1. Background
The diagnosis of nicotine dependence is the most prevalent psychiatric disorder. Tobacco is the most common form of nicotine and smoking is the most common form of tobacco use (1). In the world, one billion men and 250 million women, aged 15 and older, smoke tobacco and approximately 3 million people per year die from the health effects of smoking (2). Today, 51% of people in the United States (U.S.) currently smoke, 25% are former smokers, and 24% have never smoked. On average, people in the U.S. begin smoking at age 16, with fewer people beginning after the age of 20. According to the Center for Disease Control (CDC), approximately 20% of adults, 23% of high school students, and 8% of middle school students in the U.S. currently smoke (3). Studies in the U.S. have shown that approximately 30% of college students report smoking in the past 30 days, and 40% had smoked in the past year (4). Level of education correlates with tobacco use. Thirty-seven percent of those who did not finish high school smoke compared to only 17% of university graduates. Although cigarette use is decreasing in the U.S., cigarette use is on the rise in developing countries (1). Some studies have shown that the increase in water-pipe use has the potential to become a major public health problem in many parts of the world, particularly in the Eastern Mediterranean Region (EMR), a region which includes Iran (5, 6). Preliminary evidence on the health effects of water-pipe use and smoking links them closely to respiratory disease, cardiovascular disease, and cancer (7, 8). Researchers in Iran have studied the prevalence of substance use and substance-related disorders among students and have reported that nicotine is the most prevalent substance used. Fifteen to thirty percent of students reported that they have used nicotine once or more during their lifetime, while 10% to 15% reported using it occasionally, and 3% to 10% reported nicotine dependence (9-13). In a public sample in Iran, 14.6% of 15–69 years old smoke cigarettes regularly (14). Studies also report that nicotine use is higher in men than women. However, these studies have not considered the patterns of nicotine use and demographic variables as correlates of nicotine use or dependence. This paper reviews the epidemiology of water-pipe, cigarette, and oral tobacco use among Iranian university students and evaluates sociodemographic variables that correlate with nicotine use in this population.
2. Objectives
To determine the prevalence of cigarette, water-pipe, and oral tobacco use among Ferdowsi University students in Iran and to evaluate the association between sociodemographic characteristics and nicotine use.
3. Patients and Methods
Ferdowsi University of Mashhad is the main university in the east of Iran. Students were selected using stratified sampling. One thousand and eight hundred students were selected by gender, academic level, and faculty, and a total of 1565 students responded to the questionnaire (a response rate of 87%). As shown in Table 1, the sample includes more female respondents (54.2%) than male respondents (45.8%). The academic level of the respondents included undergraduate (71%), Master’s degree (19.7%), and PhD students (9.1%). Students of human sciences comprised 42.7% of the sample followed by engineering (24%), science (18.8%), and agriculture (14%). The sociodemographic variables of the sample are also shown in Table 1.
Table 1.Prevalence (%) of Nicotine Use for Lifetime Use (One or More Times) by Sociodemographic Variables
| Sample, No. (%) | Used, No. (%) | 95%CI | k Value | |
|---|---|---|---|---|
| Gender | 251.3 a | |||
| Male | 716 (45.8) | 378 (52.8) | 49.3–56.3 | |
| Female | 847 (54.2) | 128 (15.2) | 12.8–17.6 | |
| Not stated | 2 (0.1) | |||
| Marital status | N.S b | |||
| Single | 1287 (82.3) | 422 (32.8) | 30.3–36.3 | |
| Married | 272 (17.4) | 81 (29.7) | 24.3–35.1 | |
| Divorced, separated or widowed | 4 (0.3) | 3 (75) | - | |
| Not stated | 2 (0.1) | - | - | |
| Age groups | 68.4 a | |||
| < 20 | 569 (36.4) | 119 (20.933) | 17.6–23.3 | |
| 20-23 | 586 (37.4) | 200 (4.1) | 30.3–37.9 | |
| 23-26 | 261 (16.7) | 123 (47.1) | 41–53.2 | |
| > 26 | 139 (8.9) | 60 (43.1) | 34.9–51.3 | |
| Not stated | 10 (0.6) | |||
| Residential area | N.S b | |||
| Domestic | 916(58.4) | 283 (30.9) | 27.9–33.9 | |
| Not domestic | 622(39.7) | 213 (34.2) | 30.5–37.9 | |
| Not stated | 27(1.7) | |||
| Race | N.S b | |||
| Persian | 1340(85.6) | 436 (32.533) | 30–35 | |
| Turkish | 84(5.4) | 31 (6.9) | 26.9–46.9 | |
| Kurdish | 48(3.1) | 17 (35.4) | 21.8–48.9 | |
| Other | 64(4.1) | 19 (29.6.) | 18.5–40.7 | |
| Not stated | 29(1.9) | |||
| Family income | 19.1 a | |||
| Poor | 438 (28) | 122 (27.8) | 23.6–32 | |
| Average | 422 (27) | 133 (31.5) | 27.1–35.9 | |
| Good | 331 (21.2) | 96 (29) | 24.1–33.9 | |
| Very good | 339 (21.7) | 141 (41.5) | 36.3–46.7 | |
| Not stated | 35 (2.2) | |||
| Occupational status | 70.7 a | |||
| Unemployed | 1185 (75.7) | 318 (26.8) | 24.3–29.3 | |
| Part-time | 301 (19.2) | 147 (48.8) | 43.2–54.4 | |
| Employed | 55 (3.5) | 32 (58.1) | 45.1–71.1 | |
| Not stated | 24(1.5) | |||
| Residency | 46.7 a | |||
| At home with family | 889 (56.8) | 276 (31) | 28–34 | |
| At home with friends | 57 (3.6) | 28 (49.1) | 36.1–62.1 | |
| At home alone | 30 (1.9) | 23 (76.6) | 61.5–91.7 | |
| In student dormitory | 454 (29) | 122 (26.8) | 22.7–30.9 | |
| Other | 123 (7.9) | 52 (42.2) | 33.5–50.9 | |
| Not stated | 12 (0.8) | |||
| Faculty | 65.3 a | |||
| Human sciences | 662(42.7) | 167 (25.2) | 21.9–28.5 | |
| Sciences | 294(18.8) | 72 (24.5) | 19.6–29.4 | |
| Agriculture | 219(14) | 93 (42.5) | 36–49 | |
| Engineering | 375(24) | 171 (45.6) | 40.6–50.6 | |
| Not stated | 8(0.5) | |||
| Academic level | 49.9 a | |||
| Undergraduates | 1111 (71) | 303 (27.2) | 24.6-29.8 | |
| Master’s | 309(19.7) | 130 (42.1) | 36.8-47.4 | |
| PhD students | 142(9.1) | 73 (51.4) | 43.2-59.6 | |
| Not stated | 3(0.2) | |||
| Academic performance | 65.4 a | |||
| Very good | 433(27.7) | 115 (26.5) | 22.4–30.6 | |
| Good | 674 (43.1) | 184 (27.3) | 23.9–30.7 | |
| Average | 321 (20.5) | 141 (43.9) | 38.5–49.3 | |
| Poor | 73 (4.7) | 46 (63) | 52–74 | |
| Not stated | 64 (4.1) | |||
| Paternal (father) education | 12.1 c | |||
| Illiterate | 171 (10.9) | 69 (40.3) | 34–47.6 | |
| Primary school | 187 (11.9) | 44 (23.5) | 17.4–29.6 | |
| Guidance school | 166(10.6) | 50 (30.1) | 23.1–37.1 | |
| High school | 386 (24.7) | 127 (32.9) | 28.3–37.5 | |
| University | 625 (39.9) | 204 (32.6) | 28.9–36.3 | |
| Not stated | 30 (1.9) | |||
| Maternal (mother) education | 12.7 c | |||
| Illiterate | 213 (13.6) | 83 (38.9) | 32.4–45.4 | |
| Primary school | 305 (19.5) | 76 (24.9) | 20.1–29.7 | |
| Guidance school | 227 (14.5) | 70 (30.8) | 24.8–36.8 | |
| High school | 431(27.5) | 144 (33.4) | 28.9–37.8 | |
| University | 372(23.8) | 125 (33.6) | 28.8–38.4 | |
| Not stated | 17(1.1) | |||
| Smoking in family | 43 a | |||
| No one | 1255(80.2) | 370 (29.4) | 26.9-31.9 | |
| Father and/or mother | 238(15.2) | 89 (37.3) | 31.2-43.4 | |
| Brother and/or sister or with parents | 68(4.2) | 45 (66.1) | 54.9-77.3 | |
| Not stated | 4(0.3) | |||
| No one | ||||
| Substance use in family | 35.1 a | |||
| No one | 1481(94.6) | 455 (30.7) | 28.4–33 | |
| Father and/or mother | 45 (2.9) | 25 (55.5) | 41–70 | |
| Brother and/or sister or with parents | 23 (1.5) | 18 (78.2) | 61.3–95.1 | |
| No one | 14 (0.9) | |||
| Not stated | ||||
| Total | 1565 (100) | 506(32.33) | 30.01–34.65 |
aP < 0.001
bAbbreviation: N. S, Non-Significant
cP < 0.05, (n = 1565)
3.1. Assessment
Three manners of nicotine use were evaluated (cigarette, water-pipe and oral tobacco use) using questions from the substance use section of the Youth Risk Behavior Survey questionnaire (15). The following questions were used: A) Ever used (cigarette, water-pipe and oral tobacco) with answer choices of “yes” or “no”; B) Used (cigarette, water-pipe and oral tobacco) during the past 12 months with answer choices of yes or no, and; C) Used (cigarette, water-pipe and oral tobacco) during the previous month with answer choices of no, 1–5 days, 6–19 days and 20 or more days. For each of these manners of nicotine use, the age at first use was queried. Demographic data were determined with questions about gender, marital status, age, race, occupational status, domestic status, faculty, academic level, academic performance, residence status, paternal education level, maternal education level, family income, and history of nicotine and substance use by family members.
3.2. Statistical Analysis
Prevalence rates for nicotine use (cigarette, water-pipe and oral tobacco use) were computed using SPSS software (18.00) First, univariate analysis was performed to investigate the association between demographic and background variables with nicotine use. The relationship between nicotine use and gender, marital status, age, race, vocational status, domestic status, faculty, academic level, academic performance, residence status, paternal education level, maternal education level, family income, history of nicotine and substance use by family members as computed using χ2 tests. Next, the associations that were significant in the univariate analysis were analyzed using logistic regression models. The dependent variables in the logistic regression were lifetime nicotine use (ever used) and recent nicotine use (used within the past month).
4. Results
4.1. Prevalence of Nicotine Use
Overall, approximately one-third (32.33%) of all subjects reported using nicotine at least once during their lifetime (Table 1). The prevalence of nicotine use among men was more than 3 times the prevalence among women (52.8% vs. 15.2%, P <0.001). Differences in the prevalence of nicotine use by age group, family income, occupational status, educational level, residency, faculty, academic level, academic performance, paternal and maternal education level, history of nicotine and substance use by family members were statistically significant (Table 1). Specifically, nicotine use was higher among students aged 23–26 or 26 years and older, students with very good family income, students who were employed part-time or full-time, students who lived at home alone or with friends, students who were in agriculture or engineering faculty, Master’s degree or PhD students, students with average or poor academic performance, students with illiterate fathers or mothers, and students with a history of substance use by family members. The prevalence and manner of nicotine use in the past month and past year and are shown in Table 2. Water-pipe and cigarette smoking were the most common forms of nicotine use. The prevalence of lifetime water-pipe use was approximately 2 times greater than that for cigarette use. A small group of students (6.4% of the total sample) reported using water-pipes occasionally (1-5 days in the past month) while only 3.7% of the total sample reported using cigarettes occasionally (1-5 days in the past month). Regular water-pipe or cigarette users (defined as 5–19 and ≥ 20 days in the past month) comprised 4.3% and 3.9% of the sample, respectively. The mean ages of first use for cigarette, water-pipe, and oral tobacco use were 18.3 ± 3.4, 18 ± 3.01 and 20.5 ± 3 years, respectively.
Table 2.The Prevalence of Water Pipe, Cigarette and Oral Tobacco Use in the Previous Year and Last Month
| No, No. | Yes, No. (%) | 95%CI | |
|---|---|---|---|
| Ever Used (Lifetime Use) | |||
| Water-pipe | |||
| Male | 358 | 359 (50.06) | 46.4–53.7 |
| Female | 815 | 133 (14.03) | 11.7–16.3 |
| Total | 1078 | 487 (30.54) | 28.2–32.8 |
| Cigarette | |||
| Male | 490 | 227 (31.6) | 28.2–35 |
| Female | 799 | 49 (5.8) | 4.2–7.4 |
| Total | 1289 | 276 (17.6) | 15.7–19.5 |
| Oral tobacco | |||
| Male | 697 | 20 (2.8) | 1.6–4 |
| Female | 846 | 2 (0.23) | 0.07–0.39 |
| Total | 1543 | 22 (1.4) | 0.8–2 |
| Used in the Past Year | |||
| Water-pipe | |||
| Male | 122 | 241(66.4) | 61.6–71.2 |
| Female | 51 | 69 (57.5) | 48.7–66.3 |
| Total | 173 | 310 (64.2) | 59.9–68.5 |
| Cigarette | |||
| Male | 70 | 156 (69) | 63–75 |
| Female | 27 | 23 (46) | 32.2–59.8 |
| Total | 97 | 179 (64.8) | 59.2–70.4 |
| Oral tobacco | |||
| Male | 13 | 7 (35) | 14–56 |
| Female | 0 | 1 (1) | - |
| Total | 13 | 8 (38.1) | 18.4–58.8 |
| Used Within the Last Month | |||
| Water-pipe | |||
| Male | 215 | 84 (23.4) | 34 (9.4) |
| Female | 96 | 16 (13.3) | 5 (.2) |
| Total | 311 | 100 (20.5) | 39 (8.1) |
| Cigarette | |||
| Male | 110 | 56 (24.7) | 51 (23.1) |
| Female | 45 | 4 (8) | 0 (0) |
| Total | 155 | 59 (21.4) | 51 (18.5) |
| Oral tobacco | |||
| Male | 15 | 4 (20) | 1 (5) |
| Female | 1 | 0 (0) | 0 (0) |
| Total | 16 | 4 (19) | 1 (4.7) |
4.2. Sociodemographic Variables Analysis
The results of the logistic regression analysis are shown in Table 3. Compared to women (the reference gender), the odds of lifetime nicotine use were nearly 5.5 times higher in men [odds ratio (OR) 5.46; 95% confidence interval (CI), 3.92-7.60]. Compared to students with very good family income, students with poor (OR 0.54; 95% CI, 0.36-0.81), average (OR 0.55; 95% CI, 0.37-0.82), or good family incomes (OR 0.56; 95% CI, 0.35-0.89) had lower odds of nicotine use. The odds of lifetime nicotine use were nearly 1.8 times higher in engineering faculty students than human science students (OR 1.83; 95% CI, 1.21-2.78). Further, Master’s degree and undergraduate students had lower odds of lifetime nicotine use than PhD students, as did those students with poor academic performance. The odds of lifetime nicotine use in students who had at least 1 parent with a history of cigarette use were lower than for students with at least 1 sibling with a history of cigarette use. Other factors affecting odds of lifetime nicotine use included residency. The results of the logistic regression analysis for regular nicotine use in the previous month are shown in Table 3. Men were about 11 times more likely than women to be regular nicotine users (OR 11.267; 95% CI, 6.640-19.11). Students with poor family income, poor academic performance, and history of smoking among parents had lower odds of regular nicotine use.
Table 3.Logistic Regression Analysis of Significant Variables Related to Lifetime and Regular Nicotine Use
| Lifetime Nicotine Use | Regular Nicotine Use in the Last Month | |||||||
|---|---|---|---|---|---|---|---|---|
| β | Standard Error | P Value | Odds Ratio(95% Cl) | β | Standard Error | P Value | Odds Ratio(95%Cl) | |
| Gender | ||||||||
| Male | 1.7 | 0.16 | 0.000 | 5.46(3.9–7.60) | 2.42 | 0.270 | 0.000 | 11.267(6.64–19.11) |
| Female | 1 | - | - | - | 1 | - | - | - |
| Family income | ||||||||
| Poor | -0.61 | 0.21 | 0.003 | 0.54(0.36–0.81) | -0.67 | 0.308 | 0.030 | 0.511(0.28–0.93) |
| Average | -0.59 | 0.20 | 0.004 | 0.55(0.37–0.82) | -0.54 | 0.272 | 0.047 | 0.583(0.34–0.99) |
| Good | -0.58 | 0.24 | 0.016 | 0.56(0.35–0.89) | -0.90 | 0.277 | 0.001 | 0.404(0.23–0.93) |
| Very good | 1 | - | - | - | 1 | - | - | - |
| Faculty | ||||||||
| Agriculture | 0.21 | 0.23 | 0.345 | 1.24(0.79–1.94) | ||||
| Science | 0.17 | 0.23 | 0.442 | 1.195(0.75–1.88) | ||||
| Engineering | 0.61 | 0.21 | 0.004 | 1.83(1.21–2.78) | ||||
| Human science | 1 | - | - | - | ||||
| Academic level | ||||||||
| Undergraduates | -1.02 | 0.32 | 0.001 | 0.36(0.19–0.67) | ||||
| Master’s | -0.57 | 0.30 | 0.055 | 0.56(0.31–1.01) | ||||
| PhD students | 1 | - | - | - | ||||
| Academic performance | ||||||||
| Poor | -1.61 | 0.34 | 0.000 | 0.199(0.10–0.38) | -1.80 | 0.407 | 0.000 | 0.165(0.07–0.38) |
| Average | -1.36 | 0.32 | 0.000 | 0.256(0.13–0.48) | -1.37 | 0.362 | 0.000 | 0.254(0.12–0.51) |
| Good | -0.56 | 0.32 | 0.081 | 0.572(0.30–1.07) | -0.40 | 0.344 | 0.237 | 0.666(0.34–1.30) |
| Very good | 1 | - | - | - | 1 | - | - | - |
| Cigarette Use in family | ||||||||
| No one | -1.29 | 0.34 | 0.000 | 0.274(0.14–0.53) | -1.81 | 0.372 | 0.000 | 0.162(0.078–0.33) |
| Father and/or mother | -1.23 | 0.37 | 0.001 | 0.292(0.14–0.61) | -1.56 | 0.430 | 0.000 | 0.208(.090–0.48) |
| Brother and/or sister | 1 | - | - | - | 1 | - | - | - |
| Alone or with parents | ||||||||
| Residency | ||||||||
| At home with family | -1.09 | 0.32 | 0.001 | 0.335(0.17–0.63) | ||||
| In student dormitory | -1.62 | 0.44 | 0.000 | 0.197(0.08–0.47) | ||||
| At home alone | 1.02 | 0.65 | 0.115 | 2.789(0.78–9.97) | ||||
| At home with friends | -0.42 | 0.31 | 0.172 | 0.654(0.35–1.20) | ||||
| Other | 1 | - | - | - | ||||
5. Discussion
According to the findings in this study, 32.33% of Ferdowsi University students have used nicotine at some point during their lifetime (52.8% of men and 15.2% of women). Approximately 3.9% reported using cigarettes on a regular basis and 4.3% reported using a water-pipe on a regular basis. These results show that nicotine use among Iranian students is lower than in the U.S. and Turkey, Iran’s European neighbor (4, 16-20). Although smoking among Iranian male students is similar to that of the U.S and Turkey, the prevalence of smoking amongst Iranian female students is lower than in those countries. This difference may be the result of cultural and religious differences. Smoking is not approved of for women in Iran and this factor could be the reason for the lower rate of nicotine use in female students. The majority of tobacco users are cigarette smokers (16-20); however, this study shows that water-pipes were used more frequently among Iranian students. Compared to a public sample in Iran (14), fewer students were regular cigarette smokers. According to Johnston et al., smoking rates among young adults who do not attend college are higher than smoking rates among college students (18). Iranian students in the current sample tended to be occasional nicotine users rather than regular users, which may be because college student smokers are more likely to be non-daily smokers, meaning that they smoke more in social situations when compared to their non-college peers (21, 22).
The average age of first nicotine use agrees with studies in Iran and other countries (20, 23, 24). Prevalence of cigarette use in male students is approximately 3 times higher than in female students (9-13). According to these results, male students appear to be at higher risk of substance use than female students. Students with a very good family income have higher odds of lifetime and regular nicotine use. This finding is similar to Tot et al. (2004) (25) who reported that among Turkish adolescents, higher family socioeconomic status increased the likelihood of smoking and alcohol use, possibly because this group had the necessary funds to access these substances. Engineering students had high odds of lifetime nicotine use compared with human science students, a finding that disagrees with Metintash et al. (1998) (19). This may be attributed to the fact that the engineering faculty gender distribution is 3 to 1 (3 men for every 1 woman). Previous studies have shown that high education level is associated with lower odds of substance and cigarette smoking, except for alcohol use (1). In this study, PhD students had higher odds of lifetime nicotine use, but there was no correlation with regular nicotine use. This may be due to gender distribution (80% of PhD students are male), educational and entrance exam stressors at each level, and the competition to enter the university. Studies suggest that smokers smoke more during stressful situations or in situations involving negative mood (20), but this does not predict later regular nicotine use. Subjects who reported poor academic performance had higher lifetime and regular nicotine use rates, as has been reported previously in adolescents (25, 26). Thirty-four percent of all cigarette smokers in the U.S. have both a psychiatric disorder and are nicotine dependent, emphasizing the relevance of the comorbidity of nicotine dependence with other psychiatric disorders (27) and their possible detrimental effect on academic performance. Higher rates of smoking occur among students whose parents smoke compared to those whose parents do not smoke. Students who live with their families or in a dormitory were less likely to smoke compared to students who live with their friends or alone (19, 20, 25). Parental smoking behavior appears to be an important factor in the smoking behavior of university students. The prevalence of smoking was higher among students who had at least 2 family members who were smokers. The smoking behavior of fathers and siblings was found to be related the prevalence of student smoking (19). The most important predictors of nicotine use were gender, very good family income, poor academic performance, and cigarette use by family members.
