E-cigarette use among teenagers in Ireland has risen significantly in recent years and findings from ESPAD Ireland (European School Survey Project on Alcohol and Other Drugs) show that in 2019 in Ireland, among children born in 2003, e-cigarette ever use prevalence was 37%1. Increasing prevalence of ever use of e-cigarettes in Ireland reflects similar trends elsewhere in Europe2, the United States (US)3,4 and the Asia-Pacific region5. In Ireland, current use (30-day) of e-cigarettes among adolescents has also increased significantly from 10% in 2015 to 18% in 20196 and has been linked to significantly increased smoking prevalence among teenage boys7.

The 2019 ESPAD survey2 of 99647 students from 35 countries in Europe reported an average of 40% ever use of e-cigarettes among students aged 16 years, ranging from 18% in Serbia to 65% in Lithuania. The United Kingdom did not participate in ESPAD in 2019 but prevalence of ever use of e-cigarettes among Scottish 15-year-olds was reported at 35% in 2018, with boys more likely than girls to have ever used e-cigarettes8. Increasing prevalence is not reported everywhere, however. In England, reported prevalence for ever use of e-cigarettes among school pupils aged 11–15 years was 25% in 2018, the same as in 20169. E-cigarettes are now the most commonly used tobacco product among young people in the US10.

A narrative review11 of e-cigarette prevalence in Europe among adults and young people found that ever use ranged from 5.5% to 56.6%. Current smokers of conventional cigarettes showed the highest prevalence for e-cigarette ever use with 20.4% to 83.1%, followed by ex-smokers with 7% to 15%. In European countries, there is a higher prevalence of e-cigarette use among males, adolescents and young adults, smokers of conventional cigarettes, and former smokers.

There are concerns that the growing popularity of e-cigarettes promotes tobacco experimentation, particularly among younger children12. A Welsh study of primary schoolchildren found that children as young as 7 years have general awareness of e-cigarettes. They perceived vaping to be healthier than smoking, had some recognition that e-cigarettes were used for smoking cessation but showed limited understanding of any health harms12.

The longitudinal analysis of Tokle13 found ‘a systematic pattern in which adolescents account for vaping as a time-limited trend’. Within this Norwegian sample, over a four-year period, e-cigarettes were devalued from novelty and transgression to childish and uninteresting, leading to the conclusion that e-cigarettes represented fashionable experimentation rather than steady user patterns. Among adolescent cigarette experimenters, using e-cigarettes has been found to be positively and independently associated with progression to current established smoking, suggesting that e-cigarettes ‘do not divert from, and may encourage, cigarette smoking in this population’14.

In Ireland, ESPAD 2019 findings show that, among children born in 2003 who ever used e-cigarettes, 67% have never smoked cigarettes1, representing a worrying new trend of initiation into nicotine addiction. From 1995 to 2015, smoking prevalence has been decreasing in Ireland, markedly so, among Irish teenagers15. Now, however, for the first time in 25 years this decrease has stalled, with prevalence rates (30-day use) among people aged 15–17 years in 2019 remaining the same (14.4%) as they were in 2015, accounted for by an increase in smoking prevalence among boys (16.2%), and a decrease among girls (12.8%)1. This halt in smoking prevalence reduction has been accompanied by a rising prevalence of e-cigarette use, particularly among boys, pointing to a possible link6,7.

The association between cigarette and e-cigarette use in teenagers is established but the mechanisms are uncertain. The longest-standing theory is the Gateway Theory16 which concerns the centrality of nicotine addiction in the progression to other drugs, but it is insufficient to explain fully the progression to cigarettes from e-cigarettes. The Common Liability Theory17 allows for wider inputs from environmental and genetic influences giving rise to the use of various tobacco products and psychoactive substances16-20, while the Catalyst Model18 helps consider the factors influencing initiation and progression, which could possibly extend to a diversion model preventing progression to smoking19. Although marketed as a smoking cessation tool, e-cigarettes are rarely used for this purpose in youth21. Among adolescents in Ireland, the main motivation for using e-cigarettes was curiosity (66%) and because friends offered (29%), while only 3.4% said that their motivation for beginning to use e-cigarettes was for smoking cessation1.

E-cigarette ever use has increased among people aged 15–17 years in Ireland from 18% to 37% between 2015 and 20191,22. Our aim in this study is to profile e-cigarette ever users and never users in this age group; to examine associations with e-cigarette use; and to suggest appropriate measures to reduce use. In our model, we include sociodemographic, personal, peer, and familial associations which are available in the ESPAD dataset and known to be associated with teenage substance use.


Design, sample, data collection

The ESPAD survey is the largest quadrennial cross-national project on adolescent substance use in the world, having the overall aim of repeatedly collecting comparable data on substance use among young people in some 35 European countries ( In the 2019 Ireland (Republic) arm of the ESPAD survey, a total of 3565 students aged 15, 16 and 17 years from a nationally representative, stratified random sample of 50 schools were surveyed. Data were collected between March and May 2019 and full accounts of the sampling, data collection and cleaning procedures have been reported elsewhere2. Following data cleaning, the final sample comprised 3495 students.

Dependent variable

Prevalence of e-cigarette ever use was measured by the question: ‘Have you ever used e-cigarettes?’, No; Yes, more than 12 months ago; Yes, in the last 12 months; and Yes, in the last 30 days; recoded as ever use, no versus yes.

Independent variables

Sociodemographic, personal, peer and familial characteristics are shown in detail with full question and answer categories in the Supplementary file and we summarize them here.

Sociodemographic variables included age, sex, parental education level, perceived family wealth, and household composition. Variables measuring personal risk behaviors as well as potentially protective behaviors were: use of cigarettes, alcohol, cannabis (including problem cannabis use (CAST [Cannabis Abuse Screening Test], a 6-item, 5-point scale, Cronbach’s alpha 0.83), inhalants, tranquilizers (with prescription); age of smoking and alcohol initiation; problems with social media use (3-item, 5-point Likert scale, Cronbach’s alpha 0.67), internet use (14-item, 5-point Likert scale, Cronbach’s alpha 0.92), online gaming (12-item, 5-point Likert scale, Cronbach’s alpha 0.95), and gambling; missing school due to truancy; reading books other than school books, actively participating in sport, having other hobbies, and average school grade. Variables measuring peer risk activities were: how many of their friends smoke, drink alcohol, get drunk, use cannabis, tranquilizers/sedatives, ecstasy, and inhalants. The variable ‘peer support’ measured friends’ help, support, sharing and communication (4-item, 7-point Likert scale, Cronbach’s alpha 0.94). Familial variables measured familial support (a 4-item, 7-point Likert scale, Cronbach’s alpha 0.92), relationship with parents, and household rules about smoking (smoking regulation).

Statistical analysis

Pearson’s χ2 test (for categorical variables) and Student’s t-test (for continuous variables) were conducted to compare differences in e-cigarette use between ever users and never users in relation to the independent variables above (Table 1). All variables in the study were adjusted by the dependent variable (e-cigarette ever use) using Spearman’s correlation coefficient and variance inflation factor (VIF) as appropriate between variables, and a VIF <5 was used to detect multicollinearity. A univariate logistic regression analysis was then performed to assess the association of e-cigarette ever use with the sociodemographic, personal, peer and familial characteristics of respondents. The results are presented in Table 2 as crude odds ratios (ORs) and their respective 95% confidence intervals (95% CIs). This was followed by a stepwise logistic regression analysis to assess predictors of e-cigarette ever use after entering all the variables in the model, and only variables with a p<0.7 were retained in the final model (Table 2). Adjusted odds ratios (AORs) and their 95% confidence intervals were estimated and associations with a p<0.05 were considered statistically significant. All analyses were performed using Stata version 16.

Table 1

Sample characteristics of e-cigarette ever users and never users aged 15–17 years (N=3495)

CharacteristicsTotal n (%)E-cigarette never users n (%)E-cigarette ever users n (%)p*
Total3495 (100)2209 (63.4)1278 (36.6)
Female1835 (52.5)1200 (65.6)630 (34.4)
Male1660 (47.5)1009 (60.9)648 (39.1)
Age (years)0.263
15796 (22.8)523 (65.7)272 (34.2)
161949 (55.7)1219 (62.7)724 (37.3)
17750 (21.5)467 (62.3)282 (37.7)
Father’s education level0.012
Some secondary school or completed primary school723 (24.4)423 (58.5)300 (41.5)
Completed secondary school608 (20.6)379 (62.3)229 (37.7)
College or university1628 (55.0)1057 (64.9)571 (35.1)
Mother’s education level<0.001
Some secondary school or completed primary school364 (11.8)245 (67.3)119 (32.7)
Completed secondary school681 (22.0)494 (72.5)187 (27.5)
College or university2046 (66.2)1236 (60.4)810 (39.6)
Perceived wealth0.217
About the same1473 (44.0)951 (64.6)522 (35.4)
Much better off523 (15.6)322 (61.6)201 (38.4)
Better off1032 (30.8)664 (64.3)368 (35.7)
Less well off321 (9.6)190 (59.2)131 (40.8)
Household composition0.499
Two parents2602 (78.4)1661 (63.8)941 (36.2)
One parent524 (15.8)321 (61.3)203 (38.7)
Blended families195 (5.9)121 (62.0)74 (38.0)
Average grade0.148
A and B1511 (45.7)990 (65.5)521 (34.5)
C1389 (42.0)862 (62.2)524 (37.8)
D or lower407 (12.3)254 (62.4)153 (37.6)
Read books<0.001
No2636 (76.9)1560 (59.2)1076 (40.8)
Yes794 (23.1)613 (77.2)181 (22.8)
Actively participate in sports0.906
No551 (15.9)350 (63.5)201 (36.5)
Yes2904 (84.1)1837 (63.3)1067 (36.7)
Other hobbiesa<0.001
No1484 (44.5)889 (59.9)595 (40.1)
Yes1854 (55.5)1229 (66.3)625 (33.71)
Age of alcohol initiation (years)<0.001
<13844 (35.8)333 (39.5)511 (60.5)
≥141514 (64.2)870 (57.5)644 (42.5)
Age of smoking initiation (years)0.001
<13374 (33.7)62 (16.6)312 (83.4)
≥14736 (66.3)185 (25.1)551 (74.9)
Drank to get high<0.001
No2873 (83.5)2036 (70.9)837 (29.1)
Yes568 (16.5)155 (27.3)413 (72.7)
Problems with social media use, mean ± SD2.77 ± 1.062.83 ± 1.072.68 ±1.03<0.001
Problems with internet use, mean ± SD2.57 ± 0.882.53 ± 0.862.65 ± 0.890.001
Problems with online gaming, mean ± SD1.57 ± 0.781.56 ± 0.761.58 ± 0.810.547
Need to bet more money<0.001
No3120 (92.3)2013 (64.5)1107 (35.5)
Yes261 (7.7)137 (52.5)124 (47.5)
Lied gambling frequency<0.001
No3290 (97.5)2107 (64.0)1183 (36.0)
Yes83 (2.5)36 (43.4)47 (56.6)
Skipping school (days)<0.001
02319 (79.4)1580 (68.1)739 (31.9)
1–4503 (17.2)236 (46.9)267 (53.1)
≥599 (3.4)33 (33.3)66 (66.7)
Absent due to illness (days)<0.001
01524 (47.8)1041 (68.3)483 (31.7)
1–41422 (44.6)850 (59.8)572 (40.2)
≥5241 (7.6)141 (58.5)100 (41.5)
Perceived risk in trying e-cigarettes once or twice<0.001
No1559 (45.3)723 (46.4)836 (53.6)
Slight1263 (36.7)946 (74.9)317 (25.1)
Moderate299 (8.7)250 (83.6)49 (16.4)
Great149 (4.3)117 (78.5)32 (21.5)
Don’t know117 (5.0)143 (83.1)29 (16.9)
Ever smoked cigarettes<0.001
Never2398 (68.8)1980 (82.7)415 (17.3)
Ever1084 (31.2)225 (20.8)859 (79.2)
Current smoking status<0.001
Yes3001 (86.2)2147 (71.5)854 (28.5)
No480 (13.8)62 (12.9)418 (87.1)
Ever alcohol use<0.001
Never891 (26.5)822 (92.3)69 (7.7)
Ever2478 (73.5)1339 (54.0)1139 (46.0)
Current alcohol use<0.001
No2018 (59.3)1606 (79.6)412 (20.4)
Yes1388 (40.7)569 (41.0)819 (59.0)
Current binge drinking<0.001
Never2326 (67.1)1797 (77.3)529 (22.7)
Ever1142 (32.9)405 (35.5)737 (64.5)
Ever cannabis use<0.001
Never2824 (81.6)2066 (73.2)758(26.8)
Ever635 (18.4)135 (21.3)500 (78.7)
Current cannabis use<0.001
No3135 (91.3)2152 (68.6)983 (31.4)
Yes300 (8.7)44 (14.7)256 (85.3)
Cannabis problem use, mean ± SD1.09 ± 0.361.01 ± 0.161.24 ± 0.01<0.001
Ever use of tranquilizers with prescription<0.001
Never3110 (89.93)2039 (65.6)1071 (34.4)
Ever349 (10.1)155 (44.1)194 (55.6)
Ever use of inhalants<0.001
Never3106 (89.7)2070 (66.6)1036 (33.3)
Ever357 (10.3)131 (36.7)226 (63.3)
Peer risk activities
Smoke cigarettes2309 (69.3)1462 (63.3)847 (36.7)0.627
Drink alcoholic beverages2924 (87.8)1085 (63.5)1068 (36.5)0.724
Get drunk2727 (82.2)1728 (63.4)999 (36.6)0.630
Smoke cannabis1634 (49.2)1035 (63.3)599 (36.7)0.901
Take tranquilizers/sedatives427 (12.9)274 (64.2)153 (35.8)0.767
Take ecstasy558 (16.8)350 (62.7)208 (37.3)0.672
Take inhalants515 (15.5)320 (62.1)195 (37.9)0.483
Familial regulation0.590
Know always2154 (64.0)1368 (63.5)786 (36.6)
Know quite often794 (23.6)514 (64.7)280 (35.3)
Know sometimes302 (9.0)188 (62.2)114 (37.7)
Usually don’t know116 (3.5)68 (58.6)48 (41.4)
Familial support, mean ± SD5.41 ± 1.695.40 ± 1.705.41 ± 1.680.865
Peer support, mean ± SD5.40 ± 1.655.42 ± 1.645.36 ± 1.660.310
Relationship with mother0.361
Very satisfied1749 (52.8)1119 (64.0)630 (36.0)
Satisfied1132 (34.2)726 (64.1)406 (5.9)
Not satisfied433 (13.1)262 (60.5)171 (39.5)
Relationship with father0.318
Very satisfied1402 (43.9)884 (63.1)518 (36.9)
Satisfied1085 (34.0)708 (65.2)377 (34.8)
Not satisfied707 (22.1)438 (61.9)269 (38.0)
Smoking regulation0.384
Nowhere1706 (58.6)1077 (63.1)629 (36.9)
Somewhere1131 (38.8)728 (64.4)403 (35.6)
Anywhere74 (2.5)42 (56.8)32 (43.2)
Relationship with mother0.361
Very satisfied1749 (52.8)1119 (64.0)630 (36.0)
Satisfied1132 (34.2)726 (64.1)406 (5.9)
Not satisfied433 (13.1)262 (60.5)171 (39.5)
Relationship with father0.318
Very satisfied1402 (43.9)884 (63.1)518 (36.9)
Satisfied1085 (34.0)708 (65.2)377 (34.8)
Not satisfied707 (22.1)438 (61.9)269 (38.0)

* Statistical significance at p<0.05.

a Other hobbies (play an instrument, sing, draw, write).

Table 2

Bivariate and multivariable (stepwise) logistic regression of e-cigarette ever use among people aged 15–17 years (N=3495)

CovariatesOR (95% CI)*AOR (95% CI)*
Age (years)
15 (Ref.)11
161.14 (0.96–1.35)0.79 (0.34–1.85)
171.16 (0.94–1.43)0.43 (0.117–1.08)
Father’s education level
Some secondary school or completed primary school (Ref.)11
Completed secondary school0.85 (0.68–1.06)2.10 (0.97–4.55)
College or university0.76 (0.64–0.91)-
Mother’s education level
Some secondary school or completed primary school (Ref.)11
Completed secondary school0.78 (0.59–1.03)3.46 (1.40–8.54)
College or university1.35 (1.06–1.71)-
Perceived wealth
About the same (Ref.)11
Much better off1.14 (0.92–1.40)0.48 (0.59–1.47)
Better off1.01 (0.86–1.19)0.49 (0.24–1.02)
Less well off1.26 (0.98–1.61)-
Household composition
Two parents (Ref.)11
One parent1.12 (0.92–1.35)1.34 (0.34–5.32)
Blended families1.07 (0.80–1.46)0.72 (0.17–3.11)
Average grade
A and B (Ref.)11
C1.15 (0.99–1.34)1.19 (0.66–2.16)
D or lower1.14 (0.91–1.44)1.40 (0.53–3.74)
Read books, no vs yes0.43 (0.36–0.51)0.32 (0.16–0.64)
Actively participate in sports, no vs yes1.01 (0.84–1.22)1.17 (0.57–2.41)
Other hobbies, no vs yes0.76 (0.66–0.87)1.38 (0.77–2.46)
Age of smoking initiation (years)
<13 (Ref.)11
≥143.49 (3.03–4.02)0.70 (0.36–1.35)
Skipping school (days)
0 (Ref.)11
1–42.42 (1.99–2.94)1.19 (0.62–2.89)
≥54.27 (2.79–6.55)0.57 (0.17–1.83)
Absent due to illness (days)
0 (Ref.)11
1–41.45 (1.25–1.69)1.17 (0.66–2.07)
≥51.53 (1.16–2.02)0.23 (0.09–0.61)
Perceived risk in trying e-cigarettes once or twice
No (Ref.)11
Slight0.29 (0.25–0.34)0.86 (0.46–1.58)
Moderate0.17 (1.22–0.23)0.20 (0.07–0.67)
Great0.24 (0.16–0.35)0.42 (0.07–2.56)
Don’t know0.17 (0.12–0.26)-
Ever use of cigarettes, never vs ever18.21 (15.2–21.83)4.15 (1.29–13.41)
Current cigarette use, no vs yes16.90 (12.83–22.39)1.64 (0.85–3.16)
Ever alcohol use, never vs ever10.13 (7.83–13.11)2.38 (0.31–18.52)
Current alcohol use, no vs yes5.61 (4.82–6.53)0.44 (0.20–0.96)
Current binge drinking, no vs yes6.18 (5.29–7.22)1.80 (0.91–3.55)
Cannabis ever use, no vs yes10.09 (8.20–12.42)2.21 (1.11–4.41)
Cannabis problem use16.79 (10.75–26.23)2.78 (0.97–7.99)
Ever use of inhalants, never vs ever3.45 (2.74– 4.33)2.51 (1.07–5.88)
Peer risk activities, no vs yes
Get drunk1.05 (0.87–1.26)1.32 (0.61–2.86)
Smoke cannabis1.01 (0.88–1.16)1.80 (0.93–3.47)
Take tranquilizers/sedatives0.97 (0.78–1.20)0.45 (0.15–1.35)
Take inhalants1.07 (0.88–1.30)1.54 (0.52–4.62)
Familial regulation
Know always (Ref.)11
Know quite often0.95 (0.80–1.12)0.52 (0.26–1.04)
Know sometimes1.05 (0.82–1.35)1.68 (0.45–6.22)
Usually don’t know1.23 (0.84–1.80)-
Peer support0.98 (0.94–1.02)1.06 (0.88–1.27)
Relationship with mother
Very satisfied (Ref.)11
Satisfied0.99 (0.85–1.16)1.45 (0.66–3.16)
Not satisfied1.16 (0.93–1.44)1.87 (0.63–5.52)
Relationship with father
Very satisfied (Ref.)11
Satisfied0.91 (0.77–1.07)-
Not satisfied1.05 (0.87–1.26)0.50 (0.20–1.22)
Smoking regulation
Nowhere (Ref.)11
Somewhere0.94 (0.81–1.11)0.53 (0.30–0.94)
Anywhere1.30 (0.81–2.09)0.54 (0.05–7.04)

AOR: adjusted odds ratio.

* Bold indicates statistical significance at p<0.05.


Characteristics of e-cigarette ever users, bivariate analyses

A total of 3495 students were included in the analysis. Sample characteristics of e-cigarette ever use among people aged 15–17 years are shown in Table 1. Overall, 36.6% (n=1278) of students in the sample had ever used e-cigarettes. Girls were more likely than boys to be never users (65.6%, n=1200). In these bivariate analyses, there were significant differences between e-cigarette ever users and never users according to: sex, parental education level, household composition, absenteeism, ever and current smoking, skipping school; ever, current, and binge alcohol use; ever, current, cannabis use and problem cannabis use; ever use of tranquilizers with or without prescription; perceived risks of smoking e-cigarettes; and familial regulation (p<0.05). E-cigarette ever use was higher than cigarette ever use. More than a third (36.6%) of the sample were e-cigarette ever users compared with 31.2% who were ever smokers and 17.3% (n=415) of those who had never tried combustible cigarettes were e-cigarette ever users. Bivariate analyses, shown in Table 2, indicate that respondents’ other risk behaviors – cigarette, alcohol, cannabis, and inhalant use – have the strongest associations with e-cigarette ever use.

Multivariable analysis of e-cigarette ever use

As with the bivariate analyses, multivariable analysis (Table 2) also shows that a respondent’s other risk behaviors have the strongest associations with e-cigarette ever use. Those who had ever tried cigarettes had an AOR of 4.15 (95% CI: 1.29–13.41, p<0.05) for e-cigarette ever use while those who had ever used cannabis had an AOR of 2.21 (95% CI: 1.11–4.41, p<0.05), and those who had ever used inhalants had an AOR of 2.51 (95% CI: 1.07–5.88, p<0.05).

Compared with respondents whose parents were less well-educated, respondents with mothers who had college or university education had significantly higher odds of e-cigarette ever use (AOR=3.46; 95% CI: 1.40–8.54, p<0.05). A small number of variables had significantly lower adjusted odds ratios for e-cigarette ever use, including reading books (excluding schoolbooks) for enjoyment (AOR=0.32; 95% CI: 0.16–0.64, p<0.05), living in a household where some rules or restrictions pertained in relation to smoking cigarettes in the house (AOR=0.53; 95% CI: 0.30–0.94, p<0.05), and perceiving moderate (AOR=0.20; 95% CI: 0.07–0.67, p<0.05) risk in using e-cigarettes even once or twice. Current alcohol use was also negatively associated with e-cigarette ever use (AOR=0.44; 95% CI: 0.20–0.96, p<0.05).


Sociodemographic influences: social class, sex, and household composition

To date, findings about e-cigarette use and social class have been ambivalent. Recent Irish research found that, in a sample in which smoking was patterned by social class, e-cigarette ever use was not23. This study found that perceived relative wealth was not statistically significantly associated with e-cigarette ever use but that parental education level was. This suggests some differences in teenagers’ views and motivations regarding e-cigarettes compared with cigarettes. The association between smoking and lower socioeconomic status is well-established, but the association with other substances is more ambivalent. For example, young adults with the highest family background SES have been found to be most prone to alcohol and marijuana use, even after adjusting for covariates24. They have also been found to be more likely to use other drugs, and to use alcohol and other substances to cope with stress25. Our findings about increased e-cigarette ever use among people aged 15–17 years with higher-educated mothers (AOR=3.46; 95% CI: 1.40–8.54) may indicate that e-cigarette ever use has more in common with alcohol and other drug use than it has with smoking or that more-educated parents have different attitudes to e-cigarettes than less-educated parents.

Other familial behaviors and supports were also implicated in adolescent e-cigarette ever use. Even after adjusting for covariates, living in a household where some rules or restrictions were in place regarding whether or where people could smoke in the house lowered the odds of people aged 15–17 years e-cigarette ever use (AOR=0.53; 95% CI: 0.30–0.94)

Parental anti-smoking communication and encouragement reduces teenage smoking26. Our findings extend the role of parental influence, including having no-smoking rules in the home, from cigarette smoking to e-cigarette ever use, suggesting an encouraging role for parents in reducing nicotine consumption in teenagers.

Personal behaviors

Polysubstance use is highly prevalent among adolescents who use e-cigarettes27. E-cigarette ever use was strongly associated with ever use of tobacco, cannabis, and inhalants, and the association was especially strong for cigarette smoking. Risk-taking, indicated by experimenting with many substances, may be implicated in e-cigarette ever use and these findings provide some support for the common liability theory17. We agree28 that e-cigarette screening should include the assessment of other substances, especially cigarettes, alcohol, and cannabis, with a view to identifying and implementing prevention efforts and improving population health.

When we adjusted for covariates in our regression model, reading books for enjoyment remained protective against e-cigarette ever use (AOR=0.32; 95% CI: 0.36–0.51). Perceiving moderate risk in using e-cigarettes is indicated as protective against e-cigarette ever use (AOR=0.20; 95% CI: 0.07–0.67), suggesting a role for health education in providing clear, focused, up-to-date information for adolescents about the risks of e-cigarette ever use. Efforts should be stepped up in the junior cycle of post-primary schooling to develop health education curricula that are appropriate in terms of content, pedagogy, resources and evaluation29.

Peer influences

Studies have shown that adolescents are more likely to engage in risky behaviors in the presence of peers30,31. In our model, we tested correlations between all peer substance use [use of tobacco, alcohol (including getting drunk), cannabis, tranquilizers/sedatives, ecstasy, inhalants] and e-cigarette ever use and increased odds ratios were noted but data were not sufficiently sensitive to detect differences.

Experimentation, continuation, and cessation

E-cigarette ever use is largely associated with teenagers’ other substance use. Experimentation is widely recognized as a feature of adolescence and others have drawn ‘a positive, linear relation between substance use and psychopathology, such that the more frequently children and adolescents use illegal substances, the greater their risk for exhibiting internalizing or externalizing psychiatric disorders’32, suggesting that complete abstinence among children and adolescence is seen as a desirable outcome. At a minimum, an increased proportion of those who ever use e-cigarettes experimentally will go on to become addicted users of nicotine33, or possibly dual users of e-cigarettes and combustible tobacco34,35. Marijuana use has also been found to increase at a faster rate among e-cigarette users when compared to their peers who used cigarettes or a combination of cigarettes and e-cigarettes (dual users)36. Unlike tobacco, e-cigarettes in Ireland are currently largely unregulated. The findings suggest a role for health education highlighting the important link in e-cigarette ever use with peer and personal polysubstance use.


The study captures the associations of ever use of e-cigarettes at a point in time of school-going people aged 15–17 years in Ireland. It cannot tell us about the small percentage of students who do not attend school in Ireland at that age and may be different. ESPAD questionnaires are completed by students in a school setting therefore self-reporting bias is a consideration. Social desirability bias is a further consideration given the sensitive nature of the behavior under study – teenage substance use. Also, e-cigarette use is changing rapidly so advice on regulation and control needs regular up-dating. The use of the stepwise regression method produces confidence intervals around the parameter estimates that are too narrow and p-values that are too low due to multiple comparisons. Longitudinal and qualitative studies are certainly needed to improve our understanding and predictions for the future, but these exploratory analyses give us valuable insights in the present situation.


E-cigarette ever users are more likely to be male and to have higher-educated mothers. While sex and parental education level are associated with e-cigarette ever use, our multivariable analyses show that these influences wane in comparison with teenagers’ personal risk behaviors, particularly in terms of their polysubstance use, but cigarette use is the most strongly associated with e-cigarette ever use with odds greater than 4 times. Our findings emphasize the importance and usefulness of regulation of cigarette smoking in the home in preventing ever use of e-cigarettes. The perception of risk of e-cigarette use is also shown to be associated with ever use and this also may be influenced by e-cigarette regulation in the home. Education at school about e-cigarette use is largely absent or inadequate in many European countries, including Ireland, and needs strengthening29. Parents are important modifiers of adolescents’ nicotine use and we recommend that school-based education be extended to include interventions aimed at parents. Parental attitudes on the dangers of teenagers’ e-cigarette ever use are not well-known and need further study.