Youth sexual behaviour in South Africa: social disorganisation as an alternative explanation

Abstract

Introduction Youths’ consistent engagements in risky sexual behaviour continue to be a source of concern for parents, researchers, practitioners and policymakers. Several researchers argue that a high proportion of youths that engaged in risky sexual behaviours were influenced by risk factors at the individual, household/family and community/neighbourhood levels. However, very few studies have explored the influence of community-level factors associated with risky sexual behaviour among young people across genders in South Africa. Currently, most efforts are directed towards addressing individual-level factors at the expense of not addressing community-level issues such as social disorganisation, contributing to risky sexual behaviours among youths across genders in South Africa. The question of how socially disorganised societies/communities create adolescents’ unfavourable sexual behaviour in the modern world has remained less explored across genders in South Africa. Specifically, the purpose of this study was to understand adolescents’ sexual behaviour of youths aged between 15–24 years across genders in South Africa and explain the risk factors associated with them through the lens of social disorganisation-related factors. Further, it was to explore possible pathways through which some of these social disorganisation factors led to adolescents’ risky sexual behaviour in South Africa. The risky sexual behaviours explored in this study were multiple sexual behaviours and inconsistent/lack of condom use.

Theoretical Framework The study was situated within the confines of the social disorganisation theory. The theory argues that social disorganisation factors such as community poverty, residential instability, family dysfunction and race/ethnic heterogeneity in certain neighbourhoods diminish community attachments, including social norms and social ties, by weakening community-level social control of crime devices. Although the social disorganisation theory was originally applied to crime and delinquency, researchers have applied the theory to different behavioural studies such as risk behaviours among adolescents and youths, sexual and gender-based violence, rape and educational behaviour. The theory identifies places and community structures responsible for the creation of conditions that are favourable or unfavourable to adolescents’ behaviour. Specifically, the study would have been better explored through a concurrent triangulation approach, but due to the terrain

of South African communities and available resources to carry out the research, I decided to adopt an analytical cross-sectional method that made use of a quantitative approach to examine the influence of social disorganisation factors that are associated with risky sexual behaviours among youths across genders in South Africa,

Data and Methods The data source that was used in this study was the 2016 South Africa Demographic and Health Survey (SADHS) which provides adequate information on knowledge, perceptions and sexual behaviours of youths aged between 15–24 years in South Africa. Specifically, the SADHS obtained information on the knowledge and perceptions of the Human Immuno-Deficiency Virus, sexual debut, patterns and partner characteristics and condom use. The 2016 SADHS was nationally representative and adopted a multistage cluster sampling design. The survey made use of the sampling frame from the Statistics South Africa Master Sample Frame, which was created using census 2011 enumeration areas. Due to the geographical hierarchy structure of the census that linked enumeration areas to administrative boundaries, information was available at the municipal, district and provincial levels in the survey. The surveys involved a multistage cluster sampling design, with clusters selected from the enumeration areas, and households selected from the clusters. For instance, there were 750 clusters also known as primary sampling units (PSUs), selected from the 26 sampling strata, which included 468 urban, 224 traditional and 58 farm areas. The selected sample of youths was 2 621 females and 1 268 males, giving a total of 3 889 youths who had never married aged between 15–24 years of age.

Key findings Objective 1: Individual and family-level correlates of risky sexual behaviour The frequency distribution showed that risky sexual behaviours were found to operate at both micro and macro levels. The findings showed that at the micro level, the impact of demographic and socioeconomic characteristics on young people’s involvement in risky sexual behaviour was evident across genders. Although differences were minor, young males were shown to be more exposed to risky sexual behaviour than females. In addition, the independent effect of age on risky sexual behaviour indicates that young people between the ages of 20–24 years were found to of South African communities and available resources to carry out the research, I decided to adopt an analytical cross-sectional method that made use of a quantitative approach to examine the influence of social disorganisation factors that are associated with risky sexual behaviours among youths across genders in South Africa,

Data and Methods The data source that was used in this study was the 2016 South Africa Demographic and Health Survey (SADHS) which provides adequate information on knowledge, perceptions and sexual behaviours of youths aged between 15–24 years in South Africa. Specifically, the SADHS obtained information on the knowledge and perceptions of the Human Immuno-Deficiency Virus, sexual debut, patterns and partner characteristics and condom use. The 2016 SADHS was nationally representative and adopted a multistage cluster sampling design. The survey made use of the sampling frame from the Statistics South Africa Master Sample Frame, which was created using census 2011 enumeration areas. Due to the geographical hierarchy structure of the census that linked enumeration areas to administrative boundaries, information was available at the municipal, district and provincial levels in the survey. The surveys involved a multistage cluster sampling design, with clusters selected from the enumeration areas, and households selected from the clusters. For instance, there were 750 clusters also known as primary sampling units (PSUs), selected from the 26 sampling strata, which included 468 urban, 224 traditional and 58 farm areas. The selected sample of youths was 2 621 females and 1 268 males, giving a total of 3 889 youths who had never married aged between 15–24 years of age.

Key findings Objective 1: Individual and family-level correlates of risky sexual behaviour The frequency distribution showed that risky sexual behaviours were found to operate at both micro and macro levels. The findings showed that at the micro level, the impact of demographic and socioeconomic characteristics on young people’s involvement in risky sexual behaviour was evident across genders. Although differences were minor, young males were shown to be more exposed to risky sexual behaviour than females. In addition, the independent effect of age on risky sexual behaviour indicates that young people between the ages of 20–24 years were found to of South African communities and available resources to carry out the research, I decided to adopt an analytical cross-sectional method that made use of a quantitative approach to examine the influence of social disorganisation factors that are associated with risky sexual behaviours among youths across genders in South Africa,

Data and Methods The data source that was used in this study was the 2016 South Africa Demographic and Health Survey (SADHS) which provides adequate information on knowledge, perceptions and sexual behaviours of youths aged between 15–24 years in South Africa. Specifically, the SADHS obtained information on the knowledge and perceptions of the Human Immuno-Deficiency Virus, sexual debut, patterns and partner characteristics and condom use. The 2016 SADHS was nationally representative and adopted a multistage cluster sampling design. The survey made use of the sampling frame from the Statistics South Africa Master Sample Frame, which was created using census 2011 enumeration areas. Due to the geographical hierarchy structure of the census that linked enumeration areas to administrative boundaries, information was available at the municipal, district and provincial levels in the survey. The surveys involved a multistage cluster sampling design, with clusters selected from the enumeration areas, and households selected from the clusters. For instance, there were 750 clusters also known as primary sampling units (PSUs), selected from the 26 sampling strata, which included 468 urban, 224 traditional and 58 farm areas. The selected sample of youths was 2 621 females and 1 268 males, giving a total of 3 889 youths who had never married aged between 15–24 years of age.

Key findings Objective 1: Individual and family-level correlates of risky sexual behaviour The frequency distribution showed that risky sexual behaviours were found to operate at both micro and macro levels. The findings showed that at the micro level, the impact of demographic and socioeconomic characteristics on young people’s involvement in risky sexual behaviour was evident across genders. Although differences were minor, young males were shown to be more exposed to risky sexual behaviour than females. In addition, the independent effect of age on risky sexual behaviour indicates that young people between the ages of 20–24 years were found to engage in risky sexual behaviour more than those between the ages of 15–19 years. The findings showed that becoming older was not a protective factor for engaging in risky sexual behaviour for both male and female youths. Several studies have documented the relationship between peoples’ age and their exposure to risky sexual behaviour. The possible explanations for the results could be attributed to the fact that older youth tend to have more confidence as well as better knowledge and experience about risks in a sexual relationship, which might influence their action to engage in risky sexual behaviour. They are also capable of withstanding any sociocultural norms and values preventing them from engaging in risky sexual behaviour that exists in the environment in which they live.

Objective 2: Effects of community social disorganisation-level factors and risky sexual behaviour among young people Overall, the findings supported the social disorganisation theory (model) based on explaining variations that exist across neighbourhoods where young people live. The theory identifies neighbourhood poverty, residential mobility due to migration, family dysfunction, race/ethnic diversity and community literacy level as the main structural factors that reduce communities’ ability to regulate themselves, most especially the activities of young people, which in turn leads to risky sexual behaviour. For instance, individuals who reside in disadvantaged communities may experience these specific elements to the degree that they may influence them to engage in risky sexual behaviour. Previous studies have consistently found that some factors such as family dysfunction, residential mobility, neighbourhood poverty and ethnic and racial diversities in disorganised communities can influence an individual to engage in risky sexual behaviour. This study found that female adolescents living in a community with a high proportion of literate parents, tend to engage in RSB, unlike male youths that have fewer chances of engaging in risky sexual behaviour. This indicates that residing in a community with a high proportion of literate parents does not prevent RSB among female youths in South Africa.

Objective 3: Pathways through which social disorganisation factors influence RSB among young people in South Africa What is noteworthy in this study was the investigation of the independent association between social disorganisation-related factors and the outcome variables (multiple sexual partnerships and inconsistent condom use) to see how other variables (individual and family-level factors) influence this relationship. In each of the social disorganisation models, age, educational attainments, employment status and household size were the highly significant influences of RSB among youths. The study indicates that adolescent sexual risk behaviours in South Africa may worsen because of the link between family dysfunction, neighbourhood poverty and community literacy levels. Such a pattern of associations could be explained by the probability of adolescents from intact families (presence of father and mother) living in a low-poverty neighbourhood and also engaging in RSB even with the presence of both parents. Despite the high literacy level in the community (a high proportion can read and write), which should have provided better access to contraceptive information (through radio, the internet, TV etc), inadequate parental control over media use can make it more likely that youths will engage in RSB. These findings may not be entirely surprising given the proportion of youths congregating in the neighbourhood who have adequate media access (internet, radio, TV) without proper control, either from their father or mother, who should provide strong positive support for protection against risky behaviours. The findings showed that a lack of a stable relationship with their parents could affect positive decisions in exercising safer and healthier sexual practices. Therefore, when there is a stable relationship with parents that leads to regulation of media access among children, the odds of engaging in RSB among youths will reduce. Notwithstanding, there is indeed a high level of awareness of sexual and reproductive health safety and preventive actions, such as low condom use and sexual risk partnering. Due to the limited regulation over media content in such a highly literate South African community, this knowledge is not adequate among youths.

Conclusions The study is of high value from the academic and programme design perspectives. The findings of the study are critical to making the different relevant responsible bodies in South Africa alert and responsive – at the individual and community levels – to designing flexible programmes to respond to the high risks that youths are exposed to and their vulnerabilities. The study has also indicated potential areas of future interventions for the possible reduction of risks – unemployment, dysfunctional communities and family – and provides some directions on how to reduce RSB among youths in South Africa.

Implications of findings The results imply that intervention programmes are needed for young people in South Africa to support them and help them avoid engaging in RSB because of community/neighbourhood defects existing in some of their communities. The findings also showed that existing sexuality programmes/policies are not very effective in addressing HIV prevention. They are also not effective in tackling the interplay between ethnic diversity and cultural norms and values that expose young people to engage in RSB. Therefore, specific programmes should be implemented that address community or neighbourhood factors that have exposed young people to many sexual and reproductive health challenges including sexually transmitted infections such as HIV; unintended pregnancies which could lead to unsafe abortions and consequently, morbidity and even mortality; other non-consensual sexual experiences; unprotected sex; and multiple partnerships.

Frontier of future research Future qualitative investigations may be conducted to test the association between social disorganisation factors and youths’ RSBs in South Africa. Also, further qualitative/quantitative studies may explore the effects of extended family members on adolescent engagement in RSB among youths. Future research may also investigate the direct impacts of role models on sexual behaviour among youths. For instance, residing in a community where there are few role models/adult supervisors may not only offer youth sexual opportunities but may also provide them with the resources (eg money, time, energy, etc) by which to do so.