|Year : 2022 | Volume
| Issue : 2 | Page : 176-184
Prevalence and sociodemographic determinants of risky sexual behavior among unmarried adolescents in Southeast Nigeria
Irene I Eze1, Chinyere O Mbachu2, Mildred N Ndubuisi3, Ifunanya C Agu3, Nkoli Ezumah1, Obinna Onwujekwe4
1 Department of Community Medicine, Ebonyi State University, Abakaliki, Nigeria
2 Department of Community Medicine, University of Nigeria, Nsukka, Nigeria
3 Health Policy Research Group, University of Nigeria Enugu Campus, Enugu, Nigeria
4 Department of Health Administration and Management, University of Nigeria, Nsukka, Nigeria
|Date of Submission||19-Apr-2021|
|Date of Decision||15-May-2021|
|Date of Acceptance||24-Jan-2022|
|Date of Web Publication||3-Mar-2022|
Ifunanya C Agu
Health Policy Research Group, University of Nigeria Enugu Campus, Nsukka.
Source of Support: None, Conflict of Interest: None
Background: Adolescent risky sexual behavior is of a public health concern as most outcomes have long-term negative consequences on adolescents’ health and development. Objectives: This study was undertaken to assess the prevalence and sociodemographic determinants of risky sexual behavior among unmarried adolescents in Nigeria. Materials and Methods: A quantitative cross-sectional study was undertaken in Ebonyi state, Nigeria, using a pre-tested structured interviewer-administered questionnaire. Data were collected from 1045 adolescent boys and girls. Descriptive, bivariate, and multivariate analysis were performed using STATA software. Results: A total of 372 (35.6%) adolescents in the survey ever had a boyfriend or girlfriend. About, 369 (36.0%) had been pressurized by others to have sex, 73 (7.0%) had engaged in multiple sexual partnering, 3.0% had engaged in age-disparate sex, 27 (2.6%) had a one-night stand, and 37 (2.4%) reported they had engaged in nonconsensual sex. Lifestyle risky behaviors that were reported include partying/night clubbing 399 (38.1%), the use of mood-enhancing drugs 319 (30.5%), and alcohol consumption 316 (30.2%). Some sociodemographic factors were significantly associated with multiple sexual partnering, age-disparate sex, nonconsensual sex, and other lifestyle risky behaviors. In logistic regression analysis, gender was a predictor of multiple sexual partnering, age-disparate sex, and nonconsensual sex (odds ratio [OR] = 0.43, confidence interval [CI] = 1.40–3.71; OR = 10.0, CI = 0.03–0.29; OR = 3.0, CI = 0.01–0.14, respectively), while type of place of residence (OR = 1.75, CI = 0.35–0.92) and schooling status (OR = 3.70, CI = 0.13–0.41) were predictors of multiple sexual partnering. Conclusion: Risky sexual behaviors were prevalent among adolescents highlighting the need for strategic SRH interventions that pay close attention to identified drivers that predispose adolescents to unhealthy sexual behaviors.
Keywords: Ebonyi state, Nigeria, risky lifestyle, sexual behavior
|How to cite this article:|
Eze II, Mbachu CO, Ndubuisi MN, Agu IC, Ezumah N, Onwujekwe O. Prevalence and sociodemographic determinants of risky sexual behavior among unmarried adolescents in Southeast Nigeria. Int J Med Health Dev 2022;27:176-84
|How to cite this URL:|
Eze II, Mbachu CO, Ndubuisi MN, Agu IC, Ezumah N, Onwujekwe O. Prevalence and sociodemographic determinants of risky sexual behavior among unmarried adolescents in Southeast Nigeria. Int J Med Health Dev [serial online] 2022 [cited 2023 Jun 5];27:176-84. Available from: https://www.ijmhdev.com/text.asp?2022/27/2/176/339022
| Introduction|| |
Adolescence is a phase of emotional, physical, social, and biological maturation that contributes substantially to the development of an individual into adulthood. Considering the reproductive and physiological changes at this period of life and the accompanying social and behavioral dilemmas, adolescents can be said to have unique/special sexual and reproductive health needs. Adolescents tend to develop an increased interest in experiences and behaviors that are associated with adulthood, such as forming a new relationship with the opposite sex and engaging in sexual activity. Adolescents are more prone to risk taking because the part of the brain responsible for cognitive development does not fully mature until age 25. Consequently, adolescents have problems with self-control, delay of gratification, and risk analysis including consequences of sexual behavior. They possess distinctive psychosocial lifestyles characterized by personality identity crises, desire to be free from strict parental control, deviant behavior, insatiable desire for excitement, and emulation of modern lifestyles. Adolescent sexuality which refers to sexual feeling, behavior, and development is an issue of great concern because it is influenced by the interaction of prevailing sociocultural and environmental factors and the psychological state of the individual which could result in negative outcomes.,,
Risky sexual behaviors which include, early sexual initiation/debut, unprotected sexual intercourse, multiple sexual partners, noncontraceptive use, coerced, and transactional sexual intercourse have been widely reported to be prevalent among adolescents.,, These risky sexual behaviors could expose adolescents to sexually transmitted infections including human immunodeficiency virus/acquired immunodeficiency syndrome, early unintended teenage pregnancy, early child-birth/risky childbearing, and premature death., The 2018 Nigeria demographic health survey reported that 19% of women aged 15–19 have begun childbearing. The attendant outcomes of risky sexual behaviors and their linkage to maternal and child morbidity and mortality underline the need to investigate adolescent sexual behaviors. Also, childbearing during adolescence is known to have adverse social consequences, particularly regarding educational attainment, school drop-out, and economic empowerment.
Personal lifestyle behaviors such as alcoholism and drug use and socioeconomic drivers such as low literacy and poverty have been linked to risky sexual behaviors among adolescents., Poverty is probably a major underlying factor in risky sexual behaviors and it has been linked to the practice of transactional sex, age-disparate sex, or multiple sexual partnering. Poverty also correlates and interacts with other factors that predispose adolescents to risky sexual behaviors, such as street hawking, homelessness, and residency in slum neighborhoods. Pervasive social norms also perpetuate gendered power imbalances within sexual relationships., Although drivers of risky sexual behaviors have been documented in literature relationships,,, not much is known about whether and how these factors influence adolescents. This study assessed the sexual behavior of adolescents in Ebonyi State, as well as the demographic and socioeconomic factors that influence their sexual behaviors. Considering the abundance of some drivers of risky sexual behavior in Ebonyi State, including low literacy and high poverty levels, it was imperative to undertake this study. This article provides information that could be useful in similar contexts for proper targeting of adolescents in sexual and reproductive health programming.
| Materials and Methods|| |
Before entry into the study sites, the project protocol was submitted to the Health Research Ethics Committee of the University of Nigeria Teaching Hospital Enugu, and ethical approval to undertake the research was obtained with reference number NHREC/05/01/2008B-FWA00002458-IRB00002323 which is still applicable. In addition, approval was also secured from the Research and Ethics Committee of Ebonyi State Ministry of Health to carry out the study. Data sharing and publication were discussed during the project ethics reviews. Before data collection, participants were informed of the research purpose, their rights of participation and measures that will be taken to protect them, and the information they will give. Informed written consents were obtained from parents of adolescents between ages 13 and 18 and additional consent was obtained from the adolescents. Adolescents who are aged 18years gave consent for themselves having assured them of voluntary participation and confidentiality.
Study design and study area
A cross-sectional study design was undertaken to survey adolescents in Ebonyi State, Nigeria. Based on the 2006 population census, Ebonyi State has a population of 2,179,947 with an annual growth rate of 2.8%, and about half of the populace are aged below 18 years. The State has 13 Local Government Areas (LGAs) that are grouped into three senatorial zones and hosts many educational as well as health institutions where health services are provided. The majority of residents reside in the rural area and the prominent occupation of the people in the state include farming, trading, artisan, and civil service.
The participants who were included in this study consisted of unmarried adolescent boys and girls between ages 13 and 18 years, who were either in-school or out-of-school. Those excluded from the study were adolescents (13–17 years) whose caregivers refused consent or were not available to give consent at the time of the survey as well as those who had mental, visual, or hearing defects.
Sample size and sampling
To achieve a 5% precision at 95% confidence interval (CI) for the population >100,000, a minimum sample size of 1100 was determined from Glenn’s table of sample sizes after adjusting for subgroup analysis, robustness, and incomplete responses.
Multistage sampling technique (three-staged) was used in selecting the study participants. The first stage entailed stratifying the state into three senatorial zones. The second was a purposive selection of two LGAs across the three senatorial zones to ensure (i) geographic spread (urban and rural) and (ii) prioritization of stakeholders in Ebonyi state based on the highest rate of unwanted teenage pregnancy and abortion. In the third stage, the study adapted a modified cluster sampling technique where a cluster was picked by simple random sampling (balloting) from each of the selected LGAs, and eligible adolescents aged 13–18years from each household were recruited to participate in the study. The nearest public facility (church, school, town hall, or primary health center) from the main entrance of each cluster was identified as a beginning point from which households were consecutively selected.
A structured questionnaire was used to collect information from all eligible adolescents who were invited to participate in the study. This data collection instrument was adapted from World Health Organization (WHO) illustrative questionnaire for interview surveys with young people. The variables of interest were (i) demographic characteristics such as place of residence, gender, schooling, and wealth index, (ii) risky sexual behaviors (multiple sexual partnering, age-disparate sex, transactional sex, nonconsensual sex, and unprotected sexual intercourse), and (iii) lifestyle practices (partying/night clubbing, use of mood enhancers, and alcohol consumption).
The questionnaire was pre-tested on 24 adolescents that were not amongst the study participants, to check for validity and clarity of questions, then necessary adjustments were made based on observations. Five days of intensive training were conducted for 54 research assistants who were recruited to assist with the administration of the questionnaires. Data were collected using paper and electronic copies of the questionnaire over a period of 10 days. The electronic copies of questionnaires were filled and uploaded through android tablets using SurveyCTO. Individual matching of information on a completed electronic questionnaire with corresponding paper questionnaire was carried out before and after uploading data to the server. In other to ensure the quality of data collected, fieldwork supervision activity was piloted in two layers.
The detailed method and process of the study data analysis have been described in published articles., A total of 1045 questionnaires were found to be completely filled and without errors. This gave a response rate of 95%. The data set and materials of the results presented in this manuscript have been deposited in a repository. Using Stata software, descriptive analysis was performed, and weighted proportions were reported for categorical variables. Risky sexual and lifestyle behaviors were disaggregated by sociodemographic characteristics such as place of residence (urban or rural), gender, schooling, and wealth index to highlight distribution. The variables were tested for association using chi-square (χ2) binary logistic regression analysis was performed to identify sociodemographic predictors of risky sexual behaviors among adolescents. Statistical significance was set at P ≤ 0.05 and a confidence level of 95%.
| Results|| |
The mean age of the respondents was 15.4 years (CI, 15.3–15.5). There were 598 (57.2%) girls and 447 (42.8%) boys. Five hundred and fifty-one were surveyed from urban areas (50.7%) while 494 (49.3%) were from rural areas. The majority of the adolescents, 966 (92.4%), were currently in school, and 1033 (98.7%) were living with a parent or guardian at the time of the survey. About a quarter of the adolescents, 262 (25.1%), were currently working for pay at the time of the survey and half of these income earners were engaged in farming.
[Table 1] shows that 35.6% of adolescents have had a boyfriend or girlfriend in the past; 24.2% currently had a boyfriend or girlfriend, and 35.3% had been pressured to have sex in the past. With respect to risky sexual behaviors, 7.3% of adolescents in the survey engaged in unprotected sexual intercourse during their last sex, and 7% had engaged in multiple sexual partnering. Results on other risky lifestyles show that 30.5% of adolescents use mood-enhancing substances. See [Table 1] below:
|Table 1: Sexual behaviors and other risky lifestyles/behaviors of adolescents in the survey|
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The relationship between adolescents’ socioeconomic and demographic characteristics and their risky sexual behaviors are shown in [Table 2]. A significant association was observed between gender and risky sexual behaviors (multiple partnering, nonconsensual sex, age-disparate sex, and unprotected sex) among adolescents (P ≤ 0.01). Significant association was also found between multiple sexual partnering and age category (P < 0.001), type of place of residence (P = 0.04), and schooling status (P < 0.01).
|Table 2: Demographic and socioeconomic correlates of risky sexual behavior among adolescents|
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[Table 3] shows the relationship between adolescents’ demographic characteristics and the practice of other risky lifestyles. Significant associations were observed between age category, place of residence, gender, schooling status, and partying or nightclubbing (P ≤ 0.01). Similarly, age category, place of residence, and gender were significantly associated with the use of mood-enhancing substances (P ≤ 0.01). Income earning status also had a significant association with the use of mood-enhancing substances ((P = 0.001). See [Table 3] below:
|Table 3: Demographic and socioeconomic correlates of other risky lifestyles/behaviors among adolescents|
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The relationships between risky sexual behaviors and other risky lifestyles among adolescents in the survey are presented in [Table 4]. The significant association exists between multiple partnering and partying or nightclubbing and the use of mood-enhancing substances (P < 0.001). Age disparate sex was significantly associated with the use of mood-enhancing drugs (P = 0.04), while nonconsensual sex had a significant association with partying or nightclubbing (P = 0.04).
|Table 4: Relationships between risky sexual behavior and other risky lifestyles among adolescents|
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Results of logistic regression analysis of factors associated with risky sexual behaviors among adolescents in the survey are shown in [Table 5]. Predictors of multiple sexual partnering among adolescents include age (odds ratio [OR] 1.3, CI 1.13–1.49), type of place of residence (OR 0.57, CI 0.35–0.92), gender (OR 2.28, CI 1.40–3.71), and schooling (0.27, CI 0.13–0.41). Gender was also found to be a predictor of nonconsensual sex (OR 0.33, CI 0.01–0.14) and age-disparate sex (OR 0.10, CI 0.03–0.29). Older adolescents (>16 years) were 1.3 times more likely to have multiple sexual partners than younger adolescents (< 15 years) as shown in [Table 5] below.
|Table 5: Logistic regression of factors associated with risky sexual behaviors among adolescents in the survey|
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| Discussions|| |
Low prevalence of sexual activity was noted in this study among adolescents; less than a tenth of the sampled population reported having sexual intercourse. This is at variance with the findings of other studies conducted in Plateau State, Nigeria and in Cameroon where about half of the population surveyed reported sexual activity. Whereas the higher prevalence noted in the aforementioned studies may be linked to the populations studied which were only female; the low prevalence in this study may be related to the non-response/under-reporting usually associated with undesirable and sensitive questions like sexual intercourse.
This study found that considerable proportions of sexually active adolescents engaged in risky sexual behaviours such as multiple sexual partnering, transactional sex, age-disparate sex and non-consensual sex. This is consistent with similar studies of adolescents in Nigeria where high risk sexual behaviours have been reported.,, These risky sexual behaviours, particularly age-disparate and transactional sex, could be attributed to situations such as poor socioeconomic conditions and juvenile delinquency. It has been observed that most juvenile delinquents lack proper home training and parental care., This view is reflected in a study among young girls in Nigeria which reported that almost half of the respondents were expected to find the means to supplement the funds they were given to meet their basic needs and most of them were found to be sexually active.
More than a third of the respondents in this study reported other risky lifestyle behaviours such as partying/night clubbing, use of mood enhancers and consumption of alcohol. This finding corroborates findings from a cross sectional study conducted among secondary school students in Kenya. The significant association between risky sexual behaviours and other risky lifestyles among adolescents in this survey is also consistent with findings from the Kenyan study that reported increased likelihood of sexual activity and sexual risk-taking among young people who consumed alcohol and attended parties. Some other studies have also reported the association between risky sexual behaviours and alcoholism or drug use, and the resultant negative consequences of unwanted pregnancy, unsafe abortion and premature death.,
Socio-demographic variables such as gender, type of place of residence, schooling status and age category had significant statistical associations with risky sexual behaviours. Gender had correlation with risky sexual behaviour such as multiple partnering, non-consensual sex, age-disparate sex and unprotected sex. Adolescent girls in this survey had a threefold likelihood of engaging in non-consensual sex and a tenfold likelihood of engaging in age-disparate sex when compared to boys. This corroborates findings from other Nigerian and non-Nigerian studies that have reported young girls as being more exposed to risky sexual behaviours than boys., A Ugandan study which attempted to provide an explanation for this reported that financial pressures play a major role in influencing girls to begin engaging in sex in order to meet basic needs.
Risky sexual behaviours among adolescents in this survey also varied according to their schooling status. Adolescents who were out-of-school during the period of the survey were found to be four times more likely to have multiple sexual partners than those who were in-school. The higher likelihood of risky sexual behaviour among out-of-school adolescents compared to in-school adolescents in this study corroborate findings from other studies among adolescents Nigeria,, and in Ethiopia where those that are out-of-school were four times more likely to engage in risky sexual behaviours. Although it is unclear whether this comparative advantage that schooling offers is as a result of education itself or the socialization and improved self confidence that results from interacting with one’s age-in school. Earlier studies reported that poor socio-economic status and family instability which are common among out-of-school adolescents tend to push adolescents into risky sexual relationships.,[20.31]
Adolescents residing in rural areas in this survey were two times more likely to have multiple sexual partners than their counterparts in urban areas. This finding is also consistent with the urban-rural distinction found in a study among adolescents in Ogbomosho, Oyo State Nigeria. This variation could be explained by the potential opportunities that residents in the cities and townships have in terms of access to sexual and reproductive health information and services over their counterparts living in the suburbs and rural settings. Access to sexual and reproductive health information and services could influence adolescents to adopt safer sexual practices. A second explanation to the rural-urban variation in sexual behaviours of adolescents could be the difference in societal norms, cultural beliefs, and living conditions. The transition in norms and practices from rural areas to urban areas influence adolescent sexual behaviour.
In this survey, older (>16 years) adolescents were 1.3 times more likely to have multiple sexual partners than their younger (<15 years) counterparts. The higher likelihood of the older adolescents to have multiple sexual partners compared to the younger ones in this study shows that age has a role to play in sexual behaviours; and corroborates the findings from other studies among adolescents and young adults in Lagos, Nigeria and Zimbabwe. This finding can be explained by the fact that majority of the older adolescents are matured for sexual activities compared to the younger counterparts who are not fully matured for sexual activities; younger adolescents are yet to develop traits of secondary sexual characteristics which are physical evidences for sexual maturity. However, evidence has shown that there are cases of younger adolescents who become sexually active due to sexual abuse and molestation before developing physical evidences for sexual maturity. The abuses and molestations have detrimental effect on the victims’ physical health and psychobiological development.
This study should be interpreted with the following possible limitations. First, is the issue of social desirability. The use of an interviewer-administered questionnaire to ask “undesirable and sensitive” questions like sexual intercourse could lead to adolescents responding less to sensitive questions and more to questions that target good behavior, hence leading to response bias. This may be fraught with the prospect for under-reporting sensitive or bad behavior and over-reporting good behavior notwithstanding that confidentiality was assured. Second, since the findings were self-reported, it relied upon study participants’ recall memory hence having potential of recall bias. Despite these limitations, the rigorous methodology employed enabled us to empirically generate reliable data on adolescents’ risky sexual behaviors in the study area.
| Conclusion|| |
The study showed that considerable numbers of unmarried adolescents in Ebonyi State engage in risky sexual behaviors such as multiple sexual partnering, age-disparate sex, transactional sex, nonconsensual sex, and unprotected sexual intercourse. They also engage in nonsexual risky lifestyles such as partying/night clubbing, the use of mood enhancers, and alcohol consumption which predispose them to risky sexual behaviors. Specifically, gender was found to be a predictor of several risky sexual behaviors; adolescent boys were more likely to have multiple sexual partners than girls, while adolescent girls were more likely to engage in nonconsensual and age-disparate sex than boys. Other sociodemographic factors such as place of residence and schooling status were also found to be predictors of some risky sexual behaviors among adolescents.
Risky sexual behaviors among adolescents were found to be influenced by many factors and drivers highlighting the need for more strategic interventions. In designing interventions, adolescent sexual and reproductive health program managers and implementers should ensure that the sociodemographic predictors as well as nonsexual risky lifestyles that predispose adolescents to unhealthy sexual behaviors are taken into consideration. Designing and implementing gender-based SRH programs and services for adolescents is also of utmost importance.
The research leading to results included in this manuscript is part of a needs assessment data of a project which aims to address the unmet need of contraceptives among adolescents using a community-embedded intervention in Ebonyi state, Nigeria. A manuscript from this baseline survey has been published in BMC Public health, https://doi.org/10.1186/s12889-019-8058-5. The datasets of the result presented in our manuscript has be deposited in UK Data Service and a detailed description of the data sets is found in a published article “Survey data of adolescents’ sexual and reproductive health in selected local governments in southeast Nigeria”. Scientific Data (2020). doi: 10.1038/s41597-020-00783-w.
The authors wish to thank all the study respondents for active participation and willingness to partake in the survey.
Financial support and sponsorship
The research project leading to the results presented in the manuscript received funding from IDRC MENA+WA implementation research project on maternal and child health (IDRC grant number: 108677). However, the funder did not participate in designing the study, collecting and analyzing data, or writing and reviewing the manuscript. The views presented in the manuscript solely belong to the authors and do not necessarily represent the funders’ views.
Conflicts of interest
All the authors have no conflict of interest to disclose
Criteria for inclusion in the authors’/contributors’ list
Chinyere M, Nkoli E, and Obinna O conceptualized and designed the study protocol and instruments used for data collection. Irene E, Chinyere M, and Ifunanya A were involved in data collection. All the authors participated in data analysis. Irene E produced the first draft of the manuscript. All the authors reviewed and approved the final version of the manuscript for journal submission.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]