Article Text

Evaluation of California's in-school tobacco use prevention education (TUPE) activities using a nested school-longitudinal design, 2003–2004 and 2005–2006
1. Hye-Youn Park1,
2. Clyde Dent2,
3. Erin Abramsohn1,
4. Barbara Dietsch3,
5. William J McCarthy3,4,5
1. 1California Department of Public Health, California Tobacco, Control Program, Sacramento, California, USA
2. 2Institute for Health Promotion and Disease Prevention Research, Department of Preventive Medicine, University of Southern California, Los Angeles, California, USA
3. 3WestEd, Los Angeles, California, USA
4. 4Department of Health Services, School of Public Health, University of California, Los Angeles, California, USA
5. 5Department of Psychology, University of California, Los Angeles, California, USA
1. Correspondence to Dr Hye-Youn Park, California Department of Public Health, California Tobacco Control Program, PO Box 997377, MS 7206, Sacramento, CA 95899-7377, USA; Hye-Youn.Park{at}cdph.ca.gov

## Abstract

Background Current legislative language requires the California Department of Public Health, California Tobacco Control Program, to evaluate the effectiveness of the school-based Tobacco Use Prevention Education (TUPE) programme in California every 2 years. The objective of the study was to measure change and to identify the impact of school-based tobacco use prevention education activities on youth smoking prevalence and attitudes over time, spanning two school year surveys (2003–2004 and 2005–2006).

Methods Evaluation focused on school-based tobacco use prevention activities in 57 schools (student sample size, n=16 833) that participated in the in-school administration of the 2003–2004 and 2005–2006 California Student Tobacco Surveys. Hierarchical linear models were used to predict student tobacco use and precursors to tobacco use.

Results Overall, student tobacco use, intention to smoke, number of friends smoking and perceived smoking prevalence by peers increased as students moved through grades 9 and 10 to grades 11 and 12. TUPE-related activities showed a suggestive association (p=0.06) with reduced rate in student tobacco use between the two surveys after adjusting for other contextual factors such as each school's socioeconomic characteristics.

Conclusions TUPE activities appears to be beneficial in reducing tobacco use in California high school students over time. Other contextual factors were important moderating influences on student tobacco use.

## Introduction

Early smoking initiation increases the likelihood of adult smoking dependence.1 Historically, studies showed that 80% of US adult smokers between the ages of 30 and 39 began to smoke during their adolescent years; in other words, few Americans appeared to initiate smoking after age 20.2 3 This suggests that if youth smoking can be prevented, fewer adults will be smokers.2 However, more recent evidence suggests that reductions in youth initiation have been associated with increases in initiation among older adolescents and young adults.4

Many influences have been shown to increase the risk of smoking initiation. They include social environmental influences such as having a parent, sibling or close friend who smokes, perceiving peer smoking prevalence to be high or living in a home where smoking is allowed.5 6 Depression, low school grades and stressful life events may increase the risk of smoking initiation. Tobacco-specific experiences, such as the use of smokeless tobacco, perceived instrumental value of smoking and previous experimentation with tobacco, have also been shown to increase risk for initiation.5–9 Two character traits predictive of smoking are risk-taking/rebelliousness and susceptibility to smoking.9 10 Finally, media influences (eg, anti-tobacco advertising, smoking in movies and news media coverage) have also been documented to be an important part of an adolescent's social and environmental context and have the potential to shape attitudes and behaviours.11

School-based tobacco-use prevention interventions have the capacity to integrate prevention information into school curricula and the advantage of reaching adolescents. In the short-term, school-based tobacco-use prevention interventions have been found to be considerably effective in reducing prevalence and initiation, and improving smoking intentions and attitudes.12–16 Conversely, school-based interventions have been found to be generally ineffective in preventing long-term initiation.17 However, these interventions have been found to be effective when combined with other approaches such as media campaigns and smoke-free policies.18

## Results

### Sample characteristics

Table 1 presents basic characteristics of high schools that participated in two consecutive surveys (2003–2004 and 2005–2006). Of the 65 eligible high schools that participated in the 2003–2004 survey, the same 57 schools were surveyed again in 2005–2006.

Table 1

Demographic characteristics of re-surveyed high schools (n=50)

Overall, average student enrolment size in participating high schools was 2358; the proportion of white, non-Hispanic/Latino (a) students was 43.5%; and female students comprised 51.4% of the sample.

### Grade and time trends in tobacco use

Table 2 shows current smoking prevalence, defined as smoking on one or more days in the last 30 days, during the two different survey times by grade. Overall high school prevalence of current smoking significantly increased by 2.6% (p<0.001) from 2003–2004 to 2005–2006. Moreover, current smoking prevalence increased in every grade during this period, by approximately 2.0–3.0%. By contrast, no significant change was found in the overall lifetime smoking prevalence over time during this same period, not for any grade.

Table 2

### Cohort trends in tobacco use and its precursors

Table 3 displays the change in the birth cohort tobacco use-related outcomes over time. Increases were observed in the smoking index, intention to smoke and number of friends smoking in each birth cohort as students moved from grades 9 and 10 to grades 11 and 12. Student estimates of peer smoking increased along with actual increases in perceived smoking prevalence of students in the same grade and the smoking index.

Table 3

Time trends in tobacco use and its precursors

Among the tobacco use-related attitude and belief indices, there were significant decreases in perceived negative social and health consequences of smoking, respectively (p<0.05). The decreases in these protective factors over time were consistent with the observed increases in smoking. Overall, the belief that smoking has a positive social value did not change with age. Also, attitudes towards the tobacco industry among students as they aged remained relatively unchanged.

### Impact of TUPE exposure

In the present study, we examined the impact of exposure to the school-based TUPE activities as reflected in the global implementation index, not by TUPE funding status, because even non-TUPE funded schools still can have other federally recommended tobacco prevention activities, as mentioned earlier. The global implementation index was based on data from teachers, district TUPE coordinators and school TUPE coordinators. The impact was measured in two ways: (1) as the cross-sectional association between TUPE implementation exposure and tobacco-related outcomes at baseline; and (2) as the impact of TUPE activity exposure on the birth cohort changes over time in tobacco use-related attitudes and smoking behaviours (table 4). TUPE activity was significantly associated with smoking index increases (p=0.009) and with students' estimates of peer smoking prevalence (p=0.04) at baseline. However, other outcome variables did not show a significant cross-sectional association with TUPE activity.

Table 4

Effects of tobacco use prevention education (TUPE) implementation activities on tobacco use and other precursors (bivariate analyses)

On the other hand, the level of TUPE implementation at each school was found to affect, over time, the smoking index, intention to smoke and number of friends who smoked. The increased smoking index level for students who moved from the 9th or 10th grade to 11th or 12th grade over 2-year period was found to be reduced by an average of 0.070 SD units (p=0.004) for every one SD unit increase in the global implementation index. Similarly, intentions to smoke were also impacted, with a predicted reduction of 0.059 SD units (p=0.013) for each one SD unit increase in TUPE implementation activities. The change in the reported number of friends who smoked was also reduced by 0.076 SD units (p=0.001) for each 1 SD unit increase in TUPE activities. Somewhat surprisingly, birth cohort changes in the other precursors of smoking examined, such as attitudes about social and health consequences, appeared to be unaffected by student exposure to school TUPE activities.

### Effects of TUPE activities and contextual factors on smoking

Table 5 provides the results of the multivariate hierarchical linear model predicting smoking index as an outcome of school-level factors, both cross-sectionally and as a predictor of birth cohort changes in smoking.

Table 5

Effects of external factors on smoking index (multivariate hierarchical linear regression model)

The index of community support for tobacco control was associated with smoking in cross-sectional analysis (p<0.01) but not with birth cohort changes in smoking over time (p=0.796). The anti-tobacco media message index was not associated with smoking at baseline (p=0.182) but was associated with increases in smoking over time (p=0.021). Enrolment and an index of school-level socioeconomic factors (average API score, average parent educational attainment, and percentage of students eligible for school lunch subsidies) at each school, were related to lower levels of smoking at baseline, but were associated with higher 2-year birth cohort changes in the prevalence of smoking.

At baseline, school TUPE implementation was not significantly associated with student smoking prevalence (coefficient of 0.020 (p=0.297); table 5). However, the coefficient for the change in this association over time (−0.043, p=0.064) indicated a suggestive benefit of TUPE implementation on reducing student smoking after 2 years. The differences in coefficient estimates between the bivariate model (table 4) and the model adjusted for contextual factors such as school socioeconomic status suggests that these factors may confound the association between school TUPE-related activities and student smoking prevalence. The difference in fit statistics for full model (−2 LL=25852.93) and a reduced model without school TUPE index variable (−2 LL=25861.79) was 8.86, with 2 degrees of freedom (p<0.02).

## Discussion

California has witnessed continual decreases in the prevalence of current smoking among youths since 1995.19 20 However, in 2005–2006 this downward trend in prevalence was reversed and prevalence of current smoking increased. The current analysis confirms that the prevalence of current smoking among high school students increased relative to 2003–2004. In this study, decreases in protective factors were consistent with parallel increases observed in smoking prevalence; factors included perceived negative social and health consequences of smoking over time, an increase in intention to smoke, number of friends who smoke and student perceptions of smoking prevalence among peers.

However, the reason for the observed increase in current smoking prevalence is unclear. It may be due to an underlying cohort effect25 or to other factors such as a decrease in the real price of cigarettes26 or decrease of tobacco control mass media messages,27 which can have a significant impact on youth smoking rates. In addition to these factors, the Centers for Disease Control and Prevention has attributed the lack of decline in national youth smoking prevalence to substantial increases in tobacco industry expenditures on tobacco advertising and promotion in the USA. Tobacco industry expenditure have increased from $5.7 billion in 1997 to$15.2 billion in 2003.28

According to the final multivariate model, cross-sectional effects of TUPE implementation activities at baseline showed no association with the smoking index, whereas over the 2-year period, we observed a suggestive change towards a negative association between the level of TUPE activities and the smoking index. Two possible explanations for this pattern of results are that the schools with high tobacco use rates may have been more motivated to apply for TUPE programme funds and to carry out TUPE-related activities that might have resulted in a reduction in smoking or schools with fewer TUPE activities had greater increases in smoking prevalence over time.

The school-level index of perceived community support for tobacco control was examined as one of the contextual factors. Previously, implementation of community-level comprehensive tobacco control strategies has been recommended to reduce youth smoking.29 30 The cross-sectional results show that increases in student-reported community support for tobacco control were significantly associated with a lower smoking index. However, the school cohort analysis of change over the two time points did not show a significant association on the change which might imply the effect of community support index on smoking index started getting weakened over time.

Reitsma and Manske noted that student tobacco use varied as a function of the size of the school with smoking rates highest in schools of intermediate size and lowest in the biggest schools.31 Our study showed that larger school enrolment was associated with a lower smoking index at baseline, whereas the comparison over time showed a significant positive change, indicating that this effect had disappeared by the second time period. Generally, small schools are less likely to apply for competitive grants of any kind, because they tend not to have enough staff members with time dedicated to writing grants. Therefore, a significant change to the positive direction in the association could reflect real increased trends in the risk of students becoming smokers because reductions in TUPE activities over time may have been greater in large schools than in small schools, which would make no difference in smoking prevalence between small and large schools.

Similar trends were seen with the school socioeconomic context index, which was constructed from combining average parent education levels, Academic Performance Index (API) scores, and percentage of students eligible for federal lunch subsidies at each school. High family socioeconomic status (SES),32 33 positive parental influence34 and students' academic performance35 36 are recognised as important protective influences with respect to health behaviours such as alcohol drinking, smoking and drug use. It was therefore expected that these components of the measure of school socioeconomic context in the present study would at least partially explain a preventive influence on student smoking behaviour. However, the significant positive change in the association between the school socioeconomic context index and the smoking index over time implies a weakening of the effect and, we found nearly no difference by the second year which is counter-intuitive and warrants further research. It is possible that students with high socioeconomic status are more able to afford to buy tobacco products despite of increased prices compared to those with low socioeconomic status, and we observed by the second year distributions of smoking index among high SES groups was similar to that in low SES (data not shown).

When we controlled for other factors, including community tobacco control context, we found that higher student exposure to anti-tobacco media messages was associated with increased smoking prevalence. This change towards more positive direction of observed association was significant over the 2-year period, but was not significant at baseline. This finding is not surprising because never-smokers have been shown to be generally less attentive to commercial and public service tobacco-related messages compared to current smokers.37 38 Additionally, media exposure may be related to other factors that are not in the model, such as rural or urban geographic status. Also, the present analysis was about school effects as a main exposure of interest, rather than media effects, and only four questions were used for the anti-media index, which were not specifically targeted anti-media questions. To test the impact of media on smoking prevalence, we would have collected and used very different measures, such as student ratings of specific commercial tobacco advertisements.

There are some limitations to be addressed in this study. While the same schools were followed for two consecutive surveys, the same students were not necessarily sampled. Hence, we assume individual students at the same school followed the same developmental trajectory—for instance, social and physical development. Although differential changes in development among individuals within the same school are unlikely to be dramatic, the possibility of bias should be taken account for interpretation of the results. In addition (appendix I), eight schools were lost to follow-up at the second cycle of survey, and we found more white students and high SES groups were in those losses. However, student level demographic as well as school level SES covariates were controlled in the model. In any case, the distributions of ethnicity and smoking prevalence among the remaining cohort schools (n=57) were similar to those of the 91 non-carry high schools that participated in the 2003–2004 survey. We believe that it is less likely to introduce biases by differential attrition by ethnicity and related SES.

All student data were obtained from in-school students volunteering to complete self-reported questionnaires. Thus, self-report bias and non-participation by high school dropouts may have contributed to underestimating the true smoking prevalence among California high school students.35 Also, even though TUPE was implemented in small schools, we chose to conserve our limited evaluation resources by restricting the cohort study sample to schools with at least 50 students per school enrolled from the original sampling frame. As a result, our findings may not apply to schools with enrolment smaller than 50 students per school.

The main strengths of the present study are the large sample size and the use of TUPE implementation data collected from teachers and school administrators that yielded valid and reliable measures of TUPE activities. In addition, the use of a repeated cross-sectional design provides an efficient and minimally biased estimator of change at a much lower cost than would be required with longitudinal cohort design.39

Even after controlling for potentially biasing contextual factors, these results revealed a marginally significant association between school level TUPE activities and decreased smoking index scores over the 2-year period (p=0.06), suggesting that TUPE implementation activities helped to reduce student smoking over time; however, the normally robust inverse association between school-level SES measures and the smoking index became non-significant at the 2-year follow-up, possibly because of increased dropout among low-SES smokers in the 12th grade. Of further concern is the lack of evidence that anti-tobacco media messages had any effect on smoking prevalence among high school students in California.

Regardless of the findings, this study demonstrates how a relatively low-cost, practical evaluation design can be used to assess longitudinally the impact of school-based tobacco control intervention activities on student smoking prevalence.

Prospective examination of changes in school-average student tobacco use behaviour and related attitudes over a 2-year interval permitted stronger evaluation of programme impact than is possible with cross-sectional data. Our study suggests support for the beneficial effect of TUPE activities over time on reducing student smoking. Results also suggest that evaluation of school-based TUPE needs to consider influences of other comprehensive strategies such as community support for tobacco control.

## Acknowledgments

The authors thank the California students and schools for their participation in this survey.

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## Footnotes

• Competing interests None.

• Ethics approval This study was conducted with the approval of the Health and Welfare Agency, committee for the Protection of Human Subjects at the Office of Statewide Health Planning and Development in California.

• Provenance and peer review Not commissioned; externally peer reviewed.

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