with anxiety in Korea. Public Health Rep. 2016;131(3):411–9.PubMedPubMedCentralCrossRef
17.
go back to reference Jo HS, Na E, Kim DJ. The relationship between smartphone addiction predisposition and impulsivity among Korean smartphone users. Addict Res Theory. 2018;26(1):77–84.CrossRef Jo HS, Na E, Kim DJ. The relationship between smartphone addiction predisposition and impulsivity among Korean smartphone users. Addict Res Theory. 2018;26(1):77–84.CrossRef
18.
go back to reference Gommans R, Stevens GW, Finne E, Cillessen AH, Boniel-Nissim M, ter Bogt TF. Frequent electronic media communication with friends is associated with higher adolescent substance use. Int J Public Health. 2015;60(2):167–77.PubMedCrossRef Gommans R, Stevens GW, Finne E, Cillessen AH, Boniel-Nissim M, ter Bogt TF. Frequent electronic media communication with friends is associated with higher adolescent substance use. Int J Public Health. 2015;60(2):167–77.PubMedCrossRef
19.
go back to reference Kim HR, Han MA. Associations between problematic smartphone use, unhealthy behaviors, and mental health status in Korean adolescents: based on data from the 13th Korea Youth Risk Behavior Survey (2017). Psychiat Invest. 2020;17(12):1216–25.CrossRef Kim HR, Han MA. Associations between problematic smartphone use, unhealthy behaviors, and mental health status in Korean adolescents: based on data from the 13th Korea Youth Risk Behavior Survey (2017). Psychiat Invest. 2020;17(12):1216–25.CrossRef
20.
go back to reference Yang YS, Yen JY, Ko CH, Cheng CP, Yen CF. The association between problematic cellular phone use and risky behaviors and low self-esteem among Taiwanese adolescents. BMC Public Health. 2010;10(1):1–8.CrossRef Yang YS, Yen JY, Ko CH, Cheng CP, Yen CF. The association between problematic cellular phone use and risky behaviors and low self-esteem among Taiwanese adolescents. BMC Public Health. 2010;10(1):1–8.CrossRef
21.
go back to reference Huang GC, Okamoto J, Valente TW, Sun P, Wei Y, Johnson CA, et al. Effects of media and social standing on smoking behaviors among adolescents in China. J Child Media. 2012;6(1):100–18.CrossRef Huang GC, Okamoto J, Valente TW, Sun P, Wei Y, Johnson CA, et al. Effects of media and social standing on smoking behaviors among adolescents in China. J Child Media. 2012;6(1):100–18.CrossRef
22.
go back to reference BinDhim NF, Freeman B, Trevena L. Pro-smoking apps for smartphones: the latest vehicle for the tobacco industry? Tob control. 2014;23(1):e4–e4.PubMedCrossRef BinDhim NF, Freeman B, Trevena L. Pro-smoking apps for smartphones: the latest vehicle for the tobacco industry? Tob control. 2014;23(1):e4–e4.PubMedCrossRef
23.
go back to reference Kuh D, Ben-Shlomo Y, Lynch J, Hallqvist J, Power C. Life course epidemiology. J Epidemiol Commun H. 2003;57(10):778.CrossRef Kuh D, Ben-Shlomo Y, Lynch J, Hallqvist J, Power C. Life course epidemiology. J Epidemiol Commun H. 2003;57(10):778.CrossRef
24.
go back to reference Ben-Shlomo Y, Kuh D. A life course approach to chronic disease epidemiology: conceptual models, empirical challenges and interdisciplinary perspectives. Int J Epidemiol. 2002;31(2):285–93.PubMedCrossRef Ben-Shlomo Y, Kuh D. A life course approach to chronic disease epidemiology: conceptual models, empirical challenges and interdisciplinary perspectives. Int J Epidemiol. 2002;31(2):285–93.PubMedCrossRef
25.
go back to reference Mayhew KP, Flay BR, Mott JA. Stages in the development of adolescent smoking. Drug Alcohol Depen. 2000;59:61–81.CrossRef Mayhew KP, Flay BR, Mott JA. Stages in the development of adolescent smoking. Drug Alcohol Depen. 2000;59:61–81.CrossRef
26.
go back to reference National Youth Policy Institute. A Study on Youth Activity Survey V. Social Policy Building, Sejong National Research Complex. 2018. National Youth Policy Institute. A Study on Youth Activity Survey V. Social Policy Building, Sejong National Research Complex. 2018.
27.
go back to reference Lee S, Kim H, Na E, Lee S, Kim S, Bae J, et al. A study on the effects of mobile phone use of adolescents. Seoul: Samsung Life Public Welfare Foundation; 2002. p. 2002–1. Lee S, Kim H, Na E, Lee S, Kim S, Bae J, et al. A study on the effects of mobile phone use of adolescents. Seoul: Samsung Life Public Welfare Foundation; 2002. p. 2002–1.
28.
go back to reference Berglund P, Heeringa SG. Multiple imputation of missing data using SAS. Cary: SAS Institute Inc; 2014. Berglund P, Heeringa SG. Multiple imputation of missing data using SAS. Cary: SAS Institute Inc; 2014.
29.
go back to reference Jones BL, Nagin DS, Roeder K. A SAS procedure based on mixture models for estimating developmental trajectories. Sociol Methods Res. 2001;29(3):374–93.CrossRef Jones BL, Nagin DS, Roeder K. A SAS procedure based on mixture models for estimating developmental trajectories. Sociol Methods Res. 2001;29(3):374–93.CrossRef
30.
go back to reference Arrandale V, Koehoorn M, MacNab Y, Kennedy SM. How to use SAS® Proc Traj and SAS® Proc Glimmix in respiratory epidemiology. 2006. Arrandale V, Koehoorn M, MacNab Y, Kennedy SM. How to use SAS® Proc Traj and SAS® Proc Glimmix in respiratory epidemiology. 2006.
31.
go back to reference Costello DM, Dierker LC, Jones BL, Rose JS. Trajectories of smoking from adolescence to early adulthood and their psychosocial risk factors. Health Psychol. 2008;27(6):811.PubMedPubMedCentralCrossRef Costello DM, Dierker LC, Jones BL, Rose JS. Trajectories of smoking from adolescence to early adulthood and their psychosocial risk factors. Health Psychol. 2008;27(6):811.PubMedPubMedCentralCrossRef
32.
go back to reference Kim HHS, Chun J. Analyzing multilevel factors underlying adolescent smoking behaviors: the roles of friendship network, family relations, and school environment. J Sch Health. 2018;88(6):434–43.PubMedCrossRef Kim HHS, Chun J. Analyzing multilevel factors underlying adolescent smoking behaviors: the roles of friendship network, family relations, and school environment. J Sch Health. 2018;88(6):434–43.PubMedCrossRef
33.
go back to reference Mott JA, Crowe PA, Richardson J, Flay B. After-school supervision and adolescent cigarette smoking: contributions of the setting and intensity of after-school self-care. J Behav Med. 1999;22(1):35–58.PubMedCrossRef Mott JA, Crowe PA, Richardson J, Flay B. After-school supervision and adolescent cigarette smoking: contributions of the setting and intensity of after-school self-care. J Behav Med. 1999;22(1):35–58.PubMedCrossRef
34.
go back to reference Weiss JW, Liu I, Sussman S, Palmer P, Unger JB, Cen S, et al. After-school supervision, psychosocial impact, and adolescent smoking and alcohol use in China. J Child Fam Stud. 2006;15(4):442–59.CrossRef Weiss JW, Liu I, Sussman S, Palmer P, Unger JB, Cen S, et al. After-school supervision, psychosocial impact, and adolescent smoking and alcohol use in China. J Child Fam Stud. 2006;15(4):442–59.CrossRef
35.
go back to reference D’Amico EJ, Tucker JS, Miles JN, Zhou AJ, Shih RA, Green HD. Preventing alcohol use with a voluntary after-school program for middle school students: results from a cluster randomized controlled trial of CHOICE. Prev Sci. 2012;13(4):415–25.PubMedPubMedCentralCrossRef D’Amico EJ, Tucker JS, Miles JN, Zhou AJ, Shih RA, Green HD. Preventing alcohol use with a voluntary after-school program for middle school students: results from a cluster randomized controlled trial of CHOICE. Prev Sci. 2012;13(4):415–25.PubMedPubMedCentralCrossRef
36.
go back to reference Amuedo-Dorantes C, Mach T, Clapp JD. The impact of schools on juvenile substance initiation and use. Prev Sci. 2004;5(2):91–9.PubMedCrossRef Amuedo-Dorantes C, Mach T, Clapp JD. The impact of schools on juvenile substance initiation and use. Prev Sci. 2004;5(2):91–9.PubMedCrossRef
37.
go back to reference Tebes JK, Feinn R, Vanderploeg JJ, Chinman MJ, Shepard J, Brabham T, et al. Impact of a positive youth development program in urban after-school settings on the prevention of adolescent substance use. J Adolesc Health. 2007;41(3):239–47.PubMedCrossRef Tebes JK, Feinn R, Vanderploeg JJ, Chinman MJ, Shepard J, Brabham T, et al. Impact of a positive youth development program in urban after-school settings on the prevention of adolescent substance use. J Adolesc Health. 2007;41(3):239–47.PubMedCrossRef
39.
go back to reference Thomas RE, McLellan J, Perera R. School-based programmes for preventing smoking. Evid Based Child Health. 2013;8(5):1616–2040.CrossRef Thomas RE, McLellan J, Perera R. School-based programmes for preventing smoking. Evid Based Child Health. 2013;8(5):1616–2040.CrossRef
40.
go back to reference Thomas RE, McLellan J, Perera R. Effectiveness of school-based smoking prevention curricula: systematic review and meta-analysis. BMJ Open. 2015;5(3):e006976.PubMedPubMedCentralCrossRef Thomas RE, McLellan J, Perera R. Effectiveness of school-based smoking prevention curricula: systematic review and meta-analysis. BMJ Open. 2015;5(3):e006976.PubMedPubMedCentralCrossRef
Metadata
Title
Developmental trajectories of tobacco use and risk factors from adolescence to emerging young adulthood: a population-based panel study
Authors
Seong Yeon Kim
Sung-il Cho
Publication date
01-12-2022
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2022
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-022-14070-3

Other articles of this Issue 1/2022

BMC Public Health 1/2022 Go to the issue