Sex disparities in HIV treatment outcomes among adolescents in Nigeria: a multistate retrospective cohort study

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Evidence suggests that sex differences may influence treatment outcomes; however, sex-disaggregated analyses from routine program settings in Nigeria remain limited. This study examined sex disparities in HIV treatment outcomes and identified clinical and programmatic factors associated with retention and viral suppression among adolescents receiving ART. Methods We conducted a multistate retrospective cohort study using routinely collected electronic medical record data from adolescents aged 10–19 years who initiated ART between October 2022 and September 2024 across 479 health facilities in Southwest and Northcentral Nigeria. De-identified data were extracted from the Nigeria Medical Records System. Primary outcomes were retention in care at 6 and 12 months after ART initiation and viral suppression, defined as viral load < 1000 copies/mL. Associations between sex and treatment outcomes were assessed using bivariate analyses and multivariable logistic regression. Kaplan–Meier survival analysis evaluated time to loss to follow-up. Results A total of 964 adolescents were included (50% female), with a median age of 16 years. Females had higher baseline CD4 counts than males (p < 0.001), while WHO clinical stage did not differ by sex. Retention at 6 months was 95.6% among males and 97.5% among females (p = 0.111), declining to 86.9% and 88.6% at 12 months, respectively (p = 0.432). Viral suppression was higher among females at 6 months (87.8% vs. 83.0%; p = 0.036) and 12 months (89.6% vs. 83.8%; p = 0.008). After adjustment, sex was not independently associated with retention or viral suppression. Multi-month dispensing, baseline CD4 count, ART regimen, and year of ART initiation were significantly associated with treatment outcomes. Time to loss to follow-up did not differ between sexes (log-rank p = 0.931). Conclusion Although female adolescents demonstrated higher unadjusted viral suppression rates, sex was not an independent predictor of treatment outcomes after adjustment for clinical and programmatic factors. Service delivery characteristics and baseline clinical status were more strongly associated with retention and viral suppression. Strengthening differentiated service delivery and optimizing clinical management may improve adolescent HIV outcomes in routine care settings. Adolescents HIV antiretroviral therapy retention in care viral suppression Nigeria Figures Figure 1 Background Human Immunodeficiency Virus (HIV) remains a major global public health challenge, with adolescents representing a population in which treatment outcomes continue to lag despite substantial expansion of antiretroviral therapy (ART). Globally, an estimated 1.7 million adolescents aged 10–19 years are living with HIV, with approximately 170,000 new infections recorded in 2024 ( 1 ). Sub-Saharan Africa bears nearly 83% of this burden ( 1 ), and Nigeria remains one of the countries most affected, with an estimated 110,000 adolescents living with HIV and approximately 10,000 new infections annually ( 2 ). Although ART scale-up has improved survival overall, adolescents experience lower retention in care and viral suppression compared with other age groups, contributing to slower declines in HIV-related mortality in this population ( 3 ). Sex disparities further complicate the epidemiology of adolescent HIV. In Nigeria, HIV prevalence among girls aged 15–19 years is approximately 0.3%, three times higher than among boys of the same age (0.1%) ( 4 ). These differences reflect a combination of biological susceptibility and socio-structural vulnerabilities. Adolescent girls and young women face elevated risks associated with gender-based violence, economic inequality, early sexual debut, and stigma, whereas adolescent boys are more likely to present late for care and disengage from treatment services ( 4 – 6 ). These sex-based differences may influence patterns of treatment initiation, adherence, and long-term engagement in care. Retention in care and viral suppression are central indicators of HIV treatment success and are critical for achieving the UNAIDS 95–95–95 targets ( 7 , 8 ). However, adolescents face distinct barriers that undermine these outcomes, including stigma, challenges with disclosure, limited caregiver support, and the transition from paediatric to adult HIV services ( 9 – 11 ). Social norms and gender expectations further shape health-seeking behaviour, adherence, and sustained engagement in care ( 5 , 6 , 12 ). Despite national progress in ART coverage, retention in HIV care in Nigeria remains suboptimal, with program data indicating retention levels of approximately 72% ( 13 ). Biological differences in immune response between males and females may contribute to variations in treatment outcomes ( 14 ), while gendered social dynamics influence adherence, disclosure, and continuity of care ( 15 , 16 ). Evidence from sub-Saharan Africa suggests that adolescent boys may demonstrate lower healthcare utilization and poorer retention, whereas girls, although often engaged through maternal and child health entry points, remain vulnerable to long-term adherence challenges and social stigma ( 15 , 17 ). However, most national program evaluations aggregate adolescent data without sex disaggregation, limiting the ability to identify sex-specific inequities and tailor interventions accordingly. Furthermore, while differentiated service delivery models such as multi-month dispensing have demonstrated potential to improve retention and adherence ( 12 , 18 ), real-world evidence on the relative contribution of demographic versus programmatic factors to adolescent treatment outcomes in Nigeria remains limited. Understanding whether sex independently influences treatment outcomes, or whether observed differences reflect underlying clinical and service delivery factors, is critical for designing equitable and scalable HIV interventions. Generating evidence from routine program settings is particularly important to inform policy and strengthen implementation strategies. This study therefore aimed to examine sex disparities in retention and viral suppression among adolescents living with HIV using routinely collected data from the Nigeria Medical Records System (NMRS). In addition, the study sought to identify clinical and programmatic factors associated with treatment outcomes. We hypothesized that although crude differences in viral suppression and retention may be observed between male and female adolescents, sex would not remain an independent predictor of treatment outcomes after adjustment for clinical and service delivery factors. Methods Study design and setting We conducted a retrospective cohort study using routinely collected electronic medical record data from adolescents living with HIV in Nigeria. The study is reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (19). Data were obtained from the Nigeria Medical Records System (NMRS), an electronic medical record platform used to support routine monitoring of HIV services across facilities supported by APIN Public Health Initiatives. The NMRS captures longitudinal patient-level information including enrolment, ART initiation, clinic attendance, treatment status, viral load testing, and treatment outcomes. The study included adolescents who initiated ART between October 2022 and September 2024 across 479 health facilities located in the Southwest and Northcentral regions of Nigeria. Facilities included a mix of high-, medium-, and low-volume centres. The recruitment period corresponded to ART initiation within the study window, and follow-up extended to 12 months after ART initiation for assessment of retention and viral suppression outcomes. Participants The study population comprised adolescents aged 10–19 years who were enrolled in HIV care and initiated ART within the study period. Eligibility criteria included documented ART initiation date and availability of follow-up data for at least six months. Adolescents with incomplete demographic data, missing ART initiation dates, or who transferred out before completing six months of follow-up were excluded. All eligible adolescents meeting the inclusion criteria during the study period were included. No matching was performed, and participants were not selected through sampling; rather, the study included all eligible records within the NMRS during the specified period. Follow-up was defined as the period from ART initiation to either 12 months post-initiation, documented loss to follow-up, transfer out, death, or end of the study period, whichever occurred first. Variables The primary exposure was biological sex (male or female). Primary outcomes were: Retention in care at 6- and 12-months following ART initiation, Viral suppression, defined as the most recent viral load measurement <1000 copies/mL in accordance with national HIV treatment guidelines. The secondary outcome was loss to follow-up (LTFU), defined as failure to receive antiretroviral medication within 28 days after a missed drug pick-up. Potential confounders and predictors were selected a priori based on clinical relevance and prior literature (15–18) and included: Age (continuous and categorized as 10–14 and 15–19 years), Baseline CD4 count (categorized as ≤200, 201–300, >301 cells/mm³), WHO clinical stage (Stage 1 vs. Stage 2–4), ART regimen (TDF-3TC-DTG vs. other regimens), Multi-month dispensing (MMD) status, Year of ART initiation and Documented co-morbidities All variables were extracted from the NMRS. Measurements were based on routine clinical documentation and laboratory testing performed at participating facilities using nationally standardized protocols. Assessment methods were consistent across facilities as part of standardized HIV program implementation. Data quality and missing data Data quality assessments were conducted prior to analysis to evaluate completeness and internal consistency of key variables. Records with incomplete demographic information, missing ART initiation dates, or absent outcome data were excluded. Approximately 5% of eligible records contained incomplete data and were excluded from analysis. Given the low proportion of missingness, a complete-case analysis approach was adopted. Sample size The minimum sample size required to compare viral suppression between female and male adolescents was calculated using the two-independent-proportions formula with a two-sided alpha of 0.05 and 80% power. Viral suppression was estimated at 57% among females and 48% among males based on prior literature (18), yielding a minimum requirement of 482 participants per group (964 total). Inflation adjustments were initially applied to account for potential clustering at the facility level (design effect of 1.5) and possible data loss, resulting in a projected sample size of 1606. However, as this study used routinely collected electronic medical record data, the final sample was determined by the number of eligible records available during the study period. Following data cleaning, 964 adolescents with complete data met inclusion criteria and were included in the final analysis, meeting the minimum required sample size. Statistical analysis Data were analyzed using SPSS version 25 (IBM Corp., Chicago, IL). Continuous variables were summarized using means with standard deviations or medians with interquartile ranges, depending on distribution. Categorical variables were presented as frequencies and percentages. Quantitative variables such as age and CD4 count were analyzed both as continuous measures and in clinically relevant categories. Baseline characteristics were compared between male and female adolescents using chi-square tests for categorical variables and independent t-tests for continuous variables. Multivariable logistic regression models were used to assess the association between sex and treatment outcomes while adjusting for potential confounders. Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) were reported. Confounding control was achieved through inclusion of clinically relevant covariates identified a priori. Kaplan–Meier survival analysis was used to estimate time to loss to follow-up, with differences assessed using the log-rank test. Cox proportional hazards regression was performed to identify predictors of attrition and to account for varying follow-up times. Participants were censored at transfer out, death, or end of study follow-up. Variables with p<0.20 in bivariate analyses were entered into multivariable models. Statistical significance was set at p<0.05. No formal interaction testing was conducted; however, stratified analyses by sex were performed to explore sex-specific predictors of treatment outcomes. Sensitivity analyses were not performed, as the final sample met the minimum calculated requirement and missing data were minimal. Results Participant flow and follow-up A total of 1,015 adolescent records were identified within the Nigeria Medical Records System during the study period (October 2022–September 2024). Of these, 51 records (5.0%) were excluded due to incomplete demographic information, missing ART initiation dates, or absent outcome data. A total of 964 adolescents met eligibility criteria and were included in the final analysis ( Fig. 1 ). All included participants had at least six months of follow-up data available. Follow-up extended to 12 months post-ART initiation, unless censored due to transfer out, death, or administrative end of study. The mean follow-up time was 201 days, with no significant difference between males and females. Baseline characteristics The final cohort comprised 964 adolescents, including 482 males (50.0%) and 482 females (50.0%). The median age was 16 years (IQR: 5). Males were younger than females (median 15 years [IQR: 6] vs. 17 years [IQR: 5]). Participants were categorized into two age groups (10–14 years and 15–19 years); 62.0% were aged 15–19 years, and age distribution differed significantly by sex (p301 cells/mm³. A higher proportion of females had CD4 counts >301 cells/mm³ compared with males (47.3% vs. 28.0%; p<0.001). WHO clinical stage was categorized as Stage 1 versus Stage 2–4; approximately 90% presented at Stage 1, with no significant difference between sexes (p=0.260). Most adolescents (79.1%) initiated ART on tenofovir–lamivudine–dolutegravir (TDF-3TC-DTG). Uptake was higher among females than males (82.6% vs. 75.7%; p=0.040). Multi-month dispensing (3–5 months) was documented in 96.2% of participants and did not differ by sex (p=0.803). Missing data for included variables were <5% for all variables. Table 1. Retention in care At 6 months post-ART initiation, 932 of 964 adolescents (96.6%) remained in care. Retention was 95.6% among males and 97.5% among females (p=0.111). At 12 months, 846 of 964 adolescents (87.8%) were retained in care, including 86.9% of males and 88.6% of females (p=0.432). In unadjusted analyses, sex was not significantly associated with retention at either time point. In multivariable logistic regression models adjusting for age, baseline CD4 category, WHO stage, ART regimen, multi-month dispensing, and year of ART initiation, sex remained not independently associated with non-retention at 6 months (adjusted odds ratio [aOR], 95% CI) or 12 months. Multi-month dispensing was independently associated with retention at 6 months among males (aOR: 14.60; 95% CI: 7.74–27.55; p<0.001) and females (aOR: 23.56; 95% CI: 11.35–48.92; p<0.001). At 12 months, year of ART initiation remained significantly associated with retention among males (p=0.003) and females (p=0.011). Table 2. Viral suppression At 6 months, viral load data were available for all included participants. Viral suppression (<1000 copies/mL) was achieved in 83.0% of males and 87.8% of females (p=0.036). At 12 months, suppression was observed in 83.8% of males and 89.6% of females (p=0.008). In unadjusted analyses, females demonstrated higher viral suppression at both time points. However, in multivariable logistic regression adjusting for age, baseline CD4 category, WHO stage, ART regimen, multi-month dispensing, and year of ART initiation, sex was not independently associated with viral suppression at 6 or 12 months. Among males, younger age (10–14 years) was independently associated with viral non-suppression at 6 months (aOR: 0.54; 95% CI: 0.30–0.96). Among females, baseline CD4 category (p=0.032) and ART regimen (p=0.041) were associated with viral non-suppression at 6 months. No predictors were significantly associated with viral non-suppression at 12 months for either sex. Results are presented in Table 3. Time to loss to follow-up During follow-up, loss to follow-up occurred in 118 participants (12.2%). Kaplan–Meier survival analysis demonstrated no significant difference in time to loss to follow-up between males and females (log-rank χ²=0.008; p=0.931). The estimated mean time in care was 201 days for both sexes, with overlapping 95% confidence intervals. In Cox proportional hazards models adjusting for age, baseline CD4 category, WHO stage, ART regimen, multi-month dispensing, and year of ART initiation, sex was not associated with risk of attrition (adjusted hazard ratio [aHR], 95% CI). Year of ART initiation was significantly associated with attrition risk. Table 4. Discussion Principal findings This study examined sex disparities in retention and viral suppression among adolescents living with HIV receiving ART in routine program settings across five Nigerian states. In line with the study objectives, we found that although female adolescents demonstrated higher crude viral suppression at both 6 and 12 months, sex was not independently associated with retention, viral suppression, or time to loss to follow-up after adjustment for baseline clinical characteristics and service delivery factors. Instead, multi-month dispensing, baseline CD4 count, ART regimen, and year of ART initiation were more strongly associated with treatment outcomes. These findings suggest that differences in clinical presentation and programmatic exposure, rather than biological sex alone, may explain observed disparities in adolescent HIV outcomes. Interpretation in relation to other studies Female adolescents in this cohort had higher baseline CD4 counts than males, consistent with findings from sub-Saharan Africa indicating that females often enter HIV care earlier than their male counterparts ( 20 – 21 ). Earlier presentation may partially explain higher unadjusted viral suppression rates observed among females. However, the attenuation of sex differences after multivariable adjustment aligns with cohort studies from Ethiopia and South Africa demonstrating that baseline immune status and service delivery characteristics account for much of the observed variation in treatment outcomes ( 22 – 23 ). Retention declined between 6 and 12 months without significant sex differences. Similar longitudinal patterns have been reported in South African adolescent cohorts, where maintaining long-term engagement in care remains challenging regardless of sex ( 24 ). The absence of sex-specific differences in loss to follow-up suggests that shared structural and developmental barriers including stigma, school-related demands, transportation constraints, and limited adolescent-friendly services may exert stronger influence on retention than gender-related behavioural factors. Qualitative studies from Nigeria and Malawi similarly identify health system constraints and psychosocial challenges as drivers of adolescent disengagement from HIV care ( 25 – 28 ). The strong association between multi-month dispensing and retention reinforces evidence supporting differentiated service delivery models. Studies from Zambia and Malawi demonstrate that extended ART refill intervals reduce clinic burden and improve retention across age groups ( 29 – 30 ). Our findings provide programmatic evidence from Nigeria supporting expansion of such approaches for adolescents. Predictors of viral non-suppression differed by sex. Younger age was associated with non-suppression among males, consistent with reports from Botswana, Tanzania, and Malawi indicating adherence challenges among younger adolescents transitioning toward autonomy in care ( 31 – 33 ). Among females, baseline CD4 count and ART regimen were associated with viral non-suppression. Dolutegravir-based regimens have consistently been associated with improved viral suppression and durability ( 34 – 35 ), underscoring the importance of timely initiation and optimized treatment. Strengths and limitations This study has several strengths. It used routinely collected electronic medical record data from 479 facilities across multiple regions, enhancing representativeness across diverse service delivery contexts. Inclusion of a large, balanced cohort of male and female adolescents allowed for sex-stratified analyses and improved precision of effect estimates. However, several limitations warrant consideration. First, the use of routinely collected program data introduces potential information bias due to incomplete documentation or recording errors. Although approximately 5% of records were excluded due to incomplete data, residual misclassification of exposures or outcomes may remain. If misclassification was non-differential by sex, it would likely bias associations toward the null. Second, viral load testing intervals may have varied across facilities, introducing potential measurement variability. Third, although multivariable models adjusted for key confounders, unmeasured confounding such as socioeconomic status, adherence behaviours, or caregiver support may persist. The direction of such confounding is uncertain but could attenuate or exaggerate observed associations. Fourth, multiple analyses were conducted across outcomes and time points, increasing the possibility of chance findings. However, the primary conclusions were consistent across adjusted models, reducing concern about spurious associations. Finally, follow-up was limited to 12 months post-ART initiation; longer-term outcomes such as sustained viral suppression beyond one year could not be assessed. Generalizability The inclusion of facilities from both Southwest and Northcentral Nigeria enhances the external validity of these findings within similar routine HIV program settings. However, results may not fully generalize to non-supported sites, or settings with different service delivery models. Furthermore, adolescents not engaged in care were not captured in this dataset, limiting applicability to populations outside the treatment cascade. Public health implications These findings indicate that programmatic and clinical characteristics, rather than sex alone, drive treatment outcomes among adolescents in routine HIV care. Interventions aimed at strengthening differentiated service delivery, expanding multi-month dispensing, ensuring early diagnosis, and optimizing ART regimens may yield greater impact than strategies focused solely on demographic differences. Targeted adherence support for younger adolescents may further improve viral suppression. Strengthening these approaches may accelerate progress toward national and global HIV targets for adolescents. Conclusion This multistate retrospective cohort study found that although female adolescents demonstrated higher unadjusted viral suppression rates, sex was not independently associated with retention in care, viral suppression, or loss to follow-up after adjustment for clinical and programmatic factors. Instead, treatment outcomes were more strongly associated with multi-month dispensing, baseline immune status, ART regimen, and year of ART initiation. These findings suggest that modifiable service delivery and clinical factors play a greater role than sex in shaping adolescent HIV treatment outcomes within routine care settings. Strengthening differentiated service delivery models, promoting earlier diagnosis, and ensuring consistent access to optimized ART regimens may improve retention and viral suppression among adolescents. Targeted support for younger adolescents may further enhance treatment success. Such programmatic strategies are critical for advancing equitable care and accelerating progress toward national and global HIV targets. Declarations Ethics approval and consent to participate Ethical approval for this study was obtained from the Institute of Public Health Research Ethics Committee, Obafemi Awolowo University (Ref No: IPH/OAU/12/3110). Permission to access the Nigeria Medical Records System (NMRS) was granted by APIN Public Health Initiatives. The study used routinely collected, de-identified electronic medical record data. No direct contact with participants occurred. As the dataset was fully de-identified prior to analysis, the requirement for informed consent was waived by the ethics committee in accordance with national ethical guidelines for secondary data analysis. Consent for publication Not applicable. Availability of data and materials The dataset analyzed during the current study is not publicly available due to data governance and confidentiality restrictions associated with national HIV program data. Access to the Nigeria Medical Records System (NMRS) requires formal approval from APIN Public Health Initiatives and relevant state health authorities. De-identified data may be made available from the corresponding author upon reasonable request and with appropriate institutional approvals. Competing interests Some authors are affiliated with APIN Public Health Initiatives, which supports the HIV program from which the data were derived. However, the analysis was conducted independently, and the authors declared no competing interests. Funding The HIV program that generated the data used in this study is supported through donor funding administered by APIN Public Health Initiatives. This secondary analysis did not receive dedicated research funding. The funders of the original HIV program had no role in the design of the present study, data extraction, statistical analysis, interpretation of findings, manuscript preparation, or the decision to submit the manuscript for publication. Author contributions JON, IO, DAP, conceptualized the study JON, DAP, IO, DA, CVA, MO, and MT designed the methodology and protocol for the study JON, IO retrieved the data JON and IO performed the data analysis JON, DAP, IO, DA, CVA, MO, MT drafted the initial manuscript. LBA, AI, OA, FEO, JOS, PO critically revised the manuscript for intellectual content. All authors read and approved of the final manuscript. Acknowledgements The authors acknowledge APIN Public Health Initiatives and participating health facilities for maintaining the Nigeria Medical Records System and supporting routine data documentation. 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M., Moyo, C., Balakasi, K. T., Siwale, Z., Hubbard, J., Bardon, A., Fox, M. P., Kakwesa, G., Kalua, T., Nyasa-Haambokoma, M., Dovel, K., Campbell, P. M., Tseng, C., Pisa, P. T., Cele, R., Gupta, S., Benade, M., Long, L., Xulu, T., . . . Rosen, S. (2021). Multimonth dispensing of up to 6 months of antiretroviral therapy in Malawi and Zambia (INTERVAL): A cluster-randomised, non-blinded, non-inferiority trial. The Lancet Global Health , 9 (5), e628-e638. https://doi.org/10.1016/S2214-109X(21)00039-5 Prust ML, Banda C, Dzinjalamala F, et al. Differentiated care models for HIV treatment in Malawi: process evaluation of multiple ART service delivery approaches. J Int AIDS Soc. 2017;20(Suppl 4):21650. doi:10.7448/IAS.20.5.21650 Quaker, A. S., Shirima, L. J., & Msuya, S. E. (2024). Trend and factors associated with non-suppression of viral load among adolescents on ART in Tanzania: 2018–2021. Frontiers in Reproductive Health , 6 , 1309740. https://doi.org/10.3389/frph.2024.1309740 Ioannides KLH, Chapman J, Marukutira T, Tshume O, Anabwani G, Gross R, Lowenthal ED. Patterns of HIV treatment adherence do not differ between male and female adolescents in Botswana. AIDS Behav. 2017;21(2):410–414. doi:10.1007/s10461-016-1530-7 Umar, E., Levy, J. A., Bailey, R. C., Donenberg, G., Hershow, R. C., & Mackesy-Amiti, M. E. (2019). Virological Non-suppression and its Correlates among Adolescents and Young People Living with HIV in Southern Malawi. AIDS and Behavior , 23 (2), 513. https://doi.org/10.1007/s10461-018-2255-6 Gubavu, C., Prazuck, T., Niang, M., Buret, J., Mille, C., Guinard, J., Avettand-Fènoël, V., & Hocqueloux, L. (2016). Dolutegravir-based monotherapy or dual therapy maintains a high proportion of viral suppression even in highly experienced HIV-1-infected patients. Journal of Antimicrobial Chemotherapy , 71 (4), 1046-1050. https://doi.org/10.1093/jac/dkv430 Kanters, S., Vitoria, M., Zoratti, M., Doherty, M., Penazzato, M., Rangaraj, A., Ford, N., Thorlund, K., H Anis, P. A., Karim, M. E., Mofenson, L., Zash, R., Calmy, A., Kredo, T., & Bansback, N. (2020). Comparative efficacy, tolerability and safety of dolutegravir and efavirenz 400mg among antiretroviral therapies for first-line HIV treatment: A systematic literature review and network meta-analysis. EClinicalMedicine , 28 , 100573. https://doi.org/10.1016/j.eclinm.2020.100573 Tables Table 1: Baseline Characteristics of Adolescents Living with HIV and Comparison by Sex Total (n = 964) Characteristics Total n (%) Male (n=482) Female (n=482) p-value WHO Stage 964 482 482 0.260 1 865 (89.7%) 424 (88.0%) 441 (91.5%) 2 66 (6.8%) 39 (8.1%) 27 (5.6%) 3 21 (3.3%) 18 (3.7%) 14 (2.9%) 4 1 (0.1%) 1 (0.2%) 0 (0%) Age Category <0.001 10 - 14 366 (38.0%) 221 (45.9%) 145 (30.1%) 15 - 19 598 (62.0%) 261 (54.1%) 337 (62.0%) CD4 Category <50 12 (1.2%) 6 (1.2%) 6 (1.2%) 301 363 (37.7%) 135 (28.0%) 228 (47.3%) MMD 5 Months 16 (1.7%) 8 (1.7%) 8 (1.7%) Year of ART Initiation FY23 661 (68.6%) 344 (71.4%) 317 (65.8%) 0.061 FY24 303 (31.4%) 138 (28.6%) 165 (34.2%) Regimen at Start ABC-3TC-DTG 197 (20.4%) 116 (24.1%) 81 (16.8%) 0.040 ABC-3TC-LPV/r 1 (0.1%) 0 (0%) 1 (0.2%) AZT-3TC-NVP 1 (0.1%) 0 (0%) 1 (0.2%) TDF-3TC-DTG 763 (79.1%) 365 (75.7%) 399 (82.6%) TDF-3TC-EFV 1 (0.1%) 0 (0%) 1 (0.2%) TDF-FTC-DTG 1 (0.1%) 1 (0.2%) 0 (0%) Table 2: Sex differences in Retention and Viral Load using Bivariate Analysis Treatment Outcome Total (%) Male (%) Female (%) Chi-square (χ²) p-value Retained at 6 Months 96.6% 95.6% 97.5% 2.542 0.111 Retained at 12 Months 87.8% 86.9% 88.6% 0.618 0.432 Suppressed at 6 Months (Baseline) 85.4% 83.0% 87.8% 4.395 0.036 Suppressed at 12 months 86.7% 83.8% 89.6% 7.063 0.008 Table 3: Summary of adjusted effects in male and female clients in relation to Retention and Viral Suppression. Sex Retention at 6 months aOR (95% CI) Retention at 12 months aOR (95% CI) Viral suppression at 6 months aOR (95% CI) Viral suppression at 12 months aOR (95% CI) Male 21.952 6.651 4.878 5.179 Female 39.167 7.764 7.169 8.640 Table 4: Kaplan–Meier survival analysis Testing if differences abound in time-to-LTFU between males and females. Overall Comparisons Chi-Square df Sig. Log Rank (Mantel-Cox) .008 1 .931 Test of equality of survival distributions for the different levels of Sex1. Additional Declarations No competing interests reported. Supplementary Files STROBECheklist.doc SupplementaryTable1.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 08 Apr, 2026 Reviewers invited by journal 01 Apr, 2026 Editor invited by journal 06 Mar, 2026 Editor assigned by journal 05 Mar, 2026 Submission checks completed at journal 05 Mar, 2026 First submitted to journal 24 Feb, 2026 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8961310","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":618460634,"identity":"ed1d4485-271d-44a6-b133-2fb8091fc641","order_by":0,"name":"Justin Onyebuchi 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Initiatives","correspondingAuthor":false,"prefix":"","firstName":"Prosper","middleName":"","lastName":"Okonkwo","suffix":""}],"badges":[],"createdAt":"2026-02-24 22:08:51","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8961310/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8961310/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106357617,"identity":"9f3b4a61-7717-42d9-834a-c6eee529c6e1","added_by":"auto","created_at":"2026-04-07 19:09:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":74894,"visible":true,"origin":"","legend":"\u003cp\u003eParticipant flow diagram for adolescents included in the retrospective cohort study.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8961310/v1/6ffe32faf38e71057fbdd12b.png"},{"id":106404607,"identity":"ce1d3209-56e6-4cb9-b4cd-c2570225c19b","added_by":"auto","created_at":"2026-04-08 09:16:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1057699,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8961310/v1/400bf7cc-f455-4a24-86e5-b43d04a44cd7.pdf"},{"id":106357619,"identity":"8c764445-da23-4951-bd95-a02c917cd18f","added_by":"auto","created_at":"2026-04-07 19:09:53","extension":"doc","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":122368,"visible":true,"origin":"","legend":"","description":"","filename":"STROBECheklist.doc","url":"https://assets-eu.researchsquare.com/files/rs-8961310/v1/74772a34bf32bc0e65041318.doc"},{"id":106357637,"identity":"f7f1fee6-6fb0-442c-a999-0fcc0e5b354a","added_by":"auto","created_at":"2026-04-07 19:09:57","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":16782,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8961310/v1/6370ad613337370b805db282.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Sex disparities in HIV treatment outcomes among adolescents in Nigeria: a multistate retrospective cohort study","fulltext":[{"header":"Background","content":"\u003cp\u003eHuman Immunodeficiency Virus (HIV) remains a major global public health challenge, with adolescents representing a population in which treatment outcomes continue to lag despite substantial expansion of antiretroviral therapy (ART). Globally, an estimated 1.7\u0026nbsp;million adolescents aged 10\u0026ndash;19 years are living with HIV, with approximately 170,000 new infections recorded in 2024 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Sub-Saharan Africa bears nearly 83% of this burden (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), and Nigeria remains one of the countries most affected, with an estimated 110,000 adolescents living with HIV and approximately 10,000 new infections annually (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Although ART scale-up has improved survival overall, adolescents experience lower retention in care and viral suppression compared with other age groups, contributing to slower declines in HIV-related mortality in this population (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSex disparities further complicate the epidemiology of adolescent HIV. In Nigeria, HIV prevalence among girls aged 15\u0026ndash;19 years is approximately 0.3%, three times higher than among boys of the same age (0.1%) (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). These differences reflect a combination of biological susceptibility and socio-structural vulnerabilities. Adolescent girls and young women face elevated risks associated with gender-based violence, economic inequality, early sexual debut, and stigma, whereas adolescent boys are more likely to present late for care and disengage from treatment services (\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). These sex-based differences may influence patterns of treatment initiation, adherence, and long-term engagement in care.\u003c/p\u003e \u003cp\u003eRetention in care and viral suppression are central indicators of HIV treatment success and are critical for achieving the UNAIDS 95\u0026ndash;95\u0026ndash;95 targets (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). However, adolescents face distinct barriers that undermine these outcomes, including stigma, challenges with disclosure, limited caregiver support, and the transition from paediatric to adult HIV services (\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Social norms and gender expectations further shape health-seeking behaviour, adherence, and sustained engagement in care (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Despite national progress in ART coverage, retention in HIV care in Nigeria remains suboptimal, with program data indicating retention levels of approximately 72% (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBiological differences in immune response between males and females may contribute to variations in treatment outcomes (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), while gendered social dynamics influence adherence, disclosure, and continuity of care (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Evidence from sub-Saharan Africa suggests that adolescent boys may demonstrate lower healthcare utilization and poorer retention, whereas girls, although often engaged through maternal and child health entry points, remain vulnerable to long-term adherence challenges and social stigma (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). However, most national program evaluations aggregate adolescent data without sex disaggregation, limiting the ability to identify sex-specific inequities and tailor interventions accordingly. Furthermore, while differentiated service delivery models such as multi-month dispensing have demonstrated potential to improve retention and adherence (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), real-world evidence on the relative contribution of demographic versus programmatic factors to adolescent treatment outcomes in Nigeria remains limited.\u003c/p\u003e \u003cp\u003eUnderstanding whether sex independently influences treatment outcomes, or whether observed differences reflect underlying clinical and service delivery factors, is critical for designing equitable and scalable HIV interventions. Generating evidence from routine program settings is particularly important to inform policy and strengthen implementation strategies.\u003c/p\u003e \u003cp\u003eThis study therefore aimed to examine sex disparities in retention and viral suppression among adolescents living with HIV using routinely collected data from the Nigeria Medical Records System (NMRS). In addition, the study sought to identify clinical and programmatic factors associated with treatment outcomes. We hypothesized that although crude differences in viral suppression and retention may be observed between male and female adolescents, sex would not remain an independent predictor of treatment outcomes after adjustment for clinical and service delivery factors.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design and setting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted a retrospective cohort study using routinely collected electronic medical record data from adolescents living with HIV in Nigeria. The study is reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (19).\u003c/p\u003e\n\u003cp\u003eData were obtained from the Nigeria Medical Records System (NMRS), an electronic medical record platform used to support routine monitoring of HIV services across facilities supported by APIN Public Health Initiatives. The NMRS captures longitudinal patient-level information including enrolment, ART initiation, clinic attendance, treatment status, viral load testing, and treatment outcomes.\u003c/p\u003e\n\u003cp\u003eThe study included adolescents who initiated ART between October 2022 and September 2024 across 479 health facilities located in the Southwest and Northcentral regions of Nigeria. Facilities included a mix of high-, medium-, and low-volume centres. The recruitment period corresponded to ART initiation within the study window, and follow-up extended to 12 months after ART initiation for assessment of retention and viral suppression outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study population comprised adolescents aged 10\u0026ndash;19 years who were enrolled in HIV care and initiated ART within the study period. Eligibility criteria included documented ART initiation date and availability of follow-up data for at least six months.\u003c/p\u003e\n\u003cp\u003eAdolescents with incomplete demographic data, missing ART initiation dates, or who transferred out before completing six months of follow-up were excluded.\u003c/p\u003e\n\u003cp\u003eAll eligible adolescents meeting the inclusion criteria during the study period were included. No matching was performed, and participants were not selected through sampling; rather, the study included all eligible records within the NMRS during the specified period.\u003c/p\u003e\n\u003cp\u003eFollow-up was defined as the period from ART initiation to either 12 months post-initiation, documented loss to follow-up, transfer out, death, or end of the study period, whichever occurred first.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe primary exposure was biological sex (male or female). Primary outcomes were: Retention in care at 6- and 12-months following ART initiation, Viral suppression, defined as the most recent viral load measurement \u0026lt;1000 copies/mL in accordance with national HIV treatment guidelines.\u003c/p\u003e\n\u003cp\u003eThe secondary outcome was loss to follow-up (LTFU), defined as failure to receive antiretroviral medication within 28 days after a missed drug pick-up.\u003c/p\u003e\n\u003cp\u003ePotential confounders and predictors were selected a priori based on clinical relevance and prior literature (15\u0026ndash;18) and included: Age (continuous and categorized as 10\u0026ndash;14 and 15\u0026ndash;19 years), Baseline CD4 count (categorized as \u0026le;200, 201\u0026ndash;300, \u0026gt;301 cells/mm\u0026sup3;), WHO clinical stage (Stage 1 vs. Stage 2\u0026ndash;4), ART regimen (TDF-3TC-DTG vs. other regimens), Multi-month dispensing (MMD) status, Year of ART initiation and Documented co-morbidities\u003c/p\u003e\n\u003cp\u003eAll variables were extracted from the NMRS. Measurements were based on routine clinical documentation and laboratory testing performed at participating facilities using nationally standardized protocols. Assessment methods were consistent across facilities as part of standardized HIV program implementation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData quality and missing data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData quality assessments were conducted prior to analysis to evaluate completeness and internal consistency of key variables. Records with incomplete demographic information, missing ART initiation dates, or absent outcome data were excluded. Approximately 5% of eligible records contained incomplete data and were excluded from analysis. Given the low proportion of missingness, a complete-case analysis approach was adopted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample size\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe minimum sample size required to compare viral suppression between female and male adolescents was calculated using the two-independent-proportions formula with a two-sided alpha of 0.05 and 80% power. Viral suppression was estimated at 57% among females and 48% among males based on prior literature (18), yielding a minimum requirement of 482 participants per group (964 total).\u003c/p\u003e\n\u003cp\u003eInflation adjustments were initially applied to account for potential clustering at the facility level (design effect of 1.5) and possible data loss, resulting in a projected sample size of 1606. However, as this study used routinely collected electronic medical record data, the final sample was determined by the number of eligible records available during the study period. Following data cleaning, 964 adolescents with complete data met inclusion criteria and were included in the final analysis, meeting the minimum required sample size.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were analyzed using SPSS version 25 (IBM Corp., Chicago, IL). Continuous variables were summarized using means with standard deviations or medians with interquartile ranges, depending on distribution. Categorical variables were presented as frequencies and percentages. Quantitative variables such as age and CD4 count were analyzed both as continuous measures and in clinically relevant categories. Baseline characteristics were compared between male and female adolescents using chi-square tests for categorical variables and independent t-tests for continuous variables. Multivariable logistic regression models were used to assess the association between sex and treatment outcomes while adjusting for potential confounders. Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) were reported. Confounding control was achieved through inclusion of clinically relevant covariates identified a priori.\u003c/p\u003e\n\u003cp\u003eKaplan\u0026ndash;Meier survival analysis was used to estimate time to loss to follow-up, with differences assessed using the log-rank test. Cox proportional hazards regression was performed to identify predictors of attrition and to account for varying follow-up times. Participants were censored at transfer out, death, or end of study follow-up. Variables with p\u0026lt;0.20 in bivariate analyses were entered into multivariable models. Statistical significance was set at p\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003eNo formal interaction testing was conducted; however, stratified analyses by sex were performed to explore sex-specific predictors of treatment outcomes.\u003c/p\u003e\n\u003cp\u003eSensitivity analyses were not performed, as the final sample met the minimum calculated requirement and missing data were minimal.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eParticipant flow and follow-up\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 1,015 adolescent records were identified within the Nigeria Medical Records System during the study period (October 2022\u0026ndash;September 2024). Of these, 51 records (5.0%) were excluded due to incomplete demographic information, missing ART initiation dates, or absent outcome data. A total of 964 adolescents met eligibility criteria and were included in the final analysis (\u003cstrong\u003eFig. 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eAll included participants had at least six months of follow-up data available. Follow-up extended to 12 months post-ART initiation, unless censored due to transfer out, death, or administrative end of study. The mean follow-up time was 201 days, with no significant difference between males and females.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBaseline characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe final cohort comprised 964 adolescents, including 482 males (50.0%) and 482 females (50.0%). The median age was 16 years (IQR: 5). Males were younger than females (median 15 years [IQR: 6] vs. 17 years [IQR: 5]). Participants were categorized into two age groups (10\u0026ndash;14 years and 15\u0026ndash;19 years); 62.0% were aged 15\u0026ndash;19 years, and age distribution differed significantly by sex (p\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003eBaseline immune status varied by sex. CD4 count was categorized as \u0026le;200, 201\u0026ndash;300, and \u0026gt;301 cells/mm\u0026sup3;. A higher proportion of females had CD4 counts \u0026gt;301 cells/mm\u0026sup3; compared with males (47.3% vs. 28.0%; p\u0026lt;0.001). WHO clinical stage was categorized as Stage 1 versus Stage 2\u0026ndash;4; approximately 90% presented at Stage 1, with no significant difference between sexes (p=0.260).\u003c/p\u003e\n\u003cp\u003eMost adolescents (79.1%) initiated ART on tenofovir\u0026ndash;lamivudine\u0026ndash;dolutegravir (TDF-3TC-DTG). Uptake was higher among females than males (82.6% vs. 75.7%; p=0.040). Multi-month dispensing (3\u0026ndash;5 months) was documented in 96.2% of participants and did not differ by sex (p=0.803). Missing data for included variables were \u0026lt;5% for all variables. Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRetention in care\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt 6 months post-ART initiation, 932 of 964 adolescents (96.6%) remained in care. Retention was 95.6% among males and 97.5% among females (p=0.111). At 12 months, 846 of 964 adolescents (87.8%) were retained in care, including 86.9% of males and 88.6% of females (p=0.432).\u003c/p\u003e\n\u003cp\u003eIn unadjusted analyses, sex was not significantly associated with retention at either time point. In multivariable logistic regression models adjusting for age, baseline CD4 category, WHO stage, ART regimen, multi-month dispensing, and year of ART initiation, sex remained not independently associated with non-retention at 6 months (adjusted odds ratio [aOR], 95% CI) or 12 months.\u003c/p\u003e\n\u003cp\u003eMulti-month dispensing was independently associated with retention at 6 months among males (aOR: 14.60; 95% CI: 7.74\u0026ndash;27.55; p\u0026lt;0.001) and females (aOR: 23.56; 95% CI: 11.35\u0026ndash;48.92; p\u0026lt;0.001). At 12 months, year of ART initiation remained significantly associated with retention among males (p=0.003) and females (p=0.011). Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eViral suppression\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt 6 months, viral load data were available for all included participants. Viral suppression (\u0026lt;1000 copies/mL) was achieved in 83.0% of males and 87.8% of females (p=0.036). At 12 months, suppression was observed in 83.8% of males and 89.6% of females (p=0.008).\u003c/p\u003e\n\u003cp\u003eIn unadjusted analyses, females demonstrated higher viral suppression at both time points. However, in multivariable logistic regression adjusting for age, baseline CD4 category, WHO stage, ART regimen, multi-month dispensing, and year of ART initiation, sex was not independently associated with viral suppression at 6 or 12 months.\u003c/p\u003e\n\u003cp\u003eAmong males, younger age (10\u0026ndash;14 years) was independently associated with viral non-suppression at 6 months (aOR: 0.54; 95% CI: 0.30\u0026ndash;0.96). Among females, baseline CD4 category (p=0.032) and ART regimen (p=0.041) were associated with viral non-suppression at 6 months. No predictors were significantly associated with viral non-suppression at 12 months for either sex. Results are presented in Table 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTime to loss to follow-up\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring follow-up, loss to follow-up occurred in 118 participants (12.2%). Kaplan\u0026ndash;Meier survival analysis demonstrated no significant difference in time to loss to follow-up between males and females (log-rank \u0026chi;\u0026sup2;=0.008; p=0.931).\u003c/p\u003e\n\u003cp\u003eThe estimated mean time in care was 201 days for both sexes, with overlapping 95% confidence intervals.\u003c/p\u003e\n\u003cp\u003eIn Cox proportional hazards models adjusting for age, baseline CD4 category, WHO stage, ART regimen, multi-month dispensing, and year of ART initiation, sex was not associated with risk of attrition (adjusted hazard ratio [aHR], 95% CI). Year of ART initiation was significantly associated with attrition risk. Table 4.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003ePrincipal findings\u003c/h2\u003e \u003cp\u003eThis study examined sex disparities in retention and viral suppression among adolescents living with HIV receiving ART in routine program settings across five Nigerian states. In line with the study objectives, we found that although female adolescents demonstrated higher crude viral suppression at both 6 and 12 months, sex was not independently associated with retention, viral suppression, or time to loss to follow-up after adjustment for baseline clinical characteristics and service delivery factors. Instead, multi-month dispensing, baseline CD4 count, ART regimen, and year of ART initiation were more strongly associated with treatment outcomes. These findings suggest that differences in clinical presentation and programmatic exposure, rather than biological sex alone, may explain observed disparities in adolescent HIV outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eInterpretation in relation to other studies\u003c/h2\u003e \u003cp\u003eFemale adolescents in this cohort had higher baseline CD4 counts than males, consistent with findings from sub-Saharan Africa indicating that females often enter HIV care earlier than their male counterparts (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Earlier presentation may partially explain higher unadjusted viral suppression rates observed among females. However, the attenuation of sex differences after multivariable adjustment aligns with cohort studies from Ethiopia and South Africa demonstrating that baseline immune status and service delivery characteristics account for much of the observed variation in treatment outcomes (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRetention declined between 6 and 12 months without significant sex differences. Similar longitudinal patterns have been reported in South African adolescent cohorts, where maintaining long-term engagement in care remains challenging regardless of sex (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). The absence of sex-specific differences in loss to follow-up suggests that shared structural and developmental barriers including stigma, school-related demands, transportation constraints, and limited adolescent-friendly services may exert stronger influence on retention than gender-related behavioural factors. Qualitative studies from Nigeria and Malawi similarly identify health system constraints and psychosocial challenges as drivers of adolescent disengagement from HIV care (\u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe strong association between multi-month dispensing and retention reinforces evidence supporting differentiated service delivery models. Studies from Zambia and Malawi demonstrate that extended ART refill intervals reduce clinic burden and improve retention across age groups (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Our findings provide programmatic evidence from Nigeria supporting expansion of such approaches for adolescents.\u003c/p\u003e \u003cp\u003ePredictors of viral non-suppression differed by sex. Younger age was associated with non-suppression among males, consistent with reports from Botswana, Tanzania, and Malawi indicating adherence challenges among younger adolescents transitioning toward autonomy in care (\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Among females, baseline CD4 count and ART regimen were associated with viral non-suppression. Dolutegravir-based regimens have consistently been associated with improved viral suppression and durability (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), underscoring the importance of timely initiation and optimized treatment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eThis study has several strengths. It used routinely collected electronic medical record data from 479 facilities across multiple regions, enhancing representativeness across diverse service delivery contexts. Inclusion of a large, balanced cohort of male and female adolescents allowed for sex-stratified analyses and improved precision of effect estimates.\u003c/p\u003e \u003cp\u003eHowever, several limitations warrant consideration. First, the use of routinely collected program data introduces potential information bias due to incomplete documentation or recording errors. Although approximately 5% of records were excluded due to incomplete data, residual misclassification of exposures or outcomes may remain. If misclassification was non-differential by sex, it would likely bias associations toward the null.\u003c/p\u003e \u003cp\u003eSecond, viral load testing intervals may have varied across facilities, introducing potential measurement variability. Third, although multivariable models adjusted for key confounders, unmeasured confounding such as socioeconomic status, adherence behaviours, or caregiver support may persist. The direction of such confounding is uncertain but could attenuate or exaggerate observed associations.\u003c/p\u003e \u003cp\u003eFourth, multiple analyses were conducted across outcomes and time points, increasing the possibility of chance findings. However, the primary conclusions were consistent across adjusted models, reducing concern about spurious associations.\u003c/p\u003e \u003cp\u003eFinally, follow-up was limited to 12 months post-ART initiation; longer-term outcomes such as sustained viral suppression beyond one year could not be assessed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eGeneralizability\u003c/h2\u003e \u003cp\u003eThe inclusion of facilities from both Southwest and Northcentral Nigeria enhances the external validity of these findings within similar routine HIV program settings. However, results may not fully generalize to non-supported sites, or settings with different service delivery models. Furthermore, adolescents not engaged in care were not captured in this dataset, limiting applicability to populations outside the treatment cascade.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003ePublic health implications\u003c/h2\u003e \u003cp\u003eThese findings indicate that programmatic and clinical characteristics, rather than sex alone, drive treatment outcomes among adolescents in routine HIV care. Interventions aimed at strengthening differentiated service delivery, expanding multi-month dispensing, ensuring early diagnosis, and optimizing ART regimens may yield greater impact than strategies focused solely on demographic differences. Targeted adherence support for younger adolescents may further improve viral suppression. Strengthening these approaches may accelerate progress toward national and global HIV targets for adolescents.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis multistate retrospective cohort study found that although female adolescents demonstrated higher unadjusted viral suppression rates, sex was not independently associated with retention in care, viral suppression, or loss to follow-up after adjustment for clinical and programmatic factors. Instead, treatment outcomes were more strongly associated with multi-month dispensing, baseline immune status, ART regimen, and year of ART initiation.\u003c/p\u003e \u003cp\u003eThese findings suggest that modifiable service delivery and clinical factors play a greater role than sex in shaping adolescent HIV treatment outcomes within routine care settings. Strengthening differentiated service delivery models, promoting earlier diagnosis, and ensuring consistent access to optimized ART regimens may improve retention and viral suppression among adolescents. Targeted support for younger adolescents may further enhance treatment success. Such programmatic strategies are critical for advancing equitable care and accelerating progress toward national and global HIV targets.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for this study was obtained from the Institute of Public Health Research Ethics Committee, Obafemi Awolowo University (Ref No: IPH/OAU/12/3110). Permission to access the Nigeria Medical Records System (NMRS) was granted by APIN Public Health Initiatives.\u003c/p\u003e\n\u003cp\u003eThe study used routinely collected, de-identified electronic medical record data. No direct contact with participants occurred. As the dataset was fully de-identified prior to analysis, the requirement for informed consent was waived by the ethics committee in accordance with national ethical guidelines for secondary data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset analyzed during the current study is not publicly available due to data governance and confidentiality restrictions associated with national HIV program data. Access to the Nigeria Medical Records System (NMRS) requires formal approval from APIN Public Health Initiatives and relevant state health authorities. De-identified data may be made available from the corresponding author upon reasonable request and with appropriate institutional approvals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSome authors are affiliated with APIN Public Health Initiatives, which supports the HIV program from which the data were derived. However, the analysis was conducted independently, and the authors declared no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe HIV program that generated the data used in this study is supported through donor funding administered by APIN Public Health Initiatives. This secondary analysis did not receive dedicated research funding. The funders of the original HIV program had no role in the design of the present study, data extraction, statistical analysis, interpretation of findings, manuscript preparation, or the decision to submit the manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJON, IO, DAP, conceptualized the study\u003c/p\u003e\n\u003cp\u003eJON, DAP, IO, DA, CVA, MO, and MT designed the methodology and protocol for the study JON, IO retrieved the data\u003c/p\u003e\n\u003cp\u003eJON and IO performed the data analysis\u003c/p\u003e\n\u003cp\u003eJON, DAP, IO, DA, CVA, MO, MT drafted the initial manuscript.\u003c/p\u003e\n\u003cp\u003eLBA, AI, OA, FEO, JOS, PO critically revised the manuscript for intellectual content.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors read and approved of the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge APIN Public Health Initiatives and participating health facilities for maintaining the Nigeria Medical Records System and supporting routine data documentation. We also acknowledge the contributions of Favour Pepple of APIN Health informatics unit for her support in retrieving the data and all the healthcare workers involved in adolescent HIV service delivery across participating facilities.\u003c/p\u003e"},{"header":"References","content":"\u003col start=\"1\" type=\"1\"\u003e\n\u003cli\u003eJoint United Nations Programme on HIV/AIDS. Global HIV \u0026amp; AIDS statistics \u0026mdash; Fact sheet. UNAIDS; 2024. \u003c/li\u003e\n\u003cli\u003eUNICEF. HIV/AIDS in Nigeria 2020 \u003c/li\u003e\n\u003cli\u003eJoint United Nations Programme on HIV/AIDS. Slow progress on AIDS-related deaths among adolescents. UNAIDS; 2021 \u003c/li\u003e\n\u003cli\u003eNACA. Nigeria HIV /AIDS Indicator and Impact Survey (NAIIS) 2029. Abuja Nigeria.\u003c/li\u003e\n\u003cli\u003ePettifor A, Stoner M, Pike C, Bekker LG. Adolescent lives matter: preventing HIV in adolescents. 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Predictors of successful transition of adolescents and young adults living with HIV from pediatric to adult-oriented care in southern Ethiopia: A retrospective cohort study. \u003cem\u003eBMC Health Services Research\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e, 836. https://doi.org/10.1186/s12913-024-11319-y\u003c/li\u003e\n\u003cli\u003ePascoe, S., Huber, A., Mokhele, I., Lekodeba, N., Ntjikelane, V., Sande, L., Tchereni, T., Haimbe, P., \u0026amp; Rosen, S. (2023). The SENTINEL study of differentiated service delivery models for HIV treatment in Malawi, South Africa, and Zambia: Research protocol for a prospective cohort study. \u003cem\u003eBMC Health Services Research\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e, 891. https://doi.org/10.1186/s12913-023-09813-w\u003c/li\u003e\n\u003cli\u003eOladunni, A. A., Sina-Odunsi, A. B., Nuga, B. B., Adebisi, Y. A., Bolarinwa, O. A., \u0026amp; Adeola, A. A. (2021). Psychosocial factors of stigma and relationship to healthcare services among adolescents living with HIV/AIDS in Kano state, Nigeria. \u003cem\u003eHeliyon\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e(4), e06687. https://doi.org/10.1016/j.heliyon.2021.e06687\u003c/li\u003e\n\u003cli\u003eAkadri, A., Adepoju, A., Bamidele, O., Oluwole, T., Sodeinde, K., \u0026amp; Abiodun, O. (2024). Mental health distress and associated factors among HIV- positive adolescents attending ART Clinics in Nigeria. \u003cem\u003eGlobal Pediatrics\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e, 100180. https://doi.org/10.1016/j.gpeds.2024.100180\u003c/li\u003e\n\u003cli\u003eFaidas, M. F., Gaynes, B. N., Maganga, L., Mphonda, S. M., Matewere, M., Nyirenda, J., Kramer, J., Kulisewa, K., Bhushan, N. L., Pence, B. W., \u0026amp; Stockton, M. A. (2025). Barriers to Belonging: How Stigma Disrupts Social Roles for Malawian Adolescents Living with HIV and Opportunities for Change. \u003cem\u003eJournal of the International Association of Providers of AIDS Care (JIAPAC)\u003c/em\u003e. https://doi.org/10.1177/23259582251413319\u003c/li\u003e\n\u003cli\u003eKaunda-Khangamwa, B.N., Kapwata, P., Malisita, K. \u003cem\u003eet al.\u003c/em\u003e Adolescents living with HIV, complex needs and resilience in Blantyre, Malawi. \u003cem\u003eAIDS Res Ther\u003c/em\u003e \u003cstrong\u003e17\u003c/strong\u003e, 35 (2020). https://doi.org/10.1186/s12981-020-00292-1\u003c/li\u003e\n\u003cli\u003eHoffman, R. M., Moyo, C., Balakasi, K. T., Siwale, Z., Hubbard, J., Bardon, A., Fox, M. P., Kakwesa, G., Kalua, T., Nyasa-Haambokoma, M., Dovel, K., Campbell, P. M., Tseng, C., Pisa, P. T., Cele, R., Gupta, S., Benade, M., Long, L., Xulu, T., . . . Rosen, S. (2021). Multimonth dispensing of up to 6 months of antiretroviral therapy in Malawi and Zambia (INTERVAL): A cluster-randomised, non-blinded, non-inferiority trial. \u003cem\u003eThe Lancet Global Health\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(5), e628-e638. https://doi.org/10.1016/S2214-109X(21)00039-5\u003c/li\u003e\n\u003cli\u003ePrust ML, Banda C, Dzinjalamala F, et al. Differentiated care models for HIV treatment in Malawi: process evaluation of multiple ART service delivery approaches. \u003cem\u003eJ Int AIDS Soc.\u003c/em\u003e 2017;20(Suppl 4):21650. doi:10.7448/IAS.20.5.21650 \u003c/li\u003e\n\u003cli\u003eQuaker, A. S., Shirima, L. J., \u0026amp; Msuya, S. E. (2024). Trend and factors associated with non-suppression of viral load among adolescents on ART in Tanzania: 2018\u0026ndash;2021. \u003cem\u003eFrontiers in Reproductive Health\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e, 1309740. https://doi.org/10.3389/frph.2024.1309740\u003c/li\u003e\n\u003cli\u003eIoannides KLH, Chapman J, Marukutira T, Tshume O, Anabwani G, Gross R, Lowenthal ED. Patterns of HIV treatment adherence do not differ between male and female adolescents in Botswana. \u003cem\u003eAIDS Behav.\u003c/em\u003e 2017;21(2):410\u0026ndash;414. doi:10.1007/s10461-016-1530-7\u003c/li\u003e\n\u003cli\u003eUmar, E., Levy, J. A., Bailey, R. C., Donenberg, G., Hershow, R. C., \u0026amp; Mackesy-Amiti, M. E. (2019). Virological Non-suppression and its Correlates among Adolescents and Young People Living with HIV in Southern Malawi. \u003cem\u003eAIDS and Behavior\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(2), 513. https://doi.org/10.1007/s10461-018-2255-6\u003c/li\u003e\n\u003cli\u003eGubavu, C., Prazuck, T., Niang, M., Buret, J., Mille, C., Guinard, J., Avettand-F\u0026egrave;no\u0026euml;l, V., \u0026amp; Hocqueloux, L. (2016). Dolutegravir-based monotherapy or dual therapy maintains a high proportion of viral suppression even in highly experienced HIV-1-infected patients. \u003cem\u003eJournal of Antimicrobial Chemotherapy\u003c/em\u003e, \u003cem\u003e71\u003c/em\u003e(4), 1046-1050. https://doi.org/10.1093/jac/dkv430\u003c/li\u003e\n\u003cli\u003eKanters, S., Vitoria, M., Zoratti, M., Doherty, M., Penazzato, M., Rangaraj, A., Ford, N., Thorlund, K., H Anis, P. A., Karim, M. E., Mofenson, L., Zash, R., Calmy, A., Kredo, T., \u0026amp; Bansback, N. (2020). Comparative efficacy, tolerability and safety of dolutegravir and efavirenz 400mg among antiretroviral therapies for first-line HIV treatment: A systematic literature review and network meta-analysis. \u003cem\u003eEClinicalMedicine\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e, 100573. https://doi.org/10.1016/j.eclinm.2020.100573 \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1: Baseline Characteristics of Adolescents Living with HIV and Comparison by Sex Total (n = 964)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"574\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eTotal n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eMale (n=482)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eFemale (n=482)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eWHO Stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e482\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e482\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e865 (89.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e424 (88.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e441 (91.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e66 (6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e39 (8.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e27 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e21 (3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e18 (3.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e14 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eAge Category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e10 - 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e366 (38.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e221 (45.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e145 (30.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e15 - 19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e598 (62.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e261 (54.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e337 (62.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eCD4 Category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026lt;50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e12 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e6 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e6 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e50 - 100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e26 (2.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e8 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e18 (3.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e101 - 200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e269 (27.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e155 (32.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e114 (23.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e201 - 300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e294 (30.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e178 (36.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e116 (24.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026gt;301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e363 (37.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e135 (28.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e228 (47.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eMMD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026lt;3 Months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e21 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e12 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e9 (1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e0.803\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e3 \u0026ndash; 5 Months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e927 (96.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e462 (95.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e465 (96.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026gt;5 Months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e16 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e8 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e8 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eYear of ART Initiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eFY23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e661 (68.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e344 (71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e317 (65.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eFY24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e303 (31.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e138 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e165 (34.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eRegimen at Start\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003eABC-3TC-DTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e197 (20.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e116 (24.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e81 (16.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003eABC-3TC-LPV/r\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003eAZT-3TC-NVP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003eTDF-3TC-DTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e763 (79.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e365 (75.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e399 (82.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003eTDF-3TC-EFV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 129px;\"\u003e\n \u003cp\u003eTDF-FTC-DTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1 (0.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e1 (0.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Sex differences in Retention and Viral Load using Bivariate Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"592\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eTreatment Outcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eTotal (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eMale (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eFemale (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eChi-square (\u0026chi;\u0026sup2;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eRetained at 6 Months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e96.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e95.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e97.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e2.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eRetained at 12 Months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e87.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e86.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e88.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e0.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.432\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eSuppressed at 6 Months (Baseline)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e85.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e83.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e87.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e4.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003eSuppressed at 12 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e86.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003e83.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e89.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e7.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Summary of adjusted effects in male and female clients\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;in relation to Retention and Viral Suppression.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eRetention at 6 months\u003c/p\u003e\n \u003cp\u003eaOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eRetention at 12 months\u003c/p\u003e\n \u003cp\u003eaOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eViral suppression at 6 months\u003c/p\u003e\n \u003cp\u003eaOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eViral suppression at 12 months\u003c/p\u003e\n \u003cp\u003eaOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e21.952\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e6.651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e4.878\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e5.179\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e39.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e7.764\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e7.169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 125px;\"\u003e\n \u003cp\u003e8.640\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: Kaplan\u0026ndash;Meier survival analysis Testing if differences abound in time-to-LTFU between males and females.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"479\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 479px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall Comparisons\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 109px;\"\u003e\n \u003cp\u003eChi-Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 89px;\"\u003e\n \u003cp\u003edf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 89px;\"\u003e\n \u003cp\u003eSig.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003eLog Rank (Mantel-Cox)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e.931\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 479px;\"\u003e\n \u003cp\u003eTest of equality of survival distributions for the different levels of Sex1.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv id=\"_com_1\" language=\"JavaScript\" onmouseover=\"msoCommentShow('_anchor_1','_com_1')\" onmouseout=\"msoCommentHide('_com_1')\"\u003e\u003cbr\u003e\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Adolescents, HIV, antiretroviral therapy, retention in care, viral suppression, Nigeria","lastPublishedDoi":"10.21203/rs.3.rs-8961310/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8961310/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAdolescents living with HIV experience lower retention and viral suppression than other age groups despite expanded access to antiretroviral therapy (ART), particularly in sub-Saharan Africa. Evidence suggests that sex differences may influence treatment outcomes; however, sex-disaggregated analyses from routine program settings in Nigeria remain limited. This study examined sex disparities in HIV treatment outcomes and identified clinical and programmatic factors associated with retention and viral suppression among adolescents receiving ART.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a multistate retrospective cohort study using routinely collected electronic medical record data from adolescents aged 10\u0026ndash;19 years who initiated ART between October 2022 and September 2024 across 479 health facilities in Southwest and Northcentral Nigeria. De-identified data were extracted from the Nigeria Medical Records System. Primary outcomes were retention in care at 6 and 12 months after ART initiation and viral suppression, defined as viral load\u0026thinsp;\u0026lt;\u0026thinsp;1000 copies/mL. Associations between sex and treatment outcomes were assessed using bivariate analyses and multivariable logistic regression. Kaplan\u0026ndash;Meier survival analysis evaluated time to loss to follow-up.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 964 adolescents were included (50% female), with a median age of 16 years. Females had higher baseline CD4 counts than males (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while WHO clinical stage did not differ by sex. Retention at 6 months was 95.6% among males and 97.5% among females (p\u0026thinsp;=\u0026thinsp;0.111), declining to 86.9% and 88.6% at 12 months, respectively (p\u0026thinsp;=\u0026thinsp;0.432). Viral suppression was higher among females at 6 months (87.8% vs. 83.0%; p\u0026thinsp;=\u0026thinsp;0.036) and 12 months (89.6% vs. 83.8%; p\u0026thinsp;=\u0026thinsp;0.008). After adjustment, sex was not independently associated with retention or viral suppression. Multi-month dispensing, baseline CD4 count, ART regimen, and year of ART initiation were significantly associated with treatment outcomes. Time to loss to follow-up did not differ between sexes (log-rank p\u0026thinsp;=\u0026thinsp;0.931).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eAlthough female adolescents demonstrated higher unadjusted viral suppression rates, sex was not an independent predictor of treatment outcomes after adjustment for clinical and programmatic factors. Service delivery characteristics and baseline clinical status were more strongly associated with retention and viral suppression. Strengthening differentiated service delivery and optimizing clinical management may improve adolescent HIV outcomes in routine care settings.\u003c/p\u003e","manuscriptTitle":"Sex disparities in HIV treatment outcomes among adolescents in Nigeria: a multistate retrospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-07 19:09:46","doi":"10.21203/rs.3.rs-8961310/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"246563986460711858201899979768359740264","date":"2026-04-08T14:54:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-01T18:21:15+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-06T11:12:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-05T13:29:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-05T13:26:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-02-24T21:57:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"76b238cb-9a87-430e-9427-337d2c254351","owner":[],"postedDate":"April 7th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-07T19:09:46+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-07 19:09:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8961310","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8961310","identity":"rs-8961310","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}