Introduction
HIV continues to be a major public health issue with over 38 million people acquiring HIV globally and about 3.4 million adolescent girls and young adults aged between 15–24 years living with HIV1. HIV testing is the first step in HIV prevention of new transmissions and AIDS-related deaths, initiation on ART and improvement of quality of life among the Adolescent Girls and Young Women (AGYW)2. Testing services have become increasingly available in Kenya with over 7,000 government health facilities offering the service for free and private health facilities with minimal charges3. However, AGYW continue to be a uniquely vulnerable population that is exposed to risks that affect their health and well-being including risky sexual behaviours that expose them to HIV4. The prevalence of HIV among AGYW in Kenya is two to three times that of adolescent boys and young men (ABYM)5. Young people (15–24 years) contribute 41% of all new HIV diagnoses in the 15+ population in the country, with 70% of those new diagnoses in females3. Further, UNAIDS estimates that every week, approximately 6200 AGYW aged between 15–24 years of age get newly transmitted with HIV in Kenya6.
HIV transmission among the AGYW in Sub-Saharan Africa and other African Countries is mainly through the unprotected heterosexual route fuelled by risky sexual behaviours such as early sexual debut, low condom use, substance use, having multiple sexual partners, transactional sex, among others5. In Nigeria for example, poverty, being orphan, dropping out of school, early child marriages and sexual violence among other inequalities are attributed to risks of unprotected sex among the AGYW7.
A study done in Zimbabwe found out that AGYW who engage on sex for monetary gains are less likely to utilize HIV testing services compared to those who do not practice transactional sex, those who have multiple sexual partners are likely to test compared to those with only one and similarly, those who use condoms are less likely to test compared to those who don’t use8. A similar study in Ethiopia among the AGYW, found that those who had multiple sexual partners, those who ever had been pregnant, started sexual intercourse early and had history of sexually transmitted infections were more likely to utilize HIV testing services due to the increased risk of HIV transmission9. Additionally, studies across different parts of the globe have positively associated risky sexual behaviours such as early sexual debut, stigma, attitudes with predisposing AGYW to HIV and utilization of HIV testing services10–12.
Kenya has continually endeavoured to halt and reverse the spread of HIV transmission with remarkable achievements towards HIV prevention, and continues to implement various interventions geared towards achieving the UNAIDS 95-95-95 targets by 20303. However, despite the efforts testing gaps exist for AGYW at 44%13. As of 2016, HIV testing among AGYW in Ethiopia is 27%9. Similar population-based survey in Malawi, Zambia and Zimbabwe showed that 46% of AGYW were aware of their HIV status14. Several other studies based on demographic health surveys between 2013 – 2016 in different countries have shown low HIV testing rates among AGYW such as Nigeria 12% (2013), Uganda 26.5% (2016) and Rwanda 40% (2014–15)15. A household study conducted in Viwandani and Korogocho slums in Nairobi 2018 showed that AGYW are less aware of their HIV status compared to those above 25 years16.
Numerous investigations have focused on HIV among AGYW; however, a literature search failed to identify studies examining the nexus between risky sexual behaviours and the utilization of HIV testing services within this high-priority demographic. Consequently, this research aims to elucidate the prevalence of HIV testing and scrutinize the interplay among sociodemographic characteristics, risky sexual behaviours such as early sexual debut, condom use, substance use, having multiple sexual partners, transactional sex, among others, and the utilization of HIV testing services among AGYW aged 15–24 in Kibra Sub County, Nairobi County, Kenya. The outcomes of this study stand poised to offer valuable insights for refining extant prevention strategies concerning differentiated HIV testing services. Moreover, the findings are anticipated to play a pivotal role in the formulation of targeted behavioural interventions tailored to address the specific challenges confronted by AGYW. Consequently, the study holds the potential to make significant contributions to the development of more efficacious public health strategies geared towards attainment of the UNAIDS 95-95-95 strategy to end HIV epidemic by 2023 and contribute to attainment of the SDG3 target 3.3 which aims to fight communicable diseases.
Methods
Design
A community-based cross-sectional analytical study design, using quantitative techniques, was employed.
Study site and population
Kibra is one of the 17 sub counties in Nairobi County, it is located southwest of Nairobi County approximately 5 kilometres from CBD and projected to have a population of 206,064 persons, 21.5% of this population constitutes the AYPs aged between 15–24 years. Majority of the residents are in informal settlements17. The sample size of 379 adolescent girls and young women (AGYW) aged 15–24 was calculated using the Cochran formula18. Employing a multistage sampling technique, three out of five Wards were randomly selected. Then random walk sampling method was used, starting from common meeting points (markets, hospitals, or schools) in selected wards. A local guide assisted in choosing a random route, with data collection continuing until the minimum sample size was reached. In households with multiple AGYW, random selection using yes/no indicators determined the participant. To be eligible participant must have been a resident for at least one year before time of study, consent/assent to participate and aged between 15–24 years.
Dependent variable
The dependent variable of this study was utilization of HIV testing services among AGYW aged between 15–24 years in Kibra Sub County, which was measured by asking the question to the respondents whether have ever been tested for HIV and the outcome was binary (Yes/No).
Independent variables
Independent variables for this study were grouped into two categories i.e. (sociodemographic characteristics and risky sexual behaviours) where Socio-demographic factors included (age, education level, employment status, average monthly income, marital status and religion). Risky sexual behaviours (ever had sex, age at first sexual debut, ever tested for HIV, had sex for cash, having multiple sexual partners, condom use in sexual encounters and if ever experienced gender-based violence).
Inclusion criteria
The study included AGYW aged between 15–24 years who are residents of Kibra Sub County for at least one year.
Exclusion criteria
The study excluded eligible AGYW 15–24 years not willing to consent or assent or whose parent or guardian declined to give consent from the selected households during data collection
Sample size determination
Sample size was calculated using Cochran formula (1977) since the estimated population of AGYW in Kibra is above 10,000
Where;
n0 - is the sample size;
Z2 = Is the standard normal deviate for alpha at 95% confidence level (1.96);
E = is the desired level of precision (0.05);
P = 56% proportion of AGYW ever tested for HIV and know their status in Kenya (Kenya Demographic Health Survey (KDHS 2022);
Q = is 1-p. (0.44);
The value for Z is found in statistical tables which contain the area under the normal curve. i.e. Z = 1.96 for 95 % level of confidence
Sampling technique
The study used a four multistage sampling technique
Where;
1. Using random numbers, 3 wards from the 5 were selected (Sarang’ombe, Laini saba and Lindi)
2. According to 2019 Census, the population of AGYW in sarang’ombe waurd was 5,741, laini saba 2,870 and lindi 3,565. This population was projected to grow at arte of 2.2% per year which means that the population at the time of study was (sarang’mbe 6,263, laini saba 3,131 and lindi 3,889) giving a total population for the three wards to be 13,283.
3. Proportions were used to allocate sample for each ward i.e sarang’ombe ward 47% of 379 (179), laini saba 24% of 379 (89) and lindi 29% of 379 (111)
4.The study utilized the random walk sampling method whereby in each of the selected wards, a common meeting place, either a market, hospital, hospital or school was chosen a sthe staring point. With the help of a local guide, one route from the selected meeting point was chosen at random and the data collected proceeded along that route until the minum sample size was reached. The first household along the route was skipped and the next household was assessed for presence of the population of interest. The data collector continued to skip one household in this manner until the minimum sample size was achieved. For household with more than one AGYW, use of random numbers written yes and no was used so that the one that picks yes was interviewed. Household without AGYW were skipped.
Pre testing of data collection tools
Research assistants were trained on the data collection tools then pretesting of the data collection questionnaire was done in 30 households where 30 interviewer administered questionnaires were administered to AGYW in Mathare Sub County. Mathare Sub County was chosen because the population there has similar characteristics like the one found in Kibra Sub County, this enabled the researcher to make any necessary adjustments on the study questionnaire depending on how well the respondents understood and gave responses.
Data collection
Standardized structured quantitative interviewer-administered questionnaires were used, covering sociodemographic details, risky sexual behaviours, and HIV testing service utilization. Sociodemographic factors (age, sex, education level, marital status, average monthly income, religion) and indicators of risky sexual behaviours were assessed. Risky behaviours included sexual activity, age at first encounter, condom use, pregnancy prevention methods, transactional sex, multiple sexual partners, sex under the influence, and STI diagnosis in the past 12 months. HIV testing history was also assessed. The questionnaire was adapted with modification from 15,19. Before the actual data collection, the questionnaire was pre-tested to see if participants are able to comprehend the questions, test the time taken. This was done in the indicated sub county which has similar characteristics with the study area. Data were collected between June and July 2023.
Data analysis
Completed questionnaires were cross-checked for accuracy and completeness, then analysed using SPSS version 25. Descriptive statistics on sociodemographic characteristics such as age, sex, education level, marital status, average monthly income, religion, and risky sexual behaviours included sexual activity, age at first encounter, condom use, pregnancy prevention methods, transactional sex, multiple sexual partners, sex under the influence, and STI diagnosis in the past 12 months. Inferential statistics were employed. Regression analyses were performed to assess the association between the explanatory variables and each variable. Variables with a univariable p-value < 0.1 were included in multivariate logistic regression. Adjusted odds ratios, 95% confidence intervals, and p-values were reported, with significance set at p < 0.05.
Ethical considerations
Ethical clearance was obtained from Jomo Kenyatta University of Agriculture and Technology Research Committee (JKU/ISERC/02316/0832). Research permits were secured from the National Commission for Science Technology and Innovations (NACOSTI/P/23/24723), and Nairobi County Ethical and Research Committee (NCCG/HWN/REC/357). Informed consent and assent were obtained from participants, ensuring full disclosure of study purpose, risks, and benefits. Strict confidentiality measures, including identity code usage and password protection, were implemented. Access to data was restricted, and anonymity was maintained during data sharing.
Results
Sociodemographic characteristics
The majority of the AGYW respondents (80.7%) were single, with the rest either married (18.2%) or separated (1.1%). Almost two-thirds (64.6%) were educated to secondary school level, while tertiary and primary levels accounted for 23.5% and 11.6% respectively (Table 1)20.
Table 1. To determine risky sexual behaviors associated with HIV testing among AGYW aged between 15–24 years in Kibra Sub County.
| Ever tested for HIV? | |
|---|
| Variable | | | |
|---|
| Ever had sex? | Yes
(N=230) | No
(N=149) | Overall
(N=379) |
| No | 13 (5.7%) | 98 (65.8%) | 111 (29.3%) |
| Yes | 217 (94.3%) | 51 (34.2%) | 268 (70.7%) |
Age at first sexual intercourse (in
years) | Yes (N=217) | No (N=51) | Overall (N=268) |
| Mean (SD) | 17.9 (1.86) | 17.3 (1.97) | 17.8 (1.89) |
| Median [Min, Max] | 18.0 [14.0, 24.0] | 18.0 [13.0, 21.0] | 18.0 [13.0, 24.0] |
| Cash in return for sex? | Yes (N=217) | No (N=51) | Overall (N=268) |
| No | 175 (80.6%) | 45 (88.2%) | 220 (82.1%) |
| Yes | 42 (19.4%) | 6 (11.8%) | 48 (17.9%) |
Have more than 1 lifetime sexual
partners? | Yes (N=217) | No (N=51) | Overall (N=268) |
| No | 174 (80.2%) | 42 (82.4%) | 216 (80.6%) |
| Yes | 43 (19.8%) | 9 (17.6%) | 52 (19.4%) |
If yes to question 21 above, how
many? | Yes (N=43) | No (N=9) | Overall (N=52) |
| Mean (SD) | 2.67 (1.11) | 2.33 (0.500) | 2.62 (1.03) |
| Median [Min, Max] | 2.00 [2.00, 7.00] | 2.00 [2.00, 3.00] | 2.00 [2.00, 7.00] |
Had more than 1 sexual partners
during the past 3 months? | Yes (N=217) | No (N=51) | Overall (N=268) |
| No | 185 (85.3%) | 44 (86.3%) | 229 (85.4%) |
| Yes | 32 (14.7%) | 7 (13.7%) | 39 (14.6%) |
If yes to question 23 above, how
many? | Yes (N=32) | No (N=7) | Overall (N=39) |
| Mean (SD) | 2.37 (0.718) | 2.29 (0.488) | 2.35 (0.676) |
| Median [Min, Max] | 2.00 [2.00, 5.00] | 2.00 [2.00, 3.00] | 2.00 [2.00, 5.00] |
| Missing | 2 (6.3%) | 0 (0%) | 2 (5.1%) |
Did you use condom in your last
sexual intercourse? | Yes (N=217) | No (N=51) | Overall (N=268) |
| No | 156 (71.9%) | 20 (39.2%) | 176 (65.7%) |
| Yes | 61 (28.1%) | 31 (60.8%) | 92 (34.3%) |
Did you use any method for
prevention of pregnancy during
your last sexual intercourse? | Yes (N=217) | No (N=51) | Overall (N=268) |
| No | 109 (50.2%) | 20 (39.2%) | 129 (48.1%) |
| Yes | 108 (49.8%) | 31 (60.8%) | 139 (51.9%) |
Had sexual intercourse under the
influence of alcohol? | Yes (N=217) | No (N=51) | Overall (N=268) |
| No | 178 (82.0%) | 47 (92.2%) | 225 (84.0%) |
| Yes | 39 (18.0%) | 4 (7.8%) | 43 (16.0%) |
Ever experienced gender-based
violence? | Yes (N=217) | No (N=51) | Overall (N=268) |
| No | 185 (85.3%) | 47 (92.2%) | 232 (86.6%) |
| Yes | 32 (14.7%) | 4 (7.8%) | 36 (13.4%) |
Had any STI in the last 12
months? | Yes (N=217) | No (N=51) | Overall (N=268) |
| No | 185 (85.3%) | 44 (86.3%) | 229 (85.4%) |
| Yes | 32 (14.7%) | 7 (13.7%) | 39 (14.6%) |
Testing services utilization
Regarding HIV testing, participants from Sarangombe had the highest testing rate 47.4% (179), followed by Lindi 28.7% (111) and Laini Saba 23.9% (89). 60.7% (230) of the AGYW had tested for HIV, with a majority 71.3% (164) being in the 20–24 age group and 28.7% (66) being among participants aged 15–19. Education played a role in utilization of HIV testing services as 63.5% (146) of those with secondary education and 23.3% (56) with tertiary education having been tested, compared to only 12.2% (28) with primary education. Employment status influenced testing, with most unemployed participants, 79.6% (183), having tested for HIV, while business, and employed individuals had lower and similar testing rates at 10.4% (24), and 10.0% (23) respectively. Participants earning less than 10,000 monthly had a testing rate of 64.8% (149), contrasting sharply with the 1.3% (3) testing rate among those earning between 20,000 and 30,000. Marital status showed differences, as 69.6% (160) of single participants were tested compared to 28.7% (66) married participants. In terms of religion, 84.8% (195) of Christians and 15.2% (35) of Muslims underwent HIV testing, the overall testing prevalence was 60.7%, as seen in Table 1.
Bivariate analysis
Adolescent girls and young women aged 20–24 years exhibited a substantial likelihood of testing (OR: 4.50, 95% CI: 2.91, 7.04, p < 0.001), while not employed participants were markedly less likely to get tested (OR: 0.23, 95% CI: 0.04, 0.50, p < 0.004). Married individuals exhibited a significantly higher likelihood of HIV testing (OR: 20.1, 95% CI: 7.26, 83.32, p < 0.001). No significant association was found between religion and utilization of HIV testing services. For AGYW who had ever engaged in sexual activity, the likelihood of testing was notably elevated (OR: 32.08, 95% CI: 17.22, 64.20, p < 0.001). Furthermore, individuals not using condoms in their last sexual encounter demonstrated a higher probability of HIV testing (OR: 3.96, 95% CI: 2.12, 7.58, p < 0.001). Experiencing gender-based violence significantly increased the likelihood of testing (OR: 4.65, 95% CI: 1.93, 13.87, p = 0.002), and participants reporting recent STI contraction were also more inclined to undergo HIV testing (OR: 2.85, 95% CI: 1.33, 6.81, p = 0.011), as detailed in Table 2.
Table 2. Univariable logistic regression model assessing sociodemographic and risky sexual behaviour factors associated with utilization of HIV testing services.
| Variable | Category | n | % HIV tested | Crude OR | 95% CI | P-value |
|---|
| Ward | Laini Saba | 89 | 23.9 | Ref | | |
| Lindi | 111 | 28.7 | 0.91 | 0.51, 1.60 | 0.737 |
| Sarangombe | 179 | 47.4 | 0.96 | 0.57, 1.62 | 0.886 |
| Age (ungrouped) | | | 1.61 | 1.44, 1.82 | <0.001* |
| Age (grouped) | 15-19 years | 162 | 28.7 | Ref | | |
| 20-24 years | 217 | 71.3 | 4.5 | 2.91, 7.04 | <0.001* |
| Education level | No formal education | 1 | 0 | Ref | | |
| Primary | 44 | 12.2 | - | - | 0.979 |
| Secondary | 245 | 63.5 | - | - | 0.979 |
| Tertiary | 89 | 24.3 | - | - | 0.979 |
| Employment status | Business | 27 | 10.4 | Ref | | |
| Not employed | 34 | 10.0 | 0.23 | 0.04, 0.50 | 0.004365* |
| Employed | 318 | 79.6 | 0.26 | 0.05, 0.96 | 0.060 |
| Average monthly income | No income | 127 | 22.6 | 0.23 | 0.01, 1.86 | 0.210 |
| <10,000 | 218 | 64.8 | 0.72 | 0.04, 5.74 | 0.778 |
| 10,000 - 20,000 | 30 | 11.3 | 2.17 | 0.09, 22.71 | 0.544 |
| 20,000 - 30,000 | 4 | 1.3 | Ref | | |
| Marital status | Single | 306 | 69.6 | Ref | | |
| Married | 69 | 28.7 | 20.1 | 7.26, 83.32 | <0.001* |
| Separated | 4 | 1.7 | - | - | 0.983 |
| Religion | Christian | 321 | 84.8 | 1.02 | 0.56, 1.79 | 0.954 |
| Muslim | 58 | 15.2 | Ref | | |
| Ever had sex | No | 111 | 5.7 | Ref | | |
| Yes | 268 | 94.3 | 32.08 | 17.22, 64.20 | <0.001* |
| Age at first sex (in years) | | | 1.18 | 1.00, 1.40 | 0.053 |
| Cash in return for sex | No | 220 | 80.6 | Ref | | |
| Yes | 48 | 19.4 | 1.8 | 0.77, 4.95 | 0.208 |
| 1+ lifetime sex partners | No | 216 | 80.2 | Ref | | |
| Yes | 52 | 19.8 | 1.15 | 0.54, 2.69 | 0.725 |
| Used condom last sex | No | 176 | 71.9 | 3.96 | 2.12, 7.58 | <0.001* |
| Yes | 92 | 28.1 | Ref | | |
| Contraceptive last sex | No | 129 | 50.2 | 1.49 | 0.81, 2.78 | 0.204 |
| Yes | 139 | 49.8 | Ref | | |
| Sex under alcohol influence | No | 225 | 82.0 | Ref | | |
| Yes | 43 | 18.0 | 2.63 | 0.996, 9.08 | 0.079 |
| Experienced GBV | No | 232 | 85.3 | Ref | | |
| Yes | 36 | 14.7 | 4.65 | 1.93, 13.87 | 0.002* |
| STI last 12 months | No | 229 | 85.3 | Ref | | |
| Yes | 39 | 14.7 | 2.85 | 1.33, 6.81 | 0.011* |
Multivariable analysis
AGYW aged 20–24 years had higher odds of testing for HIV (AOR: 2.40, 95% CI: 1.44, 4.02, p = 0.001). Relative to those aged between 15–19 years. Additionally, married AGYW exhibited a significantly higher odds of testing for HIV (AOR 10.50, 95% CI: 3.63, 44.58, p = 0.000) compared to single and seperated. AGYW aged 15–24 years, those who failed to use condoms in their last sexual encounter were more likely to opt for HIV testing (AOR: 4.27, 95% CI: 2.25, 8.30, p < 0.001) relative to those who use condoms in their last sexual encounter. These findings highlight the substantial impact of age, marital status, and condom usage on HIV testing behaviours within this demographic group (Table 3).
Table 3. Multivariable logistic regression model assessing sociodemographic and risky sexual behaviour factors associated with utilization of HIV testing services.
| Variable | Adjusted OR | 95% CI | P-value |
|---|
| Age (grouped) | 15–19 yrs. | Ref | | |
| 20–24 yrs. | 2.4 | 1.44, 4.02 | <0.001* |
| Employment status | Business | Ref | | |
| Not employed | 0.81 | 0.16, 3.15 | 0.780 |
| Employed | 0.52 | 0.10, 2.25 | 0.398 |
| Average monthly income | No income | 0.42 | 0.02, 5.12 | 0.518 |
| <10,000 | 0.64 | 0.03, 7.18 | 0.734 |
| 10,000 - 20,000 | 1.22 | 0.05, 15.76 | 0.883 |
| 20,000 - 30,000 | Ref | | |
| Marital status | Single | Ref | | |
| Married | 10.5 | 3.63, 44.58 | <0.001* |
| Separated | - | - | 0.984 |
| Used condom last sex | No | 4.27 | 2.25, 8.30 | <0.001* |
| Yes | Ref | | |
| Sex under alcohol influence | No | Ref | | |
| Yes | 2.99 | 1.04, 11.02 | 0.064 |
| Experienced GBV | No | Ref | | |
| Yes | 1.8 | 0.58, 6.88 | 0.341 |
| STI last 12 months | No | Ref | | |
| Yes | 0.66 | 0.25, 1.89 | 0.411 |
Discussion
The study findings indicated that adolescent girls and young women between the age of 20–24 years had testing rate of 71.3% or were 4.5 times likely to test for HIV. The findings concur with studies conducted in different countries which attributed age among other sociodemographic factors to have a significant association with utilization of HIV testing services among the adolescent girls and young women as those aged 20 and above were more likely to utilize HIV testing services compared to those aged between 15–19 years in most Sub-Saharan Africa1,21. Better testing rates for AGYW between 20–24 years may imply that these are young women who have completed secondary education and have a higher chance of getting or accessing information on HIV awareness, better understating on the importance of HIV testing which may drive them to make evidence-based decision thus increasing their chances of being tested. Additionally, this group is more likely to have sexual partners older than them due to material benefits to meet other basic needs that they may not be getting from their parents or guardians, further, they may not be first-time testers but had been tested for HIV even before the study16. On the contrast, there is probability that AGYW younger than 20 years of age have shorter sexual experience and hence less informed on sexual matters compared to older one thus disparity in HIV testing.
Participants who had attained secondary and tertiary education had better testing rates at 63.5% and 23.5% respectively an indication that the more the AGYW are educated, the more likely they are to test for HIV compared to less educated, this is also true since the only participant who did not have formal education had not tested for HIV. Other studies indicate that people who are educated up to secondary education level and above are more likely to utilize HIV testing services compared to those with primary or no education22,23. With majority having attained secondary education, it points to better overall achievement in school enrolment, greater empowerment, and knowledge on sexual and reproductive health among the residents and a pointer to association between education level and utilization of HIV testing.
The study findings indicate that the testing prevalence for the participants in Kibra which is an informal settlement was 60.7%, the finding are not consistent with a study in Viwandani and Korogocho slums in Nairobi which showed that AGYW are less aware of their HIV status compared to those above 25 years16. Improvement in testing rates among this group may be attributed to the concerted efforts by the Ministry of Health in implementing various interventions like campaigns promoting HIV testing, increased availability of HIV testing centres and youth friendly HIV testing services in the informal settlements all geared towards ending HIV pandemic and achieving UNAIDS target to end HIV pandemic by 2030.
Majority of the participants who were married had tested for HIV which may be attributed to the program of prevention of perinatal transmission which requires that all pregnant and expectant mothers attending antennal clinics should be initiated on provider HIV testing services for them to understand the potential of reducing the chances of transmitting HIV to their unborn child hence are more likely to be tested for HIV. Studies in sub-Saharan Africa have shown that most indicated that married people were more likely to utilize HIV testing services compared to those not married or in any union as more countries adopt policies to encourage HIV testing8,24,25. This implies the importance of prevention of mother to child transmission (PMTCT) program in sensitizing expectant mothers on the advantages of undergoing HIV testing during pregnancy, labour, and delivery and postnatally, the importance of training health care workers and care givers on optimizing the interventions of HIV prevention including awareness on HIV and differentiated prevention services like PrEP that focuses on AGYW.
The study demonstrated that AGYWs who had sexual intercourse without using condom, who had sexual intercourse under the influence of alcohol, who had contracted STI in the last 12 months and who had experienced gender-based violence were more likely to test for HIV. Similarly, studies in Zimbabwe and Ethiopia indicated that AGYW who engage in sex for monetary gains are less likely to utilize HIV testing services compared to those who don’t do it for money, those who have multiple sexual partners are likely to test compared to those with only one, additionally, those who use condoms during sexual intercourse are less likely to test compared to those who don’t use8,9. The findings of the study underscore the need for interventions targeting the young AGYWs to understand the risks involved in early sexual debut and other available protective measures to prevent HIV transmission such as Pre and Post exposure prophylaxis.
Study limitations
The study was cross sectional, no causal conclusions or inference on causality can be drawn from the assessed factors, although the sample included in the study was representative, Kibra is only one of seventeen (17) sub counties in Nairobi County, it’s an informal settlement hence study findings may not be generalizable to other formal and urban settlements. The study relied on self-report on the variables assessed which may be influenced by social disparities, several other variables affecting utilization of HIV testing services such as individual level factors, hospital level factors, perceived vulnerabilities and risks, access to testing sites were not assessed hence should be included in future studies. However, the study provided pivotal insights necessary for developing targeted behavioural interventions that address the specific challenges faced by AGYW, thus contributing significantly to the design of more effective public health strategies.
Conclusion
Risky sexual behaviours among the AGYW in Kibra sub county was noted to be common and may mirror other findings on HIV burden among populations in informal settlements. This study established a clear link between sociodemographic characteristics and risky sexual behaviours. Utilization of HIV testing among AGYW is low., efforts to enhance testing rates are vital. Interventions should align with acceptable methods, focusing on this high risk population to ensure effective HIV care and prevention. The ministry of health should consider integration of HIV services in various service delivery points, upscale the uptake of HIV self-testing for both oral and blood based, social support and protective measures for AGYW as crucial in HIV response. Despite limitations, the study contributes to knowledge on the association between risky sexual behaviours and HIV testing in Kenya, more research should be conducted considering other factors such as individual level factors, hospital level factors, perceived vulnerabilities and risks, access to testing sites among other variables.
Ethics and consent
Ethical clearance was obtained from Jomo Kenyatta University of Agriculture and Technology Research Committee (ref number. JKU/ISERC/02316/0832; 23 February 2023). Research permits were secured from the National Commission for Science Technology and Innovations (NACOSTI) and Nairobi County Ethical and Research Committee. Written informed consent was obtained from participants (or the guardians/parents of the participants under 18 years old, with assent being obtained from the participants) before they filled out the questionnaire, ensuring full disclosure of study purpose, risks, and benefits.
Authors’ contributions
OMM contributed by drafting the initial manuscript. KN meticulously reviewed the manuscript and provided valuable insights. AGM played a crucial role in conducting the statistical analysis. All authors were actively involved in the major revisions, ensuring the manuscript's accuracy and coherence.
Faculty Opinions recommendedReferences
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