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Do stronger school smoking policies make a difference? Analysis of the health behaviour in school-aged children survey

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Abstract

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.
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.
School smoking policies 3of5
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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,suchasonornearschoolsoronchildrensplaygrounds.
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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School smoking policies 5of5
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... Such denormalisation may have led to the reduction in effectiveness of anti-smoking policies in UK schools. As fewer students already smoke, students exist in spaces where tobacco norms have changed and those who continue to smoke may be less influenced by the school norms [16]. Despite this, many key interventions to target adolescent smoking that have been found to be effective, are still based on harnessing peer influence and changing pro-smoking norms within the school context [7]. ...
... In particular, a meta-ethnography, whereby variation in tobacco denormalisation contexts are taken into account could help to elicit overarching theoretical interpretations and understanding of the included primary studies, that are bigger than the sum of their parts [17]. This systematic review and meta-ethnography builds upon previous research by adding a focus on smoking normalisation contexts to address the following research question and sub-questions: 1) How do school students (age [11][12][13][14][15][16][17][18], school staff, parents, or other education professionals view peer influence on adolescent smoking attitudes and behaviours? ...
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Background A relationship between smoking and interpersonal influences has been well established within the literature. There have been cultural shifts in denormalisation and a reduction in tobacco smoking in many countries. Hence there is a need to understand social influences on adolescents’ smoking across smoking normalisation contexts. Methods The search was conducted in July 2019 and updated in March 2022 within 11 databases and secondary sources. Search terms included schools, adolescents, smoking, peers, social norms and qualitative research. Screening was conducted by two researchers independently and in duplicate. Study quality was assessed using the eight-item Evidence for Policy and Practice Information and Co-ordinating Centre (EPPI-centre) tool for the appraisal of qualitative studies. Results were synthesised using a meta-narrative lens for meta-ethnography and compared across smoking normalisation contexts. Results Forty one studies were included and five themes were developed, mapping onto the socio ecological model. The social processes by which adolescents take up smoking differed according to a mixture of school type, peer group structure and the smoking culture within the school, as well as the wider cultural context. Data available from smoking denormalised contexts, described changes in social interactions around smoking to cope with its stigmatisation. This was manifested through i) direct peer influence, whereby subtle techniques were employed, ii) group belonging whereby smoking was less likely to be seen as a key determinant of group membership and smoking was less commonly reported to be used as a social tool, and iii) popularity and identity construction, whereby smoking was perceived more negatively in a denormalised context, compared with a normalised context. Conclusions This meta-ethnography is the first study to demonstrate, drawing on international data, that peer processes in adolescent smoking may undergo changes as smoking norms within society change. Future research should focus on understanding differences across socioeconomic contexts, to inform the adaptation of interventions.
... The results of the study in Table 2 showed that all the defined factors except the socio-economic status are preventive factors in quitting smoking. Recently many researches have considered the ways of helping smoker adolescents to quit smoking (27)(28)(29). In a study conducted on the Korean adolescents, the predictors of smoking cessation were the intention to stop smoking, the amount of cigarette use, self-efficacy, and paternal smoking status (30). ...
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... For example, Hallingberg et al. examined associations between the strength of school smoking policies and student cigarette, e-cigarette and cannabis use. 28 In addition, Morgan et al. undertook multi-level analysis exploring student and school-level predictors of physical activity and sedentary behaviour. 29 ...
... The significant difference in perceived pros of smoking in the preparation stage suggested that adolescents were aware of the cons or negative smoking aspects and clearly recognized the benefits of quitting (31). Self-efficacy was higher in the preparation stage, suggesting that adolescents' confidence in quitting smoking was bolstered (32). In other words, adolescents were prepared to quit smoking when they positively evaluated their abilities to quit smoking (33). ...
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... La nivel de școală, dacă școala dispune de o politică împotriva fumatului și are și în programa de învățământ ore în care se discută efectele negative ale fumatului, acești factori se comportă independent față de fumatul mai scăzut. O mai bună relație între colegii din cadrul clasei, atașamentul școlar mai mare și performanțele academice superioare sunt asociate cu cote mai mici ale fumătorilor [19,20,21]. ...
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... As well as family, schools are significant and are already recognised as a key influence of children's normative perceptions of tobacco. 21,22 While some studies have considered school influence on e-cigarette perceptions, 23,24 evidence to date is limited, particularly for younger pupils. One of the few available studies, conducted in Wales with primary school populations, identified significant variations in pupil knowledge of the function and potential risks of e-cigarettes, which varied by pupil age with older pupils being more informed, and also by whether pupils knew an e-cigarette user or not. ...
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Experimentation with e-cigarettes has grown rapidly among UK adolescents. To date, this topic has been primarily researched in secondary schools, with less understanding of development of attitudes and behaviours at an earlier age. This research reports qualitative data from interviews with pupils, parents, and teachers at 4 case study schools in Wales (N = 42). It draws on Bronfenbrenner’s Ecological Systems Theory to consider how the intersection of systems surrounding primary school-age children and their interaction with these systems, shape knowledge, and attitudes towards e-cigarettes and tobacco. Findings indicate that consistent messaging on smoking from school and family was reflected in strong disapproval among pupils and clear understanding of harms. This was less evident for e-cigarettes, where messages were mixed and inconsistent between home and school, with concerns over what to tell children about e-cigarettes in light of mixed messages and absence of official guidance. Implications of findings for policy and teaching are discussed.
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This preregistered systematic review and meta-analysis (PROSPERO: CRD 42022311392) aimed to synthesize the effectiveness of all available population-level tobacco policies on smoking behaviour. Our search across 5 databases and leading organizational websites resulted in 9,925 records, with 476 studies meeting our inclusion criteria. In our narrative summary and both pairwise and network meta-analyses, we identified anti-smoking campaigns, health warnings and tax increases as the most effective tobacco policies for promoting smoking cessation. Flavour bans and free/discounted nicotine replacement therapy also showed statistically significant positive effects on quit rates. The network meta-analysis results further indicated that smoking bans, anti-tobacco campaigns and tax increases effectively reduced smoking prevalence. In addition, flavour bans significantly reduced e-cigarette consumption. Both the narrative summary and the meta-analyses revealed that smoking bans, tax increases and anti-tobacco campaigns were associated with reductions in tobacco consumption and sales. On the basis of the available evidence, anti-tobacco campaigns, smoking bans, health warnings and tax increases are probably the most effective policies for curbing smoking behaviour.
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Full-text available
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To describe electronic cigarette (e-cigarette) use and cigarette use among adolescents and determine whether established risk factors for smoking discriminate user categories. School-based survey of 1941 high school students (mean age 14.6 years) in Hawaii; data collected in 2013. The survey assessed e-cigarette use and cigarette use, alcohol and marijuana use, and psychosocial risk and protective variables (eg, parental support, academic involvement, smoking expectancies, peer smoking, sensation seeking). Analysis of variance and multinomial regression examined variation in risk and protective variables across the following categories of ever-use: e-cigarette only, cigarette only, dual use (use of both products), and nonuser (never used either product). Prevalence for the categories was 17% (e-cigarettes only), 12% (dual use), 3% (cigarettes only), and 68% (nonusers). Dual users and cigarette-only users were highest on risk status (elevated on risk factors and lower on protective factors) compared with other groups. E-cigarette only users were higher on risk status than nonusers but lower than dual users. E-cigarette only users and dual users more often perceived e-cigarettes as healthier than cigarettes compared with nonusers. This study reports a US adolescent sample with one of the largest prevalence rates of e-cigarette only use in the existing literature. Dual use also had a substantial prevalence. The fact that e-cigarette only users were intermediate in risk status between nonusers and dual users raises the possibility that e-cigarettes are recruiting medium-risk adolescents, who otherwise would be less susceptible to tobacco product use. Copyright © 2015 by the American Academy of Pediatrics.
Chapter
This book, first published in 2002, represents a systematic discussion of the Gateway Hypothesis, a developmental hypothesis formulated to model how adolescents initiate and progress in the use of various drugs. In the United States, this progression proceeds from the use of tobacco or alcohol to the use of marijuana and other illicit drugs. This volume presents a critical overview of what is currently known about the Gateway Hypothesis. The authors of the chapters explore the hypothesis from various perspectives ranging from developmental social psychology to prevention and intervention science, animal models, neurobiology and analytical methodology. This volume is original and unique in its purview, covering a broad view of the Gateway Hypothesis. The juxtaposition of epidemiological, intervention, animal and neurobiological studies represents a new stage in the evolution of drug research, in which epidemiology and biology inform one another in the understanding of drug abuse.
Article
Healthy children achieve better educational outcomes which, in turn, are associated with improved health later in life. The World Health Organization's Health Promoting Schools (HPS) framework is a holistic approach to promoting health and educational attainment in school. The effectiveness of this approach has not yet been rigorously reviewed. METHODS: We searched 20 health, education and social science databases, and trials registries and relevant websites in 2011 and 2013. We included cluster randomised controlled trials. Participants were children and young people aged four to 18 years attending schools/colleges. HPS interventions had to include the following three elements: input into the curriculum; changes to the school's ethos or environment; and engagement with families and/or local communities. Two reviewers identified relevant trials, extracted data and assessed risk of bias. We grouped studies according to the health topic(s) targeted. Where data permitted, we performed random-effects meta-analyses. RESULTS: We identified 67 eligible trials tackling a range of health issues. Few studies included any academic/attendance outcomes. We found positive average intervention effects for: body mass index (BMI), physical activity, physical fitness, fruit and vegetable intake, tobacco use, and being bullied. Intervention effects were generally small. On average across studies, we found little evidence of effectiveness for zBMI (BMI, standardized for age and gender), and no evidence for fat intake, alcohol use, drug use, mental health, violence and bullying others. It was not possible to meta-analyse data on other health outcomes due to lack of data. Methodological limitations were identified including reliance on self-reported data, lack of long-term follow-up, and high attrition rates. CONCLUSION: This Cochrane review has found the WHO HPS framework is effective at improving some aspects of student health. The effects are small but potentially important at a population level.
Article
In contrast to curriculum-based health education interventions in schools, the school environment approach promotes health by modifying schools' physical/social environment. This systematic review reports on the health effects of the school environment and processes by which these might occur. It includes theories, intervention outcome and process evaluations, quantitative studies and qualitative studies. Research questions Research question (RQ)1: What theories are used to inform school environment interventions or explain school-level health influences? What testable hypotheses are suggested? RQ2: What are the effects on student health/inequalities of school environment interventions addressing organisation/management; teaching/pastoral care/discipline; and the physical environment? What are the costs? RQ3: How feasible/acceptable and context dependent are such interventions? RQ4: What are the effects on student health/inequalities of school-level measures of organisation/management; teaching/pastoral care/discipline; and the physical environment? RQ5: Through what processes might such influences occur? Data sources A total of 16 databases were searched between 30 July 2010 and 23 September 2010 to identify relevant studies, including the British Educational Index, the Cumulative Index to Nursing and Allied Health Literature, the Health Management Information Consortium, EMBASE, MEDLINE and PsycINFO. In addition, references of included studies were checked and authors contacted. Review methods In stage 1, we mapped references concerning how the school environment affects health and consulted stakeholders to identify stage 2 priorities. In stage 2, we undertook five reviews corresponding to our RQs. Results Stage 1: A total of 82,775 references were retrieved and 1144 were descriptively mapped. Stage 2: A total of 24 theories were identified (RQ1). The human functioning and school organisation, social capital and social development theories were judged most useful. Ten outcome evaluations were included (RQ2). Four US randomised controlled trials (RCTs) and one UK quasi-experimental study examined interventions building school community/relationships. Studies reported benefits for some, but not all outcomes (e.g. aggression, conflict resolution, emotional health). Two US RCTs assessed interventions empowering students to contribute to modifying food/physical activity environments, reporting benefits for physical activity but not for diet. Three UK quasi-experimental evaluations examined playground improvements, reporting mixed findings, with benefits being greater for younger children and longer break times. Six process evaluations (RQ3) reported positively. One study suggested that implementation was facilitated when this built on existing ethos and when senior staff were supportive. We reviewed 42 multilevel studies, confining narrative synthesis to 10 that appropriately adjusted for confounders. Four UK/US reports suggested that schools with higher value-added attainment/attendance had lower rates of substance use and fighting. Three reports from different countries examined school policies on smoking/alcohol, with mixed results. One US study found that schools with more unobservable/unsupervised places reported increased substance use. Another US study reported that school size, age structure and staffing ratio did not correlate with student drinking. Twenty-one qualitative reports from different countries (RQ5) suggested that disengagement, lack of safety and lack of participation in decisions may predispose students to engage in health risks. Limitations We found no evidence regarding health inequalities or cost, and could not undertake meta-analysis. Conclusions There is non-definitive evidence for the feasibility and effectiveness of school environment interventions involving community/relationship building, empowering student participation in modifying schools' food/physical activity environments, and playground improvements. Multilevel studies suggest that schools that add value educationally may promote student health. Qualitative studies suggest pathways underlying these effects. This evidence lends broad support to theories of social development, social capital and human functioning and school organisation. Further trials to examine the effects of school environment modifications on student health are recommended. Funding The National Institute for Health Research Public Health Research programme.
Article
Healthy children achieve better educational outcomes which, in turn, are associated with improved health later in life. The World Health Organization’s Health Promoting Schools (HPS) framework is a holistic approach to promoting health and educational attainment in school. The effectiveness of this approach has not yet been rigorously reviewed. We searched 20 health, education and social science databases, and trials registries and relevant websites in 2011 and 2013. We included cluster randomised controlled trials. Participants were children and young people aged four to 18 years attending schools/colleges. HPS interventions had to include the following three elements: input into the curriculum; changes to the school’s ethos or environment; and engagement with families and/or local communities. Two reviewers identified relevant trials, extracted data and assessed risk of bias. We grouped studies according to the health topic(s) targeted. Where data permitted, we performed random-effects meta-analyses. We identified 67 eligible trials tackling a range of health issues. Few studies included any academic/attendance outcomes. We found positive average intervention effects for: body mass index (BMI), physical activity, physical fitness, fruit and vegetable intake, tobacco use, and being bullied. Intervention effects were generally small. On average across studies, we found little evidence of effectiveness for zBMI (BMI, standardized for age and gender), and no evidence for fat intake, alcohol use, drug use, mental health, violence and bullying others. It was not possible to meta-analyse data on other health outcomes due to lack of data. Methodological limitations were identified including reliance on self-reported data, lack of long-term follow-up, and high attrition rates. This Cochrane review has found the WHO HPS framework is effective at improving some aspects of student health. The effects are small but potentially important at a population level.
Article
Background: There has been an increase in non-daily smoking, alternative tobacco product and marijuana use among young adults in recent years. Objectives: This study examined perceptions of health risks, addictiveness, and social acceptability of cigarettes, cigar products, smokeless tobacco, hookah, electronic cigarettes, and marijuana among young adults and correlates of such perceptions. Methods: In Spring 2013, 10,000 students at two universities in the Southeastern United States were recruited to complete an online survey (2,002 respondents), assessing personal, parental, and peer use of each product; and perceptions of health risks, addictiveness, and social acceptability of each of these products. Results: Marijuana was the most commonly used product in the past month (19.2%), with hookah being the second most commonly used (16.4%). The least commonly used were smokeless tobacco products (2.6%) and electronic cigarettes (4.5%). There were high rates of concurrent product use, particularly among electronic cigarette users. The most positively perceived was marijuana, with hookah and electronic cigarettes being second. While tobacco use and related social factors, related positively, influenced perceptions of marijuana, marijuana use and related social factors were not associated with perceptions of any tobacco product. Conclusions/Importance: Marketing efforts to promote electronic cigarettes and hookah to be safe and socially acceptable seem to be effective, while policy changes seem to be altering perceptions of marijuana and related social norms. Research is needed to document the health risks and addictive nature of emerging tobacco products and marijuana and evaluate efforts to communicate such risks to youth.