Background: Adolescents and youths are known to be an adventurous group, and often engage in risky behaviors such as smoking, drinking alcohol, using drugs, and early unprotected sexual activity. University students are viewed as being at higher risks to acquire STI or HIV infection and they are categorized under the most at risk population segments due to their inclination to be engaged in risky sexual behavior. Methods: Institutional based descriptive cross-sectional study design was conducted from May 2018 to June 2018 among Jigjiga University students in Jigjiga, Ethiopia. A total of 403 study participants were included in the study. Pre-tested structured questionnaire was used for interviewing the study participants. The collected data was coded and entered in to EPI-INFO version 3.5.3 software and analyzed by using SPSS version 20. Binary logit econometric model was employed. The association between variables was analyzed using Bivariate and multivariate logistic regression and the level of significance of association was determined at P-value < 0.05. Results: A total of 403 (out of which 260 (65%) were male and 143(35%) female) university students participated in this study with 97% response rate. The result indicates that, age [AOR = 3.82, 95% CI, (2.28, 9.41)], active in my faith/religion [AOR = 3.68, 95% CI, (1.344, 10.115)], contraceptive use [AOR = 6.38, 95% CI (3.96, 10.27)], condom use [AOR = 6.38, 95% CI (3.96, 10.27)], peer pressure [AOR = 14.52, 95% CI (4.702, 44.891)], tobacco consumption[AOR = 3.191 95% CI (1.83, 5.54)] and alcohol use [1.64, 95% CI (1.39, 2.06)] were the commonest factors associated with risky sexual behavior. Conclusion: The study revealed that being too young in terms of age, not believing actively in faith/religion practice, lack of contraceptive method, not using condom, peer pressure, tobacco use and drinking alcohol were factors in the study that can lead youths to engage in risky sexual behaviors.
One of the most important commitments a country can make for future economic, social, and political progress and stability, therefore, is to address the sexual and reproductive health needs of this population group [
Adolescence and adulthood are critical target groups for sexual behavioral change programs. While sexual abstinence is the preferred method of HIV prevention among this group of people, it is not practical for many of individuals. Therefore, consistent and correct condom use is a reasonable method of preventing the transmission and acquiring HIV and other sexually transmitted infections [
Risky sexual behaviors are defined as behaviors which increase the chance of contracting or transmitting disease or increase the chance of occurrence of unwanted pregnancy. Those include having more than one sexual partner, changing sexual partners frequently, having sex without condom, not using contraceptive [
Most adults are educated about risky sexual behaviors. However, unsafe sexual practices are still occurring with sufficient frequency so that sexually transmitted diseases and unwanted pregnancy remain significant public health concerns. The WHO reported in 2009 that unsafe sex was second among the top ten first factors in the global burden of all diseases caused globally [
Studies have found that the highest group infected with HIV is the age group of 15 to 24 years where most of the university student’s fall and these findings point to a need for investigation of sexual behavior in universities as a matter of priority [
University/college students are viewed as being at higher risks to acquire STI or HIV infection and they are categorized under the most at risk population segments (MARPS) due to their inclination to be engaged in risky sexual behavior and their sense of non-vulnerability [
A number of studies have investigated the consequences of sexual behavior especially among university students. Further to these, there is sufficient knowledge of these consequences based on science and medicine. Sexually Transmitted Diseases (STDs), including human immuno-deficiency virus (HIV) infections, constitute a major reproductive health burden for sexually-active individuals. Consequences of STDs include genital and other cancers, pelvic inflammatory disease, ectopic pregnancy, infertility, and adverse outcomes of pregnancy including pre-term delivery and low birth weight [
Other known consequences of irresponsible sexual behavior include unwanted pregnancies, abortion, social stigma, dropping from schools etc., which often result into a serious damage to the victims’ self-esteem. This in turn negatively impacts on their opportunities for individual growth as well as the growth of their families [
The study done in Greece shows that a high rate of tobacco, alcohol, and drug consumption among youth is present [
There are three schools of thought regarding the role of self-esteem and its association with sexual behavior. One school suggests that there is a relationship between low self-esteem and engaging in high risk sexual behaviors (i.e. if one has low self-esteem, he/she is more likely to engage in high-risk sexual behaviors such as unprotected intercourse [
Study conducted in Delta State Nigeria, indicated that emotional intelligence, self-esteem, media and religiosity made a significantly contribution of about 43% to the prediction of adolescents’ risky sexual behavior [
The vision of ministry of education (MOE) is “ building an education and training system which assures quality and equality of education by the year 2020 that aims at producing competent citizens”, reducing risky sexual behavior and promoting condom utilization in university students is essential to achieve the mission and vision [
The present study would tend to contribute to fill the gap of determinants of risky sexual behavior in this university and would be used as an input to policy makers in achieving of mission and vision of Ministry of health, Ministry of Education and the country at all [
In recent years, studies have been conducted to identify the prevalence among students with risky sexual behavior. But, few cases of factors associated for risky sexual behavior are known. Therefore, this study was aimed to assess the factors associated with risky sexual behavior, which may support the intervention towards reducing risky sexual behavior among Jigjiga university students.
This Institutional based descriptive cross-sectional study design was conducted by 2018 at Jigjiga University. It is one of the 45th universities in Ethiopia that is located in Somali regional state. It was established in 1999 E.C. The university had five programmes namely; post graduates, regular, evening, weekend and summer. It had eleven colleges. Currently, the university enrolled more than 25,532 with 17,247 males and 8285 females.
Based on, the study of prevalence on risky sexual behaviors among Jigjiga University students; about 44.6% of the variation of risky sexual behavior among adolescents was accounted. The sample size was calculated by assuming the expected risky sexual behavior among, 44.6%, 95% confidence level, using a simple population formula:
n 2 = Z α 2 p ( 1 − p ) d 2
where;
n = is the minimum sample size required
Z = standard normal distribution (Z = 1.96) with confidence interval of 95% and α = 0.05
P = the expected risky sexual behavior among the students is 44.6%; hence, P = 44.6 % (0.44) was used, d = Absolute precision or tolerable margin of error (d) = 5% = 0.05
The following assumption will be made during determining the sample size
n = ( 1 . 96 ) 2 ( 0. 44 × 0. 56 ) / ( 0.0 5 ) 2 = 378
Then adding 10% (378 × 0.1 = 37.8) of non-respondent the total sample size for this study is 378 + 37 = 415.
Similarly, to attain the second objectives, the prevalence occupied 33.5% among students consuming alcohol [
n 2 = Z α 2 p ( 1 − p ) d 2
where;
n = is the minimum sample size required
Z = standard normal distribution (Z = 1.96) with confidence interval of 95% and α = 0.05
P = prevalence of sexual risky behavior among students consuming alcohol status hence, P = 33.5% was used [
d = Absolute precision or tolerable margin of error (d) = 5% = 0.05
The following assumption was made during determining the sample size
n = ( 1 . 96 ) 2 ( 0. 33 × 0 . 67 ) ( 0.0 5 ) 2 = 339 . 75
Then adding 5% (339.75 × 0.05 = 16.98 ≈ 17) of non-respondent the total sample size for the second objective is 340 + 17 = 357.
Finally, to get the maximum sample size we have done two formulas by taking two findings from previous research. Doing all this in order to account for missing values, the higher sample size (415) was chosen.
Among 40 departments by using simple random sampling the departments was selected. And then using sampling proportional to population size the number of study participants was allocated among selected departments. From this allocated students among department using sampling frame the study unit was selected using systematic random sampling method.
Data was collected by trained persons under the supportive supervision of the investigators.
Data was collected by the structured questionnaire with the participants during a data collection time. Additionally, base line clinical information was traced from the client’s record by using checklists/ data extraction format.
The instrument was adapted from the Youth Risky Behavior Questionnaire (YRBQ). The youth risk behavior surveillance system was developed by the centers for disease and prevention to monitor health risk behavior that contributes to the leading causes of mortality, morbidity and social problems among youth and adults in the United States. The youth risk behavior surveillance system monitors six categories of behaviours: those that contribute to unintentional injuries and violence; tobacco use; alcohol and other drug use; sexual behavior that contributes to unintended pregnancy and sexually transmitted diseases; dietary behavior; and physical activity. However, the section of the scale that related to risky sexual behavior was used. The Cronbach’s alpha value obtained was 0.81. An example of items on the scale is “In the last twelve months, I have had sex with multiple partners”. Religiosity was measured using the Santa Clara strength of religiosity faith questionnaire developed by [
Data entry was done using EPI-INFO version 3.5.3 and then exported into Statistical Package for the Social Sciences (SPSS) window version 20 for analysis. The survey data was analyzed using both descriptive statistic and econometrics analysis techniques to give empirical evidences for the basic research questions of this report and presents the results and findings of the research. Hence descriptive statistics such as percentage and frequency distribution were employed and binary logistic, econometric model was used to identify determinants of risky sexual behaviors among Jigjiga University students in Jigjiga Ethiopia, 2018. P-value less than 0.05 were considered as statistically significant. Bivariate and multivariate logistic regression analysis was conducted to identify associated factors of sexual risk behaviors with the students. The strength of the association was presented by odds ratio with 95% C.I.
This study was conducted only after formal approval of the protocol was obtained from the office of research at Jigjiga University. Prior to data Collection written informed consent was obtained from the participants through detail explanation of the study and the study procedures. The right was given to the study participants to refuse or discontinue participation at any time they want and the chance to ask any thing about the study. For the purpose of anonymity participant’s name was not be used at any time of data collection and all other personnel information kept entirely anonymous and confidentiality.
A total of 403 out of which 260 (65%) male and 143 (35%) female) university students participated in this study with 97% response rate. The minimum and maximum ages of the respondents were between 17 and 29 years old respectively. About 201 (49.9%) of the respondents were Muslims, 120 (30%) of them were orthodox Christians, 37 (9%) of them were catholic, 24 (6%) of them were protestant and 21 (5%) of them were from other faiths and many more was summarized in
Attachment to religion, attitude and peer pressure has significant effect on sexual risk behaviors of the individual. Forty four percent (44%) of the students
| Variables | Categories | Frequencies | Percent |
|---|---|---|---|
| Age | 0 - 18 | 46 | 11.41% |
| 19 - 21 | 198 | 49.14% | |
| 22 - 25 | 148 | 36.72% | |
| 26 - 30 | 11 | 2.73% | |
| Sex | Male | 260 | 64.52% |
| Female | 143 | 35.48% | |
| Religion | Muslim | 201 | 49.9% |
| Orthodox | 120 | 30% | |
| Catholic | 37 | 9% | |
| Protestant | 24 | 6% | |
| others | 21 | 5% | |
| Ethnicity | Somali | 125 | 31.02% |
| Amhara | 133 | 33.00 | |
| Oromo | 45 | 11.17% | |
| Gurage | 72 | 17.87% | |
| others | 28 | 6.95% | |
| Class in year | I | 29 | 7% |
| II | 104 | 15% | |
| III | 169 | 52% | |
| IV | 17 | 6% | |
| V | 84 | 20% |
engaged in sexual risk behaviors consider themselves attached to their religion. Regarding Attitude and Peer pressure towards sexual risk behaviors, students have varied with the highest percentages having good attitude but also impact of peer pressure. Students who were engaged in risk sexual behaviors were also those reported the use of different substances including tobacco, alcoholic and khat which imply the existence of relationship between uses of substances and being in risk sexual behaviors. Regarding the interpretation of the above descriptive statistics, From among 403 respondents 61.54% reported that they had used tobacco, 46.89% used alcohol and 51.36% used khat from those engaged in sexual risk behavior. The Tobacco was the most used type of substance (61%) in the university and many more was summarized in
Most of the respondents had history of multiple sexual partners at the age between 19 to 21 years. Regarding the use of contraceptives and use, students who are age between 19 to 21 years reported that they used more contraceptives and condom than other age groups. The age at which respondent had their last sexual intercourse varied with the highest percentages being between 19 to 21 years who engaged in risk sexual behavior. The prevalence of multiple sex partners over the last 12 months among the age between 19 to 21 years was higher than other age groups. So in general we can conclude from under mentioned table that the most crucial age for the students engaged in sexual risk behavior was between 19 to 21 years (hot age)
In the preceding parts of this paper the descriptive analysis and univariate analysis of important explanatory variables, which are expected to have impact on sexual risk behaviors of Students were presented. In this section, selected explanatory variables were used to estimate the logistic regression model to analyze the determinants of Students sexual risk behaviors. A logit model was fitted to estimate the effects of the hypothesized explanatory variables on the probabilities of being in risky sexual behaviors or not. SPSS 20 was used for the econometrics analysis. Prior to the estimation of the model parameters, it is crucial to look into the problem of multi-co linearity or association among the potential candidate variables. To this end, the contingency coefficient was used to test the degree of multi-co linearity among the variables.
The various goodness of-fit measures validate that the model fits the data well. The likelihood ratio test statistics exceeds the Chi-square critical value with 14 degree of freedom at less than 1% level of significance, indicating that the hypothesis that all coefficients except the intercept are equal to zero is rejected. The value of Pearson Chi-square test shows the overall goodness of-fit of the model at less than 1% probability level and many more was summarized in
Five selected socio-demographic independent variables that are hypothesized to have influence on sexual risk behaviors in the study area were included in the model, of which four were found to be statistically significant even though the level of statistical significance for the independent variables included in the
| Variables | Categories | Frequencies | Percent |
|---|---|---|---|
| Active in my faith/religion | Strongly Agree | 181 | 44.91% |
| Agree | 134 | 33.25% | |
| Disagree | 58 | 14.39% | |
| Strongly Disagree | 30 | 7.44% | |
| Attitude | Good | 208 | 51.61% |
| Not Good | 195 | 48.39% | |
| Peer pressure | Yes | 203 | 50.37% |
| No | 200 | 49.63% | |
| Contraceptive use | Yes | 211 | 47.64% |
| No | 192 | 52.36% | |
| Condom use | Yes | 211 | 47.64% |
| No | 192 | 52.36% | |
| Unwanted pregnancy | Yes | 240 | 59.55% |
| No | 163 | 40.45% | |
| Had sex last time | ≤one month | 107 | 26.55% |
| 1 to 3 months | 203 | 50.37% | |
| ≥3 months | 93 | 23.08% | |
| Sex partners in the past 12 months | One | 129 | 32.01% |
| Two | 66 | 16.38% | |
| Three | 48 | 11.91% | |
| Four | 80 | 19.85% | |
| ≥five | 80 | 19.85% | |
| Sex Partner Age | 0 - 19 | 96 | 23.82% |
| 20 - 30 | 191 | 47.39% | |
| 31 - 40 | 94 | 23.33% | |
| above 40 | 22 | 5.46% | |
| Tobacco | Yes | 248 | 61.54% |
| No | 155 | 38.46% | |
| Alcohol | Yes | 189 | 46.89% |
| No | 214 | 53.11% | |
| khat | Yes | 207 | 51.36% |
| No | 196 | 48.64% |
| Age | |||||
|---|---|---|---|---|---|
| 15 - 18 | 19 - 21 | 22 - 25 | 26 - 30 | ||
| Do you use any contraceptive | Yes | 28 | 90 | 88 | 5 |
| No | 18 | 108 | 60 | 6 | |
| Do you use condom with your partner? | Yes | 22 | 109 | 76 | 4 |
| No | 24 | 89 | 72 | 7 | |
| Do you experience any unwanted pregnancy? | Yes | 34 | 147 | 99 | 8 |
| No | 12 | 51 | 49 | 3 | |
| When is the last time you had sex? | ≤one month | 21 | 102 | 74 | 6 |
| 1 to3 months | 16 | 48 | 41 | 2 | |
| ≥three months | 9 | 48 | 33 | 3 | |
| How many sex partners do you have in the past 12 months? | One | 20 | 101 | 73 | 4 |
| Two | 17 | 61 | 39 | 5 | |
| Three | 7 | 25 | 16 | 0 | |
| Four | 1 | 6 | 15 | 2 | |
| Five or greater | 1 | 5 | 5 | 0 | |
| Sex Partner Age | 0 - 19 | 24 | 104 | 89 | 3 |
| 20 - 30 | 19 | 75 | 43 | 5 | |
| 31 - 40 | 2 | 16 | 13 | 2 | |
| above 40 | 1 | 3 | 3 | 1 | |
model was different for individual variable and the sign of the significant parameters were as expected. The model output revealed that Age, Religion, ethnicity and class in years were significant at less than one percent probability level.
On Bivariate logistic regression, variables including: age, sex, active in my faith/religion, contraceptive use, condom use, unwanted pregnancy, had sex last time, sex partners in the past 12 months, sex partner age, attitude, peer pressure, tobacco, alcohol and chat use were found to have statistically association with the outcome variable and for further analysis entered in to multivariate logistic analysis. On the other hand religion, ethnicity and class in year were not associated at 0.25 level of significance and were excluded from further analysis.
During the multivariate analysis of risky sexual behavior in relation to all explanatory variables; age, active in my faith/religion, contraceptive use, condom use, peer pressure, tobacco and alcohol were found to be statistically significant.