Trends in Smoking among University Students between 2005-2012 in Sakarya , Turkey

The five leading global risks for mortality in the world are high blood pressure, tobacco use, high blood glucose, physical inactivity, and overweight-obesity. These are responsible for raising the risk of chronic diseases, such as heart disease and cancers and affect countries across all income groups. Worldwide smoking prevalence is 26% (males 54%, females 10%) and attributable mortality by smoking in the world is estimated to be 8.7% (males 11.5%, females 5.5%). According to the classification in July 2012 on the basis of 2011 gross national income (GNI) per capita by the World Bank, Turkey stands in “upper middle income” group among European countries (The World Bank, 2014). The prevalence of regular tobacco smoking (the main component of tobacco use) in the European Region of the World Health Organization (WHO) among the population aged 15 years and over has reached 27% on average according to the data reported from 37 countries around 2008 (World Health Organization, 2013). The WHO Framework Convention on Tobacco


Introduction
The five leading global risks for mortality in the world are high blood pressure, tobacco use, high blood glucose, physical inactivity, and overweight-obesity.These are responsible for raising the risk of chronic diseases, such as heart disease and cancers and affect countries across all income groups.Worldwide smoking prevalence is 26% (males 54%, females 10%) and attributable mortality by smoking in the world is estimated to be 8.7% (males 11.5%, females 5.5%).According to the classification in July 2012 on the basis of 2011 gross national income (GNI) per capita by the World Bank, Turkey stands in "upper middle income" group among European countries (The World Bank, 2014).The prevalence of regular tobacco smoking (the main component of tobacco use) in the European Region of the World Health Organization (WHO) among the population aged 15 years and over has reached 27% on average according to the data reported from 37 countries around 2008 (World Health on tobacco Three countries with 278 million people have put in place four measures at the highest level.Today, one country, Turkey, protects its entire population of 75 million people with all MPOWER measures at the highest level. In Turkey the 1996 Law No. 4207 on "Prevention and Control of Hazards of Tobacco Products", as amended in 2012 (Law 4207 as amended and consolidated in 2012) is the main source of law regulating the advertising of tobacco products.The law sets a general ban on tobacco products advertising, promotion and sponsorship.The Regulation on Procedure and Principles of Sales and Presentations of Tobacco Products and Alcoholic Beverages, adopted in 2011 expressly prohibits promotional discounts.
Turkey was the first country to complete data collection for the Global Adult Tobacco Survey (GATS) in 2008, and was one of the two countries to repeat GATS in 2012.According to these surveys, the smoking prevalence significantly decreased among adults from 31.2% (16.0 million) in 2008 to 27.1% (14.8 million) in 2012 which represents a 13.4% relative decline of the smoking prevalence (World Health Organization, 2013).
In this study, we aimed to design a survey to make a comparison of smoking and dependence data obtained from Sakarya University students in 2005 and 2012.

Study sample and sampling
In academic years 2005-2006 and 2012-2013, the total number of Sakarya University Campus students was 17,541 and 14,942, respectively.A total of 4,200 (2,500 and 1,700 for each academic year) students of Sakarya University in Sakarya, Turkey, were randomly selected for a proper representation of Sakarya University students.Of the 4,500 students selected, 3,749 responded (2,249 and 1,500, respectively), yielding an overall response rate of 89.3%.The study was carried out during the fall periods of each academic year.Students were informed of their selection and asked to attend the study at their classrooms.Informed verbal consent was obtained from the participating students.They were asked to answer all questions honestly, and were reassured about the anonymity and confidentiality of the information.Data were collected using a pretested anonymous and confidential, self-completed questionnaire, which was administered by one of the investigators and took 15-20 minutes to complete.

Questionnaire
Participants were asked to classify themselves as "non-smoker", "current smoker", and "ex-smoker".The demographic characteristics were age (in years), grade (1-4), and gender.Parental education level was asked in five items: illiterate, literate (no graduation), primary school, secondary/high school, college/faculty.Age was grouped into two as "20 years and younger" and "older than 20 years".Students self-rated their school success as "bad", "passable", and "good/very good".The "family members smoking index" ranged from 0 to 4, based on four items: having a smoker father, having a smoker mother, having a smoker sibling, and having a smoker relative living in the same household.Students were grouped into three (1=dormitory; 2=family or relative home; 3=student lodging) based on their accommodation status.They were asked to classify their family income as lower most segment (= 0), middle segment (= 1), and upper/uppermost segment (=2).To gather information on "peer smoking", participants were asked how many of their friends smoke cigarettes (0=none, 1=few, 2=almost half, 3=almost all, 4=all)."Intention to quit" was a measure of the student's intention to quit smoking cigarettes ("No, I do not plan to quit smoking", "Yes, within 30 days", "Yes, within one year", "Yes, in five years / I'm not sure when") and if they believe in themselves about their intentions (either "Yes" or "No").Students were asked if they ever had attempt to quit.The "self-rated dependence" was inquired ("No, I'm not dependent", "Yes, I'm dependent") and all students who smoke one or more cigarettes daily were asked to fill in Turkish version of "Fagerstrom Test for Nicotine Dependence" (FTND) (Uysal et al., 2004).The scores were categorized into five groups as very low dependence, low dependence, medium dependence, high dependence, and very high dependence .

Statistical analysis
Data were coded, entered and analyzed using SPSS for Windows 11.5 (SPSS Inc, Chicago, Illinois, USA).Results are given as frequency and in percent.Bivariate analysis was completed using chi-squared tests of significance.All statistically-significant independent variables from the correlation tests (Pearson's) were entered into a binary logistic regression model.They were regressed on the smoking status (with smokers=1) as the outcome variable.Based on this binary logistic regression model, the strength of association between the independent and outcome variables was determined by the odds ratio [with 95% confidence interval (CI)].The level of significance was kept at alpha=0.05.

Determinants of smoking
For both education years' data analysis; age/age group, gender, mothers and fathers' education level, family smoking index, mothers' smoking status, siblings' smoking status, relatives' smoking status, school success (self-rated), and accommodation were found to be correlated with smoking (Table 2).Self-declared economic status (family) and mothers' education level were not correlated with smoking in academic year 2012-2013.In the binary logistic regression (stepwise forward likelihood ratio) smoking was taken as the dependent variable and for academic year 2005-2006; age, gender, parental education level, self-declared economic status and school success, family smoking index, accommodation during academic year, and peer smoking were taken as independent variables.Among these independent variables age, gender, school success, family index, peer smoking, and self-declared economic status were the terms left in the equation (Table 3).The most remarkable contributor of the equation was peer smoking ratio; the odds of being classified as a smoker increased positively with having smoker friends (all) (OR= 47.45;95%CI= 13.25 to 167.89).
Analysis of 2012 data with binary logistic regression age, gender, accommodation, and peer smoking were the terms left in the equation (Table 4).The results reveal that peer smoking has a positive effect on student smoking: to have all peers smoking is found to increase the probability of student smoking by 58.02 times (95%CI= 16.15 to 208.45) (significant at the level 0.1%).

Discussion
Smoking ban in Turkey has inevitably carried and sustained anti-tobacco activities in public agenda Thus these activities should be taken as a whole with the new legislation while measuring the effects of the legislation per se.Sakarya University has started an outpatient clinic for students with the intention to quit smoking in 2006.At this outpatient clinic a pulmonary diseases specialist and a nurse served at weekdays, free of charge.In addition to this service, there were some social and cultural activities; "knowledge contest"s, conferences, "Don't be dependent, be free" project, concerts etc.These were under the supervision of "Sakarya University Tobacco Coordination Committee", which was comprised of representatives (a faculty and a civil servant) from each academic unit.This study's first step took place in 2005-2006 educational years which was the very first year of "anti-tobacco" activities at Sakarya University Campus.About a quarter of the students were smokers with male gender dominance.Overall prevalence was higher than Çukurova but significantly lower than Sivas, Eskişehir students' smoking prevalence during those years (Metintaş et al., 1998;Saatci, et al., 2004;Demirel et al., 2005).Significant difference between genders have been found in previous studies and mainly attributed to traditional gender roles in Turkish culture which still has influence despite changing social and economic status (Saatci et al., 2004;Erbaydar et al., 2005).In the 2012-2013 educational year there was significant decrease of smoking prevalence; from 26.9% to 18.5%.The Global Adult Tobacco Survey (GATS) is a global standard protocol for systematically monitoring adult (persons 15 years of age and older) tobacco use and tracking key tobacco control indicators.In Turkey, GATS was first conducted in 2008 and repeated in 2012.The smoking prevalence significantly decreased among adults from 31.2% in 2008 to 27.1% in 2012.This represents a 13.4% relative decline of the smoking prevalence (13.5% decline for males; 13.7% decline for females).Sangthong et al. study (2011) in Thailand revealed that susceptibility to smoking in newer cohorts is lower than that in earlier cohorts at the same age.In the same study prevalance of smoking increases from 11-15 to 26-30 years old which implies that most people begin to smoke in their teens.In Kerala a specially designed tobacco control program reduced tobacco use among school children (Philipet al., 2013).In Korea family status was highlighted (Kang et al., 2013).In Turkish teen studies smoking prevalances are between 18.1% and 38% (Arbak et al., 2000;Karlıkaya, 2002;Golbasi et al., 2011).Most of this decline in Turkey is basically due to the implementation of a comprehensive set of tobacco control policies and a national action plan.In 2007 no country protected its population with all five or Smoking determinants among Turkish adolescents have been studied and male gender, parental smoking, parents' age, mother's education, smoking of sibling, birth rank, employment of father were reported as independent variables increasing the odds of being smoker (Metintaş et al., 1998;Ozge et al., 2006;Ertas, 2007).In our study population, the odds of being smoker were high if a student was male, had smoker mother/ sibling/peer, had low school success, was of low familial income, or lived at places except for dormitories although these correlates of being smoker are not peculiar to Turkish university students.All around the world tobacco consumption studies revealed these associates of smoking (Kabir, 2007;Binu et al., 2010;Cai et al., 2012;Reda et al., 2012;Hussain et al., 2013;Kaleta et al., 2013;Karimy et al., 2013).
Self-rated dependence question was dichotomous and was highly correlated with moderate/high nicotine dependence score of FTND but for this group approximately 20% of the students rated themselves as not dependent.The assessment of nicotine dependence is indispensable in epidemiological studies.The major methods to determine nicotine dependence can be divided into four types based on their central constructs: (1) generic definitions of substance dependence and their derivatives (American Psychiatric Association, 2010), (2) Fagerstrom tests and their derivatives (Fagerström, 1978;Heatherton, et al., 1991), (3) consumption, and (4) self-rated dependence (Eiser et al., 1986).FTND is a measure of nicotine dependence that is subjective in nature.In some studies it is indicated that men tend to be more dependent than women, and in some others no difference was reported (Berlin et al., 2003;Bohadana et al., 2003;Targowski, et al., 2004;Gallus et al., 2005;John et al. 2005).In this study there was inter-gender difference in terms of mean FTND scores, i.e. men were more "dependent" than women.In some research it is suggested that men smoke primarily for pharmacological reinforcement provided by nicotine, whereas women smoke primarily for psychological reinforcement obtained through social interaction and tension reduction (Berlin et al., 2003).Evidence suggests that women are less likely to quit smoking than are men.Women tend to have a more difficult time in smoking cessation depending on the phase of menstruel cycle: greater craving and dysphoria during the luteal phase than during the follicular phase of the cycle (Carpenter, et al., 2006).Although several sex differences in nicotine dependence have been identified, the mechanisms underlying these sex differences are not clear.
In conclusion, the 2013 World Health Assembly called on governments to reduce the prevalance of smoking by about a third by 2025 (World Health Organization, 2013).Price was presented as the key determinant of smoking uptake and cessation.WHO Framework Convention on Tobacco Control and MPOWER initiative are other ways of consumption reduction.Our Sakarya sample is a crosssectional example of the university students' smoking and these results cannot be generalized to whole nation but we can speculate that all measures taken against smoking contributes to diminution of smoking prevalence.As Turkey protects its entire population with all MPOWER measures we do not have the opportunity to compare our results with university students who are not under MPOWER protection. .

Table 2 . Correlation Coefficients for Variables by Education Year
*Correlation is significant at the 0.05 level (2-tailed); **Correlation is significant at the 0.01 level (2-tailed)