Human Papillomavirus epidemiology among women seeking HIV care at two Ugandan rural hospitals

Human Papillomavirus epidemiology among women seeking HIV care at two Ugandan rural hospitals | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Human Papillomavirus epidemiology among women seeking HIV care at two Ugandan rural hospitals Kabali Bwogi, Justine Kimbowa Nakiwala, Ivan Kasamba, Christopher Bwanika, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6883555/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 14 You are reading this latest preprint version Abstract Background Persistent human papillomavirus (HPV) infection is a significant precursor to cervical abnormalities and invasive cancer. While the causal relationship between specific HPV types and cervical cancer is established, little is known about the distribution of HPV types among women living with HIV (WLWH) in Uganda. We aimed to describe the epidemiology of HPV types among women living with HIV at Mityana and Kiboga Hospitals in rural central Uganda. Methods A retrospective review of demographic and clinical data, including age and antiretroviral therapy (ART) history, was conducted among WLWH tested for HPV between July 2021 and July 2022. Real-time Polymerase Chain Reaction assay (RT-PCR) detected HPV 16, 18/45, and other pooled high-risk types. HPV infections were categorized into single, double, and multiple subtypes. Statistical analysis involved Chi-square tests and modified Poisson regression with robust standard error models to evaluate associations and identify factors linked with HPV infection. Results Among 1305 WLWH, the overall prevalence of HPV infection was 39.1%. HPV16 and HPV18/45 were the most common genotypes, with a prevalence of 8.1% and 8.2%, respectively. Multiple HPV infections were observed in 18.4% of cases, with combinations of HPV 16, HPV 18/45, and other high-risk HPV types. Increasing age was significantly associated with a lower prevalence of HPV infection (PR = 0.97; 95% CI: 0.95–0.99; p = 0.003). Conclusion The study highlights a high prevalence of HPV infection among WLWH in rural Uganda, with specific genotypes and risk factors identified. These findings underscore the importance of comprehensive cervical cancer prevention programs, including HPV vaccination, regular screening. Further research is needed to validate these findings and evaluate the effectiveness of interventions to reduce the burden of HPV-related diseases among WLWH in Uganda. human papillomavirus types women living with HIV prevalence oncogenes Figures Figure 1 Background Globally, women living with HIV (WLWH) have a significantly increased risk of cervical cancer ( 1 , 2 ). In 2018, the risk of cervical cancer among WLWH was six times higher than among women in the general population( 3 ). Global estimates show that 5.8% of new cervical cancer cases in 2018 were among WLWH, and 4.9% were attributable to HIV infection, with Eastern and Southern Africa (SEA) being the most affected regions ( 4 ). High cervical cancer prevalence among WLWH has been observed in southern (63.8%) and eastern (27.4%) Africa ( 5 , 6 ). Cervical cancer is understood to mainly be caused by persistent human papillomavirus (HPV) infection ( 2 , 7 , 8 ). HPV exists in more than 120 different genotypes; however, only 13–15 are found in cervical cancers and other cancers and are called ‘high risk’ HPV (HR-HPV) ( 9 – 11 ). HPV 16 and 18 are associated with two-thirds of all cervical cancers as well as subtypes of cancer of the vulva, vagina, anus, oropharynx, and skin ( 9 , 12 ). Globally, HPV 16 is linked to approximately 50% of the cervical cancers ( 13 ). HIV enhances HPV-induced carcinogenesis ( 6 , 14 ), increasing both the risk and the early development of cancer ( 2 , 15 ). Compared to HIV-negative women, cervical cancer mortality is two times higher among WLWH ( 2 ). Prior studies in Uganda have reported a high prevalence of HR-HPV among both HIV-negative and WLWH. One study reported prevalence ranges of 10.2–40% and 37–100% among HIV-negative women and WLWH, respectively ( 9 ). However, these studies were conducted in urban settings. The epidemiology of HPV may differ by context, yet understanding the HPV epidemiology may inform the tailoring of public health interventions such as education and screening. Our study aimed to describe the epidemiology of HPV among women seeking HIV care at two rural Ugandan hospitals. Materials and methods Study design and setting We conducted a retrospective analysis of care records from WLWH who underwent HPV testing at two public district hospitals in central Uganda (Mityana and Kiboga District Hospitals). We included records of WLWH ≥ 18 years, enrolled in the Antiretroviral Therapy (ART) care program, had an HPV test between July 2021 and July 2022, and test results reported as either "positive" or "negative" for HPV 16, 18/45, and other HR-HPV. HPV testing was performed using the GeneXpert HPV DNA Assay, which is part of routine HIV care for WLWH at these hospitals. Test results were extracted from electronic medical records and laboratory health management information systems, which are integrated into the hospitals' digital healthcare infrastructure. This electronic system ensures accurate and efficient data collection, storage, and retrieval. Data abstraction Using a standardized checklist, we abstracted data from electronic medical records and laboratory health management information systems, including HPV test results and genotypes, clinical data: ART initiation and current regimen, viral load, body mass index (BMI), WHO clinical staging, and demographics: age and duration on ART. Statistical Analysis The primary outcome was HPV infection, defined as having a record of any positive HPV test result. Frequency distributions and proportions were utilized to describe demographic characteristics and HPV genotypes among WLWH. We evaluated factors associated with HPV infection using a modified Poisson regression with robust standard errors. Factors were incorporated into the model based on hierarchical relationships, beginning with distal factors and progressing to proximate ones. The normalized residual sum of squares test was performed to evaluate the model fit, which indicated a good fit. Crude and adjusted prevalence ratios (PR) and 95% confidence intervals (CI) were calculated. Statistical significance was determined at the 5% level. Analyses were conducted using Stata version 12.0 (StataCorp, College Station, TX). Results Social demographic characteristics of the WLWH in Uganda A total of 1305 records from WLWH were included in the analysis. The median age was 36 years [interquartile range (IQR) 30–42]. Over half of WLWH (n = 911, 69.81%) had been on antiretroviral therapy (ART) for over five years. Table 1 shows characteristics of study participants. Table 1 Clinical characteristics of women living with HIV at two public hospitals in Uganda. Variable Category Median (Q1, Q3) Total n (%) Body mass index 24.13(21.2,27.4) Art category*(n = 1304) DTG based 1289 (98.85) Non DTG based 15 (1.15) Viral load status*(n = 1272) Non-Suppressed 37(2.91) Suppressed 1235 (97.09) HIV WHO clinical stage*(n = 1182) Stage 1 864 (73.10) Stage 2 255 (21.57) Stage 3 53 (4.48) Stage 4 10 (0.85) CD4 category*( n = 699) 201 574(82.1) *Missing data, n-number of participants, %percentage, Q1-1st quartile, Q3rd quartile. The participants' median body mass index (BMI) was 24.13 (IQR: 21.22–27.43). Most participants, 1289 (98.85%), used a Dolutegravir (DTG)–based regimen. Additionally, 1235 (97.09%) WLWH had a suppressed viral load, and 864 (73.10%) were classified under HIV WHO clinical stage 1. Prevalence of HPV among women living with HIV in Uganda. The prevalence of HPV among 1305 WLWH was 39.1% (n = 510, 95% CI; 36.46–41.76). Among the HPV-positive patients (n = 510), 211 came from Kiboga Hospital, with the remaining 299 from Mityana Hospital. Pooled HR-HPV subtypes were detected in 399 cases (30.57%, 95% CI, 28.13–33.13). The prevalence of specific oncogenic sub-types HPV16 was 8.12% (n = 106, 95%CI; 06.76–09.73) and HPV18 at 8.20%, (n = 107, 95%CI; 06.83–09.82) respectively. HPV Distribution among different categories of women living with HIV in Uganda. The HPV distribution among different participant categories revealed that most HPV patients (n = 113, 22.26%) were aged 30 to 34. The proportion of participants with HPV was significantly different in all age categories, with a P-value = 0.001. The highest prevalence for HPV16 was among participants aged 35–39 (n = 25, 23.6%), while HPV18/45 was most common among those aged 40–44 (n = 26, 24.0%). Of all age groups, 399 individuals between the ages of 30 and 34 were found to have HR-HPV (n = 96, 24.1%). Most HPV patients had been on ART for over five years (60.4%). There was a significant association between ART duration and testing positive for HPV (P < 0.001). The WLWH, who had been on ART for more than five years, had the highest number of cases within various subgroups of HPV. Within this group, 71 individuals (67.0%) had HPV16, 63 individuals (58.9%) had HPV16/45 and 234 individuals (58.7%) had HR- HPV. Across all BMI categories, most participants with HPV had a BMI of 24.9, 212 (47.6%), though there was no significant association between BMI category and having HPV (p-value: 0.790). Also, the BMI category of 18.6 to 24.9 had the most significant number of participants with HPV subgroups, 46 (50.0% for HPV16, 44 (47.3% for HPV18/45), and 167 (48.1%) for HR-HPV. 501 (98.2%) of the 510 participants with HPV were on a DTG-based ART regimen, but there was no significant association between the ART category and HPV (P-value: 0.240). Also, the DTG-based regimen contained most participants with HPV across all HPV subgroups, but this had no significant association. Table 2 Distribution of HPV among different categories of women living with HIV in Uganda. Variable HPV n (%) HPV16 n (%) HPV18/45 n (%) HR-HPV n (%) Age Group (years) 15–19 4 (0.8%) 1 (0.9%) 1 (0.9%) 3 (0.8%) 20–24 38 (7.5%) 8 (7.6%) 5 (4.7%) 32 (8.0%) 25–29 99 (19.4%) 16 (15.1%) 22 (20.6%) 81 (20.3%) 30–34 113 (22.2%) 24 (22.6%) 19 (17.8%) 96 (24.1%) 35–39 97 (19.0%) 25 (23.6%) 24 (22.4%) 68 (17.0%) 40–44 88 (17.2%) 18 (17.0%) 26 (24.0%) 64 (16.0%) 45–49 48 (9.4%) 8 (7.6%) 7 (6.5%) 35 (8.8%) 50 and above 23 (4.5%) 6 (5.7%) 3 (2.8%) 20 (5.0%) Duration on ART < 0.9 months 13 (2.5%) 0 (0.0%) 4 (3.7%) 11 (2.8%) 1–4.9 years 189 (37.1%) 35 (33.0%) 40 (37.4%) 154 (38.6%) ≥ 5 years 308 (60.4%) 71 (67.0%) 63 (58.9%) 234 (58.7%) BMI Category =30 66 (14.8%) 9 (9.8%) 12 (12.9%) 54 (15.6%) ART Category DTG-based 501 (98.2%) 103 (97.2%) 105 (98.1%) 392 (98.3%) NON-DTG based 9 (1.8%) 3 (2.8%) 2 (1.9%) 7 (1.8%) Distribution Characteristics of Single and Multiple Infections. The analysis of HPV infections in all the samples revealed that among the 510 individuals, 20.39% (104) were infected with a single type of HPV, while 18.43% (94) had multiple HPV infections. Among those with multiple HPV infections, 60.94% (78 out of 128) had a combination of HPV 18 along with other high-risk HPV types, 28.13% (36 out of 128) had a combination of HPV 16 along with other high-risk HPV types, and 10.94% (14 out of 128) had a combination of HPV 16 and 18/45 (Table 2 ). Further investigation into multiple infections revealed that the age group between 35 and 39 had the highest infection rates for both HPV 16 + 18/45, the age group between 30 and 34 had the highest infection rates for HPV + other high-risk HPV types, and the age group between 40 and 44 had the highest infection rates for HPV 18 + other high-risk HPV types (Fig. 1 ). Factors Associated with HPV among women living with HIV in Uganda. Factors associated with HPV among WLWH are presented in Table 3 . In bivariate analysis, increasing age was significantly associated with a lower prevalence of HPV infection (PR = 0.97; 95% CI: 0.95–0.99; p = 0.003). Participants presenting with WHO clinical stage III or IV had a significantly higher prevalence of HPV infection compared to those in stage I or II (PR = 1.73; 95% CI: 1.01–2.96; p = 0.044). Other factors such as ART duration, ART regimen category, CD4 count, viral load status, and BMI category showed no statistically significant associations with HPV prevalence in bivariate analysis ( p > 0.05 for all). In multivariate analysis, age remained independently associated with lower HPV prevalence (adjusted PR = 0.97; 95% CI: 0.96–0.99; p < 0.001). Although WHO clinical stage III/IV had a higher prevalence ratio compared to stage I/II (adjusted PR = 1.58; 95% CI: 0.95–2.61), the association was not statistically significant ( p = 0.077). Table 3 Multivariate analysis of factors associated with HPV among 1305 WLWH in Uganda. Variable Category Prevalence ratio (PR) (95% CI) p-value Multivariate PR (95% CI) p-value Age Continuous 0.97 (0.95–0.99) 0.003 0.97 (0.96–0.99) 0.000 ART Duration > 10 Years 201 < 200 0.88 (0.57–1.35) 0.558 – – Viral Load Suppressed Non-Suppressed 1.40 (0.80–2.44) 0.235 – – BMI Category 18.6–24.9 25-29.9 0.81 (0.58–1.11) 0.191 – – 30 above 0.93 (0.63–1.39) 0.730 – – < 18.5 1.02 (0.55–1.89) 0.949 – – WHO Stage Stage I & II Stage III & IV 1.73 (1.01–2.96) 0.044 1.58 (0.95–2.61) 0.077 Discussion This study investigated the prevalence and factors associated with HPV infection among WLWH in Uganda. Our findings revealed a high prevalence of HPV infection, with 39.1% of women testing positive. This prevalence rate was higher compared to previous studies conducted in Uganda ( 16 – 18 ) and other African countries( 19 , 20 ), which ranged between 17% and 25%. However, studies focusing on WLWH showed prevalence rates in line with the present study, ranging from 30–64%. ( 19 – 23 ). The study demonstrated that HPV infection rates varied across different age groups, with a significant peak in the 30–34 age group. However, it should be noted that individual HPV genotypes 16 and 18 peaked in the 35–39 and 40–44 age groups, respectively. This finding aligns with previous reports and can be attributed to more frequent sexual intercourse and inadequate safety awareness among young women ( 20 , 24 ) ( 11 ). HPV infection significantly declined in women above the age of 50 years, consistent with previous studies( 9 , 11 , 24 ) attributing this decrease to age and behavioral factors, however, this study cannot draw such conclusions ( 9 ). Additionally, the research findings revealed that many female participants in this study exhibited infection with a singular HPV genotype. Nevertheless, it is crucial to acknowledge the potential occurrence of multiple types of infections. Existing literature has consistently indicated that the presence of multiple HPV genotypes could lead to prolonged infection persistence, potentially heightening the risk of developing cervical cancer ( 7 , 11 ). The high prevalence of HPV among WLWH is of great concern due to the increased risk of developing cervical cancer. Persistent infection with high-risk HPV types is a key factor in developing cervical intraepithelial neoplasia and cervical cancer. The most common genotypes identified were the pooled high-risk HPV( 11 , 20 , 25 ). Therefore, future development of multivalent preventive HPV vaccines should consider including additional high-risk HPV genotypes beyond the currently targeted types 16/18 ( 9 ). This is reinforced by a study done in Ghana that showed an emerging possibility of other HR-HPV apart from HPV 16 and 18, being more common ( 26 ). And an epidemiological study in Uganda demonstrated that HR-HPV, apart from HPV 16 and 18, accounts for the highest number of HPV infections among women, and given that these other HR-HPV oncogenes account for 30% of invasive cervical cancer, an understanding of these other HR-HPV oncogenes is warranted among women living with HIV( 9 ). Uganda, through the Ministry of Health, has led efforts to combat the threat of HPV by making vaccinations available; however, this initiative has largely been unsuccessful, resulting in low vaccination uptake( 27 , 28 ). Therefore, approaches that involve men in the fight against the spread of HPV infections would be warranted, as studies in Uganda have shown a high incidence of 66.5 per 100 person-years in HIV-positive men and 32.9 per 100 person-years among HIV-negative men, with a prevalence of 90.7% among men living with HIV and 60.9% among HIV-negative men ( 29 ). Several studies in sub-Saharan Africa and similar settings have found that HPV infection rates among WLWH are highest in the youngest age groups and decline with increasing age. For example, a Malian cohort of WLWH reported a dramatically higher prevalence of high‐risk HPV in women under 35 (30%) compared to older women (11.1%) ( 30 ). Likewise, a South African study in the Eastern Cape found peak HPV prevalence (≈ 80.9%) in women aged 18–25 and a much lower prevalence (≈ 46.3%) in women over 45, with high‐risk HPV infections significantly decreasing with age ( 31 ). A recent national analysis in Uganda showed that WLWH aged 36–49 had lower overall high‐risk HPV prevalence than those aged 25–35 ( 32 ). In Zambia, each additional year of age was associated with an approximately 2% reduced odds of HPV infection ( 33 ). These consistent trends are attributed to behavioral factors (e.g. higher recent sexual activity and partner change in younger women) and immunological factors (older women may have cleared past infections or developed partial immunity). However, persistent infection remains a concern in all age groups. In line with our aim to characterize HPV epidemiology in rural Mityana and Kiboga, the significant age effect observed – namely, higher HPV rates among younger WLWH – accords with these regional findings. This underscores that age is an important determinant of HPV risk among WLWH and suggests that prevention and screening efforts in rural Uganda should particularly target younger WLWH to reduce the HPV burden. The study highlighted an association between a longer duration of ART and a higher prevalence of HPV infection among women who had been on ART for five years and above and showed a higher prevalence of HPV and this finding is consistent with previous studies reporting an increased risk of HPV persistence and progression to cervical dysplasia among women on long-term ART( 17 , 34 ). Despite the positive impact of ART on immune function and longevity in HIV-positive women, cervical cancer remains high( 35 ). WLWH experience increased prevalence and incidence of cervical HPV infections and higher risks of persistent HPV infections, subsequent cervical intraepithelial lesions, and cervical cancer( 36 ). Furthermore, women living with HIV are more likely to have high-risk HPV infections characterized by higher prevalence rates, co-infection, persistence, and reactivation. ( 37 , 38 ). It is important to note that the association between ART duration and HPV infection may be multifactorial, involving both immunological and potential behavioral factors such as sexual behavior and adherence to ART. This line of research holds valuable insights that could potentially aid in developing efficacious biological therapeutics targeting HPV and HPV-related diseases. Moreover, such advancements may have significant implications for preventing HPV-related cancers in individuals infected with high-risk HPV strains. Several limitations should be acknowledged in the study. Firstly, the cross-sectional design limits the ability to establish a causal relationship between the identified factors and HPV infection. Longitudinal studies are necessary to understand the dynamic nature of HPV infection in this population. Secondly, the study was conducted in specific healthcare settings in Uganda, which may restrict the generalizability of the findings to other populations or regions. Further research in diverse settings must validate these findings and ensure their applicability to broader populations. Strengths of the study include the comprehensive nature of data collection, which provided valuable insights into the prevalence, distribution, and associated factors of HPV infection among women living with HIV in Uganda. The inclusion of clinical characteristics such as body mass index, ART category, viral load status, and WHO clinical stage enriched the understanding of the cohort and allowed for more robust interpretations. In conclusion, our study highlights the high prevalence of HPV infection among WLWH in Uganda. The prevalence was higher than in previous studies in Uganda and other African countries. Age was found to be associated with HPV infection, with the highest prevalence observed in the 30–34 age group. The most common HPV genotypes identified were high-risk genotypes pooled together during testing. Longer duration of ART and lower CD4 counts were associated with higher HPV prevalence. The association between the CD4 category, longer ART duration, and HPV infection emphasizes the importance of regular monitoring of immunological status and early initiation of ART in this population. These findings have implications for implementing comprehensive cervical cancer prevention programs that include HPV vaccination, regular cervical cancer screening, and prompt treatment of cervical dysplasia. Future research should focus on validating these findings in diverse settings and exploring the effectiveness of these interventions to reduce the burden of cervical cancer among women living with HIV. Abbreviations Antiretroviral Therapy (ART); Body Mass Index (BMI); Centers for Disease Control and Prevention (CDC); Confidence Interval (CI); Dolutegravir (DTG); Eastern and Southern Africa (SEA); Electronic Medical Record (EMR); High-Risk Human Papillomavirus (HR-HPV); Human Immunodeficiency Virus (HIV); Human Papillomavirus (HPV); Sub-Saharan Africa (SSA); Women Living with HIV (WLWH); World Health Organization (WHO). Declarations Acknowledgements We are grateful to all the patients whose data were used in the study. We thank Dr. Richard Muhindo for the insightful advice during the writing and review of the manuscript. Authors’ contributions BK conceived the study. BK, JKN, IK, CB, JBB, JN, CS, RM, and BM participated in the study design and data collection. BK and IK participated in data analysis. All authors participated in writing and reviewing the manuscript. All authors read and approved the final manuscript. Ethics approval and consent to participate The study was approved by the Mildmay Uganda Research and Ethics Committee (REC REF 0804–2018), as well as the U.S Centers for Disease Control and Prevention (U.S CDC) under 45 C.F.R. part 46.101(c); 21 C.F.R. part 56. A waiver of consent was granted to use secondary data because the data were sourced from a publicly accessible Electronic Medical Records (EMR) platform. All methods were performed in accordance with the Declaration of Helsinki. Funding This research received support from the US President’s Emergency Plan for AIDS Relief (PEPFAR) via the Centers for Disease Control and Prevention (CDC), grant number 1NU2GGH002046-01–00. The views expressed in this manuscript are those of the author(s) and do not necessarily reflect the official stance of the funding organizations. 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Nakigozi H, Ndejjo R, Bazeyo W, Nabaggala A, Achola C, Iga M, et al Prevalence of genital high-risk human papillomavirus infections and associated factors among women living with human immunodeficiency virus in Uganda.BMC Cancer. 2024;24(1):243. Muchaili L, Simushi P, Mweene BC, Mwakyoma T, Masenga SK, Hamooya BM. Prevalence and correlates of Human Papillomavirus infection in females from Southern Province, Zambia: A cross-sectional study. Okunade KS, editor PLOS ONE. 2024;19(8):e0299963. Looker KJ, Rönn MM, Brock PM, Brisson M, Drolet M, Mayaud P, et al Evidence of synergistic relationships between HIV and Human Papillomavirus (HPV): systematic reviews and meta-analyses of longitudinal studies of HPV acquisition and clearance by HIV status, and of HIV acquisition by HPV status. J Int AIDS Soc [Internet]. 2018 Jun [cited 2023 Jun 20];21(6). Available from: https://onlinelibrary.wiley.com/doi/10.1002/jia2.25110 Tong Y, Orang’o E, Nakalembe M, Tonui P, Itsura P, Muthoka K, et al The East Africa Consortium for human papillomavirus and cervical cancer in women living with HIV/AIDS.Ann Med. 2022;54(1):1202–11. De Vuyst H, Lillo F, Broutet N, Smith JS HIV, human papillomavirus, and cervical neoplasia and cancer in the era of highly active antiretroviral therapy.Eur J Cancer Prev. 2008;17(6):545–54. Luckett R, Painter H, Hacker M, Simon B, Seiphetlheng A, Erlinger A, et al Persistence and clearance of high-risk human papillomavirus and cervical dysplasia at 1 year in women living with human immunodeficiency virus: a prospective cohort study.BJOG Int J Obstet Gynaecol. 2021;128(12):1986–96. Du P. Human Papillomavirus Infection and Cervical Cancer in HIV + Women. In: Meyers C, editor HIV/AIDS-Associated Viral Oncogenesis [Internet]. Cham: Springer International Publishing; 2019 [cited 2023 Jun 20]. p. 105–29. Available from: http://link.springer.com/10.1007/978-3-030-03502-0_5 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 15 Apr, 2026 Reviews received at journal 02 Apr, 2026 Reviewers agreed at journal 31 Mar, 2026 Reviews received at journal 18 Mar, 2026 Reviewers agreed at journal 09 Mar, 2026 Reviews received at journal 29 Sep, 2025 Reviewers agreed at journal 09 Sep, 2025 Reviewers agreed at journal 09 Sep, 2025 Reviewers agreed at journal 08 Sep, 2025 Reviewers invited by journal 07 Sep, 2025 Editor invited by journal 21 Jul, 2025 Editor assigned by journal 17 Jun, 2025 Submission checks completed at journal 17 Jun, 2025 First submitted to journal 12 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6883555","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":513711282,"identity":"69088efc-a196-47e0-81c5-0b8832158583","order_by":0,"name":"Kabali Bwogi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYBACCQYeBoYHBgeATMbGBwwMB4jUkgDR0mxAghaISjYJorRItp89+CGh4E5iP//itmqemjty/AzMDx/dwKNFmicvWSLB4FnizBkP227zHHtmLNnAZmycg0eLHEOOAVDL4dwNNw4CtbAdTtxwgIdNGq8W/jfGP2Bainn+EaFFWiLHDGLL+cY2Zt42IrRIzniXZgH0S/3MGYzNknP7DhtLNhPwi8T53MM3Pvy5Y8zPf/zhhzffDsvxszc/fIxPC5LmBAYmHhCDmSjlIMB/gIHxB9GqR8EoGAWjYCQBAHocVnN67wcyAAAAAElFTkSuQmCC","orcid":"","institution":"Mildmay Uganda","correspondingAuthor":true,"prefix":"","firstName":"Kabali","middleName":"","lastName":"Bwogi","suffix":""},{"id":513711283,"identity":"d2665aac-cd6c-4dda-97fd-9547f735a4fd","order_by":1,"name":"Justine Kimbowa Nakiwala","email":"","orcid":"","institution":"Mildmay Research Centre","correspondingAuthor":false,"prefix":"","firstName":"Justine","middleName":"Kimbowa","lastName":"Nakiwala","suffix":""},{"id":513711284,"identity":"561c5b0b-869d-45fd-8e2a-34254dd5a557","order_by":2,"name":"Ivan Kasamba","email":"","orcid":"","institution":"Mildmay Uganda","correspondingAuthor":false,"prefix":"","firstName":"Ivan","middleName":"","lastName":"Kasamba","suffix":""},{"id":513711285,"identity":"d07e4411-7032-462a-bd28-e589cdb9a9a4","order_by":3,"name":"Christopher Bwanika","email":"","orcid":"","institution":"Mildmay Uganda","correspondingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"","lastName":"Bwanika","suffix":""},{"id":513711286,"identity":"36a9470f-79c9-4e49-a724-6d20252c44a7","order_by":4,"name":"Joseph Baruch Baluku","email":"","orcid":"","institution":"Kiruddu National Referral Hospital","correspondingAuthor":false,"prefix":"","firstName":"Joseph","middleName":"Baruch","lastName":"Baluku","suffix":""},{"id":513711287,"identity":"73eb0d62-0d94-4dff-96f4-37d5a744bc23","order_by":5,"name":"Jane Nakawesi","email":"","orcid":"","institution":"Mildmay Uganda","correspondingAuthor":false,"prefix":"","firstName":"Jane","middleName":"","lastName":"Nakawesi","suffix":""},{"id":513711288,"identity":"7d5f9af4-b9ae-4953-b83f-1c3eb2f7d070","order_by":6,"name":"Catherine Senyimba","email":"","orcid":"","institution":"Mildmay Uganda","correspondingAuthor":false,"prefix":"","firstName":"Catherine","middleName":"","lastName":"Senyimba","suffix":""},{"id":513711289,"identity":"4d1a8e5c-575e-4a9f-bd78-f6060890a768","order_by":7,"name":"Ronald Mulebeke","email":"","orcid":"","institution":"Mildmay Research Centre","correspondingAuthor":false,"prefix":"","firstName":"Ronald","middleName":"","lastName":"Mulebeke","suffix":""},{"id":513711290,"identity":"03feccc3-bb30-4bf0-b752-3ab7ac4a9976","order_by":8,"name":"Barbara Mukasa","email":"","orcid":"","institution":"Mildmay Uganda","correspondingAuthor":false,"prefix":"","firstName":"Barbara","middleName":"","lastName":"Mukasa","suffix":""}],"badges":[],"createdAt":"2025-06-13 00:38:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6883555/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6883555/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91198444,"identity":"3d659a4a-70c8-4877-baa0-c6451e1e1eeb","added_by":"auto","created_at":"2025-09-12 15:15:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":22639,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eshows the distribution of HPV types.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6883555/v1/bd53fcbb68f63704c87c8037.png"},{"id":91199758,"identity":"e0ec991e-e142-444c-882e-367bdc5c8ab6","added_by":"auto","created_at":"2025-09-12 15:23:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":911056,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6883555/v1/c373f974-f7a0-44d5-b261-632c5fc8c491.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Human Papillomavirus epidemiology among women seeking HIV care at two Ugandan rural hospitals","fulltext":[{"header":"Background","content":"\u003cp\u003eGlobally, women living with HIV (WLWH) have a significantly increased risk of cervical cancer (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). In 2018, the risk of cervical cancer among WLWH was six times higher than among women in the general population(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Global estimates show that 5.8% of new cervical cancer cases in 2018 were among WLWH, and 4.9% were attributable to HIV infection, with Eastern and Southern Africa (SEA) being the most affected regions (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). High cervical cancer prevalence among WLWH has been observed in southern (63.8%) and eastern (27.4%) Africa (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Cervical cancer is understood to mainly be caused by persistent human papillomavirus (HPV) infection (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). HPV exists in more than 120 different genotypes; however, only 13\u0026ndash;15 are found in cervical cancers and other cancers and are called \u0026lsquo;high risk\u0026rsquo; HPV (HR-HPV) (\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). HPV 16 and 18 are associated with two-thirds of all cervical cancers as well as subtypes of cancer of the vulva, vagina, anus, oropharynx, and skin (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Globally, HPV 16 is linked to approximately 50% of the cervical cancers (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). HIV enhances HPV-induced carcinogenesis (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), increasing both the risk and the early development of cancer (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Compared to HIV-negative women, cervical cancer mortality is two times higher among WLWH (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePrior studies in Uganda have reported a high prevalence of HR-HPV among both HIV-negative and WLWH. One study reported prevalence ranges of 10.2\u0026ndash;40% and 37\u0026ndash;100% among HIV-negative women and WLWH, respectively (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). However, these studies were conducted in urban settings. The epidemiology of HPV may differ by context, yet understanding the HPV epidemiology may inform the tailoring of public health interventions such as education and screening. Our study aimed to describe the epidemiology of HPV among women seeking HIV care at two rural Ugandan hospitals.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and setting\u003c/h2\u003e\u003cp\u003e We conducted a retrospective analysis of care records from WLWH who underwent HPV testing at two public district hospitals in central Uganda (Mityana and Kiboga District Hospitals). We included records of WLWH\u0026thinsp;\u0026ge;\u0026thinsp;18 years, enrolled in the Antiretroviral Therapy (ART) care program, had an HPV test between July 2021 and July 2022, and test results reported as either \"positive\" or \"negative\" for HPV 16, 18/45, and other HR-HPV. HPV testing was performed using the GeneXpert HPV DNA Assay, which is part of routine HIV care for WLWH at these hospitals. Test results were extracted from electronic medical records and laboratory health management information systems, which are integrated into the hospitals' digital healthcare infrastructure. This electronic system ensures accurate and efficient data collection, storage, and retrieval.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData abstraction\u003c/h3\u003e\n\u003cp\u003eUsing a standardized checklist, we abstracted data from electronic medical records and laboratory health management information systems, including HPV test results and genotypes, clinical data: ART initiation and current regimen, viral load, body mass index (BMI), WHO clinical staging, and demographics: age and duration on ART.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eThe primary outcome was HPV infection, defined as having a record of any positive HPV test result. Frequency distributions and proportions were utilized to describe demographic characteristics and HPV genotypes among WLWH. We evaluated factors associated with HPV infection using a modified Poisson regression with robust standard errors. Factors were incorporated into the model based on hierarchical relationships, beginning with distal factors and progressing to proximate ones. The normalized residual sum of squares test was performed to evaluate the model fit, which indicated a good fit. Crude and adjusted prevalence ratios (PR) and 95% confidence intervals (CI) were calculated. Statistical significance was determined at the 5% level. Analyses were conducted using Stata version 12.0 (StataCorp, College Station, TX).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eSocial demographic characteristics of the WLWH in Uganda\u003c/h2\u003e\u003cp\u003eA total of 1305 records from WLWH were included in the analysis. The median age was 36 years [interquartile range (IQR) 30\u0026ndash;42]. Over half of WLWH (n\u0026thinsp;=\u0026thinsp;911, 69.81%) had been on antiretroviral therapy (ART) for over five years. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows characteristics of study participants.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical characteristics of women living with HIV at two public hospitals in Uganda.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMedian (Q1, Q3)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTotal n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBody mass index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003e24.13(21.2,27.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArt category*(n\u0026thinsp;=\u0026thinsp;1304)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDTG based\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1289 (98.85)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon DTG based\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15 (1.15)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eViral load status*(n\u0026thinsp;=\u0026thinsp;1272)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-Suppressed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37(2.91)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSuppressed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1235 (97.09)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHIV WHO clinical stage*(n\u0026thinsp;=\u0026thinsp;1182)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e864 (73.10)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e255 (21.57)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e53 (4.48)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (0.85)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD4 category*( n\u0026thinsp;=\u0026thinsp;699)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e124 (17.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;201\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e574(82.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e *Missing data, n-number of participants, %percentage, Q1-1st quartile, Q3rd quartile.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe participants' median body mass index (BMI) was 24.13 (IQR: 21.22\u0026ndash;27.43). Most participants, 1289 (98.85%), used a Dolutegravir (DTG)\u0026ndash;based regimen. Additionally, 1235 (97.09%) WLWH had a suppressed viral load, and 864 (73.10%) were classified under HIV WHO clinical stage 1.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePrevalence of HPV among women living with HIV in Uganda.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe prevalence of HPV among 1305 WLWH was 39.1% (n\u0026thinsp;=\u0026thinsp;510, 95% CI; 36.46\u0026ndash;41.76). Among the HPV-positive patients (n\u0026thinsp;=\u0026thinsp;510), 211 came from Kiboga Hospital, with the remaining 299 from Mityana Hospital. Pooled HR-HPV subtypes were detected in 399 cases (30.57%, 95% CI, 28.13\u0026ndash;33.13). The prevalence of specific oncogenic sub-types HPV16 was 8.12% (n\u0026thinsp;=\u0026thinsp;106, 95%CI; 06.76\u0026ndash;09.73) and HPV18 at 8.20%, (n\u0026thinsp;=\u0026thinsp;107, 95%CI; 06.83\u0026ndash;09.82) respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eHPV Distribution among different categories of women living with HIV in Uganda.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe HPV distribution among different participant categories revealed that most HPV patients (n\u0026thinsp;=\u0026thinsp;113, 22.26%) were aged 30 to 34. The proportion of participants with HPV was significantly different in all age categories, with a P-value\u0026thinsp;=\u0026thinsp;0.001. The highest prevalence for HPV16 was among participants aged 35\u0026ndash;39 (n\u0026thinsp;=\u0026thinsp;25, 23.6%), while HPV18/45 was most common among those aged 40\u0026ndash;44 (n\u0026thinsp;=\u0026thinsp;26, 24.0%). Of all age groups, 399 individuals between the ages of 30 and 34 were found to have HR-HPV (n\u0026thinsp;=\u0026thinsp;96, 24.1%).\u003c/p\u003e\u003cp\u003eMost HPV patients had been on ART for over five years (60.4%). There was a significant association between ART duration and testing positive for HPV (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The WLWH, who had been on ART for more than five years, had the highest number of cases within various subgroups of HPV. Within this group, 71 individuals (67.0%) had HPV16, 63 individuals (58.9%) had HPV16/45 and 234 individuals (58.7%) had HR- HPV. Across all BMI categories, most participants with HPV had a BMI of 24.9, 212 (47.6%), though there was no significant association between BMI category and having HPV (p-value: 0.790). Also, the BMI category of 18.6 to 24.9 had the most significant number of participants with HPV subgroups, 46 (50.0% for HPV16, 44 (47.3% for HPV18/45), and 167 (48.1%) for HR-HPV. 501 (98.2%) of the 510 participants with HPV were on a DTG-based ART regimen, but there was no significant association between the ART category and HPV (P-value: 0.240). Also, the DTG-based regimen contained most participants with HPV across all HPV subgroups, but this had no significant association.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDistribution of HPV among different categories of women living with HIV in Uganda.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHPV n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHPV16 n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHPV18/45 n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHR-HPV n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge Group (years)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u0026ndash;19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1 (0.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1 (0.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e38 (7.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8 (7.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5 (4.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e32 (8.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u0026ndash;29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e99 (19.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16 (15.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22 (20.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e81 (20.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30\u0026ndash;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e113 (22.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24 (22.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19 (17.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96 (24.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e35\u0026ndash;39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e97 (19.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25 (23.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24 (22.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e68 (17.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e40\u0026ndash;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e88 (17.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18 (17.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e26 (24.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e64 (16.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e45\u0026ndash;49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e48 (9.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8 (7.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7 (6.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e35 (8.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e50 and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e23 (4.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6 (5.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3 (2.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e20 (5.0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDuration on ART\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.9 months\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e13 (2.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0 (0.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4 (3.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11 (2.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;4.9 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e189 (37.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35 (33.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40 (37.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e154 (38.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;5 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e308 (60.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e71 (67.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e63 (58.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e234 (58.7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBMI Category\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;18.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31 (7.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7 (7.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9 (9.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e21 (6.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18.5\u0026ndash;24.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e212 (47.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e46 (50.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e44 (47.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e167 (48.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u0026ndash;29.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e136 (30.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30 (32.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28 (30.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e105 (30.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;=30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e66 (14.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9 (9.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e12 (12.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e54 (15.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eART Category\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDTG-based\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e501 (98.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e103 (97.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e105 (98.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e392 (98.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNON-DTG based\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9 (1.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3 (2.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2 (1.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7 (1.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eDistribution Characteristics of Single and Multiple Infections.\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe analysis of HPV infections in all the samples revealed that among the 510 individuals, 20.39% (104) were infected with a single type of HPV, while 18.43% (94) had multiple HPV infections. Among those with multiple HPV infections, 60.94% (78 out of 128) had a combination of HPV 18 along with other high-risk HPV types, 28.13% (36 out of 128) had a combination of HPV 16 along with other high-risk HPV types, and 10.94% (14 out of 128) had a combination of HPV 16 and 18/45 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFurther investigation into multiple infections revealed that the age group between 35 and 39 had the highest infection rates for both HPV 16\u0026thinsp;+\u0026thinsp;18/45, the age group between 30 and 34 had the highest infection rates for HPV\u0026thinsp;+\u0026thinsp;other high-risk HPV types, and the age group between 40 and 44 had the highest infection rates for HPV 18\u0026thinsp;+\u0026thinsp;other high-risk HPV types (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eFactors Associated with HPV among women living with HIV in Uganda.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFactors associated with HPV among WLWH are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In bivariate analysis, increasing age was significantly associated with a lower prevalence of HPV infection (PR\u0026thinsp;=\u0026thinsp;0.97; 95% CI: 0.95\u0026ndash;0.99; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003). Participants presenting with WHO clinical stage III or IV had a significantly higher prevalence of HPV infection compared to those in stage I or II (PR\u0026thinsp;=\u0026thinsp;1.73; 95% CI: 1.01\u0026ndash;2.96; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.044). Other factors such as ART duration, ART regimen category, CD4 count, viral load status, and BMI category showed no statistically significant associations with HPV prevalence in bivariate analysis (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05 for all). In multivariate analysis, age remained independently associated with lower HPV prevalence (adjusted PR\u0026thinsp;=\u0026thinsp;0.97; 95% CI: 0.96\u0026ndash;0.99; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Although WHO clinical stage III/IV had a higher prevalence ratio compared to stage I/II (adjusted PR\u0026thinsp;=\u0026thinsp;1.58; 95% CI: 0.95\u0026ndash;2.61), the association was not statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.077).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultivariate analysis of factors associated with HPV among 1305 WLWH in Uganda.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrevalence ratio (PR) (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMultivariate PR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eContinuous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.97 (0.95\u0026ndash;0.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.97 (0.96\u0026ndash;0.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eART Duration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;10 Years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;4.9 Years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.96 (0.61\u0026ndash;1.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.871\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u0026ndash;9.9 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.75 (0.50\u0026ndash;1.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eART Status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDTG \u0026ndash; Based\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-DTG \u0026ndash; Based\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.24 (0.61\u0026ndash;2.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.550\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD4 Category\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;201\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.88 (0.57\u0026ndash;1.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.558\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eViral Load\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSuppressed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-Suppressed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.40 (0.80\u0026ndash;2.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.235\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI Category\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18.6\u0026ndash;24.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25-29.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.81 (0.58\u0026ndash;1.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.191\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30 above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.93 (0.63\u0026ndash;1.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.730\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;18.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.02 (0.55\u0026ndash;1.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.949\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWHO Stage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage I \u0026amp; II\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStage III \u0026amp; IV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.73 (1.01\u0026ndash;2.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.58 (0.95\u0026ndash;2.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.077\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigated the prevalence and factors associated with HPV infection among WLWH in Uganda. Our findings revealed a high prevalence of HPV infection, with 39.1% of women testing positive. This prevalence rate was higher compared to previous studies conducted in Uganda (\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) and other African countries(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), which ranged between 17% and 25%. However, studies focusing on WLWH showed prevalence rates in line with the present study, ranging from 30\u0026ndash;64%. (\u003cspan additionalcitationids=\"CR20 CR21 CR22\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe study demonstrated that HPV infection rates varied across different age groups, with a significant peak in the 30\u0026ndash;34 age group. However, it should be noted that individual HPV genotypes 16 and 18 peaked in the 35\u0026ndash;39 and 40\u0026ndash;44 age groups, respectively. This finding aligns with previous reports and can be attributed to more frequent sexual intercourse and inadequate safety awareness among young women (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHPV infection significantly declined in women above the age of 50 years, consistent with previous studies(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) attributing this decrease to age and behavioral factors, however, this study cannot draw such conclusions (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Additionally, the research findings revealed that many female participants in this study exhibited infection with a singular HPV genotype. Nevertheless, it is crucial to acknowledge the potential occurrence of multiple types of infections. Existing literature has consistently indicated that the presence of multiple HPV genotypes could lead to prolonged infection persistence, potentially heightening the risk of developing cervical cancer (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe high prevalence of HPV among WLWH is of great concern due to the increased risk of developing cervical cancer. Persistent infection with high-risk HPV types is a key factor in developing cervical intraepithelial neoplasia and cervical cancer. The most common genotypes identified were the pooled high-risk HPV(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Therefore, future development of multivalent preventive HPV vaccines should consider including additional high-risk HPV genotypes beyond the currently targeted types 16/18 (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis is reinforced by a study done in Ghana that showed an emerging possibility of other HR-HPV apart from HPV 16 and 18, being more common (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). And an epidemiological study in Uganda demonstrated that HR-HPV, apart from HPV 16 and 18, accounts for the highest number of HPV infections among women, and given that these other HR-HPV oncogenes account for 30% of invasive cervical cancer, an understanding of these other HR-HPV oncogenes is warranted among women living with HIV(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eUganda, through the Ministry of Health, has led efforts to combat the threat of HPV by making vaccinations available; however, this initiative has largely been unsuccessful, resulting in low vaccination uptake(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Therefore, approaches that involve men in the fight against the spread of HPV infections would be warranted, as studies in Uganda have shown a high incidence of 66.5 per 100 person-years in HIV-positive men and 32.9 per 100 person-years among HIV-negative men, with a prevalence of 90.7% among men living with HIV and 60.9% among HIV-negative men (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSeveral studies in sub-Saharan Africa and similar settings have found that HPV infection rates among WLWH are highest in the youngest age groups and decline with increasing age. For example, a Malian cohort of WLWH reported a dramatically higher prevalence of high‐risk HPV in women under 35 (30%) compared to older women (11.1%) (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Likewise, a South African study in the Eastern Cape found peak HPV prevalence (\u0026asymp;\u0026thinsp;80.9%) in women aged 18\u0026ndash;25 and a much lower prevalence (\u0026asymp;\u0026thinsp;46.3%) in women over 45, with high‐risk HPV infections significantly decreasing with age (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). A recent national analysis in Uganda showed that WLWH aged 36\u0026ndash;49 had lower overall high‐risk HPV prevalence than those aged 25\u0026ndash;35 (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). In Zambia, each additional year of age was associated with an approximately 2% reduced odds of HPV infection (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). These consistent trends are attributed to behavioral factors (e.g. higher recent sexual activity and partner change in younger women) and immunological factors (older women may have cleared past infections or developed partial immunity). However, persistent infection remains a concern in all age groups. In line with our aim to characterize HPV epidemiology in rural Mityana and Kiboga, the significant age effect observed \u0026ndash; namely, higher HPV rates among younger WLWH \u0026ndash; accords with these regional findings. This underscores that age is an important determinant of HPV risk among WLWH and suggests that prevention and screening efforts in rural Uganda should particularly target younger WLWH to reduce the HPV burden.\u003c/p\u003e\u003cp\u003eThe study highlighted an association between a longer duration of ART and a higher prevalence of HPV infection among women who had been on ART for five years and above and showed a higher prevalence of HPV and this finding is consistent with previous studies reporting an increased risk of HPV persistence and progression to cervical dysplasia among women on long-term ART(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Despite the positive impact of ART on immune function and longevity in HIV-positive women, cervical cancer remains high(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). WLWH experience increased prevalence and incidence of cervical HPV infections and higher risks of persistent HPV infections, subsequent cervical intraepithelial lesions, and cervical cancer(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Furthermore, women living with HIV are more likely to have high-risk HPV infections characterized by higher prevalence rates, co-infection, persistence, and reactivation. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). It is important to note that the association between ART duration and HPV infection may be multifactorial, involving both immunological and potential behavioral factors such as sexual behavior and adherence to ART.\u003c/p\u003e\u003cp\u003eThis line of research holds valuable insights that could potentially aid in developing efficacious biological therapeutics targeting HPV and HPV-related diseases. Moreover, such advancements may have significant implications for preventing HPV-related cancers in individuals infected with high-risk HPV strains.\u003c/p\u003e\u003cp\u003eSeveral limitations should be acknowledged in the study. Firstly, the cross-sectional design limits the ability to establish a causal relationship between the identified factors and HPV infection. Longitudinal studies are necessary to understand the dynamic nature of HPV infection in this population. Secondly, the study was conducted in specific healthcare settings in Uganda, which may restrict the generalizability of the findings to other populations or regions. Further research in diverse settings must validate these findings and ensure their applicability to broader populations.\u003c/p\u003e\u003cp\u003eStrengths of the study include the comprehensive nature of data collection, which provided valuable insights into the prevalence, distribution, and associated factors of HPV infection among women living with HIV in Uganda. The inclusion of clinical characteristics such as body mass index, ART category, viral load status, and WHO clinical stage enriched the understanding of the cohort and allowed for more robust interpretations.\u003c/p\u003e\u003cp\u003eIn conclusion, our study highlights the high prevalence of HPV infection among WLWH in Uganda. The prevalence was higher than in previous studies in Uganda and other African countries. Age was found to be associated with HPV infection, with the highest prevalence observed in the 30\u0026ndash;34 age group. The most common HPV genotypes identified were high-risk genotypes pooled together during testing. Longer duration of ART and lower CD4 counts were associated with higher HPV prevalence. The association between the CD4 category, longer ART duration, and HPV infection emphasizes the importance of regular monitoring of immunological status and early initiation of ART in this population. These findings have implications for implementing comprehensive cervical cancer prevention programs that include HPV vaccination, regular cervical cancer screening, and prompt treatment of cervical dysplasia. Future research should focus on validating these findings in diverse settings and exploring the effectiveness of these interventions to reduce the burden of cervical cancer among women living with HIV.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAntiretroviral Therapy (ART); Body Mass Index (BMI); Centers for Disease Control and Prevention (CDC); Confidence Interval (CI); Dolutegravir (DTG); Eastern and Southern Africa (SEA); Electronic Medical Record (EMR); High-Risk Human Papillomavirus (HR-HPV); Human Immunodeficiency Virus (HIV); Human Papillomavirus (HPV); Sub-Saharan Africa (SSA); Women Living with HIV (WLWH); World Health Organization (WHO).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to all the patients whose data were used in the study. We thank Dr. Richard Muhindo for the insightful advice during the writing and review of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBK conceived the study. BK, JKN, IK, CB, JBB, JN, CS, RM, and BM participated in the study design and data collection. BK and IK participated in data analysis. All authors participated in writing and reviewing the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Mildmay Uganda Research and Ethics Committee (REC REF 0804\u0026ndash;2018), as well as the U.S Centers for Disease Control and Prevention (U.S CDC) under 45 C.F.R. part 46.101(c); 21 C.F.R. part 56. A waiver of consent was granted to use secondary data because the data were sourced from a publicly accessible Electronic Medical Records (EMR) platform. All methods were performed in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received support from the US President\u0026rsquo;s Emergency Plan for AIDS Relief (PEPFAR) via the Centers for Disease Control and Prevention (CDC), grant number 1NU2GGH002046-01\u0026ndash;00. The views expressed in this manuscript are those of the author(s) and do not necessarily reflect the official stance of the funding organizations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe clinical data sets used and /or analyzed during this study are available from the corresponding author upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eStrickler HD, Burk RD, Fazzari M, Anastos K, Minkoff H, Massad LS, et al. Natural History and Possible Reactivation of Human Papillomavirus in Human Immunodeficiency Virus\u0026ndash;Positive Women. JNCI J Natl Cancer Inst. 2005;97(8):577\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu G, Sharma M, Tan N, Barnabas RV. 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Available from: https://www.afro.who.int/news/uganda-embarks-multisectoral-approach-improve-vaccination-coverage-against-human\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTobian AAR, Grabowski MK, Kigozi G, Gravitt PE, Eaton KP, Serwadda D, et al High-risk human papillomavirus prevalence is associated with HIV infection among heterosexual men in Rakai, Uganda.Sex Transm Infect. 2013;89(2):122\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTraore B, Kassogue Y, Diakite B, Diarra F, Cisse K, Kassogue O, et al Prevalence of high-risk human papillomavirus genotypes in outpatient Malian women living with HIV: a pilot study.BMC Infect Dis. 2024;24(1):513.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMbulawa ZZA, Kondlo S, Toni S, Faye LM, Businge CB Prevalence, Characteristics, and Distribution of Human Papillomavirus According to Age and HIV Status in Women of Eastern Cape Province, South Africa.Viruses. 2024;16(11):1751.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNakigozi H, Ndejjo R, Bazeyo W, Nabaggala A, Achola C, Iga M, et al Prevalence of genital high-risk human papillomavirus infections and associated factors among women living with human immunodeficiency virus in Uganda.BMC Cancer. 2024;24(1):243.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMuchaili L, Simushi P, Mweene BC, Mwakyoma T, Masenga SK, Hamooya BM. Prevalence and correlates of Human Papillomavirus infection in females from Southern Province, Zambia: A cross-sectional study. Okunade KS, editor PLOS ONE. 2024;19(8):e0299963.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLooker KJ, R\u0026ouml;nn MM, Brock PM, Brisson M, Drolet M, Mayaud P, et al Evidence of synergistic relationships between HIV and Human Papillomavirus (HPV): systematic reviews and meta-analyses of longitudinal studies of HPV acquisition and clearance by HIV status, and of HIV acquisition by HPV status. J Int AIDS Soc [Internet]. 2018 Jun [cited 2023 Jun 20];21(6). Available from: https://onlinelibrary.wiley.com/doi/10.1002/jia2.25110\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTong Y, Orang\u0026rsquo;o E, Nakalembe M, Tonui P, Itsura P, Muthoka K, et al The East Africa Consortium for human papillomavirus and cervical cancer in women living with HIV/AIDS.Ann Med. 2022;54(1):1202\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDe Vuyst H, Lillo F, Broutet N, Smith JS HIV, human papillomavirus, and cervical neoplasia and cancer in the era of highly active antiretroviral therapy.Eur J Cancer Prev. 2008;17(6):545\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLuckett R, Painter H, Hacker M, Simon B, Seiphetlheng A, Erlinger A, et al Persistence and clearance of high-risk human papillomavirus and cervical dysplasia at 1 year in women living with human immunodeficiency virus: a prospective cohort study.BJOG Int J Obstet Gynaecol. 2021;128(12):1986\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDu P. Human Papillomavirus Infection and Cervical Cancer in HIV\u0026thinsp;+\u0026thinsp;Women. In: Meyers C, editor HIV/AIDS-Associated Viral Oncogenesis [Internet]. Cham: Springer International Publishing; 2019 [cited 2023 Jun 20]. p. 105\u0026ndash;29. Available from: http://link.springer.com/10.1007/978-3-030-03502-0_5\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"human papillomavirus types, women living with HIV, prevalence, oncogenes","lastPublishedDoi":"10.21203/rs.3.rs-6883555/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6883555/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003ePersistent human papillomavirus (HPV) infection is a significant precursor to cervical abnormalities and invasive cancer. While the causal relationship between specific HPV types and cervical cancer is established, little is known about the distribution of HPV types among women living with HIV (WLWH) in Uganda. We aimed to describe the epidemiology of HPV types among women living with HIV at Mityana and Kiboga Hospitals in rural central Uganda.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA retrospective review of demographic and clinical data, including age and antiretroviral therapy (ART) history, was conducted among WLWH tested for HPV between July 2021 and July 2022. Real-time Polymerase Chain Reaction assay (RT-PCR) detected HPV 16, 18/45, and other pooled high-risk types. HPV infections were categorized into single, double, and multiple subtypes. Statistical analysis involved Chi-square tests and modified Poisson regression with robust standard error models to evaluate associations and identify factors linked with HPV infection.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAmong 1305 WLWH, the overall prevalence of HPV infection was 39.1%. HPV16 and HPV18/45 were the most common genotypes, with a prevalence of 8.1% and 8.2%, respectively. Multiple HPV infections were observed in 18.4% of cases, with combinations of HPV 16, HPV 18/45, and other high-risk HPV types. Increasing age was significantly associated with a lower prevalence of HPV infection (PR\u0026thinsp;=\u0026thinsp;0.97; 95% CI: 0.95\u0026ndash;0.99; p\u0026thinsp;=\u0026thinsp;0.003).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThe study highlights a high prevalence of HPV infection among WLWH in rural Uganda, with specific genotypes and risk factors identified. These findings underscore the importance of comprehensive cervical cancer prevention programs, including HPV vaccination, regular screening. Further research is needed to validate these findings and evaluate the effectiveness of interventions to reduce the burden of HPV-related diseases among WLWH in Uganda.\u003c/p\u003e","manuscriptTitle":"Human Papillomavirus epidemiology among women seeking HIV care at two Ugandan rural hospitals","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-12 15:15:10","doi":"10.21203/rs.3.rs-6883555/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-15T08:01:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-02T08:11:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"12005690174205446792888736256730223708","date":"2026-03-31T06:36:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-18T04:24:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"180587170332839588641944006782516036976","date":"2026-03-09T07:38:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-29T19:40:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"331593681780067574705995306044034805388","date":"2025-09-09T15:53:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"276267418962140951323250317236195814733","date":"2025-09-09T06:27:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"291902051877599570258999886630247753421","date":"2025-09-08T06:28:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-07T15:00:51+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-21T10:22:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-18T01:16:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-18T01:15:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-06-13T00:34:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dd7a9236-2778-4c8c-b029-1d6335f67252","owner":[],"postedDate":"September 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-20T08:54:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-12 15:15:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6883555","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6883555","identity":"rs-6883555","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}