Infertility Predictors at Asella Referral & Teaching Hospital, Ethiopia: A Case-Control Study

Infertility Predictors at Asella Referral & Teaching Hospital, Ethiopia: A Case-Control 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 Infertility Predictors at Asella Referral & Teaching Hospital, Ethiopia: A Case-Control Study Ashenafi Degefa/AsD (MD), Ayalneh Demissie, Henok Tsegazeab/HT (MD), and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8917898/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 Introduction: Infertility is a global reproductive health challenge, defined as the failure to achieve pregnancy after 12 months of regular unprotected intercourse. In Ethiopia, where motherhood is central to social identity, infertility often leads to significant social stigma and marital instability. This study aimed to identify the socio-demographic and clinical determinants of infertility among women in Asella, South-East Ethiopia. Methods A facility-based matched case-control study was conducted at Asella Referral and Teaching Hospital (ARTH) from May 30 to December 30, 2024. A total of 405 participants (135 cases and 270 controls) were enrolled. Data were collected via structured interviews and managed through a double-entry protocol in Epi-Data 4.6. To ensure data reliability, a sensitivity analysis was performed to assess recall bias. Data were analyzed using SPSS version 27.0. Predictors were identified using conditional multivariable logistic regression, with significance set at p < 0.05. Results The mean age of participants was 27.53 ± 5.13 years, with secondary infertility being the predominant type (74.8%). Multivariable analysis revealed that formal education was the strongest predictor (AOR = 10.51; 95% CI: 4.18–26.41), followed by a history of gynaecological procedures (AOR = 7.34; 95% CI: 3.32–16.49). Women aged ≥ 30 years had nearly five times higher odds of infertility (AOR = 4.95,p < 0.001). Other significant risk factors included rural residency (AOR = 3.22), cyclic menstrual pain (AOR = 3.18), age at menarche ≥ 14 years (AOR = 2.69), and no prior use of family planning (AOR = 2.21). Aged menarche ≥ 14 years (AOR = 2.69), and no history of family planning use (AOR = 2.21). Conclusion Infertility in the Arsi Zone is a dual-natured crisis driven by biological aging among educated women and preventable clinical factors among rural populations. The strong association with prior gynaecological procedures and the high prevalence of secondary infertility point toward a need for improved surgical safety and post-operative care. Interventions should focus on enhancing reproductive health awareness and clinical standards in South-East Ethiopia. Obstetrics & Gynecology Asella Referral & Teaching Hospital Case-control study Ethiopia Gynaecological procedures Infertility Married Women Reproductive health Risk Factors Figures Figure 1 Introduction Background/Rationale Infertility is a disease of the reproductive system defined by the failure to achieve a clinical pregnancy after 12 months or more of regular unprotected sexual intercourse [ 1 , 2 ]. Globally, this condition affects approximately 10% to 15% of couples, impacting at least 186 million individuals and posing a significant public health challenge [ 3 , 4 ]. In Sub-Saharan Africa, while some regions show high rates of primary infertility, secondary infertility is considerably more common, often as a consequence of reproductive tract infections or complications from previous obstetric care [ 5 , 6 ]. Within the Ethiopian context, the prevalence is estimated at 24.2%, with secondary infertility being the dominant type at 90.7% [ 7 , 8 ]. For women in Ethiopia, parenthood is a vital social and personal milestone; consequently, the failure to conceive frequently leads to severe social stigma, marital instability, and mental illness [ 9 , 10 ]. Despite this profound impact, infertility is often neglected in national health policies, which typically prioritize maternal health and contraceptive services over the needs of childless couples [ 11 , 12 ]. This oversight has led to a shortage of specialized services and a "silent" epidemic of reproductive distress. Furthermore, previous local research has produced inconsistent findings regarding the primary drivers of infertility; for example, a history of sexually transmitted infections was a primary factor identified in Dessie [ 13 ], while rural residency was the focal predictor in Adama [ 14 ]. Such variations suggest that regional differences in lifestyle, clinical practices, and socio-economic status significantly influence reproductive outcomes. At Asella Referral and Teaching Hospital (ARTH), there is currently a critical gap in evidence-based data to explain the specific determinants affecting women in this unique catchment area. Without identifying these local factors—such as the impact of prior gynaecological surgeries, age-related risks, or menstrual patterns—it remains difficult for healthcare providers to develop effective prevention protocols or targeted patient counselling strategies [ 15 ]. To address this gap, this study was conducted to identify the socio-demographic and clinical determinants of infertility among married women attending ARTH in 2025. By evaluating variables such as education, residency, and reproductive history through a multivariable analysis, this research aims to provide the necessary evidence to improve the quality of reproductive healthcare and guide the development of regional health interventions in South-East Ethiopia. Results Sociodemographic characteristics of the study population, ARTH 2025 The study included 405 women (135 cases and 270 controls) aged 20–42 to identify infertility risk factors. The overall mean age was 27.53 ± 5.13 years. Participants were predominantly Oromo, Muslim, and married (Table 1 ). Table 1 Socio-demographic characteristics of the study population at ARTH, 2025 Variables Cases Control Frequency Percentage Frequency Percentage Age < 30 years 101 74.8 222 82.2 ≥ 30 Years 34 25.2 48 17.8 Mean Age (SD) 28.63 ± 4.68 26.97 ± 5.27 Religion Orthodox 43 31.9 94 34.8 Muslim 82 60.7 103 38.1 Protestant 4 3.0 60 22.2 Others 6 4.4 13 4.8 Ethnicity Oromo 121 89.6 211 78.1 Others** 14 10.4 59 21.9 Educational Status No Formal Education 14 10.4 94 34.8 Primary 121 89.6 176 75.2 Occupation House Wife 81 60.0 174 64.4 Merchant 28 20.7 42 15.6 Civil Servant 13 9.6 34 12.6 Others 13 9.6 20 7.4 Income < 5000 Birr 54 40.0 117 43.3 ≥ 5000 Birr 81 60.0 153 56.7 Residency Urban 27 20.0 121 44.8 Rural 108 80.0 149 55.2 Current Marital Status Married 133 98.5 263 97.4 Divorced 2 1.5 7 2.6 Duration of Marriage 5 Years 74 54.8 101 38.4 Table 2 Bivariable and Multivariable Analysis of Determinants of Infertility among Women at ARTH, 2025 (N = 405) Variables % % COR(CI) AOR(CI) Socio-Demographic Factors Age < 30Years 74.8 82.2 1 1 ≥ 30 Years 25.2 17.8 1.56[0.95,2.56]* 4.95[2.23–10.95]** Educational Status No Formal Education 10.4 34.8 1 1 Formal education 89.6 75.2 4.6[2.5–8.5]* 10.51[4.18–26.41]* Residency Urban 20.0 44.8 1 1 Rural 80.0 55.2 3.2[2.00-5.27]* 3.22[1.60–6.51]* Reproductive & Medical History Age at first Menses < 14 Years 20.0 39.6 1 1 ≥ 14 Years 80.0 60.4 2.6[1.61–4.27] 2.69[1.44–4.99]** Duration of Menses Less than 3 Days 30.4 22.2 1 1 ≥ 3 Days 69.6 77.8 0.66[0.41–1.04] 0.96[0.51–1.82] Cyclic pain during Menses Yes 40.0 67.8 1 1 No 60.0 32.2 3.16[2.01–4.84] 3.18[1.69–5.97]* Gynecological Procedure Yes 25.9 7.4 4.37[2.41–7.94] 7.34(3.32–16.49)* No 74.1 92.6 1 1 Age at first Marriage < 20 Years ≥ 20 Years 40 60 27 73 1 1.29(0.85–1.95) 1 0.93(0.49–1.77) Ever use of contraceptive Yes 34.8 53.3 1 1 No 65.2 46.7 2.14[1.39–3.28] 2.21(1.19–4.12)* Notes: AOR : Adjusted Odds Ratio; CI : Confidence Interval; * p < 0.05(Significant); ** p < 0.01(Highly Significant); *** p < 0.001(Extremely Significant) The model was adjusted for all variables with p < 0.25 in the bivariate analysis to control for potential confounders. Distribution of type and causes of Infertility, ARTH 2025 Among the 135 cases, 101 (74.8%) experienced secondary infertility, while 34 (25.2%) had primary infertility (Fig. 1 ). As shown in Fig. 1 , the leading identified cause for infertility was 'unexplained' (45.3%), followed by myoma (23.3%) and tubal obstruction (16.3% Results of the Multivariable Analysis The bivariable and multivariable logistic regression analyses were used to identify the independent determinants of infertility among women at ARTH. Variables such as age, educational status, residency, age at menarche, cyclic menstrual pain, history of gynaecological procedures, and contraceptive use remained significant after adjusting for confounders. The study found that women aged ≥ 30 years had nearly five times higher odds of being infertile compared to those under 30 (AOR = 4.95,95%CI:2.23–10.95). Formal education showed a strong association, with educated women exhibiting 10.51 times higher odds of infertility than those with no formal education (AOR = 10.51, 95%CI: 4.18–26.41). Regarding geography, rural residents were 3.22 times more likely to be in the case group compared to urban residents (AOR = 3.22, 95%CI: 1.60–6.51). In terms of reproductive history, age at menarche ≥ 14 years (AOR = 2.69,95%CI:1.44–4.99) and cyclic menstrual pain (AOR = 3.18,95%CI:1.69–5.97) were both significant risk factors. Notably, having a history of gynaecological procedures increased the odds of infertility by over seven-fold (AOR = 7.34, 95%CI: 3.32–16.49). Finally, women who had never used contraceptives were 2.21 times more likely to face infertility compared to those who had a history of contraceptive use (AOR = 2.21, 95%CI:1.19–4.12). Factors such as duration of menses and age at first marriage did not show a statistically significant association with infertility in the final multivariable model (P > 0.05). Discussion The findings of this study at ARTH underscore a complex interplay between biological, socio-demographic, and clinical determinants, revealing a dual-natured crisis of infertility in the Arsi Zone. Biological and Socio-Demographic Interplay One of the most prominent biological findings was that women aged ≥ 30 years had five times higher odds of infertility compared to those under 30 (AOR = 4.95). This result is consistent with studies conducted in other parts of Ethiopia, Nigeria, and Saudi Arabia [ 1 , 15 , 19 ], reinforcing the biological reality that both the quality and quantity of oocytes significantly decline as women age, particularly after the third decade of life [ 12 ]. Interestingly, the socio-demographic profile of the study population showed that women with formal education exhibited 10.5 times higher odds of infertility. This aligns with findings in Butajira, Ethiopia, and India [ 17 , 20 ], where higher educational attainment is often associated with delayed marriage and childbearing. However, this finding contradicts results from the Kambeta region [ 21 ], suggesting that the impact of education on fertility may vary based on regional socio-cultural norms. Furthermore, rural residency was associated with a 3.2-fold increase in infertility risk, mirroring trends seen in Adama [ 14 ] and the 2023 Ethiopian Demographic and Health Survey (EDHS) [ 8 ]. This increased risk among rural women may be linked to environmental exposures, such as pesticides in agricultural areas, or limited access to timely treatment for reproductive tract infections, which can lead to permanent tubal damage. Clinical Determinants and Secondary Infertility , the clinical determinants identified in this study highlight the significant role of secondary factors. A history of gynaecologic procedures was a major predictor (AOR = 7.34), a finding similar to results reported in Dessie [ 13 ]. This suggests that previous invasive procedures, possibly performed in settings with varying levels of post-operative care, may result in tubal damage, pelvic adhesions, or uterine scarring [ 13 , 22 ]. Additionally, late menarche (≥ 14 years) and cyclic painful menses (AOR = 3.18) were significant predictors, pointing toward underlying hormonal imbalances or inflammatory conditions such as endometriosis [ 13 , 14 , 23 ]. These clinical indicators are often symptomatic of pathologies like endometriosis, uterine fibroids, or Asherman’s syndrome, all of which can block fallopian tubes or interfere with embryo implantation. The strong association between these factors and infertility suggests that many cases at ARTH are secondary and potentially preventable through better early-stage gynaecological management. Strengths and Limitations A major strength of this study is the matched case-control design, which provided an efficient and robust framework for identifying predictors of infertility by ensuring comparability between cases and controls. The methodological rigor was further enhanced by a sensitivity analysis, which confirmed consistent findings between the total sample and a 6-month subgroup, effectively validating the accuracy of the self-reported data against recall bias. Additionally, the use of conditional multivariable logistic regression accounted for the matched study architecture, yielding statistically precise Adjusted Odds Ratios (AOR). Data integrity was further secured through double-blind entry in Epi-Data and comprehensive instrument translation protocols. However, certain limitations must be acknowledged. Despite the validation of recall accuracy, variables such as "travel and decision-making time" remain inherently subjective. Furthermore, although the model was based on established literature, it may not have fully captured unique site-specific determinants. Lastly, the p < 0.25 inclusion threshold for the multivariable model is a liberal approach that may include variables with a weaker influence in this specific context. Conclusion This study identifies critical predictors of infertility using a robust matched case-control design. By implementing a sensitivity analysis, we have scientifically validated that these findings are not distorted by recall bias, providing a high degree of confidence in the self-reported data. The multivariable analysis revealed that clinical and socio-demographic factors play a decisive role in fertility outcomes. Notably, women with a history of gynaecologic procedures were over seven times more likely to experience infertility (AOR = 7.34), while those with formal education showed a ten-fold increase in the odds of the outcome (AOR = 10.51), possibly reflecting delayed childbearing or differences in health-seeking behavior. Additionally, rural residency, menarche at age 14 or older, and cyclic menstrual pain were identified as significant predictors, each more than doubling the risk. Because the model was rigorously tested for fitness (Hosmer−Lemeshow) and multicollinearity (VIF), these associations serve as a reliable foundation for targeted clinical interventions. These findings provide a clear roadmap for healthcare providers to prioritize early screening for women with history of gynaecological procedures and cyclic pain, particularly in rural settings. Ultimately, addressing these identified risk factors is essential for developing effective, evidence-based reproductive health strategies. Recommendations 1. Clinical Practice and Early Screening Prioritize Gynaecologic History : Given that women with a history of gynaecologic procedures had over seven times the odds of infertility (AOR = 7.34), clinicians should implement rigorous post-procedure follow-ups and prioritize these patients for early fertility assessments. Pain Management as a Proxy : Healthcare providers should treat cyclic menstrual pain (AOR = 3.18) not just as a symptomatic issue, but as a clinical marker for potential underlying pathologies (such as endometriosis or PID) that may lead to infertility if left untreated. 2. Public Health and Policy Interventions Rural Healthcare Strengthening : The significant risk associated with rural residency (AOR = 3.22) highlights a gap in specialized reproductive care. Policy-makers should focus on decentralizing fertility-related diagnostic services to rural health centers to ensure early detection. Targeted Education Programs : Since formal education showed a ten-fold association (AOR = 10.51), reproductive health education should be integrated into higher education curricula. This should focus on the biological impact of age (AOR = 4.95 for age ≥ 30) and the importance of timely reproductive planning. 3. Community and Family Planning Counselling on Contraception : The finding that no family planning use doubled the odds of infertility (AOR = 2.21) suggests a need for better community counselling. Family planning should be promoted not only for birth spacing but as a tool for maintaining overall reproductive health and preventing complications that lead to secondary infertility. Methods Study Setting and period The study was conducted at Asella Referral and Teaching Hospital (ARTH), the primary clinical affiliate of Arsi University. The hospital is situated in Asella town, located approximately 175 km southeast of Ethiopia’s capital, Addis Ababa. ARTH serves as the sole referral hub for the Arsi Zone, managing a vast catchment population of approximately 3.5 million people. The hospital maintains a 310-bed capacity distributed across four major departments: Internal Medicine, Surgery, Paediatrics, and Gynaecology and Obstetrics. The Department of Gynaecology and Obstetrics is a high-volume tertiary center staffed by 15 consultants, 42 residents, 4 general practitioners, and 28 midwifery nurses. Clinical volume in the department is substantial, with an average of 670 deliveries per month and a caesarean section rate between 20.8% and 27.0%. The gynaecological outpatient clinics serve 300 to 350 clients monthly. Among these, infertility is a frequent clinical presentation, with approximately 16 to 20 new infertility cases managed per month, providing a robust environment for the recruitment of the study population. The study was carried out from May 30 to December 30, 2024. Study Design A facility-based case-control study was conducted at ARTH in South-East Ethiopia. The study population consisted of 135 cases (women diagnosed with infertility) and 270 controls (women with at least one child and no history of infertility), achieving a 1:2 case-to-control ratio. Population and Selection Criteria Populations The source population included all married or cohabiting women (15–49 years) attending ARTH for obstetric and gynaecologic services. Cases Married women of reproductive age (15–49) diagnosed with infertility according to the WHO criteria (failure to achieve pregnancy after 12 months of regular unprotected intercourse). Controls Married women with at least one biological child, recruited concurrently from the same facility to ensure a comparable source population. For each case, two pregnant controls (15–49 years) were recruited from the ARTH Antenatal Clinic during the same period to ensure a comparable study population. Selecting confirmed pregnant women concurrently with cases provided a definitive biological counter-example to infertility while minimizing selection and temporal bias. Inclusion and Exclusion Criteria Cases had to be diagnosed with female factor infertility; those with male-only or combined causes were excluded. Controls were excluded if their current pregnancy resulted from infertility treatment or if they had a history of infertility [ 13 , 14 ]. Sample size and Sampling Sample Size Determination : The sample size was calculated using Epi Info version 7, assuming a 1:2 case-to-control ratio, 80% power, and 95% confidence level. Based on a previous finding that menstrual flow > 3 days had an OR of 4.4 [ 13 ], the initial size was 375, adjusted to 413 to account for a 10% non-response rate (138 cases, 275 controls). Sampling Procedure : A dual sampling strategy was employed to recruit participants for this study. Selection of Cases Cases were recruited using a consecutive sampling technique. All women who met the inclusion criteria at the infertility clinic were enrolled sequentially until the pre-determined sample size was achieved. Selection of Controls Controls were selected from pregnant women attending the antenatal care (ANC) clinic using systematic random sampling. The daily appointment register served as the sampling frame. Sampling Frame (N) : The average monthly attendance at the ANC clinic was 1,460 women. Given the distribution across two separate ANC clinics, the population size per clinic was approximately 730. Sampling Interval (k) : With a required sample size (n) of 275 controls, the sampling interval was calculated as: The interval was rounded to 3 . Consequently, every third woman on the appointment list was invited to participate. Random Start : To initiate the process, the first participant was selected from the first three attendees using a lottery method (simple random start). Variables and Definitions The primary outcome was infertility status. Independent variables included socio-demographic (age, education, residency), gynaecologic (menarche age, cycle characteristics, history of procedures), and lifestyle factors, consistent with established literature [ 16 , 17 ]. Operational Definitions Infertility The inability to conceive after twelve months or more of regular unprotected sexual intercourse (2). Primary infertility A situation where couples married for at least one year have never achieved conception despite regular unprotected sexual intercourse (1). Secondary infertility Women in the reproductive age group who are unable to conceive after 1 year of unprotected intercourse following a previous pregnancy (1). Cases Married/cohabited women aged 15–49 years who failed to achieve a clinical pregnancy after 12 months or more with regular unprotected sexual intercourse (1, 14). Controls Married/cohabited women aged 15–49 years who are on their first postnatal care visit (14). Normal Semen Analysis : Defined as all parameters within the normal range: volume > 2 ml, sperm concentration ≥ 20×106 spermatozoa/ml, total sperm count ≥ 40×106 spermatozoa/ejaculate, morphology ≥ 30% normal forms, vitality ≥ 75% live, and motility ≥ 50% with forward progression (24). History of contraceptive use Use of a modern contraceptive method (COC, IUD, implants, or injectable) at least two years prior to the study (14). Uterine abnormality A female uterus that differs from the normal structure and position as identified by clinical or ultrasound exam (14). Substance use Intentional ingestion of psycho-stimulants (alcohol, khat, or cigarettes). Ever users are those who used at least once in their lifetime; current users are those who used at least once within the last 30 days (14). Body Mass Index (BMI) : Calculated as weight (kg) divided by height squared (m2). Classified as: Underweight (< 18.5), Normal (18.5–24.9), Overweight (25.0–29.9), and Obese (≥ 30.0) (24). Data Collection Procedure Data were collected through structured, face-to-face interviews conducted by trained health professionals. To ensure the highest degree of tool validity, the questionnaire was originally developed in English and subsequently translated into the local languages (Afan Oromo and Amharic) by linguistic experts. To maintain semantic consistency, an independent back-translation into English was performed. Data collection was performed by health professionals following a two-day training session focused on interview neutrality and the sensitive nature of infertility. Data Quality Assurance The instrument was pre-tested on 5% of the total sample at a facility with similar demographics to optimize logical flow and clarity. During the data management phase, a double-blind entry protocol was utilized in Epi-Data 4.6 to eliminate transcription errors, followed by a sensitivity analysis to validate the integrity of self-reported data against potential recall bias. Statistical Analysis To ensure high data quality, all questionnaires underwent a double-entry protocol into Epi-Data version 4.6, allowing for the immediate identification and correction of entry consistencies. The cleaned dataset was then exported to SPSS version 27.0 for formal analysis. Categorical and continuous variables were summarized as proportions and means, respectively. A conditional binary logistic regression was utilized to determine the effect of independent variables, a choice that directly accounts for the matching design of the study and provides a more precise estimation of associations. Variables were selected a priori based on established literature and those with a p < 0.25 in bivariate analysis were fitted into the multivariate model. Multi-collinearity was assessed using the Variance Inflation Factor (VIF), with values < 10 considered acceptable. Finally, model fitness was confirmed using the Hosmer-Lemeshow goodness-of-fit test, with statistical significance declared at a two-sided p-value of < 0.05 [ 18 ]. Methodological Rigor and Data Validation To further ensure the reliability of these statistical measures and to mitigate common data-collection risks, several rigorous validation protocols were implemented. A primary strength of this study was the use of a sensitivity analysis to proactively address potential recall bias. By comparing the responses of the full sample against a subgroup of participants who experienced the event within the previous six months, we confirmed that the findings remained stable. This validates the accuracy of the participants' memories and justifies the retention of the full dataset. Furthermore, the use of double-data entry significantly reduced the risk of human error, ensuring a clean and consistent dataset for analysis. Abbreviations ARTH Asella Referral and Teaching Hospital BMI Body Mass Index COC Combined Oral Contraceptive IUCD Intra Uterine Contraceptive Device OR Odds Ratio RR Relative Risk RTI Reproductive Tract Infection STD Sexually Transmitted Disease STI Sexually Transmitted Infection WHO World Health Organization Declarations Ethical Approval and Consent to Participate Ethical clearance for this study was granted by the Ethical Review Committee of the College of Health Sciences, Arsi University (Protocol/ID: A/CHS/RC/97/2024). The study was conducted in accordance with the Declaration of Helsinki. Prior to data collection, all participants were provided with a comprehensive explanation regarding the study's objectives, the nature of their involvement, and their right to withdraw at any stage without prejudice. Following this briefing, informed written consent was obtained from each participant. To maintain strict confidentiality and privacy, all interviews were conducted in dedicated private rooms within the hospital. Data were anonymized at the point of collection using unique identification codes, and no personal identifiers were recorded in the final dataset. Acknowledgements The authors would like to express their sincere gratitude to Arsi University and the administrative and clinical staff at Asella Referral and Teaching Hospital (ARTH) for their invaluable cooperation and logistical support during the study. Most importantly, we thank the study participants for their time, openness, and essential contribution to this research. Authors' Contributions AsD conceived the study, designed the methodology, performed data curation, and drafted the manuscript. AyD provided expertise in public health, supervised the statistical analysis, and served as the corresponding author. HT and AB provided clinical oversight in Obstetrics and Gynaecology and revised the manuscript. TG contributed to the study design, public health context, and critically reviewed the final draft. AyD, HT, TG, AB and TG performed validation and reviewed the manuscript for critical intellectual content. All authors read and approved the final manuscript. Funding This study was self-funded; no external funding was received. Data Availability Statement The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request. 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Health Transit Rev 7:205–220 Unisa S (2010) Childlessness in India: Levels, trends and determinants. Fertil Steril 94(4):S161 Abebe Y, Kondale M, Jilo GK, Hebo SH, Sidamo NB (2018) Determinants of high fertility among married women in Angacha District, Kambeta Tembero Zone. J Health Sci 10(3):46–54 Madziyire MG, Magwali TL, Chikwasha V, Mhlanga T (2021) The causes of infertility in women presenting to gynaecology clinics in Harare, Zimbabwe: a cross-sectional study. BMC Womens Health 21(1):1–8 Adamson PC, Krupp K, Freeman AH, Klausner JD, Reingold AL, Madhivanan P (2011) Prevalence and correlates of primary and secondary infertility among young women in a tertiary care center in Africa: a systematic review. Gynecol Obstet Invest 72(2):106–112 World Health Organization (2010) WHO laboratory manual for the examination and processing of human semen, 5th edn. World Health Organization, Geneva Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8917898","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":593965647,"identity":"1e72d5d4-1b2d-49d3-9fa0-672cc6828834","order_by":0,"name":"Ashenafi Degefa/AsD (MD)","email":"","orcid":"","institution":"Department of Obstetrics \u0026 Gynaecology, College of Health Sciences, Arsi University, Asella, Ethiopia","correspondingAuthor":false,"prefix":"","firstName":"Ashenafi","middleName":"","lastName":"Degefa/AsD","suffix":"MD"},{"id":593966161,"identity":"725030fd-89d8-47a4-8e29-52023552f9f5","order_by":1,"name":"Ayalneh Demissie","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEElEQVRIiWNgGAWjYHACxgMMDAcYGxiAiMGAQQ4kdOABAT0oWozBIgnEaYGARDADnxb+GckPDhdU3JHtFzvc/PFHQV36/LDDD4G22MnpNmDXInEjzeDwjDPPjGfOTmyT5jE4nLvxdpoBUEuysdkBHNbcSDA4zNt2OHHD7cQ2ZgaDA7kbZyeAtBxI3IZDi/yN9A+Hef8dTtx/OxHoMIO6dMPZ6R/wajG4kQO0pQFoi3RigwSPAXOCvHQOflsMz7wpOMxz7LDxjNsQvxhukM4pOJBggNsvcsfTNz7mqTks2z87/fHHH3/q5OVnp2/+8KHCTg6n9wUS0J0KVmmAQzkI8KObJd+AR/UoGAWjYBSMSAAAigNwE/rQXSwAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-7240-7238","institution":"Department of Public Health, College of Health Sciences, Arsi University, Asella, Ethiopia","correspondingAuthor":true,"prefix":"","firstName":"Ayalneh","middleName":"","lastName":"Demissie","suffix":""},{"id":593973757,"identity":"864fe926-79ce-4177-b320-ba3171ceeecf","order_by":2,"name":"Henok Tsegazeab/HT (MD)","email":"","orcid":"","institution":"Department of Obstetrics \u0026 Gynaecology, College of Health Sciences, Arsi University, Asella, Ethiopia","correspondingAuthor":false,"prefix":"","firstName":"Henok","middleName":"","lastName":"Tsegazeab/HT","suffix":"MD"},{"id":593974090,"identity":"65d2041f-926d-42f7-b51b-f215779d67ff","order_by":3,"name":"Tesfa Gebremeskel/TG (MD, MPH)","email":"","orcid":"","institution":"Department of Paediatrics, College of Health Sciences, Arsi University, Asella, Ethiopia","correspondingAuthor":false,"prefix":"","firstName":"","middleName":"Tesfa Gebremeskel/TG","lastName":"(MD","suffix":"MD"},{"id":593974124,"identity":"1ccc130b-cd5d-464f-aabf-7de45c5c1bc2","order_by":4,"name":"Andinet Beyene/AB (MD)","email":"","orcid":"","institution":"Department of Surgery, College of Medicine and Health Sciences, Haramaya University, Harar, Ethiopia","correspondingAuthor":false,"prefix":"","firstName":"Andinet","middleName":"","lastName":"Beyene/AB","suffix":"MD"},{"id":593974309,"identity":"8ffc4f90-291a-4a0f-9d99-9141bad8cc8d","order_by":5,"name":"Tujuma Guta (TG)","email":"","orcid":"","institution":"Department of Maternal \u0026 Child Health, Oromia Health Bureau, Addis Ababa, Ethiopia","correspondingAuthor":false,"prefix":"","firstName":"Tujuma","middleName":"Guta","lastName":"(TG)","suffix":""}],"badges":[],"createdAt":"2026-02-19 14:30:50","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8917898/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8917898/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103236460,"identity":"fabee5c4-15dc-40c7-9e43-1bb85a3d6c16","added_by":"auto","created_at":"2026-02-23 13:11:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":535742,"visible":true,"origin":"","legend":"\u003cp\u003eBar graph showing distribution of type and causes of Infertility, ARTH 2025\u003c/p\u003e","description":"","filename":"Figure1..png","url":"https://assets-eu.researchsquare.com/files/rs-8917898/v1/74243cdd903e553b8ec60b20.png"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eInfertility Predictors at Asella Referral \u0026amp; Teaching Hospital, Ethiopia: A Case-Control Study\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003ch3\u003eBackground/Rationale\u003c/h3\u003e\n\u003cp\u003eInfertility is a disease of the reproductive system defined by the failure to achieve a clinical pregnancy after 12 months or more of regular unprotected sexual intercourse [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Globally, this condition affects approximately 10% to 15% of couples, impacting at least 186\u0026nbsp;million individuals and posing a significant public health challenge [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In Sub-Saharan Africa, while some regions show high rates of primary infertility, secondary infertility is considerably more common, often as a consequence of reproductive tract infections or complications from previous obstetric care [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Within the Ethiopian context, the prevalence is estimated at 24.2%, with secondary infertility being the dominant type at 90.7% [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. For women in Ethiopia, parenthood is a vital social and personal milestone; consequently, the failure to conceive frequently leads to severe social stigma, marital instability, and mental illness [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite this profound impact, infertility is often neglected in national health policies, which typically prioritize maternal health and contraceptive services over the needs of childless couples [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This oversight has led to a shortage of specialized services and a \"silent\" epidemic of reproductive distress. Furthermore, previous local research has produced inconsistent findings regarding the primary drivers of infertility; for example, a history of sexually transmitted infections was a primary factor identified in Dessie [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], while rural residency was the focal predictor in Adama [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Such variations suggest that regional differences in lifestyle, clinical practices, and socio-economic status significantly influence reproductive outcomes.\u003c/p\u003e \u003cp\u003eAt Asella Referral and Teaching Hospital (ARTH), there is currently a critical gap in evidence-based data to explain the specific determinants affecting women in this unique catchment area. Without identifying these local factors\u0026mdash;such as the impact of prior gynaecological surgeries, age-related risks, or menstrual patterns\u0026mdash;it remains difficult for healthcare providers to develop effective prevention protocols or targeted patient counselling strategies [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. To address this gap, this study was conducted to identify the socio-demographic and clinical determinants of infertility among married women attending ARTH in 2025. By evaluating variables such as education, residency, and reproductive history through a multivariable analysis, this research aims to provide the necessary evidence to improve the quality of reproductive healthcare and guide the development of regional health interventions in South-East Ethiopia.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic characteristics of the study population, ARTH 2025\u003c/h2\u003e \u003cp\u003eThe study included 405 women (135 cases and 270 controls) aged 20\u0026ndash;42 to identify infertility risk factors. The overall mean age was 27.53\u0026thinsp;\u0026plusmn;\u0026thinsp;5.13 years. Participants were predominantly Oromo, Muslim, and married (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of the study population at ARTH, 2025\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eCases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e82.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;30 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean Age (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.63\u0026thinsp;\u0026plusmn;\u0026thinsp;4.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.97\u0026thinsp;\u0026plusmn;\u0026thinsp;5.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrthodox\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e34.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e38.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProtestant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOromo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e89.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e78.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eEducational Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Formal Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e34.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e89.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e75.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOccupation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHouse Wife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e64.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMerchant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCivil Servant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIncome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5000 Birr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e43.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;5000 Birr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e60.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e56.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidency\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e44.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e55.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eCurrent Marital Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e98.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e97.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eDuration of Marriage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026ndash;5 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e44.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e38.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBivariable and Multivariable Analysis of Determinants of Infertility among Women at ARTH, 2025 (N\u0026thinsp;=\u0026thinsp;405)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eCOR(CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAOR(CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eSocio-Demographic Factors\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e82.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;30 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e17.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1.56[0.95,2.56]*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e4.95[2.23\u0026ndash;10.95]**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Formal Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e34.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFormal education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e75.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e4.6[2.5\u0026ndash;8.5]*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e10.51[4.18\u0026ndash;26.41]*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidency\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e44.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e55.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e3.2[2.00-5.27]*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e3.22[1.60\u0026ndash;6.51]*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReproductive \u0026amp; Medical History\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at first Menses\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;14 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e39.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;14 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e60.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e2.6[1.61\u0026ndash;4.27]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e2.69[1.44\u0026ndash;4.99]**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of Menses\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 3 Days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3 Days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e77.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e0.66[0.41\u0026ndash;1.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e0.96[0.51\u0026ndash;1.82]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCyclic pain during Menses\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e67.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e32.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e3.16[2.01\u0026ndash;4.84]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e3.18[1.69\u0026ndash;5.97]*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGynecological Procedure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e4.37[2.41\u0026ndash;7.94]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e7.34(3.32\u0026ndash;16.49)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e92.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at first Marriage\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;20 Years\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;20 Years\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.29(0.85\u0026ndash;1.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e0.93(0.49\u0026ndash;1.77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEver use of contraceptive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e53.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e46.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e2.14[1.39\u0026ndash;3.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e2.21(1.19\u0026ndash;4.12)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cb\u003eNotes: AOR\u003c/b\u003e: Adjusted Odds Ratio; \u003cb\u003eCI\u003c/b\u003e: Confidence Interval; \u003cb\u003e*\u003c/b\u003e p\u0026thinsp;\u0026lt;\u0026thinsp;0.05(Significant); \u003cb\u003e**\u003c/b\u003e p\u0026thinsp;\u0026lt;\u0026thinsp;0.01(Highly Significant); \u003cb\u003e***\u003c/b\u003e p\u0026thinsp;\u0026lt;\u0026thinsp;0.001(Extremely Significant)\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eThe model was adjusted for all variables with p\u0026thinsp;\u0026lt;\u0026thinsp;0.25 in the bivariate analysis to control for potential confounders.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDistribution of type and causes of Infertility, ARTH 2025\u003c/h3\u003e\n\u003cp\u003eAmong the 135 cases, 101 (74.8%) experienced secondary infertility, while 34 (25.2%) had primary infertility (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the leading identified cause for infertility was 'unexplained' (45.3%), followed by myoma (23.3%) and tubal obstruction (16.3%\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eResults of the Multivariable Analysis\u003c/h3\u003e\n\u003cp\u003eThe bivariable and multivariable logistic regression analyses were used to identify the independent determinants of infertility among women at ARTH. Variables such as age, educational status, residency, age at menarche, cyclic menstrual pain, history of gynaecological procedures, and contraceptive use remained significant after adjusting for confounders.\u003c/p\u003e \u003cp\u003eThe study found that women aged\u0026thinsp;\u0026ge;\u0026thinsp;30 years had nearly five times higher odds of being infertile compared to those under 30 (AOR\u0026thinsp;=\u0026thinsp;4.95,95%CI:2.23\u0026ndash;10.95). Formal education showed a strong association, with educated women exhibiting 10.51 times higher odds of infertility than those with no formal education (AOR\u0026thinsp;=\u0026thinsp;10.51, 95%CI: 4.18\u0026ndash;26.41). Regarding geography, rural residents were 3.22 times more likely to be in the case group compared to urban residents (AOR\u0026thinsp;=\u0026thinsp;3.22, 95%CI: 1.60\u0026ndash;6.51).\u003c/p\u003e \u003cp\u003eIn terms of reproductive history, age at menarche\u0026thinsp;\u0026ge;\u0026thinsp;14 years (AOR\u0026thinsp;=\u0026thinsp;2.69,95%CI:1.44\u0026ndash;4.99) and cyclic menstrual pain (AOR\u0026thinsp;=\u0026thinsp;3.18,95%CI:1.69\u0026ndash;5.97) were both significant risk factors. Notably, having a history of gynaecological procedures increased the odds of infertility by over seven-fold (AOR\u0026thinsp;=\u0026thinsp;7.34, 95%CI: 3.32\u0026ndash;16.49). Finally, women who had never used contraceptives were 2.21 times more likely to face infertility compared to those who had a history of contraceptive use (AOR\u0026thinsp;=\u0026thinsp;2.21, 95%CI:1.19\u0026ndash;4.12). Factors such as duration of menses and age at first marriage did not show a statistically significant association with infertility in the final multivariable model (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings of this study at ARTH underscore a complex interplay between biological, socio-demographic, and clinical determinants, revealing a \u003cb\u003edual-natured crisis\u003c/b\u003e of infertility in the Arsi Zone.\u003c/p\u003e \u003cp\u003e \u003cb\u003eBiological and Socio-Demographic Interplay\u003c/b\u003e One of the most prominent biological findings was that women aged\u0026thinsp;\u0026ge;\u0026thinsp;30 years had five times higher odds of infertility compared to those under 30 (AOR\u0026thinsp;=\u0026thinsp;4.95). This result is consistent with studies conducted in other parts of Ethiopia, Nigeria, and Saudi Arabia [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], reinforcing the biological reality that both the quality and quantity of oocytes significantly decline as women age, particularly after the third decade of life [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInterestingly, the socio-demographic profile of the study population showed that women with \u003cb\u003eformal education\u003c/b\u003e exhibited 10.5 times higher odds of infertility. This aligns with findings in Butajira, Ethiopia, and India [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], where higher educational attainment is often associated with delayed marriage and childbearing. However, this finding contradicts results from the Kambeta region [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], suggesting that the impact of education on fertility may vary based on regional socio-cultural norms.\u003c/p\u003e \u003cp\u003eFurthermore, \u003cb\u003erural residency\u003c/b\u003e was associated with a 3.2-fold increase in infertility risk, mirroring trends seen in Adama [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and the 2023 Ethiopian Demographic and Health Survey (EDHS) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This increased risk among rural women may be linked to environmental exposures, such as pesticides in agricultural areas, or limited access to timely treatment for reproductive tract infections, which can lead to permanent tubal damage.\u003c/p\u003e \u003cp\u003e \u003cb\u003eClinical Determinants and Secondary Infertility\u003c/b\u003e, the clinical determinants identified in this study highlight the significant role of secondary factors. A \u003cb\u003ehistory of gynaecologic procedures\u003c/b\u003e was a major predictor (AOR\u0026thinsp;=\u0026thinsp;7.34), a finding similar to results reported in Dessie [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This suggests that previous invasive procedures, possibly performed in settings with varying levels of post-operative care, may result in tubal damage, pelvic adhesions, or uterine scarring [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdditionally, \u003cb\u003elate menarche\u003c/b\u003e (\u0026ge;\u0026thinsp;14 years) and \u003cb\u003ecyclic painful menses\u003c/b\u003e (AOR\u0026thinsp;=\u0026thinsp;3.18) were significant predictors, pointing toward underlying hormonal imbalances or inflammatory conditions such as endometriosis [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These clinical indicators are often symptomatic of pathologies like endometriosis, uterine fibroids, or Asherman\u0026rsquo;s syndrome, all of which can block fallopian tubes or interfere with embryo implantation. The strong association between these factors and infertility suggests that many cases at ARTH are secondary and potentially preventable through better early-stage gynaecological management.\u003c/p\u003e\n\u003ch3\u003eStrengths and Limitations\u003c/h3\u003e\n\u003cp\u003eA major strength of this study is the matched case-control design, which provided an efficient and robust framework for identifying predictors of infertility by ensuring comparability between cases and controls. The methodological rigor was further enhanced by a sensitivity analysis, which confirmed consistent findings between the total sample and a 6-month subgroup, effectively validating the accuracy of the self-reported data against recall bias. Additionally, the use of conditional multivariable logistic regression accounted for the matched study architecture, yielding statistically precise Adjusted Odds Ratios (AOR). Data integrity was further secured through double-blind entry in Epi-Data and comprehensive instrument translation protocols.\u003c/p\u003e \u003cp\u003eHowever, certain limitations must be acknowledged. Despite the validation of recall accuracy, variables such as \"travel and decision-making time\" remain inherently subjective. Furthermore, although the model was based on established literature, it may not have fully captured unique site-specific determinants. Lastly, the p\u0026thinsp;\u0026lt;\u0026thinsp;0.25 inclusion threshold for the multivariable model is a liberal approach that may include variables with a weaker influence in this specific context.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study identifies critical predictors of infertility using a robust matched case-control design. By implementing a sensitivity analysis, we have scientifically validated that these findings are not distorted by recall bias, providing a high degree of confidence in the self-reported data.\u003c/p\u003e \u003cp\u003eThe multivariable analysis revealed that clinical and socio-demographic factors play a decisive role in fertility outcomes. Notably, women with a history of gynaecologic procedures were over seven times more likely to experience infertility (AOR\u0026thinsp;=\u0026thinsp;7.34), while those with formal education showed a ten-fold increase in the odds of the outcome (AOR\u0026thinsp;=\u0026thinsp;10.51), possibly reflecting delayed childbearing or differences in health-seeking behavior. Additionally, rural residency, menarche at age 14 or older, and cyclic menstrual pain were identified as significant predictors, each more than doubling the risk.\u003c/p\u003e \u003cp\u003eBecause the model was rigorously tested for fitness (Hosmer\u0026minus;Lemeshow) and multicollinearity (VIF), these associations serve as a reliable foundation for targeted clinical interventions. These findings provide a clear roadmap for healthcare providers to prioritize early screening for women with history of gynaecological procedures and cyclic pain, particularly in rural settings. Ultimately, addressing these identified risk factors is essential for developing effective, evidence-based reproductive health strategies.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRecommendations\u003c/b\u003e \u003c/p\u003e\n\u003ch3\u003e1. Clinical Practice and Early Screening\u003c/h3\u003e\n\u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003ePrioritize Gynaecologic History\u003c/b\u003e: Given that women with a history of \u003cb\u003egynaecologic procedures\u003c/b\u003e had over seven times the odds of infertility (AOR\u0026thinsp;=\u0026thinsp;7.34), clinicians should implement rigorous post-procedure follow-ups and prioritize these patients for early fertility assessments.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003ePain Management as a Proxy\u003c/b\u003e: Healthcare providers should treat \u003cb\u003ecyclic menstrual pain\u003c/b\u003e (AOR\u0026thinsp;=\u0026thinsp;3.18) not just as a symptomatic issue, but as a clinical marker for potential underlying pathologies (such as endometriosis or PID) that may lead to infertility if left untreated.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003e2. Public Health and Policy Interventions\u003c/h3\u003e\n\u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eRural Healthcare Strengthening\u003c/b\u003e: The significant risk associated with \u003cb\u003erural residency\u003c/b\u003e (AOR\u0026thinsp;=\u0026thinsp;3.22) highlights a gap in specialized reproductive care. Policy-makers should focus on decentralizing fertility-related diagnostic services to rural health centers to ensure early detection.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eTargeted Education Programs\u003c/b\u003e: Since \u003cb\u003eformal education\u003c/b\u003e showed a ten-fold association (AOR\u0026thinsp;=\u0026thinsp;10.51), reproductive health education should be integrated into higher education curricula. This should focus on the biological impact of age (AOR\u0026thinsp;=\u0026thinsp;4.95 for age\u0026thinsp;\u0026ge;\u0026thinsp;30) and the importance of timely reproductive planning.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3. Community and Family Planning\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eCounselling on Contraception\u003c/b\u003e: The finding that \u003cb\u003eno family planning use\u003c/b\u003e doubled the odds of infertility (AOR\u0026thinsp;=\u0026thinsp;2.21) suggests a need for better community counselling. Family planning should be promoted not only for birth spacing but as a tool for maintaining overall reproductive health and preventing complications that lead to secondary infertility.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e "},{"header":"Methods","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003eStudy Setting and period\u003c/h2\u003e \u003cp\u003eThe study was conducted at Asella Referral and Teaching Hospital (ARTH), the primary clinical affiliate of Arsi University. The hospital is situated in Asella town, located approximately 175 km southeast of Ethiopia\u0026rsquo;s capital, Addis Ababa. ARTH serves as the sole referral hub for the Arsi Zone, managing a vast catchment population of approximately 3.5\u0026nbsp;million people.\u003c/p\u003e \u003cp\u003eThe hospital maintains a 310-bed capacity distributed across four major departments: Internal Medicine, Surgery, Paediatrics, and Gynaecology and Obstetrics. The Department of Gynaecology and Obstetrics is a high-volume tertiary center staffed by 15 consultants, 42 residents, 4 general practitioners, and 28 midwifery nurses.\u003c/p\u003e \u003cp\u003eClinical volume in the department is substantial, with an average of 670 deliveries per month and a caesarean section rate between 20.8% and 27.0%. The gynaecological outpatient clinics serve 300 to 350 clients monthly. Among these, infertility is a frequent clinical presentation, with approximately 16 to 20 new infertility cases managed per month, providing a robust environment for the recruitment of the study population. The study was carried out from May 30 to December 30, 2024.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eA facility-based case-control study was conducted at ARTH in South-East Ethiopia. The study population consisted of 135 cases (women diagnosed with infertility) and 270 controls (women with at least one child and no history of infertility), achieving a 1:2 case-to-control ratio.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePopulation and Selection Criteria\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003ePopulations\u003c/strong\u003e \u003cp\u003eThe source population included all married or cohabiting women (15\u0026ndash;49 years) attending ARTH for obstetric and gynaecologic services.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCases\u003c/strong\u003e \u003cp\u003eMarried women of reproductive age (15\u0026ndash;49) diagnosed with infertility according to the \u003cb\u003eWHO criteria\u003c/b\u003e (failure to achieve pregnancy after 12 months of regular unprotected intercourse).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eControls\u003c/strong\u003e \u003cp\u003eMarried women with at least one biological child, recruited concurrently from the same facility to ensure a comparable source population. For each case, two pregnant controls (15\u0026ndash;49 years) were recruited from the ARTH Antenatal Clinic during the same period to ensure a comparable study population. Selecting confirmed pregnant women concurrently with cases provided a definitive biological counter-example to infertility while minimizing selection and temporal bias.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eInclusion and Exclusion Criteria\u003c/strong\u003e \u003cp\u003eCases had to be diagnosed with female factor infertility; those with male-only or combined causes were excluded. Controls were excluded if their current pregnancy resulted from infertility treatment or if they had a history of infertility [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSample size and Sampling\u003c/h2\u003e \u003cp\u003e \u003cb\u003eSample Size Determination\u003c/b\u003e: The sample size was calculated using Epi Info version 7, assuming a 1:2 case-to-control ratio, 80% power, and 95% confidence level. Based on a previous finding that menstrual flow\u0026thinsp;\u0026gt;\u0026thinsp;3 days had an OR of 4.4 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], the initial size was 375, adjusted to 413 to account for a 10% non-response rate (138 cases, 275 controls).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSampling Procedure\u003c/b\u003e: A dual sampling strategy was employed to recruit participants for this study.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSelection of Cases\u003c/strong\u003e \u003cp\u003eCases were recruited using a consecutive sampling technique. All women who met the inclusion criteria at the infertility clinic were enrolled sequentially until the pre-determined sample size was achieved.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSelection of Controls\u003c/strong\u003e \u003cp\u003eControls were selected from pregnant women attending the antenatal care (ANC) clinic using systematic random sampling. The daily appointment register served as the sampling frame.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSampling Frame (N)\u003c/b\u003e: The average monthly attendance at the ANC clinic was 1,460 women. Given the distribution across two separate ANC clinics, the population size per clinic was approximately 730. \u003cb\u003eSampling Interval (k)\u003c/b\u003e: With a required sample size (n) of 275 controls, the sampling interval was calculated as: \u003c/p\u003e \n\u003cp\u003e\u003cimg 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\" width=\"271\" height=\"78\"\u003e\u003c/p\u003e\n\u003cp\u003eThe interval was rounded to \u003cb\u003e3\u003c/b\u003e. Consequently, every third woman on the appointment list was invited to participate. \u003cb\u003eRandom Start\u003c/b\u003e: To initiate the process, the first participant was selected from the first three attendees using a lottery method (simple random start).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eVariables and Definitions\u003c/h2\u003e \u003cp\u003eThe primary outcome was infertility status. Independent variables included socio-demographic (age, education, residency), gynaecologic (menarche age, cycle characteristics, history of procedures), and lifestyle factors, consistent with established literature [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eOperational Definitions\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eInfertility\u003c/strong\u003e \u003cp\u003eThe inability to conceive after twelve months or more of regular unprotected sexual intercourse (2).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePrimary infertility\u003c/strong\u003e \u003cp\u003eA situation where couples married for at least one year have never achieved conception despite regular unprotected sexual intercourse (1).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSecondary infertility\u003c/strong\u003e \u003cp\u003eWomen in the reproductive age group who are unable to conceive after 1 year of unprotected intercourse following a previous pregnancy (1).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCases\u003c/strong\u003e \u003cp\u003eMarried/cohabited women aged 15\u0026ndash;49 years who failed to achieve a clinical pregnancy after 12 months or more with regular unprotected sexual intercourse (1, 14).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eControls\u003c/strong\u003e \u003cp\u003eMarried/cohabited women aged 15\u0026ndash;49 years who are on their first postnatal care visit (14).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eNormal Semen Analysis\u003c/b\u003e: Defined as all parameters within the normal range: volume\u0026thinsp;\u0026gt;\u0026thinsp;2 ml, sperm concentration\u0026thinsp;\u0026ge;\u0026thinsp;20\u0026times;106 spermatozoa/ml, total sperm count\u0026thinsp;\u0026ge;\u0026thinsp;40\u0026times;106 spermatozoa/ejaculate, morphology\u0026thinsp;\u0026ge;\u0026thinsp;30% normal forms, vitality\u0026thinsp;\u0026ge;\u0026thinsp;75% live, and motility\u0026thinsp;\u0026ge;\u0026thinsp;50% with forward progression (24).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHistory of contraceptive use\u003c/strong\u003e \u003cp\u003eUse of a modern contraceptive method (COC, IUD, implants, or injectable) at least two years prior to the study (14).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eUterine abnormality\u003c/strong\u003e \u003cp\u003eA female uterus that differs from the normal structure and position as identified by clinical or ultrasound exam (14).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSubstance use\u003c/strong\u003e \u003cp\u003eIntentional ingestion of psycho-stimulants (alcohol, khat, or cigarettes). \u003cb\u003eEver users\u003c/b\u003e are those who used at least once in their lifetime; \u003cb\u003ecurrent users\u003c/b\u003e are those who used at least once within the last 30 days (14).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eBody Mass Index (BMI)\u003c/b\u003e: Calculated as weight (kg) divided by height squared (m2). Classified as: Underweight (\u0026lt;\u0026thinsp;18.5), Normal (18.5\u0026ndash;24.9), Overweight (25.0\u0026ndash;29.9), and Obese (\u0026ge;\u0026thinsp;30.0) (24).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eData Collection Procedure\u003c/h2\u003e \u003cp\u003eData were collected through structured, face-to-face interviews conducted by trained health professionals. To ensure the highest degree of tool validity, the questionnaire was originally developed in English and subsequently translated into the local languages (Afan Oromo and Amharic) by linguistic experts. To maintain semantic consistency, an independent back-translation into English was performed. Data collection was performed by health professionals following a two-day training session focused on interview neutrality and the sensitive nature of infertility.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eData Quality Assurance\u003c/h2\u003e \u003cp\u003eThe instrument was pre-tested on 5% of the total sample at a facility with similar demographics to optimize logical flow and clarity. During the data management phase, a double-blind entry protocol was utilized in Epi-Data 4.6 to eliminate transcription errors, followed by a sensitivity analysis to validate the integrity of self-reported data against potential recall bias.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eTo ensure high data quality, all questionnaires underwent a double-entry protocol into Epi-Data version 4.6, allowing for the immediate identification and correction of entry consistencies. The cleaned dataset was then exported to SPSS version 27.0 for formal analysis. Categorical and continuous variables were summarized as proportions and means, respectively. A conditional binary logistic regression was utilized to determine the effect of independent variables, a choice that directly accounts for the matching design of the study and provides a more precise estimation of associations. Variables were selected \u003cem\u003ea priori\u003c/em\u003e based on established literature and those with a p\u0026thinsp;\u0026lt;\u0026thinsp;0.25 in bivariate analysis were fitted into the multivariate model. Multi-collinearity was assessed using the Variance Inflation Factor (VIF), with values\u0026thinsp;\u0026lt;\u0026thinsp;10 considered acceptable. Finally, model fitness was confirmed using the Hosmer-Lemeshow goodness-of-fit test, with statistical significance declared at a two-sided p-value of \u0026lt;\u0026thinsp;0.05 [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eMethodological Rigor and Data Validation\u003c/h2\u003e \u003cp\u003eTo further ensure the reliability of these statistical measures and to mitigate common data-collection risks, several rigorous validation protocols were implemented. A primary strength of this study was the use of a sensitivity analysis to proactively address potential recall bias. By comparing the responses of the full sample against a subgroup of participants who experienced the event within the previous six months, we confirmed that the findings remained stable. This validates the accuracy of the participants' memories and justifies the retention of the full dataset. Furthermore, the use of double-data entry significantly reduced the risk of human error, ensuring a clean and consistent dataset for analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eARTH\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAsella Referral and Teaching Hospital\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCOC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCombined Oral Contraceptive\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIUCD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntra Uterine Contraceptive Device\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eOR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOdds Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRelative Risk\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eRTI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReproductive Tract Infection\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSTD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSexually Transmitted Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSTI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSexually Transmitted Infection\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eWHO\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical clearance for this study was granted by the Ethical Review Committee of the College of Health Sciences, Arsi University (Protocol/ID: A/CHS/RC/97/2024). The study was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003ePrior to data collection, all participants were provided with a comprehensive explanation regarding the study\u0026apos;s objectives, the nature of their involvement, and their right to withdraw at any stage without prejudice. Following this briefing, informed written consent was obtained from each participant.\u003c/p\u003e\n\u003cp\u003eTo maintain strict confidentiality and privacy, all interviews were conducted in dedicated private rooms within the hospital. Data were anonymized at the point of collection using unique identification codes, and no personal identifiers were recorded in the final dataset.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their sincere gratitude to Arsi University and the administrative and clinical staff at Asella Referral and Teaching Hospital (ARTH) for their invaluable cooperation and logistical support during the study. Most importantly, we thank the study participants for their time, openness, and essential contribution to this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; Contributions\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAsD\u003c/strong\u003e conceived the study, designed the methodology, performed data curation, and drafted the manuscript. \u003cstrong\u003eAyD\u003c/strong\u003e provided expertise in public health, supervised the statistical analysis, and served as the corresponding author. \u003cstrong\u003eHT and AB\u003c/strong\u003e provided clinical oversight in Obstetrics and Gynaecology and revised the manuscript. \u003cstrong\u003eTG\u003c/strong\u003e contributed to the study design, public health context, and critically reviewed the final draft. \u003cstrong\u003eAyD, HT, TG, AB\u003c/strong\u003e and \u003cstrong\u003eTG\u0026nbsp;\u003c/strong\u003eperformed validation and reviewed the manuscript for critical intellectual content. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study was self-funded; no external funding was received.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author upon reasonable request. All relevant data supporting the conclusions of this study are included within the manuscript and its accompanying tables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests. Arsi University provided institutional support and supervision but had no role in the study design, data collection, or the decision to submit this work for publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAkalewold M, Yohannes B, Abdo RA (2022) Determinants of infertility among couples at public hospitals in Addis Ababa, Ethiopia: a case-control study. BMC Womens Health 22(1):1\u0026ndash;10\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization (2023) Global prevalence of infertility. WHO, Geneva\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMascarenhas MN, Flaxman SR, Gladwin T, Stevens GA, Moller AB, Say L (2012) National, regional, and global trends in infertility prevalence since 1990: a systematic analysis of 277 health surveys. PLoS Med 9(12):e1001356\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoivin J, Bunting L, Collins JA, Nygren KG (2007) International estimates of infertility prevalence and help-seeking: transitions from delayed conception to infertility. Hum Reprod 22(6):1506\u0026ndash;1512\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePolis CB, Cox CM, Tun\u0026ccedil;alp \u0026Ouml;, McLain AC, Thoma ME (2017) Estimating infertility prevalence in low-to-middle-income countries: an application of a current prevalence indicator to Demographic and Health Surveys. Hum Reprod Update 23(2):167\u0026ndash;177\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRutstein SO, Shah IH (2004) \u003cem\u003eInfecundity, infertility, and childlessness in developing countries\u003c/em\u003e. DHS Comparative Reports No. 9. Calverton. ORC Macro and the World Health Organization, Maryland, USA\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCentral Statistical Agency (CSA) [Ethiopia] and ICF (2017) Ethiopia Demographic and Health Survey 2016. CSA and ICF, Addis Ababa, Ethiopia, and Rockville, Maryland, USA\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEthiopian Public Health Institute (EPHI) [Ethiopia] and ICF (2023) Ethiopia Demographic and Health Survey 2023: Key Indicators Report. Addis Ababa, Ethiopia, and Rockville, Maryland, USA: EPHI and ICF;\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDyer SJ, Abrahams N, Hoffman M, van der Spuy ZM (2004) Men leave me as I cannot have children': women's experiences with involuntary childlessness. Soc Sci Med 59(9):1931\u0026ndash;1936\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChimbatata NBW, Chimbatata C (2016) Investigating the causes of female infertility in Sub-Saharan Africa. Open J Soc Sci 4(04):290\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMekonnen W, Worku A (2011) Determinants of low family planning use and high unmet need in Butajira District, South Central Ethiopia. BMC Public Health 11(1):1\u0026ndash;8\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoridi A, Roozbeh N, Abbasi AK, Arya S, Dashti S (2019) Etiology and risk factors of infertility in Iran: a systematic review. Int J Womens Health Reprod Sci 7(2):140\u0026ndash;149\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBayu D, Dejene H, Tariku L, Mekonnen M, Abera M (2020) Determinants of infertility among women attending infertility clinic at Dessie Town public hospitals, Northeast Ethiopia: a case-control study. Int J Reprod Med 2020:1\u0026ndash;9\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbdisa R, Ambaw B, Gesit A (2022) Determinants of infertility among women attending infertility clinics in Adama Town, Central Ethiopia: a case control study. Am J Life Sci 10(4):55\u0026ndash;63\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlamri AA, Alshammari AS, Al-Saffan JA, AlAnazi AA, Al-Amri FA (2020) Determinants of female infertility in Saudi Arabia: a case-control study. Int J Med Dev Ctries 4(10):1555\u0026ndash;1561\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeklemicheal AG, Weldegebreal R, Tekleab AM (2022) Psychological distress and its associated factors among infertile women in Ethiopia: a facility-based cross-sectional study. BMC Psychol 10(1):1\u0026ndash;11\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eButajira Demographic Surveillance System (2021) \u003cem\u003eAnnual Report on Health and Demographic Trends\u003c/em\u003e. Butajira, Ethiopia: Addis Ababa University\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArsi University College of Health Sciences (2023) Institutional Health Research Ethics Review Guideline. Arsi University, Asella, Ethiopia\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOkonofua FE, Harris D, Odebiyi A, Thomas T, Snow RW (1997) The social meaning of infertility in Southwest Nigeria. Health Transit Rev 7:205\u0026ndash;220\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUnisa S (2010) Childlessness in India: Levels, trends and determinants. Fertil Steril 94(4):S161\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbebe Y, Kondale M, Jilo GK, Hebo SH, Sidamo NB (2018) Determinants of high fertility among married women in Angacha District, Kambeta Tembero Zone. J Health Sci 10(3):46\u0026ndash;54\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMadziyire MG, Magwali TL, Chikwasha V, Mhlanga T (2021) The causes of infertility in women presenting to gynaecology clinics in Harare, Zimbabwe: a cross-sectional study. BMC Womens Health 21(1):1\u0026ndash;8\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdamson PC, Krupp K, Freeman AH, Klausner JD, Reingold AL, Madhivanan P (2011) Prevalence and correlates of primary and secondary infertility among young women in a tertiary care center in Africa: a systematic review. Gynecol Obstet Invest 72(2):106\u0026ndash;112\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization (2010) WHO laboratory manual for the examination and processing of human semen, 5th edn. World Health Organization, Geneva\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Yarsi 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":"Asella Referral \u0026 Teaching Hospital, Case-control study, Ethiopia, Gynaecological procedures, Infertility, Married Women, Reproductive health, Risk Factors","lastPublishedDoi":"10.21203/rs.3.rs-8917898/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8917898/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eInfertility is a global reproductive health challenge, defined as the failure to achieve pregnancy after 12 months of regular unprotected intercourse. In Ethiopia, where motherhood is central to social identity, infertility often leads to significant social stigma and marital instability. This study aimed to identify the socio-demographic and clinical determinants of infertility among women in Asella, South-East Ethiopia.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA facility-based matched case-control study was conducted at Asella Referral and Teaching Hospital (ARTH) from May 30 to December 30, 2024. A total of 405 participants (135 cases and 270 controls) were enrolled. Data were collected via structured interviews and managed through a double-entry protocol in Epi-Data 4.6. To ensure data reliability, a sensitivity analysis was performed to assess recall bias. Data were analyzed using SPSS version 27.0. Predictors were identified using conditional multivariable logistic regression, with significance set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe mean age of participants was 27.53\u0026thinsp;\u0026plusmn;\u0026thinsp;5.13 years, with secondary infertility being the predominant type (74.8%). Multivariable analysis revealed that formal education was the strongest predictor (AOR\u0026thinsp;=\u0026thinsp;10.51; 95% CI: 4.18\u0026ndash;26.41), followed by a history of gynaecological procedures (AOR\u0026thinsp;=\u0026thinsp;7.34; 95% CI: 3.32\u0026ndash;16.49). Women aged\u0026thinsp;\u0026ge;\u0026thinsp;30 years had nearly five times higher odds of infertility (AOR\u0026thinsp;=\u0026thinsp;4.95,p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Other significant risk factors included rural residency (AOR\u0026thinsp;=\u0026thinsp;3.22), cyclic menstrual pain (AOR\u0026thinsp;=\u0026thinsp;3.18), age at menarche\u0026thinsp;\u0026ge;\u0026thinsp;14 years (AOR\u0026thinsp;=\u0026thinsp;2.69), and no prior use of family planning (AOR\u0026thinsp;=\u0026thinsp;2.21). Aged menarche\u0026thinsp;\u0026ge;\u0026thinsp;14 years (AOR\u0026thinsp;=\u0026thinsp;2.69), and no history of family planning use (AOR\u0026thinsp;=\u0026thinsp;2.21).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eInfertility in the Arsi Zone is a dual-natured crisis driven by biological aging among educated women and preventable clinical factors among rural populations. The strong association with prior gynaecological procedures and the high prevalence of secondary infertility point toward a need for improved surgical safety and post-operative care. Interventions should focus on enhancing reproductive health awareness and clinical standards in South-East Ethiopia.\u003c/p\u003e","manuscriptTitle":"Infertility Predictors at Asella Referral \u0026amp; Teaching Hospital, Ethiopia: A Case-Control Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-23 13:10:08","doi":"10.21203/rs.3.rs-8917898/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":"7546bc53-331b-49b8-a7f9-7505b3720bcd","owner":[],"postedDate":"February 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":63208352,"name":"Obstetrics \u0026 Gynecology"}],"tags":[],"updatedAt":"2026-02-23T13:10:09+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-23 13:10:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8917898","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8917898","identity":"rs-8917898","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}