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Looking beyond cigarettes: Are Ontario adolescents with asthma less likely to smoke e-cigarettes, marijuana, waterpipes or tobacco cigarettes?
Accepted Manuscript Looking beyond cigarettes: Are Ontario adolescents with asthma less likely to smoke e-cigarettes, marijuana, waterpipes or tobacco cigarettes? Kristian Larsen, Guy E.J. Faulkner, Angela Boak, Hayley A. Hamilton, Robert E. Mann, Hyacinth M. Irving, Teresa To PII:
S0954-6111(16)30243-8
DOI:
10.1016/j.rmed.2016.09.013
Reference:
YRMED 5014
To appear in:
Respiratory Medicine
Received Date: 8 July 2016 Revised Date:
30 August 2016
Accepted Date: 19 September 2016
Please cite this article as: Larsen K, Faulkner GEJ, Boak A, Hamilton HA, Mann RE, Irving HM, To T, for the Canadian Respiratory Research Network, Looking beyond cigarettes: Are Ontario adolescents with asthma less likely to smoke e-cigarettes, marijuana, waterpipes or tobacco cigarettes?, Respiratory Medicine (2016), doi: 10.1016/j.rmed.2016.09.013. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Looking beyond cigarettes: Are Ontario adolescents with asthma less likely to smoke e-cigarettes, marijuana, waterpipes or tobacco cigarettes? Kristian Larsen, PhD1,2 Guy EJ Faulkner, PhD3,4 Angela Boak, MA2, Hayley A Hamilton PhD2,5 Robert E Mann, PhD2,5 Hyacinth M Irving, MA6 Teresa To, PhD1,5 for the Canadian Respiratory Research Network 1
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Corresponding author: Kristian Larsen 686 Bay St. Toronto, ON M5G 0A4 [email protected] or [email protected] 416-813-7654 x 328384
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Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto; Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto; 3 Faculty of Kinesiology and Physical Education, University of Toronto, Toronto; 4 School of Kinesiology, University of British Columbia, Vancouver; 5 Dalla Lana School of Public Health, University of Toronto, Toronto; 6 Centre for Global Health Research, St. Michael’s Hospital, Toronto; 2
Take home message: Adolescents with asthma in Ontario, Canada had a significantly higher odds of smoking e-cigarettes or any substance.
Number of tables: 2
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Word count: 3,380
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Acknowledgements: Kristian Larsen received a Postdoctoral Fellowship, in part, through the Hospital for Sick Children Research Training Centre and the Canadian Respiratory Research Network (CRRN), supported by grants from the Canadian Institutes of Health Research (CIHR) - Institute of Circulatory and Respiratory Health; Canadian Lung Association (CLA)/Canadian Thoracic Society (CTS); British Columbia Lung Association; and Industry Partners Boehringer-Ingelheim Canada Ltd, AstraZeneca Canada Inc., and Novartis Canada Ltd. Data were provided from the 2013 Ontario Student Drug Use and Health Survey (OSDUHS). Disclosure: The authors declare that they have no conflict of interest. Ethical statement: This study was approved by the research ethics board at The Hospital for Sick Children.
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Looking beyond cigarettes: Are Ontario adolescents with asthma less likely to smoke e-cigarettes, marijuana, waterpipes or tobacco cigarettes? Abstract:
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Objectives: The purpose of this paper is to examine whether high school students in Ontario with asthma smoke cigarettes, waterpipes, marijuana or e-cigarettes more or less than those without asthma.
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Methods: The 2013 Ontario Student Drug Use and Health Survey provides self-report data on tobacco cigarettes, waterpipes, marijuana and e-cigarette smoking and asthma rates from 109 high schools in Ontario, Canada. Individual and social characteristics were also collected. Multiple binary logistic regression models measures the association with the various types of smoking in relation to asthma.
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Results: Adolescents with asthma have higher odds of smoking e-cigarettes or smoking any type including smoke either cigarettes, waterpipe, marijuana or e-cigarettes. Respondents of lower socioeconomic status had a higher odds of smoking marijuana or any type. Boys were more likely to smoke waterpipes, e-cigarettes or any type, while students in higher grades had a higher odds of smoking cigarettes, waterpipes, marijuana or any type.
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Conclusions: Results from this study suggest that adolescents with asthma have a higher odds of smoking e-cigarettes than those without asthma, but no relationship was found for cigarettes, waterpipes or marijuana. Findings present some new challenges as technology changes how adolescents can smoke. Public health campaigns should target adolescents, especially those with asthma, to raise their awareness of the risks of all types of smoking including e-cigarettes.
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Looking beyond cigarettes: Are Ontario adolescents with asthma less likely to smoke e-cigarettes, marijuana, waterpipes or tobacco cigarettes?
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Tobacco smoke can cause numerous health related issues. While cigarette smoking is associated with the development of certain respiratory diseases [1], the causal link between the onset of asthma and smoking has not been established. To date, studies that examined the association between cigarette smoking and incident asthma have shown mixed results [2,3,4,5]. Previous work on the topic has
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reported an increased risk for adults [6] and adolescents [4,5] but others reported no statistically significant associations [2,3].
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Although what causes the onset of asthma is still relatively unknown, experts in the field have reported that cigarette smoking or exposure to second hand smoke can certainly trigger asthma symptoms and severity [7]. Overall cigarette smoking or second hand smoke can relate to many long term respiratory health issues, but it can also influence more immediate issues for people with asthma
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including increased coughing and airway inflammation [8]. For adults in California, cigarette smoking was associated with asthma severity, worse asthma-specific quality of life and greater hospitalization for asthma [9]. Furthermore, active cigarette smoking for people with asthma can lead to accelerated loss
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of lung function and a decreased response to corticosteroids over time [10]. In the past, studies on smoking behaviour in adolescents was focused on cigarette use; however,
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more recently other types of smoking such as waterpipes, marijuana or now electronic cigarettes (ecigarettes) have emerged as a concern. Waterpipes (also known as hookah or shisha) have become more popular in North America in recent years due to the belief that it is a safer alternative to cigarettes [11]. This is a common misconception in young adults [12,13], as a waterpipe smoking session can contain over 100 times the amount of smoke in comparison to a single cigarette [14]. In Ontario, the rate of trying waterpipes in adolescents has more than doubled from 6% in 2006 to 14% in 2013 [15]. Waterpipe smoking is linked to several adverse health outcomes such as cancer, cardiovascular disease 3
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and decreased lung function [16,17,18]. While the causal effect of waterpipe smoke and asthma has not been demonstrated, exposure to tobacco smoke was shown to exacerbate asthma symptoms [19]. Since waterpipes produce tobacco smoke, it can be assumed that it will be harmful especially for those
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with asthma.
The relationship between marijuana smoking and asthma is somewhat complex. Marijuana has been used as a forbidden medicine to treat asthma symptoms for years as it may have bronchodilator
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properties [20], while long term marijuana smoking has also been associated with increased respiratory symptoms [21]. Overall, the relationship between marijuana and lung health is somewhat mixed and
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the connection may not be the same as tobacco smoke [22,23]. Previous research has suggested that adolescents with asthma smoked significantly more marijuana than those without asthma [24]. However, the number of adolescents (aged 15-24) who smoked marijuana in Canada has decreased from 32.7% in 2008 to 24.4% in 2013 [15,25].
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Electronic cigarettes are battery powered devices that vaporise nicotine and/or other flavouring mixes, but do not burn tobacco. These products have become popular in recent years and they are perceived as a safer alternative to tobacco cigarettes [26,27,28]. While preliminary studies suggest that
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they may be less harmful than cigarettes, the long term health effects and how e-cigarettes relate to asthma symptoms or severity are unknown [29]. The Canadian Tobacco, Alcohol and Drug Survey
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reported that as many as one in five (20%) adolescents aged 15-19 tried e-cigarettes [15], however, the absolute trend of usage is still unknown as these products are relatively new. The purpose of this paper is to examine whether adolescents (aged 12-19 or in grades 9 to 12)
with asthma smoke cigarettes, waterpipes, marijuana or e-cigarettes more or less than those without asthma. This study adds to the current literature by examining all smoking habits for youth with asthma, rather than focusing just on cigarettes.
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Methods Data source and study population: The 2013 Ontario Student Drug Use and Health Survey (OSDUHS) is a population based survey conducted every two years and completed by grade 7-12 students at publically
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funded schools in Ontario, Canada. Ontario is the largest province in Canada with a population of over 13 million residents. Ontario includes major urban centres such as Toronto and Ottawa, several smaller cities and an abundance of rural lands.
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The OSDUHS is designed to collect information about drug use and other health related
behaviours among students in Ontario. All parents and students gave consent prior to participation. To
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examine the association between smoking and asthma, we limit our study sample to high school students (grades 9-12, n=6,159) in 109 schools. These schools were selected with probability proportional to size, to obtain a representative sample within the province. The survey included questions that captured information on self-reported doctor diagnosed
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asthma and data on tobacco, alcohol and drug use. The survey used a random split-ballot design where some of the questions change on each of the surveys. The sample is randomly divided into 2 groups to maximize questions included and minimize burden on students, but it reduces the sample size for some
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questions. In the OSDUHS, approximately half of the full sample answered questions pertaining to asthma and all types of smoking reducing the subsample to 2,840. Data are representative of students
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in Grades 9 to 12 attending publicly funded schools in Ontario. Ages for respondents range from 12-19 years of age (mean: 15.86 years; standard deviation 1.27). In Ontario, the majority of children (92%) attended publically funded schools [30], 5% attended private schools [31], and another 3% were either home schooled, institutionalized for correctional or health reasons, schooled on a First Nation reserve (indigenous communities), military base or lived in remote northern region [30]. This study was approved by the research ethics board at the Research Institute of The Hospital for Sick Children (SickKids) (Toronto, Ontario, Canada).
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Variables Outcome measures: The primary outcome variables in this study are smoking status with regard to
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cigarettes, waterpipes, marijuana and e-cigarettes. Self-reported frequency and intensity of cigarette, waterpipe, marijuana and e-cigarette smoking in the last 12 months and lifetime use were measured in the survey. Cigarette non-smokers were classified as those who never smoked a cigarette or smoked
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less than (or equal to) one cigarette in the last 12 months, while cigarette smokers were those who smoked more than one cigarette in the past 12 months. Similarly, smoking status for waterpipe was
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also classified as a binary outcome variable. Respondents were asked how often they smoked a waterpipe (or hookah, shisha, bubble-bubble, gouza) in the last 12 months. Those who smoked a few puffs, never smoked, haven’t smoked in the past 12 months or didn’t even know what it was were considered non-waterpipe smokers. Those who smoked one or more times were defined as smokers.
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Marijuana smoking is also defined in a similar manner. Students were asked how often they smoked cannabis (or marijuana, weed, pot, grass, hashish, hash) in the past 12 months. If they smoked 1 or more times in the past year they were classified as a marijuana smoker. Respondents who have never
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or not smoked in the last 12 months were considered to be non-marijuana smokers. Finally, respondents were classified as e-cigarette smokers if they smoked an e-cigarette with or without
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nicotine in it, while those who have never smoked or never heard of e-cigarettes were considered nonsmokers.
Covariates: The primary risk factor of interest is the presence of asthma which is captured by the response to the question “has a doctor or nurse ever told you that you have asthma”. Other potential confounding variables include: grade (9-12), sex and socioeconomic status (SES). SES was measured by a 10-point social ladder. Students were asked to imagine that the ladder represents how Canadian society
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is set up, where the people at the top of the ladder are the “best off”, meaning they have the best jobs, make the most money and have the highest education. Those at the bottom of the ladder are the “worst off”, with no job, or a job no one wants, little education and the least money. Respondents
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reported what best represents their family on a 10-point scale, which was further grouped into three levels (1–6=low; 7–8=middle; 9–10=high) based on the interquartile ranges.
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Statistical analysis
The percent distributions of demographic characteristics and other covariates were compared between
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smokers and non-smokers of each type (cigarettes, waterpipes, marijuana, e-cigarettes) and the any smoking variable. The chi-square test was used to measure statistical significance between the respondents with and without asthma. Each type of smoking was modelled separately using a binary logistic regression. In addition to doctor diagnosed asthma (the main exposure), all covariates outlined
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above were included in the regression models. All interactions of smoking types were examined but no significant relationships were found so this study focussed on the four individual models, plus the combined any smoking outcome. The following was used as the reference group in the logistic
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regression models: grade 9, female and high SES. Given the OSDUHS used a probability stratified cluster sampling design, all analyses were conducted with the sampling weights and utilized Taylor series
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methods within Stata 14 v14.1 to derive unbiased standard errors and point estimates. Results of the regression models were presented in adjusted odds ratios (OR) with 95% confidence intervals (CI). Goodness of fit tests were completed with the F-adjusted mean test.
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Results Overall, the majority of the grade 9-12 students did not smoke cigarettes, waterpipes, marijuana or ecigarettes (Table 1). Approximately 1 in 7 smoked e-cigarettes, 1 in 8 smoked waterpipes, 1 in 9 smoked
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cigarettes, but more than 1 in 4 smoked marijuana or 1 in 3 smoked any type of product. Among students who reported having asthma, the percentage who smoked tended to be higher than the
percentage who did not smoke, however differences were statistically significant only for e-cigarettes
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and the any smoking variable.
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Table 1: Descriptive statistics for the weighted sample (percentages)
Cigarettes Smokers 10.9
Waterpipes Smokers 12.6
Marijuana Smokers 28.8
E-cigarettes Smokers 14.3
78.7 21.3
10.4 12.8
12.0 14.8
27.5 33.6
12.6 20.5
36.0 44.9
64.0 55.1
21.4 22.2 23.9 32.5
3.9 8.9 13.0 16.0
4.3 8.7 15.2 18.9
12.3 24.3 34.3 38.5
12.6 13.7 14.3 15.7
22.4 31.7 43.5 48.4
77.6 68.3 56.5 51.6
12.0 9.8
14.5 10.6
30.1 26.4
18.3 9.9
42.1 33.5
57.9 66.5
15.6 11.6 10.2
32.5 28.6 21.9
13.8 14.2 15.9
41.7 38.0 30.2
58.3 62.0 69.8
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51.9 48.0 32.9 53.8 13.2
Any smoking Smokers Non-smokers 37.9 62.1
15.1 9.0 8.6
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Total percentage Asthma status Without asthma With asthma Grade 9 10 11 12 Sex Male Female SES Low Middle High
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Full sample
Smoking cigarettes
Table 2 shows the results from the logistic regression that estimated the association of cigarette smoking (response) and asthma (exposure) while adjusting for other covariates. After adjusting for grade, sex and SES, the association of asthma and cigarette smoking was nonsignificant [OR:1.19; CI:0.79-1.78]. Grade was the only variable significantly associated with smoking cigarettes. The odds of
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cigarette smoking increased exponentially with grade. Compared to grade 9 students, the odds of cigarette smoking were 6-fold in grade 12 students [OR:6.07; CI:3.44-10.70].
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Table 2: Binary logistic regression estimation results with the various types of smoking as dependent variable (n=2,809) Waterpipes
Any type of smoking
Upper 1.765
OR 1.311
Lower 0.906
Upper 1.896
OR 1.784
Lower 1.153
Upper 2.762
OR 1.41
Lower 1.04
Upper 1.93
3.454 6.317 7.793
2.281 3.680 4.365
1.519 2.563 2.909
3.423 5.283 6.550
1.113 1.175 1.283
0.620 0.737 0.719
1.997 1.872 2.288
1.61 2.67 3.22
1.13 1.87 2.17
2.30 3.82 4.78
1.976
1.241
0.891
1.729
1.999
1.367
2.925
1.44
1.05
1.99
2.500 1.631
1.509 1.340
1.001 0.917
2.277 1.960
0.788 0.841
0.456 0.525
1.361 1.348
1.48 1.34
1.01 0.94
2.16 1.91
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Smoking waterpipes
E-Cigarettes
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OR Lower Upper OR Lower Asthma1 1.185 0.789 1.778 1.205 0.823 2 Grade 10 3.249 1.913 5.519 2.085 1.259 11 4.786 2.699 8.483 3.942 2.460 12 6.071 3.444 10.701 4.969 3.169 Sex3 Male 1.269 0.832 1.935 1.438 1.047 4 SES Low 1.661 0.847 3.258 1.411 0.796 Middle 0.967 0.501 1.864 1.064 0.694 1 Respondents with asthma, no asthma is the referent; 2 Grade 9 is the referent; 3 Female is the referent; 4 High SES is the referent; Significant variables in bold when p< 0.05; OR: Odds ratio
Marijuana
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Cigarettes
For waterpipe smoking there was once again no significant relationship between asthma prevalence and smoking (Table 2). Results were similar to that of cigarettes as grade was again significant, with the
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CI:1.05-1.98].
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exception that when compared to girls, boys had a 44% higher odds of smoking waterpipes [OR:1.44;
Smoking marijuana
Student’s grade and SES were the only significant factors related to smoking marijuana (Table 2). Being in grade 10 increased the odds of smoking marijuana by over 2 times [OR:2.28; CI:1.52-3.42], while students in grades 11 and 12 had even higher odds of smoking marijuana [OR:3.68; CI:2.56-5.28 and OR: 4.37; CI: 2.91-6.55]. Smoking marijuana was also associated with lower SES classification [OR:1.51;
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CI:1.01-2.28], when compared to peers from the highest SES. While asthmatic adolescents had an odds ratio for smoking marijuana of 1.31 [CI:0.91-1.9], this finding was again not significant.
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Smoking e-cigarettes
E-cigarettes produced very different results in the modelled analysis. Grade and SES were not significant factors, and looking at the odds ratios for these variables, there is very little difference between each
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category (Table 2). Grade for instance has nearly the same odds ratio for grades 10 and 11 [OR:1.11; CI:0.62-2.00, OR:1.18; CI:0.74-1.87]. The significant factors related to smoking e-cigarettes were asthma
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prevalence and sex. Adolescents with asthma were nearly 1.8 times more likely to smoke e-cigarettes than those without asthma [OR:1.78; CI:1.15-2.76]. As well, compared to girls, boys had a 2-fold odds of smoking e-cigarettes [OR:2.00; CI:1.37-2.93].
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Any smoking
Having doctor diagnosed asthma was significantly associated with a higher odds of smoking any type of substance (Table 2) [OR:1.41; CI:1.04-1.93]. Compared to girls, boys were also significantly more likely
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to smoke, as were respondents of lower SES. The results for grade were similar to many of the previous
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models, as the odds of smoking any substance becomes higher as you enter grade 10, 11 or 12.
Discussion
While cigarette smoking may aggravate symptoms and severity for adolescents with asthma, some work on the topic suggests that the prevalence of cigarette [32], waterpipe [11] and marijuana [24] smoking was actually higher in adolescents with asthma than those without. These studies, however, are not conclusive as at least one reported that adolescents with asthma were less likely to smoke cigarettes
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[33]. It is reasonable to suppose that adolescents with asthma will not smoke as it will aggravate their asthma severity and symptoms [7], but this unfortunately may not be the case. Our study showed that students in grades 9-12 with asthma in Ontario, had a higher odds of
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smoking any substance than their peers who do not have asthma. The odds of smoking e-cigarettes for adolescents with asthma, was nearly twice as high as those without asthma after adjusting for age, sex and SES. Given the cross-sectional design of the survey, we cannot infer the causal relationship between
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smoking and asthma. Previous studies suggest that smoking for adolescents with asthma may relate to the desire to obtain social status among one’s peers [34], and not wanting asthma to interfere with their
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social status.
Of all demographic characteristics studied, student's grade was most significantly associated with smoking cigarettes, waterpipes and marijuana. A longitudinal study in the United States found that rates of cigarette smoking increased from 1.8% at the age of 9 to 22.5% by age 16 years [35]. Findings
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suggest that rates for smoking cigarettes and waterpipes among grade 9 students were relatively low (3.9% and 4.3%), but doubled in grade 10, tripled by grade 11 and quadrupled by grade 12 (Table 1). Cigarette and waterpipe smoking became more popular in grade 10 and the trend continued as they
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aged. E-cigarette smoking on the other hand only marginally increased from grade 9 to 12 (12.6% in grade 9 versus 15.7% in grade 12). For adolescents with asthma, rates of e-cigarette smoking were
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similar to that of the entire sample, ranging from about 10% in grade 9 to 16.7% in grade 12. Our study also showed that cigarette, marijuana and any smoking rates were inversely related
to SES, where lower SES was associated with higher odds of smoking. Our finding is consistent with the literature that suggests an inverse relationship between individual SES or parental education and cigarette smoking in adolescents [36]. It has been suggested that lower SES households may have a poorer attitude towards health, fewer opportunities or more stressful situations which make them more
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likely to smoke [36]. Results from our study emphasise the need for tailored interventions for youth from lower SES households. This study had many strengths which relate to the size and generalizability of the survey sample
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but also the fact that it examined how all types of smoking related to asthma prevalence. That being said, there are also some limitations. Firstly, the primary purpose of this survey is to examine health risk behaviours of adolescents in Ontario and not asthma. As such, the number of respondents with asthma
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was low and this may have contributed to some of the insignificant findings. Despite the low number of asthma respondents, the self-reported asthma prevalence rate of adolescents in this study (21%) was
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similar to that reported (25%) by the Ontario Asthma Surveillance Information System (aged 15-19 years), which uses a validated health administrative data case definition to capture asthma with 84% sensitivity and 76% specificity [37]. Secondly, the cross-sectional design of the survey is a major study limitation in assessing causal relation of asthma and smoking. It is unknown from this study whether
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adolescents with asthma smoked e-cigarettes more often or if smoking e-cigarettes contributed to the risk of asthma. Thirdly, asthma was self-reported and it not clinically confirmed. Self-reported asthma may over or under represent actual prevalence of asthma. Furthermore, many studies (ours included)
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that examined the relationship between asthma and smoking did not separate severe or “uncontrolled” asthma from those with well-controlled mild to moderate asthma. The effect of smoking on adolescents
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with severe or uncontrollable asthma may be different than on those with mild to moderate asthma. The definition of smoking used may influence the study findings. We classified smoking for cigarettes, marijuana and waterpipes as smoking one or more time over the past 12 months or ever for ecigarettes. This definition includes those who smoke regularly but also adolescents who experiment with the various types of smoking. This classification of smoking has been used previously in studies using the OSDUHS dataset [e.g., 38]. We conducted additional analyses using another method of classifying smokers reported by Wong and colleagues [39]. In this method a regular smoker is defined as
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smoking more than 100 cigarettes in their lifetime and any cigarettes in the past month. Using this method the results and point estimates remained very similar. Given this method of classification was only available for cigarettes, we opted to retain the ‘any cigarettes over the past 12 months’ method to
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ensure measurement correspondence with the other types of smoking (i.e., marijuana, e-cigarettes and waterpipes). Nevertheless, results suggest that adolescents with asthma are at least experimenting with e-cigarettes or any type of smoking more often than their peers without asthma, which may lead to
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higher smoking rates later in life. Finally, we were unable to adjust for parental smoking or parental history of asthma as these data were not collected by the survey. Having a parent who smokes may
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relate to the respiratory health of children, but it also increases the odds of smoking for adolescents [40]. While information on parental smoking is not available in our data, further research should examine the association between parental smoking and asthma for all types of smoking. This paper adds discussion to the question of whether adolescents with asthma would be less
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likely to smoke cigarettes, waterpipes, marijuana or e-cigarettes. Our study findings suggest that adolescents with asthma had a significantly higher odds of smoking e-cigarettes or any substance. This may suggest a lack of knowledge of the potential harmful long term effects of smoking e-cigarettes or a
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general perception that e-cigarettes are “safer” than tobacco cigarettes [41]. While recent research has suggested that e-cigarettes are less harmful than tobacco cigarettes [42], the long term effects are still
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unknown. Furthermore, a recent study reported that e-cigarette usage for adolescents increases the odds of smoking tobacco cigarettes in adulthood by six times [OR:6.17; CI:3.3-11.6], suggesting that ecigarettes may be used as a gateway among teens [43]. Public health campaigns and education should target adolescents and especially those with asthma to raise their awareness of the risks (or potential risks) of all types of smoking. Results from this study suggest that adolescents with asthma are not more likely to be smoking cigarettes, waterpipes or marijuana than those without asthma. As the means (technology) of smoking
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change, how adolescents can smoke (such as via e-cigarettes), presents new challenges in relation to adolescent smoking and asthma. This study found that adolescents with asthma were more likely to smoke e-cigarettes than those without. The results did not change when we included any type of
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smoking. Our study findings can be used to target the adolescent asthma population for smoking
prevention and education campaigns and to raise their awareness of the risks associated with smoking in general. Although recent studies have reported that adolescents with asthma are more likely to
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smoke cigarettes or waterpipes [11,32], this does not appear to be the case in Ontario, after adjusting for confounding variables. While this is encouraging, our study suggests that e-cigarettes are now
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popular among youth with asthma. Work should continue with anti-smoking and prevention campaigns to try and further reduce all smoking rates for adolescents, with an emphasis on the unknown and potential serious long term risks associated with e-cigarettes or alternative types of smoking.
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22 Tashkin DP. Effects of marijuana smoking on the lung. Ann Am Thorac Soc 2013;10:239-247. 23 Callaghan RC, Allebeck P, Sidorchuk A. 2014. Cannabis use and risk of lung cancer: a 40-year cohort study of Swedish men. Eur J Pub Health 2014;24:162-139. 24 Jones SE, Merkle S, Wheeler L, Mannino DM, Crossett L. Tobacco and other drug use among high school students with asthma. J Adolesc Health 2006;39:291-294. 25 Health Canada. Canadian Alcohol and Drug Use Monitoring Survey (CADUMS). Ottawa, ON, Health Canada, 2012. 26 Caponnetto P, Russo C, Bruno CM, Alamo A, Amaradio MD, Polosa R. Electronic cigarette: A possible substitute for cigarette dependence. Monaldi Arch. Chest Dis 2013;79:12–19.
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27 Polosa R, Rodu, B, Caponnetto P, Maglia M, Raciti C. A fresh look at tobacco harm reduction: The case for the electronic cigarette. Harm Reduct. J 2013;10-19. 28 Hamilton HA, Ferrence RG, Boak A, Schwartz R, Mann RE, O’Connor S, Adlaf EM. Ever use of nicotine and nonnicotine electronic cigarettes among high school students. Nicotine Tob Res 2015;17:1212-1218.
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29 Hajek P, Etter JF, Benowitz N, Eissenberg T, McRobbie H. Electronic cigarettes: Review of use, content, safety, effects on smokers, and potential for harm and benefit. Addiction 2004;109:1801-1810. 30 Boak A, Hamilton HA, Adlaf EM, Mann RE. Drug use among Ontario students, 1977-2013: Detailed OSDUHS findings. Toronto, ON1,Centre for Addiction and Mental Health, 2013.
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31 Clemens, J, Palacios M, Loyer J, Fathers F. Measuring choice and competition in Canadian education: An update on school choice in Canada. Vancouver, BC, Fraser Institute, 2014.
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32 Precht DH, Keiding L, Madsen M. Smoking patterns among adolescents with asthma attending upper secondary schools: A community-based study. Pediatrics 2003;11:562-568. 33 Brook U, Shiloh S. Attitudes of asthmatic and nonasthmatic adolescents toward cigarettes and smoking. Clin Pediatr Phila 1993;32:642-646. 34 Spijkerman R, Van Den Eijnden RJ, Engels RC. Self comparison processes, prototypes, and smoking onset among early adolescents. Preventive Medicine 2005;40:785-794. 35 Mahabee-Gittens E, Xiao Y, Gordon JS, Khoury JC. The dynamic role of parental influences in preventing adolescent smoking initiation. Addict Hehav 2013;38:1905-1911.
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36 Mathur C, Erickson DJ, Stigler MH, Forster JL, Finnegan JR. Individual and neighborhood socioeconomic status effects on adolescent smoking: A multilevel cohort-sequential latent growth analysis. Am J Public Health 2013;103:543-548.
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37 Ontario Asthma Surveillance Information System (OASIS). Asthma Statistics. http://lab.research.sickkids.ca/oasis/wp-content/uploads/sites/6/2016/06/asthma_prevrt_up-to-2014.pdf. Date last assessed: June 13, 2016.
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38 Faulkner GEJ, Adlaf EM, Irving HM, Allison KR, Dwyer J. School disconnectedness: Identifying adolescents at risk in Ontario, Canada. J School Health 2009;79:312-318. 39 Wong S, Shields M, Leatherdale ST, Malaison E, Hammond D. Assessment of the validity of self-reported smoking status among Canadians. Health Rep 2012;23:47-53. 40 Gilman SE, Rende R, Boergers J. et al. Parental smoking and adolescent smoking initiation: an intergenerational perspective on tobacco control. Pediatrics 2009;123:e274-e281. 41 Pearson JL, Richardson A, Niaura RS, Vallone DM, Abrams DB. E-cigarette awareness, use, and harm perceptions in US adults. Am J Public Health 2011;102:1758-1766. 42 Farsalinos KE, Polosa R. Safety evaluation and risk assessment of electronic cigarettes as tobacco cigarette substitutes: a systematic review. Ther Adv Drug Saf 2014;5:67-86.
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43 Barrington-Trimis JL, Urman R, Berhane K, Unger JB, Cruz TB, Pentz MA, Samet JM, Leventhal AM, McConnell R. E-cigarettes and future cigarette use. Pediatrics 2016;138:e20160379.
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Highlights Adolescents with asthma had a higher odds of smoking e-cigarettes or any substance. No significant finding between asthma and cigarette, marijuana or waterpipe smoking.
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Need to raise awareness of the risks of all types of smoking including e-cigarettes.
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Conflicts of interest: none.
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All authors have seen and approved the final version of the manuscript being submitted. We confirm that the article is original work and hasn't been or under consideration for publication elsewhere.
S0954-6111(16)30243-8
DOI:
10.1016/j.rmed.2016.09.013
Reference:
YRMED 5014
To appear in:
Respiratory Medicine
Received Date: 8 July 2016 Revised Date:
30 August 2016
Accepted Date: 19 September 2016
Please cite this article as: Larsen K, Faulkner GEJ, Boak A, Hamilton HA, Mann RE, Irving HM, To T, for the Canadian Respiratory Research Network, Looking beyond cigarettes: Are Ontario adolescents with asthma less likely to smoke e-cigarettes, marijuana, waterpipes or tobacco cigarettes?, Respiratory Medicine (2016), doi: 10.1016/j.rmed.2016.09.013. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Looking beyond cigarettes: Are Ontario adolescents with asthma less likely to smoke e-cigarettes, marijuana, waterpipes or tobacco cigarettes? Kristian Larsen, PhD1,2 Guy EJ Faulkner, PhD3,4 Angela Boak, MA2, Hayley A Hamilton PhD2,5 Robert E Mann, PhD2,5 Hyacinth M Irving, MA6 Teresa To, PhD1,5 for the Canadian Respiratory Research Network 1
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Corresponding author: Kristian Larsen 686 Bay St. Toronto, ON M5G 0A4 [email protected] or [email protected] 416-813-7654 x 328384
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Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto; Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto; 3 Faculty of Kinesiology and Physical Education, University of Toronto, Toronto; 4 School of Kinesiology, University of British Columbia, Vancouver; 5 Dalla Lana School of Public Health, University of Toronto, Toronto; 6 Centre for Global Health Research, St. Michael’s Hospital, Toronto; 2
Take home message: Adolescents with asthma in Ontario, Canada had a significantly higher odds of smoking e-cigarettes or any substance.
Number of tables: 2
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Word count: 3,380
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Acknowledgements: Kristian Larsen received a Postdoctoral Fellowship, in part, through the Hospital for Sick Children Research Training Centre and the Canadian Respiratory Research Network (CRRN), supported by grants from the Canadian Institutes of Health Research (CIHR) - Institute of Circulatory and Respiratory Health; Canadian Lung Association (CLA)/Canadian Thoracic Society (CTS); British Columbia Lung Association; and Industry Partners Boehringer-Ingelheim Canada Ltd, AstraZeneca Canada Inc., and Novartis Canada Ltd. Data were provided from the 2013 Ontario Student Drug Use and Health Survey (OSDUHS). Disclosure: The authors declare that they have no conflict of interest. Ethical statement: This study was approved by the research ethics board at The Hospital for Sick Children.
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Looking beyond cigarettes: Are Ontario adolescents with asthma less likely to smoke e-cigarettes, marijuana, waterpipes or tobacco cigarettes? Abstract:
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Objectives: The purpose of this paper is to examine whether high school students in Ontario with asthma smoke cigarettes, waterpipes, marijuana or e-cigarettes more or less than those without asthma.
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Methods: The 2013 Ontario Student Drug Use and Health Survey provides self-report data on tobacco cigarettes, waterpipes, marijuana and e-cigarette smoking and asthma rates from 109 high schools in Ontario, Canada. Individual and social characteristics were also collected. Multiple binary logistic regression models measures the association with the various types of smoking in relation to asthma.
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Results: Adolescents with asthma have higher odds of smoking e-cigarettes or smoking any type including smoke either cigarettes, waterpipe, marijuana or e-cigarettes. Respondents of lower socioeconomic status had a higher odds of smoking marijuana or any type. Boys were more likely to smoke waterpipes, e-cigarettes or any type, while students in higher grades had a higher odds of smoking cigarettes, waterpipes, marijuana or any type.
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Conclusions: Results from this study suggest that adolescents with asthma have a higher odds of smoking e-cigarettes than those without asthma, but no relationship was found for cigarettes, waterpipes or marijuana. Findings present some new challenges as technology changes how adolescents can smoke. Public health campaigns should target adolescents, especially those with asthma, to raise their awareness of the risks of all types of smoking including e-cigarettes.
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Looking beyond cigarettes: Are Ontario adolescents with asthma less likely to smoke e-cigarettes, marijuana, waterpipes or tobacco cigarettes?
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Tobacco smoke can cause numerous health related issues. While cigarette smoking is associated with the development of certain respiratory diseases [1], the causal link between the onset of asthma and smoking has not been established. To date, studies that examined the association between cigarette smoking and incident asthma have shown mixed results [2,3,4,5]. Previous work on the topic has
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reported an increased risk for adults [6] and adolescents [4,5] but others reported no statistically significant associations [2,3].
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Although what causes the onset of asthma is still relatively unknown, experts in the field have reported that cigarette smoking or exposure to second hand smoke can certainly trigger asthma symptoms and severity [7]. Overall cigarette smoking or second hand smoke can relate to many long term respiratory health issues, but it can also influence more immediate issues for people with asthma
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including increased coughing and airway inflammation [8]. For adults in California, cigarette smoking was associated with asthma severity, worse asthma-specific quality of life and greater hospitalization for asthma [9]. Furthermore, active cigarette smoking for people with asthma can lead to accelerated loss
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of lung function and a decreased response to corticosteroids over time [10]. In the past, studies on smoking behaviour in adolescents was focused on cigarette use; however,
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more recently other types of smoking such as waterpipes, marijuana or now electronic cigarettes (ecigarettes) have emerged as a concern. Waterpipes (also known as hookah or shisha) have become more popular in North America in recent years due to the belief that it is a safer alternative to cigarettes [11]. This is a common misconception in young adults [12,13], as a waterpipe smoking session can contain over 100 times the amount of smoke in comparison to a single cigarette [14]. In Ontario, the rate of trying waterpipes in adolescents has more than doubled from 6% in 2006 to 14% in 2013 [15]. Waterpipe smoking is linked to several adverse health outcomes such as cancer, cardiovascular disease 3
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and decreased lung function [16,17,18]. While the causal effect of waterpipe smoke and asthma has not been demonstrated, exposure to tobacco smoke was shown to exacerbate asthma symptoms [19]. Since waterpipes produce tobacco smoke, it can be assumed that it will be harmful especially for those
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with asthma.
The relationship between marijuana smoking and asthma is somewhat complex. Marijuana has been used as a forbidden medicine to treat asthma symptoms for years as it may have bronchodilator
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properties [20], while long term marijuana smoking has also been associated with increased respiratory symptoms [21]. Overall, the relationship between marijuana and lung health is somewhat mixed and
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the connection may not be the same as tobacco smoke [22,23]. Previous research has suggested that adolescents with asthma smoked significantly more marijuana than those without asthma [24]. However, the number of adolescents (aged 15-24) who smoked marijuana in Canada has decreased from 32.7% in 2008 to 24.4% in 2013 [15,25].
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Electronic cigarettes are battery powered devices that vaporise nicotine and/or other flavouring mixes, but do not burn tobacco. These products have become popular in recent years and they are perceived as a safer alternative to tobacco cigarettes [26,27,28]. While preliminary studies suggest that
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they may be less harmful than cigarettes, the long term health effects and how e-cigarettes relate to asthma symptoms or severity are unknown [29]. The Canadian Tobacco, Alcohol and Drug Survey
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reported that as many as one in five (20%) adolescents aged 15-19 tried e-cigarettes [15], however, the absolute trend of usage is still unknown as these products are relatively new. The purpose of this paper is to examine whether adolescents (aged 12-19 or in grades 9 to 12)
with asthma smoke cigarettes, waterpipes, marijuana or e-cigarettes more or less than those without asthma. This study adds to the current literature by examining all smoking habits for youth with asthma, rather than focusing just on cigarettes.
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Methods Data source and study population: The 2013 Ontario Student Drug Use and Health Survey (OSDUHS) is a population based survey conducted every two years and completed by grade 7-12 students at publically
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funded schools in Ontario, Canada. Ontario is the largest province in Canada with a population of over 13 million residents. Ontario includes major urban centres such as Toronto and Ottawa, several smaller cities and an abundance of rural lands.
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The OSDUHS is designed to collect information about drug use and other health related
behaviours among students in Ontario. All parents and students gave consent prior to participation. To
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examine the association between smoking and asthma, we limit our study sample to high school students (grades 9-12, n=6,159) in 109 schools. These schools were selected with probability proportional to size, to obtain a representative sample within the province. The survey included questions that captured information on self-reported doctor diagnosed
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asthma and data on tobacco, alcohol and drug use. The survey used a random split-ballot design where some of the questions change on each of the surveys. The sample is randomly divided into 2 groups to maximize questions included and minimize burden on students, but it reduces the sample size for some
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questions. In the OSDUHS, approximately half of the full sample answered questions pertaining to asthma and all types of smoking reducing the subsample to 2,840. Data are representative of students
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in Grades 9 to 12 attending publicly funded schools in Ontario. Ages for respondents range from 12-19 years of age (mean: 15.86 years; standard deviation 1.27). In Ontario, the majority of children (92%) attended publically funded schools [30], 5% attended private schools [31], and another 3% were either home schooled, institutionalized for correctional or health reasons, schooled on a First Nation reserve (indigenous communities), military base or lived in remote northern region [30]. This study was approved by the research ethics board at the Research Institute of The Hospital for Sick Children (SickKids) (Toronto, Ontario, Canada).
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Variables Outcome measures: The primary outcome variables in this study are smoking status with regard to
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cigarettes, waterpipes, marijuana and e-cigarettes. Self-reported frequency and intensity of cigarette, waterpipe, marijuana and e-cigarette smoking in the last 12 months and lifetime use were measured in the survey. Cigarette non-smokers were classified as those who never smoked a cigarette or smoked
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less than (or equal to) one cigarette in the last 12 months, while cigarette smokers were those who smoked more than one cigarette in the past 12 months. Similarly, smoking status for waterpipe was
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also classified as a binary outcome variable. Respondents were asked how often they smoked a waterpipe (or hookah, shisha, bubble-bubble, gouza) in the last 12 months. Those who smoked a few puffs, never smoked, haven’t smoked in the past 12 months or didn’t even know what it was were considered non-waterpipe smokers. Those who smoked one or more times were defined as smokers.
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Marijuana smoking is also defined in a similar manner. Students were asked how often they smoked cannabis (or marijuana, weed, pot, grass, hashish, hash) in the past 12 months. If they smoked 1 or more times in the past year they were classified as a marijuana smoker. Respondents who have never
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or not smoked in the last 12 months were considered to be non-marijuana smokers. Finally, respondents were classified as e-cigarette smokers if they smoked an e-cigarette with or without
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nicotine in it, while those who have never smoked or never heard of e-cigarettes were considered nonsmokers.
Covariates: The primary risk factor of interest is the presence of asthma which is captured by the response to the question “has a doctor or nurse ever told you that you have asthma”. Other potential confounding variables include: grade (9-12), sex and socioeconomic status (SES). SES was measured by a 10-point social ladder. Students were asked to imagine that the ladder represents how Canadian society
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is set up, where the people at the top of the ladder are the “best off”, meaning they have the best jobs, make the most money and have the highest education. Those at the bottom of the ladder are the “worst off”, with no job, or a job no one wants, little education and the least money. Respondents
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reported what best represents their family on a 10-point scale, which was further grouped into three levels (1–6=low; 7–8=middle; 9–10=high) based on the interquartile ranges.
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Statistical analysis
The percent distributions of demographic characteristics and other covariates were compared between
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smokers and non-smokers of each type (cigarettes, waterpipes, marijuana, e-cigarettes) and the any smoking variable. The chi-square test was used to measure statistical significance between the respondents with and without asthma. Each type of smoking was modelled separately using a binary logistic regression. In addition to doctor diagnosed asthma (the main exposure), all covariates outlined
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above were included in the regression models. All interactions of smoking types were examined but no significant relationships were found so this study focussed on the four individual models, plus the combined any smoking outcome. The following was used as the reference group in the logistic
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regression models: grade 9, female and high SES. Given the OSDUHS used a probability stratified cluster sampling design, all analyses were conducted with the sampling weights and utilized Taylor series
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methods within Stata 14 v14.1 to derive unbiased standard errors and point estimates. Results of the regression models were presented in adjusted odds ratios (OR) with 95% confidence intervals (CI). Goodness of fit tests were completed with the F-adjusted mean test.
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Results Overall, the majority of the grade 9-12 students did not smoke cigarettes, waterpipes, marijuana or ecigarettes (Table 1). Approximately 1 in 7 smoked e-cigarettes, 1 in 8 smoked waterpipes, 1 in 9 smoked
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cigarettes, but more than 1 in 4 smoked marijuana or 1 in 3 smoked any type of product. Among students who reported having asthma, the percentage who smoked tended to be higher than the
percentage who did not smoke, however differences were statistically significant only for e-cigarettes
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and the any smoking variable.
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Table 1: Descriptive statistics for the weighted sample (percentages)
Cigarettes Smokers 10.9
Waterpipes Smokers 12.6
Marijuana Smokers 28.8
E-cigarettes Smokers 14.3
78.7 21.3
10.4 12.8
12.0 14.8
27.5 33.6
12.6 20.5
36.0 44.9
64.0 55.1
21.4 22.2 23.9 32.5
3.9 8.9 13.0 16.0
4.3 8.7 15.2 18.9
12.3 24.3 34.3 38.5
12.6 13.7 14.3 15.7
22.4 31.7 43.5 48.4
77.6 68.3 56.5 51.6
12.0 9.8
14.5 10.6
30.1 26.4
18.3 9.9
42.1 33.5
57.9 66.5
15.6 11.6 10.2
32.5 28.6 21.9
13.8 14.2 15.9
41.7 38.0 30.2
58.3 62.0 69.8
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51.9 48.0 32.9 53.8 13.2
Any smoking Smokers Non-smokers 37.9 62.1
15.1 9.0 8.6
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Total percentage Asthma status Without asthma With asthma Grade 9 10 11 12 Sex Male Female SES Low Middle High
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Full sample
Smoking cigarettes
Table 2 shows the results from the logistic regression that estimated the association of cigarette smoking (response) and asthma (exposure) while adjusting for other covariates. After adjusting for grade, sex and SES, the association of asthma and cigarette smoking was nonsignificant [OR:1.19; CI:0.79-1.78]. Grade was the only variable significantly associated with smoking cigarettes. The odds of
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cigarette smoking increased exponentially with grade. Compared to grade 9 students, the odds of cigarette smoking were 6-fold in grade 12 students [OR:6.07; CI:3.44-10.70].
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Table 2: Binary logistic regression estimation results with the various types of smoking as dependent variable (n=2,809) Waterpipes
Any type of smoking
Upper 1.765
OR 1.311
Lower 0.906
Upper 1.896
OR 1.784
Lower 1.153
Upper 2.762
OR 1.41
Lower 1.04
Upper 1.93
3.454 6.317 7.793
2.281 3.680 4.365
1.519 2.563 2.909
3.423 5.283 6.550
1.113 1.175 1.283
0.620 0.737 0.719
1.997 1.872 2.288
1.61 2.67 3.22
1.13 1.87 2.17
2.30 3.82 4.78
1.976
1.241
0.891
1.729
1.999
1.367
2.925
1.44
1.05
1.99
2.500 1.631
1.509 1.340
1.001 0.917
2.277 1.960
0.788 0.841
0.456 0.525
1.361 1.348
1.48 1.34
1.01 0.94
2.16 1.91
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Smoking waterpipes
E-Cigarettes
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OR Lower Upper OR Lower Asthma1 1.185 0.789 1.778 1.205 0.823 2 Grade 10 3.249 1.913 5.519 2.085 1.259 11 4.786 2.699 8.483 3.942 2.460 12 6.071 3.444 10.701 4.969 3.169 Sex3 Male 1.269 0.832 1.935 1.438 1.047 4 SES Low 1.661 0.847 3.258 1.411 0.796 Middle 0.967 0.501 1.864 1.064 0.694 1 Respondents with asthma, no asthma is the referent; 2 Grade 9 is the referent; 3 Female is the referent; 4 High SES is the referent; Significant variables in bold when p< 0.05; OR: Odds ratio
Marijuana
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Cigarettes
For waterpipe smoking there was once again no significant relationship between asthma prevalence and smoking (Table 2). Results were similar to that of cigarettes as grade was again significant, with the
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CI:1.05-1.98].
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exception that when compared to girls, boys had a 44% higher odds of smoking waterpipes [OR:1.44;
Smoking marijuana
Student’s grade and SES were the only significant factors related to smoking marijuana (Table 2). Being in grade 10 increased the odds of smoking marijuana by over 2 times [OR:2.28; CI:1.52-3.42], while students in grades 11 and 12 had even higher odds of smoking marijuana [OR:3.68; CI:2.56-5.28 and OR: 4.37; CI: 2.91-6.55]. Smoking marijuana was also associated with lower SES classification [OR:1.51;
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CI:1.01-2.28], when compared to peers from the highest SES. While asthmatic adolescents had an odds ratio for smoking marijuana of 1.31 [CI:0.91-1.9], this finding was again not significant.
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Smoking e-cigarettes
E-cigarettes produced very different results in the modelled analysis. Grade and SES were not significant factors, and looking at the odds ratios for these variables, there is very little difference between each
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category (Table 2). Grade for instance has nearly the same odds ratio for grades 10 and 11 [OR:1.11; CI:0.62-2.00, OR:1.18; CI:0.74-1.87]. The significant factors related to smoking e-cigarettes were asthma
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prevalence and sex. Adolescents with asthma were nearly 1.8 times more likely to smoke e-cigarettes than those without asthma [OR:1.78; CI:1.15-2.76]. As well, compared to girls, boys had a 2-fold odds of smoking e-cigarettes [OR:2.00; CI:1.37-2.93].
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Any smoking
Having doctor diagnosed asthma was significantly associated with a higher odds of smoking any type of substance (Table 2) [OR:1.41; CI:1.04-1.93]. Compared to girls, boys were also significantly more likely
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to smoke, as were respondents of lower SES. The results for grade were similar to many of the previous
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models, as the odds of smoking any substance becomes higher as you enter grade 10, 11 or 12.
Discussion
While cigarette smoking may aggravate symptoms and severity for adolescents with asthma, some work on the topic suggests that the prevalence of cigarette [32], waterpipe [11] and marijuana [24] smoking was actually higher in adolescents with asthma than those without. These studies, however, are not conclusive as at least one reported that adolescents with asthma were less likely to smoke cigarettes
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[33]. It is reasonable to suppose that adolescents with asthma will not smoke as it will aggravate their asthma severity and symptoms [7], but this unfortunately may not be the case. Our study showed that students in grades 9-12 with asthma in Ontario, had a higher odds of
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smoking any substance than their peers who do not have asthma. The odds of smoking e-cigarettes for adolescents with asthma, was nearly twice as high as those without asthma after adjusting for age, sex and SES. Given the cross-sectional design of the survey, we cannot infer the causal relationship between
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smoking and asthma. Previous studies suggest that smoking for adolescents with asthma may relate to the desire to obtain social status among one’s peers [34], and not wanting asthma to interfere with their
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social status.
Of all demographic characteristics studied, student's grade was most significantly associated with smoking cigarettes, waterpipes and marijuana. A longitudinal study in the United States found that rates of cigarette smoking increased from 1.8% at the age of 9 to 22.5% by age 16 years [35]. Findings
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suggest that rates for smoking cigarettes and waterpipes among grade 9 students were relatively low (3.9% and 4.3%), but doubled in grade 10, tripled by grade 11 and quadrupled by grade 12 (Table 1). Cigarette and waterpipe smoking became more popular in grade 10 and the trend continued as they
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aged. E-cigarette smoking on the other hand only marginally increased from grade 9 to 12 (12.6% in grade 9 versus 15.7% in grade 12). For adolescents with asthma, rates of e-cigarette smoking were
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similar to that of the entire sample, ranging from about 10% in grade 9 to 16.7% in grade 12. Our study also showed that cigarette, marijuana and any smoking rates were inversely related
to SES, where lower SES was associated with higher odds of smoking. Our finding is consistent with the literature that suggests an inverse relationship between individual SES or parental education and cigarette smoking in adolescents [36]. It has been suggested that lower SES households may have a poorer attitude towards health, fewer opportunities or more stressful situations which make them more
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likely to smoke [36]. Results from our study emphasise the need for tailored interventions for youth from lower SES households. This study had many strengths which relate to the size and generalizability of the survey sample
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but also the fact that it examined how all types of smoking related to asthma prevalence. That being said, there are also some limitations. Firstly, the primary purpose of this survey is to examine health risk behaviours of adolescents in Ontario and not asthma. As such, the number of respondents with asthma
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was low and this may have contributed to some of the insignificant findings. Despite the low number of asthma respondents, the self-reported asthma prevalence rate of adolescents in this study (21%) was
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similar to that reported (25%) by the Ontario Asthma Surveillance Information System (aged 15-19 years), which uses a validated health administrative data case definition to capture asthma with 84% sensitivity and 76% specificity [37]. Secondly, the cross-sectional design of the survey is a major study limitation in assessing causal relation of asthma and smoking. It is unknown from this study whether
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adolescents with asthma smoked e-cigarettes more often or if smoking e-cigarettes contributed to the risk of asthma. Thirdly, asthma was self-reported and it not clinically confirmed. Self-reported asthma may over or under represent actual prevalence of asthma. Furthermore, many studies (ours included)
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that examined the relationship between asthma and smoking did not separate severe or “uncontrolled” asthma from those with well-controlled mild to moderate asthma. The effect of smoking on adolescents
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with severe or uncontrollable asthma may be different than on those with mild to moderate asthma. The definition of smoking used may influence the study findings. We classified smoking for cigarettes, marijuana and waterpipes as smoking one or more time over the past 12 months or ever for ecigarettes. This definition includes those who smoke regularly but also adolescents who experiment with the various types of smoking. This classification of smoking has been used previously in studies using the OSDUHS dataset [e.g., 38]. We conducted additional analyses using another method of classifying smokers reported by Wong and colleagues [39]. In this method a regular smoker is defined as
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smoking more than 100 cigarettes in their lifetime and any cigarettes in the past month. Using this method the results and point estimates remained very similar. Given this method of classification was only available for cigarettes, we opted to retain the ‘any cigarettes over the past 12 months’ method to
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ensure measurement correspondence with the other types of smoking (i.e., marijuana, e-cigarettes and waterpipes). Nevertheless, results suggest that adolescents with asthma are at least experimenting with e-cigarettes or any type of smoking more often than their peers without asthma, which may lead to
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higher smoking rates later in life. Finally, we were unable to adjust for parental smoking or parental history of asthma as these data were not collected by the survey. Having a parent who smokes may
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relate to the respiratory health of children, but it also increases the odds of smoking for adolescents [40]. While information on parental smoking is not available in our data, further research should examine the association between parental smoking and asthma for all types of smoking. This paper adds discussion to the question of whether adolescents with asthma would be less
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likely to smoke cigarettes, waterpipes, marijuana or e-cigarettes. Our study findings suggest that adolescents with asthma had a significantly higher odds of smoking e-cigarettes or any substance. This may suggest a lack of knowledge of the potential harmful long term effects of smoking e-cigarettes or a
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general perception that e-cigarettes are “safer” than tobacco cigarettes [41]. While recent research has suggested that e-cigarettes are less harmful than tobacco cigarettes [42], the long term effects are still
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unknown. Furthermore, a recent study reported that e-cigarette usage for adolescents increases the odds of smoking tobacco cigarettes in adulthood by six times [OR:6.17; CI:3.3-11.6], suggesting that ecigarettes may be used as a gateway among teens [43]. Public health campaigns and education should target adolescents and especially those with asthma to raise their awareness of the risks (or potential risks) of all types of smoking. Results from this study suggest that adolescents with asthma are not more likely to be smoking cigarettes, waterpipes or marijuana than those without asthma. As the means (technology) of smoking
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change, how adolescents can smoke (such as via e-cigarettes), presents new challenges in relation to adolescent smoking and asthma. This study found that adolescents with asthma were more likely to smoke e-cigarettes than those without. The results did not change when we included any type of
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smoking. Our study findings can be used to target the adolescent asthma population for smoking
prevention and education campaigns and to raise their awareness of the risks associated with smoking in general. Although recent studies have reported that adolescents with asthma are more likely to
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smoke cigarettes or waterpipes [11,32], this does not appear to be the case in Ontario, after adjusting for confounding variables. While this is encouraging, our study suggests that e-cigarettes are now
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popular among youth with asthma. Work should continue with anti-smoking and prevention campaigns to try and further reduce all smoking rates for adolescents, with an emphasis on the unknown and potential serious long term risks associated with e-cigarettes or alternative types of smoking.
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References:
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27 Polosa R, Rodu, B, Caponnetto P, Maglia M, Raciti C. A fresh look at tobacco harm reduction: The case for the electronic cigarette. Harm Reduct. J 2013;10-19. 28 Hamilton HA, Ferrence RG, Boak A, Schwartz R, Mann RE, O’Connor S, Adlaf EM. Ever use of nicotine and nonnicotine electronic cigarettes among high school students. Nicotine Tob Res 2015;17:1212-1218.
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37 Ontario Asthma Surveillance Information System (OASIS). Asthma Statistics. http://lab.research.sickkids.ca/oasis/wp-content/uploads/sites/6/2016/06/asthma_prevrt_up-to-2014.pdf. Date last assessed: June 13, 2016.
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38 Faulkner GEJ, Adlaf EM, Irving HM, Allison KR, Dwyer J. School disconnectedness: Identifying adolescents at risk in Ontario, Canada. J School Health 2009;79:312-318. 39 Wong S, Shields M, Leatherdale ST, Malaison E, Hammond D. Assessment of the validity of self-reported smoking status among Canadians. Health Rep 2012;23:47-53. 40 Gilman SE, Rende R, Boergers J. et al. Parental smoking and adolescent smoking initiation: an intergenerational perspective on tobacco control. Pediatrics 2009;123:e274-e281. 41 Pearson JL, Richardson A, Niaura RS, Vallone DM, Abrams DB. E-cigarette awareness, use, and harm perceptions in US adults. Am J Public Health 2011;102:1758-1766. 42 Farsalinos KE, Polosa R. Safety evaluation and risk assessment of electronic cigarettes as tobacco cigarette substitutes: a systematic review. Ther Adv Drug Saf 2014;5:67-86.
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43 Barrington-Trimis JL, Urman R, Berhane K, Unger JB, Cruz TB, Pentz MA, Samet JM, Leventhal AM, McConnell R. E-cigarettes and future cigarette use. Pediatrics 2016;138:e20160379.
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Highlights Adolescents with asthma had a higher odds of smoking e-cigarettes or any substance. No significant finding between asthma and cigarette, marijuana or waterpipe smoking.
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Need to raise awareness of the risks of all types of smoking including e-cigarettes.
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Conflicts of interest: none.
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All authors have seen and approved the final version of the manuscript being submitted. We confirm that the article is original work and hasn't been or under consideration for publication elsewhere.