INTRODUCTION
Tobacco use in early life has been shown to negatively impact physical (e.g. pulmonary and cardiovascular diseases)1 or psychological (e.g. depression and anxiety disorders)2 health both immediately and in the future3. It also increases the likelihood of smoking later in adulthood3. In China, smoking prevalence remains high, especially in schools. For example, the 2019 Middle School Students Tobacco Survey conducted in China revealed that 24.5% of senior high school students have tried smoking, and the proportion was even higher in vocational high school students (30.3%)4. In addition, electronic cigarettes have become increasingly popular among teens. It was also reported that the proportion of Chinese junior middle school students that knew of e-cigarettes increased from 45.0% in 2014 to 69.9% in 20194. Despite of the high smoking prevalence, according to the WHO report, China was among 59 countries that have not fully implemented the MPOWER5 policy package: Monitoring tobacco use; Protecting people from the tobacco; Offering help to quit tobacco; Warning about the dangers; Enforcing bans on advertising, promotion and sponsorship; and Raising tobacco taxes.
School personnel could play an important role in adolescent smoking6,7. On the one hand, smoking status of school personnel influences students’ smoking. A study focusing on social-cognitive factors among adolescent smoking status showed that teachers’ norms on tobacco use was a significant contributor8. High visibility of teacher’s smoking was related to an increasing smoking rate among students7. On the other hand, school personnel could help students stay away from tobacco. In one study, positive relationships were observed between teachers’ anti-tobacco norms and smoke-free school policies perceived by students9. In another study, 70% of the junior middle school personnel in Taiwan have advised their students to quit smoking, which was associated with a decrease in students’ tobacco use10. Clearly, school personnel’s anti-tobacco attitudes and behaviors are closely associated with adolescent tobacco use. When it comes to the adolescent smoking control on campus, improving the tobacco control attitudes and behaviors among school personnel can be beneficial.
Studies have reported that school personnel’s attitudes and behaviors were positively associated with their anti-tobacco policy awareness11,12. Raising school personnel’s awareness of anti-smoking policies might be important to form their anti-smoking attitudes and behaviors and later reduce smoking among their students. To date, many policies have been proposed and implemented around the world in response to the globalization of tobacco epidemic. WHO MPOWER is a policy package developed by WHO Framework Convention on Tobacco Control (FCTC) to reverse the tobacco epidemic13. From 2007 to 2014, MPOWER policy was adopted in 88 countries, contributing to the decreased number of smoking-attributable deaths by almost 22 million14. In alignment with initiatives of FCTC, the Chinese government amended Advertisement Law (AL) of People’s Republic of China in 2015 to regulate tobacco advertising in all mass media and public places15. Published in 2016, the national action plan Healthy China 2030 aims to reduce smoking rate of people aged ≥15 years to 20% by the year of 2030. To meet this goal, several cities have established or amended local tobacco control laws and regulations. In Shanghai, the Regulations of Shanghai Municipality on Smoking Control in Public Places was revised to prohibit smoking in all indoor workplaces and in many public outdoor areas. Since the implementation in 2017, smoking rate in public places of Shanghai had dropped to 12.8% by 202016.
Though many anti-tobacco policies are in place, the awareness of those policies among the public is alarmingly low in many countries including China. In Nigeria, about one-third of young people had never heard of any tobacco control law, and 48.1% did not known about the WHO FCTC17,18. Data from a survey in Pakistan has indicated that 46.1% of the students had never noticed smoke-free policies around them19. The relationship between knowledge-attitude-belief and practice (KABP)20 has been widely applied in research on health behavior and decision-making theories21,22, and was important in the implications for tobacco control23. However, to the best of our knowledge, few published original studies have examined the awareness of anti-tobacco policies as part of the knowledge, which is actually a very simple but valuable perception, rather than exploring its relationship with people’s attitudes and behaviors, especially among school personnel groups. In the current study, we aimed to assess the awareness of anti-tobacco policies among school personnel and evaluate its association with their tobacco control attitudes and behaviors towards students. The findings will provide important evidence for the government to develop school tobacco control strategies with the improvement of school personnel’s role.
METHODS
Study design and participants
This cross-sectional study with a two-stage stratified cluster randomized sampling design was carried out between September 2017 and January 2018 in Shanghai, China. In the first stage, we conducted the selection of districts randomly from all the 16 districts according to location: Huangpu District and Putuo District as samples for urban areas and Minhang District, Jiading District for rural areas. The second stage involved the selection of schools based on proportion-to-size sampling approach (17 for junior middle schools, 10 for senior high schools and 6 for vocational high schools). Finally, all the 3311 school personnel working in the 33 schools were included, covering administrators, teachers and other staff.
The questionnaires were filled in anonymously on a platform for questionnaire surveys (https://www.wjx.cn/). The survey was a modified design of the Global School Personnel Survey (GSPS) initiated by WHO24 and ‘questionnaires for monitoring smoking related behaviors of key population’ from the Chinese Center for Disease Control and Prevention.
Measures
Awareness of tobacco control policies
The awareness of tobacco control policies was assessed by asking: ‘Which of the following tobacco control policies have you heard of?’. The options shown in our questionnaire included: WHO FCTC, MPOWER, Regulations of Shanghai Municipality on Smoking Control in Public Places, Advertisement Law (AL) of People’s Republic of China, and Healthy China 2030. Based on their answers, we categorized the participants into three groups: those who knew none of the policies, those who knew 1–3 types, and those who knew 4 or 5 types.
Attitudes towards tobacco control
To estimate their attitudes towards tobacco control measures which had already been put into practice, participants were asked: ‘Do you support the 'comprehensive bans on tobacco advertising'?’, ‘What is your attitude towards prohibiting smoking in indoor public places (such as schools, shops, restaurants, cinemas, airports, etc.)?’, ‘What is your attitude towards prohibiting outdoor smoking in public places (such as parks/squares/open-air sports venues/bus stations, etc.)?’, and ‘Do you support printing warning pictures of tobacco-related diseases on cigarette boxes in China?’. Answers were set on a four-point Likert-type scale: those who fully support, partially support, do not care, or not support any measure. Based on their answers, we then categorized the participants into two groups: the ‘Totally support’ group including those who chose ‘Fully support’ for all four questions and ‘Others’ group covering the rest of participants.
Behaviors related to tobacco control
Participants were asked whether they adopted the following behaviors and activities in the past one year: 1) prevented students from smoking, 2) advised students to quit smoking, and 3) participated in any educational activities related to tobacco control for students held by schools. Personnel that chose ‘Yes’ for all three questions were classified as ‘Totally participants’ and the rest were classified as ‘Others’.
Other variables
Potential confounders were district (urban or rural), school type (junior middle school, senior high school or vocational high school), age (20–29, 30–39, 40–49, 50–65 years), sex (male or female), working duration (<10 years or ≥10 years), educational level (college and below, Bachelor’s and above), and position (teachers, administrators or other staff). Personnel were also classified by their smoking status: ‘never smoker’, ‘former smoker’ and ‘current smoker’. ‘Current smoker’ refers to the personnel who smoke currently, including daily smokers and those who smoked occasionally. Participants who had never smoked were referred to as ‘never smoker’, while those with smoking experience but had quit smoking successfully at the moment of the survey were referred to as ‘former smoker’. Also, personnel’s involvement in tobacco control training was measured by asking: ‘Have you ever received any relevant training to prevent teenage smoking?’
Statistical analysis
All data analysis was performed using SPSS 22.0 (SPSS Statistic Inc., Chicago, IL, USA) complex sampling analysis procedure to provide weighted results that accounted for the complex sample design after excluding missing data. A chi-squared test was used to compare the differences in categorical variables between groups. Unadjusted (ORs) and adjusted odds ratios (AORs) and 95% confidence intervals (95% CI) were calculated using multiple logistic regression analysis to explore the associations between the independent variable (awareness level of tobacco control policy) and dependent variables (attitude and behavior of tobacco control). Adjusted odds ratios were controlled for district, school type, age, sex, work duration, education level, position in school, training of tobacco control and smoking status. Awareness of tobacco control policies was treated as both ordinal variables and continuous variable in models. A threshold for statistical significance was set at a two-sided p<0.05 level.
RESULTS
Sample characteristics
In total, 3311 school personnel from 33 schools participated in the survey. The final sample size was 3194 (response rate of 96.47%), after removing those not passing the data quality check (n=117), e.g. finished the questionnaire too quickly (<300 s). As shown in Table 1, 60.7% of the participants were from rural areas, 65.2% were aged 30–49 years, 73.3% were females and 80.6% were teachers. Sixty-eight percent had worked for over 10 years, and 91.6% had a Bachelor’s degree or above. Regarding the school type, 58.2% worked in junior middle schools, 27.0% in senior high schools, and 14.8% in vocational high schools. Among all the participants, 7.4% were currently smoking and 84.1% had never received any training on teenage smoking prevention.
Table 1
Demographic characteristics, policy awareness, tobacco control attitude and behavior of school personnel, Shanghai, China 2017–2018 (N=3194)
| Variables | Weighted | Unweighted | ||
|---|---|---|---|---|
| % | 95% CI | Population | n | |
| District | ||||
| Urban | 39.3 | 37.6–41.0 | 33979 | 1281 |
| Rural | 60.7 | 59.0–62.4 | 52576 | 1913 |
| School type | ||||
| Junior middle school | 58.2 | 56.5–59.9 | 50394 | 1719 |
| Senior high school | 27.0 | 25.4–28.7 | 23411 | 681 |
| Vocational high school | 14.8 | 13.8–15.8 | 12750 | 794 |
| Age (years) | ||||
| 20–29 | 16.9 | 15.6–18.2 | 14581 | 518 |
| 30–39 | 30.3 | 28.7–32.0 | 26261 | 961 |
| 40–49 | 34.9 | 33.3–36.6 | 30239 | 1127 |
| 50–65 | 17.9 | 16.6–19.3 | 15475 | 588 |
| Sex | ||||
| Male | 26.7 | 25.2–28.2 | 23082 | 887 |
| Female | 73.3 | 71.8–74.8 | 63474 | 2307 |
| Work duration (years) | ||||
| <10 | 32.0 | 30.4–33.7 | 27693 | 1028 |
| ≥10 | 68.0 | 66.3–69.6 | 58862 | 2166 |
| Education level | ||||
| College and below | 8.4 | 7.5–9.4 | 7283 | 319 |
| Bachelor’s and above | 91.6 | 90.6–92.5 | 79272 | 2875 |
| Position | ||||
| Teacher | 80.6 | 79.2–81.9 | 69775 | 2521 |
| Administrator | 7.3 | 6.4–8.2 | 6279 | 241 |
| Other staff | 12.1 | 11.1–13.3 | 10501 | 432 |
| Training of tobacco control | ||||
| No | 84.1 | 82.8–85.3 | 72781 | 2677 |
| Yes | 15.9 | 14.7–17.2 | 13775 | 517 |
| Smoking status | ||||
| Never | 88.8 | 87.7–89.9 | 76884 | 2805 |
| Former | 3.8 | 3.2–4.5 | 3299 | 128 |
| Current | 7.4 | 6.5–8.3 | 6373 | 261 |
| Policy awareness a | ||||
| None | 13.0 | 11.8–14.2 | 11216 | 427 |
| 1–3 types | 64.6 | 62.9–66.3 | 55952 | 2039 |
| 4–5 types | 22.4 | 21.0–23.9 | 19387 | 728 |
| Support attitude to policyb | ||||
| Others | 24.9 | 23.4–26.4 | 21515 | 827 |
| Totally support | 75.1 | 73.6–76.6 | 65041 | 2367 |
| Tobacco control behavior in schoolc | ||||
| Others | 82.3 | 80.9–83.6 | 71221 | 2581 |
| Totally participants | 17.7 | 16.4–19.1 | 15334 | 613 |
a Policy awareness: the number of anti-tobacco policies that the participant having heard of among all the five policies listed in the survey.
Tobacco control policy awareness, attitudes and behaviors among personnel
Regarding the tobacco control policies, the proportion of school personnel having heard of the WHO FCTC (49.7%), MPOWER (29.6%) and AL of People’s Republic of China (49.8%) were all lower than 50%, except for Regulations of Shanghai Municipality on Smoking Control in Public Places (68.3%). In addition, the proportion of participants knowing Healthy China 2030 was the lowest (25.4%). Among the five different types, 22.4% of the participants were aware of 4–5 types and 13.0% knew none of the policies. As for personnel’s attitudes towards four types of anti-tobacco measures, the rate of fully supportive was higher than 85% in every type, while the proportion of participants who fully supported all four measures (totally support) was 75.1%. Regarding anti-tobacco behaviors in school, less than half of the school personnel tried to prevent students from smoking (45.7%) or encourage them to stop smoking (42.4%), yet 37.4% had participated in smoking-related educational activities on campus in the previous year. The proportion of participants endorsing all three kinds of tobacco control behaviors in school was 17.7%.
Relationship between policy awareness and tobacco control attitudes and behaviors
The awareness of anti-tobacco policies was positively associated with supportive attitudes towards tobacco control (Table 2), especially for outdoor smoking banning and anti-tobacco warning pictures (p<0.05 in every type of policy). For example, rate of fully supporting anti-tobacco warning pictures was higher in participants knowing FCTC (94.0%) than those having not heard of it (85.1%). Besides, higher awareness also showed significantly higher chance of anti-tobacco behaviors in schools, with exception of the relationship between Regulations of Smoking Control in Public Place and advising students to quit smoking/preventing students from smoking as well as the difference between Healthy China 2030 and advising students to quit smoking.
Table 2
Supportive attitudes to anti-tobacco measurements and tobacco control behaviors stratified by awareness of different policies among the total sample [% (95% CI)], Shanghai, China 2017–2018 (N=3194)
| Total | FCTC c | MPOWER d | Healthy China 2030 | Regulations of smoking control in public place | Advertisement law | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| No | Yes | p | No | Yes | p | No | Yes | p | No | Yes | p | No | Yes | p | ||
| Indoor banninga | ||||||||||||||||
| Fully support | 94.6 (93.7–95.3) | 94.0 (92.7–95.0) | 95.1 (94.0–96.1) | 0.140 | 94.5 (93.5–95.4) | 94.7 (93.2–95.9) | 0.802 | 94.3 (93.3–95.2) | 95.2 (93.6–96.5) | 0.313 | 91.1 (89.2–92.7) | 96.2 (95.3–96.9) | <0.001 | 93.0 (91.7–94.2) | 96.1 (95.1–96.9) | <0.001 |
| Others | 5.4 (4.7–6.3) | 6.0 (5.0–7.3) | 4.9 (3.9–6.0) | 5.5 (4.6–6.5) | 5.3 (4.1–6.8) | 5.7 (4.8–6.7) | 4.8 (3.5–6.4) | 8.9 (7.3–10.8) | 3.8 (3.1–4.7) | 7.0 (5.8–8.3) | 3.9 (3.1–4.9) | |||||
| Outdoor banninga | ||||||||||||||||
| Fully support | 86.3 (85.1–87.5) | 84.5 (82.6–86.2) | 88.2 (86.5–89.7) | 0.002 | 85.2 (83.7–86.6) | 88.9 (86.8–90.7) | 0.005 | 85.2 (83.7–86.5) | 89.7 (87.5–91.6) | 0.001 | 83.2 (80.8–85.4) | 87.8 (86.3–89.1) | 0.001 | 84.5 (82.6–86.2) | 88.1 (86.5–89.6) | 0.003 |
| Others | 13.7 (12.5–14.9) | 15.5 (13.8–17.4) | 11.8 (10.3–13.5) | 14.8 (13.4–16.3) | 11.1 (9.3–13.2) | 14.8 (13.5–16.3) | 10.3 (8.4–12.5) | 16.8 (14.6–19.2) | 12.2 (10.9–13.7) | 15.5 (13.8–17.4) | 11.9 (10.4–13.5) | |||||
| Advertising banninga | ||||||||||||||||
| Fully support | 90.9 (89.9–91.9) | 89.8 (88.3–91.2) | 92.0 (90.5–93.2) | 0.038 | 90.6 (89.3–91.7) | 91.7 (89.8–93.3) | 0.288 | 89.8 (88.5–91.05) | 94.1 (92.2–95.5) | <0.001 | 87.7 (85.5–89.6) | 92.4 (91.2–93.5) | <0.001 | 88.9 (87.3–90.4) | 92.9 (91.5–94.1) | <0.001 |
| Others | 9.1 (8.1–10.1) | 10.2 (8.8–11.8) | 8.0 (6.8–9.5) | 9.4 (8.3–10.7) | 8.3 (6.7–10.2) | 10.2 (9.0–11.5) | 5.9 (4.5–7.8) | 12.3 (10.4–14.5) | 7.6 (6.5–8.8) | 11.1 (9.6–12.7) | 7.1 (5.9–8.5) | |||||
| Warning picturea | ||||||||||||||||
| Fully support | 89.5 (88.4–90.5) | 85.1 (83.2–86.7) | 94.0 (92.7–95.1) | <0.001 | 88.1 (86.7–89.4) | 92.9 (91.1–94.4) | <0.001 | 87.9 (86.5–89.2) | 94.1 (92.3–95.6) | <0.001 | 86.0 (83.7–88.0) | 91.1 (89.9–92.3) | <0.001 | 86.7 (85.0–88.3) | 92.3 (90.8–93.5) | <0.001 |
| Others | 10.5 (9.5–11.6) | 14.9 (13.3–16.8) | 6.0 (4.9–7.3) | 11.9 (10.6–13.3) | 7.1 (5.6–8.9) | 12.1 (10.8–13.5) | 5.9 (4.4–7.7) | 14.0 (12.0–16.3) | 8.9 (7.7–10.1) | 13.3 (11.7–15.0) | 7.7 (6.5–9.2) | |||||
| Take part in educational activities on campusb | ||||||||||||||||
| No | 62.6 (60.9–64.3) | 69.2 (66.9–71.4) | 56.0 (53.5–58.5) | <0.001 | 66.2 (64.1–68.1) | 54.3 (51.1–57.5) | <0.001 | 66.2 (64.3–68.1) | 52.1 (48.7–55.6) | <0.001 | 68.9 (66.0–71.8) | 59.7 (57.6–61.8) | <0.001 | 67.9 (65.5–70.2) | 57.3 (54.9–59.8) | <0.001 |
| Yes | 37.4 (35.7–39.1) | 30.8 (28.6–33.1) | 44.0 (41.5–46.5) | 33.8 (31.9–35.9) | 45.7 (42.5–48.9) | 33.8 (31.9–35.7) | 47.9 (44.4–51.3) | 31.1 (28.2–34.0) | 40.3 (38.2–42.4) | 32.1 (29.8–34.5) | 42.7 (40.2–45.1) | |||||
| Prevent students from smokingb | ||||||||||||||||
| No | 54.3 (52.6–56.0) | 57.8 (55.3–60.2) | 50.8 (48.3–53.3) | <0.001 | 56.9 (54.8–58.9) | 48.2 (45.0–51.4) | <0.001 | 55.8 (53.8–57.8) | 50.0 (46.5–53.4) | 0.005 | 56.3 (53.2–59.4) | 53.4 (51.2–55.5) | 0.121 | 56.8 (54.4–59.3) | 51.8 (49.3–54.2) | 0.004 |
| Yes | 45.7 (44.0–47.4) | 42.2 (39.8–44.7) | 49.2 (46.7–51.7) | 43.1 (41.1–45.2) | 51.8 (48.6–55.0) | 44.2 (42.2–46.2) | 50.0 (46.6–53.5) | 43.7 (40.6–46.8) | 46.6 (44.5–48.8) | 43.2 (40.7–45.6) | 48.2 (45.8–50.7) | |||||
| Advise students to quit smokingb | ||||||||||||||||
| No | 57.6 (55.8–59.3) | 61.0 (58.6–63.3) | 54.1 (51.6–56.6) | <0.001 | 59.8 (57.7–61.8) | 52.2 (49.0–55.4) | <0.001 | 58.5 (56.5–60.5) | 54.6 (51.2–58.1) | 0.053 | 58.6 (55.6–61.7) | 57.0 (54.9–59.1) | 0.396 | 60.2 (57.8–62.6) | 54.9 (52.4–57.3) | 0.002 |
| Yes | 42.4 (40.7–44.2) | 39.0 (36.7–41.4) | 45.9 (43.4–48.4) | 40.2 (38.2–42.3) | 47.8 (44.6–51.0) | 41.5 (39.5–43.5) | 45.4 (41.9–48.8) | 41.4 (38.3–44.4) | 43.0 (40.9–45.1) | 39.8 (37.4–42.2) | 45.1 (42.7–47.6) | |||||
| Total | 50.3 (48.6–52.1) | 49.7 (47.9–51.4) | 70.4 (68.7–71.9) | 29.6 (28.1–31.3) | 74.6 (73.0–76.1) | 25.4 (23.9–27.0) | 31.7 (30.1–33.4) | 68.3 (66.6–69.9) | 50.2 (48.4–51.9) | 49.8 (48.1–51.6) | ||||||
Policy awareness, tobacco control attitudes and behaviors in school personnel with different characteristics
Table 3 shows the distributions stratified by various influencing factors including sociodemographic factors, work duration, position, smoking status and training experience. Personnel in urban areas (compared to rural area, p<0.01) or with longer work duration (≥10 years, compared to <10 years, p<0.001) were related to increased policy awareness, anti-tobacco attitudes and behaviors. Participants who received tobacco control training knew more types of anti-tobacco policies and had taken more actions to prevent/stop smoking among students compared to those without training experiences (p<0.001). Besides, school administrators were more likely to take anti-tobacco behaviors (28.8%) than school teachers (17.6%) or other staff (12.1%) (p<0.001). Majority of school administrators (90.1%) knew one to five policies given, higher than teachers (87.3%) and other staff (83.9%). Current smokers (29.3%) were less likely to fully support all four anti-tobacco measures than never (79.5%) or former (62.4%) smokers.
Table 3
Policy awareness, support attitude to policy and tobacco control behaviors in school across different characteristic of school personnel among the total sample [% (95% CI)], Shanghai, China 2017–2018 (N=3194)
| Policy awareness a | Attitudes towards policy b | Tobacco control behavior in school c | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| None | 1–3 types | 4–5 types | p | Others | Totally support | p | Others | Totally participants | p | |
| District | ||||||||||
| Urban | 10.2 (8.7–12.0) | 65.9 (63.2–68.4) | 23.9 (21.6–26.4) | 0.001 | 22.0 (19.8–24.3) | 78.0 (75.7–80.2) | 0.002 | 79.3 (77.0–81.4) | 20.7 (18.6–23.0) | <0.001 |
| Rural | 14.7 (13.2–16.4) | 63.9 (61.7–66.0) | 21.4 (19.6–23.3) | 26.7 (24.8–28.8) | 73.3 (71.2–75.2) | 84.2 (82.5–85.8) | 15.8 (14.2–17.5) | |||
| School type | ||||||||||
| Junior middle school | 12.2 (10.8–13.8) | 64.9 (62.6–67.1) | 22.9 (21.0–24.9) | 0.006 | 2121.6 (19.7–23.6) | 78.4 (76.4–80.3) | <0.001 | 85.0 (83.3–86.6) | 15.0 (13.4–16.7) | <0.001 |
| Senior high school | 12.6 (10.4–15.3) | 67.6 (64.0–70.9) | 19.8 (17.0–22.9) | 26.6 (23.4–30.0) | 76.6 (65.4–62.0) | 83.4 (80.5–86.0) | 19.5 (30.5–27.4) | |||
| Vocational high school | 16.5 (14.1–19.2) | 58.4 (55.0–61.8) | 25.1 (22.2–28.1) | 34.6 (31.4–38.0) | 65.4 (62.0–68.6) | 69.5 (66.3–72.6) | 30.5 (27.4–33.7) | |||
| Sex | ||||||||||
| Male | 13.5 (11.4–15.9) | 62.3 (59.0–65.5) | 24.2 (21.4–27.2) | 0.229 | 41.7 (38.4–45.0) | 58.3 (55.0–61.6) | <0.001 | 80.5 (77.7–83.0) | 19.5 (17.0–22.3) | 0.104 |
| Female | 12.8 (11.4–14.2) | 65.5 (63.5–67.4) | 21.7 (20.1–23.5) | 18.7 (17.2–20.4) | 81.3 (79.6–82.8) | 82.9 (81.4–84.4) | 17.1 (15.6–18.6) | |||
| Work duration (years) | ||||||||||
| <10 | 15.4 (13.3–17.8) | 65.7 (62.7–68.6) | 18.9 (16.6–21.4) | <0.001 | 29.7 (27.0–32.6) | 70.3 (67.4–73.0) | <0.001 | 87.9 (85.8–89.7) | 12.1 (10.3–14.2) | <0.001 |
| ≥10 | 11.8 (10.5–13.2) | 64.1 (62.1–66.2) | 24.1 (22.3–25.9) | 22.6 (20.8–24.4) | 77.4 (75.6–79.2) | 79.7 (77.9–81.3) | 20.3 (18.7–22.1) | |||
| Education level | ||||||||||
| College and below | 17.7 (13.8–22.5) | 48.0 (42.3–53.6) | 34.3 (29.2–39.8) | <0.001 | 41.8 (36.3–47.4) | 58.2 (52.6–63.7) | <0.001 | 84.8 (80.2–88.5) | 15.2 (11.5–19.8) | 0.245 |
| Bachelor’s and above | 12.5 (11.4–13.8) | 66.2 (64.4–67.9) | 21.3 (19.8–22.9) | 23.3 (21.8–24.9) | 76.7 (75.1–78.2) | 82.1 (80.6–83.4) | 17.9 (16.6–19.4) | |||
| Position | ||||||||||
| Teachers | 12.8 (11.5–14.1) | 66.5 (64.6–68.3) | 20.8 (19.2–22.4) | <0.001 | 23.3 (21.7–25.0) | 76.7 (75.0–78.3) | <0.001 | 82.4 (80.9–83.9) | 17.6 (16.1–19.1) | <0.001 |
| Administrator | 9.9 (6.6–14.6) | 64.0 (57.6–69.9) | 26.1 (20.8–32.2) | 25.3 (20.1–31.2) | 74.7 (68.8–79.9) | 71.2 (65.1–76.6) | 28.8 (23.4–34.9) | |||
| Other staff | 16.1 (12.9–20.0) | 52.9 (48.0–57.7) | 31.0 (26.7–35.7) | 35.0 (30.6–39.7) | 65.0 (60.3–69.4) | 87.9 (84.4–90.7) | 12.1 (9.3–15.6) | |||
| Smoking status | ||||||||||
| Never smoker | 12.9 (11.7–14.2) | 65.2 (63.3–66.9) | 21.9 (20.4–23.5) | 0.444 | 20.5 (19.0–22.1) | 79.5 (77.9–81.0) | <0.001 | 82.5 (81.0–83.8) | 17.5 (16.2–19.0) | 0.664 |
| Former smoker | 12.0 (7.4–18.7) | 61.7 (52.9–69.8) | 26.3 (19.4–34.7) | 37.6 (29.5–46.5) | 62.4 (53.5–70.5) | 79.5 (71.4–85.7) | 20.5 (14.3–28.6) | |||
| Current smoker | 13.7 (10.1–18.4) | 60.4 (54.2–66.3) | 25.9 (20.9–31.6) | 70.7 (64.7–76.0) | 29.3 (24.0–35.3) | 81.6 (76.4–85.9) | 18.4 (14.1–23.6) | |||
| Training of tobacco control | ||||||||||
| No | 14.4 (13.1–15.7) | 66.1 (64.2–67.8) | 19.6 (18.1–21.1) | <0.001 | 24.9 (23.3–26.6) | 75.1 (73.4–76.7) | 0.825 | 86.9 (85.5–88.1) | 13.1 (11.9–14.5) | <0.001 |
| Yes | 5.6 (3.9–7.9) | 57.2 (52.8–61.5) | 37.2 (33.1–41.6) | 24.5 (20.9–28.4) | 75.5 (71.6–79.1) | 58.1 (53.7–62.3) | 41.9 (37.7–46.3) | |||
Influence of policy awareness on tobacco control attitudes and behaviors
Table 4 shows the association between policy awareness and supportive attitudes and tobacco control behaviors among school personnel (p<0.001). After adjusting for covariates, compared with personnel who knew none of the policies, those who knew 1–3 types or 4–5 types were 1.74 (95% CI: 1.36–2.21) or 3.54 (95% CI: 2.60–4.82) times more likely to have supportive attitudes. The occurrence of tobacco control behaviors in those who knew 4–5 types of policies were 1.76 (95% CI: 1.23–2.51) times those who did not know any of the policies. When treated as a continuous variable, the policy awareness was still positively associated with anti-tobacco attitudes (AOR=1.28; 95% CI: 1.21–1.36) and behaviors (AOR=1.10; 95% CI: 1.03–1.17).
Table 4
Relationship between policy awareness and tobacco control attitude/behavior in school among school personnel, Shanghai, China 2017–2018 (N=3194)
DISCUSSION
The study reported a low tobacco control policy awareness among school personnel in Shanghai, and the awareness was positively related to their anti-tobacco attitudes and behaviors. The findings indicated the importance of improving policy awareness and increasing the involvement of school personnel in tobacco control on campus for adolescent smoking.
The relationship between anti-tobacco policies and smoking-related attitudes and behaviors has been studied in adult smokers before11,25. In those studies, the social unacceptability of smoking and smoking cessation were associated with exposure to specific policy measures, such as warning labels on packages and smoking restrictions at work. On campus, teachers in schools with a loosely restrictive tobacco use policy were less concerned about smoking around students and less supportive of anti-tobacco measures than teachers at tobacco-banning schools26. However, to our knowledge our study is the first study showing that the more types of anti-tobacco policies school personnel know, their attitudes and behaviors are more supportive towards tobacco control in students. Given the importance of school personnel in students’ behaviors, raising the awareness of anti-smoking policies among this group seems to be of great interest.
In fact, some studies supported the view that the involvement of school personnel in tobacco control campaign on campus can be effective. Increased awareness has been reported to increase compliance with policies and as a result reduce smoking27. This could be explained by the KABP model20 that is well known in behavioral studies. According to this model, the school personnel who are aware of the anti-tobacco policies may have better knowledge of the provisions (hazard, legal, educations, taxation, counseling/cessation service, etc.) than those who have not heard of these policies. Therefore, first they may hold a positive attitude towards tobacco control, thinking students’ smoking as an unhealthy behavior and likely to step in to help11. Second, many policies include detailed action plan so school personnel will be equipped with necessary knowledge and skills to take more effective actions for students27-29. Finally, many policies and regulations already include the requirements or suggestions for school personnel in the plan so they will be motivated during the process30. Personnel may be more familiar with the earlier regulations (like FCTC, MPOWER and AL in our study), making the association between these regulations and tobacco control behaviors more pronounced in the current study.
One alarming result of the study is that the policy awareness among school personnel is low. Only about half (49.7%) of the surveyed participants were aware of the WHO FCTC, which is similar with the percentage in Nigeria (51.9%)18. In Myanmar, 57.3% of the high school students had ever heard about the local tobacco control law: The Control of Smoking and Consumption of Tobacco Products Law31. In addition, the awareness of MPOWER and Healthy China 2030 were also low. The low awareness might be due to the fact that the tobacco control effort in China is relatively new. For example, even though the WHO FCTC was signed by China in 2003 and was put into effect in 2006, the first state-level legislation on tobacco control in public places has not been released yet – only a draft put forward in 201432. Fortunately, many local tobacco control regulations (those of Beijing33, Guangzhou34, Chongqing35, etc.) have been enacted in recent years and provided firsthand evidence for the establishment of national law. In addition, some other state-level tobacco control related strategies or regulations have been released in recent years, such as Healthy China 2030 in 2016. In October 2020, The Law of the People’s Republic of China on the Protection of Minors36 was revised and was added to the restrictions on the sale of tobacco to minors. Moreover, to cope with the rapid growth of e-cigarette use, Measures for The Management of Electronic Cigarettes37 was released by the Tobacco Monopoly Bureau on 11 March 2022.
In our study, many school personnel had not taken many actions regarding students’ smoking. Less than half of the surveyed participants had tried to prevent students from tobacco use, encourage them to quit smoking or participate in relevant educational activities on campus. It is possible that they have a lack of policy access, knowledge about tobacco hazards or little access to tobacco-related materials as suggested by a previous study10 and other findings of the current study. As reported before, smoking banning by ‘important people’ (school administrators, teachers) was associated with less tobacco use and more smoking cessation among students10,11,38. Given the high prevalence of adolescent smoking in China4, increasing involvement of school personnel in students’ tobacco control might be one strategy to help slow the spread of the smoking pandemic on campus.
Regarding the ways of increasing policy awareness and performing more actions, our study showed that receiving training on tobacco use prevention played an important role among school personnel. Specifically, school personnel who had training experience reported to have a higher policy awareness (94.4% vs 85.6%) and perform more actions against students’ smoking compared to those who had no training (41.9% vs 13.1%). However, less than 1 in 5 of the surveyed participants had ever received training related to tobacco control, which may have resulted in a lack of knowledge and techniques to help their students. This is consistent with previous studies in which most personnel had no access to tobacco prevention training (only 8% received training)10. The factors for the low training rate might be due to school personnel’s busy schedule or a lack of adequate educational materials. Thus, it would be helpful if tobacco control training can be set as part of their routine work in school, and related educational material offered to teachers, school administrators, and other relevant staff.
Besides training, working duration was also positively associated with policy awareness in our study and other reports39. Compared to teachers or other staff, school administrators seemed to have better policy awareness, possibly due to easier access to policies and guidelines as part of their routine work. In addition, personnel in rural areas had even lower policy awareness, and were engaged less in anti-tobacco behaviors/attitudes than those in urban areas in the current study. Although there is no significant difference in policy awareness according to smoking status, current smokers were less likely to support tobacco control measures than never/former smokers. Therefore, training focus could be given more on teachers and personnel with short working duration and smoking currently, especially in rural areas.
Limitations
Some limitations exist in this study. First, the crosssectional study design cannot determine the direction of causality. Second, our participants were only selected from schools in Shanghai which may not be generalized to other regions. Third, there was no student tobacco use data in our study, thus direct association with students’ tobacco use could not be assessed. In the future, a longitudinal study could be designed in both economically developed and developing areas to explore convincing causality and mechanisms. Besides, future research could include changes in adolescent smoking as part of the results, to analyze the effect of policy awareness better. Intervention studies focusing on improving awareness of anti-tobacco policies and strategies could also be conducted among school personnel.
CONCLUSIONS
The study calls for school management and local education department to implement projects or activities (like tobacco control training) to improve policy awareness in the school environment as part of school tobacco control strategy. Not only administrators but also teachers and other staff on campus should be taken into consideration especially those who are current smokers and with shorter work durations.
