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Abstract
Background Sexually transmitted infections (STIs) are a significant global health challenge, demanding attention and intervention. Despite many STIs being manageable, their asymptomatic nature poses a formidable threat to both mental and physical well-being. This silent impact can lead to substantial morbidity and mortality, which is particularly pronounced in East Africa.
Objective To investigate the prevalence and factors associated with self-reported STIs among sexually active men in East Africa.
Design Cross-sectional study design.
Setting 10 East African countries.
Participants 66 833 sexually active men.
Primary outcome measure Self-reported STI in the 12 months preceding the survey. A multilevel mixed-effects logistic regression model was fitted to identify factors associated with self-reported STIs. An adjusted OR with the corresponding 95% CI was used to estimate the strength of the association, and statistical significance was set at a p value <0.05.
Results The pooled prevalence of self-reported STIs among sexually active men in East Africa was 5.22% (95% CI: 5.34, 5.69). Being married, having multiple sexual partners excluding a spouse and being informed about STIs were significantly associated with higher odds of self-reported STIs. However, being aged 44 years and above, having a higher education level, starting sex after the age of 20, being circumcised and being a rural resident were associated with lower odds of self-reported STIs.
Conclusion The prevalence of self-reported STIs was higher than the findings from most previous studies. It is essential to educate men about STIs and increase awareness of the risks associated with having multiple sexual partners. Implementing targeted public health initiatives for men with lower education levels, as well as devising strategies to address factors that elevate the risk of STI contraction, is also crucial.
- Sexually Transmitted Disease
- Reproductive Medicine
- Infectious Disease
- Public health
- Epidemiology
Data availability statement
All data relevant to the study are included in the article or uploaded as supplementary information.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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STRENGTHS AND LIMITATIONS OF THIS STUDY
The study was based on nationally representative data from 10 East African countries, featuring a large sample size reflective of the national population.
Consequently, the study has the potential to furnish valuable insights for policymakers and programme planners in formulating appropriate national and regional interventions.
This study used a weighted data set with advanced statistical techniques, addressing the hierarchical nature of the demographic and health survey data and providing reliable estimates and SEs.
However, the cross-sectional design limits causal inference, and the reliance on self-reported data poses a risk of recall bias, further influenced by variability in the year of data collection across countries.
Introduction
Sexually transmitted infections (STIs) encompass an array of clinical syndromes and infections transmitted through sexual intercourse.1 2 Despite the implementation of typically effective and economically viable preventive measures, the prevalence of STIs persists in its upward trajectory.1 3–5 Globally, STIs present a formidable health challenge imposing a substantial public health burden. According to the WHO, there are 374 million cases of treatable STIs each year.6 7 Notably, Sub-Saharan Africa (SSA) bears a significant brunt, holding 40% of the worldwide burden of STIs.6 8
STIs remain a significant public health challenge in East Africa, with the region experiencing some of the highest rates of STIs globally. The epidemiology of STIs in East Africa is marked by a high prevalence of conditions such as HIV, syphilis, gonorrhoea, chlamydia and human papillomavirus. The spread of these infections is influenced by various factors, including socio-economic conditions, cultural practices and access to healthcare services.9–11 In East Africa, the prevalence of chlamydia and other STIs (excluding HIV) affects approximately 3% of individuals aged 15–49 years in clinic or community settings and 10% in high-risk groups.12
While STIs are often treatable, their insidious nature is characterised by a lack of symptoms, posing a hidden threat to both physical and mental well-being.5 13 The repercussions extend beyond the apparent, encompassing consequences such as infertility, urethral strictures, genital malignancies, blindness, cardiovascular disease and elevated susceptibility to HIV infection.4 14 15 Within developing nations, the spectrum of STIs and their associated complications ranks among the top five reasons why adults seek healthcare services.16 17
The WHO has initiated a strategy to promote the prevention and control of STIs, aiming to alleviate the burden they impose and ensure the accessibility of effective prevention and therapeutic programmes.18 19 This strategy entails the organised gathering of data on the occurrence and prevalence of STIs. To accomplish this, individuals contracting STIs are urged to self-report, streamlining the process of data acquisition and enabling timely treatment.18 20 Consequently, studies that integrate self-reported STI data become crucial resources for guiding public health strategies and influencing policy development.
Effective prevention and control of STIs depend on early detection and treatment, yet many developing countries fall short in meeting these needs.21 22 There is a noticeable gap in existing STI literature, with prior studies overlooking the utilisation of multilevel modelling to address the inherent hierarchical nature of demographic and health survey (DHS) data and proper weighting techniques for sample sizes.16 20 23 Besides helping our study stand out, these improvements in methodology support a more robust examination of STIs and their associated factors. Focusing on sexually active men is particularly important as they often play a key role in the transmission dynamics of STIs, yet their health needs have been under-represented in existing studies. Therefore, the aim of this study was to assess the pooled prevalence of self-reported STIs and associated factors among sexually active men in East Africa. The results of this study will play a pivotal role in shaping and implementing initiatives aimed at addressing STIs. These efforts encompass the improvement of programme monitoring, early detection methods and surveillance. Furthermore, it will help in the formulation of innovative policies and strategies dedicated to the prevention and effective management of STIs.
Methods
Study design and setting
The DHS is a nationally representative survey designed to gather information on key indicators related to population dynamics, nutrition and health using a community-based cross-sectional study design. A two-stage stratified sampling method was employed to identify participants for the study. In the initial stage, enumeration areas were randomly chosen based on recent population data, using the housing census as a sampling frame. Subsequently, households were selected in the second stage. For this particular study, focusing on sexually active men, the data set derived from men’s records file was used. Additional information on the DHS methodology is available at https://dhsprogram.com/Methodology/index.cfm.
Data source and study population
This study was conducted using the latest DHS data from East African countries spanning the period from 2011 to 2022. The WHO region of East Africa includes 20 countries, but only 15 have a documented history of participation in the DHS. This study used recent, nationally representative DHS data from 10 countries: Burundi (2016/2017), Congo (2011/2012), Ethiopia (2016), Kenya (2022), Comoros (2012), Madagascar (2021), Rwanda (2019/2020), Tanzania (2022), Zambia (2018) and Zimbabwe (2015). Notably, Sudan and Eritrea did not have recent DHS data available, while Uganda, Mozambique and Malawi lacked information on STIs among sexually active men in their DHS data sets. The final analysis included a weighted sample of 66 833 sexually active men from these 10 East African countries.
Study variables
Dependent variable
The dependent variable was self-reported STIs. To assess this variable, respondents who had ever had sex were asked whether they had an STI or symptoms of an STI (such as an abnormal or foul-smelling discharge from the penis and/or a genital sore or ulcer) in the 12 months preceding the survey. A participant who answered ‘yes’ to any of these questions was considered to have an STI.
Independent variables
In the current study, aligning with the study’s objectives and acknowledging the hierarchical nature of the DHS data, two levels of independent variables were considered: individual and community-level variables.
Age, age at first sex, educational status, marital status, employment status, wealth status, exposure to mass media, number of sexual partners in the last 12 months excluding the spouse, circumcision status, ever heard about STI, ever been tested for HIV, comprehensive HIV and AIDS knowledge, paid for sexual intercourse in the past 12 months and health insurance coverage were individual-level variables. The community-level variables were place of residence and East African countries.
Wealth index
This was derived using a statistical procedure called principal components analysis and is used to place households on a continuous scale of relative wealth. This index is used to assess the influence of wealth on population, health and nutrition indicators. Households are typically divided into five wealth quintiles: poorest, poor, middle, rich and richest. For our analysis, these quintiles were recoded into three categories: poor (including the poorest and poor quintiles), middle and rich (including the rich and richest quintiles).
Media exposure
This variable was created by combining three factors: how often a person listens to the radio, watches television or reads newspapers/magazines. If a man engages in any of these activities at least once a week, he is considered to have media exposure (coded as ‘yes’); otherwise, it is coded as ‘no’
Comprehensive HIV and AIDS knowledge
It was a composite score based on the following six questions, each with two response options (‘no’ and ‘yes’): ‘Can the risk of getting HIV/AIDS be reduced by using condoms during sex?’ ‘Can the risk of getting HIV be reduced by having only one sex partner?’ ‘Can a healthy-looking person have HIV?’ ‘Can HIV be contracted through witchcraft or supernatural means?’ ‘Can HIV be transmitted by a mosquito bite?’ ‘Can HIV be contracted by sharing food with a person who has HIV/AIDS?’ A man was considered knowledgeable if he correctly answered all six questions: ‘yes’ for the first three and ‘no’ for the remaining three.
Data processing and statistical analysis
STATA V.17 statistical software was employed for data extraction, recoding and analysis. The DHS employs a complex survey design that requires sampling weights to ensure nationally representative results, accounting for selection probabilities, non-response and population demographics. Accordingly, the data were weighted using sampling weights, primary sampling units and strata to restore representativeness and account for the sampling design when computing SEs, ensuring reliable statistical estimates. Descriptive statistics were used to portray the study population with respect to pertinent characteristics. A multilevel mixed-effects logistic regression model was applied to account for the hierarchical nature of the DHS data. Bivariable multilevel mixed-effects logistic regression analysis was performed to identify variables eligible for the multivariable analysis at a p value <0.20, chosen to strike a balance between sensitivity and specificity while avoiding the leniency of 0.25, ensuring potentially important variables are included without compromising statistical rigour.
Following the selection of variables for the multivariable multilevel mixed-effects logistic regression analysis, four models comprising the identified variables were constructed. The first model was a null model without independent variables to determine the extent of cluster variation. The second model (Model I) incorporated individual-level variables, the third (Model II) involved community-level variables and the fourth model (Model III) simultaneously considered the effects of both individual and community-level variables.
To evaluate the degree of heterogeneity among different clusters, we employed several statistical approaches, including the intraclass correlation coefficient (ICC) and likelihood ratio (LR) test. The ICC specifically quantifies the extent of heterogeneity between clusters by assessing the proportion of total variation in self-reported STIs attributable to differences between clusters. In contrast, the LR test was used to compare the fit of nested models, helping us determine whether adding random effects for clusters significantly improves model fit. Together, these statistical methods provide a more nuanced understanding of the variation among different clusters. In the final model, the adjusted OR, along with its 95% CI, was employed to estimate the strength of association between individual and community-level characteristics with self-reported STI. At this level, variables with a p value <0.05 were considered statistically significant.
Patient and public involvement
Patients and/or the public were not involved in the design, conduct, reporting or dissemination plans of this research.
Results
Sociodemographic and economic characteristics
A total weighted sample of 66 833 sexually active men were included in the study. The median age of the participants was 33 (IQR 16–47) years, with 21 328 (31.91%) men between the ages of 25–34 years. About 73.68% were ever-married men, 39.35% of them had attended primary education and the vast majority (88.16%) were employed. Moreover, more than one-third (34.69%) resided in poor households, and 66.74% of them lived in rural households (table 1).
Sociodemographic and economic characteristics, along with the prevalence of sexually transmitted infections across independent variables (n=66 833)
Reproductive health characteristics
Among the participants included in this study, 64.79% experienced their first sexual encounter at the age of 19 or below. The majority (97.98%) had heard about STIs, and 61.19% had been tested for HIV. Most men (69.24%) have undergone circumcision, and 92.90% possess comprehensive knowledge about HIV/AIDS (table 2).
Reproductive health characteristics, along with the prevalence of sexually transmitted infections across independent variables (n=66 833)
The prevalence of STIs
The pooled prevalence of self-reported STIs among sexually active men in East Africa was 5.22% (95% CI: 5.34, 5.69). The highest prevalence was observed in Tanzania at 11.73% (95% CI: 10.79, 12.67), while the lowest was in Ethiopia at 2.52% (95% CI: 2.20, 2.85) (figure 1).
The pooled prevalence of self-reported sexually transmitted infections (STIs) among sexually active men in East Africa.
Statistical analysis and model comparison
The significant log-LR test (χ²=54.60, p<0.001) indicated that the generalised linear mixed-effects model (GLMM) provided a better fit for the data than classical regression models. While the LR test does not dictate the choice of modelling approach, it supports the selection of GLMM, which is appropriate for this analysis. The final model, incorporating both individual and community-level variables, was chosen as the best fit due to its lowest deviance value (30 176.68) (table 3).
Model comparison and random-effect results
Factors associated with self-reported STIs among sexually active men in East Africa
In the multilevel multivariable mixed-effects logistic regression analysis, age, marital status, educational status, age at first sex, number of sexual partners excluding spouse, ever heard about STIs, circumcision status, place of residence and country were statistically significant factors associated with self-reported STIs among sexually active men in East Africa (table 4).
Multilevel analysis of factors associated with self-reported sexually transmitted infection among sexually active men in East Africa
Accordingly, compared with adolescent men, those whose age is >44 were found to have 32% lower odds of reporting STIs (AOR=0.68, 95% CI: 0.59, 0.77). Ever-married men had 1.42 times higher odds of reporting STIs (AOR=1.42, 95% CI: 1.28, 1.57) compared with their unmarried counterparts. In contrast to men with no formal education and those who started sex before the age of 20, men with higher educational status and those who started sex after the age of 20 had 49% (AOR=0.51, 95% CI: 0.43, 0.61) and 19% (AOR=0.81, 95% CI: 0.75, 0.86) decreased odds of reporting STIs, respectively. The odds of self-reported STIs among men who had 1 and ≥2 sexual partners excluding their spouse were 2.02 times (AOR=2.02, 95% CI: 1.86, 2.19) and 4.34 times (AOR=4.34, 95% CI: 3.93, 4.81) higher, respectively, compared with men with no sexual partner excluding their spouse. Men who had heard about STIs had 2.86 times higher odds of reporting STIs (AOR=2.86, 95% CI: 2.14, 3.81). Circumcised men and those who resided in rural households had 11% (AOR=0.89, 95% CI: 0.81, 0.98) and 13% (AOR=0.87, 95% CI: 0.79, 0.95) decreased odds of reporting STIs, respectively. Moreover, the odds of self-reported STIs among men in Ethiopia and Madagascar decreased by 45% (AOR=0.55, 95% CI: 0.47, 0.64) and 17% (AOR=0.83, 95% CI: 0.72, 0.96), respectively. In contrast, the odds of self-reported STIs in Congo, Rwanda, Tanzania and Zimbabwe were 1.68 times (AOR=1.68, 95% CI: 1.47, 1.92), 1.23 times (AOR=1.23, 95% CI: 1.05, 1.43), 1.89 times (AOR=1.89, 95% CI: 1.67, 2.16) and 1.41 times (AOR=1.41, 95% CI: 1.22, 1.64) higher compared with sexually active men in Kenya, respectively.
Discussion
The present study sought to assess the prevalence and factors associated with self-reported STIs among sexually active men in East Africa using recent DHS data. The pooled prevalence of self-reported STIs in East Africa was 5.22% (95% CI: 5.34, 5.69), ranging from 2.52% in Ethiopia to 11.73% in Tanzania. The result reported in this study is higher than the findings from studies conducted in Ethiopia (3.5%) and other SSA countries (3.8%). However, it is lower than the findings reported in India (9.5%) and Ghana (6%). Discrepancies in self-reported STI rates among the studies may stem from differences in population characteristics, varying religious and sociocultural contexts, disparities in information and knowledge, and divergent levels of access to healthcare infrastructure and facilities across different countries and settings.
After adjusting for individual and community-level factors, age, marital status, educational status, age at first sexual encounter, number of sexual partners excluding spouse, ever heard about STIs and circumcision status from the individual-level factors, as well as place of residence from the community level factors showed a significant association with self-reported STIs.
The odds of reporting STIs were 32% lower among men aged 44 years and above compared with adolescent men. This finding aligns with previous studies that identified younger age as a risk factor for STIs.20 23 24 This could be attributed to the fact that younger individuals often engage in riskier sexual behaviours, like having multiple partners and inconsistent condom use.25 26 Limited experience and knowledge about sexual health, coupled with peer pressure and societal norms, may contribute to higher STI rates among the younger population.27 28 Furthermore, increased sexual activity and variations in communication and healthcare-seeking behaviours between age groups contribute to the observed patterns.
In contrast to men who began their sexual activity before the age of 20, those who initiated sexual experiences after the age of 20 had reduced odds of reporting STIs. This finding is supported by a study conducted in Ghana among sexually active men.23 Additionally, this finding aligns with previous studies, which reported that men who had their first sexual experience below the age of 20 had higher odds of STIs.20 29 30 Adolescence is associated with risky sexual behaviours like multiple partners, experimentation and unprotected sex. Individuals who engage in such behaviours during this phase may be more prone to STIs, highlighting the link between risky sexual practices in the transition to adulthood and STI susceptibility in sexually active men.26 31
This study revealed that men with higher education have lower odds of contracting STIs compared with those without formal education. This finding is consistent with studies done in Uganda and the Netherlands.32 33 Education, a fundamental pillar in life, grants educated individuals increased access to information and the capability to apply health education messages effectively. This empowerment enables them to proactively protect themselves against STIs, showcasing education as a potent tool for informed decision-making and healthier practices, especially in sexual health.34 35
In line with a study conducted in Malaysia,36 ever-married men had higher odds of self-reported STIs compared with unmarried men. This could be attributed to the fact that married men often have more open discussions about sexual and reproductive health concerns, fostering a better understanding of potential STIs and facilitating the disclosure of problems.
The odds of self-reported STIs among men who had sexual partners excluding their spouse were higher compared with men who had no sexual partners apart from their spouse. This conclusion is in line with previous studies.16 20 23 37 38 Engaging in sexual activities with multiple partners is widely recognised as a documented risk factor for STI infection, increasing the likelihood of contracting STIs. To prevent STIs, maintaining fidelity with a single partner and abstinence are recommended strategies. However, the promotion and practice of abstinence remain contested. Moreover, a comprehensive approach to STI prevention, including sexual education and the promotion of harm reduction strategies, is important.39 40
Men who ever heard about STIs had greater odds of reporting STIs compared with their counterparts. This can be justified by those who heard about STIs might be more attuned to recognising symptoms and seeking testing or treatment, or it could indicate that individuals with more sexual health knowledge are more proactive in disclosing their STI status.41 42
In this study, circumcised men exhibited lower odds of STIs compared with uncircumcised men, aligning with similar findings in previous studies.43 44 This can be attributed to circumcision reducing the risk of HIV and STIs by minimising pathogen entry and eliminating a conducive environment under the foreskin. Consequently, the WHO advocates for voluntary medical male circumcision as a critical strategy in preventing HIV and STIs.45–48 Evidence suggests that circumcision not only protects males but also benefits female partners.49
This study also revealed a statistically significant association between the place of residence and self-reported STIs. In line with previous studies conducted in Ghana and the USA,23 50 men who resided in rural areas had decreased odds of reporting STIs. Urban areas, with their increased population density, provide optimal conditions for the easier transmission of infections. The diversity in demographics, lifestyles and sexual activities within urban settings further amplifies the risk of transmission. Healthcare services are often more accessible in urban areas, enabling more thorough testing and reporting of STIs. Additionally, social and cultural factors, along with a potentially more permissive attitude towards sexual behaviours, all play a role.51–53
This study, grounded in nationally representative data from 10 East African countries and using a robust sample size, offers significant insights that can inform national and regional interventions. By employing a weighted data set and advanced statistical techniques to address the hierarchical structure of the DHS data, the analysis provides reliable estimates and SEs. Nevertheless, the cross-sectional design of the data limits the ability to establish causation between independent and dependent variables. Moreover, the reliance on self-reported data introduces the possibility of recall bias, and the absence of information on sexual orientation and the gender of sexual partners may limit a comprehensive understanding of STIs. These factors should be considered when interpreting the findings. Despite these limitations, the study’s results are valuable for policymakers and programme planners aiming to formulate appropriate national and regional interventions.
Conclusion
The prevalence of self-reported STIs among sexually active men in East Africa was 5.22%, with significant variation across countries, ranging from 2.52% in Ethiopia to 11.73% in Tanzania. This variation suggests that country-specific factors may play a crucial role in STI prevalence. Individual-level variables such as age, marital status, educational status, age at first sex, number of sexual partners excluding spouse, ever heard about STIs, circumcision status and community-level variables like place of residence and country were significant factors associated with self-reported STIs. Hence, it is crucial to concentrate on enlightening men about STIs and raising awareness about the consequences of having multiple sexual partners. Public health interventions tailored to reach men with lower levels of education, along with formulating strategies that counteract factors putting sexually active men at an elevated risk of contracting STIs, are also recommended.
Data availability statement
All data relevant to the study are included in the article or uploaded as supplementary information.
Ethics statements
Patient consent for publication
Ethics approval
Not applicable.
Acknowledgments
The authors express their gratitude to the Measure DHS program for providing on-request open access to its data set.
References
Footnotes
Contributors YMN and BLS conceived the idea for the study, were involved in data extraction and interpreted the findings. BLS conducted the statistical analysis. YMN assisted in the analysis and drafted the manuscript. All authors critically reviewed the draft manuscript, wrote the final version, read and approved the final manuscript. YMN is the guarantor of the study.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.