Epidemiology and Sociodemographic Predictors of Infertility among Women in Ilorin, North-central Nigeria: A 5-Year Retrospective Longitudinal Study

Epidemiology and Sociodemographic Predictors of Infertility among Women in Ilorin, North-central Nigeria: A 5-Year Retrospective Longitudinal 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 Epidemiology and Sociodemographic Predictors of Infertility among Women in Ilorin, North-central Nigeria: A 5-Year Retrospective Longitudinal Study Louis Okebunor Odeigah, Beatrice Omolola Owolabi, Ismaila Aberi Obalowu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4551360/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background There are significant variations not only in the incidence and prevalence of infertility but also its sociodemographic determinants among women in Nigeria and globally. The aim of the study was to determine the incidence and prevalence of infertility among women attending the Gynaecology Clinics of the University of Ilorin Teaching Hospital over a 5-year period, and to determine the sociodemographic predictors of the type of infertility among them. Methods The study is a 5-year retrospective longitudinal study of women who attended the clinics between 2014–2018. A total of 1163 women’s patient records were eligible for the study. All collected data were analysed using SPSS™ Version 23 statistical software. The incidence rate, and the prevalence per year were calculated and presented. Logistic regression analysis was performed to determine the significant predictors of infertility type among the women. Results The calculated incidence rates of infertility during the study period ranged from 2806/ 100,000 women in 2018 to 6918/100,000 women in 2014. The prevalence of infertility during the study period ranged from 6.9% (2014) to 14.4% (2018). The calculated 5-year Cumulative Incidence (or prevalence) for the study period was 14.4%. The burden of secondary infertility cases was twice as that of primary infertility during the study period in total (71.6% vs 28.6%). Conclusions This study reported high burden of infertility and especially secondary infertility in the study area. These findings we hope will provide a foundation for further research and the development of targeted interventions to address infertility in the local context. Epidemiology Incidence Prevalence Infertility Figures Figure 1 1.0 Introduction Infertility affects an estimated 15% of couples worldwide corresponding to about 48.5 million people, and there is significant variation in the pattern and prevalence across different regions of the world. 1 Emerging data from the World Health Organization (WHO) revealed that one out of six people will experience infertility in their lifetime globally. 2 The reported pooled lifetime prevalence for infertility was 17.5% while 12.6% was reported for period prevalence of infertility worldwide. 2 In addition, while previous reports have concluded that Sub-Sahara Africa had the highest prevalence of infertility, more recent data revealed that the WHO African region have the second lowest lifetime prevalence of infertility of 13.1% compared to 16.5% and 20% reported for European and American regions respectively. 2 However, this reported lower prevalence of infertility in Africa could be as result of low quality data or inadequate available data. In Nigeria, the overall prevalence of infertility in a rural community was 30.3%, with 9.2% having primary infertility while 21.1% had secondary infertility in 1991. 3 WHO reported the prevalence of primary infertility to be 5% and that of secondary infertility to be 8% globally in 1994. 4 Later, several hospital-based studies done in Nigeria between 2011–2016 put the pooled prevalence of infertility at between 14.5–30%. 5, 6 , 7 The difference in the reported prevalence could be because of differences in methodology, period of study and study locations across geopolitical zones in Nigeria. Infertility is a complex condition with various interwoven factors and determinants. It could be because of male factors, female factors, or both. It could also be medically unexplained. Other identified risk factors globally include unhealthy lifestyle choices like smoking, consuming excessive alcohol, and being obese which could be because of bad dietary choices and sedentary lifestyle. 8 Increasing age of the couples and exposure to environmental toxins are also important aetiologic factors for both male and female infertility. 8 Sociodemographic factors like age, level of education, occupation and level of income have been widely recognized as potential determinants of not only the occurrence of infertility but also the type of infertility diagnosed. 9 , 10 This is especially important nowadays with the increasing availability of assisted reproductive techniques worldwide Infertility is associated with huge emotional and socio-economic burden for infertile Nigerian couples because of the widely held beliefs that a marriage is only seen as successful when there are resulting children and that an infertile person is incomplete. These multidimensional impacts of infertility have been proven to affect the overall quality of life of affected Nigerian couples, most especially the women. 11 The aim of this retrospective study was to determine and compare the year-on-year incidence and prevalence rates of infertility among women attending the gynaecological clinics of UITH between 2014 to 2018, and to determine the sociodemographic predictors of infertility among them. 2.0 Participants and Methods 2.1 Study Design and Participants The study was a retrospective descriptive longitudinal study of all infertility cases managed at the gynaecology clinics of UITH between 2014 and 2018. The study was conducted with a high level of confidentiality and in accordance with the Declaration of Helsinki guiding human research. The inclusion criteria were all infertility cases managed at UITH between 2014 and 2018 whose hospital records were complete and assessable during the study period. The researchers went through all 1163 eligible patients’ hospital folders with the help of the hospital records staff. The data collected include sociodemographic data, number of new infertility cases seen per year under review, total number of infertility cases seen per year under review, and total number of gynaecological cases seen per year under review. 2.2 Data analysis The collected data were exported into IBM SPSS™ version 23 software (International Business Machine Corporation, New York, USA) for analysis. Socio-demographic data were analysed and presented in a table. The year-on-year incidence and prevalence rates of infertility among the participants were calculated and presented in the same table. A clustered bar chart of the frequency and type of infertility among the participants was generated and presented in a figure. The sociodemographic predictors of the type of infertility among the participants was analysed and presented in tables. 2.30 Declarations 2.31 Ethics approval and consent to participate The approval to conduct the study was received from the Ethical Review Committee (ERC) of UITH with approval number ERC PAN/2022/12/0336. The study was a retrospective one with no direct interaction with human subjects so there was no need for a written informed consent to participate in the study. The ethical approval is all that is required. 2.32 Consent for publication The consent for publication of the research findings is embedded in the ethical approval received from the institution’s ERC. All potential identifiers like the names and the hospital numbers of the patients were not recorded in the captured data. 2.33 Availability of data and materials All the data presented in this work and other supportive data are available upon request from the corresponding author. 2.34 Competing interests All authors declared no conflict of interests for this study. 2.35 Funding declaration We declared that the authors did not receive funding for this research except their personal contributions. 2.36 Authors' contributions 1. Odeigah LO: Conceptualization of the research ideas and design, expert review of the manuscript. 2. Owolabi BO: Literature review, data collection, manuscript writing. 3. Obalowu IA: Data collection, data analysis, manuscript writing. 4. Mutalub YB: Data analysis, manuscript writing, and review. 5. Agede OA: Manuscript writing and review 6. Jimoh AAG: Expert review of the final manuscript. 2.37 Acknowledgements The authors acknowledged the efforts of Dr. Azi-scot, Dr. Abbey, Dr. Olumorin, Dr. Olapade, Dr. Abimbola, and Dr. Akinola in getting the data used for this study. We also appreciate all the staff of the Obstetrics and Gynecology, and the Medical Records Departments of the University of Ilorin Teaching Hospital for their support in carrying out this study. 3.0 Results 3.10 Sociodemographic characteristics of the participants The mean age of the participants was 32.8 ± 6 years. More than half of participants were ≥ 30 years of age (57.4%) and had tertiary level of education (52.3%). Most of the women were working actively (80.5%) and were married into monogamous family setting (81.2%). Surprisingly, only very few of them had a documented family history of infertility in first degree relatives (1.3%). The results are presented in Table 1. 3.20 Yearly Incidence Rates and Prevalence of Infertility among the Participants The calculated incidence rates of infertility during the study period ranged from 2806/ 100,000 women in 2018 to 6918/100,000 persons in 2014. The prevalence of infertility during the study period ranged from 6.9% (2014) to 14.4% (2018). The calculated 5-year cumulative incidence (or prevalence) for the study period was 14.4%. The results are presented in Table 2. 3.30 Pattern of Infertility During the Study Period Most cases of secondary infertility were seen in 2014 (n = 212), while most cases of primary infertility were seen in 2016 (n = 117). Majority of the total infertility cases seen were secondary (n = 833, 71.6%). The results are displayed in a clustered bar chart in Figure 1. 3.40 Association between Sociodemographic Characteristics of the Participants and their Infertility Type The following sociodemographic characteristics were found to have statistically significant associations with the type of infertility experienced by the participants. Those who were ≥ 30 years of age (74%, X 2 = 4.182, P = 0.041), those who had less than tertiary education, and those who were married in the polygamous marriage setting all had higher percentages of having secondary infertility (72.4%, X 2 = 5.448, P = 0.020 and 80.8%, X 2 = 9.092, P = 0.003 respectively). The results are presented in Table 3. 3.5 Sociodemographic Predictors of Infertility Type among the Participants Only marital type remained statistically significant predictor of type of infertility experienced among the participants after confounder analysis (r = 0.434, Odds ratio = 1.5, P = 0.033). The results are presented in Table 4. Table 1: Sociodemographic Profile of the Participants Table 2: Yearly Incidence and Prevalence of Infertility among the Participants Figure 1: A Clustered Bar chart showing the Pattern of Infertility among the Participants During the Study Period Table 3: Association between Sociodemographic Characteristics of the Participants and their Infertility Type Table 4: Sociodemographic Determinants of Infertility Type among the Participants 4.0 Discussion Infertility is a complex and multifaceted reproductive health issue that warrants a thorough exploration of its epidemiology and sociodemographic predictors. Our study aimed to provide insights into the incidence, prevalence, and sociodemographic predictors of infertility among women attending the Gynaecologic Clinics of the University of Ilorin Teaching Hospital over a 5-year period. The mean age of the infertile women studied was 32.8 ± 6 years and more than half of them were ≥ 30 years old. These findings are higher but comparable to that reported by Panti et al in their study among infertile women in Sokoto, North-west Nigeria, where they reported mean age of 28.9 ± 6.5 years, and that higher percentage of their participants were < 30 years of age. 6 Age is one of the most important determinants of fertility, as increasing age during the reproductive years tends to decrease fertility in both women and men due to aging of the reproductive organs. Considering the level of education of the participants, more than half of them had at least tertiary education which reflects the increasing level of female education in Ilorin, North-central Nigeria. It might also be argued that the percentage of women with tertiary level of education in infertile women was greater than that of the general population put at 40.2% in 2011. 12 Furthermore, it is not surprising that most (80.5%) of the participants were working actively during the study period given the mean age of the participants. This might also be linked to the development of infertility in them as shown by Okpala et al, in Lagos Nigeria. They reported that civil servants were more likely to develop infertility due to work demands, and that increasing number of work years and daily hours of work negatively affect fertility. 13 They also reported that the number of children ever born was significantly higher in unemployed housewives compared to actively working civil servants. 13 Family history of infertility risk assessment is an important tool in counselling the couples about their genetic risks prior to pregnancy. 14 For some couples it might also provide information about the causes of their infertility. 14 For this study, only 1.3% of the participants had a documented family history of infertility in their first-degree relatives which align with the fact that genetics have limited aetiological role in infertility. 15 Only approximately 10 to 15 percent of infertility cases are reported to be due to a known inherited cause. 15 Year on year comparison of the prevalence and incidence rates during the study period revealed that there was 52.1% increase in the prevalence of infertility from 6.9% in 2014 to 14.4% in 2018. Similarly, the incidence rates also increased by 59.4% from 2806/100,000 women in 2014 to 6918/100,000 women in 2018. The 5-year cumulative incidence (incidence proportion) and the 5-year overall prevalence of infertility in the study was 14.4%. This value is similar to prevalence of infertility reported in other Nigerian studies. 6 , 16 , 17 It is also within the 5–23% prevalence of infertility range reported in Sub-Saharan Africa, and the 3.5–16.7% reported by Boivin et al, from review of 25 population surveys globally. 18 , 19 Our findings align with previous studies in Nigeria, indicating that about twice number of infertile women experienced secondary rather than primary infertility, emphasizing the need for targeted interventions and support for this specific subgroup. 5 , 6 , 20 The 71.6% prevalence of secondary infertility and 28.4% of primary infertility recorded over the 5-year period of this study done in North-central Nigeria is exactly the same prevalence reported by Menuba et al, in their multi-centred prospective cross-sectional study in South-eastern Nigeira. 20 The most commonly reported aetiological factor of secondary infertility in Nigerian women is chronic pelvic inflammatory disease which when comprehensively treated and managed would lead to reduction in the incidence of secondary infertility in the country. 21 , 22 Statistically significant sociodemographic factors found to have higher association with the development of secondary infertility in the participants in this study were higher age (≥ 30 years, P = 0.041), less than tertiary education status (P = 0.020) and being married in a polygamous marriage setting (P = 0.003). These findings are similar to those reported by Oguejiofor et al in Nnewi, South-eastern Nigeria. 23 They reported in their 5-year retrospective study that most of their participants had secondary infertility, were older than 30 years, and had less than tertiary education. 23 Further analysis in this study revealed that only being married in a polygamous setting remained significant determinant of secondary infertility in the study population. This could be explained by the affected women having regular sexual intercourse with men that have other wives which might increase the risk of pelvic inflammatory disease and tubal blockage in them. It might also be because more older women tend to marry into a polygamous marriage setting out of desperation to get a partner compared to younger women in the study population which might reduce their fertility. Egbe et al, in their paper on risk factors for tubal infertility reported that, young age, persons in monogamous marriages and users of barrier methods of contraception (condom) were less likely to have tubal infertility. 24 Also, a large population survey in West Africa revealed that there was no significant difference in fertility rates between women in polygamous unions and those in monogamous households in almost all countries studied. 25 This emphasizes that the predictability of polygamous marriage for secondary infertility does not include all cases of infertility. Understanding the epidemiology and sociodemographic predictors of infertility is pivotal for designing targeted interventions and support systems for the affected women. The high prevalence of secondary infertility underscores the importance of investigating underlying causes and implementing preventive strategies. Moreover, addressing age-related factors and considering sociodemographic characteristics can enhance the effectiveness of reproductive health programs in the study population. Despite the valuable data generated from this study, the study has some limitations, including that it is a single-centred hospital-based study, the fact that it is a retrospective study also meant that we were limited to only the documented information and available manual records. We suggest that future research should involve diverse populations and explore additional sociodemographic factors contributing to epidemiology of infertility in Nigeria. In conclusion, our study contributes valuable data on the epidemiology and sociodemographic predictors of infertility among women attending the Gynaecology Clinics of the University of Ilorin Teaching Hospital. These findings we hope will provide a foundation for further research and the development of targeted interventions to address infertility in the local context. Declarations Author Contribution 1. OLO: Conceptualization of the research ideas and design, expert review of the manuscript.2. OBO: Literature review, data collection, manuscript writing.3. OIA: Data collection, data analysis, manuscript writing.4. MBY: Data analysis, manuscript writing, and review. 5. AOA: Manuscript writing and review6. JAAG: Expert review of the final manuscript. Acknowledgement The authors acknowledged the efforts of Dr. Azi-scot, Dr. Abbey, Dr. Olumorin, Dr. Olapade, Dr. Abimbola, and Dr. Akinola in getting the data used for this study. We also appreciate all the staff of the Obstetrics and Gynecology, and the Medical Records Departments of the University of Ilorin Teaching Hospital for their support in carrying out this study. Data Availability All relevant data used in this study are available in the manuscript, request for more supporting data should be directed to the corresponding author. References Agarwal A, Mulgund A, Hamada A, Chyatte MR. A unique view on male infertility around the globe. Reprod Biol Endocrinol. 2015;26:13–37. 10.1186/s12958-015-0032-1 . WHO. Infertility prevalence estimates, 1990–2021. Geneva: World Health Organization; 2023. Adetoro OO, Ebomoyi EW. The prevalence of infertility in a rural Nigerian community. Afr J Med Med Sci. 1991;20(1):23–7. Khanna J, van Look PF, Griffin PD. United Nations Fund for Population Activities. Challenges in reproductive health research: biennial report: 1992–1993. World Health Organization; 1994. Dattijo LM, Andreadis N, Aminu BM, Umar NI, Black KI. The prevalence and clinical pattern of infertility in Bauchi, northern Nigeria. Trop J Obstet Gynecol. 2016;33(1):76–85. Panti AA, Sununu YT. The profile of infertility in a teaching Hospital in North West Nigeria. Sahel Med J. 2014;17(1):7. Omoaregba JO, James BO, Lawani AO, Morakinyo O, Olotu OS. Psychosocial characteristics of female infertility in a tertiary health institution in Nigeria. Ann Afr Med. 2011;10(1):19–24. 10.4103/1596-3519.76567 . WHO, Infertility. http;//www.who.int.news-room/fact-sheets/detail/infertility . Accessed on 8/6/2024. Sarkar S, Gupta P. Socio-Demographic Correlates of Women's Infertility and Treatment Seeking Behavior in India. J Reprod Infertil. 2016;17(2):123–32. Ho JR, Hoffman JR, Aghajanova L, Smith JF, Cardenas M, Herndon CN. Demographic analysis of a low resource, socioculturally diverse urban community presenting for infertility care in a United States public hospital. Contracept Reprod Med. 2017;2:17. https://doi.org/10.1186/s40834-017-0044-7 . Esan DT, Nnamani KQ, Ogunkorode A, Muhammad F, Oluwagbemi OO, Ramos CG. Infertility affects the quality of life of Southwestern Nigerian women and their partners. Int J Afr Nurs Sci. 2022;17. https://doi.org/10.1016/j.ijans.2022.100506 . World Data Atlas. Nigeria - Female students in tertiary education. https://knoema.com/atlas/Nigeria/topics/Education/Tertiary-Education/Female-students-in-tertiary-education . Accessed on 8/6/2024. Okpala AO. Female employment and family size among urban Nigerian women. J Dev Areas. 1989;23(3):439–56. Vance A, Zouves C. The Importance of family history risk assessment in the infertility setting. https://www.fertstert.org/aticle/S0015-0282(05)01764-4/fulltext . Accessed on 8/6/2024. Genome Medical. Is infertility genetic? https://www.genomemedical.com/genetic-testing-pregnancy/is-infertility-genetic/ . Accessed on 8/6/2024. Obuna JA, Ndukwe EO, Ugboma HA, Ejikeme BN, Ugboma EW. Clinical presentation of infertility in an outpatient clinic of a resource poor setting, South-east Nigeria. Int J Trop Disease Health. 2012;2:123–31. Yusuf M, Abdullahi HM. Epidemiology of infertilty in Kano, North-west Nigeria. https://ibommedicaljournal.org/index.php/imjhome/article/view/215/429 . Accessed on 8/6/2024. Larsen U. Primary and secondary infertility in sub-Saharan Africa. Int J Epidemiol. 2000;29(2):285–91. https://doi.org/10.1093/ije/29.2.285 . Boivin J, Bunting L, Collins JA, Nygren KG. International estimates of infertility prevalence and treatment-seeking: potential need and demand for infertility medical care. Hum Reprod. 2007;22(6):1506–12. https://doi.org/10.1093/humrep/dem046 . Menuba IE, Ugwu EO, Obi SN, Lawani LO, Onwuka CI. Clinical management and therapeutic outcome of infertile couples in southeast Nigeria. Ther Clin Risk Manag. 2014;1(10):763–8. 10.2147/TCRM.S68726 . Adegbola O, Akindele MO. The pattern and challenges of infertility management in Lagos, Nigeria. Afr Health Sci. 2013;13(4):1126–9. 10.4314/ahs.v13i4.37 . Oranu EO, Oyiana GI. Secondary infertility in Port Harcourt: pattern and socio-dermographic relationship. Asian J Med Health. 2011;19(11):66–74. https://doi.org/10.9734/ajmah/2021/v19i1130402 . Oguejiofor CB, Obi NC, Okafor OC, Eleje GU, Okafor CG, Nkesi JC, et al. A 5-Year Retrospective Cross-Sectional of The Pattern of Infertility in Nnamdi Azikiwe University Teaching Hospital, Nnewi, Nigeria. Gynecol Obstet Open. 2023;166(7). https://doi.org/10.29011/2577-2236.100166 . Egbe TO, Nana-Njamen T, Elong F, Tchounzou R, Simo AG, Nzeuga GP, et al. Risk factors of tubal infertility in a tertiary hospital in a low-resource setting: a case-control study. Fertil Res Pract. 2020;6(6):3. 10.1186/s40738-020-00073-4 . Millogo R, Labite JM, Greenbaum C. Many women in West Africa are in polygamous marriages, but the unique needs and preferences of this group are not well understood. https://www.prb.org/resources/polygamy-in-west-africa-impacts-on-fertility-fertility-intentions-and-family-planning/ . Accessed on 8/6/2024. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 05 Jul, 2024 Editor assigned by journal 04 Jul, 2024 Submission checks completed at journal 04 Jul, 2024 First submitted to journal 08 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4551360","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":323089099,"identity":"bb7b6840-5cfe-4727-a834-3a155b9cfbfb","order_by":0,"name":"Louis Okebunor Odeigah","email":"","orcid":"","institution":"Afe Babalola University","correspondingAuthor":false,"prefix":"","firstName":"Louis","middleName":"Okebunor","lastName":"Odeigah","suffix":""},{"id":323089102,"identity":"9ddcdc68-7fe4-4a7e-b670-a4b2805d8748","order_by":1,"name":"Beatrice Omolola Owolabi","email":"","orcid":"","institution":"University of Ilorin Teaching 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significant variation in the pattern and prevalence across different regions of the world.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Emerging data from the World Health Organization (WHO) revealed that one out of six people will experience infertility in their lifetime globally.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e The reported pooled lifetime prevalence for infertility was 17.5% while 12.6% was reported for period prevalence of infertility worldwide.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e In addition, while previous reports have concluded that Sub-Sahara Africa had the highest prevalence of infertility, more recent data revealed that the WHO African region have the second lowest lifetime prevalence of infertility of 13.1% compared to 16.5% and 20% reported for European and American regions respectively.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e However, this reported lower prevalence of infertility in Africa could be as result of low quality data or inadequate available data.\u003c/p\u003e \u003cp\u003eIn Nigeria, the overall prevalence of infertility in a rural community was 30.3%, with 9.2% having primary infertility while 21.1% had secondary infertility in 1991.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e WHO reported the prevalence of primary infertility to be 5% and that of secondary infertility to be 8% globally in 1994.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Later, several hospital-based studies done in Nigeria between 2011\u0026ndash;2016 put the pooled prevalence of infertility at between 14.5\u0026ndash;30%.\u003csup\u003e5, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e ,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e The difference in the reported prevalence could be because of differences in methodology, period of study and study locations across geopolitical zones in Nigeria.\u003c/p\u003e \u003cp\u003eInfertility is a complex condition with various interwoven factors and determinants. It could be because of male factors, female factors, or both. It could also be medically unexplained. Other identified risk factors globally include unhealthy lifestyle choices like smoking, consuming excessive alcohol, and being obese which could be because of bad dietary choices and sedentary lifestyle.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Increasing age of the couples and exposure to environmental toxins are also important aetiologic factors for both male and female infertility.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Sociodemographic factors like age, level of education, occupation and level of income have been widely recognized as potential determinants of not only the occurrence of infertility but also the type of infertility diagnosed.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e This is especially important nowadays with the increasing availability of assisted reproductive techniques worldwide\u003c/p\u003e \u003cp\u003eInfertility is associated with huge emotional and socio-economic burden for infertile Nigerian couples because of the widely held beliefs that a marriage is only seen as successful when there are resulting children and that an infertile person is incomplete. These multidimensional impacts of infertility have been proven to affect the overall quality of life of affected Nigerian couples, most especially the women.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e The aim of this retrospective study was to determine and compare the year-on-year incidence and prevalence rates of infertility among women attending the gynaecological clinics of UITH between 2014 to 2018, and to determine the sociodemographic predictors of infertility among them.\u003c/p\u003e"},{"header":"2.0 Participants and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Study Design and Participants\u003c/h2\u003e\n \u003cp\u003eThe study was a retrospective descriptive longitudinal study of all infertility cases managed at the gynaecology clinics of UITH between 2014 and 2018. The study was conducted with a high level of confidentiality and in accordance with the Declaration of Helsinki guiding human research. The inclusion criteria were all infertility cases managed at UITH between 2014 and 2018 whose hospital records were complete and assessable during the study period. The researchers went through all 1163 eligible patients\u0026rsquo; hospital folders with the help of the hospital records staff. The data collected include sociodemographic data, number of new infertility cases seen per year under review, total number of infertility cases seen per year under review, and total number of gynaecological cases seen per year under review.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Data analysis\u003c/h2\u003e\n \u003cp\u003eThe collected data were exported into IBM SPSS\u0026trade; version 23 software (International Business Machine Corporation, New York, USA) for analysis. Socio-demographic data were analysed and presented in a table. The year-on-year incidence and prevalence rates of infertility among the participants were calculated and presented in the same table. A clustered bar chart of the frequency and type of infertility among the participants was generated and presented in a figure. The sociodemographic predictors of the type of infertility among the participants was analysed and presented in tables.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.30 Declarations\u003c/h2\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.31 Ethics approval and consent to participate\u003c/h2\u003e\n \u003cp\u003eThe approval to conduct the study was received from the Ethical Review Committee (ERC) of UITH with approval number ERC PAN/2022/12/0336. The study was a retrospective one with no direct interaction with human subjects so there was no need for a written informed consent to participate in the study. The ethical approval is all that is required.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.32 Consent for publication\u003c/h2\u003e\n \u003cp\u003eThe consent for publication of the research findings is embedded in the ethical approval received from the institution\u0026rsquo;s ERC. All potential identifiers like the names and the hospital numbers of the patients were not recorded in the captured data.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e2.33 Availability of data and materials\u003c/h2\u003e\n \u003cp\u003eAll the data presented in this work and other supportive data are available upon request from the corresponding author.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e2.34 Competing interests\u003c/h2\u003e\n \u003cp\u003eAll authors declared no conflict of interests for this study.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e2.35 Funding declaration\u003c/h2\u003e\n \u003cp\u003eWe declared that the authors did not receive funding for this research except their personal contributions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e2.36 Authors\u0026apos; contributions\u003c/h2\u003e\u003cspan\u003e\n \u003cp\u003e1. Odeigah LO: Conceptualization of the research ideas and design, expert review of the manuscript.\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e2. Owolabi BO: Literature review, data collection, manuscript writing.\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e3. Obalowu IA: Data collection, data analysis, manuscript writing.\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e4. Mutalub YB: Data analysis, manuscript writing, and review.\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e5. Agede OA: Manuscript writing and review\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e6. Jimoh AAG: Expert review of the final manuscript.\u003c/p\u003e\n \u003c/span\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e2.37 Acknowledgements\u003c/h2\u003e\n \u003cp\u003eThe authors acknowledged the efforts of Dr. Azi-scot, Dr. Abbey, Dr. Olumorin, Dr. Olapade, Dr. Abimbola, and Dr. Akinola in getting the data used for this study. We also appreciate all the staff of the Obstetrics and Gynecology, and the Medical Records Departments of the University of Ilorin Teaching Hospital for their support in carrying out this study.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3.0 Results ","content":"\u003cp\u003e\u003cstrong\u003e3.10 Sociodemographic characteristics of the participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean age of the participants was 32.8 \u0026plusmn; 6 years. More than half of participants were \u0026ge; 30 years of age (57.4%) and had tertiary level of education (52.3%). Most of the women were working actively (80.5%) and were married into monogamous family setting (81.2%). Surprisingly, only very few of them had a documented family history of infertility in first degree relatives (1.3%). The results are presented in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.20\u003c/strong\u003e \u003cstrong\u003eYearly Incidence Rates and Prevalence of Infertility among the Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe calculated incidence rates of infertility during the study period ranged from 2806/ 100,000 women in 2018 to 6918/100,000 persons in 2014. The prevalence of infertility during the study period ranged from 6.9% (2014) to 14.4% (2018). The calculated 5-year cumulative incidence (or prevalence) for the study period was 14.4%. The results are presented in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.30 Pattern of Infertility During the Study Period\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMost cases of secondary infertility were seen in 2014 (n = 212), while most cases of primary infertility were seen in 2016 (n = 117). Majority of the total infertility cases seen were secondary (n = 833, 71.6%). The results are displayed in a clustered bar chart in Figure 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.40\u003c/strong\u003e \u003cstrong\u003eAssociation between Sociodemographic Characteristics of the Participants and their Infertility Type\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following sociodemographic characteristics were found to have statistically significant associations with the type of infertility experienced by the participants. Those who were \u0026ge; 30 years of age (74%, X\u003csup\u003e2\u003c/sup\u003e = 4.182, P = 0.041), those who had less than tertiary education, and those who were married in the polygamous marriage setting all had higher percentages of having secondary infertility (72.4%, X\u003csup\u003e2\u003c/sup\u003e = 5.448, P = 0.020 and 80.8%, X\u003csup\u003e2\u003c/sup\u003e = 9.092, P = 0.003 respectively). The results are presented in Table 3. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003e3.5\u003c/strong\u003e \u003cstrong\u003eSociodemographic Predictors of Infertility Type among the Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOnly marital type remained statistically significant predictor of type of infertility experienced among the participants after confounder analysis (r = 0.434, Odds ratio = 1.5, P = 0.033). The results are presented in Table 4.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Sociodemographic Profile of the Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Yearly Incidence and Prevalence of Infertility among the Participants \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 1: A Clustered Bar chart showing the Pattern of Infertility among the Participants During the Study Period\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Association between Sociodemographic Characteristics of the Participants and their Infertility Type\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: Sociodemographic Determinants of Infertility Type among the Participants\u003c/strong\u003e\u003c/p\u003e"},{"header":"4.0 Discussion","content":"\u003cp\u003eInfertility is a complex and multifaceted reproductive health issue that warrants a thorough exploration of its epidemiology and sociodemographic predictors. Our study aimed to provide insights into the incidence, prevalence, and sociodemographic predictors of infertility among women attending the Gynaecologic Clinics of the University of Ilorin Teaching Hospital over a 5-year period.\u003c/p\u003e \u003cp\u003eThe mean age of the infertile women studied was 32.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6 years and more than half of them were \u0026ge;\u0026thinsp;30 years old. These findings are higher but comparable to that reported by Panti et al in their study among infertile women in Sokoto, North-west Nigeria, where they reported mean age of 28.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5 years, and that higher percentage of their participants were \u0026lt;\u0026thinsp;30 years of age.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Age is one of the most important determinants of fertility, as increasing age during the reproductive years tends to decrease fertility in both women and men due to aging of the reproductive organs. Considering the level of education of the participants, more than half of them had at least tertiary education which reflects the increasing level of female education in Ilorin, North-central Nigeria. It might also be argued that the percentage of women with tertiary level of education in infertile women was greater than that of the general population put at 40.2% in 2011.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFurthermore, it is not surprising that most (80.5%) of the participants were working actively during the study period given the mean age of the participants. This might also be linked to the development of infertility in them as shown by Okpala et al, in Lagos Nigeria. They reported that civil servants were more likely to develop infertility due to work demands, and that increasing number of work years and daily hours of work negatively affect fertility.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e They also reported that the number of children ever born was significantly higher in unemployed housewives compared to actively working civil servants.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFamily history of infertility risk assessment is an important tool in counselling the couples about their genetic risks prior to pregnancy.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e For some couples it might also provide information about the causes of their infertility.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e For this study, only 1.3% of the participants had a documented family history of infertility in their first-degree relatives which align with the fact that genetics have limited aetiological role in infertility.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e Only approximately 10 to 15 percent of infertility cases are reported to be due to a known inherited cause.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eYear on year comparison of the prevalence and incidence rates during the study period revealed that there was 52.1% increase in the prevalence of infertility from 6.9% in 2014 to 14.4% in 2018. Similarly, the incidence rates also increased by 59.4% from 2806/100,000 women in 2014 to 6918/100,000 women in 2018. The 5-year cumulative incidence (incidence proportion) and the 5-year overall prevalence of infertility in the study was 14.4%. This value is similar to prevalence of infertility reported in other Nigerian studies.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e It is also within the 5\u0026ndash;23% prevalence of infertility range reported in Sub-Saharan Africa, and the 3.5\u0026ndash;16.7% reported by Boivin et al, from review of 25 population surveys globally.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOur findings align with previous studies in Nigeria, indicating that about twice number of infertile women experienced secondary rather than primary infertility, emphasizing the need for targeted interventions and support for this specific subgroup.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e The 71.6% prevalence of secondary infertility and 28.4% of primary infertility recorded over the 5-year period of this study done in North-central Nigeria is exactly the same prevalence reported by Menuba et al, in their multi-centred prospective cross-sectional study in South-eastern Nigeira.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e The most commonly reported aetiological factor of secondary infertility in Nigerian women is chronic pelvic inflammatory disease which when comprehensively treated and managed would lead to reduction in the incidence of secondary infertility in the country.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eStatistically significant sociodemographic factors found to have higher association with the development of secondary infertility in the participants in this study were higher age (\u0026ge;\u0026thinsp;30 years, P\u0026thinsp;=\u0026thinsp;0.041), less than tertiary education status (P\u0026thinsp;=\u0026thinsp;0.020) and being married in a polygamous marriage setting (P\u0026thinsp;=\u0026thinsp;0.003). These findings are similar to those reported by Oguejiofor et al in Nnewi, South-eastern Nigeria.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e They reported in their 5-year retrospective study that most of their participants had secondary infertility, were older than 30 years, and had less than tertiary education.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e Further analysis in this study revealed that only being married in a polygamous setting remained significant determinant of secondary infertility in the study population. This could be explained by the affected women having regular sexual intercourse with men that have other wives which might increase the risk of pelvic inflammatory disease and tubal blockage in them. It might also be because more older women tend to marry into a polygamous marriage setting out of desperation to get a partner compared to younger women in the study population which might reduce their fertility. Egbe et al, in their paper on risk factors for tubal infertility reported that, young age, persons in monogamous marriages and users of barrier methods of contraception (condom) were less likely to have tubal infertility.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Also, a large population survey in West Africa revealed that there was no significant difference in fertility rates between women in polygamous unions and those in monogamous households in almost all countries studied.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e This emphasizes that the predictability of polygamous marriage for secondary infertility does not include all cases of infertility.\u003c/p\u003e \u003cp\u003eUnderstanding the epidemiology and sociodemographic predictors of infertility is pivotal for designing targeted interventions and support systems for the affected women. The high prevalence of secondary infertility underscores the importance of investigating underlying causes and implementing preventive strategies. Moreover, addressing age-related factors and considering sociodemographic characteristics can enhance the effectiveness of reproductive health programs in the study population.\u003c/p\u003e \u003cp\u003eDespite the valuable data generated from this study, the study has some limitations, including that it is a single-centred hospital-based study, the fact that it is a retrospective study also meant that we were limited to only the documented information and available manual records. We suggest that future research should involve diverse populations and explore additional sociodemographic factors contributing to epidemiology of infertility in Nigeria.\u003c/p\u003e \u003cp\u003eIn conclusion, our study contributes valuable data on the epidemiology and sociodemographic predictors of infertility among women attending the Gynaecology Clinics of the University of Ilorin Teaching Hospital. These findings we hope will provide a foundation for further research and the development of targeted interventions to address infertility in the local context.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003e1. OLO: Conceptualization of the research ideas and design, expert review of the manuscript.2. OBO: Literature review, data collection, manuscript writing.3. OIA: Data collection, data analysis, manuscript writing.4. MBY: Data analysis, manuscript writing, and review. 5. AOA: Manuscript writing and review6. JAAG: Expert review of the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors acknowledged the efforts of Dr. Azi-scot, Dr. Abbey, Dr. Olumorin, Dr. Olapade, Dr. Abimbola, and Dr. Akinola in getting the data used for this study. We also appreciate all the staff of the Obstetrics and Gynecology, and the Medical Records Departments of the University of Ilorin Teaching Hospital for their support in carrying out this study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll relevant data used in this study are available in the manuscript, request for more supporting data should be directed to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAgarwal A, Mulgund A, Hamada A, Chyatte MR. A unique view on male infertility around the globe. Reprod Biol Endocrinol. 2015;26:13\u0026ndash;37. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12958-015-0032-1\u003c/span\u003e\u003cspan address=\"10.1186/s12958-015-0032-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO. Infertility prevalence estimates, 1990\u0026ndash;2021. Geneva: World Health Organization; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdetoro OO, Ebomoyi EW. The prevalence of infertility in a rural Nigerian community. Afr J Med Med Sci. 1991;20(1):23\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhanna J, van Look PF, Griffin PD. United Nations Fund for Population Activities. Challenges in reproductive health research: biennial report: 1992\u0026ndash;1993. 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Many women in West Africa are in polygamous marriages, but the unique needs and preferences of this group are not well understood. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.prb.org/resources/polygamy-in-west-africa-impacts-on-fertility-fertility-intentions-and-family-planning/\u003c/span\u003e\u003cspan address=\"https://www.prb.org/resources/polygamy-in-west-africa-impacts-on-fertility-fertility-intentions-and-family-planning/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed on 8/6/2024.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Epidemiology, Incidence, Prevalence, Infertility","lastPublishedDoi":"10.21203/rs.3.rs-4551360/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4551360/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThere are significant variations not only in the incidence and prevalence of infertility but also its sociodemographic determinants among women in Nigeria and globally. The aim of the study was to determine the incidence and prevalence of infertility among women attending the Gynaecology Clinics of the University of Ilorin Teaching Hospital over a 5-year period, and to determine the sociodemographic predictors of the type of infertility among them.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe study is a 5-year retrospective longitudinal study of women who attended the clinics between 2014\u0026ndash;2018. A total of 1163 women\u0026rsquo;s patient records were eligible for the study. All collected data were analysed using SPSS\u0026trade; Version 23 statistical software. The incidence rate, and the prevalence per year were calculated and presented. Logistic regression analysis was performed to determine the significant predictors of infertility type among the women.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe calculated incidence rates of infertility during the study period ranged from 2806/ 100,000 women in 2018 to 6918/100,000 women in 2014. The prevalence of infertility during the study period ranged from 6.9% (2014) to 14.4% (2018). The calculated 5-year Cumulative Incidence (or prevalence) for the study period was 14.4%. The burden of secondary infertility cases was twice as that of primary infertility during the study period in total (71.6% vs 28.6%).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study reported high burden of infertility and especially secondary infertility in the study area. These findings we hope will provide a foundation for further research and the development of targeted interventions to address infertility in the local context.\u003c/p\u003e","manuscriptTitle":"Epidemiology and Sociodemographic Predictors of Infertility among Women in Ilorin, North-central Nigeria: A 5-Year Retrospective Longitudinal Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-29 21:12:09","doi":"10.21203/rs.3.rs-4551360/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-05T09:45:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-04T09:47:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-04T09:44:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2024-06-08T16:49:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"92bf8810-f056-45bb-8f37-aaa7e7261b60","owner":[],"postedDate":"July 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-09T18:08:17+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-29 21:12:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4551360","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4551360","identity":"rs-4551360","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}