Characteristics and Pregnancy Outcomes of Teenage Mothers at Kabale Regional Referral Hospital, Uganda: A Cross-Sectional Study

Characteristics and Pregnancy Outcomes of Teenage Mothers at Kabale Regional Referral Hospital, Uganda: A Cross-Sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Characteristics and Pregnancy Outcomes of Teenage Mothers at Kabale Regional Referral Hospital, Uganda: A Cross-Sectional Study Deus Akampurira, Sebastian Olikira Baine, Christopher Tumwine, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8502790/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Teenage pregnancy remains a critical public health challenge in sub-Saharan Africa, with significant implications for maternal and neonatal health outcomes. In Uganda, teenage pregnancies account for 18-28% of maternal deaths, yet facility-specific evidence remains limited. This study assessed the characteristics and pregnancy outcomes of teenage mothers at Kabale Regional Referral Hospital (KRRH) and identified predictors of adverse maternal outcomes. Methods: We conducted a hospital-based cross-sectional study at KRRH from January to April 2025. Using consecutive sampling, we recruited 222 consenting teenage mothers aged 13-19 years. Data were collected through structured interviews and complemented by in-depth interviews with midwives. We used descriptive statistics to summarize characteristics and binary logistic regression to identify predictors of adverse maternal outcomes, defined as delivery-related complications requiring medical intervention. Results: The median age was 19 years (IQR: 18-19), with 88.3% (n=196) aged 18-19 years. Most participants were married (71.6%, n=159), resided in rural areas (67.1%, n=149), and were primigravida (86.0%, n=191). While 99.1% (n=220) attended antenatal care, only 57.2% (n=127) completed the recommended four visits. Maternal complications occurred in 33.3% (n=74) of deliveries, with obstructed labour being most prevalent (48.6% of complications, n=36). Referral from lower-level facilities was the strongest independent predictor of adverse outcomes (adjusted OR=3.77, 95% CI: 1.53-9.28, p=0.004). Conclusions: Despite high antenatal care attendance, teenage mothers at KRRH experienced substantial obstetric complications, particularly obstructed labour. The association between referral status and adverse outcomes highlights critical gaps in the referral system. Strengthening early risk identification, emergency obstetric care capacity, and referral pathways is essential for improving outcomes among teenage mothers in southwestern Uganda. Statistical Epidemiology teenage pregnancy adolescent mothers obstetric complications maternal outcomes referral systems Uganda Background Teenage pregnancy, occurring in females aged 13-19 years, represents a significant global public health challenge with far-reaching consequences for maternal and child health outcomes [1]. Approximately 16 million adolescent girls give birth annually worldwide, with 95% of these births occurring in low- and middle-income countries (LMICs) [2]. The physiological and social immaturity associated with adolescent pregnancy increases the risk of adverse maternal outcomes, including obstructed labour, postpartum haemorrhage, hypertensive disorders, and maternal mortality [3,4]. Sub-Saharan Africa bears a disproportionate burden of teenage pregnancies, with rates remaining persistently high despite global decline trends [5]. In Uganda, approximately 25% of girls become pregnant by age 19, contributing to 18-28% of maternal deaths nationally [6,7]. This burden is compounded by complex socioeconomic factors including poverty, early marriage, limited educational opportunities, and inadequate access to adolescent-friendly reproductive health services [8]. The COVID-19 pandemic has further exacerbated these challenges through increased school dropouts and reduced healthcare accessibility [9]. The Kigezi subregion of southwestern Uganda, served by Kabale Regional Referral Hospital (KRRH), faces particularly high rates of teenage pregnancy due to cultural practices favouring early marriage and limited economic opportunities for teenagers [10]. KRRH serves as the primary referral centre for approximately 1.4 million people across six districts, managing complex obstetric cases from both facility and community deliveries. Despite the recognized burden of teenage pregnancy in this region, comprehensive data on the characteristics and outcomes of teenage mothers delivering at KRRH remain limited. Understanding the demographic profiles, clinical characteristics, and pregnancy outcomes of this vulnerable population is crucial for developing targeted interventions to reduce maternal and neonatal morbidity and mortality. Furthermore, identifying predictors of adverse outcomes can inform risk stratification and resource allocation strategies. This study aimed to: (1) determine the demographic and clinical characteristics of teenage mothers delivering at KRRH, (2) identify maternal outcomes of teenage pregnancies, and (3) identify factors associated with adverse maternal outcomes to inform evidence-based interventions. Methods Study Design and Setting We conducted a hospital-based cross-sectional study at the maternity ward of Kabale Regional Referral Hospital from January to April 2025. KRRH is a 350-bed tertiary referral hospital serving as the primary obstetric care centre for Kabale, Rubanda, Rukiga, Kanungu, Rukungiri, and Kisoro districts in southwestern Uganda. The maternity ward handles approximately 4,000 deliveries annually, with teenage pregnancies comprising approximately 13% of all deliveries. Study Population and Sampling The study population comprised all teenage mothers aged 13-19 years who delivered at KRRH during the study period. We calculated the sample size using Cochran's formula with finite population correction, based on 521 teenage deliveries recorded in the 2023-2024 fiscal year. Assuming a 95% confidence level, 5% margin of error, and 50% expected proportion of adverse outcomes, the required sample size was 222 participants. We employed consecutive sampling to recruit eligible participants until reaching the target sample size. All consenting teenage mothers aged 18-19 years and assenting mothers aged 13-17 years, who delivered during the study period were included. Exclusion criteria comprised mothers with cognitive impairment or sensory disabilities that would prevent effective communication during interviews. Data Collection Procedures Quantitative data collection: We used a structured interviewer-administered questionnaire developed based on literature review and expert consultation. The questionnaire captured demographic characteristics (age, marital status, residence, education, occupation, household income), obstetric history (parity, gravidity, antenatal care attendance), pregnancy and delivery details (mode of delivery, referral status, complications), and neonatal outcomes. The questionnaire was pre-tested on 22 teenage mothers at a neighbouring health facility and translated into Rukiga (the local language) for enhanced comprehension. Qualitative data collection: We conducted in-depth interviews with purposively selected midwives using a semi-structured interview guide to explore their experiences managing teenage pregnancies and perceived risk factors for adverse outcomes. Interviews lasted 30-45 minutes and were audio-recorded with consent. Two trained midwives served as research assistants, ensuring cultural sensitivity and clinical expertise in data collection. Training covered study objectives, ethical considerations, interview techniques, and data quality assurance. Variable Definitions Adverse maternal outcomes: We defined this composite outcome as the occurrence of any delivery-related complication requiring medical or surgical intervention, including obstructed labour, postpartum haemorrhage, pregnancy-induced hypertension/preeclampsia, sepsis, or other complications documented in medical records. Antenatal care adequacy: We assessed both attendance (any ANC visit) and adequacy (≥4 visits as per WHO recommendations). Referral status: Categorized as referred (transferred from lower-level health facilities) or non-referred (direct attendance or self-referral). Data Management and Analysis Quantitative data were entered into SPSS version 20.0 and cleaned for completeness and consistency. We performed descriptive analysis using frequencies and percentages for categorical variables, and medians with interquartile ranges for continuous variables due to non-normal distribution. For inferential analysis, we used binary logistic regression to identify predictors of adverse maternal outcomes. Variables with p≤0.25 in bivariate analysis were included in the multivariable model. We assessed model fit using the Hosmer-Lemeshow goodness-of-fit test and reported adjusted odds ratios (aOR) with 95% confidence intervals. Statistical significance was set at p<0.05. Qualitative data were transcribed verbatim and analysed thematically using an inductive approach. Two researchers independently coded the transcripts, with discrepancies resolved through discussion to ensure reliability. Ethical Considerations We obtained ethical approval from Kabale University Research Ethics Committee (KABREC-2024-240) and administrative clearance from KRRH administration. Written informed consent was obtained from participants aged 18-19 years. For minors (<18 years), we obtained both parental/guardian consent and participant assent. We maintained confidentiality by using unique identifiers and storing data in password-protected files accessible only to the research team. Results Participant Characteristics We recruited 222 teenage mothers during the four-month study period, representing a 100% response rate among eligible participants. The median age was 19 years (IQR: 18-19), with the majority (88.3%, n=196) aged 18-19 years and 11.7% (n=26) aged 15-17 years. Most participants were married (71.6%, n=159), with 22.5% (n=50) single and 5.9% (n=13) separated or divorced. Two-thirds of participants (67.1%, n=149) resided in rural areas. Educational attainment was relatively balanced, with 48.2% (n=107) having completed primary education and 49.1% (n=109) secondary education. Only 2.3% (n=5) had vocational or technical training. Economic status was uniformly low, with 94.2% (n=209) reporting monthly household incomes below UGX 200,000 (approximately $54). Table 1: Demographic characteristics of teenage mothers (N=222) Variable Category n % Age group 15-17 years 26 11.7 18-19 years 196 88.3 Marital status Single 50 22.5 Married 159 71.6 Separated/divorced 13 5.9 Residence Rural 149 67.1 Urban 73 32.9 Education level Primary 107 48.2 Secondary 109 49.1 Vocational/technical 5 2.3 Monthly income <UGX 100,000 134 60.4 UGX 100,000-199,999 75 33.8 ≥UGX 200,000 13 5.9 Obstetric and Delivery Characteristics The vast majority of participants 86.0% (n=191) were primigravida, with 13.5% (n=30) having 1-2 previous pregnancies. Age at first pregnancy was predominantly 18-19 years 82.0% (n=182). Antenatal care attendance was nearly universal 99.1% (n=220), though only 57.2% (n=127) completed the recommended four or more visits. The caesarean section rate was 37.4% (n=83), notably higher than the WHO-recommended 10-15% rate. Almost one-third of mothers 31.5% (n=70) were referred from lower-level health facilities. Table 2: Obstetric and delivery characteristics (N=222) Variable Category n % Parity Primigravida 191 86.0 Para 1-2 30 13.5 Para ≥3 1 0.5 ANC attendance Yes 220 99.1 No 2 0.9 ANC visits ≥4 visits 127 57.2 <4 visits 93 41.9 No ANC 2 0.9 Mode of delivery Vaginal 139 62.6 Caesarean section 83 37.4 Referral status Referred 70 31.5 Not referred 152 68.5 Maternal and Neonatal Outcomes Maternal complications occurred in 33.3% (n=74) of deliveries. Among mothers with complications, obstructed labour was leading 48.6% (n=36), followed by preterm labour 32.4% (n=24), haemorrhage 14.9% (n=11), infection 5.4% (n=4), and preeclampsia/eclampsia 4.1% (n=3). Most newborns 73.9% (n=164) were healthy at birth. However, adverse neonatal outcomes included low birth weight 11.7% (n=26), birth asphyxia 8.1% (n=18), preterm birth 5.0% (n=11), and neonatal death 0.9% (n=2). Table 3: Maternal complications and neonatal outcomes Maternal Complications (n=74) n %* Obstructed labour 36 48.6 Preterm labour 24 32.4 Haemorrhage 11 14.9 Infection 4 5.4 Preeclampsia/eclampsia 3 4.1 Neonatal Outcomes (N=222) n % Healthy newborn 164 73.9 Low birth weight (<2.5kg) 26 11.7 Birth asphyxia 18 8.1 Preterm birth (<37 weeks) 11 5.0 Neonatal death 2 0.9 *Percentages calculated from mothers with complications (n=74) Predictors of Adverse Maternal Outcomes In bivariate analysis, several factors showed associations with adverse outcomes (p≤0.25): referral status, parity, household income, and ANC visit frequency. In multivariable logistic regression analysis, referral status emerged as the only statistically significant independent predictor of adverse maternal outcomes. Teenage mothers referred from lower-level health facilities had nearly four times higher odds of developing complications compared to non-referred mothers (aOR=3.77, 95% CI: 1.53-9.28, p=0.004). Table 4: Predictors of adverse maternal outcomes - Logistic regression analysis Variable Bivariate Analysis Multivariable Analysis OR 95% CI p-value aOR 95% CI p-value Referral status Not referred 1.00 - - 1.00 - - Referred 3.45 1.85-6.44 <0.001 3.77 1.53-9.28 0.004 Age group 18-19 years 1.00 - - 1.00 - - 15-17 years 1.15 0.48-2.78 0.749 1.10 0.24-4.99 0.903 Parity Primigravida 1.00 - - 1.00 - - Multigravida 2.21 1.02-4.78 0.044 2.60 0.85-7.94 0.099 Household income ≥UGX 100,000 1.00 - - 1.00 - - <UGX 100,000 1.89 1.05-3.41 0.035 2.10 0.88-5.02 0.091 ANC visits ≥4 visits 1.00 - - 1.00 - - <4 visits 1.67 0.95-2.93 0.073 1.45 0.67-3.16 0.347 *Bold values indicate statistical significance (p<0.05) *Hosmer-Lemeshow test: χ²=3.24, p=0.864 (good model fit) Discussion Principal Findings This study provides important insights into the characteristics and pregnancy outcomes of teenage mothers at a major referral hospital in southwestern Uganda. Our findings reveal that while teenage mothers at KRRH were predominantly older adolescents with high antenatal care attendance, they remained vulnerable to significant obstetric complications, with obstructed labour being the leading cause of morbidity. Critically, referral status emerged as the strongest independent predictor of adverse maternal outcomes, highlighting important gaps in the healthcare delivery system. Demographic Profile and Implications The predominance of older teenagers (18-19 years) in our cohort aligns with demographic trends showing peak fertility rates in late teenage years across sub-Saharan Africa [11]. The high marriage rate (71.6%) reflects cultural practices in southwestern Uganda where early marriage remains common, often driving teenage pregnancy [12]. The rural predominance (67.1%) and low economic status of participants underscore the intersection of geographical and socioeconomic vulnerabilities that characterize teenage pregnancy in this setting. The relatively balanced educational attainment between primary and secondary levels suggests that education alone may not be sufficient to prevent teenage pregnancy, consistent with findings from other Ugandan studies [13]. This highlights the need for comprehensive interventions addressing not only educational access but also economic empowerment and reproductive health education. Antenatal Care Patterns The near-universal ANC attendance (99.1%) represents a significant achievement, reflecting successful scale-up of maternal health services in the region. However, the finding that only 57.2% completed four or more visits indicates challenges in ensuring adequate care quality and continuity. This pattern is consistent with national trends where ANC initiation is high but completion rates remain suboptimal [14]. The gap between ANC attendance and adequacy suggests opportunities for strengthening service delivery, including addressing barriers such as distance to health facilities, cost of transportation, and quality of care. Given that adequate ANC is crucial for early identification and management of pregnancy complications, improving completion rates should be a priority intervention. Maternal Complications and Clinical Significance The 33.3% complication rate among teenage mothers is substantial and reflects the inherent risks associated with teenage pregnancy. The predominance of obstructed labour (48.6% of complications) is particularly concerning, as this complication can lead to severe maternal and neonatal morbidity and mortality if not promptly managed [15]. Obstructed labour in teenagers is primarily attributed to cephalopelvic disproportion due to incomplete pelvic maturation, a biological reality that underscores the importance of skilled birth attendance and emergency obstetric care capacity [16]. The finding that obstructed labour was the leading complication differs from some studies in other LMICs where haemorrhage or hypertensive disorders predominate [17,18], suggesting context-specific risk profiles that may relate to referral patterns, clinical protocols, or population characteristics. The 37.4% caesarean section rate, while higher than WHO recommendations for general populations, may be appropriate given the high-risk nature of teenage pregnancies and the predominance of obstructed labour. However, this rate warrants careful monitoring to ensure that interventions are medically justified and not contributing to unnecessary medicalization of childbirth. Referral System Challenges The most significant finding from our multivariable analysis is that referral status was the only independent predictor of adverse maternal outcomes, with referred mothers having nearly four times higher odds of complications. This finding has important implications for understanding healthcare delivery patterns and system performance. This association likely reflects the "three delays" model of maternal mortality, specifically delays in receiving appropriate care after reaching a health facility [19]. Women referred to KRRH were already experiencing complications or were identified as high-risk at lower-level facilities, explaining the higher adverse outcome rates. However, this pattern also suggests potential gaps in the referral system, including: Late recognition of complications at primary care level, Delays in decision-making for referral, Transportation challenges affecting timely arrival, Communication gaps between referring facilities and KRRH, Inadequate stabilization before transfer These findings align with broader literature on referral system challenges in sub-Saharan Africa, where delays in recognition, decision-making, and transportation contribute significantly to maternal morbidity and mortality [20]. Neonatal Outcomes While the majority of newborns were healthy (73.9%), the rates of adverse neonatal outcomes, particularly low birth weight (11.7%) and birth asphyxia (8.1%) - reflect the risks associated with teenage pregnancy. These outcomes are consistent with international literature documenting increased risks of preterm birth, low birth weight, and neonatal complications among adolescent mothers [21]. The 0.9% neonatal mortality rate, while concerning, is lower than some reported rates in similar settings, potentially reflecting the referral hospital setting with specialized neonatal care capacity. However, these outcomes underscore the importance of addressing teenage pregnancy not only for maternal health but also for child survival and development. Strengths and Limitations This study's strengths include the use of consecutive sampling to minimize selection bias, comprehensive data collection covering both demographic and clinical variables, and the inclusion of qualitative insights from healthcare providers. The hospital setting allowed for detailed documentation of complications and outcomes using medical records. However, several limitations must be acknowledged. The cross-sectional design limits causal inference, and the single-centre setting may limit generalizability to other contexts. The study captured only facility-based deliveries, potentially missing outcomes among teenagers who delivered at home or in private facilities. Additionally, some risk factors for teenage pregnancy (such as detailed social determinants) were not comprehensively assessed. The relatively short data collection period (four months) may not capture seasonal variations in pregnancy outcomes or healthcare seeking patterns. Future studies would benefit from longer observation periods and multi-centre designs to enhance external validity. Policy and Practice Implications Our findings have several important implications for policy and practice: Strengthening referral systems: The strong association between referral status and adverse outcomes highlights the urgent need to strengthen referral pathways. Interventions should focus on; enhanced training for primary care providers in early recognition of obstetric complications, improved communication systems between facilities, strengthening transportation networks for emergency referrals, standardization of referral criteria and protocols. Emergency obstetric care capacity: The high rate of obstructed labour among referred cases underscores the importance of ensuring adequate emergency obstetric care capacity at KRRH and other referral facilities. This includes maintaining skilled personnel, essential supplies, and functioning equipment for caesarean sections and other emergency procedures. Targeted interventions for high-risk groups: While referral status was the strongest predictor, the tendency toward significance for factors like parity and household income suggests the need for targeted interventions addressing socioeconomic vulnerabilities. Adolescent-friendly services: The persistence of adverse outcomes despite high ANC attendance suggests the need for adolescent-specific approaches to care that address the unique physiological and social needs of pregnant teenagers. Conclusions This study demonstrates that teenage mothers at Kabale Regional Referral Hospital, despite being predominantly older teenagers with high antenatal care attendance, remain vulnerable to significant obstetric complications, particularly obstructed labour. The finding that referral status was the strongest predictor of adverse outcomes highlights critical gaps in the healthcare delivery system, specifically in the referral pathway from primary to tertiary care. Addressing the burden of adverse outcomes among teenage mothers requires a multi-faceted approach focusing on strengthening referral systems, enhancing emergency obstetric care capacity, and developing adolescent-specific interventions. Priority interventions should include training primary care providers in early recognition of complications, improving communication and transportation systems for referrals, and ensuring adequate emergency obstetric care resources at referral facilities. Future research should explore the specific mechanisms underlying referral system challenges and evaluate interventions designed to strengthen care pathways for high-risk obstetric cases. Additionally, longitudinal studies examining long-term maternal and child health outcomes following teenage pregnancy would provide valuable insights for developing comprehensive interventions. The findings underscore the continued importance of teenage pregnancy as a public health priority in southwestern Uganda and provide evidence-based insights to guide targeted interventions aimed at reducing maternal and neonatal morbidity in this vulnerable population. Declarations Ethics approval and consent to participate: Ethical approval was obtained from Kabale University Research Ethics Committee (KABREC-2024-240). Written informed consent was obtained from participants aged 18-19 years, while parental/guardian consent and participant assent were obtained for minors under 18 years. Consent for publication: Not applicable. Availability of data and materials: The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request. Competing interests: The authors declare that they have no competing interests. Funding: This research received no external funding. The study was entirely self-financed by the authors. Authors' contributions: DA conceived and designed the study, collected and analyzed data, and drafted the initial manuscript. SOB supervised the study design and data analysis, and provided critical revisions. CT provided methodological guidance and contributed to manuscript revision. RKA supervised the overall study, provided intellectual input throughout the research process, and critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript. Acknowledgments: The authors thank Kabale University for institutional support, the administration and staff of Kabale Regional Referral Hospital for facilitating data collection, and all participating teenage mothers and healthcare providers who made this study possible. We also acknowledge the research assistants who supported data collection activities. References Abet, T. (2024, February 27). Teen mothers contribute 18% of maternal deaths - report. Monitor . https://www.monitor.co.ug/uganda/news/national/teen-mothers-contribute-18-of-maternal-deaths-report-4538242 Abebe, A. M., Fitaw, Y., Koye, D. N., Zemene, M. A., Belay, Y. A., & Teshale, A. B. (2020). Teenage pregnancy and its associated factors among school adolescents of Mecha district, West Gojam zone, northwest Ethiopia. Reproductive Health , 17 (1), 1-9. Althabe, F., Moore, J. L., Gibbons, L., Berrueta, M., Goudar, S. S., Chomba, E., ... & Belizan, J. M. (2015). Adverse maternal and perinatal outcomes in adolescent pregnancies: The Global Network's Maternal Newborn Health Registry study. Reproductive Health , 12 (2), 1-9. Amjad, S., MacDonald, I., Chambers, T., Osornio-Vargas, A., Chandra, S., Voaklander, D., & Ospina, M. B. (2018). Social determinants of health and adverse maternal and birth outcomes in adolescent pregnancies: A systematic review and meta-analysis. Paediatric and Perinatal Epidemiology , 33 (1), 88-99. Amoadu, M., Ansah, B., Gyesaw, N. Y. K., Sarfo, L. A., Mohammed, A., Yidana, A., & Bonsu, G. (2022). Prevalence and determinants of adolescent pregnancy in the Ga West Municipality of Ghana: A community-based cross-sectional study. PLoS One , 17 (4), e0265473. Bedaso, A., Adams, J., Peng, W., & Sibbritt, D. (2021). Prevalence and determinants of low social support during pregnancy among Australian women: a community-based cross-sectional study. Reproductive Health , 18 (1), 1-11. Bell, J., Jayne, J., Tschann, J., Flores, E., Deardorff, J., & Kushi, L. H. (2014). Adolescent pregnancy in Brazil: Social determinants and health outcomes. International Journal of Adolescent Medicine and Health , 26 (3), 389-395. Blencowe, H., Cousens, S., Jassir, F. B., Say, L., Chou, D., Mathers, C., ... & Lawn, J. E. (2016). National, regional, and worldwide estimates of stillbirth rates in 2015, with trends from 2000: a systematic analysis. The Lancet Global Health , 4 (2), e98-e108. Bomboka, J. B., N-Mboowa, M. G., & Nakilembe, J. (2019). Post-effects of obstetric fistula in Uganda; A case study of fistula survivors in KITOVU mission hospital (MASAKA), Uganda. BMC Public Health , 19 (1), 1-7. Byonanebye, J., Brazauskas, R., Tumwesigye, N., Young, S., May, T., & Cassidy, L. (2020). Geographic variation and risk factors for teenage pregnancy in Uganda. African Health Sciences , 20 (4), 1898-1907. Cantarutti, A., Merlino, L., Monzani, E., Giaquinto, C., & Corrao, G. (2017). Use of antidepressant medication in pregnancy and adverse neonatal outcomes: A population-based investigation. Pharmacoepidemiology and Drug Safety , 26 (9), 1100-1108. Chemutai, V., Musaba, M. W., Amongin, D., & Wandabwa, J. N. (2022). Prevalence and factors associated with teenage pregnancy among parturients in Mbale Regional Referral Hospital: a cross-sectional study. African Health Sciences , 22 (2), 451-458. Dossou, J. P., Ntambue, A. M., Mulamba, D. K., Ngatu, R. N., Mpanya, G., Chutumwa, D. K., ... & Malonga, F. K. (2021). Factors associated with antenatal care attendance in the Democratic Republic of the Congo: Results of a cross-sectional survey. BMC Pregnancy and Childbirth , 21 (1), 1-13. Evans, M. K., O'Brien, B., & Greenberg, C. R. (2022). Medical complexity and healthcare utilization among adolescent mothers and their infants. Journal of Adolescent Health , 70 (4), 584-592. Fenta, S. M., Fenta, H. M., Yilema, S. A., Chen, D. G., & Mekonnin, A. W. (2024). Individual and community-level factors associated with adequate antenatal care service utilization in sub-Saharan Africa. Tropical Medicine and Health , 52 (1), 1-12. Fosca, W. R. (2023). Understanding the Influential Factors of Teenage Pregnancy in Kirumya Sub-county, Bundibugyo District, Western Uganda. IAA Journal of Applied Sciences , 10 (1), 100-113. Ganchimeg, T., Ota, E., Morisaki, N., Laopaiboon, M., Lumbiganon, P., Zhang, J., ... & Mori, R. (2014). Pregnancy and childbirth outcomes among adolescent mothers: a World Health Organization multicountry study. BJOG: An International Journal of Obstetrics & Gynaecology , 121 (1), 40-48. Gardner, B., Warzecha, D., Shi, J., Clothier, B., Meacham, S., Wang, L., ... & Burd, I. (2023). Racial disparities in maternal morbidity and mortality. Seminars in Fetal and Neonatal Medicine , 28 (4), 101456. Islam, N., & Masud, J. (2018). Determinants of frequency and contents of antenatal care visits in Bangladesh: Assessing the extent of compliance with the WHO recommendations. PLoS One , 13 (9), e0204752. Jackson-Gibson, M., Ezeanolue, C. O., Patel, D., Yang, W., Melvin, S. C., Osuji, A., ... & Ezeanolue, E. E. (2022). HIV status disclosure and psychosocial outcomes among HIV-positive young women in Nigeria. AIDS and Behavior , 26 (3), 961-971. Karimi, M., Brazier, E., Kariuki, J., Karibe, M., Maina, B., Liku, J., ... & Warren, C. E. (2022). The influence of quality improvement on maternal health care utilization in Kenya. BMC Health Services Research , 22 (1), 1-12. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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-8502790","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":568560422,"identity":"1d903b2a-b7e8-4b9b-b181-b6bcb0cf195b","order_by":0,"name":"Deus Akampurira","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYBACCQYGNiDFzMBwAEh9AGI2dlK0MM4AaWEmRQszDwOEjRdIth9+9uDjDms5vuM9xp9tfm2T52NmYPzwMQe3FmmeNHPDmWfSjSXPnDGTzu27bdjGzMAsOXMbbi1yDDls0rxthxM33MgxY87tuc0I1MLGzItPC/8bqJb7b4w/W/bctieoRVoCbguPgTTDj9uJBLVIznhmJjmzDeSXtDLJ3obbyW3MjM14/SJxPvmZxMc2UIgd3vzhx5/btvPbmw9++IhHCypgbAOTDcSqB4E/pCgeBaNgFIyCkQIA9BROXRfOvS0AAAAASUVORK5CYII=","orcid":"","institution":"Kabale University","correspondingAuthor":true,"prefix":"","firstName":"Deus","middleName":"","lastName":"Akampurira","suffix":""},{"id":568560423,"identity":"1dada9b1-1e2a-40d6-a95a-3f925893e29a","order_by":1,"name":"Sebastian Olikira Baine","email":"","orcid":"","institution":"Kabale University","correspondingAuthor":false,"prefix":"","firstName":"Sebastian","middleName":"Olikira","lastName":"Baine","suffix":""},{"id":568560424,"identity":"e8a2b832-f097-4afb-a9c9-67ef5a29b9b9","order_by":2,"name":"Christopher Tumwine","email":"","orcid":"","institution":"Kabale University","correspondingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"","lastName":"Tumwine","suffix":""},{"id":568560425,"identity":"8ba49554-fb25-43d8-af8c-b15fb75e9642","order_by":3,"name":"Ronald Kibonire Arineitwe","email":"","orcid":"","institution":"Kabale University","correspondingAuthor":false,"prefix":"","firstName":"Ronald","middleName":"Kibonire","lastName":"Arineitwe","suffix":""}],"badges":[],"createdAt":"2026-01-02 18:23:27","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8502790/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8502790/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":99730642,"identity":"4e0ef85b-6bb2-4933-b11b-a0351855ec4f","added_by":"auto","created_at":"2026-01-07 17:41:59","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":45551,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript1forPublication.docx","url":"https://assets-eu.researchsquare.com/files/rs-8502790/v1/d8a852cad1bfbd3f2c5d67e5.docx"},{"id":99730641,"identity":"a410dde1-75b6-4980-8e5d-d0ecf0400e17","added_by":"auto","created_at":"2026-01-07 17:41:59","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":342,"visible":true,"origin":"","legend":"","description":"","filename":"rs8502790.json","url":"https://assets-eu.researchsquare.com/files/rs-8502790/v1/438164bdc039b0a65d4a05da.json"},{"id":99797581,"identity":"bb70ccd1-b91b-4522-b6fd-de4a2865d353","added_by":"auto","created_at":"2026-01-08 13:46:05","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":84830,"visible":true,"origin":"","legend":"","description":"","filename":"rs85027901enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8502790/v1/116022efe3eeb0a49552de21.xml"},{"id":99730645,"identity":"dd7f4cf8-88d0-49e7-a049-d1c879ec0cee","added_by":"auto","created_at":"2026-01-07 17:41:59","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":81234,"visible":true,"origin":"","legend":"","description":"","filename":"rs85027901structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8502790/v1/f4f8b7c38450829482cb72d9.xml"},{"id":99730643,"identity":"e247a074-d526-43dc-86a3-5f994ca70c55","added_by":"auto","created_at":"2026-01-07 17:41:59","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":92438,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8502790/v1/59a9e6bf00c50cc3dad8843b.html"},{"id":99805032,"identity":"ccc14c99-a54c-4884-b4d0-8b53fb9cd81c","added_by":"auto","created_at":"2026-01-08 14:15:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1156972,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8502790/v1/faa1339c-2766-43c3-bb13-81d10263061a.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eCharacteristics and Pregnancy Outcomes of Teenage Mothers at Kabale Regional Referral Hospital, Uganda: A Cross-Sectional Study\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eTeenage pregnancy, occurring in females aged 13-19 years, represents a significant global public health challenge with far-reaching consequences for maternal and child health outcomes [1]. Approximately 16 million adolescent girls give birth annually worldwide, with 95% of these births occurring in low- and middle-income countries (LMICs) [2]. The physiological and social immaturity associated with adolescent pregnancy increases the risk of adverse maternal outcomes, including obstructed labour, postpartum haemorrhage, hypertensive disorders, and maternal mortality [3,4].\u003c/p\u003e\n\u003cp\u003eSub-Saharan Africa bears a disproportionate burden of teenage pregnancies, with rates remaining persistently high despite global decline trends [5]. In Uganda, approximately 25% of girls become pregnant by age 19, contributing to 18-28% of maternal deaths nationally [6,7]. This burden is compounded by complex socioeconomic factors including poverty, early marriage, limited educational opportunities, and inadequate access to adolescent-friendly reproductive health services [8]. The COVID-19 pandemic has further exacerbated these challenges through increased school dropouts and reduced healthcare accessibility [9].\u003c/p\u003e\n\u003cp\u003eThe Kigezi subregion of southwestern Uganda, served by Kabale Regional Referral Hospital (KRRH), faces particularly high rates of teenage pregnancy due to cultural practices favouring early marriage and limited economic opportunities for teenagers [10]. KRRH serves as the primary referral centre for approximately 1.4 million people across six districts, managing complex obstetric cases from both facility and community deliveries.\u003c/p\u003e\n\u003cp\u003eDespite the recognized burden of teenage pregnancy in this region, comprehensive data on the characteristics and outcomes of teenage mothers delivering at KRRH remain limited. Understanding the demographic profiles, clinical characteristics, and pregnancy outcomes of this vulnerable population is crucial for developing targeted interventions to reduce maternal and neonatal morbidity and mortality. Furthermore, identifying predictors of adverse outcomes can inform risk stratification and resource allocation strategies.\u003c/p\u003e\n\u003cp\u003eThis study aimed to: (1) determine the demographic and clinical characteristics of teenage mothers delivering at KRRH, (2) identify maternal outcomes of teenage pregnancies, and (3) identify factors associated with adverse maternal outcomes to inform evidence-based interventions.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy Design and Setting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted a hospital-based cross-sectional study at the maternity ward of Kabale Regional Referral Hospital from January to April 2025. KRRH is a 350-bed tertiary referral hospital serving as the primary obstetric care centre for Kabale, Rubanda, Rukiga, Kanungu, Rukungiri, and Kisoro districts in southwestern Uganda. The maternity ward handles approximately 4,000 deliveries annually, with teenage pregnancies comprising approximately 13% of all deliveries.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Population and Sampling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study population comprised all teenage mothers aged 13-19 years who delivered at KRRH during the study period. We calculated the sample size using Cochran's formula with finite population correction, based on 521 teenage deliveries recorded in the 2023-2024 fiscal year. Assuming a 95% confidence level, 5% margin of error, and 50% expected proportion of adverse outcomes, the required sample size was 222 participants.\u003c/p\u003e\n\u003cp\u003eWe employed consecutive sampling to recruit eligible participants until reaching the target sample size. All consenting teenage mothers aged 18-19 years and assenting mothers aged 13-17 years, who delivered during the study period were included. Exclusion criteria comprised mothers with cognitive impairment or sensory disabilities that would prevent effective communication during interviews.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection Procedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantitative data collection:\u003c/strong\u003e We used a structured interviewer-administered questionnaire developed based on literature review and expert consultation. The questionnaire captured demographic characteristics (age, marital status, residence, education, occupation, household income), obstetric history (parity, gravidity, antenatal care attendance), pregnancy and delivery details (mode of delivery, referral status, complications), and neonatal outcomes. The questionnaire was pre-tested on 22 teenage mothers at a neighbouring health facility and translated into Rukiga (the local language) for enhanced comprehension.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQualitative data collection:\u003c/strong\u003e We conducted in-depth interviews with purposively selected midwives using a semi-structured interview guide to explore their experiences managing teenage pregnancies and perceived risk factors for adverse outcomes. Interviews lasted 30-45 minutes and were audio-recorded with consent.\u003c/p\u003e\n\u003cp\u003eTwo trained midwives served as research assistants, ensuring cultural sensitivity and clinical expertise in data collection. Training covered study objectives, ethical considerations, interview techniques, and data quality assurance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVariable Definitions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdverse maternal outcomes:\u003c/strong\u003e We defined this composite outcome as the occurrence of any delivery-related complication requiring medical or surgical intervention, including obstructed labour, postpartum haemorrhage, pregnancy-induced hypertension/preeclampsia, sepsis, or other complications documented in medical records.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntenatal care adequacy:\u003c/strong\u003e We assessed both attendance (any ANC visit) and adequacy (≥4 visits as per WHO recommendations).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReferral status:\u003c/strong\u003e Categorized as referred (transferred from lower-level health facilities) or non-referred (direct attendance or self-referral).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Management and Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQuantitative data were entered into SPSS version 20.0 and cleaned for completeness and consistency. We performed descriptive analysis using frequencies and percentages for categorical variables, and medians with interquartile ranges for continuous variables due to non-normal distribution.\u003c/p\u003e\n\u003cp\u003eFor inferential analysis, we used binary logistic regression to identify predictors of adverse maternal outcomes. Variables with p≤0.25 in bivariate analysis were included in the multivariable model. We assessed model fit using the Hosmer-Lemeshow goodness-of-fit test and reported adjusted odds ratios (aOR) with 95% confidence intervals. Statistical significance was set at p\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003eQualitative data were transcribed verbatim and analysed thematically using an inductive approach. Two researchers independently coded the transcripts, with discrepancies resolved through discussion to ensure reliability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe obtained ethical approval from Kabale University Research Ethics Committee (KABREC-2024-240) and administrative clearance from KRRH administration. Written informed consent was obtained from participants aged 18-19 years. For minors (\u0026lt;18 years), we obtained both parental/guardian consent and participant assent. We maintained confidentiality by using unique identifiers and storing data in password-protected files accessible only to the research team.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eParticipant Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe recruited 222 teenage mothers during the four-month study period, representing a 100% response rate among eligible participants. The median age was 19 years (IQR: 18-19), with the majority (88.3%, n=196) aged 18-19 years and 11.7% (n=26) aged 15-17 years. Most participants were married (71.6%, n=159), with 22.5% (n=50) single and 5.9% (n=13) separated or divorced.\u003c/p\u003e\n\u003cp\u003eTwo-thirds of participants (67.1%, n=149) resided in rural areas. Educational attainment was relatively balanced, with 48.2% (n=107) having completed primary education and 49.1% (n=109) secondary education. Only 2.3% (n=5) had vocational or technical training. Economic status was uniformly low, with 94.2% (n=209) reporting monthly household incomes below UGX 200,000 (approximately $54).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Demographic characteristics of teenage mothers (N=222)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 190px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 190px;\"\u003e\n \u003cp\u003e15-17 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 190px;\"\u003e\n \u003cp\u003e18-19 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e88.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 190px;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e22.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 190px;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e71.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 190px;\"\u003e\n \u003cp\u003eSeparated/divorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 190px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e67.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 190px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e32.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 190px;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e48.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 190px;\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e49.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 190px;\"\u003e\n \u003cp\u003eVocational/technical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonthly income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 190px;\"\u003e\n \u003cp\u003e\u0026lt;UGX 100,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e60.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 190px;\"\u003e\n \u003cp\u003eUGX 100,000-199,999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e33.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 147px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 190px;\"\u003e\n \u003cp\u003e\u0026ge;UGX 200,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 33px;\"\u003e\n \u003cp\u003e5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eObstetric and Delivery Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe vast majority of participants 86.0% (n=191) were primigravida, with 13.5% (n=30) having 1-2 previous pregnancies. Age at first pregnancy was predominantly 18-19 years 82.0% (n=182).\u003c/p\u003e\n\u003cp\u003eAntenatal care attendance was nearly universal 99.1% (n=220), though only 57.2% (n=127) completed the recommended four or more visits. The caesarean section rate was 37.4% (n=83), notably higher than the WHO-recommended 10-15% rate. Almost one-third of mothers 31.5% (n=70) were referred from lower-level health facilities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Obstetric and delivery characteristics (N=222)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003ePrimigravida\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e86.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003ePara 1-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e13.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003ePara \u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eANC attendance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e99.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eANC visits\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026ge;4 visits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e57.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026lt;4 visits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e41.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003eNo ANC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMode of delivery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003eVaginal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e62.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003eCaesarean section\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e37.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReferral status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003eReferred\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e31.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 195px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003eNot referred\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e68.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eMaternal and Neonatal Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMaternal complications occurred in 33.3% (n=74) of deliveries. Among mothers with complications, obstructed labour was leading 48.6% (n=36), followed by preterm labour 32.4% (n=24), haemorrhage 14.9% (n=11), infection 5.4% (n=4), and preeclampsia/eclampsia 4.1% (n=3).\u003c/p\u003e\n\u003cp\u003eMost newborns 73.9% (n=164) were healthy at birth. However, adverse neonatal outcomes included low birth weight 11.7% (n=26), birth asphyxia 8.1% (n=18), preterm birth 5.0% (n=11), and neonatal death 0.9% (n=2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Maternal complications and neonatal outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaternal Complications (n=74)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003eObstructed labour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e48.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003ePreterm labour\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e32.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003eHaemorrhage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e14.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003eInfection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 285px;\"\u003e\n \u003cp\u003ePreeclampsia/eclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e4.1\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\u003ctable border=\"1\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 279px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNeonatal Outcomes (N=222)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 279px;\"\u003e\n \u003cp\u003eHealthy newborn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e73.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 279px;\"\u003e\n \u003cp\u003eLow birth weight (\u0026lt;2.5kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 279px;\"\u003e\n \u003cp\u003eBirth asphyxia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 279px;\"\u003e\n \u003cp\u003ePreterm birth (\u0026lt;37 weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 279px;\"\u003e\n \u003cp\u003eNeonatal death\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 45px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Percentages calculated from mothers with complications (n=74)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePredictors of Adverse Maternal Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn bivariate analysis, several factors showed associations with adverse outcomes (p\u0026le;0.25): referral status, parity, household income, and ANC visit frequency. In multivariable logistic regression analysis, referral status emerged as the only statistically significant independent predictor of adverse maternal outcomes. Teenage mothers referred from lower-level health facilities had nearly four times higher odds of developing complications compared to non-referred mothers (aOR=3.77, 95% CI: 1.53-9.28, p=0.004).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: Predictors of adverse maternal outcomes - Logistic regression analysis\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBivariate Analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariable Analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eaOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eReferral status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNot referred\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eReferred\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.85-6.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e3.77\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.53-9.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAge group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e18-19 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e15-17 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.48-2.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.24-4.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eParity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePrimigravida\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMultigravida\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.02-4.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.85-7.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHousehold income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge;UGX 100,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;UGX 100,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.05-3.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.88-5.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eANC visits\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge;4 visits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;4 visits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.95-2.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.67-3.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.347\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Bold values indicate statistical significance (p\u0026lt;0.05) *Hosmer-Lemeshow test: \u0026chi;\u0026sup2;=3.24, p=0.864 (good model fit)\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cstrong\u003ePrincipal Findings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study provides important insights into the characteristics and pregnancy outcomes of teenage mothers at a major referral hospital in southwestern Uganda. Our findings reveal that while teenage mothers at KRRH were predominantly older adolescents with high antenatal care attendance, they remained vulnerable to significant obstetric complications, with obstructed labour being the leading cause of morbidity. Critically, referral status emerged as the strongest independent predictor of adverse maternal outcomes, highlighting important gaps in the healthcare delivery system.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDemographic Profile and Implications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe predominance of older teenagers (18-19 years) in our cohort aligns with demographic trends showing peak fertility rates in late teenage years across sub-Saharan Africa [11]. The high marriage rate (71.6%) reflects cultural practices in southwestern Uganda where early marriage remains common, often driving teenage pregnancy [12]. The rural predominance (67.1%) and low economic status of participants underscore the intersection of geographical and socioeconomic vulnerabilities that characterize teenage pregnancy in this setting.\u003c/p\u003e\n\u003cp\u003eThe relatively balanced educational attainment between primary and secondary levels suggests that education alone may not be sufficient to prevent teenage pregnancy, consistent with findings from other Ugandan studies [13]. This highlights the need for comprehensive interventions addressing not only educational access but also economic empowerment and reproductive health education.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntenatal Care Patterns\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe near-universal ANC attendance (99.1%) represents a significant achievement, reflecting successful scale-up of maternal health services in the region. However, the finding that only 57.2% completed four or more visits indicates challenges in ensuring adequate care quality and continuity. This pattern is consistent with national trends where ANC initiation is high but completion rates remain suboptimal [14].\u003c/p\u003e\n\u003cp\u003eThe gap between ANC attendance and adequacy suggests opportunities for strengthening service delivery, including addressing barriers such as distance to health facilities, cost of transportation, and quality of care. Given that adequate ANC is crucial for early identification and management of pregnancy complications, improving completion rates should be a priority intervention.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaternal Complications and Clinical Significance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 33.3% complication rate among teenage mothers is substantial and reflects the inherent risks associated with teenage pregnancy. The predominance of obstructed labour (48.6% of complications) is particularly concerning, as this complication can lead to severe maternal and neonatal morbidity and mortality if not promptly managed [15].\u003c/p\u003e\n\u003cp\u003eObstructed labour in teenagers is primarily attributed to cephalopelvic disproportion due to incomplete pelvic maturation, a biological reality that underscores the importance of skilled birth attendance and emergency obstetric care capacity [16]. The finding that obstructed labour was the leading complication differs from some studies in other LMICs where haemorrhage or hypertensive disorders predominate [17,18], suggesting context-specific risk profiles that may relate to referral patterns, clinical protocols, or population characteristics.\u003c/p\u003e\n\u003cp\u003eThe 37.4% caesarean section rate, while higher than WHO recommendations for general populations, may be appropriate given the high-risk nature of teenage pregnancies and the predominance of obstructed labour. However, this rate warrants careful monitoring to ensure that interventions are medically justified and not contributing to unnecessary medicalization of childbirth.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReferral System Challenges\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe most significant finding from our multivariable analysis is that referral status was the only independent predictor of adverse maternal outcomes, with referred mothers having nearly four times higher odds of complications. This finding has important implications for understanding healthcare delivery patterns and system performance.\u003c/p\u003e\n\u003cp\u003eThis association likely reflects the \"three delays\" model of maternal mortality, specifically delays in receiving appropriate care after reaching a health facility [19]. Women referred to KRRH were already experiencing complications or were identified as high-risk at lower-level facilities, explaining the higher adverse outcome rates. However, this pattern also suggests potential gaps in the referral system, including: Late recognition of complications at primary care level, Delays in decision-making for referral, Transportation challenges affecting timely arrival, Communication gaps between referring facilities and KRRH, Inadequate stabilization before transfer\u003c/p\u003e\n\u003cp\u003eThese findings align with broader literature on referral system challenges in sub-Saharan Africa, where delays in recognition, decision-making, and transportation contribute significantly to maternal morbidity and mortality [20].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNeonatal Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhile the majority of newborns were healthy (73.9%), the rates of adverse neonatal outcomes, particularly low birth weight (11.7%) and birth asphyxia (8.1%) - reflect the risks associated with teenage pregnancy. These outcomes are consistent with international literature documenting increased risks of preterm birth, low birth weight, and neonatal complications among adolescent mothers [21].\u003c/p\u003e\n\u003cp\u003eThe 0.9% neonatal mortality rate, while concerning, is lower than some reported rates in similar settings, potentially reflecting the referral hospital setting with specialized neonatal care capacity. However, these outcomes underscore the importance of addressing teenage pregnancy not only for maternal health but also for child survival and development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and Limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study's strengths include the use of consecutive sampling to minimize selection bias, comprehensive data collection covering both demographic and clinical variables, and the inclusion of qualitative insights from healthcare providers. The hospital setting allowed for detailed documentation of complications and outcomes using medical records.\u003c/p\u003e\n\u003cp\u003eHowever, several limitations must be acknowledged. The cross-sectional design limits causal inference, and the single-centre setting may limit generalizability to other contexts. The study captured only facility-based deliveries, potentially missing outcomes among teenagers who delivered at home or in private facilities. Additionally, some risk factors for teenage pregnancy (such as detailed social determinants) were not comprehensively assessed.\u003c/p\u003e\n\u003cp\u003eThe relatively short data collection period (four months) may not capture seasonal variations in pregnancy outcomes or healthcare seeking patterns. Future studies would benefit from longer observation periods and multi-centre designs to enhance external validity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePolicy and Practice Implications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur findings have several important implications for policy and practice:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengthening referral systems:\u003c/strong\u003e The strong association between referral status and adverse outcomes highlights the urgent need to strengthen referral pathways. Interventions should focus on; enhanced training for primary care providers in early recognition of obstetric complications, improved communication systems between facilities, strengthening transportation networks for emergency referrals, standardization of referral criteria and protocols.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEmergency obstetric care capacity:\u003c/strong\u003e The high rate of obstructed labour among referred cases underscores the importance of ensuring adequate emergency obstetric care capacity at KRRH and other referral facilities. This includes maintaining skilled personnel, essential supplies, and functioning equipment for caesarean sections and other emergency procedures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTargeted interventions for high-risk groups:\u003c/strong\u003e While referral status was the strongest predictor, the tendency toward significance for factors like parity and household income suggests the need for targeted interventions addressing socioeconomic vulnerabilities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdolescent-friendly services:\u003c/strong\u003e The persistence of adverse outcomes despite high ANC attendance suggests the need for adolescent-specific approaches to care that address the unique physiological and social needs of pregnant teenagers.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study demonstrates that teenage mothers at Kabale Regional Referral Hospital, despite being predominantly older teenagers with high antenatal care attendance, remain vulnerable to significant obstetric complications, particularly obstructed labour. The finding that referral status was the strongest predictor of adverse outcomes highlights critical gaps in the healthcare delivery system, specifically in the referral pathway from primary to tertiary care.\u003c/p\u003e\n\u003cp\u003eAddressing the burden of adverse outcomes among teenage mothers requires a multi-faceted approach focusing on strengthening referral systems, enhancing emergency obstetric care capacity, and developing adolescent-specific interventions. Priority interventions should include training primary care providers in early recognition of complications, improving communication and transportation systems for referrals, and ensuring adequate emergency obstetric care resources at referral facilities.\u003c/p\u003e\n\u003cp\u003eFuture research should explore the specific mechanisms underlying referral system challenges and evaluate interventions designed to strengthen care pathways for high-risk obstetric cases. Additionally, longitudinal studies examining long-term maternal and child health outcomes following teenage pregnancy would provide valuable insights for developing comprehensive interventions.\u003c/p\u003e\n\u003cp\u003eThe findings underscore the continued importance of teenage pregnancy as a public health priority in southwestern Uganda and provide evidence-based insights to guide targeted interventions aimed at reducing maternal and neonatal morbidity in this vulnerable population.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e Ethical approval was obtained from Kabale University Research Ethics Committee (KABREC-2024-240). Written informed consent was obtained from participants aged 18-19 years, while parental/guardian consent and participant assent were obtained for minors under 18 years.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research received no external funding. The study was entirely self-financed by the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions:\u003c/strong\u003e DA conceived and designed the study, collected and analyzed data, and drafted the initial manuscript. SOB supervised the study design and data analysis, and provided critical revisions. CT provided methodological guidance and contributed to manuscript revision. RKA supervised the overall study, provided intellectual input throughout the research process, and critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e The authors thank Kabale University for institutional support, the administration and staff of Kabale Regional Referral Hospital for facilitating data collection, and all participating teenage mothers and healthcare providers who made this study possible. We also acknowledge the research assistants who supported data collection activities.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbet, T. (2024, February 27). Teen mothers contribute 18% of maternal deaths - report. \u003cem\u003eMonitor\u003c/em\u003e. https://www.monitor.co.ug/uganda/news/national/teen-mothers-contribute-18-of-maternal-deaths-report-4538242\u003c/li\u003e\n\u003cli\u003eAbebe, A. M., Fitaw, Y., Koye, D. N., Zemene, M. A., Belay, Y. A., \u0026amp; Teshale, A. B. (2020). Teenage pregnancy and its associated factors among school adolescents of Mecha district, West Gojam zone, northwest Ethiopia. \u003cem\u003eReproductive Health\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(1), 1-9.\u003c/li\u003e\n\u003cli\u003eAlthabe, F., Moore, J. L., Gibbons, L., Berrueta, M., Goudar, S. S., Chomba, E., ... \u0026amp; Belizan, J. M. (2015). Adverse maternal and perinatal outcomes in adolescent pregnancies: The Global Network\u0026apos;s Maternal Newborn Health Registry study. \u003cem\u003eReproductive Health\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(2), 1-9.\u003c/li\u003e\n\u003cli\u003eAmjad, S., MacDonald, I., Chambers, T., Osornio-Vargas, A., Chandra, S., Voaklander, D., \u0026amp; Ospina, M. B. (2018). Social determinants of health and adverse maternal and birth outcomes in adolescent pregnancies: A systematic review and meta-analysis. \u003cem\u003ePaediatric and Perinatal Epidemiology\u003c/em\u003e, \u003cem\u003e33\u003c/em\u003e(1), 88-99.\u003c/li\u003e\n\u003cli\u003eAmoadu, M., Ansah, B., Gyesaw, N. Y. K., Sarfo, L. A., Mohammed, A., Yidana, A., \u0026amp; Bonsu, G. (2022). Prevalence and determinants of adolescent pregnancy in the Ga West Municipality of Ghana: A community-based cross-sectional study. \u003cem\u003ePLoS One\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(4), e0265473.\u003c/li\u003e\n\u003cli\u003eBedaso, A., Adams, J., Peng, W., \u0026amp; Sibbritt, D. (2021). Prevalence and determinants of low social support during pregnancy among Australian women: a community-based cross-sectional study. \u003cem\u003eReproductive Health\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(1), 1-11.\u003c/li\u003e\n\u003cli\u003eBell, J., Jayne, J., Tschann, J., Flores, E., Deardorff, J., \u0026amp; Kushi, L. H. (2014). Adolescent pregnancy in Brazil: Social determinants and health outcomes. \u003cem\u003eInternational Journal of Adolescent Medicine and Health\u003c/em\u003e, \u003cem\u003e26\u003c/em\u003e(3), 389-395.\u003c/li\u003e\n\u003cli\u003eBlencowe, H., Cousens, S., Jassir, F. B., Say, L., Chou, D., Mathers, C., ... \u0026amp; Lawn, J. E. (2016). National, regional, and worldwide estimates of stillbirth rates in 2015, with trends from 2000: a systematic analysis. \u003cem\u003eThe Lancet Global Health\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(2), e98-e108.\u003c/li\u003e\n\u003cli\u003eBomboka, J. B., N-Mboowa, M. G., \u0026amp; Nakilembe, J. (2019). Post-effects of obstetric fistula in Uganda; A case study of fistula survivors in KITOVU mission hospital (MASAKA), Uganda. \u003cem\u003eBMC Public Health\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(1), 1-7.\u003c/li\u003e\n\u003cli\u003eByonanebye, J., Brazauskas, R., Tumwesigye, N., Young, S., May, T., \u0026amp; Cassidy, L. (2020). Geographic variation and risk factors for teenage pregnancy in Uganda. \u003cem\u003eAfrican Health Sciences\u003c/em\u003e, \u003cem\u003e20\u003c/em\u003e(4), 1898-1907.\u003c/li\u003e\n\u003cli\u003eCantarutti, A., Merlino, L., Monzani, E., Giaquinto, C., \u0026amp; Corrao, G. (2017). Use of antidepressant medication in pregnancy and adverse neonatal outcomes: A population-based investigation. \u003cem\u003ePharmacoepidemiology and Drug Safety\u003c/em\u003e, \u003cem\u003e26\u003c/em\u003e(9), 1100-1108.\u003c/li\u003e\n\u003cli\u003eChemutai, V., Musaba, M. W., Amongin, D., \u0026amp; Wandabwa, J. N. (2022). Prevalence and factors associated with teenage pregnancy among parturients in Mbale Regional Referral Hospital: a cross-sectional study. \u003cem\u003eAfrican Health Sciences\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(2), 451-458.\u003c/li\u003e\n\u003cli\u003eDossou, J. P., Ntambue, A. M., Mulamba, D. K., Ngatu, R. N., Mpanya, G., Chutumwa, D. K., ... \u0026amp; Malonga, F. K. (2021). Factors associated with antenatal care attendance in the Democratic Republic of the Congo: Results of a cross-sectional survey. \u003cem\u003eBMC Pregnancy and Childbirth\u003c/em\u003e, \u003cem\u003e21\u003c/em\u003e(1), 1-13.\u003c/li\u003e\n\u003cli\u003eEvans, M. K., O\u0026apos;Brien, B., \u0026amp; Greenberg, C. R. (2022). Medical complexity and healthcare utilization among adolescent mothers and their infants. \u003cem\u003eJournal of Adolescent Health\u003c/em\u003e, \u003cem\u003e70\u003c/em\u003e(4), 584-592.\u003c/li\u003e\n\u003cli\u003eFenta, S. M., Fenta, H. M., Yilema, S. A., Chen, D. G., \u0026amp; Mekonnin, A. W. (2024). Individual and community-level factors associated with adequate antenatal care service utilization in sub-Saharan Africa. \u003cem\u003eTropical Medicine and Health\u003c/em\u003e, \u003cem\u003e52\u003c/em\u003e(1), 1-12.\u003c/li\u003e\n\u003cli\u003eFosca, W. R. (2023). Understanding the Influential Factors of Teenage Pregnancy in Kirumya Sub-county, Bundibugyo District, Western Uganda. \u003cem\u003eIAA Journal of Applied Sciences\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(1), 100-113.\u003c/li\u003e\n\u003cli\u003eGanchimeg, T., Ota, E., Morisaki, N., Laopaiboon, M., Lumbiganon, P., Zhang, J., ... \u0026amp; Mori, R. (2014). Pregnancy and childbirth outcomes among adolescent mothers: a World Health Organization multicountry study. \u003cem\u003eBJOG: An International Journal of Obstetrics \u0026amp; Gynaecology\u003c/em\u003e, \u003cem\u003e121\u003c/em\u003e(1), 40-48.\u003c/li\u003e\n\u003cli\u003eGardner, B., Warzecha, D., Shi, J., Clothier, B., Meacham, S., Wang, L., ... \u0026amp; Burd, I. (2023). Racial disparities in maternal morbidity and mortality. \u003cem\u003eSeminars in Fetal and Neonatal Medicine\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(4), 101456.\u003c/li\u003e\n\u003cli\u003eIslam, N., \u0026amp; Masud, J. (2018). Determinants of frequency and contents of antenatal care visits in Bangladesh: Assessing the extent of compliance with the WHO recommendations. \u003cem\u003ePLoS One\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(9), e0204752.\u003c/li\u003e\n\u003cli\u003eJackson-Gibson, M., Ezeanolue, C. O., Patel, D., Yang, W., Melvin, S. C., Osuji, A., ... \u0026amp; Ezeanolue, E. E. (2022). HIV status disclosure and psychosocial outcomes among HIV-positive young women in Nigeria. \u003cem\u003eAIDS and Behavior\u003c/em\u003e, \u003cem\u003e26\u003c/em\u003e(3), 961-971.\u003c/li\u003e\n\u003cli\u003eKarimi, M., Brazier, E., Kariuki, J., Karibe, M., Maina, B., Liku, J., ... \u0026amp; Warren, C. E. (2022). The influence of quality improvement on maternal health care utilization in Kenya. \u003cem\u003eBMC Health Services Research\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(1), 1-12.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Kabale University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"teenage pregnancy, adolescent mothers, obstetric complications, maternal outcomes, referral systems, Uganda","lastPublishedDoi":"10.21203/rs.3.rs-8502790/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8502790/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Teenage pregnancy remains a critical public health challenge in sub-Saharan Africa, with significant implications for maternal and neonatal health outcomes. In Uganda, teenage pregnancies account for 18-28% of maternal deaths, yet facility-specific evidence remains limited. This study assessed the characteristics and pregnancy outcomes of teenage mothers at Kabale Regional Referral Hospital (KRRH) and identified predictors of adverse maternal outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We conducted a hospital-based cross-sectional study at KRRH from January to April 2025. Using consecutive sampling, we recruited 222 consenting teenage mothers aged 13-19 years. Data were collected through structured interviews and complemented by in-depth interviews with midwives. We used descriptive statistics to summarize characteristics and binary logistic regression to identify predictors of adverse maternal outcomes, defined as delivery-related complications requiring medical intervention.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The median age was 19 years (IQR: 18-19), with 88.3% (n=196) aged 18-19 years. Most participants were married (71.6%, n=159), resided in rural areas (67.1%, n=149), and were primigravida (86.0%, n=191). While 99.1% (n=220) attended antenatal care, only 57.2% (n=127) completed the recommended four visits. Maternal complications occurred in 33.3% (n=74) of deliveries, with obstructed labour being most prevalent (48.6% of complications, n=36). Referral from lower-level facilities was the strongest independent predictor of adverse outcomes (adjusted OR=3.77, 95% CI: 1.53-9.28, p=0.004).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Despite high antenatal care attendance, teenage mothers at KRRH experienced substantial obstetric complications, particularly obstructed labour. The association between referral status and adverse outcomes highlights critical gaps in the referral system. Strengthening early risk identification, emergency obstetric care capacity, and referral pathways is essential for improving outcomes among teenage mothers in southwestern Uganda.\u003c/p\u003e","manuscriptTitle":"Characteristics and Pregnancy Outcomes of Teenage Mothers at Kabale Regional Referral Hospital, Uganda: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-07 17:41:54","doi":"10.21203/rs.3.rs-8502790/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ace760a1-8d66-4270-834f-ebaaa10c8fae","owner":[],"postedDate":"January 7th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":60502487,"name":"Statistical Epidemiology"}],"tags":[],"updatedAt":"2026-01-07T17:41:55+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-07 17:41:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8502790","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8502790","identity":"rs-8502790","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}