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European Journal of Public Health, 1–5
ßThe Author 2016. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
doi:10.1093/eurpub/ckw093
.........................................................................................................
Do stronger school smoking policies make a difference?
Analysis of the health behaviour in school-aged
children survey
B. Hallingberg
1
, A. Fletcher
1
, S. Murphy
1
, K. Morgan
1
, H.J. Littlecott
1
, C. Roberts
2
, G.F. Moore
1
1 Centre for the Development and Evaluation of Complex Interventions for Public Health Improvement, School of Social
Sciences, Cardiff University, Cardiff, United Kingdom
2 Social Research and Information Division, Cathays Park, Cardiff, United Kingdom
Correspondence: Graham Moore, Centre for the Development and Evaluation of Complex Interventions for Public Health
Improvement, School of Social Sciences, 1-3 Museum Place, Cardiff University, Cardiff, CF10 3BD, UK, Tel: +44 (0)29 2087
5360, Fax: +44 (0)29 2087 9054, e-mail: mooreg@cf.ac.uk
Background: Associations of the strength of school smoking policies with cigarette, e-cigarette and cannabis use in
Wales were examined. Methods: Nationally representative cross-sectional survey of pupils aged 11–16 years
(N=7376) in Wales. Senior management team members from 67 schools completed questionnaires about school
smoking policies, substance use education and tobacco cessation initiatives. Multi-level, logistic regression analyses
investigated self-reported cigarette, e-cigarette and cannabis use, for all students and those aged 15–16 years.
Results: Prevalence of current smoking, e-cigarette use and cannabis use in the past month were 5.3%, 11.5% and
2.9%, respectively. Of schools that provided details about smoking policies (66/67), 39.4% were strong (written
policy applied to everyone in all locations), 43.9% were moderate (written policy not applied to everyone in all
locations) and 16.7% had no written policy. There was no evidence of an association of school smoking policies
with pupils’ tobacco or e-cigarette use. However, students from schools with a moderate policy [OR = 0.47; 95%
(confidence interval) CI: 0.26–0.84] were less likely to have used cannabis in the past month compared to schools
with no written policy. This trend was stronger for students aged 15–16 years (moderate policy: OR =0.42; 95% CI:
0.22–0.80; strong policy: OR = 0.45; 95% CI: 0.23–0.87). Conclusions: School smoking policies may exert less
influence on young people’s smoking behaviours than they did during times of higher adolescent smoking
prevalence. Longitudinal studies are needed to examine the potential influence of school smoking policies on
cannabis use and mechanisms explaining this association.
.........................................................................................................
Introduction
Tobacco use is commonly initiated during youth.
1
Hence, recent
decades have seen growing emphasis on preventing uptake of
smoking among young people.
2
Interventions to influence
adolescent smoking are often delivered via schools because they
provide opportunities to reach most young people, while the
norms and environments of schools’ can influence risk
behaviours.
3,4
The ‘Health Promoting Schools’ framework,
endorsed by the World Health Organization,
5
consistent with
Ottawa Charter principles emphasizing the need to go beyond
simplistic health education and toward creating healthier environ-
ments,
6
advocates multi-level approaches to health improvement,
focused on integration of health into the curriculum alongside
changes to the school’s social and physical environment.
Environmental change interventions have demonstrated significant
positive effects on a range of outcomes, including tobacco use.
7
One key strategy for changing school social environments is
through written policies. These can play an important role in estab-
lishing and communicating a school’s ethos, in terms of norms for
acceptable and unacceptable ways for staff, students and others to
behave within the school environment.
8
Changing school policy has
been described as low cost, realistic and easy to address
9
and many
schools have adopted formal written smoking policies.
10
Earlier
studies investigating school substance use policies have shown that
universal smoking bans and restrictions are associated with a lower
likelihood of smoking behaviour and smoking prevalence among
youth.
11
For example, Moore et al.
9
found that having a written
smoking policy for all students, teachers and other adults on
school premises was associated with lower likelihood of daily and
weekly smoking.
However, weaker associations between school smoking policies
and tobacco use have been observed in more recent studies.
11
In
part this may be because school smoking policies have become
more common and more consistent in their universality, perhaps
limiting variance in practice between schools.
9,12,13
However,
national policies to ‘denormalize’ smoking, and limit its visibility
to children, such as smoke-free legislation, may mean that schools
operate within a macro-system in which smoking is already heavily
denormalized,
14
while adolescent smoking rates are now at an all-
time low.
15,16
Given the growing denormalization of smoking in
front of children,
17
adults may now be less likely to use tobacco
on or near school grounds than during earlier studies.
Furthermore, young people who continue to smoke in contempor-
ary society do so despite it being widely stigmatized within society
and hence may be less influenced by norms within the school envir-
onment. As such, the capacity for strong policies to achieve further
gains in reducing youth smoking may have diminished over time.
However, no previous studies have looked beyond effects on
smoking and toward understanding secondary effects on other
substances. Smoking clusters with other risky behaviours
18
and is
often considered a ‘gateway’ into future use of illicit substances such
as cannabis.
19,20
However, while smoking tobacco is increasingly
denormalized, strong government policies on tobacco have been
accompanied by mixed messages on cannabis, and it is unclear
whether cannabis use has declined at the same rate as tobacco use.
Internationally, legislation surrounding cannabis use has become
more rather than less permissive, including legalization in some jur-
isdictions. Perhaps arising from these mixed messages, there is some
evidence that young people view cannabis as less harmful than
tobacco or even e-cigarettes.
21
Hence it is plausible that the main-
tenance of non-smoking norms and norms against substance use
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more broadly by schools may have effects on cannabis use, which has
not been subjected to the same level of policy denormalization.
Emerging international evidence also indicates increasing
numbers of young people who have never used tobacco are experi-
menting with electronic (e)-cigarettes.
22–24
Some have expressed
concern regarding the visibility of e-cigarettes in places where the
use of tobacco has been banned.
25
According to advocates of the
renormalization hypothesis,
26
the appearance of smoke-like vapour
in public places will ultimately lead to a regrowth in smoking rates
through increasing the extent to which smoking is seen as a
normative behaviour. However, it may also be that contexts with
more permissive approaches to tobacco use give rise to more
widespread experimentation with e-cigarettes, as a safer means of
experimenting with nicotine use.
The objective of this study is therefore to identify the extent to
which students’ cigarette, e-cigarette and cannabis use are associated
with school smoking policies. This study conducts a multilevel
analysis, combining school-level data on smoking policies with
student-level data on substance use from a nationally representative
cross section of young people aged 11–16 years in Wales.
Methods
Sample
Data were derived from the 2013/14 Welsh Health Behaviour in
School-aged Children (HBSC) survey, a cross-sectional study of
Welsh secondary school students aged 11–16 years in a nationally
representative sample of secondary schools. The Welsh survey is part
of an international survey representing 44 countries supported by
the World Health Organization to monitor national and interna-
tional changes in health behaviours among school-age students every
four years.
27,28
A two-stage sampling procedure was used. First,
maintained and independent secondary schools in Wales were
stratified by local authority and eligibility for free school meals
(FSMs). Schools were selected using probability proportionate to
size, with the sample disproportionately stratified to allow analysis
at local health board level. An invitation letter was sent to school
head teachers to take part in the HBSC survey and was followed up
with telephone calls. Second, participating schools were asked to
randomly select one class (25 students) from each school year
7–11 (i.e. 11–16 years old). Data were collected between
November 2013 and March 2014 in the classroom under examin-
ation conditions. Teachers were present during data collection but
remained at the front of the classroom so they could not see
students’ responses. In 67 schools, members of the senior
management team also completed a school environment question-
naire on the content of school health policies. Schools received £150
to cover any costs incurred due to participating.
Measures
Socio-demographics
Students reported their sex, year and month of birth and ethnicity
[White; Mixed Race; Asian or Asian British; Black or Black British;
Chinese or Other (categorized as white/BME)]. The Family
Affluence Scale (FAS) was used to indicate family-level
socioeconomic status.
29
The measure is the sum of six survey
items which asked students whether they have their own bedroom,
how many family holidays they took in the past year, if their family
owns a dishwasher, how many bathrooms are in their home and how
many computers and cars their family own. Items on dishwashers
and bathrooms were introduced in 2013, due to concerns that some
items (i.e. computer ownership) became less differentiated by socio-
economic status over time. At the school level, the modified six-item
measure correlated slightly more strongly to the percentage of
students eligible for FSM entitlement (r=0.84, P<0.001), than
the original four-item FAS measure (r=0.76, P< 0.001), and
hence the six-item measure was used.
Substance use measures
Cigarette use Smoking behaviour was assessed using the question
‘How often do you smoke at present?’ (responses: ‘every day’; ‘at
least once a week but not everyday’; ‘less than once a week’ and ‘I do
not smoke’). For analyses, a binary variable was created that
compared those stating ‘I do not smoke’ against all others.
E-cigarette use E-cigarette use was based on the question ‘Have you
ever used or tried electronic cigarettes?’ (responses: ‘I have never
used or tried e-cigarettes’; ‘I have used e-cigarettes on a few
occasions (1–5 times)’ and ‘I regularly use e-cigarettes (at least
once a month)’. A binary variable was created that compared ever
e-cigarette users to never users.
Cannabis use Cannabis use was measured by asking students to
report the number of days they used cannabis in the past 30 days
(responses: ‘never’; ‘1–2 days’; ‘3–5 days’; ‘6–9 days’; ‘10–19 days’;
‘20–29 days’ or ‘30 days (or more)’. A binary variable was created to
indicate those who used any cannabis in the past 30 days.
School environment measures
School smoking policies Schools reported whether they had a written
policy in place for smoking and tobacco use and whether it
prohibited tobacco use on: school grounds during school hours;
school grounds outside school hours; in private vehicles on school
grounds and/or, school events off school grounds. They were also
asked whether their policy applied to everyone, including students,
staff, families and/or visitors. A three-level categorical variable was
derived to indicate the strength of school smoking policies. These
were categorized as ‘no written policy’, ‘moderate’ (a written policy
but not applied to everyone in all locations) and ‘strong’ (a written
policy that applied to everyone in all locations).
Substance use education and tobacco cessation initiatives In all models
other school-level approaches aimed at reducing students’ substance
use, such as tobacco cessation initiatives and substance use
education, are controlled for as school smoking policies may
reflect wider school norms around substance use. Schools were
asked if they provided any tobacco, alcohol or drug education to
students in years 7, 8, 9, 10 and 11. A scale was created by adding the
number of year groups that received education on the various
substances and divided by three to indicate the average number of
years within a school that received substance use education. A binary
variable indicated whether schools provided tobacco cessation
initiatives.
FSM entitlement The Welsh Government provided information on
the percentage of students entitled to FSMs within schools. This was
used to generate a continuous variable to indicate school-level
socioeconomic status. A higher percentage represented more
deprived schools.
Statistical analyses
Multi-level, binary logistic regression models (students nested within
schools) were used to investigate cigarette use, e-cigarette use and
cannabis use. Three models were used for each substance use
outcome and applied to both the entire student sample and a sub-
sample of students aged 15–16 years with complete data. For each
model, a null model was first developed and included schools as a
random effect. For the second model, individual-level variables (age,
gender, ethnicity and FAS) were then entered as fixed effects. Finally,
school-level predictors (school smoking policy strength, substance
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use education, tobacco cessation initiatives and FSM entitlement)
were entered into the model. All analyses were conducted in STATA
(v.14.0). Analyses are conducted with the whole sample (i.e. all year
groups) and with young people aged 15–16 years; the latter to
enhance comparability with an aforementioned study of the link
between school policy and tobacco use which included only 15–
16-year olds.
9
Data for the one school which did not provide full
details of their school smoking policy were excluded from regression
analyses.
Results
Questionnaires were completed by 7376 students (49.1% girls and
50.9% boys) at the 67 schools. Table 1 provides a description for
individual level variables for the entire student sample and for
students aged 15–16 years. Overall, 5.3% of students were
identified as current cigarette smokers, with a small percentage of
students reporting smoking daily (2.3%) or weekly (0.9%). The
prevalence of e-cigarette ‘ever use’ was 11.5%, while 2.9% of
students reported that they had used cannabis in the past month.
For all substance use outcomes, prevalence rates among students
aged 15–16 years were around double the rate of the sample as a
whole.
Of the 67 schools, 37 (55.2%) provided tobacco cessation initia-
tives, 41 (65%) delivered education on alcohol, tobacco and drug
use to all students in years 7–11 and 56 (83.6%) had a written school
smoking and tobacco policy. An average of 15.9% (SD = 8.7) of
students within schools were entitled to FSM. All but one school
provided all the information needed to generate an indicator of
school smoking policy strength. Of the remaining 66 schools, 26
(39.4%) had a strong policy, 29 (43.9%) had a moderate policy
and 11 (16.7%) had no written policy.
As indicated in table 2 for the entire sample, individual and
school-level characteristics were associated with some substance
use behaviours. Older age was associated with a greater likelihood
of all substance use outcomes. Females were more likely to be
current smokers and to have used cannabis in the past month. At
the school level, having a greater percentage of students entitled to
FSM was associated with a greater likelihood of e-cigarette use.
For the whole sample, percentages reporting smoking were 5.5%
(N= 64), 5.2% (N= 167) and 5.6% (N= 158), respectively, in
schools with no policy, moderate policy or strong policy. For
cannabis use, percentages were 4.1% (N= 46), 2.5% (N= 77) and
2.9% (N= 78), and for ever e-cigarette use 12.6% (N= 146), 11.9%
(N= 379) and 10.9% (N=307). For over 15s, percentages reporting
smoking were 11.5% (N= 30), 9.9% (N= 81) and 12.0% (N= 87) in
schools with no policy, moderate policy or strong policy. For
cannabis use, percentages were 12.6% (N= 31), 6.0% (N= 47) and
6.5% (N= 46), respectively, and for ever e-cigarette use 23.8%
(N= 62), 20.3% (N= 164) and 18.5% (N= 133). Students who
attended schools with a moderate smoking policy were significantly
less likely than students from schools with no written smoking policy
to use cannabis in the past month, though there was no association
with tobacco or e-cigarette use. As indicated by the ICCs, school-
level clustering was substantially greater for e-cigarettes and cannabis
than for tobacco use in models excluding school-level variables, par-
ticularly for older adolescents. Among 15–16-year olds, inclusion of
school level variables substantially reduces the ICC for cannabis,
suggesting that half of school-level variance is explained by the
included variables.
Among students aged 15–16 years, females were more likely to be
current smokers and use cannabis in the past month, while higher
FSM entitlement was associated with a greater likelihood of
e-cigarette use. Schools with a moderate or strong smoking policy
had lower rates of cannabis use compared to schools with no written
smoking policy, though as for the full sample, there was no associ-
ation with tobacco or e-cigarette use. The provision of tobacco,
alcohol and drug use education across a greater number of school
years was associated with an increased likelihood of cannabis use.
Discussion
Compared to earlier studies,
9
this study indicated an increased
uptake of smoking policies within schools, in line with growing
societal anti-smoking norms. In the 1998 HBSC survey, only
16.4% of schools had a strong smoking policy,
9
while in this
study, 39.4% schools had a strong smoking policy. Smoking
prevalence among students in Wales has also dramatically
decreased. In this study, 2.3% of the entire sample and 5.1% of
students aged 15–16 years smoked daily compared to approximately
one in five 15–16-year olds in 1998. While a key function of school
smoking policies has been to communicate a strong non-smoking
norm,
30
schools now operate within a wider macro-system in which
smoking, particularly in spaces where children are present,
17
is in-
creasingly denormalized. Policies banning smoking on or near
school grounds may therefore make less difference to the visibility
of smoking in these spaces than they once did. Furthermore, young
people who continue to take up smoking despite the widespread
stigma associated with smoking in contemporary UK society are
perhaps also less influenced by school norms.
To our knowledge, this study is the first to examine the relation-
ship between school smoking policies and other substance use
outcomes, such as cannabis and e-cigarette use. Although school
smoking policies were not associated with student’s e-cigarette use,
a stronger school smoking policy was associated with less cannabis
use, particularly among those aged 15–16 years. The mechanisms
through which school smoking policies might influence cannabis
use are unclear. However, this may arise in part from the greater
ambiguity in public health messages around cannabis use compared
to those surrounding tobacco use. In the UK, cannabis was
reclassified as a Class C (the category of drug associated with the
lowest penalties for sale and use, due to lower perceptions of harm),
before being returned to Class B (an intermediate category between
Class A drugs such as heroin, which are associated with the strongest
penalties, and Class C drugs such as ketamine and anabolic steroids)
status in 2008; a decision which was again debated in 2012, with a
Home Affairs Committee tied on a vote regarding reclassification to
Class C.
31
In the USA, a number of states have recently legalized
cannabis is widely perceived by young adults to be significantly less
harmful, and more socially acceptable, than tobacco.
21
Table 1 Description of sociodemographics and substance use
outcomes for the entire sample and those aged 15–16 years
Characteristics Entire sample 15–16 years only
Age, years,
a
M (SD) 13.7 (1.4) 15.6 (0.4)
FAS,
b
M (SD) 15.0 (2.3) 15.0 (2.3)
Male/female, % (n) 50.9 (3743)/49.1 (3607) 50.9 (937)/49.1 (903)
White/BME, % (n) 92.7 (6808)/7.3 (534) 93.7 (1729)/6.3 (116)
Smoking status
Smoke daily 2.3 (169) 5.1 (93)
Smoke weekly 0.9 (68) 2 (37)
Smoke <1/week 2.1 (152) 3.7 (68)
Don’t smoke 94.7 (6969) 89.2 (1644)
Current smoker (yes/no) 5.3 (389)/94.7 (6969) 10.8 (198)/89.2 (1644)
E-cigarette use
A few times (1–5) 10.1 (743) 17.5 (320)
At least once a month 1.3 (97) 2.3 (42)
Any e-cigarette
use (yes/no)
11.5 (840)/88.5 (6451) 19.8 (362)/80.2 (1465)
Cannabis use past
month (yes/no)
2.9 (204)/97.1 (6850) 7.1 (125)/92.9 (1644)
a: n= 7345.
b: n= 7200.
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Notably, in schools with more comprehensive coverage of substance
use education, cannabis use was more likely among 15–16-year olds
(though not for the whole sample). However, this likely reflects reverse
causality;schoolswithgreaterperceivedproblemswithcannabisuse
may be more likely to increase health education coverage as a response
to this. Experimentation with e-cigarettes for the whole sample, and
cannabis use for older adolescents, were highly clustered within
schools, perhaps indicating a higher degree of influence by aspects of
the school environment such as peer relationships than for tobacco.
Associations between tobacco use and e-cigarette use remains highly
ambiguous. Experimentation with e-cigarettes has increased among
adolescents, although this has not been accompanied by widespread
regular use, and e-cigarettes do not appear to be making a major
contribution to young people’s nicotine addiction.
17
While the large, nationally representative sample is a strength,
data for this study are based on self-reports of substance use. As
with any cross-sectional study, the current results should be inter-
preted with caution. Reverse causality cannot be ruled out: for
example, schools with less prevalent substance use may face less
resistance from students, teachers and other adults in implementing
strong non-smoking policies. Future research should examine the
impact of school smoking policy change on student’s substance use
over time to aid interpretation of any directional relationships.
While this study did examine the strength of school smoking
policy it did not investigate the enforcement of policy and conse-
quences from breaking school policy which have been associated
with lower student smoking rates in other studies.
9,32,33
It is
possible that details of the content of these policies, which were
not captured in this study, may have moderated their effects.
Finally, associations from the multi-level analyses may be caused
from unmeasured differences between schools and student charac-
teristics confounded with smoking policy. The power to detect
impacts of school-level variables on young people’s smoking has
diminished over time as smoking has become confined to a small
minority of students and retesting these associations with larger
samples is perhaps important.
Nevertheless, the study has important implications for policy
and practice. Firstly, school smoking policies appear to make a
less important contribution to the reduction of smoking uptake
than they did when smoking was highly prevalent among young
people. It is perhaps the case that within a macro-context in
which smoking is already heavily denormalized, the potential con-
tribution of school policies to further reducing smoking has been
reduced. Hence, revisiting our assumptions about how best to
influence young people’s smoking uptake within this changed
macro-context is important. Nevertheless, despite the apparently
declining effect of smoking policies on tobacco use itself, schools
should be advised to continue to implement such policies, due to
their potential effects on other substances such as cannabis. In
some countries, including Wales, policy debates are moving
towards extending smoke-free legislation to some outdoor
spaces,suchasonornearschoolsoronchildren’splaygrounds.
Hence, all schools may in time become entirely smoke-free spaces,
regardless of internal school policies. The failure of the Public
Health Wales Bill to pass through the Welsh Assembly due in
large part to the retention of controversial legislation on
e-cigaretteswithinthishasdelayedsuchamoveinWales.
34
Nevertheless, examining the effects of further strengthening of
smoke-free public place policies on youth tobacco use, and on
cannabis use, is important. Given that cannabis use appears to be
more sensitive than tobacco use to norms within the school gates,
wider societal efforts to address ambiguities regarding the harms of
cannabis are perhaps also needed. Relationships of e-cigarettes
with tobacco use remain ambiguous and contested, and further
research is needed to understand the substantial clustering of
e-cigarette within schools, and the nature of their relationships
with other substances.
Acknowledgements
The study was funded by the Public Health Division, Welsh
Government (C044/2012/2013) with the support of The Centre for
the Development and Evaluation of Complex Interventions for
Public Health Improvement (DECIPHer), a UKCRC Public Health
Research Centre of Excellence. Joint funding (MR/KO232331/1)
from the British Heart Foundation, Cancer Research UK,
Economic and Social Research Council, Medical Research Council,
the Welsh Government and the Wellcome Trust, under the auspices
of the UK Clinical Research Collaboration, is gratefully
acknowledged. The work was also undertaken with support from
the Public Health Improvement Research Network (PHIRN).
PHIRN is part of the research infrastructure for Wales funded by
NISCHR, Welsh Government www.wales.gov.uk/nischr. Author
Graham Moore is funded by a MRC Population Health Scientist
Fellowship (MR/K021400/1).
Conflicts of Interest: None declared.
Table 2 Odds ratios and 95% confidence intervals from logistic regression analyses of cigarette use, e-cigarette use and cannabis use, for
the entire sample and 15–16-year-old students
Entire sample Students 15–16 years
Cigarette use E-cigarette use Cannabis use Cigarette use E-cigarette use Cannabis use
(N= 6538) (N= 6484) (N= 6266) (N= 1629) (N= 1620) (N= 1568)
Individual
level variables
Age 1.8 (1.65–1.97) 1.64 (1.54–1.74) 2.47 (2.13–2.87) 1.69 (1.15–2.50) 1.73 (1.25–2.39) 1.96 (1.20–3.18)
Female 1.39 (1.11–1.74) 0.90 (0.76–1.07) 1.44 (1.05–1.98) 1.78 (1.28–2.47) 1.08 (0.83–1.40) 1.57 (1.04–2.35)
Ethnicity 0.80 (0.47–1.34) 0.98 (0.70–1.38) 1.29 (0.69– 2.41) 0.79 (0.37–1.69) 0.90 (0.50–1.62) 1.09 (0.47–2.53)
FAS 0.96 (0.91–1.01) 0.99 (0.96–1.03) 0.95 (0.89–1.02) 0.94 (0.88–1.01) 1.00 (0.94–1.06) 0.97 (0.89–1.06)
School level
variables
FSM 1.07 (0.93–1.24) 1.40 (1.18–1.65) 1.22 (0.98–1.52) 0.98 (0.81–1.18) 1.25 (1.02–1.54) 1.05 (0.82–1.35)
Tobacco Cessation 1.09 (0.81–1.49) 0.72 (0.51–1.02) 0.79 (0.50–1.24) 0.94 (0.64–1.40) 0.76 (0.49–1.17) 0.76 (0.46–1.23)
Education 0.98 (0.85–1.14) 1.04 (0.87–1.25) 1.18 (0.93–1.51) 0.96 (0.79–1.17) 1.05 (0.84–1.31) 1.40 (1.03–1.89)
Policy -Weak
Moderate 0.83 (0.55–1.25) 0.64 (0.39–1.03) 0.47 (0.26–0.84) 0.83 (0.49–1.42) 0.66 (0.37–1.18) 0.42 (0.22–0.80)
Strong 0.87 (0.57–1.33) 0.82 (0.50–1.34) 0.61 (0.33–1.11) 0.93 (0.54–1.62) 0.77 (0.42–1.41) 0.45 (0.23–0.87)
ICC: constant only 0.04 0.12 0.05 0.04 0.11 0.11
ICC: level 1 variables 0.05 0.14 0.05 0.04 0.12 0.12
ICC: level 1 and 2 variables 0.03 0.09 0.05 0.03 0.09 0.6
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Key points
School smoking policies play a crucial role in setting behav-
ioural norms and guiding student behaviour.
National policies have aimed to ‘denormalize’ smoking
within society as a whole and an increasing number of
schools have implemented school smoking policies in the
last two decades; however, this has also been accompanied
by mixed messages on cannabis and e-cigarette use.
More recent studies that have investigated the impact of
school smoking policies on student smoking show weaker
associations compared to earlier studies that took place
when tobacco use was more prevalent among students.
While strong school smoking policies were not associated
with student’s smoking or e-cigarette use in this study,
they were associated with less cannabis use, particularly
among students aged 15–16 years.
Schools should continue to implement strong school
smoking policies due to their potential effects on other
substances. There is a need to better understand how to
influence the minority of young people who still take up
smoking in contemporary society.
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