Sun, Nov 8, 2026
[Archive]
Volume 11, Issue 4 (11-2026)
J Nutr Food Secur. 2026, 11(4): 561-570 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Kharrazi M, Hossaini B Z, Kosari A, Darabi Z, Hosseinzadeh M. Exploring the Link Between Global Diet Quality Score and Sperm Parameters in Infertile Men: A Cross-Sectional Study. J Nutr Food Secur. 2026; 11 (4) :561-570
URL: http://jnfs.ssu.ac.ir/article-1-1475-en.html
URL: http://jnfs.ssu.ac.ir/article-1-1475-en.html
Nutritional Health Research Center, School of Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran
Full-Text [PDF 924 kb]
(39 Downloads)
| Abstract (HTML) (534 Views)
1 Nutritional Health Research Center, School of Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran; 2 Department of Nutrition Sciences, Varastegan Institute for Medical Sciences, Mashhad, Iran;
3 Department of Nutrition, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran; 4 Research Center for Food Hygiene and Safety, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Introduction
Dietary intakes of participants
Table 2 presents the mean and standard deviation of dietary component intakes across tertiles of the GDQS. Participants in the highest GDQS tertile (T3) showed significantly higher intake of energy, fruits, vegetables, nuts, and legumes compared to those in the lowest GDQS tertile (T1). There were no significant differences in the intake of whole grains, Polyunsaturated fatty acids (PUFA), and monounsaturated fatty acids (MUFA) between the two tertiles.
Full-Text: (7 Views)
Exploring the Link Between Global Diet Quality Score and Sperm Parameters in Infertile Men: A Cross-Sectional Study
Marziyeh Kharrazi; MSc Candidate1, Bibi Zainab Hossaini; BSc2, Ali Kosari; MSc Candidate1, Zahra Darabi; PhD1* & Mahdieh Hosseinzadeh; PhD3, 4
Marziyeh Kharrazi; MSc Candidate1, Bibi Zainab Hossaini; BSc2, Ali Kosari; MSc Candidate1, Zahra Darabi; PhD1* & Mahdieh Hosseinzadeh; PhD3, 4
1 Nutritional Health Research Center, School of Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran; 2 Department of Nutrition Sciences, Varastegan Institute for Medical Sciences, Mashhad, Iran;
3 Department of Nutrition, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran; 4 Research Center for Food Hygiene and Safety, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
| ARTICLE INFO | ABSTRACT | |
| ORIGINAL ARTICLE | Background: In examining the causes of a couple's infertility, the male factor generally accounts for about 50%. According to the World Health Organization (WHO), an infertile man is defined as someone whose sperm cannot fertilize a healthy egg after at least one year of regular, unprotected sex. Diet is known to be one of the most important factors affecting male fertility. Therefore, the purpose of this study was to examine the relationship between the Global Diet Quality Score (GDQS) and sperm quality. Methods: This cross-sectional study involved 218 infertile men aged between 20 and 50 who visited an infertility referral clinical and research center. A 168-question food frequency questionnaire (FFQ) was used to evaluate their food intake. The GDQS was calculated from the sum of scores across 25 food groups, with scores ranging from 0 to 49. To assess the relationship between GDQS and sperm parameters, logistic regression was used to account for potential confounding factors. Results: The results of this study demonstrated that in the unadjusted model, higher adherence to the GDQS was associated with lower odds of low sperm concentration, though this association was not statistically significant (OR: 0.60; 95% CI: 0.29–1.20; P=0.15). This association was attenuated and no longer significant after adjusting for confounding factors, with no significant associations observed for other sperm parameters in either crude or adjusted models (all P>0.05). Conclusion: Future research requires large-scale prospective cohorts, clinical trials, and more detailed dietary pattern assessments to better understand the diet-fertility relationship. | |
| Article history: Received: 24 Sep 2025 Revised: 11 Jul 2026 Accepted: 12 Jul 2026 |
||
| *Corresponding author: z,darabi91@yahoo.com Nutritional Health Research Center, School of Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran. Postal code: 6819789741 Tel: +98 066-33302033 |
||
Keywords: Global Diet Quality Score (GDQS); Sperm parameters; Male infertility; Dietary pattern. |
Introduction
Infertility issues are on the rise globally, impacting many couples (Vander Borght and Wyns, 2018, Wasilewski et al., 2020). It is a condition affecting the male or female reproductive system, and is characterized by the inability to achieve pregnancy after 12 months or more of regular, unprotected intercourse (de Vries et al., 2024). Moreover, infertility affects about 15% of the world's population (Sun et al., 2019). Recent findings indicate that about 186 million individuals and 48 million couples worldwide experience infertility (Almabhouh and Singh, 2022, Annapurna and Pattnaik, 2022, Inhorn and Patrizio, 2015). A meta-analysis published in 2019 reports a 7.88% prevalence rate of infertility in Iran (Naz et al., 2019). Some causes of male infertility include obesity, genetic factors, lifestyle choices, genital infections, reproductive tract obstructions, abnormalities in sperm parameters (motility, count, and morphology), testicular torsion or trauma, testicular varicocele, erectile disorders, hypogonadotropic hypogonadism, and chronic systemic disorders (Vander Borght and Wyns, 2018, Wasilewski et al., 2020).
Research suggests that diet is one of the most important modifiable factors affecting male fertility (Cristodoro et al., 2024, Salas-Huetos et al., 2017b, Salas-Huetos et al., 2018b). A healthy diet has been linked to improved fertility in both men and women (Cristodoro et al., 2024). Observational studies have found a link between dietary patterns, food, nutrients, and sperm quality. Results of previous studies have also shown that a healthy dietary pattern may improve the quality of men's sperm parameters (Salas-Huetos et al., 2017b, Salas-Huetos et al., 2018b). A meta-analysis indicates that dietary patterns characterized by a high intake of fruits and vegetables, plant protein, legumes and nuts, moderate consumption of low-fat dairy products, and reduced animal protein intake, positively influence sperm concentration, total sperm count, and progressive sperm motility in males (Cao et al., 2022). Evidence suggests that diets rich in fruits, vegetables, fish, whole grains, and low-fat dairy products are associated with better semen quality, whereas dietary patterns high in processed meats, refined grains, sweets, and sugary beverages have a detrimental effect on sperm parameters (Eslamian et al., 2015, Soltani et al., 2025).
Given the growing evidence linking diet to reproductive health, there is a need for a practical tool to assess overall dietary quality. The Global Diet Quality Score (GDQS) is a standardized, food-based metric developed to assess overall dietary quality across diverse populations and settings. It captures two key dimensions of diet: nutrient adequacy and risk of non-communicable diseases (NCDs) (Bell et al., 2025). The GDQS serves as a validated metric that assesses nutritional adequacy and predicts the risk of major non-communicable diseases, and can serve as a universal and practical tool to assess diet quality globally, as it is designed to be simple, timely, and cost-effective for tracking both nutritional deficiency and NCD risks in diverse settings (Bell et al., 2025, Mehrabani et al., 2025). Several studies have confirmed its relationship with various health outcomes in different communities(Angulo et al., 2021, He et al., 2021, Satija et al., 2017, Seidelmann et al., 2018). A 20-year study conducted in a Mediterranean population found that higher diet quality (GDQS) and increased consumption of healthy foods (GDQS+) are associated with a reduced risk of cardiovascular diseases and type 2 diabetes. These findings suggest that focusing on increasing the intake of healthy foods in the diet is more important for the prevention of cardiovascular diseases and type 2 diabetes (Damigou et al., 2023).
In addition to these findings, more recently, multiple investigations have indicated a positive association between semen quality and dietary patterns characterized by high intakes of fish, shellfish, seafood, poultry, cereals, vegetables, fruit, and low-fat dairy products (Ricci et al., 2019, Salas-Huetos et al., 2017a). Conversely, dietary patterns abundant in processed meats, soy, potatoes, full-fat dairy products, coffee, alcohol, sugary beverages, and sweets appear to have a detrimental effect on semen quality (Salas-Huetos et al., 2017a, Torres-Arce et al., 2021). The GDQS covers 25 food groups, promoting the consumption of whole grains, orange vegetables, fruits, fish, chicken, eggs, legumes, nuts, liquid oils, and low-fat dairy products. It also emphasizes reducing intake of red and processed meats, sweets, sugar sweetened beverages, refined grains, fried foods, and salt (Bromage et al., 2021). Despite the well-documented role of diet in male fertility and the validation of GDQS as a comprehensive dietary assessment tool, its direct association with sperm parameters in infertile men has not yet been investigated. Therefore, this study aims to address this gap by examining the relationship between adherence to the GDQS and sperm quality in a sample of Iranian infertile men.
Materials and Methods
Study population
This cross-sectional study was conducted among infertile men who visited the research and clinical center for infertility. Eligible participants included men aged 20 to 50 years with any abnormalities in sperm morphology, motility, or concentration. Exclusion criteria encompassed chronic illnesses, azoospermia, genetic disorders, a history of vasectomy, varicocele, macroorchidism, and cryptorchidism. Additionally, individuals who failed to respond to more than 35 items on the food frequency questionnaire or reported energy intake outside the range of 800 to 4200 kcal were excluded from the study.
Sample size calculation
The sample size was measured based on a 95% confidence interval and 80% test power and according to the correlation coefficient (r=0.26) between WC and total sperm count in a study by Fejes et al. (Fejes et al., 2005) according to the following equation: N=[(Zα+Zβ)/C]²+3]. The standard normal deviated for Zα=1.9600. Further, the standard normal deviated for Zβ=0.8416 and C=0.5. Participants were selected using convenience sampling. Ultimately, after applying the inclusion and exclusion criteria and removing incomplete data, 218 men were included in the final analysis.
Dietary intake and physical activity
Data on dietary intake were collected through face-to-face interviews conducted by trained dietitians using a validated semi-quantitative FFQ with 168 food items (Eghtesad et al., 2025). Participants were asked about the frequency of consumption of each food item over the preceding year. The portion sizes and items reported in household measures were converted to grams following guidelines from Nutritionist 4 scales (Rohde et al., 2019). Then, the dietary intake for each participant was quantified in grams per day. To assess energy, macronutrient, and micronutrient intake, the authors referenced a food ingredients table tailored for Iranian foods. Additionally, daily physical activity was evaluated using a brief version of the International Physical Activity Questionnaire (IPAQ), with results expressed in MET-hours per week (Campos-Perez et al., 2020).
GDQS index
Globally, GDQS serves as a validated metric that assesses nutritional adequacy and predicts the risk of major non-communicable diseases (Bromage et al., 2021). The scoring system is based on the consumption amounts (in grams per day) of 25 specific food groups, categorized into three or four distinct groups. The GDQS includes 16 healthy food groups (including citrus fruits, deep-orange fruits and vegetables, dark-green leafy vegetables, cruciferous vegetables, legumes, nuts and seeds, whole grains, fish and shellfish, poultry, eggs, and low-fat dairy), seven unhealthy food groups (including processed meat, refined grains and baked goods, sweets and ice cream, sugar-sweetened beverages, juice, white roots and tubers, and purchased deep-fried foods), and two additional unhealthy food groups (high-fat dairy and red meat) that are considered detrimental when consumed in excess. The total possible score ranges from 0 to 49 points. For the healthy food categories, higher scores are awarded for greater intake, whereas for the unhealthy categories, higher scores are associated with lower consumption levels. In the case of unhealthy foods that are harmful when consumed excessively, scores increase up to a certain threshold, beyond which no further points are granted (Bromage et al., 2021).
Collection and analysis of semen samples
Semen samples were obtained through masturbation in a designated room adjacent to the laboratory and were maintained at a temperature of 37 °C. Participants were instructed to abstain from ejaculation for a minimum of 48 hours prior to sample collection. The analysis of semen was performed in accordance with the guidelines established by the WHO (Björndahl and Brown, 2022). Then, key sperm parameters, including sperm concentration (measured in millions per milliliter), motility, viability, and normal morphology, were evaluated based on a count of 200 spermatozoa from each sample. Sperm concentration and motility were assessed using a Makler chamber under light microscopy (Olympus Co., Tokyo, Japan). Viability was then determined using Eosin staining, while morphological assessment was conducted utilizing Papanicolaou staining techniques.
General, medical, and anthropometric measurements
General information, including education level, economic status, and employment details, was gathered through personal interviews. Anthropometric measurements were also taken using standardized methods. Then, body weight was measured with an accuracy of 100 grams using a Seca scale. Height was recorded with a tape measure while the individual stood without shoes, ensuring that the shoulders were in a neutral position, also utilizing a Seca scale. After that, body mass index (BMI) was calculated by dividing weight in kilograms by the square of height in meters (kg/m²). Waist circumference was also measured to an accuracy of 0.1 cm using a tape measure, ensuring no pressure was applied to the body surface. This measurement was taken at the midpoint between the lower rib and the upper part of the pelvis at the end of a normal exhalation. In cases where it was difficult to identify the narrowest point of the waist, measurements were taken just below the last rib, as this area is typically the narrowest between the iliac crests and lower ribs (Chaves and Reis, 2019). Finally, hip circumference was measured with a tape measure to an accuracy of 0.1 cm, taken in a standing position without any additional clothing covering the area. This measurement was conducted at the widest point of the hip bone, corresponding to the largest circumference of the thigh.
Ethical considerations
The study protocol received approval from the ethics committee of Shahid Sadoughi University of Medical Sciences in Yazd, Iran (Ethics ID: IR.SSU.SPH.REC.1402.059). Informed consent was also obtained from all participants prior to their enrollment in the study.
Data analysis
After entering the data into SPSS software version 26, to assess differences in general characteristics across tertiles, the authors employed one-way ANOVA for continuous variables and the chi-square test for categorical variables. Dietary intakes among the tertiles were analyzed using ANOVA. To examine the association between adherence to the GDQS and sperm parameters, the authors utilized multivariate logistic regression in both crude and adjusted models.
Results
Characteristics of the study population
Characteristics of the participants are presented in Table 1. The mean age of the participants was 33.8±5.7 years.
Research suggests that diet is one of the most important modifiable factors affecting male fertility (Cristodoro et al., 2024, Salas-Huetos et al., 2017b, Salas-Huetos et al., 2018b). A healthy diet has been linked to improved fertility in both men and women (Cristodoro et al., 2024). Observational studies have found a link between dietary patterns, food, nutrients, and sperm quality. Results of previous studies have also shown that a healthy dietary pattern may improve the quality of men's sperm parameters (Salas-Huetos et al., 2017b, Salas-Huetos et al., 2018b). A meta-analysis indicates that dietary patterns characterized by a high intake of fruits and vegetables, plant protein, legumes and nuts, moderate consumption of low-fat dairy products, and reduced animal protein intake, positively influence sperm concentration, total sperm count, and progressive sperm motility in males (Cao et al., 2022). Evidence suggests that diets rich in fruits, vegetables, fish, whole grains, and low-fat dairy products are associated with better semen quality, whereas dietary patterns high in processed meats, refined grains, sweets, and sugary beverages have a detrimental effect on sperm parameters (Eslamian et al., 2015, Soltani et al., 2025).
Given the growing evidence linking diet to reproductive health, there is a need for a practical tool to assess overall dietary quality. The Global Diet Quality Score (GDQS) is a standardized, food-based metric developed to assess overall dietary quality across diverse populations and settings. It captures two key dimensions of diet: nutrient adequacy and risk of non-communicable diseases (NCDs) (Bell et al., 2025). The GDQS serves as a validated metric that assesses nutritional adequacy and predicts the risk of major non-communicable diseases, and can serve as a universal and practical tool to assess diet quality globally, as it is designed to be simple, timely, and cost-effective for tracking both nutritional deficiency and NCD risks in diverse settings (Bell et al., 2025, Mehrabani et al., 2025). Several studies have confirmed its relationship with various health outcomes in different communities(Angulo et al., 2021, He et al., 2021, Satija et al., 2017, Seidelmann et al., 2018). A 20-year study conducted in a Mediterranean population found that higher diet quality (GDQS) and increased consumption of healthy foods (GDQS+) are associated with a reduced risk of cardiovascular diseases and type 2 diabetes. These findings suggest that focusing on increasing the intake of healthy foods in the diet is more important for the prevention of cardiovascular diseases and type 2 diabetes (Damigou et al., 2023).
In addition to these findings, more recently, multiple investigations have indicated a positive association between semen quality and dietary patterns characterized by high intakes of fish, shellfish, seafood, poultry, cereals, vegetables, fruit, and low-fat dairy products (Ricci et al., 2019, Salas-Huetos et al., 2017a). Conversely, dietary patterns abundant in processed meats, soy, potatoes, full-fat dairy products, coffee, alcohol, sugary beverages, and sweets appear to have a detrimental effect on semen quality (Salas-Huetos et al., 2017a, Torres-Arce et al., 2021). The GDQS covers 25 food groups, promoting the consumption of whole grains, orange vegetables, fruits, fish, chicken, eggs, legumes, nuts, liquid oils, and low-fat dairy products. It also emphasizes reducing intake of red and processed meats, sweets, sugar sweetened beverages, refined grains, fried foods, and salt (Bromage et al., 2021). Despite the well-documented role of diet in male fertility and the validation of GDQS as a comprehensive dietary assessment tool, its direct association with sperm parameters in infertile men has not yet been investigated. Therefore, this study aims to address this gap by examining the relationship between adherence to the GDQS and sperm quality in a sample of Iranian infertile men.
Materials and Methods
Study population
This cross-sectional study was conducted among infertile men who visited the research and clinical center for infertility. Eligible participants included men aged 20 to 50 years with any abnormalities in sperm morphology, motility, or concentration. Exclusion criteria encompassed chronic illnesses, azoospermia, genetic disorders, a history of vasectomy, varicocele, macroorchidism, and cryptorchidism. Additionally, individuals who failed to respond to more than 35 items on the food frequency questionnaire or reported energy intake outside the range of 800 to 4200 kcal were excluded from the study.
Sample size calculation
The sample size was measured based on a 95% confidence interval and 80% test power and according to the correlation coefficient (r=0.26) between WC and total sperm count in a study by Fejes et al. (Fejes et al., 2005) according to the following equation: N=[(Zα+Zβ)/C]²+3]. The standard normal deviated for Zα=1.9600. Further, the standard normal deviated for Zβ=0.8416 and C=0.5. Participants were selected using convenience sampling. Ultimately, after applying the inclusion and exclusion criteria and removing incomplete data, 218 men were included in the final analysis.
Dietary intake and physical activity
Data on dietary intake were collected through face-to-face interviews conducted by trained dietitians using a validated semi-quantitative FFQ with 168 food items (Eghtesad et al., 2025). Participants were asked about the frequency of consumption of each food item over the preceding year. The portion sizes and items reported in household measures were converted to grams following guidelines from Nutritionist 4 scales (Rohde et al., 2019). Then, the dietary intake for each participant was quantified in grams per day. To assess energy, macronutrient, and micronutrient intake, the authors referenced a food ingredients table tailored for Iranian foods. Additionally, daily physical activity was evaluated using a brief version of the International Physical Activity Questionnaire (IPAQ), with results expressed in MET-hours per week (Campos-Perez et al., 2020).
GDQS index
Globally, GDQS serves as a validated metric that assesses nutritional adequacy and predicts the risk of major non-communicable diseases (Bromage et al., 2021). The scoring system is based on the consumption amounts (in grams per day) of 25 specific food groups, categorized into three or four distinct groups. The GDQS includes 16 healthy food groups (including citrus fruits, deep-orange fruits and vegetables, dark-green leafy vegetables, cruciferous vegetables, legumes, nuts and seeds, whole grains, fish and shellfish, poultry, eggs, and low-fat dairy), seven unhealthy food groups (including processed meat, refined grains and baked goods, sweets and ice cream, sugar-sweetened beverages, juice, white roots and tubers, and purchased deep-fried foods), and two additional unhealthy food groups (high-fat dairy and red meat) that are considered detrimental when consumed in excess. The total possible score ranges from 0 to 49 points. For the healthy food categories, higher scores are awarded for greater intake, whereas for the unhealthy categories, higher scores are associated with lower consumption levels. In the case of unhealthy foods that are harmful when consumed excessively, scores increase up to a certain threshold, beyond which no further points are granted (Bromage et al., 2021).
Collection and analysis of semen samples
Semen samples were obtained through masturbation in a designated room adjacent to the laboratory and were maintained at a temperature of 37 °C. Participants were instructed to abstain from ejaculation for a minimum of 48 hours prior to sample collection. The analysis of semen was performed in accordance with the guidelines established by the WHO (Björndahl and Brown, 2022). Then, key sperm parameters, including sperm concentration (measured in millions per milliliter), motility, viability, and normal morphology, were evaluated based on a count of 200 spermatozoa from each sample. Sperm concentration and motility were assessed using a Makler chamber under light microscopy (Olympus Co., Tokyo, Japan). Viability was then determined using Eosin staining, while morphological assessment was conducted utilizing Papanicolaou staining techniques.
General, medical, and anthropometric measurements
General information, including education level, economic status, and employment details, was gathered through personal interviews. Anthropometric measurements were also taken using standardized methods. Then, body weight was measured with an accuracy of 100 grams using a Seca scale. Height was recorded with a tape measure while the individual stood without shoes, ensuring that the shoulders were in a neutral position, also utilizing a Seca scale. After that, body mass index (BMI) was calculated by dividing weight in kilograms by the square of height in meters (kg/m²). Waist circumference was also measured to an accuracy of 0.1 cm using a tape measure, ensuring no pressure was applied to the body surface. This measurement was taken at the midpoint between the lower rib and the upper part of the pelvis at the end of a normal exhalation. In cases where it was difficult to identify the narrowest point of the waist, measurements were taken just below the last rib, as this area is typically the narrowest between the iliac crests and lower ribs (Chaves and Reis, 2019). Finally, hip circumference was measured with a tape measure to an accuracy of 0.1 cm, taken in a standing position without any additional clothing covering the area. This measurement was conducted at the widest point of the hip bone, corresponding to the largest circumference of the thigh.
Ethical considerations
The study protocol received approval from the ethics committee of Shahid Sadoughi University of Medical Sciences in Yazd, Iran (Ethics ID: IR.SSU.SPH.REC.1402.059). Informed consent was also obtained from all participants prior to their enrollment in the study.
Data analysis
After entering the data into SPSS software version 26, to assess differences in general characteristics across tertiles, the authors employed one-way ANOVA for continuous variables and the chi-square test for categorical variables. Dietary intakes among the tertiles were analyzed using ANOVA. To examine the association between adherence to the GDQS and sperm parameters, the authors utilized multivariate logistic regression in both crude and adjusted models.
Results
Characteristics of the study population
Characteristics of the participants are presented in Table 1. The mean age of the participants was 33.8±5.7 years.
| Table 1. Descriptive characteristics of the study population (N=218). |
|
| Variable | |
| Quantitative | Mean ± SD |
| Age (y) | 33.8 ± 5.7 |
| Body mass index (kg/m2) | 25.7 ± 4.8 |
| Fat mass (%) | 22.9 ± 7.9 |
| Waist circumference (cm) | 93.8 ± 12.4 |
| Visceral fat (%) | 8.4 ± 4.3 |
| Sperm concentration | 36.2 ± 28.5 |
| Sperm motility Progressive |
30.8 ± 15.2 |
| Nonprogressive | 10.8 ± 6.1 |
| Immotile | 57.8 ± 16.4 |
| Sperm. morphology | 2.6 ± 1.7 |
| Physical activity (met) | 43.9 ± 4.9 |
| Qualitative | n (%) |
| Smoker Yea No |
72(33.1) 146 (66.9) |
| Education level High school Diploma Bachelor Master’s degree and higher |
33(15.1) 131(60.1) 44 (20.2) 10 (4.6) |
Dietary intakes of participants
Table 2 presents the mean and standard deviation of dietary component intakes across tertiles of the GDQS. Participants in the highest GDQS tertile (T3) showed significantly higher intake of energy, fruits, vegetables, nuts, and legumes compared to those in the lowest GDQS tertile (T1). There were no significant differences in the intake of whole grains, Polyunsaturated fatty acids (PUFA), and monounsaturated fatty acids (MUFA) between the two tertiles.
| Table 2. Dietary intakes of participants across tertiles of Global Diet Quality Score (GDQS). | ||||
| Variables | Tertiles of GDQS | P-valuea | ||
| T1 | T2 | T3 | ||
| Energy (kcal) | 2962.32±702.74b | 3106.85±627.24 | 3393.14±467.87 | ˂0.001 |
| Fruits (g) | 392.58±392.05 | 492.63±438.70 | 695.48±375.12 | 0.000 |
| Vegetables (g) | 100.25±138.91 | 116.08±88.46 | 163.92±117.18 | 0.004 |
| Nuts (g) | 10.25±12.28 | 18.98±22.39 | 20.22±21.57 | ˂0.01 |
| Legumes (g) | 38.88±31.81 | 47.14±39.42 | 64.85±30.87 | ˂0.001 |
| Whole grain (g) | 92.11±108.26 | 112.56±101.97 | 105.39±96.67 | 0.472 |
| PUFA (g) | 26.18±15.87 | 25.17±11.02 | 24.60±14.56 | 0.792 |
| MUFA (g) | 31.58±17.51 | 28.61±12.35 | 32.05±15.74 | 0.335 |
| a: obtained from one-way ANOVA; b: Mean±SD; PUFA: Polyunsaturated fatty acids; MUFA: Monounsaturated fatty acids. | ||||
Association between adherence to GDQS and odds of decreased sperm quality
Crude and multivariate-adjusted odds ratios for decreased sperm quality based on tertiles of GDQS are listed in Table 3. The results of this study demonstrated that in the unadjusted model, higher adherence to the GDQS was associated with a lower odds of low sperm concentration (OR: 0.60; 95% CI: 0.29–1.20; P=0.15). The significant association was no longer observed after adjusting for confounding factors, including BMI, total energy intake, physical activity, age, fat mass, waist circumference, visceral fat, tobacco and education. Furthermore, no significant associations were found between GDQS exposure and the odds of low semen volume, low sperm morphology, and low progressive/non-progressive motility in either crude or adjusted models. These findings from this observational study suggest a lack of statistically significant associations between overall GDQS exposure and the odds of decreased sperm quality across the examined semen parameters.
Discussion
While previous studies have focused on various nutritional aspects related to sperm quality parameters, this research examines the association between adherence to the GDQS and sperm parameters among Iranian adults in a Middle Eastern country, which has received less attention to date. The authors observed a non-significant association between adherence to GDQS and sperm parameters Accordingly, a cross-sectional study conducted on Iranian infertile men by Leilami et al. found no significant association between the Healthy Eating Index and most of the semen parameters after adjustment for confounders, except for sperm concentration; this highlights that the relationship between overall dietary quality and male fertility can be complex and may not always show universal significant associations across all parameters or populations (Leilami et al., 2022). A study on dietary patterns and semen quality in a university-based cohort by Joseph et al. concluded that while a 'Prudent' dietary pattern was linked to higher progressive sperm motility, it showed no significant association with sperm concentration and morphology. Furthermore, a 'Western' dietary pattern was found to be unrelated to conventional semen quality parameters (Joseph, 2021), and the following studies report observed effectiveness. The study by Nassan et al. investigated a consistent association between healthy dietary patterns and improved semen parameters (Nassan et al., 2018). The result of this study indicated that diets such as the Mediterranean pattern, as well as those rich in seafood, poultry, whole grains, legumes, skimmed milk, fruits, and vegetables, have been linked to enhanced semen quality across various studies conducted in North America, Europe, the Middle East, and East Asia. In contrast, unhealthy dietary patterns characterized by high consumption of fats, red and processed meats, refined grains, sweets, and sugary beverages are associated with lower semen quality (Nassan et al., 2018).
Crude and multivariate-adjusted odds ratios for decreased sperm quality based on tertiles of GDQS are listed in Table 3. The results of this study demonstrated that in the unadjusted model, higher adherence to the GDQS was associated with a lower odds of low sperm concentration (OR: 0.60; 95% CI: 0.29–1.20; P=0.15). The significant association was no longer observed after adjusting for confounding factors, including BMI, total energy intake, physical activity, age, fat mass, waist circumference, visceral fat, tobacco and education. Furthermore, no significant associations were found between GDQS exposure and the odds of low semen volume, low sperm morphology, and low progressive/non-progressive motility in either crude or adjusted models. These findings from this observational study suggest a lack of statistically significant associations between overall GDQS exposure and the odds of decreased sperm quality across the examined semen parameters.
Discussion
While previous studies have focused on various nutritional aspects related to sperm quality parameters, this research examines the association between adherence to the GDQS and sperm parameters among Iranian adults in a Middle Eastern country, which has received less attention to date. The authors observed a non-significant association between adherence to GDQS and sperm parameters Accordingly, a cross-sectional study conducted on Iranian infertile men by Leilami et al. found no significant association between the Healthy Eating Index and most of the semen parameters after adjustment for confounders, except for sperm concentration; this highlights that the relationship between overall dietary quality and male fertility can be complex and may not always show universal significant associations across all parameters or populations (Leilami et al., 2022). A study on dietary patterns and semen quality in a university-based cohort by Joseph et al. concluded that while a 'Prudent' dietary pattern was linked to higher progressive sperm motility, it showed no significant association with sperm concentration and morphology. Furthermore, a 'Western' dietary pattern was found to be unrelated to conventional semen quality parameters (Joseph, 2021), and the following studies report observed effectiveness. The study by Nassan et al. investigated a consistent association between healthy dietary patterns and improved semen parameters (Nassan et al., 2018). The result of this study indicated that diets such as the Mediterranean pattern, as well as those rich in seafood, poultry, whole grains, legumes, skimmed milk, fruits, and vegetables, have been linked to enhanced semen quality across various studies conducted in North America, Europe, the Middle East, and East Asia. In contrast, unhealthy dietary patterns characterized by high consumption of fats, red and processed meats, refined grains, sweets, and sugary beverages are associated with lower semen quality (Nassan et al., 2018).
| Table 3. Odds ratio of considered sperm disorder across tertiles of Global Diet Quality Score (GDQS) (Multivariable-adjusted odds ratios and 95% confidence intervals). |
||||
| Variables | Tertiles of GDQS | |||
| T1 | T2 | T3 | P-valuea | |
| Low concentration | ||||
| Crude | 1.00 | 0.603(0.299-1.216) | 0.600(0.295-1.220) | 0.15 |
| Adjusted model 1 | 1.00 | 0.718(0.342-1.509) | 0.360 (0.302-1.440) | 0.29 |
| Adjusted model 2 | 1.00 | 0.610(0.235-1.586) | 0.670(0.250-1.794) | 0.42 |
| Low morphology | ||||
| Crude | 1.00 | 1.100(0.433-2.793) | 0.836(0.340-2.058) | 0.69 |
| Adjusted model 1 | 1.00 | 1.081(0.394-2.968) | 0.620(0.223-1.725) | 0.36 |
| Adjusted model 2 | 1.00 | 0.983(0.250-3.857) | 0.675(0.163-2.791) | 0.58 |
| Low_progressive_nonprogressive_motility | ||||
| Crude | 1.00 | 0.658(0.329-1.316) | 0.768(0.384-1.539) | 0.45 |
| Adjusted model 1 | 1.00 | 0.645(0.307-1.354) | 0.938(0.438-2.009) | 0.86 |
| Adjusted model 2 | 1.00 | 0.827(0.325-2.102) | 0.864(0.324-2.308) | 0.77 |
| Low volume | ||||
| Crude | 1.00 | 1.331(0.400-4.431) | 1.055(0.289-3.844) | 0.93 |
| Adjusted model 1 | 1.00 | 1.088(0.309-3.827) | 0.810(0.196-3.353) | 0.77 |
| Adjusted model 2 | 1.00 | 1.156 (0.173-7.719) | 1.156 (0.173-7.719) | 0.88 |
| a: Third tertile compared to first tertile; Adjusted model 1: Adjusted for Body Mass Index, Total energy intake, physical activity; Adjusted model 2: adjusted for body mass index, total energy intake, physical activity, age, fat mass, waist circumference, visceral fat, tobacco and education. |
||||
A study conducted by Mahmoud Benatta et al. revealed that epidemiological observations consistently demonstrate an association between low-quality sperm parameters and higher intake of red meat, processed meat, organ meat, and full-fat dairy. Conversely, improved semen parameters were observed in subjects consuming a healthy diet rich in fruit, vegetables, whole grains, and fish (Benatta et al., 2020). Also. the study of Qostingh et al. examined the effect of dietary patterns on sperm quality. The results indicated that low intake of high-fat dairy products, sweets, and processed meats, combined with high consumption of folate-rich foods such as fruits and vegetables, is associated with better sperm quality. Additionally, a high intake of fruits, vegetables, fish, and whole grains is linked to a reduction in sperm DNA damage (Oostingh et al., 2017). In these studies, different dietary quality indicators have been utilized, including the Healthy Diet Score, Healthy Eating Index, Alternative Healthy Eating Index, and various adaptations of the Mediterranean diet. Despite these differences, a common finding is that diets rich in fruits, vegetables, legumes, nuts, whole grains, seafood, and fish are linked to improved sperm concentration and motility. Conversely, unhealthy dietary patterns characterized by high intake of fats, red and processed meats, refined grains, sweets, and sugary beverages are correlated with diminished semen quality. Currently, there is a global initiative to encourage a shift towards more plant-based diets for better human health (Willett et al., 2019). GDQS comprises 25 food groups, with those selected aligning well with this objective. Among the 17 healthy food groups recommended for inclusion in the diet, only four are of animal origin (Bromage et al., 2021). In contrast, of the nine unhealthy food groups that should be limited, three consist of animal proteins, along with sweets and ice cream, which often contain animal-derived ingredients. Consequently, a high GDQS is indicative of a predominantly plant-based diet (Bromage et al., 2021). The consumption of foods rich in omega-3 fatty acids in the context of GDQS is considered a positive factor, Numerous studies have documented the diverse biological effects of fatty acids on sperm membrane function. Specifically, dietary intake of certain fatty acids has been shown to influence sperm parameters through a variety of mechanisms. The biophysical characteristics of Docosahexaenoic acid (DHA) are likely to enhance the membrane fluidity and flexibility required for sperm tail motility (Calder, 2017). During epididymal maturation, sperm membranes exhibit an increased proportion of PUFAs, particularly DHA (Eslamian et al., 2015). This rise in PUFA levels appears to be largely regulated by local fatty acid metabolism, as indicated by the heightened expression of enzymes involved in this metabolic pathway within the testis and epididymis (Eslamian et al., 2015). Furthermore, trans fatty acids (TFAs) seem to inhibit the activity of these enzymes (Ferramosca and Zara, 2022), which may restrict the incorporation of long-chain PUFAs into sperm membranes, thereby influencing spermatogenesis (Niederberger, 2015). Nuts are energy-rich foods that are primarily composed of MUFAs, with the exception of walnuts, which are predominantly high in PUFAs, along with other essential nutrients (Alasalvar et al., 2020). The enhancements observed in specific seminal parameters may be attributed to their possible influence on sperm DNA fragmentation (SDF) and RNA expression (Salas-Huetos et al., 2018a). It is important to acknowledge that this study found no significant associations between GDQS and sperm parameters, including concentration, morphology, motility, and volume. This may be attributed to several limitations. First, the sample size, although substantial, might have been insufficient to detect subtle association of dietary patterns on sperm quality. Second, the sensitivity of the GDQS assessment, while designed to capture overall dietary quality, may not have been granular enough to identify specific nutrient-related impacts. Third, potential unmeasured confounding factors, such as genetic predispositions or environmental exposures, could have obscured the isolated impact of overall dietary quality. Furthermore, the complex interplay of nutrients and other lifestyle factors may obscure the isolated impact of overall dietary quality. Future studies with larger cohorts, more refined dietary assessments, and comprehensive control for confounders are warranted to further elucidate the relationship between diet and male fertility.
One of the strengths of the present study was a large sample size. Additionally, as the infertility clinic serves as a referral center in Middle Eastern countries, the unique dietary cultures and backgrounds may yield novel insights into the GDQS and its relationship with infertility. Another notable strength is that FFQ was administered by trained interviewers, ensuring that each item was clearly explained to participants before they selected their responses, thus minimizing self-reporting bias. Furthermore, the authors accounted for a variety of potential confounders, including energy intake, BMI, educational level, and physical activity. However, this study also had several limitations. The cross-sectional design restricts our ability to draw causal inferences. Additionally, employing a one-year FFQ may introduce errors in assessing dietary intakes and patterns, potentially leading to measurement errors and misclassification of participants, as well as reporting bias. Therefore, caution should be exercised when generalizing these results.
Conclusion
This cross-sectional study of infertile Iranian men found no significant association between the GDQS and sperm parameters after controlling for confounders. While this does not dismiss the importance of healthy eating, it suggests that specific nutrients, genetic factors, and lifestyle may play larger roles in male fertility. Future research requires large-scale prospective cohorts, clinical trials, and more detailed dietary pattern assessments to better understand the diet-fertility relationship.
Acknowledgements
The authors would like to thank all the participants without whom this study was
impossible.
Authors’ contributions
Darabi Z and Hosseinzadeh M conceived the idea and supervised the study. Hossaini BZ and Kharrazi M wrote the first draft. Kosari A were involved in study analysis. Hosseinzadeh M revised the manuscript. Authors read and approved the final version of the manuscript.
Conflict of interests
The authors declared no conflict of interest.
Funding
The present study was not funded.
References
Alasalvar C, Salvadó J-S & Ros E 2020. Bioactives and health benefits of nuts and dried fruits. Food chemistry. 314: 126192.
Almabhouh FA & Singh HJ 2022. Systematic review of literature documenting the link between BMI, sperm parameters, and leptin. Fertility & Reproduction. 4 (01): 1-10.
Angulo E, et al. 2021. Changes in the Global Diet Quality Score, weight, and waist circumference in Mexican women. Journal of nutrition. 151: 152S-161S.
Annapurna P & Pattnaik N 2022. Evaluation of histopathology of endometrium in primary infertile women, a prospective five years observational study in Konaseema region of Andhra Pradesh. International journal of reproduction, contraception, obstetrics and gynecology. 11 (3): 839-844.
Bell W, Blakstad MM, Milani P & Deitchler M 2025. The Global Diet Quality Score (GDQS)–Meal and GDQS-Menu metrics: How to measure meal and menu quality in institutional feeding programs. Nutrition reviews. 83 (Supplement_1): 81-92.
Benatta M, Kettache R, Buchholz N & Trinchieri A 2020. The impact of nutrition and lifestyle on male fertility. Arch Ital Urol Androl. 92 (2): 121-131.
Björndahl L & Brown JK 2022. The sixth edition of the WHO Laboratory Manual for the Examination and Processing of Human Semen: ensuring quality and standardization in basic examination of human ejaculates. Fertility and sterility. 117 (2): 246-251.
Bromage S, et al. 2021. Development and validation of a novel food-based Global Diet Quality Score (GDQS). Journal of nutrition. 151 (12 Suppl 2): 75s-92s.
Calder PC 2017. Omega-3 fatty acids and inflammatory processes: from molecules to man. Biochemical society transactions. 45 (5): 1105-1115.
Campos-Perez W, et al. 2020. Physical inactivity and excessive sucrose consumption are associated with higher serum lipids in subjects with Taq1B CETP polymorphism. Journal of human nutrition and dietetics. 33 (3): 299-307.
Cao LL, et al. 2022. The effect of healthy dietary patterns on male semen quality: a systematic review and meta-analysis. Asian Journal of Andrology. 24 (5): 549-557.
Chaves TdO & Reis MS 2019. Abdominal circumference or waist circumference? International journal of cardiovascular sciences. 32 (3): 290-292.
Cristodoro M, Zambella E, Fietta I, Inversetti A & Di Simone N 2024. Dietary patterns and fertility. Biology. 13 (2): 131.
Damigou E, et al. 2023. Diet quality and consumption of healthy and unhealthy foods measured via the global diet quality score in relation to Cardiometabolic outcomes in apparently healthy adults from the Mediterranean region: the ATTICA epidemiological cohort study (2002–2022). Nutrients. 15 (20): 4428.
de Vries CEJ, Veerman-Verweij EM, van den Hoogen A, de Man-van Ginkel JM & Ockhuijsen HDL 2024. The psychosocial impact of male infertility on men undergoing ICSI treatment: a qualitative study. Reprod health. 21 (1): 26.
Eghtesad S, et al. 2025. Relative Validity and Reproducibility of a Semi-quantitative Food Frequency Questionnaire to Assess Nutrient Intakes of PERSIAN Cohort Participants: Comparisons to 24-Hour Dietary Recalls and Selected Biomarkers. Archives of Iranian Medicine. 28 (9): 485.
Eslamian G, et al. 2015. Dietary fatty acid intakes and asthenozoospermia: a case-control study. Fertility and sterility. 103 (1): 190-198.
Fejes I, Koloszar S, Szöllo J, Zavaczki Z & Pal A 2005. Is semen quality affected by male body fat distribution? Andrologia. 37 (5): 155-159.
Ferramosca A & Zara V 2022. Diet and male fertility: the impact of nutrients and antioxidants on sperm energetic metabolism. International journal of molecular sciences. 23 (5): 2542.
He Y, et al. 2021. Application of the Global Diet Quality Score in Chinese adults to evaluate the double burden of nutrient inadequacy and metabolic syndrome. Journal of nutrition. 151: 93S-100S.
Inhorn MC & Patrizio P 2015. Infertility around the globe: new thinking on gender, reproductive technologies and global movements in the 21st century. Human reproduction update. 21 (4): 411-426.
Joseph MD 2021. Anthropometric and lifestyle determinants of semen quality: A prospective cohort study. Boston University.
Leilami K, Zareie A, Nouri M, Bagheri M & Shirani M 2022. The association between healthy eating index score with semen parameters in infertile men: A cross-sectional study. International journal of reproductive bioMedicine. 20 (11): 931-940.
Mehrabani S, et al. 2025. The association between global and prime diet quality scores and the risk of bacterial vaginosis: a secondary analysis of case-control study. Journal of health, population and nutrition. 44 (1): 58.
Nassan FL, Chavarro JE & Tanrikut C 2018. Diet and men's fertility: does diet affect sperm quality? Fertil steril. 110 (4): 570-577.
Naz MSG, et al. 2019. The prevalence of polycystic ovary syndrome in adolescents: A systematic review and meta-analysis. International journal of reproductive biomedicine. 17 (8): 533.
Niederberger C 2015. Re: Dietary fatty acid intakes and asthenozoospermia: A case-control study. Journal of urology. 194 (2): 499.
Oostingh EC, Steegers-Theunissen RP, de Vries JH, Laven JS & Koster MP 2017. Strong adherence to a healthy dietary pattern is associated with better semen quality, especially in men with poor semen quality. Fertil steril. 107 (4): 916-923.e912.
Ricci E, et al. 2019. Mediterranean diet and the risk of poor semen quality: cross-sectional analysis of men referring to an Italian Fertility Clinic. Andrology. 7 (2): 156-162.
Rohde K, et al. 2019. Genetics and epigenetics in obesity. Metabolism. 92: 37-50.
Salas-Huetos A, Bulló M & Salas-Salvadó J 2017a. Dietary patterns, foods and nutrients in male fertility parameters and fecundability: a systematic review of observational studies. Hum Reprod Update. 23 (4): 371-389.
Salas-Huetos A, Bulló M & Salas-Salvadó J 2017b. Dietary patterns, foods and nutrients in male fertility parameters and fecundability: a systematic review of observational studies. Human reproduction update. 23 (4): 371-389.
Salas-Huetos A, et al. 2018a. Effect of nut consumption on semen quality and functionality in healthy men consuming a Western-style diet: a randomized controlled trial. American journal of clinical nutrition. 108 (5): 953-962.
Salas-Huetos A, et al. 2018b. The effect of nutrients and dietary supplements on sperm quality parameters: a systematic review and meta-analysis of randomized clinical trials. Advances in nutrition. 9 (6): 833-848.
Satija A, et al. 2017. Healthful and unhealthful plant-based diets and the risk of coronary heart disease in US adults. Journal of the American college of cardiology. 70 (4): 411-422.
Seidelmann SB, et al. 2018. Dietary carbohydrate intake and mortality: a prospective cohort study and meta-analysis. Lancet public health. 3 (9): e419-e428.
Soltani M, et al. 2025. The association between consumption of ultra-processed foods and sperm quality parameters: a cross-sectional study. BMC research notes. 18 (1): 48.
Sun H, et al. 2019. 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. 11 (23): 10952.
Torres-Arce E, Vizmanos B, Babio N, Márquez-Sandoval F & Salas-Huetos A 2021. Dietary antioxidants in the treatment of male infertility: Counteracting oxidative stress. Biology. 10 (3).
Vander Borght M & Wyns C 2018. Fertility and infertility: Definition and epidemiology. Clinical biochemistry. 62: 2-10.
Wasilewski T, Łukaszewicz-Zając M, Wasilewska J & Mroczko B 2020. Biochemistry of infertility. Clinica chimica acta. 508: 185-190.
Willett W, et al. 2019. Food in the anthropocene: the EAT-Lancet commission on healthy diets from sustainable food systems. Lancet. 393 (10170): 447-492.
One of the strengths of the present study was a large sample size. Additionally, as the infertility clinic serves as a referral center in Middle Eastern countries, the unique dietary cultures and backgrounds may yield novel insights into the GDQS and its relationship with infertility. Another notable strength is that FFQ was administered by trained interviewers, ensuring that each item was clearly explained to participants before they selected their responses, thus minimizing self-reporting bias. Furthermore, the authors accounted for a variety of potential confounders, including energy intake, BMI, educational level, and physical activity. However, this study also had several limitations. The cross-sectional design restricts our ability to draw causal inferences. Additionally, employing a one-year FFQ may introduce errors in assessing dietary intakes and patterns, potentially leading to measurement errors and misclassification of participants, as well as reporting bias. Therefore, caution should be exercised when generalizing these results.
Conclusion
This cross-sectional study of infertile Iranian men found no significant association between the GDQS and sperm parameters after controlling for confounders. While this does not dismiss the importance of healthy eating, it suggests that specific nutrients, genetic factors, and lifestyle may play larger roles in male fertility. Future research requires large-scale prospective cohorts, clinical trials, and more detailed dietary pattern assessments to better understand the diet-fertility relationship.
Acknowledgements
The authors would like to thank all the participants without whom this study was
impossible.
Authors’ contributions
Darabi Z and Hosseinzadeh M conceived the idea and supervised the study. Hossaini BZ and Kharrazi M wrote the first draft. Kosari A were involved in study analysis. Hosseinzadeh M revised the manuscript. Authors read and approved the final version of the manuscript.
Conflict of interests
The authors declared no conflict of interest.
Funding
The present study was not funded.
References
Alasalvar C, Salvadó J-S & Ros E 2020. Bioactives and health benefits of nuts and dried fruits. Food chemistry. 314: 126192.
Almabhouh FA & Singh HJ 2022. Systematic review of literature documenting the link between BMI, sperm parameters, and leptin. Fertility & Reproduction. 4 (01): 1-10.
Angulo E, et al. 2021. Changes in the Global Diet Quality Score, weight, and waist circumference in Mexican women. Journal of nutrition. 151: 152S-161S.
Annapurna P & Pattnaik N 2022. Evaluation of histopathology of endometrium in primary infertile women, a prospective five years observational study in Konaseema region of Andhra Pradesh. International journal of reproduction, contraception, obstetrics and gynecology. 11 (3): 839-844.
Bell W, Blakstad MM, Milani P & Deitchler M 2025. The Global Diet Quality Score (GDQS)–Meal and GDQS-Menu metrics: How to measure meal and menu quality in institutional feeding programs. Nutrition reviews. 83 (Supplement_1): 81-92.
Benatta M, Kettache R, Buchholz N & Trinchieri A 2020. The impact of nutrition and lifestyle on male fertility. Arch Ital Urol Androl. 92 (2): 121-131.
Björndahl L & Brown JK 2022. The sixth edition of the WHO Laboratory Manual for the Examination and Processing of Human Semen: ensuring quality and standardization in basic examination of human ejaculates. Fertility and sterility. 117 (2): 246-251.
Bromage S, et al. 2021. Development and validation of a novel food-based Global Diet Quality Score (GDQS). Journal of nutrition. 151 (12 Suppl 2): 75s-92s.
Calder PC 2017. Omega-3 fatty acids and inflammatory processes: from molecules to man. Biochemical society transactions. 45 (5): 1105-1115.
Campos-Perez W, et al. 2020. Physical inactivity and excessive sucrose consumption are associated with higher serum lipids in subjects with Taq1B CETP polymorphism. Journal of human nutrition and dietetics. 33 (3): 299-307.
Cao LL, et al. 2022. The effect of healthy dietary patterns on male semen quality: a systematic review and meta-analysis. Asian Journal of Andrology. 24 (5): 549-557.
Chaves TdO & Reis MS 2019. Abdominal circumference or waist circumference? International journal of cardiovascular sciences. 32 (3): 290-292.
Cristodoro M, Zambella E, Fietta I, Inversetti A & Di Simone N 2024. Dietary patterns and fertility. Biology. 13 (2): 131.
Damigou E, et al. 2023. Diet quality and consumption of healthy and unhealthy foods measured via the global diet quality score in relation to Cardiometabolic outcomes in apparently healthy adults from the Mediterranean region: the ATTICA epidemiological cohort study (2002–2022). Nutrients. 15 (20): 4428.
de Vries CEJ, Veerman-Verweij EM, van den Hoogen A, de Man-van Ginkel JM & Ockhuijsen HDL 2024. The psychosocial impact of male infertility on men undergoing ICSI treatment: a qualitative study. Reprod health. 21 (1): 26.
Eghtesad S, et al. 2025. Relative Validity and Reproducibility of a Semi-quantitative Food Frequency Questionnaire to Assess Nutrient Intakes of PERSIAN Cohort Participants: Comparisons to 24-Hour Dietary Recalls and Selected Biomarkers. Archives of Iranian Medicine. 28 (9): 485.
Eslamian G, et al. 2015. Dietary fatty acid intakes and asthenozoospermia: a case-control study. Fertility and sterility. 103 (1): 190-198.
Fejes I, Koloszar S, Szöllo J, Zavaczki Z & Pal A 2005. Is semen quality affected by male body fat distribution? Andrologia. 37 (5): 155-159.
Ferramosca A & Zara V 2022. Diet and male fertility: the impact of nutrients and antioxidants on sperm energetic metabolism. International journal of molecular sciences. 23 (5): 2542.
He Y, et al. 2021. Application of the Global Diet Quality Score in Chinese adults to evaluate the double burden of nutrient inadequacy and metabolic syndrome. Journal of nutrition. 151: 93S-100S.
Inhorn MC & Patrizio P 2015. Infertility around the globe: new thinking on gender, reproductive technologies and global movements in the 21st century. Human reproduction update. 21 (4): 411-426.
Joseph MD 2021. Anthropometric and lifestyle determinants of semen quality: A prospective cohort study. Boston University.
Leilami K, Zareie A, Nouri M, Bagheri M & Shirani M 2022. The association between healthy eating index score with semen parameters in infertile men: A cross-sectional study. International journal of reproductive bioMedicine. 20 (11): 931-940.
Mehrabani S, et al. 2025. The association between global and prime diet quality scores and the risk of bacterial vaginosis: a secondary analysis of case-control study. Journal of health, population and nutrition. 44 (1): 58.
Nassan FL, Chavarro JE & Tanrikut C 2018. Diet and men's fertility: does diet affect sperm quality? Fertil steril. 110 (4): 570-577.
Naz MSG, et al. 2019. The prevalence of polycystic ovary syndrome in adolescents: A systematic review and meta-analysis. International journal of reproductive biomedicine. 17 (8): 533.
Niederberger C 2015. Re: Dietary fatty acid intakes and asthenozoospermia: A case-control study. Journal of urology. 194 (2): 499.
Oostingh EC, Steegers-Theunissen RP, de Vries JH, Laven JS & Koster MP 2017. Strong adherence to a healthy dietary pattern is associated with better semen quality, especially in men with poor semen quality. Fertil steril. 107 (4): 916-923.e912.
Ricci E, et al. 2019. Mediterranean diet and the risk of poor semen quality: cross-sectional analysis of men referring to an Italian Fertility Clinic. Andrology. 7 (2): 156-162.
Rohde K, et al. 2019. Genetics and epigenetics in obesity. Metabolism. 92: 37-50.
Salas-Huetos A, Bulló M & Salas-Salvadó J 2017a. Dietary patterns, foods and nutrients in male fertility parameters and fecundability: a systematic review of observational studies. Hum Reprod Update. 23 (4): 371-389.
Salas-Huetos A, Bulló M & Salas-Salvadó J 2017b. Dietary patterns, foods and nutrients in male fertility parameters and fecundability: a systematic review of observational studies. Human reproduction update. 23 (4): 371-389.
Salas-Huetos A, et al. 2018a. Effect of nut consumption on semen quality and functionality in healthy men consuming a Western-style diet: a randomized controlled trial. American journal of clinical nutrition. 108 (5): 953-962.
Salas-Huetos A, et al. 2018b. The effect of nutrients and dietary supplements on sperm quality parameters: a systematic review and meta-analysis of randomized clinical trials. Advances in nutrition. 9 (6): 833-848.
Satija A, et al. 2017. Healthful and unhealthful plant-based diets and the risk of coronary heart disease in US adults. Journal of the American college of cardiology. 70 (4): 411-422.
Seidelmann SB, et al. 2018. Dietary carbohydrate intake and mortality: a prospective cohort study and meta-analysis. Lancet public health. 3 (9): e419-e428.
Soltani M, et al. 2025. The association between consumption of ultra-processed foods and sperm quality parameters: a cross-sectional study. BMC research notes. 18 (1): 48.
Sun H, et al. 2019. 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. 11 (23): 10952.
Torres-Arce E, Vizmanos B, Babio N, Márquez-Sandoval F & Salas-Huetos A 2021. Dietary antioxidants in the treatment of male infertility: Counteracting oxidative stress. Biology. 10 (3).
Vander Borght M & Wyns C 2018. Fertility and infertility: Definition and epidemiology. Clinical biochemistry. 62: 2-10.
Wasilewski T, Łukaszewicz-Zając M, Wasilewska J & Mroczko B 2020. Biochemistry of infertility. Clinica chimica acta. 508: 185-190.
Willett W, et al. 2019. Food in the anthropocene: the EAT-Lancet commission on healthy diets from sustainable food systems. Lancet. 393 (10170): 447-492.
Type of article: orginal article |
Subject:
public specific
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
