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Background and aim: For over 40 years of the HIV/AIDS global epidemic, no effective cure nor vaccine is yet available, making the current control strategies focused on curbing new infections through risk reduction. The study aimed to determine the prevalence of HIV risk factors and their associated socio-demographics among women of reproductive age in Sierra Leone. Methods: We used weighted data from the Sierra Leone Demographic and Health Survey (SLDHS) of 2019 for 12,005 women aged 15–49 years. Multistage sampling was used to select study participants. Exposure to HIV risk factors was considered if a woman reported at least one of the following; having multiple sexual partners, transactional sex, non-condom use for the unmarried, and having other sexually transmitted infections (STIs). We, then, conducted multivariable logistic regression to explore the associated socio-demographics. All the analyses were done using SPSS (version 25). Results: Of the 12,005 women, 38.1% (4577/12005) (95% confidence interval (CI) 37.3–39.0) had at least one of the four risk factors. Women of 15 to 19 years (adjusted odds ratio (AOR) = 1.34, 95% CI 1.00–1.80) and 20 to 34 years (AOR = 1.25, 95% CI 1.05–1.49) had more odds of having HIV risk factors compared to those of 35 to 49 years. Urban residents (AOR = 1.49, 95% CI 1.17–1.89) and those from the Northwestern region (AOR = 1.81, 95% CI 1.26–2.60) were also more likely to encounter HIV risk factors compared to their respective counterparts. Moreover, unmarried women (AOR = 111.17, 95% CI 87.55–141.18) and those working (AOR = 1.38, 95% CI 1.14–1.67) also had higher odds of having HIV risk factors, compared to their respective counterparts. Sex of household head and parity were also significant associates. Conclusions: More than a third of women in Sierra Leone had encountered at least one HIV risk factor, and this was associated with age, place of residence, region, marital status, working status, household head and parity. There is a need for strengthening HIV/AIDS education programs, laws and policies targeting the young, working, unmarried and urban-resident women.
The Sierra Leone Demographic and Health Surveys (SLDHS) are cross-sectional surveys that are periodically conducted to obtain information on demographic, health and nutritional indicators of non-elderly adults and children. The latest survey was conducted over 4 months between May 2019 and August 2019 [5]. This national survey used a stratified, two-stage cluster sampling design with the first stage having 578 enumeration areas (EAs) (214 urban and 364 rural) selected leading to 13,872 households [5]. Using interviewer-administered questionnaires, the survey obtained sociodemographic information about the respondents. A detailed explanation of the sampling process is available elsewhere [5]. Women aged 15–49 years who were either permanent residents or visitors who had stayed in the selected households the night before the survey were eligible for interviews with a total of 15,574 women being interviewed. Of these, a weighted sample of 12,005 had been sexually active within 12 months preceding the survey and was included in this secondary analysis as shown in Table Table1.1. Written informed consent was provided by all participants of the survey. Written permission to access the whole SLDHS database was obtained through the DHS program website [23]. Socio-demographic characteristics of reproductive aged women in Sierra Leone as per the 2019 SLDHS Four variables from the SLDHS were used in this study to measure the risk factors for HIV and these included; (1) engaging in sex with more than one partner in the past 12 months, (2) engaging in transactional sex in the past 12 months, (3) not using a condom during the most recent intercourse for those who were not married, and (4) having had a sexually transmitted infection in the past 12 months [19, 20]. The total number of risk factors per woman was not a variable in the SLDHS but was generated by first giving a score of 1 for every exposure to an HIV risk factor and a score of 0 for every non-exposure, and then summing up the scores for each woman. The minimum possible score is 0 while the maximum possible score is 4. Exposure to any of the four risk factors for HIV was categorized as a binary (Yes/No) outcome and women were considered to have been exposed to risk factors for HIV if they reported any of the four behaviours. The use of alcohol/being drunk during the last sexual intercourse was not included because the data was not available in the SLDHS data set. Nineteen explanatory variables were used and included: Maternal age (15–19 years, 20–34 years and 35–49 years), Wealth index (poorest, poorer, middle, richer and richest quintiles), place of residence (urban and rural), region (Northern, Eastern, Southern, Western and Northwestern), level of education (no education, primary education, and post-primary education), household size (less than seven members and seven and above members), sex of household head (male or female), working status (not working and working), marital status (married including those in formal and informal unions, and not married). Religion was categorised as Muslims and Christians and others, problems seeking permission and distance to health facility were categorised as a big problem and no big problem while exposure to mass media was categorised as yes and no (if exposed to any of TV, radio, internet and newspapers), and visited by field worker or visited a health facility were categorised as yes and no, parity (less than 2, 2–4 and 5 and above). Wealth quintiles (poorest, poorer, middle, richer and richest) are a measure of relative household economic status and were calculated from household asset ownership information using Principal Component Analysis [5]. According to Sierra Leone, an urban area is a town with 2000 inhabitants or more [24]. The study first presented descriptive statistics of the background characteristics and risk factors of HIV of the study sample. This study first examined the proportion of women that reported ever engaging in risk factors for HIV and then examined the factors associated with these risk factors. Bivariable and multivariable logistic regression analyses were conducted where variables found significant at p-value less than 0.25 in the bivariable analysis and not strongly collinear with other independent variables were included as candidate variables in the multivariable model [25]. Multi-collinearity was assessed using variance inflation factor (VIF) and wealth index was excluded in the multivariable model because it had VIFs above 3 with marital status, age, working, exposure to newspapers, internet, parity and problems with distance and seeking permission to healthcare. Hosmer and Lemeshow test was finally done to test the goodness of the multivariable regression model. Analysis was carried out based on the weighted count to account for the unequal probability sampling in different strata and to ensure the representativeness of the survey results at the national and regional levels. In order to account for the multi-stage cluster study design, we used SPSS (version 25.0) statistical software complex samples package incorporating the following variables in the analysis plan to account for the multistage sample design inherent in the DHS dataset: individual sample weight, sample strata for sampling errors/design, and cluster number [26–28]. Adjusted odds ratios (AOR), 95% confidence intervals (CI) and p-values were calculated with statistical significance level set at p-value < 0.05.
