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Influence of socio-contextual factors on the link between traditional and new media use, and young people’s sexual risk behaviour in Sub-Saharan Africa: a secondary data analysis

Reproductive Health volume 21, Article number: 138 (2024) Cite this article

Abstract

Background

Traditional and new media use links to young people’s sexual risk behaviour. The social contexts of young people’s daily lives that influence media use and sexual risk behaviour are often investigated as independent causal mechanisms. We examined the link between media use and young people’s sexual risk behaviour, considering the intersecting socio-contextual factors in Sub-Saharan Africa.

Methods

Age-adjusted bivariate logistic regression models tested the association between traditional media (TV, radio, and newspapers), and new media (mobile phone and online) use and sexual risk behaviour using the Demographic and Health Surveys from six Sub-Saharan African countries among unmarried sexually active youths, aged 15–24 years. Multivariate logistic regression models ascertained the media sources that had an additional influence on young people’s sexual risk behaviour, after accounting for socio-contextual factors, and knowledge about HIV and other sexually transmitted infections.

Results

Socio-contextual factors attenuated the association between media use and young people’s sexual risk behaviour in many countries. However, those who did not have access to new and traditional media were more likely to use unreliable contraceptive methods or not use contraception. Adolescents in Nigeria who did not own phones were 89% more likely to use unreliable contraceptive methods or not use any methods [(AOR = 1.89 (1.40–2.56), p < .001)], those in Angola who did not read newspapers had higher odds of not using contraception or used unreliable methods [(aOR = 1.65 (1.26–2.15), p < .001)]. Young people in Angola (aOR = 0.68 (0.56–0.83), p < .001), Cameroon [(aOR = 0.66 (0.51–0.84), p < .001)], Nigeria [(aOR = 0.72 (0.56–0.93), p = .01)], and South Africa [(aOR = 0.69 (0.49–0.98), p = .03)] who did not own phones were less likely to have 2 or more sexual partners compared to those who owned phones. Lack of internet access in Mali was associated with lower odds of having 2 or more sexual partners (aOR = 0.45 (0.29–0.70), p < .001). Traditional media use was significantly associated with transactional sex in many countries.

Conclusions

Media use is linked to sexual risk behaviour among young people in Sub-Saharan Africa. Socioeconomic inequalities, levels of globalization, as well as rural–urban disparities in access to media, underscore the need to deliver tailored and targeted sexual risk reduction interventions to young people using both traditional and new media.

Plain language summary

In addition to television, radio, magazines, and newspapers, young people in Sub-Saharan Africa are increasingly using their phones and the Internet to connect with their peers. However, these media sources can lead to sexual risk behaviour because of access to inappropriate and inaccurate information. Social environmental factors in Sub-Saharan Africa, such as gender, place of residence, and socio-economic status influence young people’s access to and use of these media sources. However, many studies that consider the influence of these social factors on the use of media among young people evaluate each of them and fail to consider that these social forces jointly influence young people’s access to the internet, and ability to own phones, watch television, or read newspapers. Our study considered these combined social factors and their influence on the link between the use of media and sexual risk behaviour among young people. We found that considering these social environmental factors reduced the association between media use and young people’s sexual risk behaviour but those who did not have access to these media sources were more likely to use unreliable methods to prevent pregnancy or sexually transmitted diseases. Those who listened to the radio, or read newspapers and magazines were more likely to give or receive cash or other gifts in exchange for sex. In contrast, young people who never owned phones or lacked access to the internet were less likely to have had multiple sexual partners. Our findings stress the need to consider social contexts and media use in promoting young people’s sexual health.

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Introduction

Sexual risk behaviour among young people remains a major public health concern in Sub-Saharan Africa, where risky sexual behaviour and related adverse health outcomes are disproportionately higher compared to high-income countries [1,2,3]. The transitional changes in the biological, cognitive, psychosocial, and emotional domains during adolescence predispose young people to sexual and reproductive risk behaviour [4,5,6]. Further, longer school years, and later age of marriage, as well as social transformations in many countries in Sub-Saharan Africa elevate sexual risk behaviour among unmarried young people [7, 8]. Additionally, globalization, and the information, communication, and technology (ICT) revolution of the twenty-first century facilitate easy access to digital sexual and reproductive health information and misinformation among young people in Sub-Saharan Africa [9, 10]. Young people are growing up in a highly digitalized world, where new media sources, such as mobile applications, social media networks, websites, and other internet-related forms of communication have transformed information access and social connections among youth [11,12,13].

New media refers to internet-based applications that permit access to videos, digital texts, images, associated web links, and user interactions [9, 14, 15]. Available evidence in Sub-Saharan Africa indicates that most of the internet users are young people, thus, new media use constitutes emerging social contextual factors that can have significant impacts on sexual and reproductive health during this critical stage in the life course [16,17,18]. Indeed, uncontrolled access to inappropriate pornographic materials on digital media among young people in Sub-Saharan Africa is linked to sexual and reproductive risk behaviour [9, 19,20,21]. For example, sexting, or sharing sexually explicit materials through mobile phones is common among youths and is linked to a higher number of sexual partners and other sexual risk behaviour [17, 22, 23]. Mobile phones and the internet are common new media utilized by young people in Sub-Saharan Africa to access digital information and thus present opportunities for the delivery of mobile sexual and reproductive health interventions [24, 25].

Consequently, many programs and interventions that focus on promoting youths’ sexual and reproductive health in Sub-Saharan Africa leverage the ubiquitous use of new media, particularly mobile phones by young people to communicate factual and comprehensive sexual health information [14, 18, 26, 27]. Indeed, the digital age has revolutionized the dissemination of sexual health messages, and HIV risk awareness campaigns, and increased the uptake of sexual risk preventive services in the region [28,29,30]. Moreover, young people take advantage of the proliferation of new media and the availability of sexual information on the internet, and social networking sites (e.g., Facebook, YouTube, WhatsApp, Myspace, and Twitter) at no cost to search for answers to sensitive sexual health topics [13, 26, 31]. Thus, young people use new media as alternative sources of sexual health information to circumvent unfriendly sexual health services in the region and to meet their sexual health information needs [26, 32,33,34,35,36].

Besides, the new media, traditional media (such as television, radio, newspapers, and magazines) are sources of sexual and reproductive health, and HIV-related information in Sub-Saharan Africa [37,38,39,40]. For example, a study carried out in Nnewi, Nigeria, found that 40% of young people sought information about sexual issues online, another 30% obtained similar information from television, and 7% from newspapers and magazines [41]. Another study in Kenya that investigated the influence of television on adolescents’ sexual behaviour reports that young people were attracted to television programs with sexual content and would rather seek sexual information from the television rather than from their parents or other adults [42].

Given the curiosity and exploration that occur during these developmental years, studies suggest that young people in Sub-Saharan Africa access uncensored sexually explicit materials that are easily available on the internet [15, 17, 21]. A body of evidence reports a positive correlation between media use and a higher likelihood of sexual risk behaviour (such as multiple sexual partners, transactional sex, and non-use or unreliable contraception) among young people in the region [20, 31, 38, 43,44,45]. For example, a study carried out in Osogbo, Nigeria found that, out of the 68% of young people who owned smartphones, only about 39% used them to access sexual health information and 78% of young people used their phones to access sexually explicit materials [16]. Another study that examined the predictors of risky sexual behaviour among pre-college students in Ethiopia found that social media users had higher odds of having engaged in sexual risk behaviour compared to non-users [45]. Such risky behaviours lead to unsafe abortions, early pregnancy, pregnancy-related complications, intergenerational poverty among girls, and predispose young people to HIV/AIDS [46,47,48].

However, not all young people in Sub-Saharan Africa have access to new and traditional media sources because of the social circumstances of their daily lives [10, 49,50,51]. Socio-contextual factors (such as gender, educational attainment, religion, socio-economic status, and place of residence) play a key role in access to and use of media as well as engagement in sexual risk behaviour [43, 49, 52, 53]. From an intersectional theoretical standpoint, the broader social forces (e.g., policies, laws, national wealth, and its distribution), as well as power imbalances place individuals and groups at structural disadvantages and social deprivations [54,55,56,57]. Consequently, many young people may not be reached by intervention efforts that aim to address their sexual health information needs through digital health platforms and traditional media sources [10, 24, 49]. Further, poverty and lack of access to formal education expose many young people to sexual risk behaviour [10, 58, 59]. For instance, adolescent girls and young women’s desire to own a mobile phone to earn social status, gain peer approval, or overcome economic vulnerabilities is also related to engagement in transactional sex [60,61,62,63].

Additionally, there is conflicting evidence about the role that social factors play in the link between media use and risky sexual behaviour among young people in Sub-Saharan Africa. For example, one study that pooled the Demographic and Health Survey datasets from 27 Sub-Saharan African countries reported that adolescent girls and young unmarried women, who listened to the radio, lived in urban areas, belonged to high social class, or were employed had higher odds of having had a sexually transmitted infection [38]. The same study found that ever attending school, or exposure to television correlated with lower odds of reporting an STI [38]. Another study in Mali reported that mass media exposure had a positive correlation with self-reported sexually transmitted infections [64]. Moreover, many studies in Sub-Saharan Africa examine these social forces as independent causal mechanisms and fail to account for the interacting social factors that influence the link between media use and adolescent sexual risk behaviour [65, 66]. To fill these important gaps in the literature, we explored the link between media use and adolescent sexual risk behaviour in Sub-Saharan Africa while considering the simultaneous influence of other socio-contextual factors.

Specifically, we addressed the following research questions; (1) What is the association between media use and young people’s sexual risk behaviour, over and beyond other social factors? (2) How do young people’s HIV and other STIs knowledge modify the influence of media on their sexual risk behaviour? (3) What are the between-country and regional differences in the link between media use and young people’s sexual risk behaviour?

Methods

Design of the study and data source

Our study was a secondary analysis of the publicly available Demographic and Health Surveys (DHS) datasets (2014–2018) from six Sub-Saharan African countries. Demographic and Health Surveys use nationally representative samples to monitor population health. The surveys are carried out every five years by the DHS Program, an agency of the United States Agency for International Development (USAID) in collaboration with participating countries. The DHS uses a cross-sectional design and two-stage sampling to select clusters and households, and an interviewer-administered questionnaire collects information from participants, aged 15–49 in selected households. The DHS has standard model questionnaires that collect health information separately from men, women, and entire households [67]. For the current study, we merged the men's and women’s data files.

More details about the DHS and its administration are provided elsewhere [43, 68]. Most of the questionnaire items that address the socio-demographic characteristics, HIV, and other sexual risks related knowledge, as well as sexual risk behaviour among young people in SSA, are comparably the same for most Sub-Saharan African countries and thus allow for between-country comparisons. We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist in our study and in reporting our findings.

Sampling and inclusion criteria

We selected the sub-sample of all the unmarried sexually active young people, aged 15–24 years, in countries that met our inclusion criteria. We considered the national income classification, geographical location of the country in Sub-Saharan Africa, data availability, and consistency of the items that assessed traditional and new media use among young people. We included countries that had measures for phone ownership, access to the internet, and traditional media sources, as well as measures of sexual risk behaviour among young people. For statistical power and to allow for between-country comparisons of adolescent sexual risk behaviour, we selected countries with a population of twenty million or more. We used the World Bank’s Classification of Sub-Saharan African countries based on their Gross National Income (GNI) to categorize these countries into low-income, lower-middle-income, and upper-middle-income countries. This will facilitate an understanding of how the link between media use and sexual and reproductive risk behaviour is similar or different across countries in the region. The countries we included in the study were Angola, Ethiopia, Cameroon, Mali, Nigeria, and South Africa.

Study variables

Outcome variables

Engagement with multiple sexual partners, transactional sex, and contraceptive use (non-use, the use of unreliable contraceptive methods, and the use of modern methods of contraception) among young people were the outcome variables in our study. Our study sample included all unmarried sexually active young people, given their heightened risk of sexual risk behaviour. We used the variable that assessed the number of sexual partners in the 12 months before the survey to assess engagement in sexual risk behaviours. We reasoned that the variable that asked for the number of sexual partners in the last 12 months facilitates easy recall of sexual activity among sexually active young people, so we used the variable that assessed the number of sexual partners in the last 12 months. Since a higher number of sexual partners increases the risk of HIV and other STIs, the number of sexual partners in the 12 months before the surveys was re-coded from a continuous variable to an ordinal level variable (no sexual partner, one sexual partner, two or more sexual partners). Transactional sex was assessed separately for males using the variable that asked whether male youths have ever exchanged cash or other gifts for sex, with females—we used the variable that asked whether they ever had sex in return for gifts, cash, or other material gratification.

The measure of contraceptive method used by the participants was an ordinal level variable (no method, the use of traditional methods, and the use of modern methods of contraception). We dichotomized contraceptive method use at the time of the survey, so that, non-use of any contraceptive method and the use of traditional methods constitute non-use or the use of unreliable methods. While the use of modern methods of contraception represented the use of reliable contraceptive methods. The DHS conceptualizes the traditional methods of contraception as the use of periodic abstinence, coitus interruptus (withdrawal), and other country-specific folkloric methods, such as the use of herbs, amulets, etc. We reasoned that the non-use of contraception, or the use of unreliable methods, for example, folkloric and other methods that have higher failure rates compared to modern methods of contraception could expose young people to unintended pregnancy, as well as sexually transmitted infections including HIV. Further, early pregnancy and unintended pregnancy may result in unsafe abortion, early childbearing, or early marriage [48, 69, 70]. These adverse reproductive outcomes increase morbidity and mortality rates and have lifelong and intergenerational consequences among young people, particularly among unmarried sexually active girls and young women [48, 71]. Moreover, many traditional methods of contraception that are used in Sub-Saharan Africa are not scientifically proven, even the more commonly used methods, e.g., withdrawal or periodic abstinence have higher failure rates and are less effective compared to most modern methods of contraception [72,73,74,75]. For instance, one study found no significant difference in preventing unwanted pregnancy among women who used traditional methods compared to those who did not use any contraceptive method [73]. Another study notes that unwanted outcomes, such as unintended births and abortions were higher for non-users of modern methods compared to those who used modern methods [74]. Thus, we used the re-coded binary variable (non-use, or the use of unreliable methods of contraception, and the use of modern methods of contraception) as one of the sexual risk behaviour among young people.

Explanatory variables

We included access to the internet and ownership of mobile phones as measures of new media use. These media sources were dichotomous variables that required a yes or no response. The measures of traditional media sources were the frequency of watching television, listening to the radio, and reading magazines and newspapers. The items that measured traditional media use were ordinal level variables (not at all, at least once a week, and almost every day). These measures were dichotomized so that no access to traditional media represented non-use, and the use of these media sources at least once a week and almost every day constituted access to these traditional media sources. We then included several socio-contextual factors that are associated with media use, and risky sexual behaviour among young people in Sub-Saharan Africa [22, 38, 43, 64, 76,77,78]. We used the DHS classification of the place of residence as urban and rural and the categorization of gender into male and female.

Further, we considered that level of education may influence engagement in sexual and reproductive risk behaviour. For example, available evidence indicates that lower levels of education correlate positively with engagement in sexual risk behaviour among young people [79]. We used an intersectionality lens to categorize young people based on their educational attainment into no education/primary education, and higher/secondary education. Given the prevalent poverty and the precarious social circumstances in Sub-Saharan Africa, young people who never attended school, who had just primary education, or dropped out of school have a higher likelihood of engaging in sexual risk behaviour compared to their counterparts who are enrolled in secondary school or higher [22, 80,81,82,83]. For instance, evidence indicates that the odds of condomless sex were lower among young people who had six or more years of schooling [84]. Further, most sex education programs in Sub-Saharan Africa are school-based, and many sexual risk behaviour reduction interventions target young people in high or tertiary education [85]. For example, one systematic review reported that 84% of school-based sexual health education programs to prevent sexually transmitted infections and HIV/AIDS in Sub-Saharan Africa were carried out in secondary and tertiary schools [86].

Socioeconomic status was a proxy variable created from the DHS wealth quintile that incorporates not only participants' income but also inequalities in household characteristics and assets. The wealth quintiles were re-coded into poor, middle class, and rich. Ethnicity was re-coded into least, moderate, and most dominant groups in countries when the ethnic identities could be categorized into distinct groups. We included religious affiliation in all countries except South Africa because the variable was not available in the datasets. Head of the household was a dichotomous variable that categorized households into male- and female-headed households.

Ethical consideration

Our study was a secondary analysis of existing anonymous datasets and did not require ethical review.

Data analysis

Complex Sample frequencies and percentages described the characteristics of the sample. Rao-Scott’s adjusted chi-square tested the significant association between technology and media use and sexual risk behaviour. Binomial and ordinal logistic regression models tested the relationship between media use and sexual risk behaviour in each country. Next, we sequentially included the social factors in logistic regression models without replacement to assess the change in the influence of each socio-contextual factor on the relationship between media use and young people’s sexual risk behaviour. The multivariate models examined the media sources’ relationship, controlling for all the socio-contextual factors, on each sexual risk behaviour. Last, we included young people’s knowledge about HIV risk and other STIs in the final multivariate model to evaluate the independent influence of new and traditional media use on young people’s sexual risk behaviour, controlling for personal knowledge and socio-contextual factors. Additionally, we ascertained the media sources that had significant independent links to sexual risk behaviours, over and beyond other socio-contextual factors, as well as knowledge about HIV and other STIs. We adjusted for age in the logistic regression models because sexual risk behaviour and media use vary by age [87,88,89,90,91,92]. In addition, we were interested in understanding the influence of social factors on the link between unmarried young people's use of technology and media, and engagement in sexual risk behaviour. We performed all the data analysis in the Complex Samples Module in SPSS, version 28.0 (IBM Corporation, Armonk, NY, USA), and the level of significance was 0.05.

Results

Sociodemographic profile of the study participants

The results in Table 1, reveal that more than half of the young people in Angola, close to two-thirds in Cameroon, and more than 86% in South Africa were unmarried and sexually active. In contrast, only a fifth in Ethiopia and about a fourth in Mali were unmarried and sexually active. A greater percentage of youths in Angola and Mali were between 15 and 19 years old, rather than 20–24 years. More than half of unmarried sexually active young people in Mali and about two-thirds in Cameroon were girls, while more than 77% in Nigeria and 65% in South Africa were girls. A greater majority of young people in Angola, Cameroon, Nigeria, and South Africa had secondary education or higher. A good number of the youths in South Africa had secondary education or higher, and a greater percentage of youths in Ethiopia, Mali, and Nigeria were employed. A greater percentage of young people had access to the internet in Cameroon and South Africa. Across all the countries, most young people had mobile phones, and more than half of them watched television or listened to the radio in all the countries. In contrast, most youths did not read newspapers in all countries, except in South Africa where more than 66% read newspapers.

Table 1 Sociodemographic characteristics
Full size table

The frequency distribution of sexual risk behaviours among the youths (Table 2) indicates a greater percentage of young people had one sexual partner in the 12 months before the survey. About one-fifth of youths in Cameroon had two or more sexual partners, and up to 15% in South Africa had two or more sexual partners. About 70% of the young people in Angola, Mali, and Nigeria did not use any contraception or used unreliable contraceptive methods. Similarly, more than half in Cameroon and 49% in Ethiopia did not use any contraception or used unreliable contraceptive methods.

Table 2 Sexual risk behaviour among young people in Sub-Saharan Africa
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Association between the use of technology and media and sexual risk behaviour

The age-adjusted logistic regression models on the relationship between technology and media and sexual risk behaviour (Table 3) show that, in all six countries (Angola, Cameroon, Ethiopia, Mali, Nigeria, and South Africa), lack of access to technology and media was associated with lower odds of having two or more sexual partners. In Angola, youths who did not have access to the internet [(aOR = 0.68 (0.56–0.83), p < 0.001)], those who did not read newspapers [(0.74 (0.59–0.94), p = 0.01)], as well as those who did not own mobile phones [(aOR = 0.59 (0.48–0.72), p < 0.001)] were significantly less likely to have two or more sexual partners. Similarly, in Cameroon, Ethiopia, Mali, Nigeria, and South Africa lack of access to the internet or no mobile phone ownership was significantly associated with lower odds of having two or more sexual partners.

Table 3 Age-adjusted bivariate logistic regression media use and sexual risk behaviour
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On the other hand, in five out of the six countries, lack of access to the internet and no ownership of mobile phones was associated with higher odds of non-use or the use of unreliable methods of contraception. Lack of access to traditional media sources was also associated with higher odds of unreliable contraception or non-use of any contraceptive method in these five countries. In Cameroon, young people who did not have access to the internet, did not watch television, and did not listen to the radio were 96% (aOR = 1.96 (1.64–2.34), p = 0.000), 81% (aOR = 1.81 (1.36–2.41), p < 0.001), and 48% (aOR = 1.48 (1.24–1.76), p < 0.001) more likely to use unreliable contraceptive methods or not use any contraception at all. While lack of access to or non-use of both traditional and new media was significantly associated with engagement in transactional sex among both young women and young men in many countries, young men in Mali (aOR = 0.48 (0.24–0.98), p = 0.04) and South Africa (aOR = 0.24 (0.07–0.84), p = 0.02) who did not read newspapers were significantly less likely to report transactional sex. There was no significant association between technology and media use and engagement in transactional sex among young people in Ethiopia.

Relationship between new and traditional media use and sexual risk behaviour adjusting for socio-contextual factors and HIV and other STIs knowledge

The multivariate models reveal that socio-contextual factors modified the relationship between technology and media use and young people’s sexual risk behaviour. In many countries, the socio-economic class of families, young people’s place of residence, religion, educational attainment, and employment status significantly influenced the link between media use and sexual risk behaviour. However, ownership of phones had an independent influence on having multiple sexual partners in four out of the six countries, after adjusting for socio-contextual factors. This relationship persisted even after adjusting for HIV and other STIs knowledge (Table 4). Those who did not own a mobile phone were significantly less likely to have two or more sexual partners in Angola (aOR = 0.68 (0.55–0.83), p < 0.001); Cameroon (aOR = 0.66 (0.51–0.84), p < 0.001); Nigeria (aOR = 0.72 (0.56–0.93), p = 0.01), and South Africa (aOR = 0.69 (0.49–0.98), p = 0.03). In Mali, lack of access to the internet was significantly associated with lower odds of having had two or more sexual partners (aOR = 0.45 (0.29–0.70), p < 0.001).

Table 4 Relationship between media use and sexual behaviour adjusting for social factors, HIV and other STIs knowledge
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Similarly, social factors and HIV and other STI knowledge attenuated the relationship between media and contraceptive use; and after we accounted for HIV and other STI knowledge, those who did not read newspapers in Angola were 65% (aOR = 1.65 (1.26–2.15), p < 0.001), and in Nigeria were 85% (aOR = 1.89 (1.40–2.56), p < 0.001) more likely to use unreliable methods of contraception or not to use any form of contraception. Additionally, young men in Cameroon who did not own a phone were significantly less likely to engage in transactional sex (aOR = 0.53 (0.31–0.93), p = 0.02). With regards to traditional media use, young men in Mali who did not listen to radio were significantly less likely to have given cash or other gifts in exchange for sex (aOR = 0.41(0.18–0.94), p = 0.03). In contrast, their counterparts in South Africa were over five times (aOR = 5.33 (2.11–13.48), p < 0.001), and in Ethiopia were about four times more likely to engage in transactional sex (aOR = 3.60 (1.38–9.40), p = 0.009). On the other hand, young women in Nigeria who did not listen to the radio were 44% more likely (aOR = 1.44 (1.04–1.99), p = 0.02) to have engaged in transactional sex, and those who did not read newspapers and magazines were 77% more likely (aOR = 1.77 (1.67–2.69), p = 0.007) to have received cash, gift, or other materials in exchange for sex.

Discussion

We examined the link between traditional and new media use and adolescent sexual risk behaviour, accounting for the socio-contextual factors that influence young people’s sexual and reproductive risk behaviour in Sub-Saharan Africa. We also considered the influence of HIV and other STIs knowledge in the association between media use and young people’s sexual risk behaviour. The findings of our study underscore the importance of simultaneously considering the social context in which young people are embedded and the synergistic influence of these social forces on sexual risk behaviour among young people. While accounting for the contextual factors and knowledge about HIV and other STIs knowledge attenuated the link between media use and some sexual risk behaviour in many Sub-Saharan African countries, both new media, and traditional media use continued to contribute to many sexual risk behaviours among young people. Despite the influence of these contextual factors on the link between media use and adolescent sexual risk behaviour, there remained remarkable between-country and regional differences in the link between media use and many sexual risk behaviours.

Our study reveals that having owned a mobile phone had the strongest independent influence on having multiple sexual partners in many countries, after accounting for these contextual factors and HIV and other STIs knowledge. This finding may be expected considering the proliferation of uncensored sexually explicit materials in Sub-Saharan Africa [16, 17, 19, 93]. In addition, those who did not have access to the internet in Mali had lower odds of having had two or more sexual partners. Hence, young people who do not have access to these new media sources may be protected from the uncontrolled availability of sexually explicit materials in the region. Moreover, lack of phone ownership and access to the internet limit networking and social connection among young people; lower connectivity between youths who lack these new media sources may reduce their number of sexual partners, which has been reported in previous studies [16, 31, 47]. Given that many intervention programs take advantage of the widespread use of new media by young people to provide accurate digital sexual and reproductive health information, young people who do not have phones or lack access to the internet may be deprived of accessing sexual health information. Additionally, the lack of phone ownership and access to the internet by youths relates to widespread poverty and skewed wealth distribution in Sub-Saharan Africa, which continue to prevent many young people from accessing digital health services [10, 49, 77].

Further, simultaneously accounting for contextual factors and HIV and other STIs knowledge lessened the odds of non-use or the use of unreliable contraception that are associated with lack of media use. However, the use of unreliable contraception or non-use of contraceptive methods remained prevalent in many countries because of a lack of access to both traditional and new media. Our findings about the high prevalence of unreliable contraception or non-use of contraceptive methods do not match available evidence about the impact of mass media communications on improving contraceptive use, and the progress that has been made in meeting the contraceptive needs of young people in Sub-Saharan Africa [28, 94, 95]. It is possible many young people may not be reached by programs that utilize digital and traditional media to disseminate sexual risk reduction interventions. Our findings corroborate other studies that document how poverty and sociocultural practices impede contraceptive uptake in parts of Nigeria and some Sub-Saharan African countries [96, 97]. Thus, there is a need for country-specific programs, increased health education efforts, reduction in the cost of modern contraceptive methods, and provision of youth-friendly health services to enhance contraceptive uptake among young people. Overall, the reduction in many sexual risk behaviours corroborates existing evidence that sexual and reproductive health interventions, community engagement, and collaborative efforts between national governments and international agencies in the region have contributed to reducing sexual risk behaviour among young people [94, 98].

Those who did not read newspapers in Cameroon were less likely to use unreliable contraception or not use any contraception. Similarly, boys in South Africa who did not read newspapers were less likely to engage in transactional sex. Cameroon and South Africa are highly globalized countries, and the use of the internet and phone ownership is remarkably high among young people. Since only a few youths read newspapers, the use of new media and other traditional media sources may exert a greater influence on sexual risk behaviour in those countries. On the other hand, boys in Mali and South Africa who listened to the radio had a higher likelihood of having exchanged cash or gifts for sex. These two countries are at various stages of globalization, with South Africa being a highly globalized country. On the other hand, a greater percentage of young people in Mali who participated in the survey listened to the radio, and it has been reported in previous studies that radio is commonly used among young people in Mali [99]. In addition, young people may tune on to erotic music on the radio, and they may view erotic scenes in newspapers and magazines which some studies link to a heightened risk of sexual risk behaviour [31, 100].

Similarly, young women in Nigeria who did not listen to the radio nor read newspapers and magazines were more likely to exchange sex for cash, gifts, or other material gratification. This finding could be because of the higher percentage of young people in Nigeria who did not have access to traditional media sources, and less than half of young people had access to the Internet. Poverty and the desire to own a phone may motivate girls and young women to seek cash, or other material gifts in exchange for sex [63, 101]. Our findings about the independent influence of media use on young people’s sexual risk behaviour match existing evidence that gaps remain in meeting global targets for adolescent sexual and reproductive risk behaviour in the region [102]. Thus, intervention programs should take advantage of the pervasive use of traditional and new media among young people in the region to provide accurate and comprehensive sexual and reproductive health education so that young people can make informed sexual health decisions. Our findings also emphasize the need to advocate for policies and legislation that will control young people’s access to inappropriate sexually explicit materials on both new and traditional media sources. Given that many countries in Sub-Saharan Africa are at various stages of globalization, country-specific programs, and intervention efforts will address the unique influences of both traditional and new media on youth sexual risk behaviour in the region. Finally, programs that aim to promote young people’s sexual and reproductive health in the region should consider the social inequities in phone ownership and access to the internet, as well as access to other media sources. This could guide the provision of targeted intervention to the most vulnerable groups. Programs and intervention efforts should leverage the proliferation of web-based applications and the use of both traditional and new media by young people to disseminate accurate and comprehensive sexual and reproductive risk prevention information to young people.

We acknowledge that our study used cross-sectional data and thus we do not claim a causal relationship between media use and youth sexual risk behaviour. We also recognize that the socio-contextual factors we included in our model may not be exhaustive, given the myriad of social factors, and socio-cultural practices in Sub-Saharan Africa that influence health behaviours among young people. For instance, peer and family relationships may influence media use and sexual risk behaviour. These areas are worth exploring in future studies. Our study involved youths, aged 15 to 24 years, not younger adolescents, because the Demographic and Health Surveys do not include those aged 10–14 years. Despite these limitations, our study provides population-based evidence about the role of several contextual factors in the link between traditional and new media use, as well as the gaps that remain in preventing sexual and reproductive risk behaviour among young people in Sub-Saharan Africa.

Conclusion

Our findings reveal the importance of considering the embeddedness of young people within a wide array of intersecting socio-contextual factors that influence media use and engagement in sexual risk behaviour. We found that simultaneously accounting for socio-contextual factors and knowledge about HIV and other sexually transmitted infections attenuated the link between traditional and new media use and adolescent sexual risk behaviour in many Sub-Saharan African countries. However, media use (and lack of access to media) continues to be linked to sexual risk behaviour among young people in the region. Lack of access to traditional and new media sources links to unreliable contraception or non-use of any contraceptive methods. Further, young people, particularly boys who listened to the radio or read newspapers and magazines had higher odds of engaging in transactional sex in many countries. On the other hand, poverty, lack of access to sexual health information, and the desire to own mobile phones continue to expose young women to sexual risk behaviour. Young people who did not have mobile phones and lacked access to the internet were less likely to have multiple sexual partners in many countries of Sub-Saharan Africa. While progress has been made in reducing sexual risk behaviour among young people, gaps remain between countries and regions of Sub-Saharan Africa. These findings have implications for country-specific and tailored sexual and reproductive health intervention programs to meet the sexual and reproductive information needs of young people from diverse social backgrounds using both traditional and new media.

Availability of data and materials

Data that support the findings of the study are provided by the Demographic and Health Surveys (DHS) Program of the United States Agency for International Development and are available upon reasonable request and permission from the DHS Program. No datasets were generated or analysed during the current study.

References

  1. Kharsany ABM, Karim QA. HIV infection and AIDS in Sub-Saharan Africa: current status, challenges and opportunities. Open AIDS J. 2016;10:34–48.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Melesse DY, Cane RM, Mangombe A, Ijadunola MY, Manu A, Bamgboye E, et al. Inequalities in early marriage, childbearing, and sexual debut among adolescents in sub-Saharan Africa. Reprod Health. 2021;18:12.

    Article  Google Scholar 

  3. Morris JL, Rushwan H. Adolescent sexual and reproductive health: the global challenges. Int J Gynecol Obstet. 2015;131:S40–2.

    Article  Google Scholar 

  4. C Browning JC Malave 2015. Adolescent sexual risk International Encyclopedia of the Social & Behavioral Sciences. https://doi.org/10.1016/B978-0-08-097086-8.35003-6

  5. Viner RM, Ozer EM, Denny S, Marmot M, Resnick M, Fatusi A, et al. Adolescence and the social determinants of health. The Lancet. 2012;379:1641–52.

    Article  Google Scholar 

  6. Spear LP. Adolescent neurodevelopment. J Adolesc Health. 2013. https://doi.org/10.1016/j.adohealth.2012.05.006.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Liang M, Simelane S, Fortuny Fillo G, Chalasani S, Weny K, Salazar Canelos P, et al. The state of adolescent sexual and reproductive health. J Adolesc Health. 2019. https://doi.org/10.1016/j.adohealth.2019.09.015.

    Article  PubMed  Google Scholar 

  8. Sawyer SM, Azzopardi PS, Wickremarathne D, Patton GC. The age of adolescence. Lancet Child Adolesc Health. 2018. https://doi.org/10.1016/S23352-4642(18)30022-1.

    Article  PubMed  Google Scholar 

  9. Abdullahi AA, Abdulquadri NT. New media and adolescents’ sexual behaviour in sub-sahara Africa: linking theories to realities. SAGE Open. 2018. https://doi.org/10.1177/2158244018804606.

    Article  Google Scholar 

  10. Mayo-Wilson JLL, Kang BA, Mathai M, Mak’anyengo MO, Ssewamala FM. Mobile phone access, willingness, and usage for HIV-related services among young adults living in informal urban settlements in Kenya: A cross-sectional analysis. Int J Med Inf. 2022. https://doi.org/10.1016/j.ijmedinf.2022.104728.

    Article  Google Scholar 

  11. Benvenuti M, Wright M, Naslund J, Miers AC. How technology use is changing adolescents’ behaviors and their social, physical, and cognitive development. Curr Psychol. 2023;42:16466–9.

    Article  Google Scholar 

  12. Livingston JA, Testa M, Windle M, Bay-Cheng LY. Sexual risk at first coitus: does alcohol make a difference? J Adolesc. 2015;43:148–58.

    Article  PubMed  PubMed Central  Google Scholar 

  13. O’Keeffe GS, Clarke-Pearson K, Mulligan DA, Altmann TR, Brown A, Christakis DA, et al. Clinical report - The impact of social media on children, adolescents, and families. Pediatrics. 2011. https://doi.org/10.1542/peds.2011-0054.

    Article  PubMed  Google Scholar 

  14. Hagg E, Dahinten VS, Currie LM. The emerging use of social media for health-related purposes in low and middle-income countries: a scoping review. Int J Med Inf. 2018. https://doi.org/10.1016/j.ijmedinf.2018.04.010.

    Article  Google Scholar 

  15. Owens EW, Behun RJ, Manning JC, Reid RC. The impact of internet pornography on adolescents: a review of the research. Sex Addict Compulsivity. 2012;19:99–122.

    Article  Google Scholar 

  16. Asekun-Olarinmoye E, Asekun-Olarinmoye OS, Adebimpe W, Omisore AG. Effect of mass media and internet on the sexual behavior of undergraduates in Osogbo metropolis. Southwestern Nigeria Adolesc Health Med Ther. 2014. https://doi.org/10.2147/AHMT.S54339.

    Article  PubMed  Google Scholar 

  17. Habesha T, Aderaw Z, Lakew S. Assessment of exposure to sexually explicit materials and factors associated with exposure among preparatory school youths in Hawassa City, Southern Ethiopia: a cross-sectional institution-based survey. Reprod Health. 2015;12:1.

    Article  Google Scholar 

  18. Kimemia KA. Social media and teenage pregnancy among students in secondary schools in Imenti North Sub-County, Meru County. Kenya Int J Sci Res Manag. 2016. https://doi.org/10.18535/IJSRM/V419.18.

    Article  Google Scholar 

  19. Banougnin BH, Toska E, Maughan-Brown B, Rudgard W, Hertzog L, Jochim J, et al. Associations of social media and health content use with sexual risk behaviours among adolescents in South Africa. Sex Reprod Health Matter. 2023;31:226.

    Google Scholar 

  20. Fevriasanty FI, Suyanto B, Soedirham O, Sugihartati R, Ahsan A. Effects of social media exposure on adolescent sexual attitudes and behavior: a systematic review. Int J Public Health Sci. 2021;10:272–80.

    Google Scholar 

  21. Kunnuji M. Risk-bearing sexuality within the context of internet use among young people in Lagos metropolis. Jnl Hum & Soc Sci. 2011;3:1.

    Google Scholar 

  22. Bukenya JN, Nakafeero M, Ssekamatte T, Isabirye N, Guwatudde D, Fawzi WW. Sexual behaviours among adolescents in a rural setting in eastern Uganda: a cross-sectional study. Trop Med Int Health. 2020. https://doi.org/10.1111/tmi.13329.

    Article  PubMed  Google Scholar 

  23. Makgale OL, Plattner IE. Sexting and risky sexual behaviours among undergraduate students in Botswana: an exploratory study. Cyberpsychology. 2017;11:10.

    Article  Google Scholar 

  24. Doyle AM, Bandason T, Dauya E, McHugh G, Grundy C, Dringus S, et al. Mobile phone access and implications for digital health interventions among adolescents and young adults in Zimbabwe: cross-sectional survey. JMIR MHealth UHealth. 2021;9:10.

    Article  Google Scholar 

  25. Toffolutti V, Ma H, Menichelli G, Berlot E, Mencarini L, Aassve A. How the internet increases modern contraception uptake: evidence from eight sub-Saharan African countries. BMJ Glob Health. 2020;5:10.

    Article  Google Scholar 

  26. Hampshire K, Porter G, Owusu SA, Mariwah S, Abane A, Robson E, et al. Informal m-health: How are young people using mobile phones to bridge healthcare gaps in Sub-Saharan Africa? Soc Sci Med. 2015. https://doi.org/10.1016/j.socscimed.2015.07.033.

    Article  PubMed  Google Scholar 

  27. Tebb KP, Pica G, Twietmeyer L, Diaz A, Brindis CD. Innovative approaches to address social determinants of health among adolescents and young adults. Health Equity. 2018;2:321–8.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Babalola S, Figueroa ME, Krenn S. Association of mass media communication with contraceptive use in Sub-Saharan Africa: a meta-analysis of demographic and health surveys. J Health Commun. 2017;22:885–95.

    Article  PubMed  Google Scholar 

  29. Kawuki J, Gatasi G, Sserwanja Q, Mukunya D, Musaba MW. Comprehensive knowledge about HIV/AIDS and associated factors among adolescent girls in Rwanda: a nationwide cross-sectional study. BMC Infect Dis. 2023;23:1–14.

    Article  Google Scholar 

  30. Somefun OD, Wandera SO, Odimegwu C. Media exposure and HIV testing among youth in Sub-Saharan Africa: evidence from demographic and health surveys (DHS). Reprod Health Sub-Sahar Afr. 2019;9:1–13.

    Google Scholar 

  31. Oladeji D. Media influence as predictors of adolescent’s sexual risky behaviour in Nigeria. Womens Health. 2017;5:192–6.

    Google Scholar 

  32. Femi-Adebayo TT, Kuyinu Y, Adejumo OA, Goodman O. Factors affecting utilization of youth-friendly health services in Lagos State. Nigeria Int J Adolesc Med Health. 2019;31:20160.

    Google Scholar 

  33. Geary RS, Webb EL, Clarke L, Norris SA. Evaluating youth-friendly health services: young people’s perspectives from a simulated client study in urban South Africa. Glob Health Action. 2015;8:1.

    Article  CAS  Google Scholar 

  34. James S, Pisa PT, Imrie J, Beery MP, Martin C, Skosana C, et al. Assessment of adolescent and youth-friendly services in primary healthcare facilities in two provinces in South Africa. BMC Health Serv Res. 2018;18:1–10.

    Article  CAS  Google Scholar 

  35. Odo AN, Samuel ES, Nwagu EN, Nnamani PO, Atama CS. Sexual and reproductive health services (SRHS) for adolescents in Enugu state, Nigeria: a mixed methods approach. BMC Health Serv Res. 2018;18:1–12.

    Article  Google Scholar 

  36. Ogu R, Maduka O, Alamina F, Adebiyi O, Agala V, Eke G, et al. Mainstreaming youth-friendly health services into existing primary health care facilities: experiences from South-South Nigeria. Int J Adolesc Med Health. 2018. https://doi.org/10.1515/ijamh-2017-0151.

    Article  PubMed  Google Scholar 

  37. Ankunda D, Asiimwe JB. Determinants of comprehensive knowledge of HIV/AIDS among women of reproductive age (15–49) in Uganda. Int J Commun Med Public Health. 2017;4:3530–3530.

    Article  Google Scholar 

  38. Dadzie LK, Agbaglo E, Okyere J, Aboagye RG, Arthur-Holmes F, Seidu AA, et al. Self-reported sexually transmitted infections among adolescent girls and young women in sub-Saharan Africa. Int Health. 2022;14:545–53.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Shamu S, Khupakonke S, Farirai T, Slabbert J, Chidarikire T, Guloba G, et al. Knowledge, attitudes, and practices of young adults towards HIV prevention: an analysis of baseline data from a community-based HIV prevention intervention study in two high HIV burden districts. South Africa BMC Public Health. 2020;20:1–10.

    Google Scholar 

  40. Teshale AB, Yeshaw Y, Alem AZ, Ayalew HG, Liyew AM, Tessema ZT, et al. Comprehensive knowledge about HIV/AIDS and associated factors among women of reproductive age in sub-Saharan Africa: a multilevel analysis using the most recent demographic and health survey of each country. BMC Infect Dis. 2022;22:1–10.

    Article  Google Scholar 

  41. Duru C, Ubajaka C, Nnebue C, Ifeadike C, Okoro O. Sexual behaviour, and practices among secondary school adolescents in Anambra State. Nigeria Afrimedic J. 2010;1:22–7.

    Google Scholar 

  42. Baya SY, Mberia HK, Yaah Baya Is S, Scholar P. The impact of television viewing in influencing adolescents sexual behaviour. Int J Sci Res Publ. 2014;4:11.

    Google Scholar 

  43. Ferede TA, Muluneh AG, Wagnew A, Walle AD. Prevalence, and associated factors of early sexual initiation among youth female in sub-Saharan Africa: a multilevel analysis of recent demographic and health surveys. BMC Womens Health. 2023;12:23.

    Google Scholar 

  44. Hailegebreal S, Gilano G, Seboka BT, Sidelil H, Awol SM, Haile Y, et al. Prevalence and associated factors of early sexual initiation among female youth in East Africa: further analysis of recent demographic and health survey. BMC Womens Health. 2022. https://doi.org/10.1186/s12905-022-01895-8.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Wana GW, Arulogun O, Roberts A, Kebede AS. Predictors of risky sexual behaviour among pre-college students in Adama town. Ethiopia Pan Afr Med J. 2019;33:1–12.

    Google Scholar 

  46. Murewanhema G, Musuka G, Moyo P, Moyo E, Dzinamarira T. HIV and adolescent girls and young women in sub-Saharan Africa: a call for expedited action to reduce new infections. IJID Reg. 2022. https://doi.org/10.1016/j.ijregi.2022.08.009.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Nalugoda F, Kreniske P, Hofer S, Zhong X, Wei Y, Grilo SA, et al. Cell phones, sexual behaviors and HIV prevalence in Rakai, Uganda: a cross-sectional analysis of longitudinal data. AIDS Behav. 2020;24:1574–1574.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Santhya KG, Jejeebhoy SJ. Sexual and reproductive health and rights of adolescent girls: evidence from low- and middle-income countries. Glob Public Health. 2015;10:189–221.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Chib A, Wilkin H, Hoefman B. Vulnerabilities in mHealth implementation: a Ugandan HIV/AIDS SMS campaign. Glob Health Promot. 2013;20(SUPPL. 1):26–32.

    Article  PubMed  Google Scholar 

  50. Commission on Social Determinants of Health. CSDH final report: closing the gap in a generation: health equity through action on the social determinants of health. 2008. https://www.who.int/publications/i/item/WHO-IER-CSDH-08.1. Accessed 25 Mar 2023.

  51. Marmot M, Allen JJ. Social determinants of health equity. Am J Public Health. 2014;104(SUPPL. 4):S517–S517.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Folayan MO, Adebajo S, Adeyemi A, Ogungbemi KM. Differences in sexual practices, sexual behavior and HIV risk profile between adolescents and young persons in rural and urban Nigeria. PLoS ONE. 2015;10:12.

    Article  Google Scholar 

  53. Odimegwu C, Somefun OD. Ethnicity, gender, and risky sexual behaviour among Nigerian youth: an alternative explanation. Reprod Health. 2017;14:1–15.

    Article  Google Scholar 

  54. Bowleg L. The problem with the phrase women and minorities: intersectionality-an important theoretical framework for public health. Am J Public Health. 2012;102:1267–73.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Crenshaw KW. Demarginalizing the intersection of race and sex: A Black feminist critique of antidiscrimination doctrine, feminist theory, and antiracist politics. University of Chicago Legal Forum; 1989. http://chicagounbound.uchicago.wedu/uc1f/vol1989/iss1/8. Accessed 24 Feb 2022.

  56. Crenshaw KW. Mapping the margins: intersectionality, identity politics, and violence against women of color. Stanford Law Rev. 1991;11:1241–99.

    Article  Google Scholar 

  57. Richman LS, Zucker AN. Quantifying intersectionality: an important advancement for health inequality research. Soc Sci Med. 2019;226:246–8.

    Article  PubMed  Google Scholar 

  58. Mufune P. Poverty and HIV/AIDS in Africa: specifying the connections. Soc Theory Health. 2015;13:1–29.

    Article  Google Scholar 

  59. Pascoe SJS, Langhaug LF, Mavhu W, Hargreaves J, Jaffar S, Hayes R, et al. Poverty, food insufficiency and HIV infection and sexual behaviour among young rural Zimbabwean women. PLoS ONE. 2015;10:e0115290.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Choudhry V, Ambresin AE, Nyakato VN, Agardh A. Transactional sex and HIV risks—evidence from a cross-sectional national survey among young people in Uganda. Glob Health Action. 2015;8:1–13.

    Article  Google Scholar 

  61. Kamndaya M, Thomas L, Vearey J, Sartorius B, Kazembe L. Material deprivation affects high sexual risk behavior among young people in urban slums. South Africa J Urban Health. 2014;91:581–91.

    Article  PubMed  Google Scholar 

  62. Kyegombe N, Meiksin R, Wamoyi J, Heise L, Stoebenau K, Buller AM. Sexual health of adolescent girls and young women in Central Uganda: exploring perceived coercive aspects of transactional sex. Sex Reprod Health Matters. 2020;28:1700770.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Mensah EO. When you open your legs, you eat: the discourse of transactional sex among female youth in Nigeria. Sex Cult. 2020;24:543–60.

    Article  Google Scholar 

  64. Appiah CK, Dowou RK, Balame SK, Adzigbli LA, Yeboah PA, Aboagye RG, et al. Self-reported sexually transmitted infections among adolescent girls and young women in Mali: analysis of prevalence and predictors. BMJ Open. 2023;13:1–10.

    Article  Google Scholar 

  65. Chandra-Mouli V, Neal S, Moller AB. Adolescent sexual and reproductive health for all in sub-Saharan Africa: a spotlight on inequalities. Reprod Health. 2021;18(Suppl 1):1–4.

    Google Scholar 

  66. Melesse DY, Mutua MK, Choudhury A, Wado YD, Faye CM, Neal S, et al. Adolescent sexual and reproductive health in sub-Saharan Africa: Who is left behind? BMJ Glob Health. 2020;5:e002231–e002231.

    Article  PubMed  PubMed Central  Google Scholar 

  67. The Demographic and Health Surveys Program. Guide to DHS statistics DHS-7 (version 2). 2020. https://www.dhsprogram.com/pubs/pdf/DHSG1/Guide_to_DHS_Statistics_DHS-7_v2.pdf. Accessed 28 May 2023.

  68. The DHS Program. The Demographic and Health Surveys Program. 2023. https://dhsprogram.com/. Accessed 14 Nov 2023.

  69. Adde KS, Dickson KS, Ameyaw EK, Amo-Adjei J. Contraception needs and pregnancy termination in sub-Saharan Africa: a multilevel analysis of demographic and health survey data. Reprod Health. 2021;18:177.

    Article  PubMed  PubMed Central  Google Scholar 

  70. Phillips SJ, Mbizvo MT. Empowering adolescent girls in Sub-Saharan Africa to prevent unintended pregnancy and HIV: A critical research gap. Int J Gynecol Obstet. 2016;132:1.

    Article  Google Scholar 

  71. Wado YD, Sully EA, Mumah JN. Pregnancy, and early motherhood among adolescents in five East African countries: a multi-level analysis of risk and protective factors. BMC Pregnancy Childbirth. 2019;19:213.

    Article  Google Scholar 

  72. Ajayi AI, Adeniyi OV, Akpan W. Use of traditional and modern contraceptives among childbearing women: findings from a mixed methods study in two southwestern Nigerian states. BMC Public Health. 2018;18:101.

    Article  Google Scholar 

  73. Ayyuba R, Asma’u AR. The role of traditional contraceptive methods in family planning among women attending primary health care centers in Kano. Ann Afr Med. 2018;17:189–95.

    Article  Google Scholar 

  74. Ross JA. Contraceptive use, access to methods, and program efforts in urban areas. Front Glob Womens Health. 2021;2:13.

    Article  Google Scholar 

  75. Rossier C, Corker J. Contemporary use of traditional contraception in Sub-Saharan Africa. Popul Dev Rev. 2017;43:192–215.

    Article  PubMed  PubMed Central  Google Scholar 

  76. Ajaero CK, Odimegwu C, Ajaero ID, Nwachukwu CA. Access to mass media messages, and use of family planning in Nigeria: a spatio-demographic analysis from the 2013 DHS. BMC Public Health. 2016;16:21.

    Article  Google Scholar 

  77. Iacoella F, Gassmann F, Tirivayi N. Which communication technology is effective for promoting reproductive health? Television, radio, and mobile phones in sub-Saharan Africa. PLoS ONE. 2022. https://doi.org/10.1371/journal.pone.0272501.

    Article  PubMed  PubMed Central  Google Scholar 

  78. Shasha L, Phiri M, Namayawa S, Sikaluzwe M, Nakazwe C, Lemba M, et al. Prevalence and factors associated with early childbearing in Sub-saharan Africa: evidence from demographic and health surveys of 31 countries. BMC Womens Health. 2023;23:301.

    Article  Google Scholar 

  79. Jackson F, Haile ZT. Association between educational attainment and risky sexual behaviour among Ghanaian female youth. Afr Health Sci. 2023;23:301–8.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Lewis L, Kharsany ABM, Humphries H, Maughan-Brown B, Beckett S, Govender K, et al. HIV incidence and associated risk factors in adolescent girls and young women in South Africa: a population-based cohort study. PLoS ONE. 2022;17:1–14.

    Article  Google Scholar 

  81. Mohr R, Carbajal J, Sharma BB. The influence of educational attainment on teenage pregnancy in low-income countries: a systematic literature review. J Soc Work Glob Community. 2019;4:19–31.

    Google Scholar 

  82. Shangase N, Kharsany ABM, Ntombela NP, Pettifor A, McKinnon LR. A systematic review of randomized controlled trials of school-based interventions on sexual risk behaviors and sexually transmitted infections among young adolescents in Sub-Saharan Africa. AIDS Behav. 2021;25:3669–86.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Zuilkowski SS, Jukes MCH. The impact of education on sexual behavior in sub-Saharan Africa: A review of the evidence. AIDS Care. 2012;24:562–76.

    Article  PubMed  Google Scholar 

  84. Ali MM, Merdad L, Bellizzi S. Socioeconomic variations in risky sexual behavior among adolescents in 14 Sub-Saharan Africa countries who report ever having had sex. Int J Equity Health. 2021;20:1–7.

    Article  Google Scholar 

  85. Wangamati CK. Comprehensive sexuality education in Sub-Saharan Africa: adaptation and implementation challenges in universal access for children and adolescents. Sex Reprod Health Matt. 2020;28:12.

    Google Scholar 

  86. Sani AS, Abraham C, Denford S, Ball S. School-based sexual health education interventions to prevent STI/HIV in sub-Saharan Africa: a systematic review and meta-analysis. BMC Public Health. 2016;16:1–26.

    Article  Google Scholar 

  87. Adedini SA, Mobolaji JW, Alabi M, Fatusi AO. Changes in contraceptive and sexual behaviours among unmarried young people in Nigeria: Evidence from nationally representative surveys. PLoS ONE. 2021;16:1.

    Article  Google Scholar 

  88. Agaba P, Makai R, Bankat C, Chebu P, Apena T, Iyaji-Paul O, et al. Sexual behavior, and risk factors for HIV infection among young people aged 15–24 years in North-Central Nigeria. J Med Trop. 2016;18:60–60.

    Article  Google Scholar 

  89. Andreassen CS, Pallesen S, Griffiths MD. The relationship between addictive use of social media, narcissism, and self-esteem: findings from a large national survey. Addict Behav. 2017;64:287–93.

    Article  PubMed  Google Scholar 

  90. Berhan Y, Berhan A. A meta-analysis of risky sexual behaviour among male youth in developing countries. AIDS Res Treat. 2015. https://doi.org/10.1155/2015/580961.

    Article  PubMed  PubMed Central  Google Scholar 

  91. Chassiakos YR, Radesky J, Christakis D, Moreno MA, Cross C, Hill D, et al. Children and adolescents and digital media. Pediatrics. 2016;138:1.

    Google Scholar 

  92. Mabaso M, Sokhela Z, Mohlabane N, Chibi B, Zuma K, Simbayi L. Determinants of HIV infection among adolescent girls and young women aged 15–24 years in South Africa: A 2012 population-based national household survey. BMC Public Health. 2018;18:1–7.

    Article  Google Scholar 

  93. Nnebue CC, Okolo EH, Zimughan JE, Onyia CP, Ugwokpe LA. social media and sexual behaviour: a study of undergraduate students in a public university in Imo State. Southeast Nigeria Asian J Med Health. 2022;20(9):56–66.

    Article  Google Scholar 

  94. Chandra-Mouli V, Akwara E. Improving access to and use of contraception by adolescents: What progress has been made, what lessons have been learned, and what are the implications for action? Best Pract Res Clin Obstet Gynaecol. 2020. https://doi.org/10.1016/j.bpobgyn.2020.04.003.

    Article  PubMed  PubMed Central  Google Scholar 

  95. Onukwugha FI, Smith L, Kaseje D, Wafula C, Kaseje M, Orton B, et al. The effectiveness and characteristics of mHealth interventions to increase adolescent’s use of Sexual and Reproductive Health services in Sub-Saharan Africa: a systematic review. PLoS ONE. 2022;17:1.

    Article  Google Scholar 

  96. James PB, Osborne A, Babawo LS, Bah AJ, Margao EK. The use of condoms and other birth control methods among sexually active school-going adolescents in nine sub-Saharan African countries. BMC Public Health. 2022;22:1–13.

    Article  Google Scholar 

  97. Taiwo MO, Oyekenu O, Hussaini R. Understanding how social norms influence access to and utilization of adolescent sexual and reproductive health services in Northern Nigeria. Front Sociol. 2023;8:1.

    Article  Google Scholar 

  98. Azzopardi PS, Hearps SJC, Francis KL, Kennedy EC, Mokdad AH, Kassebaum NJ, et al. Progress in adolescent health and wellbeing: tracking 12 headline indicators for 195 countries and territories, 1990–2016. The Lancet. 2019;393:1101–18.

    Article  Google Scholar 

  99. Asare BYA, Zegeye B, Ahinkorah BO, Ameyaw EK, Seidu AA, Yaya S. Early sexual debut and its associated factors among young women aged 15–24 in Mali: a multilevel analysis. Arch Sex Behav. 2023;52:2491–502.

    Article  PubMed  Google Scholar 

  100. Miller AN, Nalugya E, Gabolya C, Lagot S, Mulwanya R, Kiva J, et al. Ugandan adolescents’ sources, interpretation, and evaluation of sexual content in entertainment media programming. Sex Educ. 2016;16:707–20.

    Article  Google Scholar 

  101. Stark L. Transactional sex and mobile phones in a Tanzanian slum. J Eur Ethnol. 2019;46:1.

    Google Scholar 

  102. Chandra-Mouli V, Ferguson BJ, Plesons M, Paul M, Chalasani S, Amin A, et al. The political, research, programmatic, and social responses to adolescent sexual and reproductive health and rights in the 25 years since the International on population and development. J Adolesc Health. 2019;65:S16-40.

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors extend special thanks to the Demographic and Health Surveys (DHS) Program for access to the DHS datasets.

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  1. School of Nursing, University of British Columbia, T201-2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada

    Helen Uche Okoye & Elizabeth Saewyc

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HUO conceived the study, designed the study, interpreted the data, performed the statistical analyses, and wrote the first and final draft of the manuscript. ES guided the statistical analyses and critically reviewed the draft of the manuscript. All authors reviewed the manuscript.

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Okoye, H.U., Saewyc, E. Influence of socio-contextual factors on the link between traditional and new media use, and young people’s sexual risk behaviour in Sub-Saharan Africa: a secondary data analysis. Reprod Health 21, 138 (2024). https://doi.org/10.1186/s12978-024-01868-0

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Reproductive Health

ISSN: 1742-4755