High-Risk Behaviors Among Iranian University Students: A Web-Based Survey

doi:10.21203/rs.3.rs-100107/v1

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High-Risk Behaviors Among Iranian University Students: A Web-Based Survey

https://doi.org/10.21203/rs.3.rs-100107/v1

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published 09 Dec, 2020

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Background :High-risk behaviors is one of the most serious factors threatening the physical and mental health of adolescents and young adults. The aims of this study were to investigate thesubgroups of students based on risky behaviors and to identify the prevalence rate of these subgroups.

Methods: This cross-sectional web-based survey was conducted from July to August 2019 in Tabriz, Iran. Sampling of all universities in the city was performed proportionally according to the number of students in each university. . Applying an online survey questionnaire, the data were collected from 3649 students and included into Latent Class Analysis.

Results: For both genders, standardized prevalence rates of cigarrette smoking, hookah use, alcohol consumption, substance abuse and unsafe sex were 18.5 (CI 95%: 17.3-19.8), 9.1 (CI 95%: 8.2-10.1), 9.2 (CI 95%: 8.3-10.2), 8.3 (CI 95%: 7.4-9.3) and 14.5 (CI 95%: 13.3-15.7), respectively. Three latent classes of risky behaviors were determined among students: 1) low risk 2) smoking and 3) high risk. About 18% of boys and 1.5% of girls were in the high risk class. Cigarrette smoking (18.5%, CI 95%: 17.3-19.8) and substance abuse (8.3%, CI 95%: 7.4-9.3) were the most and the least common risky behaviors among the students.

Conclusion: In this we-based survey, a considerable percentage of students, particularly boys, were at high-risk class, stressing the need for preventive interventions for this group of youth. Our findings are beneficial for planning and development of risky-behavior preventive measures to prevent high-risk behaviors among college students.

Health Economics & Outcomes Research

Health Policy

Web-based survey

Latent class analysis

Risky behaviors

Students

Performing risky behaviors, individualsexpose themselves potentially to significant risk of harm [1]. High-risk behaviors are associated with an increased risk of chronic diseases, premature mortality and disability, and have a negative impact on the physical and mental health of individuals [2]. Risky behaviors are also one of the most serious risk factors for adolescent and young people's physical and mental health. Tobacco use, alcohol consumption, high-risk sexual behaviors, and drug abuse are among the most risky behaviors that increase the likelihood of harmful physical, psychological and social consequences for individuals [3]. Drug use, alcohol consumption and risky sexual behaviors account for 2%, 7%, and 4% of disability-adjusted life years (DALY), respectively, among individuals aged 15 to 24 years [4]. Considering their negative consequences, high-risk behaviors are among the most important areas of research in youth studies.

The prevalence of some risky behaviors is reported to be high among university students who constitue a large part of young population [5, 6]. Among Asian countries, high-risk behaviors are prevalent in Thailand, Saudi Arabia, and the Middle East [7–9]. The high prevalence of such behaviors among Iranian students has also been reported. For example, a study conducted in 2017 among Iranian university students showed that 13.5% of the students smoked cigarette, 7.8% drank alcohol, 4.9% had drug abuse and 7.8% had unprotected sex [10].

Analyzing youth subgroups in terms of risky behaviors may provide health care providers and policy makers with the opportunity to identify those who share the same characteristics based on high-risk behaviors [11]. It seems also pivotal while designing traffic injury prevention strategies for youth. For instance, individuls who are solely involved in drug abuse may have charachteristics the differed from those involved in other high-risk behaviors. In the Iranian studies that clustering method was used to investigate high-risk behaviors among students,different subgroups of students for high-risk behaviors are concluded. In a study conducted in Tabriz, Iran, three subgroups were identified for risky behaviors; (a) low-risk (b) cigarette and hookah smoker, and (c) high-risk. According to this study, 3.7% of boys and 0.4% of girls were in the high risk group [12]. In another study conducted in Iran four subgroups of high-risk behaviors among students were identified; 1. low-risk, 2. smoking cigarette and hookah, 3. risky sexual behavior (in girls), risky sexual behavior and alcohol consumption (in boys), and 4. high-risk. According to the study, 13.3% of boys and 4.3% of girls had high-risk behaviors [13]. Another study conducted in Bushehr showed five subgroups of risky behaviors among students: low-risk, high-risk, somewhat low-risk, hookah consumption, and very high-risk. It is noteworthy that 7.7% and 2.5% of students had high-risk and very high-risk behaviors, respectively [14].

Evidence suggests that compared to the traditional paper-based studies, in the studies where online or web-based questionnaires were used to collect data, respondents were more honest in answering to sensitive questions like having sex or using drugs, due to anonymity [15–20]. All previous studies conducted in Iran to examine high-risk behaviors among students have used a written questionnaire to collect data. As mentioned, in this method of data collection, there is the possibility for the respondents to answer the sensitive questions incorrectly. Therefore, considering this issue and also considering the high prevalence of high-risk behaviors among Iranian students [10, 21–23], this web-based study was conducted to identify subgroups of students based on risky behaviors, and determine the prevalence of these subgroups among a representative sample of students in Tabriz, Iran.

This web-based cross-sectional study was conducted in Tabriz from July to August, 2019. There are 9 universities in Tabriz. Sampling was performed from all the universities proportionally to the number of students in each university. In total, 3788 students completed the online questionnaire, of which 139 cases were incomplete. Finally, the data collected from 3649 students were analyzed.

In this study, a questionnaire was developed to evaluate high-risk behaviors among the students. All items were designed according to the scientific literature and using the opinions of experts, which had previously been used in other studies. To assess validity, thequestionnaire was presented to five experts in substance abuse, six experts in methodology and instrumentation, and five knowledgeable students, along with a response form for the quantitative comments on the relevancy and transparency of the questionnaire. To asses reliability, a pilot studywas conducted on 30 students. After receiving the responses and revising the questionnaire, the final questionnaire was designed in the Google form.

All students were invited to participate in the study, and a short link to the questionnaire was provided to them to complete the questionnaire online.Telegram and Instagram applications were also used to get more students involved in the study.The administrators and representatives of the channels and groups of the students in Tabriz universities were identified and all were asked to place the questionnaire link in the channel or group so that the students can enter into the link and complete the questionnaire, in the case being consent to participate in the study. Participation was voluntary, and the participants' anonymity was ensured. To maintain the sampling portion in the universities, the number of study participants from each university was monitored as the questionnaires were completed. In the case of fulfilling the predetermined number of participants from a given university, the researchers then terminanted sampling from that university and focused on the universities with insufficient sample size.

To assess risky behaviors among students, five questions with dichotomous response format were developed. These questions were: 1) cigarette smoking “Have you currently smoked?”, 2) smoking Hookah “Have you currently used hookah (At least once a week)?” 3) alcohol consumption “Have you consumed alcohol in the last 30 days?” 4) Substance abuse “Have you ever experienced substance abuse?” and 5) Unsafe sex. Unsafe sex was assessed applying three separate questions; In the case of having sexual relationship, have you consumpted alcohol or medication prior/while sexual intercourse?? Do you have sexual intercourse with multiple partners? and Do you regularly use condom while sexual intercourse?. Respondents who answer "yes" to at least one of the three questions were classified as having unsafe sex.

Latent class Analysis (LCA) with gender as a group variable was used to analyze data. To perform LCA, the 5 dichotomous variables were used to assess risk-taking behaviors among students, as a latent variable. To perform LCA, the models with 1 to 7 classes were considered and for each model Akaike information criterion (AIC) and Bayesian information criterion (BIC) were calculated. For all information criteria, a smaller value represented a more optimal balance of model fit and parsimony; thus, a model with the minimum AIC or BIC was selected. All analyses were performed using proc-LCA in SAS software version 9.2 (SAS Institute Inc., Cary, NC, USA). Because of the difference between the number of girls and boys and the frequency of risk-taking behaviors between the two genders, we used direct standardization method to calculate the risk-taking behaviors for all the sample.

The age range of participants was 18–37 years (Mean (standard devisation): 22.8 (3.7)). More that half of the students were male (55.7%) and only 10.0% were married. The frequency of risk-taking behaviors is shown in Table 1. As our results showed, the frequency of smoking and having unsafe sex were highercompared to other risky behaviors. Also, risk-taking behaviors were more prevalent among males than females.

Table 1

Frequency of Students Responding “Yes” to Questions about Risk-Taking Behaviors.
Items	Male (N = 2034)		Female (N = 1615)		Total (Standardized prevalence for sex)
	n	% (CI 95%)	n	% (CI 95%)	% (CI 95%)
Smoking	734	36.4 (34.3–38.5)	121	7.6 (6.4–8.9)	18.5 (17.3–19.8)
Hookah use	359	17.7 (16.1–19.4)	62	3.9 (3.0-4.9)	9.1 (8.2–10.1)
Alcohol use	337	16.7 (15.1–18.4)	75	4.7 (3.7–5.8)	9.2 (8.3–10.2)
Substance abuse	299	15.3 (13.8–17.0)	65	4.1 (3.2–5.2)	8.3 (7.4–9.3)
Sexual risk behavior	408	20.5 (18.7–22.3)	168	10.7 (9.3–12.4)	14.5 (13.3–15.7)
Note. CI = Confidence Interval

Based on the five dichotomous variables, there were 32 possible response patterns. The comparision of LCA models with different latent classes is presented in Table 2. We found that the three latent classes model was appropriate for both males and females, based on the model selection indices and interpretability of the models results.

Table 2

Comparison of LCA Models with Different Latent Classes Based on Model Selection Statistics.
Number of latent Classes	Number of parameters estimated	G²	df	AIC	BIC	Maximum log-likelihood
1 2 3 4 5 6 7	5 11 17 23 29 35 41	1806.28 124.29 48.75 25.70 13.34 6.81 6.86	53 41 29 17 5 - -	1826.28 168.29 116.75 117.70 129.34 146.81 170.86	1888.28 304.71 327.58 402.94 488.98 580.87 679.32	-6824.14 -5983.15 -5945.38 -5933.86 -5927.67 -5924.41 -5924.43
Note. LCA = latent class analysis; AIC = Akaike Information Criterion; BIC = Bayesian Information Criterion.

The results of three classes LCA models are presented in Tables 3 and 4 for both male and female students, respectively. As shown in these tables, nearly 59% and 18% of male students were in low risk and high risk for having risk-taking behaviors, respectively. Among females about 88% were at low risk and 1.5% were at high risk for performing risk-taking behaviors. Also, about 23% of male students and 10.6% of female students were in the cigarette smoker class.

Table 3

The three latent classes model of risk-taking behaviors among male students.
		Latent class
	Low risk	Cigarette smoker	High risk
Latent class prevalence	58.9	23.2	17.9
Item-response probabilities	Probability of a “Yes” response
Smoking	0.000	0.934^*	0.818
Hookah use	0.054	0.236	0.507
Alcohol use	0.022	0.140	0.676
Substance abuse	0.021	0.204	0.543
Sexual risk behavior	0.110	0.107	0.638
Note. The probability of a “No” response can be calculated by subtracting the item-response probabilities shown above from 1.
^*Item-response probabilities > 0.5 in bold to facilitate interpretation.

Table 4

The three latent classes model of risk-taking behaviors among female students.
		Latent class
	Low risk	Cigarette smoker	High risk
Latent class prevalence	87.9	10.6	1.5
Item-response probabilities	Probability of a “Yes” response
Smoking	0.008	0.523^*	0.895
Hookah use	0.006	0.240	0.556
Alcohol use	0.010	0.214	0.999
Substance abuse	0.000	0.296	0.743
Sexual risk behavior	0.073	0.264	1.000
Note. The probability of a “No” response can be calculated by subtracting the item-response probabilities shown above from 1.
^*Item-response probabilities > 0.5 in bold to facilitate interpretation.

Our aim in this web-based study was to identify subgroups of students based on risky behaviors, and determine the prevalence of these subgroups among a representative sample of students in Tabriz, Iran. Our results showed that the frequency of smoking, hookah use, alcohol use, substance abuse, and having unsafe sex, as the risky behaviors, were 18.5%, 9.1%, 9.2%, 8.3% and 14.5%, respectively. The results of a previously published meta-analysis also showed the prevalence rate of high-risk sexual behaviors among Ethiopian students to be 42%, approximately [24]. In a study among American students, the prevalence rates of alcohol consumption, cigarette and hookah smoking were 44%, 31% and 22%, respectively [25]. Another study on Canadian students revealed that 55% of students smoked cigarette, 62% consumed alcohol, 36% had drug abuse, and 28% had high-risk sexual intercourse [26]. The reason for the low prevalence of high-risk behaviors among Iranian students compared to other countries may be due to cultural-religious beliefs in Iran, as well as the religious prohibition of alcohol consumption and the legal prohibition of alcohol and drug abuse.

The results of a study among students in Khorramabad, Iran, showed that the prevalence rates of smoking cigarette, drug abuse, and alcohol consumption were 3.7%, 2.4%, and 5.5%, respectively [27]. Another study conducted on Tehran University students showed that the prevalence rates of alcohol, drug abuse, and high-risk sexual behaviors were 4.6%, 2.3%, and 5.6%, respectively [28]. Another study on the prevalence of high-risk behaviors among students in Rudan, Iran, demonstrated that the prevalence rates of drug use, alcohol consumption, and high-risk sexual behaviors were 5.5%, 4.9%, and 6.6%, respectively [29]. Another study conducted in 2011 in Tabriz, Iran, showed that the prevalence rates of smoking cigarette, smoking hookah, alcohol consumption, drug abuse, and high-risk sexual intercourse were 15.8%, 8.5%, 8%, 7.6%, and 10.8%, respectively [13]. As evident, all these studies reported lower levels of risk-taking behaviors compared to our findings in the present study, which may be attributed to the use of online questionnaire in the present study, as evidences suggest that the quality of responses in sensitive issues to online questionnaires is better than that of paper questionnaires [15–20].

Overall, the results of this study showed that smoking cigarette (18.5%, boys: 36.4% and girls: 7.6%) and drug abuse (8.3%, boys: 15.3% and girls: 4.1%) were the most and the least common risky behaviors among Iranian college students, respectively. Our results also showed that boys had more risky behaviors than girls. These findings were in line with those of other studies conducted on Iranian students [29–31]. The low prevalence of risky behaviors among Iranian female students compared to male students can be due to different cultural and social expectations and greater freedom of boys which may facilitate the inclination of boys towards risky behaviors [32, 33].

A useful preventive approach is to pay attention to the concurrency of high-risk behaviors, Various studies have shown that engagement in one high-risk behavior is associated with engagement in other high-risk behaviors [34]. Numerous studies have shown the concurrency of cigarette smoking and hookah smoking [35], smoking and alcohol consumption [36], cigarette smoking and drug abuse [37], and high-risk sexual behaviors and alcohol and drug abuse [38]. The present study showed that the students of both genders had three subgroups in terms of risk taking behaviors including low-risk, smoking cigarette and high-risk, with the prevalence rates of 58.9%, 23.2% and 17.9% in boys and 87.9%, 10.6% and 1.5% in girls, respectively.

In the previous studies that used the clustering method to investigate high-risk behaviors among students, different subgroups of students in terms of high-risk behaviors were identified. A study in Tabriz showed three subgroups or classes of risky behaviors among students: 1. low-risk 2. smoking cigarette and hookah 3. high-risk [12]. According to this study, 3.7% of boys and 0.4% of girls were in the high-risk class. As mentioned above, another reason could be attributed to the quality of responses due to online questionnaires in the present study. In the study conducted by Safiri et al (12), high-risk behaviors were less prevalent among girls than boys, which is in line with the findings of our study. Another study conducted in Tabriz in 2011, four subgroups of high-risk behaviors among students were identified: 1. low-risk 2. smoking cigarette and hookah 3. risky sexual behavior in girls and risky sexual behavior and alcohol consumption in boys, and 4. high-risk. According to this study, 13.3% of boys and 4.3% of girls had high-risk behaviors [13].

Studies applying the LCA method to investigate the concurrency of high-risk behaviors among students in different societies have different patterns of behavior among university students. For instance, a study on the US students involved in tobacco use, drug abuse, and alcohol consumption showed five latent classes for the behaviors [25]. According to this study, being a boy increased the chance of placement in high-risk class. Additionally,, 61.8% of the students were in non/low user class and 5.6% were in poly-substance user class. Another similar study in Canada identified three latent classes of the behavior: 1. normal, 2. relatively healthy, and 3. high-risk. The prevalence rates of these classes were 65.7%, 14.5% and 19.8%, respectively [26]. Similarly, Chiauzzi et al., in the US found the following four classes for the behaviors: 1. low-risk alcohol consumption/low prevalence of drug abuse, 2. lower alcohol consumption/moderate prevalence of drug abuse, 3. moderate-risk alcohol consumption/moderate prevalence of drug abuse, and 4. high-risk alcohol consumption/high prevalence of drug abuse. The prevalence rates of these classes were 46.0%, 20.2%, 13.6% and 20.2%, respectively [39]. The high prevalence rates of high-risk classes in these studies compared to our study may be due to geographical and cultural differences and the type of norms.

There were several limitations in the present study. First, although we believe that the students provided us with a more honest answers, compared to paper-based surveys, our results were still based on the self-report of the participants. According to previous research, the studies in which online questionnaires are used for data collection have usually a problem with low response rate [40, 41], and this may come true for our study, yet we do not know how much was the number of students who viewed the questionnaire link but did not answer to the questions. Thus, we cannot determine the response rate. Another limitation of our web-based study is participation bias, which may distort the results [42], because certain people with internet access may have a social network account and wish to participate in the study.

In this we-based survey, three subgroups of risky behaviors were identified among students for both genders. There were also a considerable percentage of students, particularly boys, at high-risk class, stressing the need for preventive interventions for this group of youth. Our findings are beneficial for planning and development of risky-behavior preventive measures to prevent high-risk behaviors among college students.

LCA: Latent class Analysis

AIC: Akaike information criterion

BIC: Bayesian information criterion

Ethics approval and consent to participate

Ethical approval was obtained from the Ethics Committee in Tabriz University of Medical Sciences (Ethical code:IR.TBZMED.REC.1398.190).

Consent for publication

Not applicable.

Availability of data and material

Please contact the corresponding author for data requests.

Competing interests

The authors declare that they have no competing interests.

Funding

This study was supported by Tabriz University of Medical Sciences.

Authors' contributions

Study design: All authors. Study conduct: FS, PH, and AM. Data collection: FS, PH. Data analysis: AM and FS. Data interpretation: All authors. Drafting manuscript: AM, FS, and PH. Revising manuscript and content: HN and AM. Approving final version of manuscript: All authors. AM takes responsibility for the integrity of the data analysis.

Acknowledgements

The authors would like to greatly acknowledge financial support for this study from Tabriz University of Medical Sciences. The authors also wish to thank all the participants of this study for their valuable cooperation and participation.

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High-Risk Behaviors Among Iranian University Students: A Web-Based Survey

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