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Background: Despite the importance of self-reporting health in sexually transmitted infections (STIs) control, studies on self-reported sexually transmitted infections (SR-STIs) are scanty, especially in sub-Saharan Africa (SSA). This study assessed the prevalence and factors associated with SR-STIs among sexually active men (SAM) in SSA. Methods: Analysis was done based on the current Demographic and Health Survey of 27 countries in SSA conducted between 2010 and 2018. A total of 130,916 SAM were included in the analysis. The outcome variable was SR-STI. Descriptive and inferential statistics were performed with a statistical significance set at p < 0.05. Results: On the average, the prevalence of STIs among SAM in SSA was 3.8%, which ranged from 13.5% in Liberia to 0.4% in Niger. Sexually-active men aged 25–34 (AOR = 1.77, CI:1.6–1.95) were more likely to report STIs, compared to those aged 45 or more years. Respondents who were working (AOR = 1.24, CI: 1.12–1.38) and those who had their first sex at ages below 20 (AOR = 1.20, CI:1.11–1.29) were more likely to report STIs, compared to those who were not working and those who had their first sex when they were 20 years and above. Also, SAM who were not using condom had higher odds of STIs (AOR = 1.35, CI: 1.25–1.46), compared to those who were using condom. Further, SAM with no comprehensive HIV and AIDS knowledge had higher odds (AOR = 1.43, CI: 1.08–1.22) of STIs, compared to those who reported to have HIV/AIDS knowledge. Conversely, the odds of reporting STIs was lower among residents of rural areas (AOR = 0.93, CI: 0.88–0.99) compared to their counterparts in urban areas, respondents who had no other sexual partner (AOR = 0.32, CI: 0.29–0.35) compared to those who had 2 or more sexual partners excluding their spouses, those who reported not paying for sex (AOR = 0.55, CI: 0.51–0.59) compared to those who paid for sex, and those who did not read newspapers (AOR = 0.93, CI: 0.86–0.99) compared to those who read. Conclusion: STIs prevalence across the selected countries in SSA showed distinct cross-country variations. Current findings suggest that STIs intervention priorities must be given across countries with high prevalence. Several socio-demographic factors predicted SR-STIs. To reduce the prevalence of STIs among SAM in SSA, it is prudent to take these factors (e.g., age, condom use, employment status, HIV/AIDS knowledge) into consideration when planning health education and STIs prevention strategies among SAM.
We pooled data from the Demographic and Health Survey (DHS) of 27 countries in SSA conducted between 2010 and 2018, which had information on SR-STI (Table 1). Specifically, we used data from the men’s file from the various countries. The DHS is a nationally representative survey that is conducted in over 85 low- and middle-income countries globally through a two-stage stratified sampling protocol. The survey focuses on essential maternal and child health markers and men’s health, including SR-STIs [10]. The dataset is freely accessible via this link: https://dhsprogram.com/data/available-datasets.cfm. Details of the DHS methodology have been reported in previous studies [10, 11]. A sample of 130,196 men in SSA who had ever had sexual intercourse in the past 12 months and had complete information on all the variables of interest was used. The ‘Strengthening the Reporting of Observational Studies in Epidemiology’ (STROBE) statement was followed in conducting this research. Sample size of the study (weighted) The outcome variable in this analysis was STIs among SAM. It is a variable with a dichotomous outcome (Yes/No). Specifically, men were asked whether they had a disease they acquired through sexual contact in the past 12 months [1]. Independent variables included in this analysis were age (15–24, 25–34, 35–44, 44+), residence (rural, urban), educational level (no education, primary, secondary/higher), wealth status (poor, middle, rich), marital status (married, not married), employment status (working, not working), age at first sex (<=19, 20+), number of sexual partners in the last 12 months excluding the spouse (0,1, 2+), comprehensive HIV and AIDS knowledge (Yes, No), HIV testing (Yes, No), exposure to mass media (newspaper, radio, TV) (Yes, No), and health insurance coverage (Yes, No) (see Table 2). Socio-demographic characteristics and self-reported STIs among sexually active men in sub-Saharan Africa (Weighted) *P-values are from Chi-square Test HIV testing was measured by asking the participants this question: ‘Have you ever tested for HIV?’. Exposure to mass media was captured as follows: “Do you watch television almost every day, at least once a week, less than once a week or not at all? Do you read a newspaper or magazine at least once a week, less than once a week or not at all? Do you listen to the radio at least once a week, less than once a week or not at all?” The responses included the following: Not at all, less than once a week, and at least once a week. The responses from these questions were then categorized as Yes/No. Wealth, in the DHS, is a composite measure computed by combining data on a household’s ownership of carefully identified assets including television, bicycle, materials used for house construction, sanitation facilities, and type of water access. Principal component analysis was used to transform these variables into wealth index by placing individual households on a continuous measure of relative wealth. The DHS segregates households into five wealth quintiles: poorest, poorer, middle, richer, and richest. These parameters were then grouped into three: poorest, poorer (Poor), Middle and, richer and richest (rich). Comprehensive HIV knowledge was defined as knowing that consistent use of condoms during sexual intercourse and having just one uninfected faithful partner can reduce the chance of getting AIDS virus, knowing that a healthy-looking person can have the AIDS virus, and rejecting the two most common local misconceptions about AIDS transmission or prevention (i.e., mosquito bites can give HIV and HIV can be gotten from witchcraft and supernatural means). Comprehensive HIV knowledge was coded as Yes = 1 and No = 0. These factors were chosen based on their theoretical and empirical relationship with SR-STIs in previous studies [1, 2]. Stata version 14.0 was used to conduct the analyses. Both descriptive and inferential analyses were carried out. Descriptive statistics were calculated to characterize men. The data on men were weighted to account for sampling probability and non-response. Besides, the data were adjusted to account for the complex survey design and robust standard errors. Bivariate logistic regression analysis was conducted to select potential variables for the follow-up multivariable logistics regression analysis. Variables with a p < 0.05 in the bivariate analysis were included in the multivariable logistic regression model. Before fitting the final model, multi-collinearity between the independent variable was checked (Mean VIF = 1.35, Minimum = 1.05, Maximum VIF = 2.01) were deemed satisfactory. The multivariable binary logistic regression analysis was performed to identify factors associated with STIs. The reference categories were informed by previous studies and a priori. The descriptive results were presented as proportions while the regression results were presented as crude odds ratios (cORs) and adjusted odds ratios (aORs) with 95% confidence intervals and p-values. The statistical tests were reported as significant if p-value < 0.05 and the 95% confidence interval did not contain the null value.
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