Archives of

1. Introduction
Health is a multidimensional issue that includes physical, mental, social, and spiritual health [1]. Smoking is one of the important factors that threaten the health of people, especially young people, and one of the priorities of public health to reduce the prevalence of smoking is to prevent young people from becoming smokers [2,3].
Compared to drugs, smoking is a substance that is easily available to the public and its social stigma is low. Therefore, people, especially young people, easily turn to smoking and become addicted to it as a result of continued use. In addition to having physical and psychological effects on the individual, smoking addiction also threatens the health of society from a cultural, social, economic, and political point of view [2,4]. According to the information provided by the United States Centers for Disease Control and Prevention (CDC), smoking is the most important and preventable cause of death in the United States. In this country, 443 000 people die every year due to smoking [5]. If current patterns of tobacco use in the United States continue, about 5 million people under the age of 18 will die prematurely from smoking-related diseases [6]. The World Health Organization (WHO) has estimated that in the 20th century, about 100 million people died due to smoking, most of whom were in rich countries [7,8]. According to the estimate by the WHO, the number of deaths caused by smoking will reach more than 10 million people in 2030 [9]. Smoking in Iran among people over 15 years old is 13.2 cigarettes (12.7% in the city and 11.9% in the village) [10]. The International Burden of Disease Study has estimated the number of deaths caused by tobacco to be higher than the WHO. According to this study, 8.7 million people die every year due to smoking. Unfortunately, the prevalence of smoking in the world has doubled in the last twenty years, and the annual number of deaths caused by smoking is growing [8]. The prevalence of smoking among young people has increased, especially among people in the age
group of 18-24 years old which is mainly constituted of
students [11].
Exposure to secondhand smoke has immediate
and long-term health effects. Exposure to cigarette
smoke occurs in different environments such as home,
workplace, and public environments [12]. Exposure at
home and work may be particularly harmful because
many people spend most of their time at home and
work [12,13]. Exposure to cigarette smoke increases
the angiotensin-converting enzyme (ACE2) receptor in
the respiratory tract [14]. Furthermore, smoking and
exposure to secondhand smoke mostly lead to heart, liver,
and lung diseases. Moreover, smoking is the main risk
factor for diseases such as heart attack, stroke, chronic
obstructive pulmonary diseases (e.g., emphysema and
chronic bronchitis), and cancer, especially lung cancer,
larynx cancer, and pancreatic cancer [15-17].
To prevent smoking, special attention should be paid
to young people. Young people are more exposed to
smoking due to social, demographic, environmental, and
individual risk factors [18]. Social and demographic risk
factors related to smoking include families with low social
and economic status. Environmental risk factors include
the availability of cigarettes, smoking by classmates
and siblings, and parents’ inattention to this issue [19].
Individual risk factors include the lack of self-confidence,
the belief that smoking is beneficial, and inability to
refuse tobacco use [18].
This study was to investigate the relationship and
the effect of different variables on smoking prevention
behaviors among the students of Payame Noor University
of Ahvaz in southwest Iran in 2022 using regression
analysis.
2. Materials and Methods
2.1. The study setting
This cross-sectional descriptive study was conducted
in Ahvaz, located in southwest Iran in 2022 among the
students of Payame Noor University (Figure 1). Ahvaz is
located at 31 degrees and 30 minutes of latitude north and
48 degrees and 65 minutes of longitude east, in the plains
of Khuzestan, 12 m above the sea level [20,21].
2.2. Method, data collection, and statistical analysis
This cross-sectional descriptive study was conducted to
assess the relationship and the effect of different variables
on smoking prevention behaviors among students
using regression analysis. The tools used in this study
included a demographic and background information
questionnaire, a questionnaire based on the health belief
model [22], and a questionnaire related to smoking
prevention behaviors [23]. The statistical population
of this study comprised the undergraduate students of
Payame Noor University of Ahvaz, among whom 120
men and women were randomly selected. Thus, first,
a list of all undergraduate students of Payame Noor
University, Ahvaz, was prepared and randomly selected
from among these students. The inclusion criteria for
this study included people’s willingness to enter the
study and studying at the undergraduate level (second
or third year of study) at Payame Noor University. In
addition, unwillingness to continue participating in the
study and incomplete completion of questionnaires were
considered as exclusion criteria.
It was decided to consider 120 students (P2 = 7%) in
this study according to the results obtained from the
pilot study conducted on 30 students. Furthermore, P1
was set at 0.45 for smoking prevention behaviors, and
Bocock’s kappa formula was used considering the test
power of 80% and the confidence level of 95% to enhance
accuracy. Additionally, a 5% drop in samples was taken
into account to address potential uncertainties [24].
1 (1 ) 1 1 2 2
2
2
1 2
( )2 ( )
( )
Z Z p q p q
n
p p
α β −
−
+ × +
=
−
(1)
Figure 1. The location of the study areas
Geravandi et al
180 Arch Hyg Sci. Volume 12, Number 4, 2023
At this stage, sampling was randomly selected from
among the different undergraduate programs at Payame
Noor University involving both males and females.
2.3. Statistical analysis of data
In the section related to the cross-sectional study, central
indices, dispersion, frequency, percentages, and analysis
of variance were used to identify the difference between
different variables related to the adoption of smoking
prevention behaviors. Multiple linear regression test was
also used to compare the predictive power of the health
belief model. The data were then analyzed using SPSS
version 16 statistical software.
3. Results
This study included 120 students of Payame Noor
University of Ahvaz in 1400. The results of the survey
of the research subjects were investigated using a
demographic and background information questionnaire
and a questionnaire based on the health belief model
related to smoking prevention behaviors. The following
table presents the results of the frequency of qualitative
demographic variables (Table 1).
Table 1 depicts that the studied subjects were female
(70%), and the average age of people is 68.23 with a
standard deviation of 57.3. The results of this study
showed that the average age group of the participants
is 68.23, most of the participants (80%) are single, and
36.7 are in the sixth semester of study. Moreover, a higher
percentage (23.3%) of the participating students were
studying in the field of medical engineering, most of
whom (43.3%) lived in a family with 5-6 people, and 8.3%
of students had a family with 3 people.
Table 2 illustrates the results of the descriptive
indicators of different dimensions of the questionnaire.
The results showed an average score of 10.917 out of
20 scores for the structure of perceived sensitivity, an
average score of 12.717 out of 30 scores for the structure
of perceived intensity, an average score of 14.917 out of
30 scores for the structure of perceived obstacles, and the
average score of 18.542 out of 35 scores for the structure
of perceived benefits for preventive behaviors. Moreover,
an average score of 18.100 out of 36 scores for the action
guide structure, an average score of 17.213 out of 30
scores for the self-efficacy structure, and an average score
of 6.892 out of 18 scores were obtained for preventive
behaviors (Table 2).
Table 3 shows the results of the relationship and the
effect of different variables on prevention behaviors
using regression analysis. The results indicated
that the perceived barriers dimension (beta = 0.168,
P value = 0.038) and action guide (beta = 0.235, P
value < 0.001) have a significant effect on prevention
behaviors. According to the reported coefficients, a oneunit
increase in perceived barriers and action guidelines,
0.168 and 0.235 units, respectively, increased the number
of prevention behaviors (Table 3). The effect of each
variable on the distribution charts is also intuitively
presented in Figure 2.
The results of the regression analysis revealed the
relationship and the effect of different variables on
prevention behaviors, as depicted in Figure 2a-d. The
results showed that the perceived barriers dimension
(beta = 0.168, P value = 0.038) and action guide
(beta = 0.235, P value < 0.001) have a significant effect
on prevention behaviors. According to the reported
coefficients, a one-unit increase in perceived barriers
and action guidelines, 0.168 and 0.235 units, respectively,
increased the number of prevention behaviors. The
effect of each variable on the distribution charts is also
intuitively shown in Figure 2a-d.
4. Discussion
The current study is a descriptive-analytical study
that was conducted to assess the relationship and the
effect of different variables on smoking prevention
behaviors among students in southwest Iran in 2022 by
the regression analysis. In the first phase of the study,
120 students of Payame Noor University of Ahvaz were
examined.
In terms of gender, most of the studied subjects were
female (70%). The results of this study showed that the
average age group of the participants is 68.23, most of
the participants (80%) were single, and 36.7 were in the
sixth semester of the study. A higher percentage (23.3%)
of the participating students were studying in the field
of medical engineering. Most of them (43.3%) lived in a
family with 5-6 people, and 8.3% of students had a family
with 3 people. In the current study, 18% of the students
had a smoking father, and 11% of the students were in
a family with more than 2 smokers. Moreover, 10.8% of
students had smoking friends, while 87% did not have
any smoking friends.
Smoking among the participants of this study was 15%.
In a large systematic review and meta-analysis study
conducted on 99 studies by Aryaie et al and indexed by
the WHO website, the prevalence of smoking among high
school students was 13% for girls and 23% for boys [25].
Furthermore, a meta-analysis which was conducted on
46 studies in the population of Iranian students showed
that the prevalence of smoking among female and male
students was 11% and 33%, respectively [25]. Moreover,
a meta-analysis of 37 studies in Iran that included a
total of 16 937 female students and 25647 male students
reported the prevalence of smoking among male and
female students to be 22% on average [25]. The figure for
the prevalence of smoking obtained in our study (15%) is
relatively lower than that reported in this meta-analysis
(22%), which is due to the higher prevalence of smoking
in males than in females, and one of the reasons for this
Arch Hyg Sci. Volume 12, Number 4, 2023 181
Variables on smoking prevention behaviors
Table 1. Frequency of qualitative demographic variables
Variables Qualitative Demographic Number Percent
Valid
Percentage
The Cumulative
Percentage
Gender
Female 84 70 70 70
Male 36 30 30 100
Field of study
Biomedical engineering 28 23.3 23.3 23.3
Computer 11 9.2 9.2 32.5
Rights 13 10.8 10.8 43.3
Business management 1 0.8 0.8 44.2
Electricity 9 7.5 7.5 51.7
Psychology 23 19.2 19.2 70.8
IT 2 1.7 1.7 72.5
Counseling 6 5 5 77.5
Accounting 13 10.8 10.8 88.3
Instrumentation 1 0.8 0.8 89.2
Physics 1 0.8 0.8 90
Construction 1 0.8 0.8 90.8
English language 2 1.7 1.7 92.5
Metallurgy 2 1.7 1.7 94.2
Architecture 1 0.8 0.8 95
Industry 1 0.8 0.8 95.8
Agriculture 1 0.8 0.8 96.7
Physical Education 3 2.5 2.5 99.2
Literature 1 0.8 0/8 100
Semester
5 39 32.5 32.5 32.5
6 44 36.7 36.7 69.2
7 18 15 15 84.2
8 19 15.8 15.8 100
Marital status
Single 96 80 80 80
Married 23 19.2 19.2 99.2
Divorced 1 0.8 0.8 100
Job
No 71 59.2 59.2 59.2
Yes 49 40.8 40.8 100
Constitutional record
No 107 89.2 89.2 89.2
Yes 13 10.8 10.8 100
Sports activity
Never 12 10 10 10
Sometimes 52 43.3 43.3 53.3
Once a month 5 4.2 4.2 57.5
Once a week 16 13.3 13.3 70.8
Three times a week 35 29.2 29.2 100
Father’s education
Illiterate 6 5 5 5
High school 43 35.8 35/8 40/8
Diploma 41 34.2 34/2 75
Bachelor’s degree 22 18.3 18/3 93/3
Master’s degree 8 6.7 6.7 100
Mother’s education
Illiterate 11 9.2 9.2 9.2
High school 40 33.3 33.3 42.5
Diploma 51 42.5 42.5 85
Bachelor’s degree 15 12.5 12.5 97.5
Master’s degree 3 2.5 2.5 100
Geravandi et al
182 Arch Hyg Sci. Volume 12, Number 4, 2023
Variables Qualitative Demographic Number Percent
Valid
Percentage
The Cumulative
Percentage
The number of children
The first 45 37.5 37.5 37.5
The second 28 23.3 23.3 60.8
The third 23 19.2 19.2 80
The fourth 7 5.8 5.8 85.8
The fifth 17 14.2 14.2 100
The number of family members
3 persons 10 8.3 8.3 8.3
4 persons 36 30 30 38.3
5 or 6 people 52 43.3 43.3 81.7
7 or more 22 18.3 18.3 100
Which members of your family smoke?
Father 18 15 15 15
Brother 4 3.3 3.3 18.3
Grandfather 7 5.8 5.8 24.2
Grandmother 1 0.8 0.8 25
Other 79 65.8 65.8 90.8
More than 2 people 11 9.2 9.2 100
How many of your friends smoke?
None 87 72.5 72.5 72.5
1 person 10 8.3 8.3 80.8
2 persons 5 4.2 4.2 85
3 persons 5 4.2 4.2 89.2
More than 3 13 10.8 10.8 100
Has there ever been a history of death due to
the effects of smoking in your family or close
relatives?
No 104 86.7 86.7 86.7
Yes 16 13.3 13.3 100
Have you ever smoked (even once)?
No 102 85 85 85
Yes 18 15 15 100
Who suggested smoking your first cigarette?
Nobody 29 24.2 72.5 72.5
Friends 5 4.2 12.5 85
Brother 3 2.5 7.5 92.5
Other relatives 3 2.5 7.5 100
Missing System 80 66.7
At what age did you smoke your first cigarette?
Less than 10 5 4.2 20 20
10 or 14 3 2.5 12 32
15 or 19 8 6.7 32 64
Above 20 9 7.5 36 100
Missing System 95 79.2
Do you currently smoke?
No 34 28.3 87.2 87.2
Yes 5 4.2 12.8 100
Missing System 81 67.5
What is your current smoking status?
1 cigarette 7 5.8 63.6 63.6
2 to 3 1 0.8 9.1 72.7
4 to 10 1 0.8 9.1 81.8
16 to 20 2 1.7 18.2 100
Missing System 109 90.8
If you smoke every day, how many cigarettes do
you smoke every night?
Less than 10 years old 3 2.5 27.3 27.3
10 to 14 2 1.7 18.2 45.5
15 to 19 years old 3 2.5 27.3 72.7
Above 20 years old 3 2.5 27.3 100
Table 1. Continued
Arch Hyg Sci. Volume 12, Number 4, 2023 183
Variables on smoking prevention behaviors
may be due to the higher percentage of girls in our study
compared to the study by Aryaie et al [25]. In their study,
they showed that male students have a higher percentage
(60%) of the population, and the number of males in the
meta-analysis is 1.5 times the number of females [25].
In the study by Panahi et al on the population of students
living in the dormitory of Shahid Beheshti University of
Medical Sciences, the average age of the students was
22.93, and 60% of the female population, 40% of the male
population, and 17.1% of the students were smokers. A
possible reason for the higher prevalence of smoking in
Panahi and colleagues’ study compared to our study is
Variables Qualitative Demographic Number Percent
Valid
Percentage
The Cumulative
Percentage
Missing System 109 90.8
How old have you been smoking regularly?
No 18 15 69.2 69.2
Sometimes 4 3.3 15.4 84.6
Each month 1 0.8 3.8 88.5
Every week 2 1.7 7.7 96.2
Everyday 1 0.8 3/8 100
Missing System 94 78.3
Does smoking shorten human life?
No 30 25.0 25.0 25.0
Yes 90 75.0 75.0 100.0
Is there dependence (addiction) in smoking?
No 20 16.7 16.7 16.7
Yes 100 83.3 83.3 100.0
Can smoking cause cancer?
No 17 14.2 14.2 14.2
Yes 103 85.8 85.8 100.0
What is the most common cancer caused by
smoking?
Cannot 19 15.8 15.8 15.8
Leukemia 2 1.7 1.7 17.5
Lung cancer 99 82.5 82.5 100.0
Does quitting smoking reduce the risk of most
diseases caused by smoking?
No 34 28.3 28.3 28.3
Yes 86 71.7 71.7 100.0
Which sentence below is correct?
I do not know 17 14.2 14.2 14.2
Hookah is more dangerous than cigarettes. 97 80.8 80.8 95.0
Smoking is more dangerous than hookah. 5 4.2 4.2 99.2
Both are the same. 1 0.8 0.8 100.0
Can being exposed to cigarette smoke be
dangerous for a person?
No 14 11.7 11.7 11.7
Yes 106 88.3 88.3 100.0
Father’s job
Employee 28 23.3 23.3 23.3
Manual worker 12 10 10 33.3
Self-employed 43 35.8 35.8 69.2
Retired 34 28.3 28.3 97.5
Other 3 2.5 2.5 100
Mother’s job
Housewife 105 87.5 87.5 87.5
Employee 12 10 10 97.5
Self-employed 3 2.5 2.5 100
Total 120 100
Mean SD The least The most
Age 68.23 3.57 19 43
Table 1. Continued
Table 2. Descriptive indicators of different dimensions of the examined
questionnaire
Dimensions Mean Middle
Standard
Deviation
The
least
The
most
Perceived sensitivity 10.917 12 4.477 0 16
Perceived intensity 12.717 13 5.552 0 24
Perceived barriers 14.917 15/5 6.165 0 24
Perceived benefits 18.542 21 7.558 0 28
Action guide 18.100 17 5.073 11 33
Efficacy 17.213 18 3.524 6 28
Prevention behaviors 6.892 6/5 2.875 1 13
Geravandi et al
184 Arch Hyg Sci. Volume 12, Number 4, 2023
that the entire sample population of their study lived in
the dormitory [26].
Another study conducted among 130 students of
Yazd University of Medical Sciences indicated that
the prevalence of drug use among students who lived
with their families is lower, and the students’ perceived
sensitivity, threat perceived barriers, and perceived
benefits to drug use were greater among students in this
study [27]. However, the study by Khazaee-Pool et al in
Nowshahr, which investigated the effect of an educational
intervention based on the health belief model in a sample
of male students with an average age of 17, demonstrated
that more than half of the students in the intervention
group have a history of smoking [28].
In our study, the variables of gender, marital status,
having a job, academic term, probation history, and
sports activity status had no significant relationship
with the dimensions of the health belief model, but
Table 3. Regression analysis of overestimation of prevention behaviors in the health belief model
Prevention behaviors Coefficients Standard deviation Standard coefficients t-statistic P value R-square
Constant 2.646 1.048 0.138 2.525 0.013
0. 413a
Perceived sensitivity -0.020 0.070 -0.032 -0.289 0.773
Perceived intensity -0.021 0.059 -0.040 -0.352 0.726
Perceived barriers 0.168 0.054 0.158 3.111 0.038
Perceived benefits 0.004 0.049 0.010 0.080 0.936
Action guide 0.235 0.051 0.415 4.609 < 0.001
Figure 2. (a-d). Regression analysis test to consider the relationship between perceived susceptibility and prevention behaviors (fig 2a); the relationship
between perceived severity and prevention behaviors (fig 2b); the relationship between perceived barriers and prevention behaviors (fig 2c); the relationship
between perceived benefits and prevention behaviors (fig 2d).
Arch Hyg Sci. Volume 12, Number 4, 2023 185
Variables on smoking prevention behaviors
the Kruskal-Wallis test showed that the dimension of
perceived benefits has a significant relationship with
parents’ education (P value = 0.026, P value = 0.013).
Furthermore, the results suggested that the dimension
of perceived benefits is the highest in people with a
father’s education level of diploma and post-diploma. In
addition, the results revealed that the perceived benefits
are the highest in people with a mother’s education level
of post-graduate and bachelor’s degrees. This result is in
line with the results obtained from previous studies in
this field. Masodi et al in their study found a direct and
significant relationship between the students’ knowledge
score regarding the factors related to the prevention of
drug addiction and the education of their parents [29].
5. Conclusion
According to the results of this study, the dimension of
perceived benefits had a significant and direct relationship
with the education of students’ parents. These results
showed how much students will be influenced by their
parents’ knowledge and attitude. Therefore, it is possible
to have a positive effect on students’ prevention of
smoking by properly educating students’ parents.
In the present study, the results of the data analysis
showed that the lower the number of existing obstacles,
the higher the probability of preventive behaviors. Based
on the results of this study, paying attention to the
written recommendations in the educational package can
increase the probability of students’ understanding of
the prevention of smoking. Therefore, using the results
obtained in the present study can be extremely helpful
for education and intervention in the field of health
behaviors related to smoking among young people to
reduce the current problems.
Acknowledgments
This work was part of a funded M.S thesis by Simin Geravandi, a
student at Ahvaz Jundishapur University of Medical Sciences, and
the financial support of this study (SDH-0102) was provided by the
Social Determinants of Health Research Center.
Authors’ Contribution
Conceptualization: Simin Geravandi, Mohammad Javad
Mohammadi, Nasser Hatamzadeh.
Data curation: Simin Geravandi, Saeed Ghanbari.
Formal analysis: Akbar Babaei Heydarabadi, Saeed Ghanbari,
Nasser Hatamzadeh.
Funding acquisition: Nasser Hatamzadeh.
Investigation: Simin Geravandi, Mohammad Javad Mohammadi,
Nasser Hatamzadeh.
Methodology: Simin Geravandi, Akbar Babaei Heydarabadi, Saeed
Ghanbari, Nasser Hatamzadeh.
Project administration: Mohammad Javad Mohammadi, Akbar
Babaei Heydarabadi, Nasser Hatamzadeh.
Resources: Simin Geravandi, Mohammad Javad Mohammadi,
Nasser Hatamzadeh.
Software: Saeed Ghanbari.
Supervision: Nasser Hatamzadeh.
Validation: Simin Geravandi, Akbar Babaei Heydarabadi, Saeed
Ghanbari, Nasser Hatamzadeh.
Visualization: Simin Geravandi, Mohammad Javad Mohammadi,
Nasser Hatamzadeh.
Writing–original draft: Simin Geravandi, Mohammad Javad
Mohammadi, Akbar Babaei Heydarabadi, Saeed Ghanbari, Nasser
Hatamzadeh.
Writing–review & editing: Simin Geravandi, Mohammad Javad
Mohammadi, Akbar Babaei Heydarabadi, Saeed Ghanbari, Nasser
Hatamzadeh.
Competing Interests
The authors declare no competing interests.
Consent for Publication
Not applicable.
Data Availability Statement
The datasets generated and/or analyzed during the current study are
available from the corresponding author upon reasonable request.
Ethical Approval
The Ethics Committee of Ahvaz Jundishapur University of Medical
Sciences approved the study protocol. This study was originally
approved by the Ahvaz Jundishapur University of Medical Sciences
with code IR.AJUMS.REC.1401.067.
Funding
This work was part of a fund at the Ahvaz Jundishapur University of
Medical Sciences (AJUMS), and the financial support of this study
(IR.AJUMS.REC.1401.067) was provided by AJUMS.
References
1. Fukai M, Kim S, Yun YH. Depression and suicidal ideation:
association of physical, mental, social, and spiritual health
status. Qual Life Res. 2020;29(10):2807-14. doi: 10.1007/
s11136-020-02538-x.
2. GBD 2019 Tobacco Collaborators. Spatial, temporal, and
demographic patterns in prevalence of smoking tobacco use
and attributable disease burden in 204 countries and territories,
1990-2019: a systematic analysis from the Global Burden of
Disease Study 2019. Lancet. 2021;397(10292):2337-60. doi:
10.1016/s0140-6736(21)01169-7.
3. Abbasi M, Dargahi S, Bagiyan Koole Marz MJ, Bakhti M,
Dargahi A. Examining the role of difficulty in emotional
self-regulation, impulsiveness and defensive mechanisms in
discriminate smokers and non-smokers students. Arch Hyg
Sci. 2014;3(2):59-69.
4. Arabshahi A, Mohebi S, Gharlipour Z. Perspectives and
reasons for smoking tendency in youth. Arch Hyg Sci.
2021;20(3):189-200. doi: 10.32598/ahs.10.3.189.
5. World Health Organization (WHO). WHO Report on the
Global Tobacco Epidemic, 2021: Addressing New and
Emerging Products. WHO; 2021. Available from: https://
www.who.int/publications/i/item/9789240032095.
6. Singh T, Arrazola RA, Corey CG, Husten CG, Neff LJ, Homa
DM, et al. Tobacco use among middle and high school
students--United States, 2011-2015. MMWR Morb Mortal
Wkly Rep. 2016;65(14):361-7. doi: 10.15585/mmwr.
mm6514a1.
7. Sharifirad G, Hazavei MM, Hasanzadeh A, Daneshamouz A.
The effect of health education based on health belief model
on preventive actions of smoking in grade one, middle school
students. J Arak Univ Med Sci. 2007;10(1):79-86. [Persian].
8. Finkelstein E, Baid D, Almudarra S, Alqunaibet A, Msemburi
W, Watkins D, et al. Calculating the economic burden of
NCDs in Saudi Arabia: an application of three common
Geravandi et al
186 Arch Hyg Sci. Volume 12, Number 4, 2023
approaches. In: Noncommunicable Diseases in Saudi Arabia:
Toward Effective Interventions for Prevention. World Bank
Publications; 2021. p. 65-77. doi: 10.1596/978-1-4648-
1717-5_ch4.
9. Fan Z, Gong X, Xu H, Wang H, Zeng N, Li L, et al. Gender
differences in the associations between tobacco smoke
exposure and depressive symptoms among US adults:
NHANES 2007-2018. J Psychiatr Res. 2022;146:249-57. doi:
10.1016/j.jpsychires.2021.11.013.
10. Meysamie A, Ghaletaki R, Zhand N, Abbasi M. Cigarette
smoking in Iran. Iran J Public Health. 2012;41(2):1-14.
11. Reitsma MB, Flor LS, Mullany EC, Gupta V, Hay SI, Gakidou
E. Spatial, temporal, and demographic patterns in prevalence
of smoking tobacco use and initiation among young
people in 204 countries and territories, 1990-2019. Lancet
Public Health. 2021;6(7):e472-81. doi: 10.1016/s2468-
2667(21)00102-x.
12. Rosen LJ, Lev E, Guttman N, Tillinger E, Rosenblat S,
Zucker DM, et al. Parental perceptions and misconceptions
of child tobacco smoke exposure. Nicotine Tob Res.
2018;20(11):1369-77. doi: 10.1093/ntr/ntx169.
13. Cho H, Lee K, Hwang Y, Richardson P, Bratset H, Teeters
E, et al. Outdoor tobacco smoke exposure at the perimeter
of a tobacco-free university. J Air Waste Manag Assoc.
2014;64(8):863-6. doi: 10.1080/10962247.2014.896295.
14. Smith JC, Sausville EL, Girish V, Yuan ML, Vasudevan A,
John KM, et al. Cigarette smoke exposure and inflammatory
signaling increase the expression of the SARS-CoV-2 receptor
ACE2 in the respiratory tract. Dev Cell. 2020;53(5):514-29.
e3. doi: 10.1016/j.devcel.2020.05.012.
15. Lo Sasso G, Schlage WK, Boué S, Veljkovic E, Peitsch MC,
Hoeng J. The Apoe(-/-) mouse model: a suitable model to
study cardiovascular and respiratory diseases in the context of
cigarette smoke exposure and harm reduction. J Transl Med.
2016;14(1):146. doi: 10.1186/s12967-016-0901-1.
16. Altamirano J, Bataller R. Cigarette smoking and chronic
liver diseases. Gut. 2010;59(9):1159-62. doi: 10.1136/
gut.2008.162453.
17. Lee HW, Park SH, Weng MW, Wang HT, Huang WC, Lepor
H, et al. E-cigarette smoke damages DNA and reduces repair
activity in mouse lung, heart, and bladder as well as in
human lung and bladder cells. Proc Natl Acad Sci U S A.
2018;115(7):E1560-9. doi: 10.1073/pnas.1718185115.
18. Brinn MP, Carson KV, Esterman AJ, Chang AB, Smith BJ.
Cochrane review: mass media interventions for preventing
smoking in young people. Evid Based Child Health.
2012;7(1):86-144. doi: 10.1002/ebch.1808.
19. Olsson T, Barcellos LF, Alfredsson L. Interactions between
genetic, lifestyle and environmental risk factors for multiple
sclerosis. Nat Rev Neurol. 2017;13(1):25-36. doi: 10.1038/
nrneurol.2016.187.
20. Goudarzi G, Geravandi S, Foruozandeh H, Babaei AA, Alavi
N, Vosoughi Niri M, et al. Cardiovascular and respiratory
mortality attributed to ground-level ozone in Ahvaz, Iran.
Environ Monit Assess. 2015;187(8):487. doi: 10.1007/
s10661-015-4674-4.
21. Bagherian Marzouni M, Moradi M, Zarasvandi A, Akbaripoor
S, Hassanvand MS, Neisi A, et al. Health benefits of PM10
reduction in Iran. Int J Biometeorol. 2017;61(8):1389-401.
doi: 10.1007/s00484-017-1316-2.
22. Mohammadi K, Tavafian SS. Effect of educational intervention
based on health belief model on prevention of substance
abuse among the students of Khatam Al-Nabieen University
in Afghanistan. Iran Red Crescent Med J. 2020;22(5):e101935.
doi: 10.5812/ircmj.101935.
23. Fernandez DM, Larson JL, Zikmund-Fisher BJ. Associations
between health literacy and preventive health behaviors
among older adults: findings from the health and retirement
study. BMC Public Health. 2016;16:596. doi: 10.1186/
s12889-016-3267-7.
24. Ramezankhani A, Heidarnia A, Ghofrani Pour F. Effect of
Education Based on Health Belief Model on Khowlage and
Preventive Behavior of Cigarette Consumption [dissertation].
Tehran: Tarbiat Modares University; 2000.
25. Aryaie M, Sharifi H, Khorrami Z, Ardalan G, Rajaei L,
Heydari G, et al. Prevalence of cigarette smoking in Iranian
adolescents and young adults: a systematic review and metaanalysis.
East Mediterr Health J. 2021;27(6):612-28.
26. Panahi R, Ramezankhani A, Tavousi M, Osmani F, Niknami
S. Predictors of adoption of smoking preventive behaviors
among university students: application of health belief model.
J Educ Community Health. 2017;4(1):35-42. doi: 10.21859/
jech.4.1.35.
27. Baghianimoghadam MH, Mazloomy Mahmoodabad SS,
Mohammadi S, Baghianimoghadam B. Attitude towards and
use of ecstasy in medical university interns’ based on HBM. J
Prev Med Hyg. 2009;50(4):241-5.
28. Khazaee-Pool M, Zarei F, Pashaei T, Shojaeizadeh D. The
effect of an educational intervention based on health belief
model on improving smoking preventive behaviors among
students. Iran J Health Educ Health Promot. 2017;4(4):300-8.
doi: 10.18869/acadpub.ihepsaj.4.4.300. [Persian].
29. Masoudi Boroujeni D, Baghianimoghadam MH, Sharifirad
G, Fallahzadeh H. Evaluation of preventive behaviors of
addiction based on health belief model (HBM) among male
high school students in Boroujen, Iran. J Health Syst Res.
2012;8(2):237-46. [Persian].