School characteristics may account for some of the variation in smoking prevalence among schools. The purpose of this study was to investigate the relationships between characteristics of school tobacco policies and school smoking prevalence. We also examined the relationship between these characteristics and individual smoking status.
Tobacco policy data were collected from schools in 10 Canadian provinces during the 2004-2005 school year. Written tobacco policies were collected from each school to examine policy intent, and school administrators were surveyed to assess policy enforcement. Students in grades 5 through 9 completed the Youth Smoking Survey to assess smoking behaviors and attitudes. We used negative binomial regression and multilevel logistic regression to predict the influence of school policies on smoking behavior at the school and student levels.
School policies that explicitly stated purpose and goals predicted lower prevalence of smoking at the school and individual levels. Policies that prohibited smoking on school grounds at all times predicted lower smoking prevalence at the school level but not at the individual level.
For maximum effectiveness, school smoking policies should clearly state a purpose and goals and should emphasize smoking prohibition. These policies can help reduce smoking prevalence among youths and are part of a comprehensive school approach to tobacco control.
Environmental factors influence smoking behaviors (
Tobacco control policies targeted at the population level have been a successful public health strategy, but school smoking policies have had mixed effects on individual behavior (
A school smoking policy is considered to be strong if it was developed with input from students and is comprehensive, consistently enforced, and addresses prevention education and cessation strategies (
Both policy content and implementation need to be considered when predicting smoking behavior (
Both individual and community factors influence smoking behaviors, and the prevalence of smoking varies from school to school. This variation suggests that an ecologic analysis is necessary to understand student smoking behaviors. Yet most research on school smoking policies has focused on examining the relationship of policies to individual smoking status. Although we acknowledge that the purpose of school smoking policies is to influence individual smoking behavior, school policies are primarily intended to focus on the environment by encouraging and reinforcing nonsmoking norms within the school setting.
The purpose of this study was to examine how policy characteristics are associated with school smoking prevalence. We conducted a secondary analysis to examine how these characteristics influence the smoking status of individual students.
A total of 281 elementary and secondary schools in 10 Canadian provinces were recruited (55% response rate) as part of the 2004-2005 Youth Smoking Survey (YSS) (
In conjunction with the YSS, school administrators were asked to provide all written documentation pertaining to the school's smoking policy at the time of data collection. At each school, an administrator who was knowledgeable about the smoking policy was interviewed to assess enforcement. This study was approved by the University of British Columbia behavioral research ethics board.
Student smoking behaviors were assessed by the YSS (
We measured smoking status as a binary outcome at the student level (1 = smoker, 0 = nonsmoker). A smoker was defined as having smoked at least 100 cigarettes in his or her lifetime and also having smoked, even just a puff, in the last 30 days. At the school level, smoking prevalence was calculated as a continuous variable by dividing the number of respondents identified as smokers by the total number of respondents.
To assess policy intent, we examined the school's written smoking policy. A policy could either be the school's own policy or, in cases where schools did not develop their own policy, the school board policy. Some schools had both their own policy and a board policy, in which case the school policy was used. We omitted from analysis schools that did not have their own policy or a board policy.
To quantify policy intent, we used a coding scheme adapted from a validated school policy rubric (
To assess policy implementation, we developed a survey that incorporated school health questionnaires (
Two comparable variables were used to examine student or school grade. For the school-level analysis, the highest grade at the school (eg, 12) was used to indicate the potential influence of older students. For the student-level analysis, the grade of the respondent was used as a control variable. For this level of analysis, highest grade at the school was not a significant covariate after students' grades were included; thus, we omitted this variable from the analysis.
For our full models, we tested the relationship between the score for each policy variable and the school smoking prevalence or student smoking status. Using type 3 hypothesis testing of the variables included in these models (
Negative binomial regression analysis was used to examine the relationship between school policy characteristics and school smoking prevalence. This approach was selected to account for overdispersion of smoking prevalence (mean, 1.53%; standard deviation, 3.08%). The distribution of smoking prevalence was nonnormal and was too skewed to allow traditional methods of transforming the data for linear modeling. This nonnormal distribution was due to a high number of schools at both extremes of smoking prevalence; 61% of schools had no identified smokers. For the purposes of the negative binomial regression, smoking prevalence was represented as a count or discrete variable instead of a continuous variable. The fit of the negative binomial distribution was adequate for both the full and reduced models (full model: χ2 /
Multilevel logistic regression analysis was used to determine the relationship between school policy characteristics and individual smoking status. Pearson χ2 analysis indicated that the overall fit of the logistic model was adequate for both the full and reduced models (full model: χ2 /
For all variables included in the models (Tables
Of the 281 schools recruited, complete data were available for 272 schools and 27,892 students in grades 5 through 9. Students were approximately evenly distributed by sex (girls, 53%) and grade level.
The overall smoking prevalence was 1.5%; there was no significant difference in smoking status by sex. The grade configuration of each school (by highest grade at school) is reported in
Eight percent of schools had no written tobacco policy. The mean smoking prevalence was highest for schools with only a school-developed policy (2.6%), followed by schools with their own policy and a district policy in place (1.6%), schools with only a district policy in place, (1.2%), and schools with no policy (0.7%).
Predictors of school smoking prevalence that were retained from the full model were the highest grade level at the school, 3 policy intent variables (purpose and goals, smoking prohibition, and assistance overcoming tobacco addictions), and 1 enforcement variable, the presence of an enforcement officer (
Predictors of student smoking status that were retained from the full model were the student's grade, 3 policy intent variables (purpose and goals, smoking prohibition, and assistance overcoming tobacco addictions), and 1 enforcement variable, the presence of an enforcement officer (
We found that school smoking policies can influence individual smoking status at both the school and individual levels, which is consistent with previous studies (
Policies that included a clearly stated purpose and goals predicted less smoking at both the individual and school levels. A clearly stated rationale may suggest a more established tobacco control strategy or a stronger commitment by school administrators to address smoking issues. Policy guidelines indicate that purpose and goals are key components of a good policy (
Schools with written policies that mandated cessation programs had higher smoking rates at both school and individual levels. Schools with many students and staff who smoke likely would have had more reason to develop and mandate tobacco cessation programs. The cross-sectional nature of this research does not allow us to address this question.
Most (92%) schools in this study had a written school or board tobacco policy in place. This finding is encouraging and suggests that schools are taking action to reduce and prevent student tobacco use. However, the policies were generally weak. In particular, scores for developing, overseeing, and communicating policy and strength of enforcement were very low, which may explain their lack of statistical significance. Also, many of the written policies, particularly in elementary schools, were simple excerpts from a student handbook and not fully developed. Anecdotally, many school personnel commented that they did not feel that a policy was necessary for an elementary school.
Older students were more likely to smoke than were younger students, and smoking rates among students in grades 5 through 9 were higher in schools with older students (up to grade 12) than in schools with younger students. Having older students at a school appears to influence the smoking behavior of younger students, which confirms similar findings (
In recent years, schools have been encouraged to provide tobacco use prevention education as part of an effective strategy. The effectiveness of these programs is mixed (
We found that many elements of school tobacco policies were not associated with smoking behaviors. Most policy characteristics alone likely account for only small variations in smoking. Many factors work together to influence smoking, including individual, school, and community factors that were not measured in this study. A study by Murnaghan et al (
Many studies have used multilevel analysis to address factors related to smoking, but this approach makes it difficult to "disentangle effects with observational data sets" (
This study has limitations that should be considered. First, students were in grades 5 through 9, where smoking rates tend to be lower than among older students. We coordinated this study with a national survey of youth focused on this age group. The survey has been recently expanded to include older students. Second, the coding rubrics in this study need to be further tested for reliability and validity. Policy scores derived from our coding scheme were restricted in range, particularly for certain items, which may have limited our ability to detect any relationship with smoking. Finally, data in this study are cross-sectional. Longitudinal analyses examining smoking and the school environment are needed to better understand the effects of school context on smoking behavior.
Despite these limitations, this study contributes to research on school tobacco policies by focusing on the school outcomes, the level to which policies are directed. On the basis of our results and the existing research, we conclude that school smoking policies can contribute to reducing youth smoking as part of a comprehensive school approach to tobacco control. To maximize impact, policies should describe their purpose and goals and should emphasize smoking prohibition.
This research was supported by a Canadian Tobacco Control Research Initiatives policy research grant (no. 016038). We thank the students and school administrators for their participation in this project. We also thank the Propel Centre for Population Health Impact at the University of Waterloo and the Interdisciplinary Capacity Enhancement Program for providing support for this project. The 2004-2005 Youth Smoking Survey (YSS) is a product of the Pan-Canadian Capacity Building Project funded through a contribution agreement between Health Canada and the Propel Centre for Population Health Impact. The YSS Consortium included Canadian tobacco control researchers from all provinces and provided training opportunities for university students at all levels. Production of this paper was funded by Health Canada.
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Sampling Framework, Youth Smoking Survey, Canada, 2004-2005
| Province | Selected Boards by Stratum | Selected Schools by Stratum | |||
|---|---|---|---|---|---|
| High | Low | Other | Junior | Senior | |
| Newfoundland and Labrador | 0 | 0 | 4 | 12 | 12 |
| Nova Scotia | 0 | 0 | 5 | 11 | 13 |
| Prince Edward Island | 0 | 0 | 2 | 14 | 10 |
| New Brunswick | 2 | 2 | 0 | 8 | 12 |
| Quebec | 4 | 5 | 1 | 24 | 12 |
| Ontario | 5 | 6 | 1 | 11 | 30 |
| Manitoba | 3 | 3 | 2 | 11 | 17 |
| Saskatchewan | 2 | 3 | 1 | 3 | 19 |
| Alberta | 5 | 2 | 1 | 10 | 20 |
| British Columbia | 4 | 4 | 1 | 16 | 16 |
School boards in a health region with a smoking rate at the median or higher.
School boards in a health region with a smoking rate lower than the median smoking rate.
All school boards in Newfoundland and Labrador, Nova Scotia, and Prince Edward Island were selected. This stratum also includes private, French language, and First Nation school boards for provinces in which these are administratively separate from public boards.
Schools with students in grades 5, 6, 5-6, and 6-7.
Schools with students in grades 5-8, 5-9, 6-8, 6-9, 7, 7-8, 7-9, 8, and 9.
Sample Items Used to Code Policy Intent Variables, Youth Smoking Survey, Canada, 2004-2005
| Sample Items | Scoring Range | Cronbach α | |
|---|---|---|---|
| Developing, overseeing, and communicating policy | Is the tobacco policy written? | 0-14 | .67 |
| Purpose and goals | Are the intent and rationale of the tobacco policy outlined? | 0-1 | NA |
| Smoking prohibition | Does the policy prohibit smoking of tobacco by students? | 0-1 | NA |
| Possession prohibition | Does the policy prohibit possession of tobacco by students? | 0-1 | NA |
| Strength of enforcement | Does the policy specify how often specific punishments, referrals, and mandatory programs are administered when students violate the tobacco policy? | 0-9 | .67 |
| Characteristics of enforcement | Does the tobacco policy specify that sanctions should get stronger with repeat offenses? | 0-2 | .42 |
| Tobacco use prevention education | Does the tobacco policy mandate that all students receive instruction to avoid tobacco use? | 0-1 | NA |
| Assistance to overcome tobacco addictions | Does the tobacco policy specify the availability of cessation programs for students and/or staff? | 0-1 | NA |
Abbreviation: NA, not applicable.
Computed for school-level data; student-level data showed comparable values.
Items Used to Code Policy Enforcement Variables, Youth Smoking Survey, Canada, 2004-2005
| Description | Scoring Range | Cronbach α | |
|---|---|---|---|
| Enforcement officer | Does the school designate a person who has primary responsibility for enforcement of tobacco use policy? | 0-1 | NA |
| Consistency of tobacco policy enforcement (students) | How consistently is tobacco policy enforced with students (never to always)? | 0-3 | NA |
| Consistency of tobacco policy enforcement (other) | How consistently is tobacco policy enforced with teachers or staff, parents, and school visitors? | 0-9 | .92 |
Abbreviation: NA, not applicable.
Highest Grade in Participating Schools, Youth Smoking Survey, Canada, 2004-2005
| No. of Schools (%), N = 272 | |
|---|---|
| 5 | 17 (6) |
| 6 | 81 (30) |
| 7 | 18 (7) |
| 8 | 54 (20) |
| 9 | 21 (8) |
| 10 | 4 (1) |
| 11 | 5 (2) |
| 12 | 72 (26) |
Predictors of School Smoking Prevalence for Students in Grades 5-9, Youth Smoking Survey, Administrator Survey, and Collected School Written Policies, Canada, 2004-2005
| Relative Risk (95% CI) | ||
|---|---|---|
| Highest grade present at school | 1.66 (1.47-1.88) | <.001 |
| Developing, overseeing, and communicating policy | 1.02 (0.80-1.28) | .93 |
| Purpose and goals | 0.64 (0.36-1.18) | .15 |
| Smoking prohibition | 0.44 (0.20-0.98) | .04 |
| Possession prohibition | 0.61 (0.34-1.12) | .10 |
| Strength of enforcement | 1.02 (0.88-1.20) | .79 |
| Characteristics of enforcement | 1.06 (0.69-1.61) | .80 |
| Tobacco use prevention education | 0.65 (0.23-1.78) | .40 |
| Assistance to overcome tobacco addictions | 2.33 (0.98-6.00) | .06 |
| Enforcement officer | 0.65 (0.39-1.08) | .09 |
| Consistency of enforcement (students) | 1.03 (0.55-1.87) | .92 |
| Consistency of enforcement (other) | 0.97 (0.80-1.17) | .69 |
| Highest grade present at school | 1.65 (1.47-1.87) | <.001 |
| Purpose and goals | 0.57 (0.34-0.99) | .04 |
| Smoking prohibition | 0.43 (0.20-0.97) | .04 |
| Assistance to overcome tobacco addictions | 2.15 (1.10-4.37) | .03 |
| Enforcement officer | 0.65 (0.39-1.06) | .08 |
Abbreviation: CI, confidence interval.
Calculated by using χ2 test.
Predictors of Smoker Status
| Odds Ratio (95% CI) | ||
|---|---|---|
| Student's grade | 2.81 (1.93-4.09) | <.001 |
| Male sex | 0.82 (0.54-1.23) | .33 |
| Developing, overseeing, and communicating policy | 0.79 (0.57-1.09) | .14 |
| Purpose and goals | 0.40 (0.14-1.14) | .08 |
| Smoking prohibition | 0.54 (0.23-1.26) | .15 |
| Possession prohibition | 0.97 (0.48-1.96) | .95 |
| Strength of enforcement | 0.97 (0.83-1.11) | .67 |
| Characteristics of enforcement | 1.31 (0.74-2.38) | .35 |
| Tobacco use prevention education | 0.69 (0.18-2.66) | .29 |
| Assistance to overcome tobacco addictions | 2.69 (1.34-5.42) | .005 |
| Enforcement officer | 0.60 (0.36-0.99) | .05 |
| Consistency of enforcement (students) | 1.63 (0.55-4.82) | .38 |
| Consistency of enforcement (other) | 0.91 (0.64-1.30) | .62 |
| Student's grade | 2.81 (1.92-4.12) | <.001 |
| Purpose and goals | 0.38 (0.15-0.95) | .04 |
| Smoking prohibition | 0.53 (0.22-1.26) | .15 |
| Assistance to overcome tobacco addictions | 2.23 (1.12-4.45) | .02 |
| Enforcement officer | 0.62 (0.37-1.04) | .07 |
Abbreviation: CI, confidence interval.
Smoker status was defined as having smoked at least 100 cigarettes in his or her lifetime and having smoked, even just a puff, in the last 30 days.
Calculated by using χ2 test.