Is a Large Neck Circumference a Risk Factor for Male Infertility in the Turkish Population?

doi:10.21203/rs.3.rs-3580133/v1

Download PDF

Article

Is a Large Neck Circumference a Risk Factor for Male Infertility in the Turkish Population?

https://doi.org/10.21203/rs.3.rs-3580133/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Background

Currently, the potential role of obesity on semen quality has not yet been fully elucidated. In recent years, alternative anthropometric measurements to body mass index (BMI), which more reflect of body fat distribution, have been established to estimate central adiposity. The association between neck circumference (NC), a novel index of central adiposity, and semen quality has not been explored yet.

Objective

The present study aimed to reveal the potential of NC to predict male infertility.

Subjects and Methods:

This is a cross-sectional study including 4739 male participants aged 17–55 years. Semen parameters included sperm concentration, total count, total motility, progressive motility, rapid progressive motility and vitality. As anthropometric measurements of obesity, BMI and central obesity indices including waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHpR), waist-to-height ratio (WHtR) and NC were examined. The predictive potentials of obesity indices for low semen parameters were evaluated by Receiver Operating Characteristics curve analysis. The associations of obesity indices with semen parameters were analyzed by binary logistic regression analyze after adjusting potential confounders.

Results

Patients with lower semen parameters had higher anthropometric obesity indices than those with normal parameters. The obesity indices had predictive potentials for low semen parameters, excluding WHpR for sperm concentration and, BMI and HC for rapid progressive motility. After adjusting for confounders, the strongest associations were found between HC with sperm count parameters, WC and WHtR with sperm vitality and motility parameters and NC with rapid progressive motility (OR: 2.37, 95% CI: 2.02–2.79, p < .001).

Conclusions

Obesity, particularly central obesity plays important a role in male infertility. The distribution of adipose tissue appears to may have specific roles on sperm functions, resulting in different fertility markers may be affected. A larger NC may be a risk factor for male infertility, specifically low sperm rapid progressive motility.

Health sciences/Diseases/Endocrine system and metabolic diseases/Obesity

Health sciences/Risk factors

Male infertility

semen quality

central obesity indices

neck circumference

body mass index

About 15% of couples are affected by infertility. The male factor plays a role in 50% of infertile cases and contributes to infertility alone in approximately 25–30% of cases^1,2. Obesity is a global health problem and the prevalence of obesity has been increasing worldwide in recent decades³. A simultaneous decline in semen quality⁴ with the increasing prevalence of obesity suggests that obesity can contribute to male infertility. Obesity has been shown to disrupt male reproductive functions by means of multiple mechanisms such as erectile dysfunction, sex hormone dysregulations, increased production of inflammatory mediators and reactive oxygen species, and increased testicular temperature that may have harmful effects on spermatogenesis^5–7.

Obesity is characterized as an increased body fat that has a detrimental impact on health outcomes and is clinically defined based on body mass index (BMI)⁸. However, the distribution of body fat rather than the amount play a more critical role in the development of obesity-related complications⁹. There is evidence that excessive visceral fat plays an important role in the detrimental effects of obesity¹⁰. Whereas, BMI does not distinguish between lean and fat body mass and characterize body fat distribution and therefore has a low sensitivity to estimate the risk of central adiposity and obesity-related complications¹¹. In this context, alternative anthropometric measurements, which are more precise measures of body fat distribution, to predict central obesity have been established, including waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR). However, there are conflicting data about the potential role of obesity-related markers on semen quality. Some studies have reported negative association between obesity-related markers and semen parameters^12–14, while others have suggested that they failed to predict semen quality^15,16.

It has recently been suggested that excess fat accumulation around the neck, a measure of upper body subcutaneous fat distribution, more closely resembles visceral fat than subcutaneous fat, and that a large NC may be an indicator for central obesity. The effectiveness of NC in identifying excess body weight and central adiposity has been proven^17,18. Several studies have demonstrated that NC has a unique association with some health outcomes such as cardiovascular disease, hyperinsulinemia, metabolic syndrome and obstructive sleep apnea, independently of other obesity indices^19–21. NC may be a useful tool to screen for excess body fat because it is an easy-to-apply, low-cost method, less invasive and a more stable measure than BMI and WC²².

This study aimed to elucidate the role of central obesity on male infertility, which remains unclear today. In this sense, it is important to reveal for the first time whether NC, which is considered a novel index of central obesity, is a predictive factor for poor semen quality. Furthermore, these associations, examined in a large sample of patients, were confirmed after adjustment for potential confounding factors related to obesity and semen quality.

Study Population

The population of this cross-sectional study consisted of a total of 4739 male participants 17–55 aged, who applied to Selçuk University Hospital Andrology Laboratory for standard semen analysis between 2017–2022 years. The study was approved by the Ethics Committee of Selcuk University, Faculty of Medicine. The ages, anthropometric obesity measurements and semen analysis parameters of all participants were recorded. NC measurements were obtained in 3665 of the participants. Sperm viability test was performed on a total of 4438 participants. The inclusion criteria of the study were all patients who were between the ages of 17–55 and did not have testicular tumor, clinical varicocele, orchiditis and azoospermia.

Semen Analysis

Semen analysis was performed according to WHO guideline (2010)²³. Semen parameters were included sperm concentration, total count, total motility, progressive motility, rapid progressive motility and vitality. Semen variables were divided to two categories according to WHO (2010) criteria; sperm concentration: ≥ 15 M/ml and < 15 M/ml, total count: ≥ 39 M and < 39 M, total motility ≥ 40% and < 40%, progressive motility ≥ 32% and < 32%, rapid progressive motility ≥ 5% and < 5%, vitality ≥ 58% and < 58%.

Semen samples collected after a period of 2–6 days of sexual abstinence were left to liquefy for 30–60 min at 37°C. After liquefaction, sperm concentration and motility characteristics were determined with a makler counting chamber. Sperm motility was classified as total sperm motility (WHO class A + B + C), progressive motility (WHO class A + B) and rapid progressive motility (WHO class A).

Sperm vitality was assessed by Eosin-Nigrosin staining. The stained semen samples were evaluated under an Olympus CX21 microscope at the least 200 spermatozoa cells for each semen sample. The percentage of sperm vitality was calculated as the ratio of viable cells to total cells.

Anthropometric Measurements

As the anthropometric measurements of obesity, BMI, WC, HC, WHpR, WHtR and NC were examined. Participants' height and weight were measured in standing and upright position, without shoes and heavy outer clothing. BMI was calculated as weight in kilograms divided by height in meters squared. WC was measured at the midpoint between the lowest costal margin and the iliac crest, and HC was measured at the widest point around the greater trochanter. WHpR was calculated as waist circumference divided by hip circumference, and WHtR was calculated as waist circumference divided by height. NC was measured perpendicular to the neck axis, above the laryngeal prominence. Obesity was classified according to the WHO guideline (2000) (8); normal weight: BMI < 25 and overweight/obese: BMI ≥ 25. Central obesity indices were divided into two categories, according to the cutoff points we determined for low semen parameters by ROC curve analysis.

Statistical Analysis

All statistical analysis was performed using R version 4.1.2 (The R Foundation for Statistical Computing. Vienna. Austria; https://www.r-project.org). The Kolmogorov-Smirnov test was applied to determine whether the analyzed parameters were normally distributed. Kolmogorov-Smirnov test was applied to determine whether the analyzed parameters were normally distributed. The differences of age and anthropometric obesity measurements between the categories of semen parameters were compared using Mann Whitney U test. Descriptive values were given as mean ± standard deviation and median. P-value < 0.05 was considered statistically significant.

Receiver Operating Characteristics (ROC) curve analysis was applied to predictive performance of obesity indices for low semen parameters. The area under the curve (AUROC) was calculated with 95% confidence intervals. The optimum cut-off values of obesity indices obtained by Youden index. The determined cut-off values, sensitivity and specificity were calculated with 95% confidence intervals. P-value < 0.05 was considered statistically significant.

The associations between the categories of semen parameters and obesity indices were analyzed by binary logistic regression analysis after adjusting confounding factors. The associations of BMI with semen parameters were assessed after adjusting for age and smoking status. The associations of central obesity indices with semen parameters were evaluated after adjusting for age, smoking status and BMI. Odds ratios were calculated with 95% confidence intervals. P-value < 0.10 was considered statistically significant.

The Associations of Age and Anthropometric Obesity Indices with Semen Parameters

The average age of the participants included in the study was 29.6 years, ranged from 17-55. The mean, standard deviation and median values of age, anthropometric obesity indices and semen parameters of participants are summarized in Table 1. Table 2 demonstrates age and obesity indices of participants according to the categories of semen parameters. Age, BMI and all central obesity indices showed significantly differences between the categories of low and normal semen parameters for all semen parameters; the participants with lower parameters had higher values than those with normal parameters.

The Predictive Performance of Anthropometric Obesity Indices for Low Semen Parameters

Table 3 demonstrates the predictive potentials of anthropometric obesity indices for low semen parameters, analyzed by ROC curve. BMI, WC, HC, WHtR and NC were able to identify low sperm concentration, but WHpR could not. AUCs of BMI, WC, HC, WHtR and NC for low sperm concentration were 0.534 (p = 0.001), 0.539 (p < 0.001), 0.549 (p < 0.001), 0.535 (p < 0.001), 0.518 (p = 0.05), respectively. The cut-off values of BMI, WC, HC, WHtR and NC for sperm concentration were 25.71, 97.5, 104.5, 0.54 and 40.5 with a sensitivity/specificity of 52.4/52.6%, 52.5/53%, 52.2/56.6%, 52.4/52.6% and 46.4/55.4% respectively. All obesity indices were able to identify low total sperm count, total motility, progressive motility and vitality. AUCs of BMI, WC, HC, WHpR, WHtR and NC for low total sperm count were 0.535 (p < 0.001), 0.544 (p < 0.001), 0.544 (p < 0.001), 0.523 (p = 0.02), 0.545 (p < 0.001), 0.523 (p = 0.017), respectively. The cut-off values of BMI, WC, HC, WHpR, WHtR and NC for total count were 25.71, 97.5, 104.5, 0.92, 0.54 and 40.5 with a sensitivity/specificity of 52.3/52.5%, 52.2/53.3%, 51.9/56.2%, 51.1/51.2%, 53.2/53.3%, 47.8/56.2%, respectively. AUCs of BMI, WC, HC, WHpR, WHtR and NC for low total sperm motility were 0.560 (p < 0.001), 0.563 (p < 0.001), 0.557 (p < 0.001), 0.544 (p = 0.001), 0.569 (p < 0.001), 0.542 (p = 0.001), respectively. The cut-off values of BMI, WC, HC, WHpR, WHtR and NC for total motility were 25.95, 97.5, 104.5, 0.92, 0.55 and 40.5 with a sensitivity/specificity of 54.5/55%, 52.5/58.6%, 53.5/54.2%, 52.2/53.1%, 55.2/55.7%, 50.3/55.6%, respectively. AUCs of BMI, WC, HC, WHpR, WHtR and NC for low progressive sperm motility were 0.559 (p < 0.001), 0.563 (p < 0.001), 0.559 (p < 0.001), 0.535 (p = 0.002), 0.570 (p < 0.001), 0.532 (p = 0.005), respectively. The cut-off values of BMI, WC, HC, WHpR, WHtR and NC for progressive motility were 25.93, 97.5, 104.5, 0.92, 0.55 and 40.5 with a sensitivity/specificity of 54.6/54.7%, 52.2/59.3%, 54/54.9%, 51.2/53.2%, 55.4/55.5%, 48.9/55.6%, respectively. AUCs of BMI, WC, HC, WHpR, WHtR and NC for low sperm vitality were 0.562 (p < 0.001), 0.565 (p < 0.001), 0.553 (p < 0.001), 0.546 (p < 0.001), 0.572 (p < 0.001), 0.528 (p = 0.017), respectively. The cut-off values of BMI, WC, HC, WHpR, WHtR and NC for vitality were 25.95, 97.5, 104.5, 0.92, 0.55 and 40.5 with a sensitivity/specificity of 55.4/55.5%, 52.8/59.2%, 51.6/55.9%, 51.9/53 %, 55.7/56%, 49.2/54.6%, respectively. WC, WHpR, WHtR and NC were able to identify low rapid progressive sperm motility, but BMI and HC could not. AUCs of WC, WHpR, WHtR and NC for low rapid progressive sperm motility were 0.561 (p < 0.001), 0.605 (p < 0.001), 0.568 (p < 0.001), 0.587 (p < 0.001), respectively. The cut-off values of WC, WHpR, WHtR and NC for rapid progressive motility were 96.5, 0.92, 0.54 and 40.5 with a sensitivity/specificity of 52.8/56.5%, 57.4/58.6%, 54.4/54.7%, 51.6/65.1%, respectively.

However, although the AUC values, sensitivities and specificities of all obesity indices in predicting low sperm parameters were close, for sperm count parameters HC had relatively higher AUC values with higher specificity, while for vitality and motility parameters, except for rapid progressive motility, WHtR and WC had relatively higher AUC values, with higher sensitivity of WHtR and higher specificity of WC. For rapid progressive motility, higher AUC values of WHpR and NC, with higher sensitivity of WHpR, and higher specificity of NC were noted.

The Associations of Anthropometric Obesity Indices with Semen Parameters after Adjusting for Potential Confounding Factors

Binary logistic regression analysis showed that higher BMI was associated with lower semen parameters except for rapid progressive sperm motility when adjusted for age and smoking status (Table 4). It was found that sperm concentration was associated with WC and HC, total sperm count, total motility and progressive motility were associated with WC, HC and WHtR, rapid progressive motility was associated with WC, WHpR, WHtR and NC and sperm vitality was associated with WC and WHtR after adjusting for age, smoking status and BMI (Table 4). The patients with lower sperm concentration (< 15 M/ml) had a WC greater than 96.5 cm (OR: 1.23, 95% CI: 1.06-1.43, p=0.008) and a HC greater than104.5 cm (OR: 1.45, 95% CI: 1.26-1.68, p<.001). Lower total sperm count (< 39 M) was associated with a WC greater than 96.5 cm (OR: 1.26, 95% CI: 1.08-1.47, p=0.003), a HC greater than104.5 cm (OR: 1.34, 95% CI: 1.16-1.55, p<.001) and a WHtR greater than 0.54 (OR: 1.17, 95% CI: 1.01-1.37, p=0.04). Lower total sperm motility (< 40%) was associated with a WC greater than 97.5 cm (OR: 1.40, 95% CI: 1.14-1.71, p=0.001), a HC greater than104.5 cm (OR: 1.18, 95% CI: 0.9-1.43, p=0.089) and a WHtR greater than 0.55 (OR: 1.45, 95% CI: 1.18-1.78, p<.001). The patients with lower progressive sperm motility (< 32%) had a WC greater than 97.5 cm (OR: 1.33, 95% CI: 1.11-1.59, p=0.002), a HC greater than104.5 cm (OR: 1.16, 95% CI: 0.98-1.38, p=0.087) and a WHtR greater than 0.55 (OR: 1.35, 95% CI: 1.12-1.62, p=0.001). The patients with lower rapid progressive sperm motility (< 25%) had a WC greater than 96.5 cm (OR: 1.54, 95% CI: 1.32-1.80, p<.001), a WHpR greater than 0.92 (OR: 1.71, 95% CI: 1.51-1.95, p<.001), a WHtR greater than 0.54 (OR: 1.55, 95% CI: 1.33-1.81, p<.001) and a NC greater than 40.5 cm (OR: 2.37, 95% CI: 2.02-2.79, p<.001). Lower sperm vitality (< 58%) was associated with a WC greater than 97.5 cm (OR: 1.37, 95% CI: 1.14-1.64, p=0.001) and a WHtR greater than 0.55 (OR: 1.34, 95% CI: 1.12-1.62, p=0.002) (Table 4).

In the current study, we found that BMI and central obesity indices were negatively associated with all semen parameters and could identify low semen parameters except BMI and HC for rapid progressive motility and WHpR for sperm concentration. HC for sperm count parameters, WHtR and WC for vitality and motility parameters except rapid progressive motility, and WHpR and NC for rapid progressive motility had relatively higher predictive potentials. Furthermore, in our study, we evaluated the associations between the categories of obesity indices and semen parameters by logistic regression analysis after adjusting for potential confounders, including age, smoking status and BMI that known to be the related with obesity and semen quality. Our results showed that increased age caused to significantly decrease in all semen parameters, consistent with the results of other studies²⁴. BMI was associated with all semen parameters except for rapid progressive motility, after adjusting for age and smoking status. In addition, all of central obesity indices showed a significantly positive correlation with age and BMI. After adjustment for age, BMI and smoking status, it was observed that the associations of WC and HC with sperm concentration, WC, HC and WHtR with total sperm count, total motility, progressive motility and vitality, WC, WHpR, WHtR and NC with rapid progressive motility, persisted. The strongest associations were found between HC with sperm concentration and WC and WHtR with total count, total motility, progressive motility and vitality, and NC and WHpR with rapid progressive motility.

It was noteworthy according to our findings that WC, which is the best indicator of abdominal fat accumulation, was associated with all sperm parameters, independent of BMI. Previous studies have recognized a high WC as a risk factor for many health outcomes, including cardiovascular diseases, diabetes, and risk of all-cause mortality, independent of BMI²⁵. Furthermore, even if male BMI is normal, a larger male WC has been reported to be a risk factor for lower sperm concentration and poor outcomes of infertility treatment²⁶. In addition, a stronger negative correlation of WC, WHpR and WHtR with sperm parameters, than BMI has been shown, suggesting that central obesity indices are superior to BMI to predict semen quality¹². Our results revealed that the associations of central obesity indices with related-sperm parameters were stronger than those of BMI when adjusted for the same confounding factors. WC for all semen parameters, HC for sperm count parameters, WHtR for sperm vitality and motility parameters, including rapid progressive motility, and NC and WHpR for only rapid progressive motility was superior to BMI. One of the mechanisms of action of obesity on male reproductive functions is disruption of the balance between sex hormones. It is well known that particularly central adiposity leads to a decrease in plasma testosterone levels and an increase in plasma oestradiol levels^6,15,16,27, produced by aromatization of testosterone, primarily in abdominal fatty tissues. The stronger associations of WC and WHtR with most infertility markers than BMI may be explained by these hormonal alterations occur in abdominal fat. However, WHpR, unlike WHtR, was only associated with rapid progressive motility and exhibited superiority over other obesity indices only for this parameter. Height, a component of WHtR, likely has a role on sperm parameters to which WHtR is associated beyond WHpR.

Other notable findings of our study were that WC and WHtR had stronger associations with sperm vitality and motility parameters specifically, HC with sperm count parameters specifically, and WHpR and NC with rapid progressive motility only. Sperm progressive motility was negative correlated with WHtR^12,28 and WHpR^12,29, and sperm concentration was negative correlated with HC^12,28, according to recent researches that provide evidence consistent with our findings. The association of different obesity indices with certain fertility markers suggests that fat distribution may have different effects on sperm functions, which give different characteristics to sperm. Therefore, it seems that fat around the hip may especially impair testicular functions, which leads to a decrease in the number of sperm. The fat around the waist (and, by extension, WHtR and WHpR) and around the neck may especially impair post-testicular functions, which leads to deterioration in the motility characteristics of sperm. After spermatozoa are produced in the testicles, they acquire progressive motility and fertilizing abilities by taking in the fluids secreted by these ducts during their transfer from the ductus epididymis and other genital ducts and glands, known as the post-testicular maturation process. Another mechanism of impairment of testicular functions caused by obesity is heat-induced dis-spermatogenesis. Testicular temperature increases in obese men, and this is mainly due to fat accumulation in areas close to the testicles³⁰. This may explain how a large HC disrupts spermatogenesis and testicular functions, leading to a decrease in sperm concentration. We believe that there are different types of factors related to hip, waist, and neck fat that may specifically influence different fertility markers. However, the impact of obesity on male reproductive functions is not limited to these. Obesity also causes oxidative stress, induces systemic inflammation and apoptosis, and promotes epigenetic modifications that can be transmitted to offspring³¹.

NC, a novel index of central obesity, has a unique association with many health problems, independent of other adiposity indices^19–21,32. The cross-sectional and cohort studies have suggested that large NC may predict cardiovascular risk factors, even all-cause mortality, in both sexs^33,34. Wan et al. have demonstrated that among central obesity indices, only NC was associated with the prevalence of common carotid artery plaque, independently of BMI²⁰. NC has also been found to associate with metabolic syndrome, independently of WC or BMI¹⁹. Moreover, NC has been proved to be strong predictor of obstructive sleep apnea, a common disease associated with obesity and metabolic disorder, even in individuals without obesity³². Most of these associations were found to be stronger in men than in women, suggesting additional factors specific to neck fat in particularly men. However, there are few studies on the relationship of NC with female reproductive functions and infertility, but no studies on men. A study on premenopausal women has been reported that NC is a good predictive measure for menstrual irregularity, hirsutism, infertility, insulin resistance and PCOS³⁵. Increasing evidence shows that male fertility ability is associated with increased risk of many health problems, and that male infertility can be a predictor of overall health³⁶. In males, hypogonadism is considered as a common feature of obesity and metabolic syndrome, further increasing the risk for infertility³⁷. The unique association between NC and many health outcomes leading to further increase risk of male infertility raised the question of whether NC may also be a predictive factor for male infertility. To answer this question, we investigated for the first time the associations of NC with semen parameters and showed that although NC could identify all low semen parameters, it was associated with only rapid progressive sperm motility after adjusting for confounding factors. Moreover, the association of NC with rapid progressive motility is stronger than all other obesity indices, suggesting superiority of NC over other central obesity indices for this parameter. The association between neck fat and metabolic syndrome and its components has been attributed to excess release of free fatty acids into plasma from the upper body subcutaneous fat by lipolytic activity, which leads to oxidative stress and insulin resistance³⁸. However, the potential underlying mechanisms by which excess neck fat impairs sperm functions need to be investigated. Rapid progressive motility is a highly specialized and important function of sperm, acquired during the post-testicular maturation process and the fertilizing capacity of sperm mainly depends on this function. Neck fat-related some factors may play an important role in the maturation process, influencing some, but not all fertility markers. A study has reported that the fat content of the android region is significantly higher in boys and girls with a larger NC and suggested that NC is a predictive factor for excess android fat³⁹. According to the current study, the poor semen quality of individuals with a large NC may be related to the excessive android fat content of these individuals. Limitations of the current study are that the fat distribution was not determined by more precise methods such as computed tomography or MRI. It may be important to determine the relationship between the especially amount of fat in the android region and semen quality. Additionally, semen volume and sperm morphology were not included in the study. The mechanisms by which obesity impairs male reproductive function are many and complex and further studies are needed to fully elucidate the exact mechanisms.

Our study demonstrates that obesity, particularly central obesity, plays an important role in male infertility. There is no consensus in the literature about individual sperm parameters affected by obesity-related markers. Central obesity indices appear to be superior to BMI for certain sperm parameters in predicting semen quality. It is noteworthy after adjusting for potential confounders, that WC and WHtR had stronger associations with sperm vitality and motility parameters specifically, HC with sperm count parameters specifically, and WHpR and NC with rapid progressive motility only. This suggests that fat distribution may have specific roles on sperm functions, resulting in different fertility markers may be affected. A larger NC, a novel index of central obesity, is a risk factor for low sperm progressive motility, suggesting the possible role of some type of neck fat-related factor that may specifically influence this parameter. However, the potential mechanisms by which neck fat impairs sperm function need to be further investigated.

Conflict of interest

There is no any conflict of interest as financial or other potential interests that could be perceived to undermine the objectivity of the research.

Acknowledgements

I would like to thank Assist. Prof. Kazım Muslu Körez from Selcuk University, Faculty of Medicine, Department of Biostatistics, for his contributions to the statistical analysis of the study.

Thoma ME, McLain AC, Louis JF, King RB, Trumble AC, Sundaram R, et al. Prevalence of infertility in the United States as estimated by the current duration approach and a traditional constructed approach. Fertil Steril 2013;99:1324–31.e1. doi: 10.1016/j.fertnstert.2012.11.037.
Diagnostic evaluation of the infertile male: a committee opinion. Fertil Steril 2015;103:e18–25. doi: 10.1016/j.fertnstert.2014.12.103.
Chooi YC, Ding C, Magkos F. The epidemiology of obesity. Metab Clin Exp 2019;92:6–10. doi: 10.1016/j.metabol.2018.09.005.
Rolland M, Le Moal J, Wagner V, Royère D, De Mouzon J. Decline in semen concentration and morphology in a sample of 26 609 men close to general population between 1989 and 2005 in France. Hum Reprod 2013;28:462–470. doi: 10.1093/humrep/des415.
Cheng JYW, Ng EM. Body mass index, physical activity and erectile dysfunction: an U-shaped relationship from population-based study. Int J Obes 2007;31(10):1571–8. doi: 10.1038/sj.ijo.0803639. doi: 10.1038/sj.ijo.0803639.
Salas-Huetos A, Maghsoumi-Norouzabad L, James ER, Carrell DT,Aston KI, Jenkins TG, Becerra-Tomas N, Javid AZ, Abed R, Torres PJ,et al. Male adiposity, sperm parameters and reproductive hormones: anupdated systematic review and collaborative meta-analysis. Obes Rev 2021;22(1):e13082. doi:10.1111/obr.13082.18.
Nguyen RHN, Wilcox AJ, Rolv S, Baird DD. Men’s body mass index and infertility. Hum Reprod 2007;(9):9. doi: 10.1093/humrep/dem139.
WHO. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser 2000:894:i-xii, 1-253.
Lee SW, Son JY, Kim JM, Hwang SS, Han JS, Heo NJ. Body fat distribution is more predictive of all-cause mortality than overall adiposity. Diabetes Obes Metab 2018;20(1):141–7. doi: 10.1111/dom.13050.
Neeland IJ, Ross R, Després J-P, Matsuzawa Y, Yamashita S, ShaiI, Seidell J, et al. Visceral and ectopic fat, atherosclerosis, and cardiometabolic disease: a position statement. Lancet Diabetes Endocrinol 2019;7(9):715–25. doi: 10.1016/S2213-8587(19)30084-1.
Okorodudu D, Jumean M, Montori VM, Romero-Corral A, Somers V, Erwin, P, et al. Diagnostic performance of body mass index to identify obesity as defined by body adiposity: A systematic review and meta-analysis. Int J Obes (Lond) 2010;34(5):791–9. doi: 10.1038/ijo.2010.5.
Ma JX, Wang B, Li HS, Jiang XJ, Yu J, Ding CF, et al. Association between obesity-associated markers and semen quality parameters and serum reproductive hormones in Chinese infertile men. Reprod Biol Endocrinol 2020;29;18(1):95. doi: 10.1186/s12958-020-00652-6.
Belloc S, Cohen-Bacrie M, Amar E, Izard V, Benkhalifa M, Dalléac A, et al. High body mass index has a deleterious effect on semen parameters except morphology: Results from a large cohort study. Fertil Steril 2014;102(5):1268–1273. https://doi.org/10.1016/j.fertnstert.2014.07.1212
Tsao CW, Liu CY, Chou YC, Cha TL, Chen SC, Hsu CY. Exploration of the association between obesity and semen quality in a 7630 male population. PLoS One 2015;10(3):e0119458. doi: 10.1371/journal.pone.0119458.
Lu JC, Jing J, Dai JY, Zhao AZ, Yao Q, Fan K, et al. Body mass index, waist to-hip ratio, waist circumference and waist-to-height ratio cannot predict male semen quality: A report of 1231 subfertile Chinese men. Andrologia 2015;47(9):1047–1054. https://doi.org/10.1111/and.12376.
Al-Ali M, Gutschi T, Pummer K, Zigeuner R, Brookman-May S, Wieland WF, et al. Body mass index has no impact on sperm quality but on reproductive hormones levels. Andrologia 2014:46(2):106–111. https://doi.org/10.1111/and.12051.
Zhao L, Huang G, Xia F, Li Q, Han B, Chen Y, et al. Neck circumference as an independent indicator of visceral obesity in a Chinese population. Lipids Health Dis. 2018;17(1):85. doi: 10.1186/s12944-018-0739-z.
Yang GR, Yuan SY, Fu HJ, Wan G, Zhu LX, Bu XL, et al. Neck circumference positively related with central obesity, overweight, and metabolic syndrome in Chinese subjects with type 2 diabetes: Beijing Community Diabetes Study 4. Diabetes Care 2010;33(11):2465–7. doi: 10.2337/dc10-0798. Epub 2010 Aug 19.
Onat A, Hergenç G, Yüksel H, Can G, Ayhan E, Kaya Z, et al. Neck circumference as a measure of central obesity: associations with metabolic syndrome and obstructive sleep apnea syndrome beyond waist circumference. Clin Nutr 2009;28:46–51. doi: 10.1016/j.clnu.2008.10.006. Epub 2008 Nov 17.
Wan H, Wang Y, Xiang Q, Fang S, Chen Y, Chen C, et al. Associations between abdominal obesity indices and diabetic complications: Chinese visceral adiposity index and neck circumference. Cardiovasc Diabetol 2020;31;19(1):118. doi: 10.1186/s12933-020-01095-4.
Vallianou NG, Evangelopoulos AA, Bountziouka V, Vogiatzakis ED, Bonou MS, Barbetseas J, et al. Neck circumference is correlated with triglycerides and inversely related with HDL cholesterol beyond BMI and waist circumference. Diabetes Metab Res Rev 29:90–97. doi: 10.1002/dmrr.2369.
Joshipura K, Munoz-Torres F, Vergara J, Palacios C, Perez CM. Neck circumference may be a better alternative to standard anthropometric measures. J Diabetes Res 2016:6058916. doi: 10.1155/2016/6058916.
World Health Organization. WHO laboratory manual for the examination and processing of human semen. 5th ed; Geneva, Switzerland, 2010.
Paasch U, Grunewald S, Kratzsch J, Glander HJ. Obesity and age affect male fertility potential. Fertil Steril 2010;94:2898–2901. doi: 10.1016/j.fertnstert.2010.06.047.
Zhang C, Rexrode KM, Van Dam RM, Li TY, Hu FB. Abdominal obesity and the risk of all-cause, cardiovascular, and cancer mortality. Circulation 2008;117(13):1658–67. doi: 10.1161/CIRCULATIONAHA.107.739714.
Bian H, Mínguez- Alarcón L, Salas-Huetos A, Bauer D, Williams PL, Souter I, et al. Male waist circumference in relation to semen quality and partner infertility treatment outcomes among couples undergoing infertility treatment with assisted reproductive technologies. Am J Clin Nutr 2022;115(3):833–842. https://doi.org/10.1093/ajcn/nqab364
Haffner SM. Sex hormones, obesity, fat distribution, type 2 diabetes and insulin resistance: epidemiological and clinical correlation. Int J Obes Relat Metab Disord 2000;24(2):S56-8. doi: 10.1038/sj.ijo.0801279.
Esmaeili V, Zendehdel M, Shahverdi A, Alizadeh AR. Relationship between obesity-related markers, biochemical metabolic parameters, hormonal profiles and sperm parameters among men attending an infertility clinic. Andrologia 2022;54(10):e14524. doi: 10.1111/and.14524. Epub 2022 Jul 19.
Keszthelyi M, Gyarmathy VA, Kaposi A, Kopa Z. The potential role of central obesity in male infertility: Body mass index versus waist to hip ratio as they relate to selected semen parameters. BMC Public Health 2020;20(1):307. https://doi.org/10.1186/s12889-020-8413-6
Liu Y, Ding Z. Obesity, a serious etiologic factor for male subfertility in modern society. Reproduction 2017;154:123–131. doi: 10.1530/REP-17-0161.
Hu Q, Lu Y, Hu F, He S, Xu X, Niu Y, et al. Resistant dextrin reduces obesity and attenuates adipose tissue inflammation in high-fat diet-fed mice. Int J Med Sci 2020;17:2611–2621. doi: 10.7150/ijms.45723.
Mortimore I, Marshall I, Wraith P, Sellar R, Douglas N. Neck and total body fat deposition in non obese and obese patients with sleep apnea compared with that in control subjects. Am J Respir Crit Care Med 1998;157:280–3. doi: 10.1164/ajrccm.157.1.9703018.
Dai Y, Wan X, Li X, Jin E, Li X. Neck circumference and future cardiovascular events in a high-risk population—a prospective cohort study. Lipids Health Dis. 2016;5:15:46. doi: 10.1186/s12944-016-0218-3.
Coelho HJJ, Sampaio RA, Goncalvez IO, Aguiar SD, Palmeira R, Oliveira JF, et al. Cutoffs and cardiovascular risk factors associated with neck circumference among community-dwelling elderly adults: a cross-sectional study. Sao Paulo Med J 2016;134(6):519–27. doi: 10.1590/1516-3180.2016.0160110906.
Dixon JB and O’Brien PE. Neck circumference a good predictor of raised insulin and free androgen index in obese premenopausal women: changes with weight loss. Clin Endocrinol (Oxf) 2002;57(6):769–78. doi: 10.1046/j.1365-2265.2002.01665.x.
Choy JT and Eisenberg ML. Male infertility as a window to health. Fertil Steril 2018;110(5):810–814. doi: 10.1016/j.fertnstert.2018.08.015.
Du Plessis SS, Cabler S, McAlister DA, Sabanegh E, Agarwal A. The effect of obesity on sperm disorders and male infertility. Nat Rev Urol 2010;7(3):153–61. doi:10.1038/nrurol.2010.6. Epub 2010 Feb 16.
Inoguchi T, Li P, Umeda F, Yu HY, Kakimoto M, Imamura M, et al. High glucose level and free fatty acid stimulate reactive oxygen species production through protein kinase C-dependent activation of NAD(P)H oxidase in cultured vascular cells. Diabetes 2000;49(11):1939–45. doi: 10.2337/diabetes.49.11.1939.
Filgueiras MS, Albuquerque FM, Castro APP, Rocha NP, Milagres LC, Novaes JF. Neck circumference cutoff points to identify excess android fat. J Pediatr (Rio J) 2020;96(3):356–363. doi: 10.1016/j.jped.2018.11.009.

Table 1. Age, anthropometric obesity indices and semen parameters of participants

Variable	N	Mean ± SD	Median
Age (years)	4739	29,64 ± 6,67	29
BMI (kg/m²)	4739	25,93 ± 4,37	25,60
WC (cm)	4739	95,64 ± 11,45	95
HC (cm)	4739	104,08 ± 9,17	104
WHpR	4739	0,92 ± 0,06	0,92
WHtR	4739	0,54 ± 0,06	0,54
NC (cm)	3665	39,99 ± 3,20	40
Semen Volume (ml)	4739	3,32 ± 1,49	3
Sperm Concentration (10⁶ per ml)	4739	32,99 ± 33,06	23
Total Sperm Count (10⁶ per ejaculate)	4739	108,09 ± 120,08	70
Total Sperm Motility (%)	4739	57,55 ± 24,09	65
Progressive Sperm Motility (%)	4739	43,75 ± 20,49	48
Rapid Progressive Sperm Motility (%)	4739	4,89 ± 5,27	3
Sperm Vitality (%)	4438	41,65 ± 29,79	45

Table 2. Age and anthropometric obesity indices of participants according to the categories of semen parameters

Age (years)

BMI (kg/m²)

WC (cm)

HC (cm)

WHpR

WHtR

NC (cm)

Mean ± SD (Median)

Sperm Concentration

≥ 15 M/ml

29,12±6,66 (28)

2872

25,69±4,32 (25,38)

2872

94,75±11,07 (94)

2872

103,38±9,0 (102)

2872

0,91±0,06 (0,92)

2872

0,54±0,06 (0,54)

2872

39,89±3,1 (40)

2159

< 15 M/ml

30,45±6,66 (30)

1867

26,28±4,40 (25,95)

1867

97,03±11,87 (97)

1867

105,16±9,32 (104)

1867

0,92±0,06 (0,92)

1867

0,55±0,07 (0,55)

1867

40,13±3,34 (40)

1506

Total

29,64±6,67 (29)

4739

25,93 ± 4,37 (25,60)

4739

95,64 ± 11,45 (95)

4739

104,08 ± 9,17 (104)

4739

0,92 ± 0,06 (0,92)

4739

0,54 ± 0,06 (054)

4739

39,99 ± 3,2 (40)

3665

p-value

<.001

0.002

<.001

0.05

Total Sperm Count

≥ 39 M

29,08±6,59 (28)

2928

25,65±4,29 (25,34)

2928

94,63±11,07 (94)

2928

103,39±8,96 (102)

2928

0,91±0,06 (0,92)

2928

0,54±0,06 (0,53)

2928

39,87±3,1 (40)

2214

< 39 M

30,55±6,69 (30)

1811

26,37±4,55 (26,02)

1811

97,28±11,85 (97)

1811

105,2±9,41 (104)

1811

0,92±0,06 (0,92)

1811

0,55±0,06 (0,55)

1811

40,16±3,34 (40)

1451

Total

29,64±6,67 (29)

4739

25,93 ± 4,37 (25,60)

4739

95,64 ± 11,45 (95)

4739

104,08 ± 9,17 (104)

4739

0,92 ± 0,06 (0,92)

4739

0,54 ± 0,06 (054)

4739

39,99 ± 3,2 (40)

3665

p-value

<.001

0.017

Total Sperm Motility

≥ %40

29,3±6,6 (29)

3966

25,78±4,38 (25,46)

3966

95,16±11,28 (94)

3966

103,78±9,18 (103)

3966

0,92±0,06 (0,92)

3966

0,54±0,06 (0,54)

3966

39,91±3,17 (40)

3070

< %40

31,43±6,7 (31)

773

26,63±4,22 (26,36)

773

98,15±11,96 (98)

773

105,63±8,97 (105)

773

0,93±0,06 (0,93)

773

0,56±0,06 (0,56)

773

40,39±3,32 (41)

595

Total

29,64±6,67 (29)

4739

25,93 ± 4,37 (25,60)

4739

95,64 ± 11,45 (95)

4739

104,08 ± 9,17 (104)

4739

0,92 ± 0,06 (0,92)

4739

0,54 ± 0,06 (054)

4739

39,99 ± 3,2 (40)

3665

p-value

<.001

0.001

Progressive Sperm Motility

≥ %32

29,16±6,58 (29)

3694

25,73±4,37 (25,39)

3694

95,05±11,29 (94)

3694

103,7±9,17 (103)

3694

0,91±0,06 (0,92)

3694

0,54±0,06 (0,54)

3694

39,91±3,17 (40)

2873

< %32

31,37±6,69 (31)

1045

26,59±4,27 (26,29)

1045

97,75±11,77 (97)

1045

105,44±9,06 (105)

1045

0,92±0,06 (0,93)

1045

0,56±0,06 (0,55)

1045

40,27±3,3 (40)

792

Total

29,64±6,67 (29)

4739

25,93 ± 4,37 (25,60)

4739

95,64 ± 11,45 (95)

4739

104,08 ± 9,17 (104)

4739

0,92 ± 0,06 (0,92)

4739

0,54 ± 0,06 (0,54)

4739

39,99 ± 3,2 (40)

3665

p-value

<.001

0.005

Rapid Progressive Sperm Motility

≥ %25

28,99±6,4 (28)

1900

25,77±4,54 (25,35)

1900

94,22±11,57 (94)

1900

103,84±9,56 (103)

1900

0,91±0,06 (0,91)

1900

0,53±0,07 (0,53)

1900

39,39±3,0 (39)

1373

< %25

30,01±6,79 (29)

2839

26,04±4,24 (25,71)

2839

96,6±11,24 (96)

2839

104,26±8,89 (104)

2839

0,92±0,06 (0,93)

2839

0,55±0,06 (0,554

2839

40,35±3,26 (41)

2292

Total

29,64±6,67 (29)

4749

25,93 ± 4,36 (25,60)

4739

95,65 ± 11,43 (95)

4739

104,09 ± 9,16 (104)

4739

0,92 ± 0,06 (0,92)

4739

0,54 ± 0,06 (0,54)

4739

39,99 ± 3,2 (40)

3665

p-value

<.001

0.004

<.001

0.05

<.001

Sperm Vitality

≥ %58

29,1±6,55 (29)

3363

25,68±4,23 (25,38)

3363

95,0±11,02 (94)

3363

103,47±8,9 (103)

3363

0,92±0,06 (0,92)

3363

0,54±0,06 (0,54)

3363

39,97±3,15 (40)

2571

< %58

31,32±6,69 (31)

1075

26,56±4,33 (26,23)

1075

97,71±11,82 (97)

1075

105,14±9,15 (104)

1075

0,93±0,06 (0,93)

1075

0,56±0,07 (0,55)

1075

40,28±3,38 (40)

798

Total

29,64±6,66 (29)

4438

25,89 ± 4,27 (25,6)

4438

95,66 ± 11,27 (95)

4438

103,87 ± 8,99 (103)

4438

0,92 ± 0,06 (0,92)

4438

0,54 ± 0,06 (0,54)

4438

40,02±3,21 (40)

3369

p-value

<.001

0.018

P-value < 0.05 was considered statistically significant.

Table 3. The predictive performance of anthropometric obesity indices for low semen parameters

		ROC Curve Analysis			Statistical Diagnostic Measures (95% CIs)
		AUC (95% CI)	p-value	Cut-off	Sensitivity	Specificity
Sperm Concentration	BMI	0.534 (0.515– 0.552)	0.001	> 25.71	52.4	52.6
	WC	0.539 (0.520 – 0.558)	<.001	> 96.5	52.5	53.0
	HC	0.549 (0.530– 0.568)	<.001	> 104.5	52.2	56.6
	WHpR	0.511 (0.492 – 0.530)	> 0.05	–	–	–
	WHtR	0.535 (0.516 – 0.554)	<.001	> 0.54	52.4	52.6
	NC	0.518 (0.499 – 0.537)	0.05	> 40.5	46.4	55.4
Total Sperm Count	BMI	0.535 (0.516 – 0.554)	<.001	> 25.71	52.3	52.5
	WC	0.544 (0.525 – 0.563)	<.001	> 96.5	53.2	53.3
	HC	0.544 (0.525 – 0.564)	<.001	> 104.5	51.9	56.2
	WHpR	0.523 (0.504 – 0.542)	0.02	> 0.92	51.1	51.2
	WHtR	0.545 (0.526 – 0.564)	<.001	> 0.54	53.2	53.3
	NC	0.523 (0.504 – 0.543)	0.017	> 40.5	47.8	56.2
Total Sperm Motility	BMI	0.560 (0.535 – 0.584)	<.001	> 25.95	54.5	55.0
	WC	0.563 (0.537 – 0.589)	<.001	> 97.5	52.5	58.6
	HC	0.557 (0.533– 0.582)	<.001	> 104.5	53.5	54.2
	WHpR	0.544 (0.518 – 0.570)	.001	> 0.92	52.2	53.1
	WHtR	0.569 (0.543 – 0.594)	<.001	> 0.55	55.2	55.7
	NC	0.542 (0.516 – 0.567)	.001	> 40.5	50.3	55.6
Progressive Sperm Motility	BMI	0.559 (0.537 – 0.581)	<.001	> 25.93	54.6	54.7
	WC	0.563 (0.541 – 0.586)	<.001	> 97.5	52.2	59.3
	HC	0.559 (0.537 – 0.581)	<.001	>104.5	54.0	54.9
	WHpR	0.535 (0.512 – 0.559)	.002	> 0.92	51.2	53.2
	WHtR	0.570 (0.547 – 0.593)	<.001	> 0.55	55.4	55.5
	NC	0.532 (0.509 – 0.555)	.005	> 40.5	48.9	55.6
Rapid Progressive Sperm Motility	BMI	0.513 (0.494 – 0.532)	> 0.05	-	-	-
	WC	0.561 (0.541 – 0.580)	<.001	> 96.5	52.8	56.5
	HC	0.500 (0.480 – 0.519)	> 0.05	-	-	-
	WHpR	0.605 (0.586 – 0.624)	<.001	> 0.92	57.4	58.6
	WHtR	0.568 (0.549 – 0.588)	<.001	> 0.54	54.4	54.7
	NC	0.587 (0.568 – 0.606)	<.001	> 40.5	51.6	65.1
Sperm Vitality	BMI	0.562 (0.540 – 0.585)	<.001	> 25.95	55.4	55.5
	WC	0.565 (0.542 – 0.588)	<.001	> 97.5	52.8	59.6
	HC	0.553 (0.530 – 0.576)	<.001	> 104.5	51.6	55.9
	WHpR	0.546 (0.523 – 0.569)	<.001	> 0.92	52.9	53.0
	WHtR	0.572 (0.549 – 0.595)	<.001	> 0.55	55.7	56.0
	NC	0.528 (0.505 – 0.551)	.017	> 40.5	49.2	54.6

P-value < 0.05 was considered statistically significant.

Table 4. The Associations of Anthropometric Obesity Indices with Semen Parameters after Adjustment Potential Confounding Factors

Semen Parameters	Anthropometric Obesity Indices	OR	95% Confidence Intervals	p-value
Sperm Concentration (≥ 15 M/ml vs. < 15 M/ml)	BMI	1.020	1.006 – 1.034	0.005*
	WC	1.229	1.056 – 1.430	.008
	HC	1.453	1.256 – 1.681	<.001
	WHpR	1.004	0.888 – 1.137	>.10
	WHtR	1.121	0.963 – 1.304	>.10
	NC	0.940	0.809 – 1.091	>.10
Total Sperm Count (≥ 39 M vs. < 39 M)	BMI	1.025	1.011 – 1.039	<.001*
	WC	1.259	1.081 – 1.466	.003
	HC	1.343	1.160 – 1.554	<.001
	WHpR	1.047	0.925 – 1.186	>.10
	WHtR	1.173	1.008 – 1.367	.04
	NC	1.041	0.896 – 1.210	>.10
Total Sperm Motility (≥ %40 vs. < %40)	BMI	1.022	1.004 – 1.040	0.017*
	WC	1.396	1.143 – 1.707	.001
	HC	1.183	0.975 – 1.435	0.089
	WHpR	1.072	0.906 – 1.268	>.10
	WHtR	1.451	1.182 – 1.781	<.001
	NC	1.046	0.854 – 1.281	>.10
Progressive Sperm Motility (≥ %32 vs. < %32)	BMI	1.023	1.007 – 1.040	0.006*
	WC	1.331	1.112 – 1.593	.002
	HC	1.163	0.978 – 1.383	0.087
	WHpR	1.016	0.874 – 1.180	>.10
	WHtR	1.347	1.122– 1.618	.001
	NC	0.968	0.806 – 1.161	>.10
Rapid Progressive Sperm Motility (≥ %25 vs. < %25)	BMI	1.003	0.989 – 1.017	>.10*
	WC	1.542	1.322 – 1.798	<.001
	HC	0.887	0.763 – 1.030	>.10
	WHpR	1.715	1.510 – 1.948	<.001
	WHtR	1.551	1.326 – 1.813	<.001
	NC	2.373	2.020 – 2.787	<.001
Sperm Vitality (≥ %58 vs. < %58)	BMI	1.025	1.009 – 1.043	0.003*
	WC	1.371	1.143 – 1.644	.001
	HC	1.078	0.905 – 1.285	>.10
	WHpR	1.038	0.893 – 1.206	>.10
	WHtR	1.343	1.116– 1.616	.002
	NC	0.899	0.747 – 1.081	>.10

P values are adjusted for age, smoking status and BMI. P-value < 0.10 was considered statistically significant. *P values are adjusted for age and smoking status.

There is NO conflict of interest to disclose

Download PDF

Version 1

posted

You are reading this latest preprint version

Is a Large Neck Circumference a Risk Factor for Male Infertility in the Turkish Population?

Status:

Version 1

Abstract

Background

Objective

Subjects and Methods:

Results

Conclusions

INDRODUCTION

SUBJECTS AND METHODS

Study Population

Semen Analysis

Anthropometric Measurements

Statistical Analysis

RESULTS

DISCUSSION

CONCLUSIONS

Declarations

Conflict of interest

References

Tables

Additional Declarations

Status:

Version 1