Is There an Association Between Insulin Resistance and Infertile Men With Non- Obstructive Azoospermia?

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Merve Baktıroğlu, Pınar Kırıcı, Fatma Ferda Verit, Duygu Güzel, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6614806/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 Purpose To investigate the relationship between insulin resistance and non-obstructive azoospermia in infertile men. Methods Seventy infertile men diagnosed with non-obstructive azoospermia or severe oligospermia and seventy infertile men with normospermia who presented to Suleymaniye Women’s Health Hospital between August 1, 2014, and August 1, 2016, were retrospectively reviewed. Demographic characteristics (height, weight, smoking status, duration of marriage) and laboratory parameters (FSH, LH, total testosterone, fasting insulin, fasting blood glucose, LDL, HDL, total cholesterol, triglycerides, and CRP) were compared between groups. Semen parameters were also analyzed. Comparisons were made using the Student’s t-test, with p < 0.05 considered statistically significant. Results There were no significant differences between groups in terms of age or marriage duration. However, body mass index (BMI) was significantly higher in the azoospermic group. FSH and LH levels were also higher in the azoospermic group, while total testosterone levels remained within normal ranges in both groups. Sperm count and progressive motility were lower in the azoospermic group. No significant differences were found between groups in terms of fasting glucose, insulin levels, lipid profile, or CRP levels. Conclusion Insulin resistance does not appear to be associated with non-obstructive azoospermia. The higher BMI observed in azoospermic men may suggest a potential role for obesity in male infertility. Weight management strategies may be beneficial for improving reproductive health in this population. infertility male factor non-obstructive azoospermia insulin resistance dyslipidemia obesity Introduction Infertility is becoming an increasingly significant public health concern, partly due to rising marriage age and lifestyle changes in modern societies. It imposes a substantial psychological burden on affected individuals and couples, in addition to posing high financial costs related to diagnosis and treatment. As such, infertility continues to be a focus of intense clinical and scientific investigation aimed at improving prevention, diagnosis, and management strategies. Infertility is classically defined as the inability of a couple to achieve pregnancy despite regular, unprotected sexual intercourse for at least one year [ 1 ]. While approximately 85% of couples conceive within this time frame, the remaining 15% meet the clinical criteria for infertility [ 2 ]. Evaluation and management of infertility must take into account factors such as the couple’s age, duration of infertility, lifestyle, socioeconomic status, and psychological well-being. Male infertility can result from a wide variety of congenital or acquired disorders affecting the urogenital tract, infections, hormonal imbalances, and genetic abnormalities [ 3 ]. A comprehensive evaluation of the male partner begins with a detailed medical history and physical examination, followed by semen analysis, endocrine profiling, and genetic testing when indicated [ 4 ]. Key prognostic factors in male infertility include the duration and type of infertility (primary vs. secondary), semen analysis results, male age (with advanced age—particularly over 45 years—being associated with poorer prognosis), and the fertility status of the female partner [ 5 ]. Semen analysis remains the cornerstone of male infertility evaluation and is interpreted using the criteria established by the World Health Organization (WHO) [ 6 , 7 ]. One important diagnostic finding is azoospermia, defined as the complete absence of sperm in at least two semen samples. While azoospermia is observed in approximately 1% of the general male population, its prevalence rises to 10–15% among infertile men [ 8 ]. Azoospermia is categorized into three main etiological groups: pre-testicular, testicular, and post-testicular. Pre-testicular azoospermia is typically associated with hormonal deficiencies or hypothalamic–pituitary axis dysfunction resulting in inadequate gonadotropin stimulation. Testicular azoospermia is caused by intrinsic testicular damage due to congenital, acquired, or idiopathic factors that impair spermatogenesis [ 9 ]. Post-testicular azoospermia results from ejaculatory dysfunction or obstruction in the reproductive tract that prevents sperm delivery. The diagnostic approach to azoospermia involves four key steps: (1) confirmation of azoospermia with repeated semen analyses, (2) differentiation between obstructive and non-obstructive causes, (3) identification of reversible etiologies, and (4) assessment for genetic abnormalities, including chromosomal or Y-chromosome microdeletions [ 10 ]. Materials and Methods This single-center, retrospective study was conducted at Süleymaniye Women’s Health Training and Research Hospital. Approval for the study protocol was obtained from the Training Planning Committee (EPK) of the hospital and the Ethics Committee of Bakırköy Sadi Konuk Training and Research Hospital. A total of 140 male patients who presented with infertility between August 1, 2014, and August 1, 2016, were included. The study group comprised 70 patients diagnosed with male factor infertility due to non-obstructive azoospermia (NOA) or severe oligospermia. The control group consisted of 70 infertile men with normozoospermic semen parameters. Participants in the NOA group were selected from among Turkish-speaking male patients aged 25–50 years, who voluntarily participated and had no history of obstructive azoospermia, genetic abnormalities on diagnostic testing, or active urogenital infection. Patients with a history of genital trauma, urogenital surgery, or previous urogenital infection were excluded. All patients were evaluated in the Urology Department, and semen analyses were interpreted by the Embryology Department. Genetic testing was performed in the Genetics Department, and final assessments were conducted by the Infertility Unit. Physical examinations and patient demographics—including age, height, weight, smoking status, and duration of marriage—were recorded. Biochemical parameters, including follicle-stimulating hormone (FSH), luteinizing hormone (LH), total testosterone, fasting glucose, fasting insulin, C-reactive protein (CRP), high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol (TC), and triglycerides (TG), were measured. Semen analysis parameters were also documented. Insulin resistance was assessed using the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) formula: HOMA-IR = (Fasting glucose [mg/dL] × Fasting insulin [µU/mL]) ÷ 405 Patients were divided into two groups: those with NOA/severe oligospermia and those with normozoospermia. The two groups were compared to assess the relationship between insulin resistance and non-obstructive azoospermia. Statistical Analysis All data are expressed as mean ± standard deviation. Comparisons of demographic characteristics, biochemical markers, and semen parameters between the study and control groups were performed using Student’s t-test. A p-value of < 0.05 was considered statistically significant. Results Descriptive statistics for participants' age, body mass index (BMI), and marriage duration are presented in Table 1 . Table 1 Demographic parameters of patients Azoospermic group (Mean ± SD) (n = 70) Control group (Mean ± SD) (n = 70) p value Age (year) 34.8 ± 5.8 35.4 ± 5.8 0.51 Body Mass Index (kg/m2) 26.9 ± 2.0 25.7 ± 1.7 < 0.0001 Length of Marriage (year) 7.7 ± 4.2 8.4 ± 4.4 0.31 The mean age was 34.8 ± 5.8 years in the non-obstructive azoospermic group and 35.4 ± 5.8 years in the normospermic group. The mean BMI was significantly higher in the azoospermic group (26.9 ± 2.0) compared to the normospermic group (25.7 ± 1.7) (p < 0.0001). The mean duration of marriage was 7.7 ± 4.2 years in the azoospermic group and 8.4 ± 4.4 years in the normospermic group. No statistically significant differences were observed between the groups regarding age (p = 0.51) or duration of marriage (p = 0.31). Semen analysis results are provided in Table 2 . Table 2 Semen analysis of patients Azoospermic group (Mean ± SD) (n = 70) Control group (Mean ± SD) (n = 70) p value Volume (mL) 2.7 ± 0.9 2.7 ± 0.7 0.83 Total sperm count (sperm × 10⁶) 0.0 ± 0.1 152.8 ± 60.7 < 0.0001 Progressive motility (%) 4.0 ± 9.5 28.9 ± 13.3 < 0.0001 The mean semen volume was 2.7 ± 0.9 mL in the azoospermic group and 2.7 ± 0.7 mL in the normospermic group, with no significant difference between groups. Total sperm count was 0.0 ± 0.1 × 10⁶/mL in the azoospermic group (due to inclusion of a few patients with severe oligospermia) and 152.8 ± 60.7 × 10⁶/mL in the normospermic group. Progressive motility was 4.0 ± 9.5% in the azoospermic group and 28.9 ± 13.3% in the normospermic group. Differences in total sperm count and progressive motility between groups were statistically significant (p < 0.05 for both). Hormonal and biochemical parameters are summarized in Table 3 . Table 3 Hormonal and biochemical profiles of patients Azoospermic group (Mean ± SD) (n = 70) Control group (Mean ± SD) (n = 70) p value FSH (mIU/mL) 11.9 ± 4.8 5.2 ± 1.7 < 0.0001 LH (mIU/mL) 7.2 ± 3.4 5.0 ± 1.5 < 0.0001 Total testosterone (ng/ml) 3.7 ± 1.6 2.9 ± 0.8 < 0.0001 Fasting glucose (mg/dL) 89.6 ± 7.6 87.6 ± 7.2 0.10 Fasting insulin (µIU/mL) 11.1 ± 4.3 9.9 ± 3.7 0.08 HOMA-IR 2.4 ± 0.9 2.1 ± 0.8 0.06 LDL (mg/dL) 121.9 ± 25.5 118.4 ± 24.9 0.41 HDL (mg/dL) 42.7 ± 5.4 44.3 ± 5.5 0.10 TC (mg/dL) 193.4 ± 31.2 189.2 ± 30.3 0.41 TG (mg/dL) 144.8 ± 50.6 137.6 ± 47.5 0.39 C-reactive protein (mg/L) 3.3 ± 1.9 3.0 ± 1.9 0.43 In the azoospermic group, mean serum FSH was 11.9 ± 4.8 mIU/mL, LH was 7.2 ± 3.4 mIU/mL, and total testosterone was 3.7 ± 1.6 ng/mL. Fasting glucose was 89.6 ± 7.6 mg/dL, fasting insulin 11.1 ± 4.3 µIU/mL, and HOMA-IR 2.4 ± 0.9. Lipid values included LDL 121.9 ± 25.5 mg/dL, HDL 42.7 ± 5.4 mg/dL, total cholesterol 193.4 ± 31.2 mg/dL, and triglycerides 144.8 ± 50.6 mg/dL. CRP was 3.3 ± 1.9 mg/L. In the normospermic group, mean FSH was 5.2 ± 1.7 mIU/mL, LH 5.0 ± 1.5 mIU/mL, and total testosterone 2.9 ± 0.8 ng/mL. Fasting glucose was 87.6 ± 7.2 mg/dL, fasting insulin 9.9 ± 3.7 µIU/mL, and HOMA-IR 2.1 ± 0.8. LDL was 118.4 ± 24.9 mg/dL, HDL 44.3 ± 5.5 mg/dL, total cholesterol 189.2 ± 30.3 mg/dL, triglycerides 137.6 ± 47.6 mg/dL, and CRP 3.0 ± 1.9 mg/L. Statistical analysis revealed significant differences between the groups in FSH, LH, and total testosterone levels (p < 0.05 for each). No statistically significant differences were found for glucose, insulin, HOMA-IR, lipid profile parameters, or CRP. Discussion Male infertility accounts for approximately 50% of all infertility cases, making it a major public health issue [ 2 ]. Among these, azoospermia—defined by the absence of sperm in semen analysis—represents around 15% of cases in men [ 11 ], with the majority classified as non-obstructive azoospermia (NOA) due to impaired spermatogenesis [ 1 ]. Meta-analyses by Carlsen et al. (1992) and Swan et al. (1999) documented a progressive decline in sperm quality and concentration since the 1970s, indicating a rising future prevalence of azoospermia [ 12 , 13 ]. While patients with obstructive azoospermia may benefit from surgical correction or assisted reproductive techniques (ART), the diagnosis and management of NOA is more complex. This is due not only to the wide range of possible etiologies—including infections, trauma, congenital anomalies, endocrine disorders, and genetic or systemic diseases—but also to the fact that a large proportion of NOA cases remain idiopathic [ 14 ]. Improved understanding of idiopathic NOA could facilitate earlier diagnosis, avoid unnecessary or ineffective ART interventions, and reduce complications such as testicular atrophy, hematoma, infection, or pain [ 15 ]. Moreover, etiologic insight could help reduce TESE (testicular sperm extraction) failure rates, which can be as high as 50%, and lead to the retrieval of higher quality sperm [ 16 ]. Insulin resistance is a key component of metabolic syndrome, which encompasses overweight, dyslipidemia, endothelial dysfunction, systemic inflammation, and glucose metabolism disorders. Based on the well-established negative impact of diabetes mellitus on sperm function and male fertility, we hypothesized a possible link between insulin resistance and NOA [ 17 , 18 ]. Previous studies support this hypothesis. La Vignera et al. (2012) found associations between hyperglycemia and decreased sperm concentration, motility, abnormal morphology, DNA damage, and seminal abnormalities [ 19 ]. Mallidis et al. (2009) observed that advanced glycation end-products accumulated in the male reproductive tract, leading to sperm damage in men with type 2 diabetes mellitus [ 20 ]. Ballester et al. (2004), in an animal model, demonstrated that streptozotocin-induced diabetic mice exhibited impaired spermatogenesis due to insulin deficiency. This insulin reduction diminished Leydig cell stimulation and decreased FSH receptor expression in seminiferous tubules, ultimately impairing sperm production and quality [ 21 ]. Similarly, Renata et al. (2016) reported that insulin resistance and hyperglycemia impaired Sertoli cell proliferation and function, which are essential for germ cell development. Disrupted glucose uptake and excess lactate accumulation due to insulin resistance adversely affected spermatogenesis [ 22 , 23 ]. Despite this background, our study found no significant differences in glucose metabolism markers—including insulin, glucose, HOMA-IR values, lipid profiles, and CRP—between NOA patients and normospermic controls. This suggests that insulin resistance may not play a direct role in the pathophysiology of NOA. Conversely, a significant difference in body mass index (BMI) was observed between the NOA and normospermic groups. Given the global rise in obesity and parallel decline in sperm quality, the relationship between BMI and male infertility has gained considerable interest. Sermondade et al. conducted two meta-analyses encompassing data from 21 and 14 studies, respectively, and concluded that overweight (BMI 25–29.9) and obesity (BMI ≥ 30) were associated with increased risk of azoospermia and oligospermia, in line with our findings [ 26 ]. Similarly, Cold et al. (Denmark, 1558 men) reported a significant inverse relationship between BMI and sperm count [ 27 ]. Pathophysiologically, increased oxidative stress—a key contributor to DNA damage—has been implicated in obesity-related male infertility [ 28 , 29 ]. Additionally, studies show that weight loss in overweight or obese men with idiopathic infertility and high sperm DNA fragmentation can improve semen parameters and facilitate conception through spontaneous means or intrauterine insemination (IUI) [ 30 ]. Conclusion When we search the literature, we can see that metabolic syndrome has many negative effects on the male reproductive system. However, in our study, we could not establish a clear relationship between insulin resistance and hyperlipidemia, which are components of metabolic syndrome, and non-obstructive azoospermia. To clarify the relationship between insulin resistance and non-obstructive azoospermia, there is a need for further biochemical, molecular, and genetic clinical studies involving larger sample sizes and more comprehensive parameters. According to the results of our study, which align with many other publications, an increased body mass index (BMI) negatively affects sperm count and quality. Therefore, all clinicians involved in the treatment of infertility should inform their patients about the adverse effects of weight gain on male fertility. Patients should be advised of the benefits of weight loss on fertility, including improvements in sperm function, erectile function, and libido, and encouraged to maintain a healthy weight. We believe that studies on infertility, such as ours, will continue to grow in number. These studies will help elucidate the etiopathogenesis of idiopathic male infertility and ultimately contribute to improved pregnancy outcomes. Declarations Conflicts of Interest: The authors declare no competing interests. Acknowledgments Acknowledgments are provided on the title page. Declaration of Interest None. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Author Contribution M.B collected and analyzed the data and wrote the manuscript; P.K helped writing the manuscript; D.G helped writing manuscript; E.S helped collecting the data; Z.Y helped collecting data; Ş.Y helped collecting data; F.V have done the statystics. All authors reviewed the manuscript. Data Availability ata is provided within the manuscript or supplementary information files References John O. Schorge, Joseph I. Schaffer, Lisa M. Halvorson, Barbara L. Hoffman, Karen D. Bradshaw, F. Gary Cunningham. Williams Gynecology. Second Edition. 2015, p506. A. J. Wein, L. R. Kavoussi, A. C. Novick, A. W. Partin, and C. A. Peters, Campbell-Walsh Urology 10th Edition. 2012. C. Niederberger, “WHO manual for the standardized investigation, diagnosis and management of the infertile male,” Urology, vol. 57, no. 1, p. 208, 2001. V. M. Brugh and L. I. Lipshultz, “Male factor infertility: evaluation and management,” Med. Clin. North Am., vol. 88, no. 2, pp. 367–385, 2004. H. K. A. Snick, T. S. Snick, J. L. H. Evers, and J. A. Collins, “The spontaneous pregnancy prognosis in untreated subfertile couples: The Walcheren primary care study,” Hum. Reprod., vol. 12, no. 7, pp. 1582–1588, 1997. M. Sigman and A. Zini, “Semen analysis and sperm function assays: What do they mean?,” Semin. Reprod. Med., vol. 27, no. 2, pp. 115–123, 2009. World Health Organization, WHO laboratory manual for the examination and processing of human semen, 5th ed., 2010. B. M. Berookhim and P. N. Schlegel, “Azoospermia due to spermatogenic failure,” Urol. Clin. North Am., vol. 41, no. 1, pp. 97–113, 2014. A. Jungwirth et al., “European Association of Urology guidelines on male infertility: The 2012 update,” Eur. Urol., vol. 62, no. 2, pp. 324–332, 2012. R. Kumar, “Medical management of non-obstructive azoospermia,” Clinics, vol. 68, no. S1, pp. 75–79, 2013. G. M. Willott, “Frequency of azoospermia,” Forensic Sci. Int., vol. 20, no. 1, pp. 9–10, 1982. E. Carlsen et al., “Evidence for decreasing quality of semen during past 50 years,” BMJ, vol. 305, no. 6854, pp. 609–613, 1992. S. H. Swan and E. P. Elkin, “Declining semen quality: Can the past inform the present?,” BioEssays, vol. 21, no. 7, pp. 614–621, 1999. M. Cocuzza et al., “The epidemiology and etiology of azoospermia,” Clinics, vol. 68 Suppl 1, pp. 15–26, 2013. R. Mercan et al., “Outcome of testicular sperm retrieval procedures in non-obstructive azoospermia: percutaneous aspiration versus open biopsy,” Hum. Reprod., vol. 15, no. 7, pp. 1548–1551, 2000. M. Marconi et al., “Combined trifocal and microsurgical testicular sperm extraction is the best technique for testicular sperm retrieval in ‘low-chance’ non-obstructive azoospermia,” Eur. Urol., vol. 62, no. 4, pp. 713–719, 2012. S. S. Kasturi et al., “The metabolic syndrome and male infertility,” J. Androl., vol. 29, no. 3, pp. 251–259, 2008. I. Gorbachinsky et al., “Metabolic syndrome and urologic diseases,” Rev. Urol., vol. 12, no. 4, pp. e157–180, 2010. S. La Vignera et al., “Diabetes mellitus and sperm parameters,” J. Androl., vol. 33, no. 2, pp. 145–153, 2012. C. Mallidis et al., “Advanced glycation end products accumulate in the reproductive tract of men with diabetes,” Int. J. Androl., vol. 32, no. 4, pp. 295–305, 2009. J. Ballester et al., “Insulin-dependent diabetes affects testicular function by FSH- and LH-linked mechanisms,” J. Androl., vol. 25, no. 5, pp. 706–719, 2004. R. S. T. A et al., “High glucose levels affect spermatogenesis: an in vitro approach,” 2016. P. F. Oliveira et al., “Effect of insulin deprivation on metabolism and metabolism-associated gene transcript levels of in vitro cultured human Sertoli cells,” Biochim. Biophys. Acta, vol. 1820, no. 2, pp. 84–89, 2012. F. Farzadfar et al., “National, regional, and global trends in serum total cholesterol since 1980,” Lancet, vol. 377, no. 9765, pp. 578–586, 2011. A. Katib, “Mechanisms linking obesity to male infertility,” Cent. Eur. J. Urol., vol. 68, no. 1, pp. 79–85, 2015. N. Sermondade et al., “BMI in relation to sperm count: An updated systematic review and collaborative meta-analysis,” Hum. Reprod. Update, vol. 19, no. 3, pp. 221–231, 2013. T. K. Jensen et al., “Body mass index in relation to semen quality and reproductive hormones among 1,558 Danish men,” Fertil. Steril., vol. 82, no. 4, pp. 863–870, 2004. S. Furukawa et al., “Increased oxidative stress in obesity and its impact on metabolic syndrome,” J. Clin. Invest., vol. 114, no. 12, pp. 1752–1761, 2004. O. Tunc et al., “Impact of body mass index on seminal oxidative stress,” Andrologia, vol. 43, no. 2, pp. 121–128, 2011. C. Faure et al., “In subfertile couple, abdominal fat loss in men is associated with improvement of sperm quality and pregnancy: A case-series,” PLoS One, vol. 9, no. 2, 2014. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6614806","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":464056810,"identity":"6e455fb2-83b3-4e2b-8532-11d3176c85ad","order_by":0,"name":"Merve Baktıroğlu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIiWNgGAWjYLACxgYGAwZm5oOP/1QcAAsceECUFna2ZAOeMwcYeEBaEojSws9jJsHbBtHCgE+LbnvvM4mPO+yMGZh5jA0k592Rsxc7/BBoi52cbgN2LWZnjptJzjyTbMbAzFb4wHDbM2Me6TQDoJZkY7MDOLTcSGM25m1jtgF6f7NB4rbDiT3SCSAtBxK34dJy/xmz8d+2eqAWBjOJg3NAWtI/4Ndyg43xMWPbYaDDWMwkGxtAWnII2HImjfFh75njQO+zJRszHDtszHM7p+BAggEevxw/xnDg545qwwb+wwcfM9QclmOfnb75w4cKOzlcWuDAHlWBAQHlo2AUjIJRMArwAgBQbWBlMg9/egAAAABJRU5ErkJggg==","orcid":"","institution":"Suleymaniye Women’s Health Training and Research Hospital","correspondingAuthor":true,"prefix":"","firstName":"Merve","middleName":"","lastName":"Baktıroğlu","suffix":""},{"id":464056811,"identity":"76662be1-7663-4222-bbd4-fac240ecaa9a","order_by":1,"name":"Pınar Kırıcı","email":"","orcid":"","institution":"Adıyaman University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Pınar","middleName":"","lastName":"Kırıcı","suffix":""},{"id":464056812,"identity":"bd30c793-2385-4a34-b06e-415b5d19ba11","order_by":2,"name":"Fatma Ferda Verit","email":"","orcid":"","institution":"Suleymaniye Women’s Health Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fatma","middleName":"Ferda","lastName":"Verit","suffix":""},{"id":464056813,"identity":"d94c3b5f-aced-4d08-90a9-972ee0c64fe3","order_by":3,"name":"Duygu Güzel","email":"","orcid":"","institution":"Ege University","correspondingAuthor":false,"prefix":"","firstName":"Duygu","middleName":"","lastName":"Güzel","suffix":""},{"id":464056814,"identity":"45135756-74fc-4424-8eb7-4d9ad8354d4b","order_by":4,"name":"Ziya Yıldırım","email":"","orcid":"","institution":"Suleymaniye Women’s Health Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ziya","middleName":"","lastName":"Yıldırım","suffix":""},{"id":464056815,"identity":"1b2a216e-375f-446e-bc23-43a6e903f903","order_by":5,"name":"Ekrem Sezgin","email":"","orcid":"","institution":"Suleymaniye Women’s Health Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ekrem","middleName":"","lastName":"Sezgin","suffix":""},{"id":464056816,"identity":"18e37d52-f2ad-4524-9cff-b2b9f77be6ec","order_by":6,"name":"Şener Yalçınkaya","email":"","orcid":"","institution":"Suleymaniye Women’s Health Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Şener","middleName":"","lastName":"Yalçınkaya","suffix":""}],"badges":[],"createdAt":"2025-05-07 20:08:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6614806/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6614806/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83751505,"identity":"f61bf236-1748-4ed5-9786-82585553a288","added_by":"auto","created_at":"2025-06-02 07:04:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":518906,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6614806/v1/33fabb30-5d1a-4f61-86e5-d8deac1c1d60.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Is There an Association Between Insulin Resistance and Infertile Men With Non- Obstructive Azoospermia?","fulltext":[{"header":"Introduction","content":"\u003cp\u003eInfertility is becoming an increasingly significant public health concern, partly due to rising marriage age and lifestyle changes in modern societies. It imposes a substantial psychological burden on affected individuals and couples, in addition to posing high financial costs related to diagnosis and treatment. As such, infertility continues to be a focus of intense clinical and scientific investigation aimed at improving prevention, diagnosis, and management strategies.\u003c/p\u003e \u003cp\u003eInfertility is classically defined as the inability of a couple to achieve pregnancy despite regular, unprotected sexual intercourse for at least one year [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. While approximately 85% of couples conceive within this time frame, the remaining 15% meet the clinical criteria for infertility [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Evaluation and management of infertility must take into account factors such as the couple\u0026rsquo;s age, duration of infertility, lifestyle, socioeconomic status, and psychological well-being.\u003c/p\u003e \u003cp\u003eMale infertility can result from a wide variety of congenital or acquired disorders affecting the urogenital tract, infections, hormonal imbalances, and genetic abnormalities [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. A comprehensive evaluation of the male partner begins with a detailed medical history and physical examination, followed by semen analysis, endocrine profiling, and genetic testing when indicated [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Key prognostic factors in male infertility include the duration and type of infertility (primary vs. secondary), semen analysis results, male age (with advanced age\u0026mdash;particularly over 45 years\u0026mdash;being associated with poorer prognosis), and the fertility status of the female partner [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSemen analysis remains the cornerstone of male infertility evaluation and is interpreted using the criteria established by the World Health Organization (WHO) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. One important diagnostic finding is azoospermia, defined as the complete absence of sperm in at least two semen samples. While azoospermia is observed in approximately 1% of the general male population, its prevalence rises to 10\u0026ndash;15% among infertile men [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAzoospermia is categorized into three main etiological groups: pre-testicular, testicular, and post-testicular. Pre-testicular azoospermia is typically associated with hormonal deficiencies or hypothalamic\u0026ndash;pituitary axis dysfunction resulting in inadequate gonadotropin stimulation. Testicular azoospermia is caused by intrinsic testicular damage due to congenital, acquired, or idiopathic factors that impair spermatogenesis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Post-testicular azoospermia results from ejaculatory dysfunction or obstruction in the reproductive tract that prevents sperm delivery.\u003c/p\u003e \u003cp\u003eThe diagnostic approach to azoospermia involves four key steps: (1) confirmation of azoospermia with repeated semen analyses, (2) differentiation between obstructive and non-obstructive causes, (3) identification of reversible etiologies, and (4) assessment for genetic abnormalities, including chromosomal or Y-chromosome microdeletions [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThis single-center, retrospective study was conducted at S\u0026uuml;leymaniye Women\u0026rsquo;s Health Training and Research Hospital. Approval for the study protocol was obtained from the Training Planning Committee (EPK) of the hospital and the Ethics Committee of Bakırk\u0026ouml;y Sadi Konuk Training and Research Hospital.\u003c/p\u003e \u003cp\u003eA total of 140 male patients who presented with infertility between August 1, 2014, and August 1, 2016, were included. The study group comprised 70 patients diagnosed with male factor infertility due to non-obstructive azoospermia (NOA) or severe oligospermia. The control group consisted of 70 infertile men with normozoospermic semen parameters.\u003c/p\u003e \u003cp\u003eParticipants in the NOA group were selected from among Turkish-speaking male patients aged 25\u0026ndash;50 years, who voluntarily participated and had no history of obstructive azoospermia, genetic abnormalities on diagnostic testing, or active urogenital infection. Patients with a history of genital trauma, urogenital surgery, or previous urogenital infection were excluded.\u003c/p\u003e \u003cp\u003eAll patients were evaluated in the Urology Department, and semen analyses were interpreted by the Embryology Department. Genetic testing was performed in the Genetics Department, and final assessments were conducted by the Infertility Unit. Physical examinations and patient demographics\u0026mdash;including age, height, weight, smoking status, and duration of marriage\u0026mdash;were recorded. Biochemical parameters, including follicle-stimulating hormone (FSH), luteinizing hormone (LH), total testosterone, fasting glucose, fasting insulin, C-reactive protein (CRP), high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol (TC), and triglycerides (TG), were measured. Semen analysis parameters were also documented.\u003c/p\u003e \u003cp\u003eInsulin resistance was assessed using the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) formula:\u003c/p\u003e \u003cp\u003eHOMA-IR = (Fasting glucose [mg/dL] \u0026times; Fasting insulin [\u0026micro;U/mL])\u0026thinsp;\u0026divide;\u0026thinsp;405\u003c/p\u003e \u003cp\u003ePatients were divided into two groups: those with NOA/severe oligospermia and those with normozoospermia. The two groups were compared to assess the relationship between insulin resistance and non-obstructive azoospermia.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll data are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Comparisons of demographic characteristics, biochemical markers, and semen parameters between the study and control groups were performed using Student\u0026rsquo;s t-test. A p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eDescriptive statistics for participants' age, body mass index (BMI), and marriage duration are presented in 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\u003eDemographic parameters of patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e Azoospermic group (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (n\u0026thinsp;=\u0026thinsp;70)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl group (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (n\u0026thinsp;=\u0026thinsp;70)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e34.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e35.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody Mass Index (kg/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e26.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e25.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of Marriage (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e8.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.31\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\u003eThe mean age was 34.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8 years in the non-obstructive azoospermic group and 35.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8 years in the normospermic group. The mean BMI was significantly higher in the azoospermic group (26.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0) compared to the normospermic group (25.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The mean duration of marriage was 7.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.2 years in the azoospermic group and 8.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4 years in the normospermic group. No statistically significant differences were observed between the groups regarding age (p\u0026thinsp;=\u0026thinsp;0.51) or duration of marriage (p\u0026thinsp;=\u0026thinsp;0.31).\u003c/p\u003e \u003cp\u003eSemen analysis results are provided in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\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\u003eSemen analysis of patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAzoospermic group (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (n\u0026thinsp;=\u0026thinsp;70)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl group (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (n\u0026thinsp;=\u0026thinsp;70)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVolume (mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal sperm count (sperm \u0026times; 10⁶)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e152.8\u0026thinsp;\u0026plusmn;\u0026thinsp;60.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgressive motility (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e28.9\u0026thinsp;\u0026plusmn;\u0026thinsp;13.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\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\u003eThe mean semen volume was 2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 mL in the azoospermic group and 2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 mL in the normospermic group, with no significant difference between groups. Total sperm count was 0.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 \u0026times; 10⁶/mL in the azoospermic group (due to inclusion of a few patients with severe oligospermia) and 152.8\u0026thinsp;\u0026plusmn;\u0026thinsp;60.7 \u0026times; 10⁶/mL in the normospermic group. Progressive motility was 4.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.5% in the azoospermic group and 28.9\u0026thinsp;\u0026plusmn;\u0026thinsp;13.3% in the normospermic group. Differences in total sperm count and progressive motility between groups were statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for both).\u003c/p\u003e \u003cp\u003eHormonal and biochemical parameters are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHormonal and biochemical profiles of patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAzoospermic group (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (n\u0026thinsp;=\u0026thinsp;70)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl group (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (n\u0026thinsp;=\u0026thinsp;70)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFSH (mIU/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e11.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLH (mIU/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal testosterone (ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting glucose (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e89.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e87.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting insulin (\u0026micro;IU/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e11.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e9.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOMA-IR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e121.9\u0026thinsp;\u0026plusmn;\u0026thinsp;25.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e118.4\u0026thinsp;\u0026plusmn;\u0026thinsp;24.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e42.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e44.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e193.4\u0026thinsp;\u0026plusmn;\u0026thinsp;31.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e189.2\u0026thinsp;\u0026plusmn;\u0026thinsp;30.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e144.8\u0026thinsp;\u0026plusmn;\u0026thinsp;50.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e137.6\u0026thinsp;\u0026plusmn;\u0026thinsp;47.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC-reactive protein (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.43\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\u003eIn the azoospermic group, mean serum FSH was 11.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.8 mIU/mL, LH was 7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4 mIU/mL, and total testosterone was 3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6 ng/mL. Fasting glucose was 89.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6 mg/dL, fasting insulin 11.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3 \u0026micro;IU/mL, and HOMA-IR 2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9. Lipid values included LDL 121.9\u0026thinsp;\u0026plusmn;\u0026thinsp;25.5 mg/dL, HDL 42.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4 mg/dL, total cholesterol 193.4\u0026thinsp;\u0026plusmn;\u0026thinsp;31.2 mg/dL, and triglycerides 144.8\u0026thinsp;\u0026plusmn;\u0026thinsp;50.6 mg/dL. CRP was 3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9 mg/L.\u003c/p\u003e \u003cp\u003eIn the normospermic group, mean FSH was 5.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7 mIU/mL, LH 5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 mIU/mL, and total testosterone 2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 ng/mL. Fasting glucose was 87.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2 mg/dL, fasting insulin 9.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7 \u0026micro;IU/mL, and HOMA-IR 2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8. LDL was 118.4\u0026thinsp;\u0026plusmn;\u0026thinsp;24.9 mg/dL, HDL 44.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5 mg/dL, total cholesterol 189.2\u0026thinsp;\u0026plusmn;\u0026thinsp;30.3 mg/dL, triglycerides 137.6\u0026thinsp;\u0026plusmn;\u0026thinsp;47.6 mg/dL, and CRP 3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9 mg/L.\u003c/p\u003e \u003cp\u003eStatistical analysis revealed significant differences between the groups in FSH, LH, and total testosterone levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for each). No statistically significant differences were found for glucose, insulin, HOMA-IR, lipid profile parameters, or CRP.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMale infertility accounts for approximately 50% of all infertility cases, making it a major public health issue [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Among these, azoospermia\u0026mdash;defined by the absence of sperm in semen analysis\u0026mdash;represents around 15% of cases in men [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], with the majority classified as non-obstructive azoospermia (NOA) due to impaired spermatogenesis [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Meta-analyses by Carlsen et al. (1992) and Swan et al. (1999) documented a progressive decline in sperm quality and concentration since the 1970s, indicating a rising future prevalence of azoospermia [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile patients with obstructive azoospermia may benefit from surgical correction or assisted reproductive techniques (ART), the diagnosis and management of NOA is more complex. This is due not only to the wide range of possible etiologies\u0026mdash;including infections, trauma, congenital anomalies, endocrine disorders, and genetic or systemic diseases\u0026mdash;but also to the fact that a large proportion of NOA cases remain idiopathic [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Improved understanding of idiopathic NOA could facilitate earlier diagnosis, avoid unnecessary or ineffective ART interventions, and reduce complications such as testicular atrophy, hematoma, infection, or pain [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Moreover, etiologic insight could help reduce TESE (testicular sperm extraction) failure rates, which can be as high as 50%, and lead to the retrieval of higher quality sperm [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInsulin resistance is a key component of metabolic syndrome, which encompasses overweight, dyslipidemia, endothelial dysfunction, systemic inflammation, and glucose metabolism disorders. Based on the well-established negative impact of diabetes mellitus on sperm function and male fertility, we hypothesized a possible link between insulin resistance and NOA [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrevious studies support this hypothesis. La Vignera et al. (2012) found associations between hyperglycemia and decreased sperm concentration, motility, abnormal morphology, DNA damage, and seminal abnormalities [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Mallidis et al. (2009) observed that advanced glycation end-products accumulated in the male reproductive tract, leading to sperm damage in men with type 2 diabetes mellitus [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBallester et al. (2004), in an animal model, demonstrated that streptozotocin-induced diabetic mice exhibited impaired spermatogenesis due to insulin deficiency. This insulin reduction diminished Leydig cell stimulation and decreased FSH receptor expression in seminiferous tubules, ultimately impairing sperm production and quality [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Similarly, Renata et al. (2016) reported that insulin resistance and hyperglycemia impaired Sertoli cell proliferation and function, which are essential for germ cell development. Disrupted glucose uptake and excess lactate accumulation due to insulin resistance adversely affected spermatogenesis [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite this background, our study found no significant differences in glucose metabolism markers\u0026mdash;including insulin, glucose, HOMA-IR values, lipid profiles, and CRP\u0026mdash;between NOA patients and normospermic controls. This suggests that insulin resistance may not play a direct role in the pathophysiology of NOA.\u003c/p\u003e \u003cp\u003eConversely, a significant difference in body mass index (BMI) was observed between the NOA and normospermic groups. Given the global rise in obesity and parallel decline in sperm quality, the relationship between BMI and male infertility has gained considerable interest. Sermondade et al. conducted two meta-analyses encompassing data from 21 and 14 studies, respectively, and concluded that overweight (BMI 25\u0026ndash;29.9) and obesity (BMI\u0026thinsp;\u0026ge;\u0026thinsp;30) were associated with increased risk of azoospermia and oligospermia, in line with our findings [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSimilarly, Cold et al. (Denmark, 1558 men) reported a significant inverse relationship between BMI and sperm count [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Pathophysiologically, increased oxidative stress\u0026mdash;a key contributor to DNA damage\u0026mdash;has been implicated in obesity-related male infertility [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Additionally, studies show that weight loss in overweight or obese men with idiopathic infertility and high sperm DNA fragmentation can improve semen parameters and facilitate conception through spontaneous means or intrauterine insemination (IUI) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWhen we search the literature, we can see that metabolic syndrome has many negative effects on the male reproductive system. However, in our study, we could not establish a clear relationship between insulin resistance and hyperlipidemia, which are components of metabolic syndrome, and non-obstructive azoospermia. To clarify the relationship between insulin resistance and non-obstructive azoospermia, there is a need for further biochemical, molecular, and genetic clinical studies involving larger sample sizes and more comprehensive parameters.\u003c/p\u003e \u003cp\u003eAccording to the results of our study, which align with many other publications, an increased body mass index (BMI) negatively affects sperm count and quality. Therefore, all clinicians involved in the treatment of infertility should inform their patients about the adverse effects of weight gain on male fertility. Patients should be advised of the benefits of weight loss on fertility, including improvements in sperm function, erectile function, and libido, and encouraged to maintain a healthy weight.\u003c/p\u003e \u003cp\u003eWe believe that studies on infertility, such as ours, will continue to grow in number. These studies will help elucidate the etiopathogenesis of idiopathic male infertility and ultimately contribute to improved pregnancy outcomes.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eAcknowledgments are provided on the title page.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eDeclaration of Interest\u003c/h2\u003e \u003cp\u003eNone.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eM.B collected and analyzed the data and wrote the manuscript; P.K helped writing the manuscript; D.G helped writing manuscript; E.S helped collecting the data; Z.Y helped collecting data; Ş.Y helped collecting data; F.V have done the statystics. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eata is provided within the manuscript or supplementary information files\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJohn O. Schorge, Joseph I. Schaffer, Lisa M. Halvorson, Barbara L. Hoffman, Karen D. Bradshaw, F. Gary Cunningham. Williams Gynecology. Second Edition. 2015, p506.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eA. J. Wein, L. R. Kavoussi, A. C. Novick, A. W. Partin, and C. A. Peters, Campbell-Walsh Urology 10th Edition. 2012.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC. Niederberger, \u0026ldquo;WHO manual for the standardized investigation, diagnosis and management of the infertile male,\u0026rdquo; Urology, vol. 57, no. 1, p. 208, 2001.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eV. M. Brugh and L. I. Lipshultz, \u0026ldquo;Male factor infertility: evaluation and management,\u0026rdquo; Med. Clin. North Am., vol. 88, no. 2, pp. 367\u0026ndash;385, 2004.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eH. K. A. Snick, T. S. Snick, J. L. H. Evers, and J. A. Collins, \u0026ldquo;The spontaneous pregnancy prognosis in untreated subfertile couples: The Walcheren primary care study,\u0026rdquo; Hum. Reprod., vol. 12, no. 7, pp. 1582\u0026ndash;1588, 1997.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM. Sigman and A. Zini, \u0026ldquo;Semen analysis and sperm function assays: What do they mean?,\u0026rdquo; Semin. Reprod. Med., vol. 27, no. 2, pp. 115\u0026ndash;123, 2009.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization, WHO laboratory manual for the examination and processing of human semen, 5th ed., 2010.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eB. M. Berookhim and P. N. 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Marconi et al., \u0026ldquo;Combined trifocal and microsurgical testicular sperm extraction is the best technique for testicular sperm retrieval in \u0026lsquo;low-chance\u0026rsquo; non-obstructive azoospermia,\u0026rdquo; Eur. Urol., vol. 62, no. 4, pp. 713\u0026ndash;719, 2012.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS. S. Kasturi et al., \u0026ldquo;The metabolic syndrome and male infertility,\u0026rdquo; J. Androl., vol. 29, no. 3, pp. 251\u0026ndash;259, 2008.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eI. Gorbachinsky et al., \u0026ldquo;Metabolic syndrome and urologic diseases,\u0026rdquo; Rev. Urol., vol. 12, no. 4, pp. e157\u0026ndash;180, 2010.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS. La Vignera et al., \u0026ldquo;Diabetes mellitus and sperm parameters,\u0026rdquo; J. Androl., vol. 33, no. 2, pp. 145\u0026ndash;153, 2012.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC. Mallidis et al., \u0026ldquo;Advanced glycation end products accumulate in the reproductive tract of men with diabetes,\u0026rdquo; Int. J. Androl., vol. 32, no. 4, pp. 295\u0026ndash;305, 2009.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJ. Ballester et al., \u0026ldquo;Insulin-dependent diabetes affects testicular function by FSH- and LH-linked mechanisms,\u0026rdquo; J. Androl., vol. 25, no. 5, pp. 706\u0026ndash;719, 2004.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eR. S. T. A et al., \u0026ldquo;High glucose levels affect spermatogenesis: an in vitro approach,\u0026rdquo; 2016.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eP. F. Oliveira et al., \u0026ldquo;Effect of insulin deprivation on metabolism and metabolism-associated gene transcript levels of in vitro cultured human Sertoli cells,\u0026rdquo; Biochim. Biophys. 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Faure et al., \u0026ldquo;In subfertile couple, abdominal fat loss in men is associated with improvement of sperm quality and pregnancy: A case-series,\u0026rdquo; PLoS One, vol. 9, no. 2, 2014.\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":"","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":"infertility, male factor, non-obstructive azoospermia, insulin resistance, dyslipidemia, obesity","lastPublishedDoi":"10.21203/rs.3.rs-6614806/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6614806/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the relationship between insulin resistance and non-obstructive azoospermia in infertile men.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeventy infertile men diagnosed with non-obstructive azoospermia or severe oligospermia and seventy infertile men with normospermia who presented to Suleymaniye Women’s Health Hospital between August 1, 2014, and August 1, 2016, were retrospectively reviewed. Demographic characteristics (height, weight, smoking status, duration of marriage) and laboratory parameters (FSH, LH, total testosterone, fasting insulin, fasting blood glucose, LDL, HDL, total cholesterol, triglycerides, and CRP) were compared between groups. Semen parameters were also analyzed. Comparisons were made using the Student’s t-test, with p \u0026lt; 0.05 considered statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere were no significant differences between groups in terms of age or marriage duration. However, body mass index (BMI) was significantly higher in the azoospermic group. FSH and LH levels were also higher in the azoospermic group, while total testosterone levels remained within normal ranges in both groups. Sperm count and progressive motility were lower in the azoospermic group. No significant differences were found between groups in terms of fasting glucose, insulin levels, lipid profile, or CRP levels.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInsulin resistance does not appear to be associated with non-obstructive azoospermia. The higher BMI observed in azoospermic men may suggest a potential role for obesity in male infertility. Weight management strategies may be beneficial for improving reproductive health in this population.\u003c/p\u003e","manuscriptTitle":"Is There an Association Between Insulin Resistance and Infertile Men With Non- Obstructive Azoospermia?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-02 06:56:14","doi":"10.21203/rs.3.rs-6614806/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":"44a46baa-2f8a-40d7-ba78-5321a660ee32","owner":[],"postedDate":"June 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-02T06:56:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-02 06:56:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6614806","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6614806","identity":"rs-6614806","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}