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Cigarettes smoking and e-cigarettes using among university students: a cross-section survey in Guangzhou, China, 2021

Abstract

Background

There is an increase in the use of cigarettes and e-cigarettes worldwide, and the similar trends may be observed in young adults. Since 2014, e-cigarettes have become the most commonly used nicotine products among young adults (Sun et al., JAMA Netw Open 4:e2118788, 2021). With the increase in e-cigarette use and the decrease in use of cigarettes and other tobacco products, however, there is limited information about Chinese smokers, e-cigarettes users and trends in cigarettes and e-cigarettes use among university students. Therefore, our objective was to investigate the using status of cigarettes, e-cigarettes and smoking behavior among the students from 7 universities in Guangzhou, China.

Methods

Students at 7 different universities in Guangzhou were investigated online in 2021 through a cross-sectional survey. A total of 10,008 students were recruited and after screening, 9361 participants were adopted in our statistics. Descriptive analysis, Chi-square analysis, and multiple logistic regression analysis were used to explore the smoking status and influencing factors.

Results

The average age of the 9361 university students was 22.4 years (SD = 3.6). 58.3% of participants were male. 29.8% of the participants smoked or used e-cigarettes. Among the smokers and users of e-cigarettes, 16.7% were e-cigarettes only users, 35.0% were cigarettes only users, and 48.3% were dual users.

Males were more likely to smoke or use e-cigarettes. Medical students, students from prestigious Chinese universities, and students with higher levels of education were less likely. Students with unhealthy lifestyles (e.g., drinking alcohol frequently, playing video games excessively, staying up late frequently) were more likely to smoke or use e-cigarettes. Emotion can have significant impacts on both cigarettes and e-cigarettes dual users when choosing cigarettes or e-cigarettes to use. More than half of dual users said they would choose cigarettes when they were depressed and e-cigarettes when they were happy.

Conclusion

We identified factors influencing the use of cigarettes and e-cigarettes among university students in Guangzhou, China. Gender, education level background, specialization, lifestyle habits and emotion all influenced the use of cigarettes and e-cigarettes among university students in Guangzhou, China. Male, low education level, from non-prestigious Chinese universities or vocational schools, non-medical specialization, and presence of unhealthy lifestyles were influencing factors for the use of cigarettes and e-cigarettes among university students in Guangzhou and students with these factors were more likely to smoke or use e-cigarettes. Besides, emotions can influence dual users' choice of products.

This study provides more information to better understand young people's preferences for cigarettes and e-cigarettes by elucidating the characteristics of cigarettes and e-cigarettes use, as well as related influencing factors, among university students in Guangzhou. Further research involving more variables connected to the use of cigarettes and e-cigarettes will be required in our future study.

Peer Review reports

Introduction

Despite numerous efforts to stop the tobacco epidemic, tobacco smoking is recognized as a major preventable cause of disease worldwide [1]. The 2021 Global Report on trends in the prevalence of tobacco use 2000–2025, published by the World Health Organization (WHO), states that tobacco use in any form kills and sickens millions of people every year and over 8 million people died from a tobacco-related disease in 2019 [2]. Smoking and passive smoke (exposure to second-hand smoke) are the key contributors to the mortality of specialization chronic diseases, namely, cardiovascular disease, chronic respiratory disease, and cancer [3]. The prevalence of current (at least 1 of the last 30 days) cigarettes smoking among Chinese adults reached 27.7% in 2015, making it one of the highest smoking rates in the world [4]. The health risks of smoking have attracted more and more attention, and smoking on campus has become a serious school and social problem [2, 5].

Customers are getting more worried about the physical harm as their awareness of cigarettes' dangers is increased, and they are more encouraged to choose e-cigarettes which are claimed as less harmful and can meet their needs of risk reduction [6]. Many researches have shown that e-cigarettes, although they cannot be considered safe [7], may cause less harm to the body than cigarettes [8,9,10,11]. Some cigarettes smokers are converting to e-cigarettes to avoid the effects of smoking [12].

E-cigarettes are electronic devices that deliver nicotine to the respiratory system by atomizing an aerosol of smoke containing glycerin, propylene glycol, nicotine and other additives through an electric heating element [13]. Since e-cigarettes produce much less tar, carbon monoxide, and carcinogenic ingredients such as aldehydes, acids, and phenols, the exclusive use of e-cigarettes among smokers may reduce the number of diseases caused by such ingredients [14,15,16]. Studies have shown that cigarettes and e-cigarettes are the most frequently used nicotine products in youth adults in the USA [17,18,19,20] and probably China. China is the world’s largest consumer of tobacco products and contributes substantially to the global burden of smoking-related diseases [21]. It is noteworthy that the use of e-cigarettes in China is far less frequent than in some European countries and the United States [22,21,22,23,24,27].

However, the health risks of e-cigarettes have not been adequately studied, data on their effects and risks on human body are limited [15, 28]. Despite the fact that using e-cigarettes is a worldwide phenomenon [29, 30], there is a paucity of data regarding the knowledge and attitude of e-cigarettes users particularly among the young adults in China [31]. Studies of cigarettes and e-cigarettes use among e-cigarettes consumers are still in their infancy, with most of them being questionnaires about basic consumer information, consumption behavior and preferences. Most survey respondents are European and American e-cigarettes consumers, and there are limited reports on Chinese e-cigarettes consumers' vaping behavior. There is an urgent need to investigate the status quo and influence factors of smoking and using e-cigarettes [32].

Therefore, we conducted a cross-sectional survey of using cigarettes and e-cigarettes to investigate the smoking behaviors among university students in Guangzhou. One of our research interests was the use of cigarettes and e-cigarettes among university students. Another focus was on the factors that influence the use of cigarettes and e-cigarettes by university students.

Methods

Research design and participants

A cross-sectional survey was developed in China that collected data through a self-administered online structured questionnaire from July to December 2021 among undergraduate and graduate students with different disciplinary backgrounds from 7 universities in Guangzhou. In total, 10,008 participants were recruited through WeChat, while 9361 university students completed the questionnaire with a response rate of 93.5%. The online survey was anonymous, and data were encrypted for added security protection. Before entering the online survey system, all participants reviewed and approved the electronic consent page. By prohibiting users with the same IP (Internet Protocol) address from accessing the survey more than once, duplicate entries were avoided. Incomplete surveys were not sent to the system because of a missed response reminder component that alerted participants in real time about incomplete surveys. This investigation was conducted after obtaining the approval of the Ethics Review Committee (IRB), whose approval number is SYSU202108001.

Sociodemographic

Participants self-reported their gender, age, race/ethnicity, levels of education, and monthly living expenses. We also distinguished the university by three types (vocational school, general universities and prestigious universities) including 7 different universities in Guangzhou, China. A separate variable was created to distinguish the specialization of participants (medical specialization or not).

Cigarettes and e-cigarettes use

Respondents to the survey were asked whether they had smoked or used e-cigarettes even once. Those who had ever smoked or used e-cigarettes were asked if they now smoke or use e-cigarettes. We defined current cigarettes or(and) e-cigarettes use as having smoked or(and) used e-cigarettes at least one day in the last 30 days.

Current cigarettes or(and) e-cigarettes users were asked about the age at first use of cigarettes or e-cigarettes and the product of choice for first use (cigarettes or e-cigarettes). Respondents also were asked how long they have been smoking or using e-cigarettes with the possible answers being from within a month to more than ten years. The using product of initiation (cigarettes or e-cigarettes) was asked if the respondent was a dual user.

Regarding the future choices of smokers and e-cigarettes users, the main focus was to examine whether they choose to become cigarettes only users, e-cigarettes only users or dual users in a year.

Lifestyles variables

Previous studies [17, 18, 33] have shown that unhealthy lifestyles such as alcohol abuse, video gaming addiction, and sleep deprivation are strongly associated with smoking or using e-cigarettes in young adults, so we added lifestyle variables to the study. Three common unhealthy lifestyles were distinguished in our questionnaire including drinking alcohol excessively, playing video games frequently and staying up late (falling asleep after 24 o’clock and getting tired next morning) frequently. We defined frequently as more than three times in a week, and excessively as play video games more than 20 h per week.

Related concepts and definitions

In the survey, participants were divided into four types: cigarettes only users (cigarettes smokers who currently do not use e-cigarettes), e-cigarettes only users (e-cigarettes users who currently do not use cigarettes), dual users (those who currently use both cigarettes and e-cigarettes) and non-nicotine users (those who currently do not use cigarettes and e-cigarettes).

The selected Chinese universities were classified according to their academic prominence as prestigious and non-prestigious according to the QS World University Rankings [34]. Prestigious Chinese universities refer to Sun Yat-sen University and Jinan University in this study. Non-prestigious Chinese universities include Guangzhou University of Chinese Medicine, Southern Medical University and Guangzhou City Polytechnic. Guangzhou Institute of Science and Technology and Guangzhou Huashang University are vocational schools in China.

Statistical analysis

The categorical variables were expressed as the frequency (%), while the continuous variables were presented as mean ± SD. A single sample Kolmogorov–Smirnov test was used to test whether the data conform to normal distribution. Chi square test was used to compare categorical variables, while independent sample t-test and Mann–whitney U test were respectively used to compare the continuous variables with and without normal distribution. An analysis of multiple logistic regression was conducted to explore the relationship between using behavior of cigarettes and e-cigarettes and lifestyle. When multiple comparisons were involved, the Bonferroni method was used to correct for the test level α. All analyses were done using R software. Significant test was a bilateral test and the level of statistical significance was set at P < 0.05 for all the analyses.

Results

Participant characteristics and status of cigarettes and e-cigarettes use

Table 1 shows characteristics of participants. The final sample was composed of 9361 individuals, providing a response rate of 93.5%. In the full sample of 9361 participants, 58.3% (n = 5461) were male and 41.7% (n = 3900) were female.

Table 1 Sociodemographic and other characteristics of university students in Guangzhou, China

Table 1 shows that 29.8% of students smoke or use e-cigarettes and that among them, the typical patterns is dual use (48.3%) with 35.0% smoking only cigarettes and 16.7% using only e-cigarettes. Among the dual users, 51.2% (n = 690) participants started using cigarettes, 34.4% (n = 464) participants e-cigarettes, 14.4% (n = 193) did not recall the exact order (Fig. 1).

Fig. 1
figure 1

The source distribution of cigarettes and e-cigarettes dual users among university students in Guangzhou, China

Factors associated with smoking or using e-cigarettes

Table 2 shows factors associated with smoking or using e-cigarettes. Among e-cigarettes users, females were more likely to choose e-cigarettes compared to males (78.1 vs. 62.8%, P < 0.05).

Table 2 Possible influencing factor related to the use of cigarettes or(and) e-cigarettes among university students in Guangzhou, China

In general, medical students have a higher level of knowledges about health [16, 35] and it is important to understand their perceptions of e-cigarettes as they need to communicate and interact with patients during their training and later in their careers. Therefore, we divided the specialization into non-medical specialization and medical specialization, using medicine as a criterion.

The prevalence of cigarettes and e-cigarettes was significantly higher among non-medical specialization than medical specialization (32.7% vs. 12.8%, P < 0.05), and the highest rate of cigarettes and e-cigarettes use was found among law specialization compared to medical specialization (47.2% vs. 12.8%, P < 0.05), followed by history (46.1% vs. 12.8%) and philosophy (43.8% vs. 12.8%, P < 0.05).However, there was no difference in the choice of cigarettes or e-cigarettes between non-medical and medical students.

The use of both e-cigarettes and cigarettes was lower in prestigious Chinese universities compared to other types of schools. Students in non-prestigious Chinese universities had the highest rate of cigarettes and e-cigarettes use and a correspondingly higher rate of e-cigarettes use.

Among the participants, undergraduates and vocational school students had the highest rate of cigarettes and e-cigarettes use (32.8% and 31.8%), followed by Ph.D. students (20.2%), while master students had the lowest rate of cigarettes and e-cigarettes use at 9.7%, with a statistically significant difference (P < 0.05).

Among them, there was no difference in the distribution of cigarettes and e-cigarettes use among undergraduates and vocational school students, while the rate of cigarettes use among master students was significantly lower than other students (P < 0.05), and the rate of e-cigarettes use? was also the lowest.

Lifestyles have significant impacts on the use of cigarettes and e-cigarettes. Compared to those with appropriate lifestyles, students who drank alcohol frequently, played video games excessively, stayed up late frequently, and did all of the above had an increased odds of cigarettes use, e-cigarettes use, and dual use. Multiple logistic regression analyses of cigarettes only users, e-cigarettes only users, and dual users indicated that the using of cigarettes, e-cigarettes and dual use increased 8.1, 6.8 and 10.2 times respectively for those who drank alcohol compared to those who did not drink alcohol; The odds of cigarettes using, e-cigarettes using and dual using were 2.6, 3.2, and 4.7 times higher for gamers compared to non-gamers, respectively; The odds of cigarettes using, e-cigarettes using and dual using increased by 1.3, 1.2 and 2.4 times respectively for those who stayed up late compared to those who did not stay up late. All results are presented in Table 3.

Table 3 Multifactorial logistic regression assessing the effect of lifestyles on using cigarettes or(and) e-cigarettes

Table 4 shows that 83.5% (n = 1125) of dual users chose using products (whether cigarettes or e-cigarettes) according to their emotional state, while 56.5% (n = 761) of dual users chose cigarettes when they are depressed and e-cigarettes when they are happy.

Table 4 Effects of emotion on products adjustment of cigarettes and e-cigarettes dual users among university students in Guangzhou, China

Future choices of smokers and e-cigarettes users

Table 5 shows that e-cigarettes only users and dual users have a stronger intention to quit using their current nicotine product of use than cigarettes only users(P < 0.05). Figure 2 displays the willingness of cigarettes only users or e-cigarettes only users to try another product (cigarettes or e-cigarettes) among university students in Guangzhou, China. For cigarettes only users, 41.8% (n = 408) report that they will not use e-cigarettes in the future, 30.9% (n = 301) use both cigarettes and e-cigarettes in the future, and 27.3% (n = 266) would give up cigarettes and use e-cigarettes. For e-cigarettes only users, 42.0% (n = 195) would give up e-cigarettes and only use cigarettes, 37.5% (n = 174) would use both cigarettes and e-cigarettes, and 20.5% (n = 95) would not use cigarettes in the future.

Table 5 Percentage of intention to quit using among cigarettes or(and) e-cigarettes users among university students in Guangzhou, China
Fig. 2
figure 2

Willingness of cigarettes only users or e-cigarettes only users to try another nicotine product among university students in Guangzhou, China

Discussion

Our findings were consistent with some prior prevalence studies in which males were more likely to smoke than females (males: females = 37.2:7.5) [10, 36,35,38]. However, the gender difference in e-cigarettes were smaller than in cigarettes, which is also consistent with previous research studies [39,38,41].

The gender differences in smoking may be attributed to traditional sociocultural influences [31, 32, 42,41,44]. Habitual thinking suggests that female's smoking is associated with an inappropriate social image. The social circumstances put more pressure on female smokers, whereas, for male smokers, social opinion has a much smaller negative impact than for females, suggesting that the socio-cultural context have an intervening role in smoking.

In addition, we found that the rate of using cigarettes and e-cigarettes was the highest among undergraduates, followed by Ph.D. students, and the lowest was among master students, both for cigarettes, e-cigarettes, and dual use. It indicates that cigarettes and e-cigarettes use was shown as a non-linear relationship with education level, which is consistent with other studies [45]. This may be due to the fact that undergraduates have less academic stress and more social activities [46], which are susceptibility factors for cigarettes and e-cigarettes use. A number of studies have shown that there is a significant correlation between smoking and the education level of the smoker, the higher the education level is, the lower the smoking rate is [47, 48]. This is because people with a higher level of education level have a higher level of health awareness, and a relatively higher level of awareness of the diseases caused by smoking and harmful results [49, 50], and thus have a lower smoking rate, which explains the relatively lower rate of cigarettes and e-cigarettes use among master student s and Ph.D. students. Undergraduate students were more likely to use e-cigarettes, in contrast to master students and Ph.D. students, who had the lowest rates of cigarettes and e-cigarettes use and a greater preference for cigarettes. It has been established that e-cigarettes use shows a non-linear relationship with education level, but the exact reasons for this are unclear and warrant further study [51]. Our findings displayed that the use of both e-cigarettes and cigarettes was lower in prestigious Chinese universities perhaps due to the widely different circumstances, different management, and different type of student in different universities. In addition, we found that the cigarettes use rate of Ph.D. students is much higher than the e-cigarettes use rate, which is different from the situation of undergraduates and vocational school students. The reasons for this may be that Ph.D. students are older than others and e-cigarettes are emerging products, so many Ph.D. students are used to using cigarettes and are not familiar or are not willing to try e-cigarettes.

Similar to previous surveys, we found that non-medical students have higher rates of cigarettes and e-cigarettes use than medical students [52]. This may be due to the fact that medical students are more aware of the effects of nicotine on the body after learning extensive knowledge of physiology and pathology [16, 30, 43]. It is noteworthy that, the highest rate of using cigarettes and e-cigarettes was law students. The considerable pressure placed on them in academic performance can explain this result [53].

A growing body of research indicates that emotion is also one of the influencing factors of smoking and negative emotions can induce smoking [54, 55]. Our findings found that the majority of dual users will use cigarettes rather than e-cigarettes when they are depressed. This result may be due to the different experiences of smoking and vaping while there is no related data to illustrate that smoking cigarettes will provide more pleasure in the present.

We also discovered that among all the future choices, dual use is becoming increasingly popular, as the previous study reported [56]. 51.2% of the dual users started as cigarettes only users, indicating a huge shift of nicotine products using pattern in young adults. Consistent with our findings above, some studies [30, 41, 57] also indicated that cigarettes only users are more likely to try e-cigarettes than non-smokers. However, a study by Sean Esteban McCabe et al. indicated that dual users had the greatest risk for engaging in risk behaviors (including truancy, grade point average <  = C + , binge drinking, alcohol use, marijuana use, illicit drug use and nonmedical Rx drug use) followed by cigarettes only users, e-cigarettes only users, and non-nicotine products users [5].

Limitations

There are several limitations to this study. First, the source of the sample was university students, whose smoking behaviors may differ from the general population of young adults and may not apply to the group who are not students. Second, the data was not weighted for adjusting biases to non-equal probability of selection, non-coverage, and non-response. Third, these data are self-reported and might be subject to reporting bias. Finally, the study was a cross-sectional study and could not dynamically observe changes in cigarette and e-cigarette use, we were unable to assess causal relationships.

Conclusion

The present study reveals the use rate of cigarettes and e-cigarettes among university students in Guangzhou, China. This study also provides the possible future choices of cigarettes or e-cigarettes users among university students. Our investigation shows that 29.8% of participants reports that they used cigarettes or e-cigarettes. Among them, 16.7% were e-cigarettes only users, 35.0% were cigarettes only users and 48.3%were dual users. 51.2% of the dual users were developed from cigarette only users.

Additionally, this study investigated influencing factors to cigarettes and e-cigarettes use, showing that gender, school, education level, specialization, and lifestyles all had impacts on the use of cigarettes and e-cigarettes among university students in Guangzhou. Students who were male, had low education levels, from non-prestigious Chinese universities or vocational schools, had non-medical specialization, and the presence of inappropriate lifestyles such as drinking and playing video games excessively were more likely to use cigarettes and e-cigarettes. Besides, emotion also can have significant effects on the choice of using cigarettes or e-cigarettes for dual users.

This study elucidates the characteristics of cigarettes and e-cigarettes use and related influencing factors among university students in Guangzhou, providing more information to better understand young people's preferences for cigarettes and e-cigarettes. This cross-section survey offers a perspective for policy makers to develop more guiding industry rules of young adult's cigarettes and e-cigarettes using.

In our future work, further investigations, which take more variables related to cigarettes and e-cigarettes using into account, will need to be undertaken, and more reliable analytical methods must be required.

Availability of data and materials

All data generated or analyzed during this study are included in this published article.

References

  1. Perez-Warnisher MT, Carballosa de Miguel MDP, Seijo LM. Tobacco Use Worldwide: legislative efforts to curb consumption. Ann Glob Health. 2019;85(1).

  2. WHO global report on trends in prevalence of tobacco use 2000–2025, fourth edition [https://www.who.int/publications-detail-redirect/9789240039322].

  3. Xie B, Palmer P, Li Y, Lin C, Johnson CA. Developmental trajectories of cigarette use and associations with multilayered risk factors among Chinese adolescents. Nicotine Tob Res. 2013;15(10):1673–81.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Goodchild M, Zheng R. Tobacco control and Healthy China 2030. Tob Control. 2019;28(4):409–13.

    Article  PubMed  Google Scholar 

  5. McCabe SE, West BT, Veliz P, Boyd CJ. E-cigarette use, cigarette smoking, dual use, and problem behaviors among U.S. Adolescents: results from a national survey. J Adolesc Health. 2017;61(2):155–62.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Wang L, Wang Y, Chen J, Yang XM, Jiang XT, Liu P, Li M. Comparison of biological and transcriptomic effects of conventional cigarette and electronic cigarette smoke exposure at toxicological dose in BEAS-2B cells. Ecotoxicol Environ Saf. 2021;222:112472.

    Article  CAS  PubMed  Google Scholar 

  7. Sharan RN, Chanu TM, Chakrabarty TK, Farsalinos K. Patterns of tobacco and e-cigarette use status in India: a cross-sectional survey of 3000 vapers in eight Indian cities. Harm Reduct J. 2020;17(1):21.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Tavolacci MP, Vasiliu A, Romo L, Kotbagi G, Kern L, Ladner J. Patterns of electronic cigarette use in current and ever users among college students in France: a cross-sectional study. BMJ Open. 2016;6(5):e011344.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Pisinger C, Dossing M. A systematic review of health effects of electronic cigarettes. Prev Med. 2014;69:248–60.

    Article  PubMed  Google Scholar 

  10. Alzalabani AA, Eltaher SM. Perceptions and reasons of E-cigarette use among medical students: an internet-based survey. J Egypt Public Health Assoc. 2020;95(1):21.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Barbeau AM, Burda J, Siegel M. Perceived efficacy of e-cigarettes versus nicotine replacement therapy among successful e-cigarette users: a qualitative approach. Addict Sci Clin Pract. 2013;8(1):5.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Pasquereau A, Guignard R, Andler R, Nguyen-Thanh V. Electronic cigarettes, quit attempts and smoking cessation: a 6-month follow-up. Addiction. 2017;112(9):1620–8.

    Article  PubMed  Google Scholar 

  13. Kinouani S, Pereira E, Tzourio C. Electronic cigarette use in students and its relation with tobacco-smoking: a cross-sectional analysis of the i-share study. Int J Environ Res Public Health. 2017;14(11):1345.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Go YY, Mun JY, Chae SW, Chang J, Song JJ. Comparison between in vitro toxicities of tobacco- and menthol-flavored electronic cigarette liquids on human middle ear epithelial cells. Sci Rep. 2020;10(1):2544.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Schraufnagel DE, Blasi F, Drummond MB, Lam DC, Latif E, Rosen MJ, Sansores R, Van Zyl-Smit R. Forum of International Respiratory S: Electronic cigarettes. A position statement of the forum of international respiratory societies. Am J Respir Crit Care Med. 2014;190(6):611–8.

    Article  PubMed  Google Scholar 

  16. Al-Sawalha NA, Almomani BA, Mokhemer E, Al-Shatnawi SF, Bdeir R. E-cigarettes use among university students in Jordan: Perception and related knowledge. PLoS ONE. 2021;16(12):e0262090.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Raiff BR, Jarvis BP, Rapoza D. Prevalence of Video Game Use, Cigarette Smoking, and Acceptability of a Video Game-Based Smoking Cessation Intervention Among Online Adults. Nicotine Tob Res. 2012;14(12):1453–7.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Hughes K, Bellis MA, Hardcastle KA, McHale P, Bennett A, Ireland R, Pike K. Associations between e-cigarette access and smoking and drinking behaviours in teenagers. BMC Public Health. 2015;15(1):244.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Sun R, Mendez D, Warner KE. Trends in Nicotine Product Use Among US Adolescents, 1999–2020. JAMA Netw Open. 2021;4(8):e2118788.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Gotts JE, Jordt SE, McConnell R, Tarran R. What are the respiratory effects of e-cigarettes? BMJ. 2019;366:l5275.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Zheng Y, Ji Y, Dong H, Chang C. The prevalence of smoking, second-hand smoke exposure, and knowledge of the health hazards of smoking among internal migrants in 12 provinces in China: a cross-sectional analysis. BMC Public Health. 2018;18(1):655.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Copeland AL, Peltier MR, Waldo K. Perceived risk and benefits of e-cigarette use among college students. Addict Behav. 2017;71:31–7.

    Article  PubMed  Google Scholar 

  23. Lanza HI, Teeter H. Electronic Nicotine Delivery Systems (E-cigarette/Vape) use and Co-occurring health-risk behaviors among an ethnically diverse sample of young adults. Subst Use Misuse. 2018;53(1):154–61.

    Article  PubMed  Google Scholar 

  24. Delnevo CD, Giovenco DP, Steinberg MB, Villanti AC, Pearson JL, Niaura RS, Abrams DB. Patterns of Electronic Cigarette Use Among Adults in the United States. Nicotine Tob Res. 2016;18(5):715–9.

    Article  PubMed  Google Scholar 

  25. Wallace LN, Roche MJ. Vaping in Context: Links Among E-cigarette Use, Social Status, and Peer Influence for College Students. J Drug Educ. 2018;48(1–2):36–53.

    Article  Google Scholar 

  26. Grant JE, Lust K, Fridberg DJ, King AC, Chamberlain SR. E-cigarette use (vaping) is associated with illicit drug use, mental health problems, and impulsivity in university students. Ann Clin Psychiatry. 2019;31(1):27–35.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Jones RD, Asare M, Lanning B. A Retrospective Cross-Sectional Study on the Prevalence of E-cigarette Use Among College Students. J Community Health. 2021;46(1):195–202.

    Article  PubMed  Google Scholar 

  28. Gorna I, Napierala M, Florek E: Electronic Cigarette Use and Metabolic Syndrome Development: A Critical Review. Toxics 2020, 8(4).

  29. Misra M, Leverette RD, Cooper BT, Bennett MB, Brown SE. Comparative in vitro toxicity profile of electronic and tobacco cigarettes, smokeless tobacco and nicotine replacement therapy products: e-liquids, extracts and collected aerosols. Int J Environ Res Public Health. 2014;11(11):11325–47.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Iqbal N, Khan ZA, Anwar SMH, Irfan O, Irfan B, Mushtaq A, Bibi M, Siddiqui F, Khan JA. Electronic cigarettes use and perception amongst medical students: a cross sectional survey from Sindh, Pakistan. BMC Res Notes. 2018;11(1):188.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Mao R, Li X, Stanton B, Wang J, Hong Y, Zhang H, Chen X. Psychosocial correlates of cigarette smoking among college students in China. Health Educ Res. 2009;24(1):105–18.

    Article  PubMed  Google Scholar 

  32. Eticha T, Kidane F. The prevalence of and factors associated with current smoking among College of Health Sciences students, Mekelle University in northern Ethiopia. PLoS ONE. 2014;9(10):e111033.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Wetter DW, Young TB. The relation between cigarette smoking and sleep disturbance. Prev Med. 1994;23(3):328–34.

    Article  CAS  PubMed  Google Scholar 

  34. QS World University Rankings 2021 [https://www.topuniversities.com/university-rankings/world-university-rankings/2021].

  35. Alenazi ASABAAMSMAKAFAAAOT. Knowledge and attitudes toward HIV among medical and non-medical students in Riyadh, Saudi Arabia. Int J Med Dev Countries. 2020;4(12):2120–30.

    Google Scholar 

  36. Bin Abdulrahman KA, Khalaf AM, Bin Abbas FB, Alanezi OT. The lifestyle of Saudi medical students. Int J Environ Res Public Health. 2021;18(15):7869.

  37. Kong G, Idrisov B, Galimov A, Masagutov R, Sussman S. Electronic Cigarette Use Among Adolescents in the Russian Federation. Subst Use Misuse. 2017;52(3):332–9.

    Article  PubMed  Google Scholar 

  38. Bhaskar RK, Sah MN, Gaurav K, Bhaskar SC, Singh R, Yadav MK, Ojha S. Prevalence and correlates of tobacco use among adolescents in the schools of Kalaiya, Nepal: a cross-sectional questionnaire based study. Tob Induc Dis. 2016;14:11.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Zhu J, Shi F, Xu G, Li N, Li J, He Y, Yu J. Conventional Cigarette and E-Cigarette Smoking among School Personnel in Shanghai, China: Prevalence and Determinants. Int J Environ Res Public Health. 2019;16(17):3197.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Brozek GM, Jankowski M, Lawson JA, Shpakou A, Poznanski M, Zielonka TM, Klimatckaia L, Loginovich Y, Rachel M, Gereova J, et al. The prevalence of cigarette and e-cigarette smoking among students in central and eastern europe-results of the YUPESS study. Int J Environ Res Public Health. 2019;16(13):2297.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Balogh E, Wagner Z, Faubl N, Riemenschneider H, Voigt K, Terebessy A, Horvath F, Fuzesi Z, Kiss I. Increasing prevalence of electronic cigarette use among medical students. repeated cross-sectional multicenter surveys in Germany and hungary, 2016-2018. Subst Use Misuse. 2020;55(13):2109–15.

    Article  PubMed  Google Scholar 

  42. MbatchouNgahane BH, Luma H, Mapoure YN, Fotso ZM, AfaneZe E. Correlates of cigarette smoking among university students in Cameroon. Int J Tuberc Lung Dis. 2013;17(2):270–4.

    Article  CAS  Google Scholar 

  43. Khader YS, Alsadi AA. Smoking habits among university students in Jordan: prevalence and associated factors. East Mediterr Health J. 2008;14(4):897–904.

    CAS  PubMed  Google Scholar 

  44. Prijic Z, Igic R. Cigarette smoking and medical students. J BUON. 2021;26(5):1709–18.

    PubMed  Google Scholar 

  45. Assari S, Mistry R, Bazargan M. Race, educational attainment, and e-cigarette use. J Med Res Innov. 2020;4(1). https://doi.org/10.32892/jmri.185.

  46. Martin LM, Sayette MA. A review of the effects of nicotine on social functioning. Exp Clin Psychopharmacol. 2018;26(5):425–39.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Shuja M, Sarrafzadegan N, Roohafza HR, Sadeghi M, Ghafari M, Mohammadian M, MohammadianHafshejani A. Factors associated with cigarette smoking in central parts of Iran. Asian Pac J Cancer Prev. 2017;18(3):647–53.

    PubMed  PubMed Central  Google Scholar 

  48. Böckerman P, Hyytinen A, Kaprio J. Smoking and long-term labour market outcomes. Tob Control. 2015;24(4):348–53.

    Article  PubMed  Google Scholar 

  49. van der Heide I, Wang J, Droomers M, Spreeuwenberg P, Rademakers J, Uiters E. The relationship between health, education, and health literacy: results from the Dutch Adult Literacy and Life Skills Survey. J Health Commun. 2013;18(Suppl 1):172–84.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Sudhakar S, Aebi ME, Burant CJ, Wilson B, Wenk J, Briggs FBS, Pyatka N, Blixen C, Sajatovic M. Health literacy and education level correlates of participation and outcome in a remotely delivered epilepsy self-management program. Epilepsy Behav. 2020;107:107026.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Wilson FA, Wang Y. Recent Findings on the Prevalence of E-Cigarette Use Among Adults in the U.S. Am J Prev Med. 2017;52(3):385–90.

    Article  PubMed  Google Scholar 

  52. Hinderaker K, Power DV, Allen S, Parker E, Okuyemi K. What do medical students know about e-cigarettes? A cross-sectional survey from one U.S. medical school. BMC Med Educ. 2018;18(1):32.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Bergin A, Pakenham K. Law Student Stress: Relationships Between Academic Demands, Social Isolation, Career Pressure, Study/Life Imbalance and Adjustment Outcomes in Law Students. Psychiatry, Psychology and Law. 2015;22(3):388–406.

    Article  Google Scholar 

  54. Weinberger AH, McKee SA. Mood and smoking behavior: the role of expectancy accessibility and gender. Addict Behav. 2012;37(12):1349–52.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Weinberger AH, McKee SA. Gender differences in smoking following an implicit mood induction. Nicotine Tob Res. 2012;14(5):621–5.

    Article  PubMed  Google Scholar 

  56. Lee S, Grana RA, Glantz SA. Electronic cigarette use among Korean adolescents: a cross-sectional study of market penetration, dual use, and relationship to quit attempts and former smoking. J Adolesc Health. 2014;54(6):684–90.

    Article  PubMed  Google Scholar 

  57. Bowker K, Lewis S, Phillips L, Orton S, Ussher M, Naughton F, Bauld L, Coleman T, Sinclair L, McRobbie H, et al. Pregnant women’s use of e-cigarettes in the UK: a cross-sectional survey. BJOG. 2021;128(6):984–93.

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Acknowledgements

Not applicable.

Statement

Informed consent was obtained from all subjects. Informed consent was obtained from all subjects and/or their legal guardian(s).

Funding

This work was supported by the National Natural Science Foundation of China (31970699), the Guangdong Basic and Applied Basic Research Foundation (2021A1515010766 and 2019A1515011030), the Guang-dong Provincial Key Laboratory of Construction Foundation(2019B030301005), the Key-Area Research and Development Program of Guangdong Province (2020B1111110003), and the National Major Special Projects for the Creation and Manufacture of New Drugs(2019ZX09301104).

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Contributions

PL and JC contributed to the conception of the study. XY and HS participated in designing the research, performing the bibliography searches, selecting studies and extracting data. WY and HS contributed significantly to analysis and manuscript preparation. HS performed the data analyses and wrote the manuscript. YD, GZ and HS contributed to the interpretation and discussion of the results of the analysis. All authors edited and critically reviewed the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Guoping Zhong, Peiqing Liu or Jianwen Chen.

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Ethical approval and consent to participate.

Students from universities and vocational schools in Guangzhou, China received an online survey after their consent. Ethical approval was obtained from Dongguan Kanghua Hospital Clinical Trial Research Ethics Committee (Approval number: SYSU202108001). This study was conducted in accordance with the Declaration of Helsinki. All methods were performed in accordance with the relevant guidelines and regulations.

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Not applicable.

Competing interests

At the time of the research, Xuemin Yang, Kun Duan and Xingtao Jiang were employees of RELX Tech. The rest of the authors have no competing interests to disclose.

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Song, H., Yang, X., Yang, W. et al. Cigarettes smoking and e-cigarettes using among university students: a cross-section survey in Guangzhou, China, 2021. BMC Public Health 23, 438 (2023). https://doi.org/10.1186/s12889-023-15350-2

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