Self-reported Male Infertility and Metabolic Disturbance: A Cross-Sectional Study


avatar Mahbanoo Farhadi-Azar ORCID 1 , avatar Marzieh Saei Ghare Naz ORCID 1 , avatar Mehrdad Ghahremani ORCID 2 , avatar Maryam Mousavi ORCID 1 , 3 , avatar Fereidoun Azizi ORCID 4 , avatar Fahimeh Ramezani Tehrani ORCID 1 , *

Reproductive Endocrinology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Education Program in Reproduction and Development, Department of Obstetrics and Gynecology, Monash University, Melbourne, VIC, Australia
Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

how to cite: Farhadi-Azar M, Saei Ghare Naz M, Ghahremani M, Mousavi M, Azizi F, et al. Self-reported Male Infertility and Metabolic Disturbance: A Cross-Sectional Study. Int J Endocrinol Metab. 2023;21(2):e134895.



Male infertility is a growing health problem. It is proposed that infertility is associated with some metabolic abnormalities.


This study aimed to examine the prevalence of self-reported male infertility and related metabolic disturbances.


This is a cross-sectional analysis of the Tehran Lipid and Glucose Study (TLGS). A total of 1526 males participated in the study. Logistic regression was used to examine metabolic factors associated with self-reported male infertility.


The total prevalence of self-reported male infertility was 6.42%. The mean (SD) body mass index (BMI) of participants among fertile and infertile males was 26.80 (3.93) and 26.92 (4.36), respectively. The majority of participants in both groups were in the age group of 40-50 years old. In the fully adjusted model, the odds of infertility were significantly increased by each unit increase in total cholesterol [TC; odds ratio (OR), 1.01; 95% CI, 1.01 - 1.01; P = 0.03] and hip circumference (HC; OR, 1.06; 95% CI, 1.00 - 1.12; P = 0.02), respectively.


The prevalence of self-reported male infertility was 6.42%. Male infertility was positively associated with TC and HC, indicating that knowledge about these risks might assist health care professionals and governments in developing and executing measures to change the status quo.

1. Background

Infertility is a common health concern around the world. Infertility is the failure to conceive after at least a year of regular unprotected sexual intercourse (1, 2). It is estimated that more than 186 million people worldwide are infertile (3). According to a recent meta-analysis of population-based studies, the overall prevalence of infertility was 7.88% among the Iranian population (4). In a study, the prevalence of infertility was reported at 24.58% among the Chinese population (5). Male factors are the primary cause of infertility in approximately one-third of couples (1, 2). According to the study by Agarwal et al., the prevalence of male infertility in Sub-Saharan Africa was (2.5% to 4.8%), followed by Central/Eastern Europe (8% to 12%), North America (4.5% to 6%), and Australia (8% to 9%) (6).

Various factors can influence male fertility, of which some factors have been reported as possible causes and risk factors, including biological, physiological, genetic, behavioral/lifestyle, environmental, and sociodemographic risk factors (7). Furthermore, it has been shown that there is a strong link between metabolic abnormality and infertility (8, 9). Infertility and metabolic syndrome (MetS) share a common risk factor (10). The production of reactive oxygen species (ROS) and increased oxidative stress (OS), endothelial dysfunction, and altered semen quality might be occurred due to metabolic abnormality (10).

Although several studies have reported the prevalence of male infertility, most have been conducted on the population who referred to infertility centers (11-13). Furthermore, there is limited evidence among the Iranian population that highly focuses on the metabolic determinants of male infertility. Hence, our study aimed to investigate the prevalence and metabolic determinants of self-reported male infertility among participants in the Tehran Lipid and Glucose Study (TLGS).

2. Objectives

This study aimed to examine the prevalence of self-reported male infertility and related metabolic disturbance.

3. Methods

3.1. Ethics Approval

This study was approved by the Medical Ethics Committee of the Endocrine Sciences Research Institute, Shahid Beheshti University of Medical Sciences (code: IR.SBMU.ENDOCRINE.REC.1398.007). Written informed consent was obtained from all participants.

3.2. Subjects

Participants were selected from the TLGS. TLGS is a cohort study conducted to evaluate the prevalence and associated factors for non-communicable conditions. There are previously published details of TLGS (14-16). The current study employed data from the sixth visit of the TLGS (2015 - 2018), comprising detailed information on individuals' fertility status (16).

Inclusion criteria included individuals who had been married or had not documented female infertility. The fertility information of 1881 fertile females was matched with their husbands. After excluding participants with missing male infertility information, 1526 males were included in this study (Figure 1).

The flowchart of the selection of participants

3.3. Measurements

A professional team measured clinical, anthropometric, and biochemical parameters. The body weight was measured on a digital scale (Seca 707, Seca GmbH) while wearing the least amount of clothes, and the result was rounded to the closest to 100 g. Similarly, the shoulders' natural posture and height without shoes in the standing position were measured using a meter. The following formula was used to determine the Body Mass Index (BMI): Weight in kilograms divided by height in meters squared (kg/m2).

A tape measure was used to measure the waist circumference (WC) without applying pressure to the body's surface or tension to the umbilical surface. Without applying any pressure on the body's surface, the anterior-superior iliac spine was used to measure the hip circumference (HC). We also measured the blood pressure twice (after 15 minutes of rest) on the arm while seated using a conventional mercury sphygmomanometer. The average of these readings was then noted.

Between 7 AM and 9 AM, the blood samples were collected following a 12-hour fast. All samples were kept at -80°C until analysis. By employing glucose oxidase as an enzyme, we assessed fasting plasma glucose (FPG). Total cholesterol (TC) was determined by an enzymatic colorimetric method using cholesterol esterase and cholesterol oxidase. Glycerol phosphate was used to determine the levels of serum triglyceride (TG). High-density lipoprotein cholesterol (HDL-C) levels were measured after the deposition of apolipoprotein B (apoB) containing lipoproteins using phosphotungstic acid. We used a modified Friedewald formula to estimate low-density lipoprotein cholesterol (LDL-C) levels (17). All metabolic parameters were evaluated using relevant kits (Pars Azmoun, Tehran, Iran) and Selectra 2 autoanalyzers (Vital Scientific, Spankeren, the Netherlands). The controls of lyophilized serum in the normal and pathological ranges were used to check the assay's performance after every 25 trials, and all samples were evaluated once the internal quality control passed muster (18, 19).

3.4. Definitions

Infertility occurs when a couple is unable to conceive after engaging in unprotected sex for at least 1 year (20, 21). In the current study, data on male infertility were gathered by reviewing the history of infertility using a self-report questionnaire and then verified by further medical records.

Metabolic syndrome was defined as having at least 3 of the following 5 criteria: TG level ≥ 150 mg/dL, taking a certain medication, or HDL ≤ 40 mg/dL; diastolic blood pressure (DBP) 85 mmHg, systolic blood pressure (SBP) ≥ 30 mmHg, or the use of a specific medication; FPG ≥ 100 mg/dL or receive special treatment (22); WC ≥ 90 cm for males according to the specific population threshold of Iran. Dyslipidemia was defined as hypertriglyceridemia (TG ≥ 150 mg/dL), hypo-HDL (HDL < 40 mg/dL), and/or using lipid-lowering drugs (23). Also, obesity was defined as BMI ≥ 30 kg/m2, and central obesity was defined as WC ≥ 90 cm (24).

The criteria for underweight, normal weight, overweight, and obese were based on BMI (kg/m2) and the following WHO and the National Heart, Lung, and Blood Institute (NHLBI) definitions: underweight < 18.5, normal weight 18.5 to 24.9, overweight 25 to 29.9, obese 30 or more kg/m2 (25, 26).

Type 2 diabetes mellitus was defined as FPG ≥ 126 mg/dL, 2-hour post-challenge plasma glucose (2h-PCPG) values in the oral glucose tolerance test (OGTT) that were 200 mg/dL, or utilizing an anti-diabetic medicine (27). A set of heart and blood vessel problems is referred to as cardiovascular disease (CVD). Coronary heart disease, cerebrovascular disease, peripheral arterial disease, rheumatic heart disease, congenital heart disease, deep vein thrombosis, and pulmonary embolism are examples of these conditions (28).

3.5. Statistical Analysis

Participants' initial traits were reported and contrasted in the groups of fertile and infertile males. We used the Kolmogorov-Smirnov test to determine the normality of the continuous variables. Mean ± SD and the Mann-Whitney U test were employed to characterize and compare continuous data if the normality assumption was rejected. Mean (SD) and the independent Student t test were utilized when the normality assumption was not rejected. The chi-square or Fisher exact test was used to compare the categorical variables, expressed as frequencies (%; for tables with sparse cells).

Statistical analysis was executed using the Logistic regression model. The coefficients obtained from the model's fit for each independent variable are interpreted as the odds ratio (OR) of that variable in the outcome occurrence. Model 1 was an unadjusted model. Model 2 was adjusted for age and BMI. Model 3 (fully adjusted) was adjusted for variables in model 2 plus WC, HC, SBP, DBP, FPG, TC, TG, HDL, LDL, educational level, smoking history, diabetes mellitus, MetS, dyslipidemia, CVD, obesity, normal weight, overweight, and obese. Data analysis was performed using R version 4.1.1 and SPSS version 21 (SPSS Inc., Chicago, IL, USA). P values less than 0.05 were considered statistically significant.

4. Results

A total of 1526 subjects were enrolled in this study. Males with self-reported infertility (n = 98) and fertile males with at least 1 live birth (n = 1428). The total prevalence of self-reported male infertility was 6.42% (98/1526). The median [interquartile range (IQR)] age of the sample was 55 (47 - 63) years. In both the fertile and infertile groups, most individuals were between 40 and 50 years old. The mean (SD) of BMI was 26.80 (3.93) and 26.92 (4.36) kg/m2 in fertile and infertile participants, respectively. The overview of the participants' initial characteristics is shown in Table 1, suggesting that there was no significant difference between the 2 groups in any of the covariates in the study.

Table 1. Characteristics of Participants According to Their History of Self-reported Male Infertility
VariablesFertile (n = 1428)Infertile (n = 98)P Value a
Age (y)0.217
< 40285 (20)21 (21.4)
40 - 50642 (45)51 (52)
> 50501 (35)26 (26.5)
BMI (kg/m2)26.80 ± 3.9326.92 ± 4.360.793
WC (cm)94.86 ± 11.9294.79 ± 10.500.851
HC (cm)97.15 ± 8.1397.89 ± 7.820.424
SBP (mm Hg)120.58 ± 17.52121.62 ± 17.520.436
DBP (mm Hg)78.74 ± 10.6679.50 ± 10.140.311
FPG (mg/dL)106.15 ± 37.30103.31 ± 29.980.752
TC (mg/dL)186.52 ± 40.26193.90 ± 35.590.077
TG (mg/dL)159.86 ± 97.00165.88 ± 74.610.078
HDL-C (mg/dL)42.08 ± 9.7141.94 ± 9.250.622
LDL-C (mg/dL)113.23 ± 34.71119.20 ± 33.560.099
Educational level (y)0.389
< 623 (1.6)0 (0)
6 - 121048 (73.6)75 (77.3)
> 12352 (24.7)22 (22.7)
Smoking history (yes)647 (45.3)44 (44.9)0.937
Dyslipidemia (yes)1275 (89.3)82 (83.7)0.087
Diabetes mellitus (yes)320 (22.4)19 (19.4)0.486
MetS (yes)883 (61.8)60 (61.2)0.958
Underweight23 (1.6)3 (3.1)
Normal weight404 (28.3)27 (27.6)
Overweight679 (47.5)47 (48.0)
Obese322 (22.5)21 (21.4)
CVD (yes)247 (17.3)10 (10.2)0.070

To investigate the effect of hypothetical factors on infertility in males, we used logistic regression in 3 models: unadjusted, age- and BMI-adjusted, and fully adjusted models.

The results of unadjusted models showed that TC had a statistically significant effect on infertility (OR, 1.01; 95% CI, 1.00 - 1.01; P = 0.04; Table 2). In other words, according to this model, a 1 mg/dL increase in TC increases the risk of male infertility by 1%. According to unadjusted models, the effect of other variables on infertility was not significant. Based on the age- and BMI-adjusted models, TC (OR, 1.01; 95% CI, 1.01 - 1.01; P = 0.03) and HC (OR, 1.06; 95% CI, 1.00 - 1.12; P = 0.02) were positively related to the risk of infertility occurrence. In model 2, which adjusted for age and BMI, a 1 mg/dL increase in TC increases the risk of male infertility by 1%, and a 1 cm increase in HC increases the risk of male infertility by 6%. The results of the fully adjusted model showed that HC was positively related to the risk of infertility in males (OR, 1.06; 95% CI, 1.00 - 1.13; P = 0.032; Table 2).

Table 2. Risk Factors for Male Infertility based on the Logistic Regression Model
VariablesModel 1 OR (95% CI) aModel 2 OR (95% CI) bModel 3 OR (95% CI) c
Age (y; reference: < 40)
40-501.07 (0.63 - 1.82)-1.15 (0.66 - 2.02)
> 500.83 (0.62 - 1.12)-0.87 (0.63 - 1.20)
BMI (kg/m2)0.99 (0.94 - 1.04)-0.91 (0.78 - 1.05)
WC (cm)1.00 (0.98 - 1.01)1.01 (0.97 - 1.05)0.99 (0.95 - 1.04)
HC (cm)1.01 (0.98 - 1.03)1.06 (1.00 - 1.12)1.06 (1.00 - 1.13)
SBP (mmHg)1.00 (0.99 - 1.01)1.00 (0.99 - 1.02)1.01 (0.99 - 1.02)
DBP (mmHg)1.00 (0.98 - 1.02)1.00 (0.98 - 1.02)0.99 (0.97 - 1.02)
FPG (mg/dL)0.99 (0.99 - 1.00)0.99 (0.99 - 1.00)0.99 (0.99 - 1.00)
TC (mg/dL)1.00 (1.00 - 1.01)1.00 (1.00 - 1.01)1.01 (0.98 - 1.05)
TG (mg/dL)1.00 (0.99 - 1.00)1.00 (0.99 - 1.00)0.99 (0.99 - 1.00)
HDL-C (mg/dL)0.99 (0.97 - 1.02)0.99 (0.97 - 1.02)0.98 (0.94 - 1.02)
LDL-C (mg/dL)1.00 (0.99 - 1.01)1.00 (0.99 - 1.01)0.98 (0.95 - 1.02)
Educational level (y; reference: < 6)
6 - 122.00 (0.26 - 14.93)2.06 (0.27 - 15.51)1.33 (0.16 - 10.53)
> 121.75 (0.22 - 13.46)1.77 (0.22 - 13.72)1.10 (0.13 - 9.04)
Smoking history (reference: no)0.98 (0.65 - 1.48)0.99 (0.65 - 1.51)0.94 (0.61 - 1.44)
Diabetes mellitus (reference: no)0.83 (0.49 - 1.39)0.86 (0.50 - 1.47)1.04 (0.51 - 2.09)
MetS (reference: no)0.97 (0.64 - 1.48)1.02 (0.64 - 1.61)1.12 (0.63 - 2.01)
Dyslipidemia (reference: no)0.61 (0.35 - 1.07)0.61 (0.33 - 1.12)0.52 (0.26 - 1.03)
CVD (reference: no)0.54 (0.27 - 1.06)0.54 (0.27 - 1.09)0.62 (0.30 - 1.27)
Obesity (reference: underweight)
Normal weight0.51 (0.14 - 1.81)0.47 (0.12 - 1.85)0.49 (0.12 - 1.99)
Overweight0.53 (0.15 - 1.83)0.45 (0.09 - 2.19)0.48 (0.09 - 2.47)
Obese0.50 (0.13 - 1.80)0.38 (0.05 - 2.73)0.43 (0.05 - 3.30)

5. Discussion

This study presents the prevalence of self-reported male infertility and metabolic disturbance. The prevalence of self-reported infertility was 6.42%. Moreover, regarding its determinant factors, we found that a 1 unit increase in TC and HC increased the risk of male infertility by 1% and 6%, respectively.

Infertility is a common problem with serious socioeconomic and health implications for individuals and society (29, 30). The results from a global burden of disease study demonstrated that the prevalence of male infertility from 1990 to 2017 increased by 8.2% (30). Also, other investigations found a greater frequency of male infertility (31-33). A recent study indicated a connection between men's overall health and infertility (34, 35).

In a meta-analysis of Iranian studies, the prevalence of male infertility was reported as 2% (11). According to Agarwal et al., 2.5% to 12% of infertility cases are due to the male factor (6). As demonstrated by Krausz and Riera-Escamilla, male infertility is a widespread problem affecting at least 7% of males worldwide and is frequently assumed to have a hereditary predisposition (36). Although several studies have been reported on the prevalence of infertility among couples, little information was available about the prevalence of male infertility in different regions. Apart from this, the methodological assessment of infertility affects the estimated male infertility prevalence rates in different regions. Since we used the self-reported history of infertility, there is a possibility of recall bias, which is common in epidemiology and medical studies (37). However, in Iran, due to sociocultural dimensions of infertility, the possibility of recall bias might decrease. Jung et al. reported that the accuracy of self-reported infertility history was moderate almost 20 years later (38). Another study also reported that self-reported assisted conception had a sensitivity of 83% (39).

Among lipid profiles, only a positive association between infertility and serum TC levels was demonstrated in this study. Although TG and LDL levels were higher in the infertile group, this measure was not significant. Male infertility should be considered as a window to health (40). Eisenberg et al. reported that males with infertility are at higher risk of developing diabetes and ischemic heart disease (41). Another study also reported that childless men had an increased risk of death from CVD (42). Ergun et al. demonstrated that increased LDL and TG had an adverse impact on seminal parameters (43). Also, Hagiuda et al. found that among Japanese patients, the serum TG level was linked to sperm morphological traits (44). It is well-documented that hyperlipidemia might affect the male reproductive system by the alteration in hormone levels, semen parameters, and male reproductive organs (45). It is possible that due to the cross-sectional design, we were unable to demonstrate a causal link between some lipid risk variables and infertility. It is necessary to conduct long-term prospective studies to examine these causal links.

Moreover, in this study, among all obesity-related parameters, there was only a slight positive association between HC and self-reported male infertility. Hip circumference risk may result from its link to MetS (46). However, there is a contradiction in any association between MetS and male infertility (21, 47-49). In our study, there were no significant differences in terms of metabolic abnormalities (MetS and diabetes) between the 2 groups; in addition, these factors were not significant determinants of male infertility in this study.

It is universally acknowledged that obesity could affect human fertility. Evidence showed that the likelihood of subfertility increased by 1.2 times for every 3 kg/m2 increase in BMI, according to a separate study conducted in the United States (50). A recent study indicated that the prevalence of subfertility and infertility was 20% higher among obese individuals (51). The obesogenic environment per se induced OS and inflammatory pathways, which can disrupt the reproductive function (52). Also, Keszthelyi et al. conducted a study on 1169 men who visited an andrology clinic in Budapest for infertility, showing that BMI and waist-to-hip ratio were significantly correlated in all semen parameters (53). Le et al. evaluated 534 men from infertile couples and found that the waist-to-hip ratio was associated with abnormal semen parameters (54). Nonetheless, it should be emphasized that the consequences of male obesity on fertility are likely multidimensional. In addition, obesity commonly coexists with metabolic disorders that enhance the risk of male infertility, such as MetS, hyperlipidemia, CVD, and pro-inflammatory state (55).

Moreover, the findings of our investigation failed to find any link between smoking and male infertility. There is an inconsistency between studies regarding the association between smoking and infertility. Some evidence showed no significant association between male infertility and smoking (56, 57), while others found a positive association between smoking and male infertility (58). Smoking has been shown to negatively impact semen parameters. However, this is still debatable (59, 60). Overall, it is well-documented that all smokers are not infertile (61).

There are some limitations and strengths to this study. The estimated self-reported male infertility is among population-based TLGSs generalized to the urban population. In terms of limitations, this study could not fully cover all risk factors of male infertility due to the lack of measurement of all factors. In this study, the reported male infertility was based on the self-reported questionnaire, and male infertility was not defined by semen data. The absence of this analysis is, therefore, another limitation. Furthermore, this is a cross-sectional study that may be susceptible to problems in a distinction between cause and effect; thus, the results must be judged cautiously. There is a tremendous need to further investigate all causes of male infertility.

5.1. Conclusion

The prevalence of self-reported male infertility was 6.42%. Infertility in males had a positive association with TC and HC, indicating that knowledge about these risks might assist health care professionals and governments in developing and executing measures to change the status quo. In this study, we restrict our attention to males to close the knowledge gap in the infertile male population. However, there are currently little and conflicting epidemiological data. To verify these results, it is necessary to do more research with larger sample sizes.



  • 1.

    Vander Borght M, Wyns C. Fertility and infertility: Definition and epidemiology. Clin Biochem. 2018;62:2-10. [PubMed ID: 29555319].

  • 2.

    Mahboubi M, Foroughi F, Ghahramani F, Shahandeh H, Moradi S, Shirzadian T. A case-control study of the factors affecting male infertility. Turk J Med Sci. 2014;44(5):862-5. [PubMed ID: 25539558].

  • 3.

    Inhorn MC, Patrizio P. Infertility around the globe: new thinking on gender, reproductive technologies and global movements in the 21st century. Hum Reprod Update. 2015;21(4):411-26. [PubMed ID: 25801630].

  • 4.

    Saei Ghare Naz M, Ozgoli G, Sayehmiri K. Prevalence of Infertility In Iran: A Systematic Review And Meta-Analysis. Urol J. 2020;17(4):338-45. [PubMed ID: 32281088].

  • 5.

    Liang S, Chen Y, Wang Q, Chen H, Cui C, Xu X, et al. Prevalence and associated factors of infertility among 20-49 year old women in Henan Province, China. Reprod Health. 2021;18(1):254. [PubMed ID: 34930324]. [PubMed Central ID: PMC8691046].

  • 6.

    Agarwal A, Mulgund A, Hamada A, Chyatte MR. A unique view on male infertility around the globe. Reprod Biol Endocrinol. 2015;13:37. [PubMed ID: 25928197]. [PubMed Central ID: PMC4424520].

  • 7.

    Okonofua FE, Ntoimo LFC, Omonkhua A, Ayodeji O, Olafusi C, Unuabonah E, et al. Causes and Risk Factors for Male Infertility: A Scoping Review of Published Studies. Int J Gen Med. 2022;15:5985-97. [PubMed ID: 35811778]. [PubMed Central ID: PMC9268217].

  • 8.

    Martins AD, Majzoub A, Agawal A. Metabolic Syndrome and Male Fertility. World J Mens Health. 2019;37(2):113-27. [PubMed ID: 30350486]. [PubMed Central ID: PMC6479081].

  • 9.

    Kasturi SS, Tannir J, Brannigan RE. The metabolic syndrome and male infertility. J Androl. 2008;29(3):251-9. [PubMed ID: 18222914].

  • 10.

    Salvio G, Ciarloni A, Cutini M, Delli Muti N, Finocchi F, Perrone M, et al. Metabolic Syndrome and Male Fertility: Beyond Heart Consequences of a Complex Cardiometabolic Endocrinopathy. Int J Mol Sci. 2022;23(10). [PubMed ID: 35628307]. [PubMed Central ID: PMC9143238].

  • 11.

    Saremi AT, Zamanian M, Pooladi A. [Male Infertility Effective Factors and Failure Type Determination in Iranian Infertile Men]. Sarem Journal of Reproductive Medicine. 2017;2(1):3-8. Persian.

  • 12.

    Al-Kandari AM, Al-Enezi AN, Ibrahim H, Alkandari O. A population-based study of the epidemiology and the risk factors for male infertility in Kuwait. Urol Ann. 2020;12(4):319-23. [PubMed ID: 33776326]. [PubMed Central ID: PMC7992523].

  • 13.

    Frikh M, Benaissa M, Kasouati J, Benlahlou Y, Chokairi O, Barkiyou M, et al. [Prevalence of male infertility in a university hospital in Morocco]. Pan Afr Med J. 2021;38:46. French. [PubMed ID: 33854675]. [PubMed Central ID: PMC8017356].

  • 14.

    Azizi F, Ghanbarian A, Momenan AA, Hadaegh F, Mirmiran P, Hedayati M, et al. Prevention of non-communicable disease in a population in nutrition transition: Tehran Lipid and Glucose Study phase II. Trials. 2009;10:5. [PubMed ID: 19166627]. [PubMed Central ID: PMC2656492].

  • 15.

    Azizi F, Zadeh-Vakili A, Takyar M. Review of Rationale, Design, and Initial Findings: Tehran Lipid and Glucose Study. Int J Endocrinol Metab. 2018;16(4 Suppl). e84777. [PubMed ID: 30584442]. [PubMed Central ID: PMC6289309].

  • 16.

    Ramezani Tehrani F, Behboudi-Gandevani S, Rostami Dovom M, Farahmand M, Minooee S, Noroozzadeh M, et al. Reproductive Assessment: Findings from 20 Years of the Tehran Lipid and Glucose Study. Int J Endocrinol Metab. 2018;16(4 Suppl). e84786. [PubMed ID: 30584446]. [PubMed Central ID: PMC6289318].

  • 17.

    Chen Y, Zhang X, Pan B, Jin X, Yao H, Chen B, et al. A modified formula for calculating low-density lipoprotein cholesterol values. Lipids Health Dis. 2010;9:52. [PubMed ID: 20487572]. [PubMed Central ID: PMC2890624].

  • 18.

    Hosseinpanah F, Kasraei F, Nassiri AA, Azizi F. High prevalence of chronic kidney disease in Iran: a large population-based study. BMC Public Health. 2009;9:44. [PubMed ID: 19183493]. [PubMed Central ID: PMC2658666].

  • 19.

    Tohidi M, Hasheminia M, Mohebi R, Khalili D, Hosseinpanah F, Yazdani B, et al. Incidence of chronic kidney disease and its risk factors, results of over 10 year follow up in an Iranian cohort. PLoS One. 2012;7(9). e45304. [PubMed ID: 23028919]. [PubMed Central ID: PMC3459968].

  • 20.

    Barratt CLR, Björndahl L, De Jonge CJ, Lamb DJ, Osorio Martini F, McLachlan R, et al. The diagnosis of male infertility: an analysis of the evidence to support the development of global WHO guidance-challenges and future research opportunities. Hum Reprod Update. 2017;23(6):660-80. [PubMed ID: 28981651]. [PubMed Central ID: PMC5850791].

  • 21.

    Behboudi-Gandevani S, Bidhendi Yarandi R, Rostami Dovom M, Azizi F, Ramezani Tehrani F. The Association Between Male Infertility and Cardiometabolic Disturbances: A Population-Based Study. Int J Endocrinol Metab. 2021;19(2). e107418. [PubMed ID: 34149845]. [PubMed Central ID: PMC8198602].

  • 22.

    Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120(16). [PubMed ID: 19805654].

  • 23.

    Expert Panel on Detection Evaluation and Treatment of High Blood Cholesterol in Adults. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III). Jama. 2001;285(19):2486-97. [PubMed ID: 11368702].

  • 24.

    Romero-Corral A, Somers VK, Sierra-Johnson J, Thomas RJ, Collazo-Clavell ML, Korinek J, et al. Accuracy of body mass index in diagnosing obesity in the adult general population. Int J Obes (Lond). 2008;32(6):959-66. [PubMed ID: 18283284]. [PubMed Central ID: PMC2877506].

  • 25.

    No authors listed. Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults--The Evidence Report. National Institutes of Health. Obes Res. 1998;6 Suppl 2:51s-209s. [PubMed ID: 9813653].

  • 26.

    No authors listed. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser. 2000;894:i-xii. 1-253. [PubMed ID: 11234459].

  • 27.

    American Diabetes Association. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2019. Diabetes Care. 2019;42(Suppl 1):S13-s28. [PubMed ID: 30559228].

  • 28.

    Goyal A, Gupta Y, Singla R, Kalra S, Tandon N. American Diabetes Association "Standards of Medical Care-2020 for Gestational Diabetes Mellitus": A Critical Appraisal. Diabetes Ther. 2020;11(8):1639-44. [PubMed ID: 32564336]. [PubMed Central ID: PMC7376815].

  • 29.

    Kazemijaliseh H, Ramezani Tehrani F, Behboudi-Gandevani S, Hosseinpanah F, Khalili D, Azizi F. The Prevalence and Causes of Primary Infertility in Iran: A Population-Based Study. Glob J Health Sci. 2015;7(6):226-32. [PubMed ID: 26153187]. [PubMed Central ID: PMC4803880].

  • 30.

    Sun H, Gong TT, Jiang YT, Zhang S, Zhao YH, Wu QJ. Global, regional, and national prevalence and disability-adjusted life-years for infertility in 195 countries and territories, 1990-2017: results from a global burden of disease study, 2017. Aging (Albany NY). 2019;11(23):10952-91. [PubMed ID: 31790362]. [PubMed Central ID: PMC6932903].

  • 31.

    Bayasgalan G, Naranbat D, Radnaabazar J, Lhagvasuren T, Rowe PJ. Male infertility: risk factors in Mongolian men. Asian J Androl. 2004;6(4):305-11. [PubMed ID: 15546021].

  • 32.

    Tekatli H, Schouten N, van Dalen T, Burgmans I, Smakman N. Mechanism, assessment, and incidence of male infertility after inguinal hernia surgery: a review of the preclinical and clinical literature. Am J Surg. 2012;204(4):503-9. [PubMed ID: 22578405].

  • 33.

    Saleh RA, Sharma RK, Kandirali E, Evenson DP, Thomas AJ, Agarwal A. Cigarette smoking in infertile men is highly correlated with leukocytospermia and oxidative stress. Fertil Steril. 2001;76(3). S100.

  • 34.

    Salonia A, Matloob R, Gallina A, Abdollah F, Saccà A, Briganti A, et al. Are infertile men less healthy than fertile men? Results of a prospective case-control survey. Eur Urol. 2009;56(6):1025-31. [PubMed ID: 19297076].

  • 35.

    Eisenberg ML, Li S, Behr B, Cullen MR, Galusha D, Lamb DJ, et al. Semen quality, infertility and mortality in the USA. Hum Reprod. 2014;29(7):1567-74. [PubMed ID: 24838701]. [PubMed Central ID: PMC4059337].

  • 36.

    Krausz C, Riera-Escamilla A. Genetics of male infertility. Nat Rev Urol. 2018;15(6):369-84. [PubMed ID: 29622783].

  • 37.

    Althubaiti A. Information bias in health research: definition, pitfalls, and adjustment methods. J Multidiscip Healthc. 2016;9:211-7. [PubMed ID: 27217764]. [PubMed Central ID: PMC4862344].

  • 38.

    Jung AM, Missmer SA, Cramer DW, Ginsburg ES, Terry KL, Vitonis AF, et al. Self-reported infertility diagnoses and treatment history approximately 20 years after fertility treatment initiation. Fertil Res Pract. 2021;7(1):7. [PubMed ID: 33712085]. [PubMed Central ID: PMC7953690].

  • 39.

    Hvidtjørn D, Grove J, Schendel D, Schieve LA, Ernst E, Olsen J, et al. Validation of self-reported data on assisted conception in The Danish National Birth Cohort. Hum Reprod. 2009;24(9):2332-40. [PubMed ID: 19454590].

  • 40.

    Choy JT, Eisenberg ML. Male infertility as a window to health. Fertil Steril. 2018;110(5):810-4. [PubMed ID: 30316415].

  • 41.

    Eisenberg ML, Li S, Cullen MR, Baker LC. Increased risk of incident chronic medical conditions in infertile men: analysis of United States claims data. Fertil Steril. 2016;105(3):629-36. [PubMed ID: 26674559].

  • 42.

    Eisenberg ML, Park Y, Hollenbeck AR, Lipshultz LI, Schatzkin A, Pletcher MJ. Fatherhood and the risk of cardiovascular mortality in the NIH-AARP Diet and Health Study. Hum Reprod. 2011;26(12):3479-85. [PubMed ID: 21946940]. [PubMed Central ID: PMC3212876].

  • 43.

    Ergün A, Köse SK, Aydos K, Ata A, Avci A. Correlation of seminal parameters with serum lipid profile and sex hormones. Arch Androl. 2007;53(1):21-3. [PubMed ID: 17364460].

  • 44.

    Hagiuda J, Ishikawa H, Furuuchi T, Hanawa Y, Marumo K. Relationship between dyslipidaemia and semen quality and serum sex hormone levels: an infertility study of 167 Japanese patients. Andrologia. 2014;46(2):131-5. [PubMed ID: 23278423].

  • 45.

    Hamad Zubi ZB, Hamad Alfarisi HA. Hyperlipidemia and male infertility. Egypt J Basic Appl Sci. 2021;8(1):385-96.

  • 46.

    Del Giudice F, Kasman AM, Ferro M, Sciarra A, De Berardinis E, Belladelli F, et al. Clinical correlation among male infertility and overall male health: A systematic review of the literature. Investig Clin Urol. 2020;61(4):355-71. [PubMed ID: 32665992]. [PubMed Central ID: PMC7329649].

  • 47.

    Ventimiglia E, Capogrosso P, Colicchia M, Boeri L, Serino A, Castagna G, et al. Metabolic syndrome in white European men presenting for primary couple's infertility: investigation of the clinical and reproductive burden. Andrology. 2016;4(5):944-51. [PubMed ID: 27368157].

  • 48.

    Morrison CD, Brannigan RE. Metabolic syndrome and infertility in men. Best Pract Res Clin Obstet Gynaecol. 2015;29(4):507-15. [PubMed ID: 25487258].

  • 49.

    Lotti F, Corona G, Degli Innocenti S, Filimberti E, Scognamiglio V, Vignozzi L, et al. Seminal, ultrasound and psychobiological parameters correlate with metabolic syndrome in male members of infertile couples. Andrology. 2013;1(2):229-39. [PubMed ID: 23315971].

  • 50.

    Sallmén M, Sandler DP, Hoppin JA, Blair A, Baird DD. Reduced fertility among overweight and obese men. Epidemiology. 2006;17(5):520-3. [PubMed ID: 16837825].

  • 51.

    Guo D, Wu W, Tang Q, Qiao S, Chen Y, Chen M, et al. The impact of BMI on sperm parameters and the metabolite changes of seminal plasma concomitantly. Oncotarget. 2017;8(30):48619-34. [PubMed ID: 28159940]. [PubMed Central ID: PMC5564712].

  • 52.

    Leisegang K, Sengupta P, Agarwal A, Henkel R. Obesity and male infertility: Mechanisms and management. Andrologia. 2021;53(1). e13617. [PubMed ID: 32399992].

  • 53.

    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. [PubMed ID: 32164645]. [PubMed Central ID: PMC7066798].

  • 54.

    Le MT, Tran NQT, Nguyen ND, Nguyen QHV. The Prevalence and Components of Metabolic Syndrome in Men from Infertile Couples and Its Relation on Semen Analysis. Diabetes Metab Syndr Obes. 2021;14:1453-63. [PubMed ID: 33824599]. [PubMed Central ID: PMC8018567].

  • 55.

    McPherson NO, Lane M. Male obesity and subfertility, is it really about increased adiposity? Asian J Androl. 2015;17(3):450-8. [PubMed ID: 25652636]. [PubMed Central ID: PMC4430951].

  • 56.

    Kovac JR, Khanna A, Lipshultz LI. The effects of cigarette smoking on male fertility. Postgrad Med. 2015;127(3):338-41. [PubMed ID: 25697426]. [PubMed Central ID: PMC4639396].

  • 57.

    Mostafa T. Cigarette smoking and male infertility. J Adv Res. 2010;1(3):179-86.

  • 58.

    Rehman R, Zahid N, Amjad S, Baig M, Gazzaz ZJ. Relationship Between Smoking Habit and Sperm Parameters Among Patients Attending an Infertility Clinic. Front Physiol. 2019;10:1356. [PubMed ID: 31736779]. [PubMed Central ID: PMC6834764].

  • 59.

    Sepaniak S, Forges T, Gerard H, Foliguet B, Bene MC, Monnier-Barbarino P. The influence of cigarette smoking on human sperm quality and DNA fragmentation. Toxicology. 2006;223(1-2):54-60. [PubMed ID: 16621218].

  • 60.

    Sharma R, Harlev A, Agarwal A, Esteves SC. Cigarette Smoking and Semen Quality: A New Meta-analysis Examining the Effect of the 2010 World Health Organization Laboratory Methods for the Examination of Human Semen. Eur Urol. 2016;70(4):635-45. [PubMed ID: 27113031].

  • 61.

    Harlev A, Agarwal A, Gunes SO, Shetty A, du Plessis SS. Smoking and Male Infertility: An Evidence-Based Review. World J Mens Health. 2015;33(3):143-60. [PubMed ID: 26770934]. [PubMed Central ID: PMC4709430].

Copyright © 2023, International Journal of Endocrinology and Metabolism. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License ( which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.