1. Introduction Tobacco use represents a significant burden of death, disease, and economic cost around the world—particularly in low- and middle-income countries. Smoking-related diseases such as lung cancer, heart disease, and chronic obstructive pulmonary diseases are among the most common and deadly health risks. Smoking is spreading throughout many countries in the world due to the increasing number of young people. Mass media likes to focus on spreading the realization of the negative eff ...
1. Introduction to Tobacco Use and Its Prevalence The use of any form of tobacco poses an enormous and distinctive threat to the public's health, being responsible for a disparate variety of lethal ailments, innumerable chronic illnesses, millions of hospital admissions, and untold human pain and suffering. This report examines in depth the current state of tobacco consumption worldwide and its increasing concentration in developing countries. It describes several aspects of tobacco consumption ...
1. Introduction Although prevention of death has always been an underlying desire in man, a short but difficult life has meant that strategies aimed at achieving this end have conspicuously not been used wherein society has had a choice, since their side effects have either limited the quality of an individual's life or have resulted in death before the onset of the diseases of affluence that are now so common. However, an increased average life span has resulted from reduced starvation and the ...
1. Introduction Good health needs care. Proper care can be taken by choosing to live a healthy lifestyle. A healthy lifestyle implies trying to remain physically active and having good habits such as physical, mental, and social well-being. A person needs to stay updated with health and to do this, he should open a library for himself where he can gather various health books, and he should also gather useful health information. This will benefit him in the long run. To live a healthy lifestyle, ...
1. Introduction The impact of lifestyle choices on general well-being is significant. Many people are unaware that the simplest choices we make on a day-to-day basis can greatly affect our quality of life. Living a life full of ailments is inconvenient and can be avoided by making better lifestyle choices. One simple but significant lifestyle choice is to eat raw fruits and vegetables. Regularly consuming these foods can have a positive impact on your health and help prevent illnesses. Choosing ...
1. Introduction This research studies the impact of state smoking cessation programs on cigarette smoking both at the individual level and at the population level. A survey of 1,064 Kentuckians provides information on smoking behavior and program participation. A smoking cigarette demand estimation is carried out using the most likely participation equation. The negative effects of the measure are significant. A comparison of 2005 and 1990 datasets increases our confidence in the estimated resu ...
1. Introduction The study group on lifestyle-related diseases and the ministries of health and labour of the 195 member nations of the World Health Organization concluded that lifestyle choices contribute significantly to public health worldwide. Many of these lifestyle-related diseases limit both the number of healthy years a person lives and his or her quality of life. This paper examines lifestyle choices and the consequences of those decisions in six major issue areas: first, smoking and al ...
1. Introduction Smoking is a long-term addiction of younger age. It is recognized as one of the largest preventable causes of mortality, and in the prevention and reduction of smoking, it is very crucial to examine the effects of any condition and to raise awareness of the importance of the issue. In our country and worldwide, smoking prevalence is still quite high. In particular, when smoking effects are taken into consideration, the overall loss is much higher than the benefits. It is noticea ...
1. Introduction Addiction and its related problems, alongside psychological complications, are widely recognized and deeply interrelated. Addicted individuals face prejudice from society and have low social acceptability. This is an area that has been widely recognized recently in the scientific environment. Among the most common addictions are alcohol, tobacco, and illicit substance use. The number of deaths due to this problem is 11.8% of the whole, and around 85.3% of all causes are related ...
1. Introduction Chronic diseases have become a silent epidemic that is reaching crisis proportions because of the way people live their lives. The prevention and management of chronic diseases are heavily influenced by lifestyle choices, including physical inactivity, lack of exercise, smoking, and improper diet. Four behavioral risk factors - poor diet, physical inactivity, tobacco use, and excessive alcohol consumption - account for 60% of global deaths and almost 30% of the global burden of ...
1. Introduction High rates of chronic kidney disease (CKD) and insuficiencia renal are a concern as they silently progress, developing long-term disability, complications, and ultimately increasing the risk of death. Unhealthy lifestyle habits can lead to the development and progression of CKD, even though it is preventable and manageable with proper care and medical treatments. Clinical practice guidelines recommend risk factor modification and promote health, self-management, and shared decis ...
1. Introduction to Pender's Health Promotion Model Pender's Health Promotion Model (HPM) was developed to help people improve their well-being, and this model has provided useful guidance for developing health strategies in a variety of settings. Researchers have generated evidence for the efficacy and utility of the model based on modified and unmodified applications with a variety of populations and in a variety of settings. This chapter presents case studies that demonstrate the use of Pende ...
1. Introduction Non-communicable diseases (NCDs) have become the main cause of illness and death worldwide, especially within the industrialized nations. It is predicted that by the year 2020, NCDs will contribute to up to 75% of global deaths. The increasing prevalence of these diseases is associated with societal behavioral changes, such as cigarette smoking, increased alcohol consumption, lack of physical activity, and progressive levels of obesity. Medical research has focused on the identi ...
1. Introduction Though of course there are reasonable limits to the impact of subjective individual choices (smoking in enclosed public places impinging on non-smokers' health is an obvious example), nobody can seriously doubt the overall importance of individual lifestyle choices such as eating, drinking, exercise, hours of work, and sexual activity with regard to health and well-being. As in so many other areas, the fall in income poverty over time has been accompanied by a rise in depth and ...
1. Introduction Long-term health issues plague almost everyone, but only some people are permanently beset with ailments; the remainder never appear to have health problems unless they are involved in an accident. Some of this discrepancy is related to accidents, but most long-term health problems are not caused by accidents. Health problems can arise from birth, of course, and many health problems are exacerbated by a person's living and working conditions. Yet a fundamental aspect of why some ...
Smoking can be viewed as one of the trendy habits. Numerous teenagers try it since they think that it is cool or can help them socialize. Often students start smoking due to stress or mental illnesses. But is it okay?
Educators tend to give different written assignments, which may disclose this topic. If you have to develop a teenage smoking essay, you should learn the effects and harm that this habit causes.
That’s when our Custom-writing.org writers can help you!In the article, you’ll see how to deal with writing about smoking students. We’ve gathered tips for different paper types and prompts that can inspire you to start. In the end, you’ll find some smoking essay topics as well.
✍️ how to write a teenage smoking essay.
Just like any other academic paper, a teen smoking essay should be organized according to its type. You are probably familiar with the following writing ones:
Below, you can find insightful tips on how to compose a teenage smoking essay, fulfilling the requirements of each type.
An argumentative essay on teenage smoking should give the reader a rational discussion of a specific issue. The ideas are expected to be well-structured and solidified with valid evidence.
Below, you can find the most useful tips for writing an argumentative teen smoking essay. Don’t hesitate to use them!
A cause and effect of the teenage smoking essay should answer two questions:
How to create an excellent cause and effect paper? You can start by checking successful teen smoking essay examples. Then, learn some useful tips here:
A persuasive essay about teenage smoking resembles an argumentative one but has a different purpose. Here, you have to convince your reader in your opinion, using evidence and facts. Moreover, in some papers, you have to call your reader to action. For example, to quit or ban smoking . So, see how to do so:
You have a lot of ways of creating fantastic teen smoking essays. You should just turn around and gather material. Sometimes it lies near your foot.
To smoke or not to smoke? – This is the question! You should decide what is for you: To be yourself or follow the fashion! It is not difficult to do!
Do you know what the critical secret of a successful essay is? A well-chosen topic!
If you find something you are passionate about, your essay writing process will be much easier. So, take a look at our smoking essay topics. Select one of them or use some to come up with your idea.
Here are some writing prompts that you can use for your smoking essay:
Smoking among teenagers is a serious problem that has long-term consequences for their physical and mental health. In your essay, you can dwell on the following ideas:
Despite the implementation of smoke-free policies, a large percentage of teenagers start smoking during their school years. You can write an essay advocating for more effective initiatives to address not only students’ access to cigarettes but also the core causes of teen smoking.
Check out some more ideas for your “Smoking in School” essay:
Peer pressure is a common reason why teenagers start smoking. Friends, romantic attachments, or other social circles — all have significant effects on teens’ smoking intentions and possible tobacco addiction.
Here are some practical ideas that can help you highlight the role of peer pressure in teenage smoking :
There are many reasons why people start smoking, ranging from simple curiosity to complicated social and psychological factors, including anxiety, low self-esteem, and domestic violence.
Check out several ideas for an essay about the causes of smoking:
Cigarette smoking impacts nearly every organ in the body, causes a variety of diseases, and worsens smokers’ overall health.
In your essay, you can expand on the following ideas to show the severe consequences of smoking on human well-being:
According to the CDC, in 2023, 1 out of every 100 middle school students and nearly 2 out of every 100 high school students had smoked cigarettes in the past 30 days . Public health experts are especially concerned about e-cigarettes since flavorings in tobacco products can make cigarettes more appealing to teenagers.
To evaluate the current situation with smoking among teens, dwell on the following ideas in your essay:
Thanks for reading till the end! Make sure to leave your opinion about the article below. Send it to your friends who may need our tips.
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BMC Public Health volume 23 , Article number: 438 ( 2023 ) Cite this article
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There is an increase in the use of cigarettes and e-cigarettes worldwide, and the similar trends may be observed in young adults. Since 2014, e-cigarettes have become the most commonly used nicotine products among young adults (Sun et al., JAMA Netw Open 4:e2118788, 2021). With the increase in e-cigarette use and the decrease in use of cigarettes and other tobacco products, however, there is limited information about Chinese smokers, e-cigarettes users and trends in cigarettes and e-cigarettes use among university students. Therefore, our objective was to investigate the using status of cigarettes, e-cigarettes and smoking behavior among the students from 7 universities in Guangzhou, China.
Students at 7 different universities in Guangzhou were investigated online in 2021 through a cross-sectional survey. A total of 10,008 students were recruited and after screening, 9361 participants were adopted in our statistics. Descriptive analysis, Chi-square analysis, and multiple logistic regression analysis were used to explore the smoking status and influencing factors.
The average age of the 9361 university students was 22.4 years (SD = 3.6). 58.3% of participants were male. 29.8% of the participants smoked or used e-cigarettes. Among the smokers and users of e-cigarettes, 16.7% were e-cigarettes only users, 35.0% were cigarettes only users, and 48.3% were dual users.
Males were more likely to smoke or use e-cigarettes. Medical students, students from prestigious Chinese universities, and students with higher levels of education were less likely. Students with unhealthy lifestyles (e.g., drinking alcohol frequently, playing video games excessively, staying up late frequently) were more likely to smoke or use e-cigarettes. Emotion can have significant impacts on both cigarettes and e-cigarettes dual users when choosing cigarettes or e-cigarettes to use. More than half of dual users said they would choose cigarettes when they were depressed and e-cigarettes when they were happy.
We identified factors influencing the use of cigarettes and e-cigarettes among university students in Guangzhou, China. Gender, education level background, specialization, lifestyle habits and emotion all influenced the use of cigarettes and e-cigarettes among university students in Guangzhou, China. Male, low education level, from non-prestigious Chinese universities or vocational schools, non-medical specialization, and presence of unhealthy lifestyles were influencing factors for the use of cigarettes and e-cigarettes among university students in Guangzhou and students with these factors were more likely to smoke or use e-cigarettes. Besides, emotions can influence dual users' choice of products.
This study provides more information to better understand young people's preferences for cigarettes and e-cigarettes by elucidating the characteristics of cigarettes and e-cigarettes use, as well as related influencing factors, among university students in Guangzhou. Further research involving more variables connected to the use of cigarettes and e-cigarettes will be required in our future study.
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Despite numerous efforts to stop the tobacco epidemic, tobacco smoking is recognized as a major preventable cause of disease worldwide [ 1 ]. The 2021 Global Report on trends in the prevalence of tobacco use 2000–2025, published by the World Health Organization (WHO), states that tobacco use in any form kills and sickens millions of people every year and over 8 million people died from a tobacco-related disease in 2019 [ 2 ]. Smoking and passive smoke (exposure to second-hand smoke) are the key contributors to the mortality of specialization chronic diseases, namely, cardiovascular disease, chronic respiratory disease, and cancer [ 3 ]. The prevalence of current (at least 1 of the last 30 days) cigarettes smoking among Chinese adults reached 27.7% in 2015, making it one of the highest smoking rates in the world [ 4 ]. The health risks of smoking have attracted more and more attention, and smoking on campus has become a serious school and social problem [ 2 , 5 ].
Customers are getting more worried about the physical harm as their awareness of cigarettes' dangers is increased, and they are more encouraged to choose e-cigarettes which are claimed as less harmful and can meet their needs of risk reduction [ 6 ]. Many researches have shown that e-cigarettes, although they cannot be considered safe [ 7 ], may cause less harm to the body than cigarettes [ 8 , 9 , 10 , 11 ]. Some cigarettes smokers are converting to e-cigarettes to avoid the effects of smoking [ 12 ].
E-cigarettes are electronic devices that deliver nicotine to the respiratory system by atomizing an aerosol of smoke containing glycerin, propylene glycol, nicotine and other additives through an electric heating element [ 13 ]. Since e-cigarettes produce much less tar, carbon monoxide, and carcinogenic ingredients such as aldehydes, acids, and phenols, the exclusive use of e-cigarettes among smokers may reduce the number of diseases caused by such ingredients [ 14 , 15 , 16 ]. Studies have shown that cigarettes and e-cigarettes are the most frequently used nicotine products in youth adults in the USA [ 17 , 18 , 19 , 20 ] and probably China. China is the world’s largest consumer of tobacco products and contributes substantially to the global burden of smoking-related diseases [ 21 ]. It is noteworthy that the use of e-cigarettes in China is far less frequent than in some European countries and the United States [ 22 , 21 , 22 , 23 , 24 , 27 ].
However, the health risks of e-cigarettes have not been adequately studied, data on their effects and risks on human body are limited [ 15 , 28 ]. Despite the fact that using e-cigarettes is a worldwide phenomenon [ 29 , 30 ], there is a paucity of data regarding the knowledge and attitude of e-cigarettes users particularly among the young adults in China [ 31 ]. Studies of cigarettes and e-cigarettes use among e-cigarettes consumers are still in their infancy, with most of them being questionnaires about basic consumer information, consumption behavior and preferences. Most survey respondents are European and American e-cigarettes consumers, and there are limited reports on Chinese e-cigarettes consumers' vaping behavior. There is an urgent need to investigate the status quo and influence factors of smoking and using e-cigarettes [ 32 ].
Therefore, we conducted a cross-sectional survey of using cigarettes and e-cigarettes to investigate the smoking behaviors among university students in Guangzhou. One of our research interests was the use of cigarettes and e-cigarettes among university students. Another focus was on the factors that influence the use of cigarettes and e-cigarettes by university students.
A cross-sectional survey was developed in China that collected data through a self-administered online structured questionnaire from July to December 2021 among undergraduate and graduate students with different disciplinary backgrounds from 7 universities in Guangzhou. In total, 10,008 participants were recruited through WeChat, while 9361 university students completed the questionnaire with a response rate of 93.5%. The online survey was anonymous, and data were encrypted for added security protection. Before entering the online survey system, all participants reviewed and approved the electronic consent page. By prohibiting users with the same IP (Internet Protocol) address from accessing the survey more than once, duplicate entries were avoided. Incomplete surveys were not sent to the system because of a missed response reminder component that alerted participants in real time about incomplete surveys. This investigation was conducted after obtaining the approval of the Ethics Review Committee (IRB), whose approval number is SYSU202108001.
Participants self-reported their gender, age, race/ethnicity, levels of education, and monthly living expenses. We also distinguished the university by three types (vocational school, general universities and prestigious universities) including 7 different universities in Guangzhou, China. A separate variable was created to distinguish the specialization of participants (medical specialization or not).
Respondents to the survey were asked whether they had smoked or used e-cigarettes even once. Those who had ever smoked or used e-cigarettes were asked if they now smoke or use e-cigarettes. We defined current cigarettes or(and) e-cigarettes use as having smoked or(and) used e-cigarettes at least one day in the last 30 days.
Current cigarettes or(and) e-cigarettes users were asked about the age at first use of cigarettes or e-cigarettes and the product of choice for first use (cigarettes or e-cigarettes). Respondents also were asked how long they have been smoking or using e-cigarettes with the possible answers being from within a month to more than ten years. The using product of initiation (cigarettes or e-cigarettes) was asked if the respondent was a dual user.
Regarding the future choices of smokers and e-cigarettes users, the main focus was to examine whether they choose to become cigarettes only users, e-cigarettes only users or dual users in a year.
Previous studies [ 17 , 18 , 33 ] have shown that unhealthy lifestyles such as alcohol abuse, video gaming addiction, and sleep deprivation are strongly associated with smoking or using e-cigarettes in young adults, so we added lifestyle variables to the study. Three common unhealthy lifestyles were distinguished in our questionnaire including drinking alcohol excessively, playing video games frequently and staying up late (falling asleep after 24 o’clock and getting tired next morning) frequently. We defined frequently as more than three times in a week, and excessively as play video games more than 20 h per week.
In the survey, participants were divided into four types: cigarettes only users (cigarettes smokers who currently do not use e-cigarettes), e-cigarettes only users (e-cigarettes users who currently do not use cigarettes), dual users (those who currently use both cigarettes and e-cigarettes) and non-nicotine users (those who currently do not use cigarettes and e-cigarettes).
The selected Chinese universities were classified according to their academic prominence as prestigious and non-prestigious according to the QS World University Rankings [ 34 ]. Prestigious Chinese universities refer to Sun Yat-sen University and Jinan University in this study. Non-prestigious Chinese universities include Guangzhou University of Chinese Medicine, Southern Medical University and Guangzhou City Polytechnic. Guangzhou Institute of Science and Technology and Guangzhou Huashang University are vocational schools in China.
The categorical variables were expressed as the frequency (%), while the continuous variables were presented as mean ± SD. A single sample Kolmogorov–Smirnov test was used to test whether the data conform to normal distribution. Chi square test was used to compare categorical variables, while independent sample t-test and Mann–whitney U test were respectively used to compare the continuous variables with and without normal distribution. An analysis of multiple logistic regression was conducted to explore the relationship between using behavior of cigarettes and e-cigarettes and lifestyle. When multiple comparisons were involved, the Bonferroni method was used to correct for the test level α. All analyses were done using R software. Significant test was a bilateral test and the level of statistical significance was set at P < 0.05 for all the analyses.
Table 1 shows characteristics of participants. The final sample was composed of 9361 individuals, providing a response rate of 93.5%. In the full sample of 9361 participants, 58.3% ( n = 5461) were male and 41.7% ( n = 3900) were female.
Table 1 shows that 29.8% of students smoke or use e-cigarettes and that among them, the typical patterns is dual use (48.3%) with 35.0% smoking only cigarettes and 16.7% using only e-cigarettes. Among the dual users, 51.2% ( n = 690) participants started using cigarettes, 34.4% ( n = 464) participants e-cigarettes, 14.4% ( n = 193) did not recall the exact order (Fig. 1 ).
The source distribution of cigarettes and e-cigarettes dual users among university students in Guangzhou, China
Table 2 shows factors associated with smoking or using e-cigarettes. Among e-cigarettes users, females were more likely to choose e-cigarettes compared to males (78.1 vs. 62.8%, P < 0.05).
In general, medical students have a higher level of knowledges about health [ 16 , 35 ] and it is important to understand their perceptions of e-cigarettes as they need to communicate and interact with patients during their training and later in their careers. Therefore, we divided the specialization into non-medical specialization and medical specialization, using medicine as a criterion.
The prevalence of cigarettes and e-cigarettes was significantly higher among non-medical specialization than medical specialization (32.7% vs. 12.8%, P < 0.05), and the highest rate of cigarettes and e-cigarettes use was found among law specialization compared to medical specialization (47.2% vs. 12.8%, P < 0.05), followed by history (46.1% vs. 12.8%) and philosophy (43.8% vs. 12.8%, P < 0.05).However, there was no difference in the choice of cigarettes or e-cigarettes between non-medical and medical students.
The use of both e-cigarettes and cigarettes was lower in prestigious Chinese universities compared to other types of schools. Students in non-prestigious Chinese universities had the highest rate of cigarettes and e-cigarettes use and a correspondingly higher rate of e-cigarettes use.
Among the participants, undergraduates and vocational school students had the highest rate of cigarettes and e-cigarettes use (32.8% and 31.8%), followed by Ph.D. students (20.2%), while master students had the lowest rate of cigarettes and e-cigarettes use at 9.7%, with a statistically significant difference ( P < 0.05).
Among them, there was no difference in the distribution of cigarettes and e-cigarettes use among undergraduates and vocational school students, while the rate of cigarettes use among master students was significantly lower than other students ( P < 0.05), and the rate of e-cigarettes use? was also the lowest.
Lifestyles have significant impacts on the use of cigarettes and e-cigarettes. Compared to those with appropriate lifestyles, students who drank alcohol frequently, played video games excessively, stayed up late frequently, and did all of the above had an increased odds of cigarettes use, e-cigarettes use, and dual use. Multiple logistic regression analyses of cigarettes only users, e-cigarettes only users, and dual users indicated that the using of cigarettes, e-cigarettes and dual use increased 8.1, 6.8 and 10.2 times respectively for those who drank alcohol compared to those who did not drink alcohol; The odds of cigarettes using, e-cigarettes using and dual using were 2.6, 3.2, and 4.7 times higher for gamers compared to non-gamers, respectively; The odds of cigarettes using, e-cigarettes using and dual using increased by 1.3, 1.2 and 2.4 times respectively for those who stayed up late compared to those who did not stay up late. All results are presented in Table 3 .
Table 4 shows that 83.5% ( n = 1125) of dual users chose using products (whether cigarettes or e-cigarettes) according to their emotional state, while 56.5% ( n = 761) of dual users chose cigarettes when they are depressed and e-cigarettes when they are happy.
Table 5 shows that e-cigarettes only users and dual users have a stronger intention to quit using their current nicotine product of use than cigarettes only users( P < 0.05). Figure 2 displays the willingness of cigarettes only users or e-cigarettes only users to try another product (cigarettes or e-cigarettes) among university students in Guangzhou, China. For cigarettes only users, 41.8% ( n = 408) report that they will not use e-cigarettes in the future, 30.9% ( n = 301) use both cigarettes and e-cigarettes in the future, and 27.3% ( n = 266) would give up cigarettes and use e-cigarettes. For e-cigarettes only users, 42.0% ( n = 195) would give up e-cigarettes and only use cigarettes, 37.5% ( n = 174) would use both cigarettes and e-cigarettes, and 20.5% ( n = 95) would not use cigarettes in the future.
Willingness of cigarettes only users or e-cigarettes only users to try another nicotine product among university students in Guangzhou, China
Our findings were consistent with some prior prevalence studies in which males were more likely to smoke than females (males: females = 37.2:7.5) [ 10 , 36 , 35 , 38 ]. However, the gender difference in e-cigarettes were smaller than in cigarettes, which is also consistent with previous research studies [ 39 , 38 , 41 ].
The gender differences in smoking may be attributed to traditional sociocultural influences [ 31 , 32 , 42 , 41 , 44 ]. Habitual thinking suggests that female's smoking is associated with an inappropriate social image. The social circumstances put more pressure on female smokers, whereas, for male smokers, social opinion has a much smaller negative impact than for females, suggesting that the socio-cultural context have an intervening role in smoking.
In addition, we found that the rate of using cigarettes and e-cigarettes was the highest among undergraduates, followed by Ph.D. students, and the lowest was among master students, both for cigarettes, e-cigarettes, and dual use. It indicates that cigarettes and e-cigarettes use was shown as a non-linear relationship with education level, which is consistent with other studies [ 45 ]. This may be due to the fact that undergraduates have less academic stress and more social activities [ 46 ], which are susceptibility factors for cigarettes and e-cigarettes use. A number of studies have shown that there is a significant correlation between smoking and the education level of the smoker, the higher the education level is, the lower the smoking rate is [ 47 , 48 ]. This is because people with a higher level of education level have a higher level of health awareness, and a relatively higher level of awareness of the diseases caused by smoking and harmful results [ 49 , 50 ], and thus have a lower smoking rate, which explains the relatively lower rate of cigarettes and e-cigarettes use among master student s and Ph.D. students. Undergraduate students were more likely to use e-cigarettes, in contrast to master students and Ph.D. students, who had the lowest rates of cigarettes and e-cigarettes use and a greater preference for cigarettes. It has been established that e-cigarettes use shows a non-linear relationship with education level, but the exact reasons for this are unclear and warrant further study [ 51 ]. Our findings displayed that the use of both e-cigarettes and cigarettes was lower in prestigious Chinese universities perhaps due to the widely different circumstances, different management, and different type of student in different universities. In addition, we found that the cigarettes use rate of Ph.D. students is much higher than the e-cigarettes use rate, which is different from the situation of undergraduates and vocational school students. The reasons for this may be that Ph.D. students are older than others and e-cigarettes are emerging products, so many Ph.D. students are used to using cigarettes and are not familiar or are not willing to try e-cigarettes.
Similar to previous surveys, we found that non-medical students have higher rates of cigarettes and e-cigarettes use than medical students [ 52 ]. This may be due to the fact that medical students are more aware of the effects of nicotine on the body after learning extensive knowledge of physiology and pathology [ 16 , 30 , 43 ]. It is noteworthy that, the highest rate of using cigarettes and e-cigarettes was law students. The considerable pressure placed on them in academic performance can explain this result [ 53 ].
A growing body of research indicates that emotion is also one of the influencing factors of smoking and negative emotions can induce smoking [ 54 , 55 ]. Our findings found that the majority of dual users will use cigarettes rather than e-cigarettes when they are depressed. This result may be due to the different experiences of smoking and vaping while there is no related data to illustrate that smoking cigarettes will provide more pleasure in the present.
We also discovered that among all the future choices, dual use is becoming increasingly popular, as the previous study reported [ 56 ]. 51.2% of the dual users started as cigarettes only users, indicating a huge shift of nicotine products using pattern in young adults. Consistent with our findings above, some studies [ 30 , 41 , 57 ] also indicated that cigarettes only users are more likely to try e-cigarettes than non-smokers. However, a study by Sean Esteban McCabe et al. indicated that dual users had the greatest risk for engaging in risk behaviors (including truancy, grade point average < = C + , binge drinking, alcohol use, marijuana use, illicit drug use and nonmedical Rx drug use) followed by cigarettes only users, e-cigarettes only users, and non-nicotine products users [ 5 ].
There are several limitations to this study. First, the source of the sample was university students, whose smoking behaviors may differ from the general population of young adults and may not apply to the group who are not students. Second, the data was not weighted for adjusting biases to non-equal probability of selection, non-coverage, and non-response. Third, these data are self-reported and might be subject to reporting bias. Finally, the study was a cross-sectional study and could not dynamically observe changes in cigarette and e-cigarette use, we were unable to assess causal relationships.
The present study reveals the use rate of cigarettes and e-cigarettes among university students in Guangzhou, China. This study also provides the possible future choices of cigarettes or e-cigarettes users among university students. Our investigation shows that 29.8% of participants reports that they used cigarettes or e-cigarettes. Among them, 16.7% were e-cigarettes only users, 35.0% were cigarettes only users and 48.3%were dual users. 51.2% of the dual users were developed from cigarette only users.
Additionally, this study investigated influencing factors to cigarettes and e-cigarettes use, showing that gender, school, education level, specialization, and lifestyles all had impacts on the use of cigarettes and e-cigarettes among university students in Guangzhou. Students who were male, had low education levels, from non-prestigious Chinese universities or vocational schools, had non-medical specialization, and the presence of inappropriate lifestyles such as drinking and playing video games excessively were more likely to use cigarettes and e-cigarettes. Besides, emotion also can have significant effects on the choice of using cigarettes or e-cigarettes for dual users.
This study elucidates the characteristics of cigarettes and e-cigarettes use and related influencing factors among university students in Guangzhou, providing more information to better understand young people's preferences for cigarettes and e-cigarettes. This cross-section survey offers a perspective for policy makers to develop more guiding industry rules of young adult's cigarettes and e-cigarettes using.
In our future work, further investigations, which take more variables related to cigarettes and e-cigarettes using into account, will need to be undertaken, and more reliable analytical methods must be required.
All data generated or analyzed during this study are included in this published article.
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This work was supported by the National Natural Science Foundation of China (31970699), the Guangdong Basic and Applied Basic Research Foundation (2021A1515010766 and 2019A1515011030), the Guang-dong Provincial Key Laboratory of Construction Foundation(2019B030301005), the Key-Area Research and Development Program of Guangdong Province (2020B1111110003), and the National Major Special Projects for the Creation and Manufacture of New Drugs(2019ZX09301104).
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Hongjia Song, Wanchun Yang, Yuxing Dai, Guangye Huang, Min Li, Guoping Zhong, Peiqing Liu & Jianwen Chen
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PL and JC contributed to the conception of the study. XY and HS participated in designing the research, performing the bibliography searches, selecting studies and extracting data. WY and HS contributed significantly to analysis and manuscript preparation. HS performed the data analyses and wrote the manuscript. YD, GZ and HS contributed to the interpretation and discussion of the results of the analysis. All authors edited and critically reviewed the manuscript. All authors read and approved the final manuscript.
Correspondence to Guoping Zhong , Peiqing Liu or Jianwen Chen .
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Tobacco Induced Diseases volume 2 , Article number: 133 ( 2004 ) Cite this article
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A cross-sectional study was conducted to identify the factors related to smoking habits of adolescents among secondary school boys in Kelantan state, Malaysia. A total of 451 upper secondary male students from day, boarding and vocational schools were investigated using a structured questionnaire. Cluster sampling was applied to achieve the required sample size. The significant findings included: 1) the highest prevalence of smoking was found among schoolboys from the vocational school; 2) mean duration of smoking was 2.5 years; 3) there were significant associations between smoking status and parents' smoking history, academic performance, perception of the health hazards of smoking, and type of school attended. Peer influence was the major reason students gave for taking up the habit. Religion was most often indicated by non-smokers as their reason for not smoking. Approximately 3/5 of the smokers had considered quitting and 45% of them had tried at least once to stop smoking. Mass media was indicated as the best information source for the students to acquire knowledge about negative aspects of the smoking habit. The authors believe an epidemic of tobacco use is imminent if drastic action is not taken, and recommend that anti-smoking campaigns with an emphasis on the religious aspect should start as early as in primary school. Intervention programs to encourage behavior modification of adolescents are also recommended.
Smoking is the single most important preventable cause of death [ 1 ]. The secondary school age is a critical period in the formation of the smoking habit. Most smokers start smoking during their adolescence or early adult years. The earlier they start to smoke, the more likely they are to become regular smokers [ 2 , 3 ]. Those concerned about the health, welfare and education of young people should be anxious to find ways to prevent them from taking up this habit.
In Malaysia, with the improvement of socioeconomic status and the standard of health care, the incidence of communicable diseases has declined significantly, but other health problems are emerging. An example of the diseases related to smoking is coronary artery disease, which now is the main cause of death in hospitals in peninsular Malaysia [ 4 ].
Adolescent and teenage smoking have been studied widely, and it has been found in developed countries that nearly one-half of school students who have reached the age of 18 have already established the habit of smoking with some degree of regularity, and it is a rather unrealistic hope on the part of adults to expect that children will abstain until reaching the adult approved age of decision [ 5 ].
Smoking is a major problem among youth in Malaysia. In a recent survey by the Ministry of Youth and Sports on negative behaviors among 5,860 adolescents, 80% indicated that they had ever experienced smoking [ 6 ]. Schooling is the major activity of most children between the ages of 7 and 17 years and school is the place where most of them socialize outside their home environment for the first time. A school is the place where much knowledge is obtained, attitudes are formed and sometimes habits are chosen. Studies have demonstrated that the secondary school age is a critical period in the formation of the smoking habit [ 7 ]. Experimenting with cigarettes often begins during childhood or early adolescence and there is usually a period of about 1.5 to 2 years between initiation of smoking and establishment of the smoking habit [ 8 , 9 ].
Schooling is compulsory in Malaysia. A child enters school at the age of 7 and attends primary school for six years, after which he enters lower secondary school (Form I–III). At the end of Form III there is a qualifying examination, and only students who pass this examination proceed to upper secondary school (Form IV–V). Those who fail repeat Form III, go to vocational or private schools, or drop out of school [ 10 ].
A number of factors influence an individual to start smoking. Lack of awareness and knowledge have been reported as contributing factors based on studies in the past. This study aimed to highlight environmental, religious and other factors influencing smoking in male adolescents in secondary schools.
A cross-sectional study was conducted during January through June 2001. Applying the cluster sampling method, 451 Form IV and V (upper secondary) male students from three different schools (day, boarding and vocational) were included in the study. The reason for selecting different schools was to examine smoking habits in relation to the nature of the schools attended by the students. Only male adolescents were included in the study. The number of participants from each school were: 150 from day school (33.26%), 150 from boarding school (33.26%) and 151 from vocational school (33.48%). Since the population of Kelantan state is 90% Islamic, all study participants were Malay Muslim schoolboys. A structured questionnaire was distributed among them for self-administration with prior explanation. Subjects were asked to indicate their reasons for smoking or non-smoking based on factors such as religion, parental control, parental smoking status, peer influence, feeling of maturity, enjoyment, monetary and other factors. The validity and reliability of the questionnaire was tested earlier based on pre-test results, using statistical software. Smoking status was self-reported, and was not verified by any biochemical measures. The Pearson Chi-square test was applied to determine the statistical significance of association at 5% level of significance. The data was analyzed using SPSS software, version 10.0.
Definition of terms used were:
Tried/smoked before: one who has only tried smoking and is not a smoker now, or one who has previously smoked but is currently not a smoker;
Never tried: one who has never tried smoking in his life;
Current smoker: one who smokes currently, regardless of frequency and amount smoked.
Mean age of subjects was 16.46 years. Current smokers comprised 35.92% of 451 male students surveyed. Vocational school students had the highest proportion of smokers. Among non-smokers, 187 students had smoked some time in their lives. Mean duration of smoking was 2.49 years. Approximately two-thirds of the smokers started the smoking habit before the age of 15. A total of nearly 21% of the students smoked daily for more than three years (Table 1 ).
A significant proportion of the smokers (41.98%) smoked more than 10 cigarettes per day. There was a significant association between the smoking habit of the fathers and that of the students (p < 0.01) (Table 2 ). Reasons most often given for smoking were: following friends, feeling of maturation, enjoyment, following parents, relaxation in free time, and feeling that smoking is the normal behavior of a man (Figure 1 ). Non-smokers most often cited religion, parents' influence, health protection, and financial reasons as factors preventing them from smoking (Figure 2 ).
Reasons for smoking, among smokers .
Reasons for not smoking, among non-smokers .
The perception of the health hazards of smoking was significantly different between smokers and non-smokers (p < 0.001) (Table 2 ). Smokers had relatively poor academic performance compared to non-smokers (p < 0.001) (Table 2 ). The proportions of smokers in the three schools were significantly different (p < 0.001). The vocational school had the highest number of smokers compared to the other two (Table 2 ). About 60% of smokers had thought of quitting smoking and of these nearly 45% had tried at least once to quit (Table 3 ). Mass media was cited as the best source of information about smoking hazards, followed by medical personnel (Figure 3 ). There was no significant association between source of knowledge and smoking status of the students.
Sources of knowledge about the hazards of smoking .
In Kelantan, where the community is relatively conservative, the prevalence of smoking of 35.9% among male adolescents reported by this study was high. The prevalence of male adolescent smoking in Malaysia was reported as 30.7% by the National Health Morbidity survey conducted nationwide in 1996 [ 11 ]. Our study has shown an even higher prevalence than the national level. The authors believe this may be because of the homogeneity of study participants, who were from only the Malay ethnic group. The National Health Morbidity Survey indicated that adolescent smoking was highest in Bumiputras [ 11 ]. The races included under Bumiputra status are Malays and other local tribes. The Non-Bumiputras category includes Chinese and Indians who migrated to Malaysia some decades ago. While the results of our study may not be generalizable to the entire population, this study supports the fact that smoking is a serious problem among the majority ethnic group in the Malaysian population. Among a few locally conducted studies, Thambypillai in 1985 found a prevalence of 17.0% among secondary school boys in urban school in Kuala Lumpur, Malaysia [ 9 ]. In Saudi Arabia, the prevalence of smoking among secondary school boys was only 17% while in China, among middle school students, it was only 2.24% [ 12 , 13 ].
Among the schools where the study was carried out, the highest smoking prevalence was found in vocational school, as expected. Those who entered vocational schools had relatively poorer academic performance than those who went to the other two types of schools. This is no doubt due to the fact that those who fail the qualifying examinations in Form III have to leave school or join vocational or private schools. This study points out that the likelihood of being a smoker increases among academically poorly performing students. Thambypillai in 1985 reported a similar finding of association between high smoking prevalence and poor academic performance [ 10 ].
Our study found that peer influence is the major reason for initiation of smoking; this is similar to findings of other studies [ 14 ]. Peer influence was found to be a strong predictor of smoking initiation in almost all studies that included these measures. Similar findings have been documented by the Surgeon General of the United States [ 2 ]. Two types of peer pressure (i.e., having close friends who smoked, and having close friends who encouraged the student to smoke) were among the strongest risk factors for both regular and occasional smoking. Similar results were found in reports on junior and senior high school students in China [ 15 , 16 ]. Studies from Japan [ 17 ] and Spain [ 18 ] have shown that smoking rates of school students are strongly related to having friends who smoke. This suggests that pupils should be advised to avoid accepting smokers as friends, as the effects are not limited to the odor of tobacco and hazards of passive smoking, but may include pressure to take up this habit.
This study found religion was the strongest reason among non-smokers for not smoking. A similar finding has been shown in earlier studies in Saudi Arabia of schoolboys [ 19 ], medical students [ 20 ] and university students [ 21 ]. Smoking has not been declared as "forbidden" from the Islamic religious point of view in Malaysia. However, Malaysia has experienced rapid economic progress in recent years and as the nation has opened to advertising, marketing and imports by international tobacco corporations, smoking rates among teenagers and adolescents have increased [ 22 ]. We recommend that religious education including a religious perspective on the smoking issue should be more emphasized in school curriculum and anti-smoking campaigns, since it is potentially an effective way to educate students especially at the secondary school age. While our study found mass media were the source of information on smoking more than medical personnel, parents, teachers and others, we point out that mass media can not replace face-to-face communication between a student and a doctor, a teacher or parents.
Parental smoking has great influence on the children with respect to taking up the smoking habit. There was a significant association between the students' smoking status and their fathers' smoking habits found in this study. The social learning theory of behavior [ 23 ] states that children are more likely to model their own behavior on actions of people they regard as worthy, similar to themselves, and models of their own sex. Two studies [ 24 , 25 ] reported that parental attitude in actively discouraging their children from smoking may be more powerful than parental behavior in shaping adolescent cigarette smoking behavior. Two other studies [ 26 , 27 ] reported that the majority of smokers began their habits in imitation of friends, co-workers or family members. This suggests that in order for campaigns against smoking in adolescents to be most effective, parents must not smoke in the presence of children. More importantly, the children must not be allowed to smoke in their parents' presence. The home environment should complement the school to discipline the students. The role model should be set at home.
Academic performance of the students had a highly significant association with the smoking status of the students. Smokers had marked poorer performance than the non-smokers. This finding supports the findings reported by University of Malaya in 1985 in which a higher prevalence of smoking was shown to be associated with poor academic performance [ 28 ]. We call on school authorities to conduct more regular exhibitions and talks, with the help of health personnel, to educate the students about the negative impact of smoking on learning activities. We also recommend that sports and other co-curriculum activities should be encouraged more, in order to provide ways for students to be constructively occupied to prevent them from being attracted to unwanted vice.
There was a statistically significant difference in perception towards hazards of smoking between smokers and non-smokers shown by this study. Agreement on the harmfulness of smoking to health was higher among non-smoking students. A similar finding was shown by a study published in 1991 [ 29 ]. Even though smoking may not be regarded as a major discipline problem, the main adverse effects on health are well documented. Smoking is considered the main avoidable cause of death and the most important public health risk. The hazards of tobacco affect not only smokers, but also non-smokers who are exposed to cigarette smoke, "passive smokers." The earlier a person starts smoking, the more difficult it is to quit, the less likely it is that he will quit, [ 30 ] and the greater the risk of lung cancer [ 31 ] or death from coronary heart disease [ 32 ]. The chances of success in quitting decrease as age increases [ 33 ]. To develop and implement effective measures of smoking control, one must understand the reasons and risk factors for smoking initiation.
Information about health hazards is usually insufficient for change; studies in Indonesia and other countries in Asia confirmed the observation that knowledge of health risks does not prevent children from smoking [ 34 ]. In addition to demonstrating the hazards of smoking, the benefits of quitting should also be stressed. This study found that more than 50% of regular and occasional smokers expressed their wish to stop smoking. Nearly 45% of them attempted quitting, though a significantly higher proportion was found among occasional smokers. This shows that there was a desire to quit smoking despite the fact that it is difficult to stop the habit once it has become established.
While new and innovative approaches to smoking prevention and cessation are being sought, the addictive nature of cigarette smoking and the health advantages of stopping smoking should be given further emphasis in current prevention programs among adolescents. Community and school education programs should include sessions on quitting smoking since there are scientifically proven cessation methods available now. Efforts to prevent experimentation with smoking must also be given higher priority. Promising strategies may include a ban on cigarette advertising and higher tobacco taxes. There is considerable evidence that tobacco advertising and promotion encourage adolescents to smoke [ 35 , 36 ] and that increasing the price of cigarettes discourages young people from starting to smoke.
This study focused on smoking behavior on male adolescents. Schoolgirls were not included in the study because in the cultural setting chosen for the study smoking is considered primarily a problem of males, and because of the small sample size of the girls in the schools which were chosen to be included in the study. Also, an unpublished report by the state education department authorities indicated a very small proportion of the smokers among Muslim girls. However, the National Health Morbidity Survey conducted in 1996 reported that the prevalence of female adolescent smoking was as high as 4.8% [ 10 ]. This was an alarming reminder to parents in Malaysia that girls, as well as boys, are at risk to take up smoking. Other studies [ 10 , 26 , 37 ] conducted in Western countries show a higher percentage of smokers among boys and girls of the same age. Given the increasing influence of western culture in Asia and other parts of the world, we would recommend a study exploring smoking behavior among Malaysian female adolescents.
The magnitude of the smoking problem in adolescents is large enough to be considered a warning of an impending epidemic. Intervention programs that focus on behavior modification of adolescents should be carried out on a large scale. Multi-centered studies with a homogenous population would be appropriate to measure the effectiveness of intervention strategies.
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We would like to express our heartfelt thanks to authorities from the Kelantan state education department, headmasters, teachers, and students from three schools who participated in the study.
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Department of Community Medicine, School of Medical Sciences Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia
Nyi Nyi Naing, Zulkifli Ahmad, Razlan Musa, Farique Rizal Abdul Hamid, Haslan Ghazali & Mohd Hilmi Abu Bakar
Department of Community Medicine, School of Medical Sciences, Universiti Sains Malaysia, 16150, Kubang Kerian, Kelantan, Malaysia
Nyi Nyi Naing
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Naing, N.N., Ahmad, Z., Musa, R. et al. Factors Related to Smoking Habits of Male Adolescents. Tob. Induced Dis. 2 , 133 (2004). https://doi.org/10.1186/1617-9625-2-3-133
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School tobacco policies (STPs) might prove to be a promising strategy to prevent smoking initiation among adolescents, as there is evidence that the school environment can influence young people to smoke. STPs are cheap, relatively easy to implement and have a wide reach, but it is not clear whether this approach is effective in preventing smoking uptake.
To assess the effectiveness of policies aiming to prevent smoking initiation among students by regulating smoking in schools.
We searched seven electronic bibliographic databases, including the Cochrane Tobacco Addiction Group specialized register, MEDLINE, EMBASE, PsycINFO and ERIC. We also searched the grey literature and ongoing trials resources. The most recent search was performed in May 2014.
We included cluster‐randomised controlled trials (c‐RCTs) in which primary and secondary schools were randomised to receive different levels of smoking policy or no intervention. Non‐randomised controlled trials, interrupted time series and controlled before‐after studies would also have been eligible. Cross‐sectional studies were not formally included but we describe their findings and use them to generate hypotheses to inform future research.
We independently assessed studies for inclusion in the review, and present a narrative synthesis, as the studies are too limited in quality to undertake a formal meta‐analysis.
We found only one study which was eligible for inclusion in the review. It was judged to be at high risk of bias. The study compared two 'middle schools' from two different regions in China. The experimental conditions included the introduction of a tobacco policy, environmental changes, and communication activities, while the control condition was no intervention. After a year's follow‐up the study found no differences in smoking prevalence between intervention and control schools. We also described 24 observational studies, the results of which we considered for hypothesis generation. In these, policy exposure was mainly described using face‐to‐face interviews with school staff members, and the outcome evaluation was performed using self‐administered questionnaires. Most studies reported no differences in students' smoking prevalence between schools with formal STPs when compared with schools without policies. In the majority of studies in schools with highly enforced policies, smoking bans extended to outdoor spaces, involving teachers and including sanctions for transgressions, with assistance to quit for smokers plus support by prevention programmes, there was no significant difference in smoking prevalence when compared to schools adopting weaker or no policies.
Despite a comprehensive literature search, and rigorous evaluation of studies, we found no evidence to support STPs. The absence of reliable evidence for the effectiveness of STPs is a concern in public health. We need well‐designed randomised controlled trials or quasi‐experimental studies to evaluate the effectiveness of school tobacco policies.
Do school tobacco policies prevent uptake of smoking?
Background: We reviewed the evidence that School tobacco policies (STPs) might prevent smoking initiation among adolescents, as there may be some evidence that the school environment can influence young people to smoke. STP is intended to regulate whether and where pupils can smoke, adult smoking in school, and penalties for pupils caught smoking. We were also interested to know whether specific components of STPs might increase their impact. Components such as a smoking ban for students and/or teachers and their extent, levels of enforcement, monitoring strategies, sanctions for students or teachers found smoking, and the offer of tobacco cessation programmes.
Study characteristics : Our study search was conducted in May 2014. We identified one c‐RCT from China that we judged to be at high risk of bias. We also focussed on 24 observational studies to generate a hypothesis for future research.
Key findings : In the only included c‐RCT with 1807 participants, the intervention did not significantly affect students' smoking behavior. The majority of observational studies reported that schools with highly enforced policies, smoking ban extended to outdoor spaces, involving teachers and including sanctions for transgressions, with assistance to quit for smokers plus support by prevention programmes, did not show a significant difference in smoking prevalence, when compared to schools adopting weaker or no policies.
Quality of the evidence : We found no relevant high‐quality experimental studies. A great limitation within observational studies is the heterogeneity of exposure definitions. There is large variability in policy formats, which can include several different characteristics, which in turn makes comparison difficult. Only a few studies are based on policy definition in written documents, while in the majority the information was obtained by interviewing school heads, teachers or administrators. With regard to analysis methods, some studies did not mention any adjustment for potential confounders and in the others there was a large variability in the factors considered for adjustment. Studies differed in statistical methods employed to examine the relationship between policy and smoking behaviour.
Conclusions : We cannot draw conclusions about the effectiveness of STP from currently available data. Large, possibly multi‐centric studies, employing experimental or a quasi‐experimental design to assess the effectiveness of STPs are needed. Characteristics that could be studied are: degree of formality, participants to which the policy applies, extension of the ban (indoor areas or external school premises), level of enforcement, sanctions for transgression; assistance with smoking cessation and combination with prevention and education activities.
The authors of the review did not receive any external funding or grants to support their research for this review, and have no potential conflicts of interest.
For the main comparison.
| ||||
Prevalence of current smokers | No significant difference in prevalence between either pair of schools | 1 c‐RCT with 2 pairs of schools, 1807 students | ⊕⊝⊝⊝ very low | Observational studies also provided limited evidence that school policies affected smoking behaviour. |
GRADE Working Group grades of evidence Further research is very unlikely to change our confidence in the estimate of effect. Further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate. Further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. We are very uncertain about the estimate. |
1 Only one study with small number of clusters judged at high risk of bias.
Tobacco smoking is an addictive behaviour associated with over five million deaths per year. The World Health Organization projects that the number of deaths per year attributable to tobacco smoking will rise to eight million by 2030. Tobacco use is a major preventable cause of morbidity and mortality, killing an average of one person every six seconds, and is responsible for one in ten adult deaths worldwide ( WHO 2012 ).
Though the majority of smoking‐related deaths are in people aged 35 years or older, the onset of tobacco use occurs primarily in early adolescence, and adolescents are a special target for smoking prevention projects. Trends in youth smoking show a decline during the 1970s and 1980s, and an increase in the 1990s in both the USA and Europe ( Warren 2008 ). A younger age of smoking initiation is associated with smoking more cigarettes per day ( Everett 1999 ) and with a lower cumulative probability of quitting ( Chen 1998 ) than in people who start smoking later on in life. Delaying the onset of smoking may affect the likelihood of becoming addicted to nicotine and smoking heavily.
Schools have been considered an ideal site to deliver tobacco prevention programmes since they universally involve youths across a wide age range, including the ages when most young people initiate smoking. Generally school programmes show relatively weak effects in reducing adolescent smoking, and these modest results have been explained by the strong social influence effect in favour of smoking inside and outside school premises ( Friend 2011 ). Early studies suggested the role of peer and parental smoking as moderators of school‐based effects ( Tyas 1998 ; Faggiano 2010 ), and perceived smoking by friends has been found to be a stronger predictor of cigarette use than friends' actual use ( Iannotti 1992 ). Some authors have therefore stressed the need to address adolescent smoking at the environmental level ( Griesbach 2002 ; Nakamura 2004 ).
Although smoking bans in school settings are common worldwide, because of their low enforcement adolescents are still frequently exposed to teachers and other pupils smoking during the school day. In a study conducted in 48 Danish schools, three in five students reported that they had seen or knew of teachers smoking outdoors on the school premises; and most of them reported that they had seen or knew of teachers smoking inside the school building ( Poulsen 2002 ). In the same study, teachers smoking outdoors on school premises were significantly associated with students' smoking behaviour, while exposure to other pupils smoking outdoors was not. Furthermore, it could be argued that students in a school without anti‐tobacco policies would perceive smoking as being acceptable, increasing their risk of taking up the habit.
As an intervention, school tobacco policy (STP) is intended to inform whether and where pupils can smoke, to set penalties for pupils caught smoking, and to regulate adult smoking in school ( Evans‐Whipp 2004 ). The primary objectives of this intervention are to prevent or delay tobacco use by youth, and also to reduce the exposure of employees and students to second‐hand smoke.
In many cases the introduction of an STP is combined with other smoking prevention programmes. For example, Ariza 2008 describes a multi‐modal intervention, which includes specific lessons for students and strategies to involve adults in smoking cessation programmes. Policies can vary depending on the extent of the ban, teacher and staff training, and the roles and responsibilities of teachers and staff in policy enforcement. Policy can be governed by a central authority at regional or national level rather than locally, and the mandatory nature of a law may moderate its effect on implementation and impact. Other consequences of STPs have also been observed, e.g. schools which do not accommodate student smoking in a specific area can result in adolescents, sometimes in large groups, leaving school property during school hours to smoke elsewhere ( MacBride 2005 ).
From the perspective of social learning theory, the interplay between individual and environment is crucial in developing intentions, expectations and ultimately behaviour ( Bandura 1986 ). Cognitive processes such as perceived health risks or benefits of smoking and perceived availability of tobacco could be involved In smoking behaviour. According to Eccles and Roeser’s ecological perspective ( Eccles 1999 ), factors such as peer and adults' smoking habits influence adolescents’ behaviour in combination with other factors. Therefore STPs, implemented as a part of a comprehensive approach, may affect smoking indirectly by influencing beliefs about acceptability (approval or disapproval) of cigarette smoking by adults and by peers ( Lipperman‐Kreda 2009a ). According to identity theory, it has been hypothesised that a strong condemnation of smoking by the school communicates to young people that smoking is an unacceptable part of mainstream identities ( Lloyd 1998 ). A further possibility is that STPs strengthen the connection to school among students and staff, as well as school ethos beyond its regulatory content ( Fletcher 2008 ). An STP can also reduce youth smoking by directly limiting smoking opportunities and access to tobacco ( Alesci 2003 ).
The teachers' perceived capacity to act as role models is an important element of the success of this type of intervention. Galaif 1996 found that teachers will comply with a smoking regulation only if they believe that they can directly affect students' smoking behaviour. If students who smoke perceive that it is acceptable for teachers to smoke in school, they are less likely to adhere to school smoking bans. For this reason Trinidad 2005 argues that encouraging teachers not to smoke on school grounds should be considered as a key component of school‐based tobacco prevention programmes; however, conversely smoking bans may encourage teachers to smoke outside school, with the unanticipated result of making teachers who smoke even more visible to students ( Wold 2004 ).
Implementing STPs was described as a promising strategy to prevent smoking initiation among adolescents ( Bowen 1995 ) However, it is not yet clear whether this approach is effective. It is unclear whether policies contribute to a reduction of youth smoking only when they are included in a comprehensive tobacco control plan at the school level ( Lovato 2010a ), or whether a policy constitutes a suitable and cost‐effective stand‐alone intervention ( Reid 1999 ). A summary of evidence is critical in order to define which STP elements are effective, and which require further research.
To assess the effectiveness of policies aiming to prevent smoking initiation among students by regulating smoking in schools. We addressed the following questions:
Types of studies.
We include cluster‐randomised controlled trials (c‐RCTs) in which schools or classes were randomised to receive different levels of smoking policy or no intervention. As we expected to find a limited number of RCTs, if any, the following prospective designs were also eligible; non‐randomised controlled trials, interrupted time series and controlled before‐after studies. Cross‐sectional studies were not formally included. In the absence of higher quality evidence, their findings were described and used to generate hypotheses for future studies.
Students in primary and secondary schools (10 to 18 years old).
All written policies that regulate tobacco use inside and/or outside the school property were eligible. We would have classified interventions as partial bans, inside bans and comprehensive policies.
We would have included studies of policies aiming to ban drug or alcohol use in addition to smoking if tobacco use outcomes were reported. We would have considered interventions in which an STP was a component of a smoking prevention program only if it was possible to isolate its effect. Studies that compared stronger and weaker policies were eligible. We would have considered whether the implementation of a policy had an impact on its effect.
Primary outcomes.
Smoking prevalence among students, measured by individual self‐report. Biochemically validated smoking data, where provided, were used in preference to self‐report. Young people were classified as smokers or non‐smokers in different ways (daily, weekly, monthly, ever, non‐smoker, smokeless tobacco user, smoker). Where multiple definitions were provided, we used the strictest measure given. In studies with multiple follow‐up periods, we would have used data from the longest follow‐up period reported.
1. Actual tobacco use by teachers and school staff. 2. Tobacco use of teachers, school staff, and students as perceived by other students. 3. Compliance with the policy by students, teachers and school staff. 4. Exposure to environmental tobacco smoke.
We conducted the most recent search in May 2014.
We searched the following databases:
1. Cochrane Tobacco Addiction Group's Specialised Register 2. Cochrane Central Register of Controlled Trials (CENTRAL) 3. MEDLINE 4. EMBASE 5. PsycINFO 6. ERIC (Educational Resources Information Center) 7. Sociological abstracts (CSA) 8. 'Grey' literature (conference proceedings and unpublished reports) via Google Scholar and dissertation abstracts. 9. Unpublished literature, by searching trial registers (www.clinicaltrials.gov, www.controlled‐trials.com, www.clinicaltrialsregister.eu) and contacting researchers and agencies whom are known to have conducted or sponsored relevant research to identify further studies not found and unpublished reports.
The Tobacco Addiction Group Specialized Register contains reports of controlled trials of interventions for smoking cessation or prevention, evaluations of tobacco control policies, identified from regularly updated highly sensitive searches of CENTRAL, MEDLINE, EMBASE, PsycINFO, and the Science Citation Index. The search strategy for the register used the following topic related terms; (polic* or ban* or restriction* or rule* or environment* or health promoting or smoke‐free) AND (school*) in title, abstract or keyword fields. The search strategies for MEDLINE, EMBASE and PsycINFO combined these topic terms with the smoking and tobacco terms and the study design terms used for the Register searches. The full MEDLINE search strategy can be found in Appendix 1 . Searches of ERIC, Sociological Abstracts and other sources combined topic related and smoking related terms.
We checked cited studies in all studies identified. We did not apply language restrictions. In the case of languages other than English, French, German, Italian, Spanish, Portuguese, Greek, Russian or Swedish, we would have looked for translation facilities within the Cochrane Collaboration.
All search results were imported into an electronic register. Titles and abstracts were classified according to their relevance to the review. Once bibliographic searches was completed, all retrieved records were assembled in a database and processed in order to de‐duplicate them (i.e., remove duplicate records). Two reviewers (AC, FF) screened all identified studies in the electronic databases. Articles were rejected if the title or abstract was not pertinent to the topic of the review. Any disagreements was resolved between the two reviewers by referring to the full‐text, and by consulting with a third party when necessary (MRG). The same reviewers conducted further screening of the full text of the studies that passed the initial screening stage.
Two reviewers (AC, FF) independently extracted data from the selected study using a tailored standardised data extraction form including the following elements:
Any discrepancies were resolved through discussion or, if required, through consultation with a third person (MRG).
Two review authors assessed independently risk of bias for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions ( Higgins 2011 ): • adequate sequence generation; • adequate allocation concealment; • blinding of personnel/outcome assessors; • addressing incomplete outcome data; • free of selective outcome reporting; • free of other bias. For each of these domains, risk of bias was judged High, Low, or Unclear Any disagreement was resolved by discussion or by involving a third assessor.
For dichotomous data, we used the risk ratio (RR) to summarize individual trial outcomes ((number of events in intervention condition/ intervention denominator)/ (number of events in control condition/control denominator)) with 95% confidence intervals. For our primary outcome, the RR was calculated using the student population of the school as the denominator ((number of student smokers in intervention condition/student population in intervention condition)/(number of student smokers in control condition/student population in control condition)). Where the event measured was students classified as smokers, a risk ratio less than one indicated that fewer students were smokers in the intervention group than in the control group. For continuous data, we used the mean difference if outcomes were measured in the same way between trials. We used the standardised mean difference to combine trials that measured the same outcome, but use different methods.
Though in cluster randomised trials we expected the school (or classes) to be the unit of randomisation, we used the individual as the unit of analysis. We reported adjustments for design effect when provided and dealt with any unit of analysis issues using the guidance in the Cochrane Handbook for Systematic Reviews of Interventions ( Higgins 2011 ).
If the proportion of missing data suggested a risk of bias, the study would have been classified accordingly and included in a sensitivity analysis. Participants who has been missing follow‐up data for our primary outcome would have been counted as smokers in an intention‐to‐treat analysis.
The statistical heterogeneity was to be examined using the I 2 statistic. However, this was not necessary as we included only one study.
Had we found sufficient studies, we would have tested publication bias using a funnel plot. The relevance of outcomes had been checked to determine if there was any bias in outcome reporting.
If we had found sufficient studies we would have carried out summary analyses using RevMan 5.1. We would have used the Mantel‐Haenszel fixed‐effect model for meta‐analyses, combining data where trials examined the same intervention and populations and methods were judged sufficiently similar. Where we had suspected clinical or methodological heterogeneity between studies sufficient to suggest that treatment effects may differ between trials, we would have used a random‐effects meta analyses.
If relevant studies had been available, we would have conducted subgroup analyses for the following policy characteristics: • ban extended only to school staff versus extended both to staff and students; • only indoor area affected by the ban versus ban extended to outdoor area; • policies enforced by punishment versus policies not enforced by punishment; • policies as stand‐alone interventions versus policies accompanied by educational programmes.
In the presence of substantial heterogeneity, we would have explored the reasons for this, undertaking sensitivity analyses (if there have been sufficient studies to warrant this approach).
Results of the search.
Figure 1 shows the study selection process (up to May 2014). Two review authors (AC, FF) independently assessed all the titles and abstracts identified as a result of the comprehensive updated search. Initially 2182 citations were identified in the electronic databases, of which 1702 remained after de‐duplication. No ongoing studies were found in trial registers. We excluded 1553 studies after screening the titles and then 90 after reading the abstracts. At the end of selection process we included one study in this review, which aimed to study the effect of the introduction of smoking policies at school.
Study flow diagram
The included study ( Chen 2014 ) was conducted in 2008 in two Chinese regions and involved two schools in the intervention group and two in the control group. Of a total of 1807 participants aged between 13 and 15 years old, 941 students attended intervention schools and 866 attended control schools. The students were then surveyed a year later about their smoking habits. To assess the frequency of smoking, participants were asked whether they smoked daily, weekly, or were smoking currently. Ever‐smoking was defined as having ever used cigarettes, even one or two times. Characteristics of the intervention were: smoking banned inside the school; peer educators trained to encourage smokers to quit; and brochures about health hazards of smoking distributed among students. The study measured changes in students' smoking behaviour, knowledge and attitudes. The Characteristics of included studies table provides further details on participants, interventions, and outcomes of the study.
Among the 58 studies that were excluded, 51 were observational and therefore not eligible. Seven studies were randomised controlled trials (RCTs) ( Andersen 2012 , Elder 1996 , De Vries 2006 , Gorini 2014 , Hamilton 2005 , Schofield 2003 , Wen 2010 ), evaluating multi‐modal programmes, but it was not possible to disentangle the effect of STP from those of others interventions, and so they were excluded. Of the 51 observational studies, 27 reported a predictor not suitable for this review (STP not sufficiently specified) or no outcome suitable for the review. The Characteristics of excluded studies table provides details of the respective reasons for excluding each study. The remaining 24 studies reported an effect on students' smoking behaviour and information about the policies' characteristics was collected through interviews with school staff. Even if excluded from the review, they were considered useful for hypothesis generation. All but one were cross sectional studies, while one ( Rosendhal 2002 ) was a cohort study. Twenty‐two studies involved middle or secondary schools, and two were conducted in primary schools ( Rosendhal 2002 ; Huang 2010 ). Information about the study, characteristics of the policy and main results are summarised in Table 2 .
Nr ref | Study | Participants | Characteristics of the policy | Associations with outcomes |
1 | 16561 students in grade 7 ‐ 12 (age 12 ‐ 17) attending 20 middle schools and 20 high schools in 24 towns in northern and central Illinois (USA) 2002 ‐ 2005 | STP measured with 2 scales: a) Enforcement (beliefs about the relative problem of youth tobacco use at school, level of active enforcement, strategies employed to enforce the policy, staff and student perceptions about the policy, environmental factors that may be related to tobacco use at school such as assessment of closed vs open campus) b) Comprehensiveness (defined as applicability, restrictions, repercussions, programmes, notification, and evaluation of the written policies) | Enforcement linked to lower odds of smoking (OR 0.83, 95% CI: 0.70 to 0.99) but not with comprehensiveness nor with the interaction between comprehensiveness and enforcement | |
2 | 763 students (mean age 13) in 50 schools and 762 students (mean age 16) in 57 schools in Quebec (Canada) in 1999. 25 students randomly selected in each school | STP defined as staff permitted to smoke indoors/outdoors; students permitted to smoke on school ground | Policies permitting students to smoke indoors were not associated with daily smoking among either 13‐ or 16‐year‐old students. Policies permitting staff to smoke outdoors were significantly associated with daily smoking among 13‐year‐old students. Multivariate effect limited to staff smoking outdoors among 13 years girls (OR 4.8, 95% CI: 1.1 to 21.1) | |
3 | 4469 students in grade 9 (mean age 15.4) and 1041 teachers in high schools in Louisiana (USA) in 2004 | Comparison between schools prohibiting all tobacco use by anyone on the school campus and at all school events (no‐use policy) and schools that allow teachers and other staff to smoke in one 'restricted' area on campus (restricted‐use policy) | No differences in students smoking in the 2 types of schools | |
4 | 26,429 students from grades 7 ‐ 12 (12 ‐ 18 years) from 351 secondary schools and 347 teachers in Australia in 1990 | All the schools have a smoking policy for students; differences between school about policies' characteristics for teachers and visitors and presence of smoking signs around the school | Smoking prevalence unrelated to staff and visitor smoking policy and presence of smoking signs | |
5 | 26,58 students in grade 10 and 12 (mean age 15) from 63 schools in New Zealand in 2002 | STP focus categorized as punishment (having sanctions for students who were caught smoking), cessation (having a cessation support), prevention (having included prevention guidelines), comprehensiveness (having communicate students to be smoke‐free and informed the public about the policy); each group of schools was contrasted with the group of schools not having the specific focus | No association between any policy component or intensity with current smoking | |
6 | 3466 students in grade 8 and 10 (age 13 ‐ 15) from 285 schools: 153 (1777 students) in Washington state (USA) and 132 (1689 students) in Victoria state (Australia) in 2003 | STP components: comprehensiveness (teachers and staff covered by smoking policy; in force on school grounds and during school‐related activities where students are present; extended to visitors) enforcement (policy rated between 'strictly enforced' and 'not at all strictly'), 'harsh' (expulsion, calling the police and out of school suspension) or 'remedial' (referred to a school counsellor or nurse, recommended to participate in an assistance, education, or cessation programme or required to participate in an assistance, education, or cessation program) response for students violating the policy, orientation (emphasizing of total abstinence from drug use and emphasizing harm minimisation) | No differential effects of policy dimensions on current and daily smoking (between harm minimisation and abstinence policies, and between comprehensive and non‐comprehensive smoking ban) | |
7 | 9127 students attending 4th year of compulsory secondary education (15 ‐ 16 years) from 203 schools in Spain, 2001 ‐ 2005 | Variables taken into account: years before (2001 – 2002) and after (2003, 2004, 2005) the introduction of the law banning smoking at school; characteristics related to the school centre (compliance with the law banning smoking; written reference to smoking control policy in the school regulations; existence of complaints about smoking; undertaking of educational activities regarding smoking prevention) | No differences in smoking prevalence and amount of smoking between the schools that complied with the legislation and those that did not, or with those centres including smoking prevention policies in the school regulation | |
8 | 4697 students in grade 9 (mean age 13.6) from 31 schools in Australia in 1999 | STP components: involvement in school health promotion projects, formation of a school health committee, presence of a health policy and a written drug policy, availability of counselling, education, and discipline strategies used to deal with students caught smoking, quit strategies used to support students and staff who smoke | No association with having a health committee and a drug policy. Counseling, education for students caught smoking associated with lower probability of ever smoking (OR 0.73; 95% CI 0.64 to 0.84) or regular smoking (OR 0.67; 95% CI 0.53 to 0.85) | |
9 | 2350 students from grade 3 ‐ 6 (mean age 10.9) from 26 schools in South Taiwan in 2008 | STP components: a) Policy status (written/informal/uncertain policy) b) Smoking restrictions (smoking banned completely on school premises/permitted in restricted areas] c) Level of enforcement of smoking restrictions (always/not always) d) Health education related to tobacco, participation in smoke‐free health promotion events, access to cessation programmes and sanctions imposed on students smoking at school | No association with written policy status or restrictions; Ever‐smoking elevated for students in schools without anti‐tobacco activities or curricula | |
10 | 35,745 students in grade 8, 10 and 12 (age 13 ‐ 16) in 342 schools of Michigan (USA) in 1999 and 2000 | STP components: a) Monitoring of students' compliance b) Severity of consequences when students are caught violating the policy c) School policy regulating tobacco use by staff | Monitoring students' behaviour negatively associated with current daily smoking in middle, but not in high schools. Severity of consequences positively related to smoking in high schools, but no longer after adjustments. Permission for staff to smoke positive predictor of smoking in high schools | |
11 | 22,318 students in 10 ‐ 11 grade (15 ‐ 19 years old) from 81 schools in Canada | STP characteristics derived from a) Written policies coded in developing, overseeing and communicating the policy; purpose and goals; prohibition; strength of enforcement; characteristics of enforcement; tobacco use prevention education and assistance to overcome tobacco addictions b) School administrators' interviews on STP implementation c) students' survey on perception of policy enforcement | Smoking prevalence was only significantly correlated with perception of smoking prevalence, but not with policy. On school property smoking prevalence, but not smoking prevalence related to consistency of enforcement in policy implementation | |
12 | 27,892 students from grade 5 ‐ 9 (age 10 ‐ 14) from 281 elementary and secondary schools (mean age 16) in 10 Canadian provinces in 2004 ‐ 2005 | Policy enforcement derived from information about who was involved in policy development, how students were informed, and the nature of enforcement | Purpose and goals clearly stated (OR 0.38; 95% CI 0.15 to 0.95) and presence of an enforcement officer (OR 0.60; 95% CI 0.36 to 0.99) associated with lower probability of being a smoker. Availability of assistance to quit smoking was associated with a higher probability of smoking (OR 2.23; 95% CI 1.12 to 4.45) | |
13 | 24,474 students in 10 ‐ 11 grade (15 ‐ 19 years old) from 82 randomly sampled secondary schools in 5 Canadian provinces (during the 2003 – 2004 school year) | School policy intent extracted by examining written documentation on smoking policies. Policy enforcement derived by principals' or teachers' interviews. Tobacco control programmes data derived from a survey completed by school administrators | Strong prohibition in the written policy was associated with a lower probability of smoking (OR 0.92; 95% CI 0.88 to 0.97). Policy enforcement (OR 1.20; 95% CI 1.07 to 1.35) and enforcement officer (OR 1.22; 95% CI 1.04 to 1.43) were associated with higher probabilities of smoking. Focus on preventive programmes was associated with a lower probability of smoking (OR 0.87; 95% CI 0.81 to 0.94) | |
14 | 1375 students in year 11 (aged 15 ‐ 16) from 55 schools in Wales (UK) in 1998 | STP coded as: 1. Written policy where pupils and teachers were not allowed to smoke anywhere on the school premises 2. No written policies for pupils and teachers and/or teachers allowed to smoke in restricted areas 3. Either no smoking policy for pupils or for teachers. Level of extension of the ban, enforcement | Weak policy was associated with daily (OR 3.84; 95% CI 1.76 to 8.37) and weekly (OR 2.55; 95% CI 1.26 to 5.15) smoking. Low enforcement associated with daily (OR 1.41; 95% CI 0.96 to 2.07) and weekly (OR 1.32; 95% CI 0.92 to 1.91) smoking for pupils. In logistic regression models the associations remained, even after adjustment for individual‐level variables. Low enforcement for teachers compared to high enforcement was not associated with pupils' daily (OR 1.03; 95% CI 0.66 to 1.59) or weekly (OR 0.86; 95% CI 0.56 to 1.31) smoking | |
15 | 3965 students in grade 12 (mean age 17.6) from 10 schools in Canada, surveyed 1999 ‐ 2001 | Repeated cross‐sectional with comparison time to assess the effect of implementation of smoking prevention programmes and introduction of STP in a school district. Characteristics of STP not reported | Students exposed to educational and cessation programmes less likely to be occasional smokers rather than non‐smokers (OR 0.42; 95% CI 0.18 to 0.97). Students exposed to STP (OR 1.06; 95% CI 0.67 to 1.68) or the combination of the 2 did not differ from the reference group (OR 0.83; 95% CI 0.61 to 1.12) | |
16 | 4709 students in grade 10 (age 15 – 16) ) from 10 schools in Canada, surveyed 1999 ‐ 2001 | Repeated cross‐sectional with comparison time to assess the effect of implementation of smoking prevention programmes and introduction of STP in a school district. No report of the characteristics of STP. | STP only associated with non‐significant decrease of occasional smoker vs current non‐smokers (OR 0.72; 95% CI 0.50 to 1.03) and increase of regular smokers vs occasional smokers (OR 1.54; 95% CI 1.04 to 2.29). Smoking prevention only associated with a significant reduction of occasional (OR 0.57; 95% CI 0.44 to 0.75), but not of regular smoking (OR 0.94; 95% CI 0.69 to 1.28). Presence of both activities not associated with students' smoking | |
17 | 983 students in grades 9 and 12 (age 12 ‐ 19) from 14 schools in Michigan (USA) | STP components: types of prohibiting tobacco products, hours of prohibiting tobacco use, places of prohibiting tobacco use, communication of tobacco policy, person in charge of enforcing tobacco policy, designation of a tobacco‐free school zone, anti‐smoking communications, tobacco cessation services, actions taken for students who are caught smoking cigarettes, stringency of tobacco policy enforcement | No association with policy variables after controlling for individual characteristics | |
18 | 4807 students in grade 7 (mean age 12) in 23 schools in California (USA) in 1986 | STP components: comprehensiveness (presence of formal rule about no smoking on school grounds, near school grounds, closed campus policy, formal health education plan for smoking prevention programming, prevention emphasis, cessation emphasis, punishment emphasis, policy enforcement, time in effect, consequences for violation (7 categories increasing in severity), policy on school ground | Higher number of components and emphasis on prevention rather than cessation associated with statistically non‐significant lower school smoking prevalence both weekly and in last 24 hrs. High punishment emphasis not associated with lower prevalence. More consistent effect obtained on amounts of smoking rather than on prevalence rates in particular, with high emphasis on prevention and low emphasis on cessation | |
19 | 3364 students (mean age 14.05, range 10 ‐ 21) from 40 schools in Germany | STP characteristics investigated: a) Extension of smoking ban for students (in school building, on school grounds, or in immediate surroundings) b) Extension of smoking ban for adults (teachers, non‐teaching staff, school visitors in school buildings) c) Monitoring of students’ compliance with the smoking ban (monitored regularly in corridors, rest rooms and on school grounds) d) Sanctions following breaking the smoking rules (different sanction activities) e) Offers of smoking cessation courses f) Smoking prevention activities. Mediating variables: school engagement, attachment to school, risk behaviours, use of substances | Comprehensive ban for students (OR 0.62; 95% CI 0.42 to 0.92) and presence of evidence‐based prevention programmes (OR 0.62; 95% CI 0.39 to 0.99) associated with lower smoking prevalence. Smoking prevalence not affected by smoking restrictions for adults, sanctions, monitoring of students or availability of smoking cessation | |
20 | (Cohort study) 2883 children recruited in the 5th grade with follow‐up in 6th grade across 213 classes from 91 compulsory schools in Sweden in 1997 | STP assessed through questions about formal adoption of a local anti‐smoking policy; implementation of a local plan for anti‐tobacco education; ongoing pedagogic activities against tobacco; presence of a smoking room for the staff; and availability of smoking cessation programmes for staff or for students | Having formally adopted a STP is not associated with smoking prevalence (OR 1.06; 95% CI 0.80 to 1.41) | |
21 | 24,213 students in grade 10 and 11 (mean age 16) in 81 schools in Canada during 2003 – 2004 school year | STP reported in written policy (intent) and by administrators' interview. characteristics examined were: participation and communication (excellent if students were involved in the development of the policy, group appointed to oversee the policy, communication to students); stated goals and purpose (excellent if all groups in school were prohibited from all tobacco), strength of enforcement (excellent if verbal and written warnings were delivered to the student and parent/guardian, and sanctions were based on zero tolerance); characteristic of the enforcement (excellent if more than one person/group was designated as ensuring policy enforcement, and the policy outlined clear enforcement strategies), prevention education; availability of cessation programmes, time in effect | Prohibition (OR 0.83; 95% CI 0.72 to 0.95) and availability of cessation assistance (OR 0.74; 95% CI 0.60 to 0.92), but not prevention education (OR 1.23; 95% CI 0.96 to 1.57), linked to lower probability of smoking; length of time a policy was in place associated with a 1% increase in smoking probability per year | |
22 | 6587 students (age 13 ‐ 15) from 50 State and 50 Federal schools in India in 2000 ‐ 2001 | Federal schools having STP contrasted to State schools (no STP). STP consists in specific rules and regulations prohibiting use of tobacco and tobacco products on school premises by students, school personnel, parents, and visitors | In State schools there was 5 ‐ 6 times higher prevalence of any tobacco and smokeless tobacco use, 3 ‐ 4 times higher prevalence of any smoking, and 5 ‐ 6 times higher prevalence of cigarette smoking | |
23 | 1941 students in grades 10 and 11 (age 11 ‐ 16) from 45 schools in Wales (UK) in 2001 ‐ 2002 | STP characteristics examined: policy restriction; formal policy (whether written); staff policy approach (consultative vs prescriptive); dissemination for pupils and staff; sanctions for students (underline health or underline transgression); consistency between policy, environment and school | No association with policy variables after controlling for individual characteristics. The only statistically significant association found was that pupils attending schools that did not disseminate pupil smoking policy in a written document had a greater tendency (OR 2.16; 95% CI 1.13 to 4.10) to smoke daily on school premises than those who attended schools that disseminated policy through a written document | |
24 | 1404 students (mean age 15) from 73 schools in Norway | STP characteristics examined the extent to which actions taken by schools (i.e., informing parents of adolescents’ violation of the school tobacco policy, disciplining and counselling adolescents who are caught smoking) changed prevalence | School enforcement of smoking restrictions was not related to adolescent smoking prevalence (OR 1.29; 95% CI 0.80 to 2.05) |
All the studies are cross‐sectional with the exception of Rosendhal 2002 that is a cohort study.
The only study included ( Chen 2014 ), had a small sample size of only 4 schools, a high risk of intraclass correlation, a likely absence of blinding, and lack of information to assess the presence of selective reporting; we judged the risk of bias of this study to be very high. This assessment is summarised in Figure 2 .
Risk of bias summary: review authors' judgements about each risk of bias item for each included study.
See: Table 1
In Chen 2014 a school tobacco policy (STP) was not significantly associated with all smoking outcomes studied. There weren't substantial differences in the prevalence of current smokers between intervention and control schools in either of the two regions: risk ratio (RR) 0.98 (95% CI 0.71 to 1.4) and RR 1.35 (95% CI 0.57 to 3.2). The study didn't consider other outcomes of interest for this review.
Using data from 24 observational studies, we were interested if specific characteristics of STPs were associated with students smoking behaviour. The characteristics analysed were the following:
The mere adoption of an STP did not seem to affect smoking behaviour. Nine studies measured the effects of a formally‐adopted STP on students' smoking. These studies present mixed results, as three studies showed lower prevalence of smoking in schools with STPs, when compared with schools without a formal policy ( Lovato 2010b ; Moore 2001 ; Sinha 2004b ), while six studies reported no differences ( Galán 2012 ; Hamilton 2003 ; Huang 2010 ; Murnaghan 2007 ; Murnaghan 2008 ; Rosendhal 2002 ).
We also analysed the effects of five aspects of policy: extent of a smoking ban, inclusion of teachers' smoking, sanctions for transgression, assistance for smoking cessation, and a ban combined with prevention and education activities. Only a few studies reported results to support the effects of these features.
With respect to the extent of bans, one study detected a difference in students' smoking prevalence, when comparing schools which prohibited students’ smoking on school premises or outdoors, with those which permitted smoking ( Piontek 2008b ). Three studies found no differences ( Barnett 2007 ; Huang 2010 ; Pentz 1989 ); however, of these Pentz 1989 found a difference only in the number of cigarettes smoked.
One policy forbidding teachers to smoke was associated with a decrease in students' daily smoking ( Kumar 2005 ). Prohibition of indoor smoking for teachers was not significantly associated with student smoking, while prohibiting teachers from smoking outdoors was associated only with decreased daily smoking in girls aged 13 years, but not among boys and girls aged 16 years ( Barnett 2007 ). In Boris 2009 , Clarke 1994 , Piontek 2008b , and Wiium 2011a , comprehensive policies prohibiting teachers from smoking, when compared with those allowing them to smoke in restricted areas, were not related to student smoking.
Nine studies considered the relationship between sanctions for students found smoking and smoking prevalence. Sanctions cited in the STP were not related to smoking prevalence in the majority of the studies ( Darling 2006 ; Pentz 1989 ; Piontek 2008b ; Wiium 2011a ). Harsh and remedial penalties ( Evans‐Whipp 2010 ), the severity of sanctions ( Kumar 2005 ; Paek 2013 ), and sanctions put in place at school and informing parents ( Wiium 2011b ) were not associated with adolescent smoking. In one study ( Hamilton 2003 ) counselling and education for students caught smoking appeared to be more effective against student smoking than a disciplinary approach alone.
Seven studies considered the effect of assistance with smoking cessation for students. Out of these, only Sabiston 2009 showed a link to a lower probability of smoking. Of the others, five studies did not show a link ( Darling 2006 ; Evans‐Whipp 2010 ; Lovato 2007 ; Pentz 1989 ; Piontek 2008b ); in fact Pentz 1989 reported a higher number of cigarettes smoked in schools where cessation support was available. Moreover, Lovato 2010a showed that in schools that mandated cessation programmes students had a higher probability of smoking.
Six studies compared the effect of 'STP only' to 'STP with prevention and education components', but did not find an association with reduction of smoking prevalence ( Darling 2006 ; Lovato 2007 ; Murnaghan 2007 ; Murnaghan 2008 ; Pentz 1989 ; Sabiston 2009 ). Pentz 1989 reported lower numbers of cigarettes smoked and lower smoking prevalence (although not statistically significant) in schools with smoking ban policies and smoking prevention programmes.
Eleven of the considered studies focused particularly on the role of policy enforcement. Four studies showed that policy enforcement was linked to lower rates of smoking ( Adams 2009 ; Kumar 2005 ; Moore 2001 ; Sabiston 2009 ). In one study, the data were in favour of schools adopting policy enforcement, but the effect was no longer statistically significant after adjustment for state, gender, age and family socioeconomic status ( Evans‐Whipp 2010 ). The presence of an enforcement officer, but not the strength of the enforcement, was associated with a lower probability of smoking in one study ( Lovato 2010a ). Smoking prevalence was not related to policy enforcement in two studies ( Lovato 2007 ; Wiium 2011b ). One study found no difference in smoking prevalence between schools with a high versus a low degree of monitoring of students’ compliance with the policy ( Piontek 2008b ). In contrast, Lovato 2010b found that students were more likely to smoke if they attended a school with stronger enforcement of the tobacco policy. Policy enforcement for teachers was not associated with a difference in daily and weekly smoking among students in one study ( Moore 2001 ).
Table 2 shows further details on characteristics, outcomes and results of the considered studies for hypothesis generation, while Table 3 summarizes the effect of policies' characteristics on students' smoking behaviour as reported in the studies.
| ||||
Favours policy (3) | 24,474 (Canada) | 15 ‐ 19 years | OR 0.92* current smoker (last 30 days) | |
1375 (UK) | 15 ‐ 16 years | OR 0.26* daily smoker | ||
6587 (India) | 13 ‐ 15 years | OR 0.2* current smoker | ||
Total: | ||||
No difference (6) | 9127 (Spain) | 15 ‐ 16 years | OR 0.96 current smoker | |
4697 (Australia) | 13.6 mean age | OR 0.82 regular smoker | ||
2350 (Taiwan) | 10.9 mean age | No differences (values not reported) | ||
3965 (Canada) | 17.6 mean age | OR 1.06 occasional smoker | ||
4709 (Canada) | 15 ‐ 16 years | OR 0.72 occasional smoker | ||
2883 (Sweden) | 10 ‐ 11 years | RR 1.06 ever smoker | ||
Total: | ||||
Favours policy (1) | 2818 (Germany) | 10 ‐ 21 years | OR 0.62* current smoker (last 30 days) | |
Total: | ||||
No difference (3) | 762 (Canada) | 13 ‐ 16 years | 20.8% (school with outdoor ban) vs 23.6% (school without outdoor ban) daily smoker prevalence | |
2350 (Taiwan) | 10.9 mean age | No differences (values not reported) | ||
4807 (USA) | 12 ‐ 13 years | 4.93% (schools with comprehensive STP) vs 5.60% weekly smoker | ||
Total: | ||||
Favours policy (2) | 395 (Canada) | 13 mean age | OR 0.2* (staff cannot smoke outdoors) daily smoker among 13 years (girls) | |
35,745 (USA) | 13 ‐ 16 years | OR 1.24 daily smoker in middle schools and OR 0.82 in high schools | ||
Total: | ||||
No difference (5) | 1130 (Canada) | 13 ‐ 16 years | 23.3% (staff can smoke outdoors) vs 22.8% (staff cannot smoke outdoors) daily smokers among 13 years (boys) and 16 years (P = ns) | |
4469 (USA) | 15.4 mean age | 24.6% (staff cannot smoke) vs. 25.2% (staff can smoke in restricted area) 30‐day cigarette smoking prevalence (P = ns) | ||
26,429 (Australia) | 12 ‐ 18 years | 27.2% (staff not allowed to smoke) vs 30.9% (no restrictions) weekly smokers among grade 11 and 12 (P < 1) | ||
2818 (Germany) | 10 ‐ 21 years | ß coefficient –0.06 current smoker | ||
1941 (UK) | 11 ‐ 16 years | 16.4% (staff not allowed to smoke) vs 18.6% (restricted area) daily smokers | ||
Total: | ||||
Favours policy (4) | 16,561 (USA) | 12 ‐ 17 years | OR 0.83* current smoker (last 30 days) | |
35,745 (USA) | 13 ‐ 16 years | OR 0.81* daily smoker in middle school, OR 1.03 in high school | ||
1375 (UK) | 15 ‐ 16 years | OR 0.65* daily smoker | ||
24,213 (Canada) | 16 mean age | OR 0.90* current smoker (last 30 days) | ||
Total: | ||||
No difference (5) | 3466 (USA and Australia) | 13 ‐ 15 years | OR 0.78 current smoker (last 30 days) | |
22,318 (Canada) | 15 ‐ 19 years | OR 1.11 smoking prevalence | ||
27,892 (Canada) | 10 ‐ 14 years | RR 1.63 current smoker (last 30 days) | ||
2818 (Germany) | 10 ‐ 21 years | ß coefficient 0.25 current smoker | ||
1404 (Norway) | 16 mean age | OR 1.29 daily smoker | ||
Total: | ||||
Favours controls (1) | 24,474 Canada | 15 ‐ 19 years | OR 1.20* current smoker | |
Total: | ||||
Favours counselling and education for students vs disciplinary approach only (1) | 4697 Australia | 13.6 mean age | OR 0.67* regular smoker | |
Total: | ||||
No difference (8) | 2658 (New Zealand) | 15 mean age | RR 0.89 daily smoker in school with sanctions included in the policy | |
3466 (USA and Australia) | 13 ‐ 15 years | OR 0.99 current smoker (last 30 days) | ||
35,745 (USA) | 13 ‐ 16 years | OR 0.98 daily smoker in middle school, OR 1.01 in high school | ||
983 (USA) | 12 ‐ 19 years | ß coefficient −0.02 current smoker (last 30 days) | ||
4807 (USA) | 12 ‐ 13 years | 4.91% weekly smokers in school with high punishment emphasis vs 5.38% in school with low punishment emphasis | ||
2818 (Germany) | 10 ‐ 21 years | ß coefficient 0.10 current smoker with punishment emphasis | ||
1941 (UK) | 11 ‐ 16 years | 18.1% (sanctions tending to health) vs 15.7% (sanctions tending to discipline) daily smokers | ||
1404 Norway | 15 years | OR 0.65 daily smoker when pupils were disciplined at school vs other forms, OR 2.90 daily smoker when parents were informed vs other forms | ||
Total: | ||||
Favours policy (1) | 24,213 (Canada) | 16 mean age | OR 0.74* current smoker (last 30 days) | |
Total: | ||||
No difference (5) | 2658 (New Zealand) | 15 mean age | RR 1.17 daily smoker | |
3466 (USA and Australia) | 13 ‐ 15 years | OR 1.15 current smoker (last 30 days) | ||
22,318 (Canada) | 15 ‐ 19 years | No differences in smoking prevalence | ||
4807 (USA) | 12 ‐ 13 years | 5.29% (high cessation emphasis) vs 4.72% (low cessation emphasis) weekly smokers | ||
2818 (Germany) | 10 ‐ 21 years | ß coefficient 0.32 current smoker when cessation programme is offered | ||
Total: | ||||
Favours controls (1) | 27,892 Canada | 10 ‐ 14 years | RR 2.23* current smoker (last 30 days) | |
Total: | ||||
No difference (6) | 2658 (New Zealand) | 15 mean age | RR 1.17 daily smoker | |
22,318 (Canada) | 15 ‐ 19 years | No differences in smoking prevalence | ||
3965 (Canada) | 17.6 mean age | OR 0.83 occasional smoker | ||
4709 (Canada) | 15 ‐ 16 years | OR 1.54 occasional smoker | ||
4807 (USA) | 12 ‐ 13 years | 4.31% (high prevention emphasis) vs 5.77% (low prevention emphasis) weekly smokers | ||
24,213 (Canada) | 16 mean age | OR 1.10 current smoker (last 30 days) | ||
total: |
OR: odds ratio RR: risk ratio
The results of this review are limited by the number of studies identified and the low methodological quality of the only one we included, Chen 2014 , which showed no significant differences for students' smoking behaviours between schools with and without a STP. Furthermore, the study was judged as having high risk of bias. For this reason at present there is insufficient evidence that STPs are effective for the reduction of smoking initiation among young people. Through a systematic search of observational studies, we also identified some studies exploring different aspects of STP. Specific characteristics like enforcement, extended outdoor bans, strict surveillance measures, assistance to quit smoking, formal adoption of a STP and inclusion of prevention or education activities were not found to be associated with a decreased likelihood of smoking. These results questioned the effectiveness of STPs, but, given the very low quality of the evidence, in the absence of large and rigorous intervention studies, they should be considered in order to orient future research on this topic. The review didn't include studies that addressed whether STPs are able to reduce the start of smoking in adolescents or reduce the number of cigarettes among smokers.
It is important to consider that the main conclusion of this review is based only on one randomised controlled trial (RCT) at high risk of bias. This is because the included study did not describe the randomisation method for the schools and did not provide information on allocation concealment, which may introduce significant selection bias. On the other hand the number of dropouts and participants lost to follow‐up were very low. Given the characteristics of the assessed intervention, it is important to note that it was not feasible to blind the participants or the school personnel. The investigators measuring the outcomes could have been blinded, but this was not reported in the included study. Insufficient details were provided on variables used In the statistical analysis for the adjustment for possible confounders.
We have also analysed some observational studies, which in turn have important limitations, apart from their study design. One important issue is the heterogeneity of exposure definition. There is large variability in policy formats, and these can include several different characteristics, which make comparisons difficult. Only a few studies are based on policy definition in written documents. Policy information obtained by interviewing school principals, school administrators or teachers might overstate the extent of the STP, and frequently it is not possible to differentiate the contribution of the STP from that of other school interventions. Descriptive terms, like 'enforcement' or 'comprehensiveness', were used in different and incompatible ways, with specific policy characteristics being differently defined. This was true of smoking prevention programmes, availability of cessation support, and the sanctions for violations. The outcome variables were heterogeneous, and the age range between studies was variable. Since age is a major determinant of the prevalence of tobacco use, with a doubling of the initiation rates between early and middle adolescence ( DiFranza 2007 ), discrepancies between studies should always be interpreted with respect to age distribution. With regard to analysis methods, some studies did not mention any adjustment for potential confounders ( Clarke 1994 ; Darling 2006 ; Sinha 2004b ; Wiium 2011b ) and in general there is large variability in the factors considered for adjustment.
Five RCTs excluded from this review ( Elder 1996 ; De Vries 2006 ; Hamilton 2005 ; Schofield 2003 ; Wen 2010 ), as it was not possible to differentiate the effect of smoking policy from other interventions, were included in another Cochrane review ( Thomas 2013 ). A recent Cochrane review ( Langford 2014 ) aimed to assess the impact of the Health Promoting School framework on several health behaviours; four ( De Vries 2006 ; Hamilton 2005 ; Schofield 2003 ; Wen 2010 ) of 14 studies included for evaluating the effect on smoking behaviour were also considered in this review, but excluded for the reason mentioned above. The conclusions of the present work largely agree with those produced in a previous systematic review ( Galanti 2014 ). Other reviews on STP have previously been published. A review conducted with the scope of identifying which school characteristics are responsible for the variation in smoking prevalence found weak associations between some aspects of STPs and smoking ( Aveyard 2004 ). A narrative review on the impact of school drug policies on youth substance use concluded that more comprehensive and strictly enforced policies are associated with less smoking, but may also displace the behaviour from school grounds to off‐school premises ( Evans‐Whipp 2004 ). A non‐systematic review of school contextual effects on students' behavioural outcomes showed how in schools without STPs, smoking was more prevalent among pupils ( Sellström 2006 ), but no detailed description of the characteristics of the policies was provided.
Despite a comprehensive search of the literature evaluating the effectiveness of school policies for preventing smoking among young people, we did not find any evidence of an effect. This is mainly explained by the absence of rigorous studies. Whlie this finding suggests that STP is an ineffective stand‐alone intervention, we believe that the theoretical basis of this intervention ( Wilson 2012 ) should be tested under the control of well designed studies.
Large, possibly multi‐centric studies, employing an experimental or a quasi‐experimental design, are needed to assess the effectiveness of this intervention.
Future research in this area must be rigorously designed and evaluated. Design issues of particular importance include the following:
Several STP components can play an essential role in contributing to policy effectiveness; the most important ones suggested by this review are:
9 February 2016 | Amended | External source of support added |
The authors would like to thank the editorial staff of the Cochrane Tobacco Addiction Review Group for running the search strategy and for their advice and support during the review process.
1 RANDOMIZED‐CONTROLLED‐TRIAL.pt.
2 CONTROLLED‐CLINICAL‐TRIAL.pt.
3 CLINICAL‐TRIAL.pt.
4 Meta analysis.pt.
5 exp Clinical Trial/
6 Random‐Allocation/
7 randomized‐controlled trials/
8 double‐blind‐method/
9 single‐blind‐method/
10 placebos/
11 Research‐Design/
12 ((clin$ adj5 trial$) or placebo$ or random$).ti,ab.
13 ((singl$ or doubl$ or trebl$ or tripl$) adj5 (blind$ or mask$)).ti,ab.
14 (volunteer$ or prospectiv$).ti,ab.
15 exp Follow‐Up‐Studies/
16 exp Retrospective‐Studies/
17 exp Prospective‐Studies/
18 exp Evaluation‐Studies/ or Program‐Evaluation.mp.
19 exp Cross‐Sectional‐Studies/
20 exp Behavior‐therapy/
21 exp Health‐Promotion/
22 exp Community‐Health‐Services/
23 exp Health‐Education/
24 exp Health‐Behavior/
25 1 or 2 or 3 or 4 or 5 or 6 or 7 or 8 or 9 or 10 or 11 or 12 or 13 or 14 or 15 or 16 or 17 or 18 or 19 or 20 or 21 or 22 or 23 or 24
26 smoking cessation.mp. or exp Smoking Cessation/
27 "Tobacco‐Use‐Cessation"/
28 "Tobacco‐Use‐Disorder"/
29 Tobacco‐Smokeless/
30 exp Tobacco‐Smoke‐Pollution/
31 exp Tobacco‐/
32 exp Nicotine‐/ (19782)
33 ((quit$ or stop$ or ceas$ or giv$) adj5 smoking).ti,ab.
34 exp Smoking/pc, th [Prevention & Control, Therapy]
35 26 or 27 or 28 or 29 or 30 or 31 or 32 or 33 or 34 [A category smoking terms]
36 exp Smoking/ not 35 [B category smoking terms]
37 1 or 2 or 3 [Likely CT design terms; RCTs, CCTs, Clinical trials]
38 35 and 25 [A category smoking+all design terms]
39 35 and 37 [A category smoking terms+likely CT design terms]
40 (animals not humans).sh. [used with 'not' to exclude animal studies for each subset]
41 ((26 or 27 or 28 or 29) and REVIEW.pt.) not 38 [Set 4: Core smoking related reviews only]
42 36 and 25 [B category smoking+all design terms]
43 (42 and 37) not 40 [Set 3: B smoking terms, likely CT design terms, human only]
44 38 not 39 not 40 [Set 2: A smoking terms, not core CT terms, human only]
45 (35 and 37) not 40 [Set 1: A smoking terms, likely CT design terms, human only]
46 (36 and 25) not 40 not 43 [Set 4: B smoking terms, not core CT terms]
47 (polic* or ban* or restriction* or rule* or environment*).mp.
48 school*.mp.
49 47 and 48 [Topic related terms]
50 45 and 49 [Topic + A smoking terms & core CT terms SET 1 ]
51 44 and 49 [Topic + A smoking terms & wide design terms SET 2 ]
52 43 and 49 [Topic + B smoking terms & core CT terms SET 3 ]
53 46 and 49 [Topic + B smoking terms & wide design terms SET 4 ]
Lines 1 to 24 identify controlled trials and other types of programme evaluations, as used to identify reports of studies for the Tobacco Addiction Group Specialised Register. Lines 26 to 34 identify reports related to smoking and tobacco control. Lines 47 and 48 identify reports relevant to the topic of this review. Sets 1 to 4 will be screened for the review, Sets 1 and 2 are expected to be the most likely to contain relevant reports, and Set 4 to be unlikely to identify any.
Edited (no change to conclusions)
Characteristics of included studies [ordered by study id].
Methods | Cluster‐RCT at level of school | |
Participants | China (Linzhi, Tibet and Guangzhou, Guangdong Province) School type: Middle Grades 6 and 7 (13 ‐ 15 yrs) 1 in Linzhi and 1 in Guangzhou 1 in Linzhi and 1 in Guangzhou 941 in intervention schools and 866 in control schools | |
Interventions | 2008 : 1 year No intervention A tobacco control committee headed by the principal was established; regulations on smoking were made at the beginning of the study No‐smoking signs were placed in the school yards. Peer education was conducted to help smokers to quit smoking. Teachers were required not to smoke in front of students. Brochures of health hazards of smoking and .blackboard newsletter, posters and publicity pictures were disseminated. Smoking‐related health education lectures were given. Students participated in smoking cessation‐related activities including essay competitions, signing a non‐smoking pledge, Additional components: No‐Tobacco‐Day theme activities, self‐producing newspaper competition and logo design contests. | |
Outcomes | Ever smoking, daily smoking, weekly smoking, current smoking. Smoking‐related knowledge and smoking‐related attitudes | |
Notes | ||
Random sequence generation (selection bias) | Unclear risk | No details provided on random sequence generation |
Allocation concealment (selection bias) | Unclear risk | No details provided on allocation concealment |
Blinding of participants and personnel (performance bias) All outcomes | High risk | Unlikely that participants could have been adequately blinded |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Outcomes were self‐reported |
Incomplete outcome data (attrition bias) All outcomes | Low risk | Attrition rates were very low; correspondence rate from matched questionnaires between the two surveys was 99.6% in Linzhi and 99.4% in Guangzhou |
Selective reporting (reporting bias) | High risk | No protocol available |
Other bias | High risk | selection bias: unclear sample procedure and no citation of stratified sampling |
Study | Reason for exclusion |
---|---|
Cross‐sectional study; considered for hypothesis generation | |
Inappropriate outcomes (no association with smoking behaviour) | |
RCT; not possible to isolate the predictor | |
Not possible to isolate the predictor | |
Inappropriate outcomes (no association with smoking behaviour) | |
Cross‐sectional study; considered for hypothesis generation | |
Cross‐sectional study; considered for hypothesis generation | |
Cross‐sectional study; considered for hypothesis generation | |
Inappropriate outcomes (no association with smoking behaviour) | |
Cross‐sectional study; considered for hypothesis generation | |
RCT; not possible to isolate the predictor (see ) | |
RCT; not possible to isolate the predictor | |
RCT; not possible to isolate the predictor | |
Inappropriate outcome (students' smoking based on observation) | |
Cross‐sectional study; considered for hypothesis generation | |
Cross‐sectional study; considered for hypothesis generation | |
Not possible to isolate the predictor | |
RCT; not possible to isolate the predictor | |
Inappropriate outcome (pupils' perception of teacher and student smoking) | |
Cross‐sectional study; considered for hypothesis generation | |
RCT; not possible to isolate the predictor | |
Cross‐sectional study; considered for hypothesis generation | |
Not possible to isolate the predictor | |
Cross‐sectional study; considered for hypothesis generation | |
Not possible to isolate the predictor | |
Inappropriate predictor's measure (policy reported by students) | |
Inappropriate predictor's measure (policy reported by students) | |
Cross‐sectional study; considered for hypothesis generation | |
Cross‐sectional study; considered for hypothesis generation | |
Cross‐sectional study; considered for hypothesis generation | |
Inappropriate predictor | |
Not possible to isolate the predictor | |
Cross‐sectional study; considered for hypothesis generation | |
Repeated cross‐sectional study. Considered for hypothesis generation | |
Repeated cross‐sectional study. Considered for hypothesis generation | |
Not possible to isolate the predictor | |
Inappropriate predictor | |
Inappropriate predictor | |
Cross‐sectional study; considered for hypothesis generation | |
Cross‐sectional study; considered for hypothesis generation | |
Inappropriate predictor's measure (policy reported by students) | |
Inappropriate predictor's measure (policy reported by students) | |
Cross‐sectional study; considered for hypothesis generation | |
Inappropriate predictor's measure (policy reported by students) | |
Inappropriate predictor's measure (policy reported by students) | |
Cohort study. Considered for hypothesis generation | |
Inappropriate outcomes (no association with smoking behaviour) | |
Cross‐sectional study; considered for hypothesis generation | |
RCT; not possible to isolate the predictor | |
Inappropriate predictor | |
Cross‐sectional study; considered for hypothesis generation | |
Inappropriate outcomes | |
Inappropriate predictor's measure (policy reported by students) | |
Inappropriate predictor's measure (policy reported by students) | |
RCT; not possible to isolate the predictor | |
Cross‐sectional study; considered for hypothesis generation | |
Cross‐sectional study; considered for hypothesis generation | |
Inappropriate outcomes | |
Inappropriate predictor's measure (policy reported by students) | |
Inappropriate predictor's measure (policy reported by students) |
Background section has been summarised from the original protocol. List of eligible study designs now uses EPOC recommended terminology.
AC was involved in coordinating the review, developing the protocol, extracting data, conducting the analysis and co‐wrote and edited the review.
MRG was involved in developing the protocol and co‐wrote the review.
LG, DB and SB were involved in conducting the analysis and co‐wrote the review.
FF was involved in coordinating the review, developing the protocol, extracting data and co‐wrote and edited the review.
Internal sources.
Participant organizations in ALICE RAP can be seen at http://www.alicerap.eu/about‐alice‐rap/partners.html. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
AC, MRG, LG, DB, SB and FF have no potential conflict of interest.
Chen 2014 {published data only}.
Adams 2009 {published data only}.
Alesci 2003.
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500 Words Essay On Smoking. One of the most common problems we are facing in today's world which is killing people is smoking. A lot of people pick up this habit because of stress, personal issues and more. In fact, some even begin showing it off. When someone smokes a cigarette, they not only hurt themselves but everyone around them.
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