Skip to main content
Download PDF
Download ePub

Association between dietary inflammatory index and infertility of women; Results from RaNCD Cohort Study

Nutrition Journal volume 22, Article number: 35 (2023) Cite this article

Abstract

Background

In recent decades, more and more attention has been paid to the influence of nutrition on reproductive health. Nevertheless, the imminent association between diet-related inflammation and the risk of infertility has not yet been established. The aim of the current study was to investigate the ability of the Dietary Inflammatory Index (DII) to estimate infertility incidence in women.

Methods

This cross-sectional study was conducted using data from Ravansar non-communicable diseases (RaNCD) cohort study on 4437 participants. The DII was calculated based on the reported consumption of up to 31 food parameters measured via a validated and reproducible 118-item food-frequency questionnaire (FFQ). Multiple logistic regression analysis was applied to estimate the multivariable odds ratio (OR) adjusted for potential confounding variables.

Results

Out of all participants, 411 women (9.26%) were infertile. The mean ± SD age and weight of infertile women were 43.67 ± 7.47 years and 72.86 ± 13.02 kg, respectively. Statistical analyses showed the odds ratio of infertility in the fourth quartile (pro-inflammatory diet) was 1.76 times higher than in the first quartile (anti-inflammatory diet) of DII (95% CI: 1.57–2.02).

Conclusions

The findings of this study provide compelling evidence about the association between infertility and the quality of diet in women. Therefore, interventions and programs aimed at promoting a healthy lifestyle and using healthy diets can be considered as one of the effective approaches in the prevention and treatment of infertility in women.

Peer Review reports

Introduction

Infertility is defined as a reproductive failure after at least one year of unprotected sex, which affects approximately 10–15% of women worldwide. Approximately 15.5% of married women aged 15 to 44 years in Iran are unable to become pregnant after one year of unprotected sex (infertility) [1, 2]. Although male infertility is involved in more than half of childlessness, women’s infertility is still considered a global social problem [3]. The results from the Tehran Lipid and Glucose Study showed that the prevalence of all causes of infertility is higher than that of global infertility among Iranian women [4].

Although infertility therapeutic techniques have been developed, the high cost of these methods can lead individuals to come to alternative and inexpensive treatments [5]. Most recently, the recognition of modifiable factors in the treatment of infertility has been of interest in many studies [6,7,8,9]. The role of diet and lifestyle in infertility is largely unknown. However, substantial data suggest that dietary factors affecting inflammation may have a significant role in the etiology of some types of infertility. In addition, biochemical markers of chronic inflammation, such as high concentrations of C reactive protein (CRP), have been prospectively linked to increased infertility [10, 11]. Studies have shown that diet modification, as an important component of lifestyle, seems to be a promising approach to reducing inflammation and consequently reducing the risk of infertility [12].

The dietary inflammatory index has been designed to recognize the inflammatory potential of individuals’ dietary patterns [13]. The pro-inflammatory or anti-inflammatory properties of some foods can have beneficial or harmful effects on inflammatory factors, including interleukin-1β, IL-4, IL-6, IL-10, tumor necrosis factor-alpha (TNF-α), and CRP [14,15,16,17]. In addition, most previous studies have evaluated the relationship between reproductive function and individual nutrients, foods, food groups, or diets. Systematic reviews in this area reported no significant differences in menstrual, reproductive or metabolic characteristics of different food components in the majority of included studies [18]. Besides, Stamets et al. showed that following two different low-calorie diets (high protein and high carbohydrate) improved fertility and there was no difference between the two diets [19]. In addition, another study looked at the effects of a low-carb diet, or a diet high in monounsaturated fat, compared to a standard diet. This study found that a low-carb diet increases insulin sensitivity but has no effect on circulating reproductive hormones [20].

Table 1 Prevalence and 95% confidence interval of fertility status based on demographic variables
Full size table

To date, no study has examined the association between DII and the risk of women’s infertility. Therefore, to illuminate this uncharted area, the current study was performed using data from a cohort study in a RaNCD cohort study to examine the relationship between women’s infertility and DII.

Materials and methods

Study design and participants

This cross-sectional study was performed by using data from the RaNCD cohort study. The RaNCD cohort study is part of the PERSIAN (Prospective Epidemiological Research Studies in Iran) Cohort that has been conducted to investigate non-communicable diseases in 10,047 Kurdish participants aged 35–65 years living in Ravansar city, Kermanshah Province, West Iran since 2014. Details of this study were defined in previous studies [21, 22]. All study subjects included women who participated in the RaNCD cohort study. Also, this study was approved by the ethics committee of Kermanshah University of medical sciences with code No.IR.KUMS.REC.1401.218 and conducted in accordance with the Declaration of Helsinki.

Infertility was determined based on a self-administered questionnaire about fertility history that was completed for all participant women. All women aged 20–50 years old who had the inclusion criteria and were willing to collaborate were included in the study. Written consent has been obtained from all participants. The collected data were investigated by the center supervisor and ultimately recorded after ensuring their accuracy on the same day. In case of any problem, follow-up was performed and the subjects were asked to present in the cohort center and complete the questionnaire again. In this study, the online version of the standard questionnaires was used to collect information, in accordance with the PERSIAN cohort protocol. However, the questionnaires used in this study were revised after performing a pre-pilot phase to improve their validity and reliability. The exclusion criteria were the absence of any malignancy, following a special diet, and having conditions such as neurological, hepatic, and endocrine diseases was our inclusion criteria. Among the all participants, 4764 were men and excluded from the study. Also, other excluded participants were as follows; 447 single and divorced women, 162 women with a history of hysterectomy, 105 pregnant women, 112 women who intake more than 4200 calories, and 20 who intake less than 800 calories. Finally, 4437 women (411 infertile and 4026 non-infertile) were included in this study.

Basic data collection

Baseline questionnaires including demographic, socioeconomic status, physical activity, smoking status, alcohol intake, dietary habits, medical history, family medical history, and FFQ were completed in face-to-face interviews by a trained interviewer for all participants recruited to RaNCD.

Table 2 The Metabolic profile and dietary intakes of participants
Full size table

Physical activity assessment

In RaNCD cohort study, physical activity was assessed by the standard questionnaire designed by PERSIAN mega cohort study with twenty two questions about the amount of daily activities. After collecting data, the participants’ responses were reported based on the metabolic equivalent of task per hour per day (MET/h per day). Detail of this questionnaire was described in the previous study [23]. Finally the total MET were categorized in three tertiles (Light-intensity activities < 3, Moderate-intensity activities: 3–6, Vigorous intensity activities: ≥ 6) [24, 25].

Anthropometry data

Weight was measured by an InBody 770 device while the participant was wearing light and without shoes with a precision of 100 gr. Height measurement was performed by using the automatic stadiometer BSM 370 in a standing position without shoes. Body mass index (BMI) was determined by dividing the weight (kg) by squared height (meter).

Table 3 Characteristics of the participants according to the quartiles of DII
Full size table

Dietary assessment and DII calculation

At the RaNCD study site, a 118-item FFQ was completed, and the validity and reliability of this questionnaire have been assessed in previous studies [26, 27]. We obtained dietary information from this questionnaire and then calculated the DII score based on the method developed by Shivappa et al. [28]. In this method, 45 food items were introduced that had a role in decreasing or increasing inflammation. In this study, among these food items, we accessed only 31 of them, including onion, garlic, coffee, tea, energy, protein, carbohydrates, fiber, vitamins A, C, D, E, B1, B2, B3, B6, B12, folate, beta-carotene, total fat, saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), polyunsaturated fatty acids (PUFAs), omega 3 and 6, cholesterol, Mg, Fe, Se, and Zn. These food item intakes were linked to the world database mean and SD from 11 studies worldwide [28]. Finally, all food items specified for the DII score were summed, and the DII score was created. A higher DII adhered to a pro-inflammatory diet, and a low DII was associated with an anti-inflammatory diet. The DII quartile cutoff points were categorized based on cutoff points: Quartiles 1= < -2.02; Quartiles 2= -2.02, -1.02; Quartiles 3= -1.03, 0.25; and Quartiles 4 ≥ 0.26.

Statistical methods

Data are accessible as the mean (standard deviation) and frequency (%) for continuous and categorical variables. The normality of the data was assessed and proven by the Kolmogorov–Smirnov test. Independent samples t-tests and one-way ANOVA tests were used for between-group differences of continuous variables. Additionally, the chi-square/Fisher exact test was used to assess the associations between two categorical variables, as well as the chi-square test was used for testing multiple categorical variables. Logistic regression was performed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for infertility as the outcome adjusting for age, BMI, SES, and physical activity. P-values for trends were calculated across DII quartiles. All statistical analyses were performed using STATA version 14.1 (Stata Corp, College Station, TX, USA). A P-value < 0.05 was considered statistically significant.

Results

Among 4437 women enrolled in this study, 411 (9.26%) were infertile. Almost 60% of participants were urban and 299 (12.51%) of them were infertile. Among infertile women, 252 (61.3%) of them had low physical activity (3 > MET/ h per day) which was significantly different from the fertile women (P = 0.001). (Table 1).

Table 4 Findings from the logistic regression models that evaluated infertility according to DII quartiles
Full size table

The mean ± SD age in the infertile women was 43.67 ± 7.47 years and in the non-fertile was 48.42 ± 8.16 years. Also, the mean ± SD weight in the infertile women was 72.86 ± 13.02 kg, and in non-fertile was 70.27 ± 12.77 kg. The mean energy intake in the infertile women was 2004.5 ± 275.2 kcal/day, containing 322.9 ± 95.7 g/day carbohydrates, 49.4 ± 15.2 g/day fat, and 71.4 ± 13.2 g/day protein. According to the gram of intake from each macronutrient in infertile women, the daily percentages of carbohydrates, fat, and protein were 64.4%, 22.1%, and 14.2%, respectively (Table 2).

Table 3 summarizes the characteristics of the participants according to the quartiles of DII. The minimum and, maximum DII score was from − 2.02, (the most powerful anti-inflammatory diet) to 0.26 (the most powerful pro-inflammatory diet). There was a significant difference in the age, weight, and BMI of the participants (P < 0.001) between the DII quartiles. Also, the lipid profile including Total cholesterol (P < 0.001), LDL-C (P < 0.001), and HDL-C (P < 0.001) were significant differences between the DII quartiles. The mean total calorie intake in the fourth quartile (2135.58 ± 175.58 Kcal/d) was significantly higher than the first quartile (1877.52 ± 131.39 Kcal/d) of DII (P < 0.001). Besides, the mean energy intake from protein in the fourth quartile (391.78 ± 22.09 Kcal/d) was significantly higher than the first quartile (150.52 ± 14.06 Kcal/d) of DII (P < 0.001). However, there is no significant difference in the mean energy intake from carbohydrates and fat between the DII quartiles. In addition, the highest and lowest fiber intake was related to the first and fourth quartiles, respectively, which showed a significant difference (P < 0.001). (Table 3).

The odds of infertility in the fourth quartile of the DII (pro-inflammatory diet) is significantly 86% (OR: 1.86; 95% CI: 1.65, 2.14) higher than the first quartile (anti-inflammatory diet). After adjusting for main confounding factors including age, BMI, marital status, smoking, education, alcohol drinking, energy intake, and physical activity, the odds of infertility in the fourth quartile (pro-inflammatory) was 76% (OR: 1.76; 95% CI: 1.57–2.02) higher than first quartile (anti-inflammatory) (Table 4).

Discussion

The present study provides evidence of an association between dietary inflammation and infertility in women. The findings of this cross-sectional study showed that having a pro-inflammatory diet increases the probability of infertility in women by 86%, which remained significant after controlling for confounding factors with odds of 76%.

Some previous investigations have examined the association between major dietary patterns and infertility. In this way, a study investigated the relationship between diet and reproductive outcomes in infertile women. In this study, three major dietary patterns have been identified (healthy, western, and unhealthy diets). Consistent with our study, they concluded that greater adherence to a healthy diet may enhance oocyte quality and quantity. On the other hand, an unhealthy diet could negatively affect the chance of pregnancy [29]. Unisa et al. 2021; conducted a study on 402,807 currently married women aged 20–49 years in India to assess the degree of primary infertility and its associated factors. At the end of the study, the results showed infertility in women is related to their diet and morbidity, and a positive influence of dark green leafy vegetables, fruits, and milk/curd was observed [30].

In addition, a randomized clinical trial showed that a healthy diet rich in fruits and vegetables, similar to the Dietary Approaches to Stop Hypertension (DASH), can have a positive effect on total antioxidant capacity (TAC). In this study, 60 women were randomly assigned to the DASH diet group (rich in fruits, vegetables, whole grains, low-fat dairy, low in saturated fat and cholesterol, refined grains, and sweets) and a control group. After 12 weeks of follow-up, women in the DASH diet group had increased TAC. Additionally, another study showed that an increase in the DASH diet was associated with an increase in plasma TAC in obese subjects with PCOS. In this study, the “healthy diet” had higher vegetables, fruits, and nuts which these food groups are rich in antioxidants [31]. It has been shown that the antioxidant capacity of plasma can be increased significantly by the antioxidants found in fruits and vegetables and it seems that a high TAC level can positively affect the percentage of oocytes and the quality of second-stage oocytes [32].

Inflammation is one of the main causes of infertility in endometriosis. It prevents decasualization, lowers progesterone levels, and disrupts endometrial function. Moreover, hormonal imbalances caused by the different diseases play a significant role in infertility, as inflammation increases aromatase activity and creates an estrogen-dominant phase. Besides, oocyte maturation and fertilization are influenced by prostaglandins and cytokines from inflammatory cells. In this way, not only the reproductive system of the woman is affected, but also the sperm entering through the uterus and fallopian tubes, their movement is reduced and their attachment to the ovary is damaged. Reactive oxygen species also damage the endometrium, Oocyte, and sperm, resulting in oxidative stress that affects the molecular level [33].

Chronic inflammation is a popular explanation of the positive association between DII and infertility, which may occur through the effect of a pro-inflammatory diet on increasing systemic inflammation [13]. Some studies have also reported that chronic inflammation plays a significant role in the risk of infertility [34]. However, we recognize that there are extensive debates among researchers about the etiology of infertility, which is multifactorial, and the only mechanism will not be whispered responsible for all cases of infertility.

The present study had some limitations in terms of methodology and nature. Firstly, the DII score was calculated using only 31 dietary parameters due to a limitation in the number of parameters. A second limitation of the present study was that, because of its cross-sectional design, there was no way to examine the causal relationship between DII and the progression of infertility. However, this study had some strengths. An important strength of this study was its large sample size, which allowed it to determine the relationship between DII and infertility among Kurdish women in Iran. Other strengths of this study are the high quality of data collection, population-based study design, and adjustment for all known confounders such as age, BMI, SES, and physical activity. As well, using DII instead of inflammatory markers to assess the effect of inflammation may help directly measure the impact of diet on clinical outcomes through inflammation and reduce the overall cost of the study. Additionally, the calculation of the DII by an inexpensive and non-invasive method (FFQ) makes it possible to evaluate the inflammatory properties of food and its relationship with some diseases. In summary, these novel findings from the cohort study provide evidence that a more pro-inflammatory diet as indexed by the DII score increased the odds of infertility. Our findings showed that a diet rich in vegetable fibers and omega-3 fatty acids and low in unhealthy dietary factors such as high simple sugars and saturated fats can be considered an appropriate approach for reducing the risk of infertility. However, more investigations are necessary to validate the kinds of conclusions that can be drawn from this study. Our data suggest that we still have a long way to go, and future research should also examine whether altering the inflammatory potential of the diet can reduce chronic inflammation and the risk of infertility.

Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Barbieri RL. Female infertility. Yen and Jaffe’s Reproductive Endocrinology. Elsevier; 2019. pp. 556–81. e7.

  2. Akhondi MM, Ranjbar F, Shirzad M, Ardakani ZB, Kamali K, Mohammad K. Practical difficulties in estimating the prevalence of primary infertility in Iran. Int J Fertil Steril. 2019;13(2):113–7.

    PubMed  PubMed Central  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  4. Kazemijaliseh H, Tehrani FR, 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.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Chavarro JE, Rich-Edwards JW, Rosner BA, Willett WC. Protein intake and ovulatory infertility. Am J Obstet Gynecol. 2008;198(2):210. e1-. e7.

    Article  PubMed Central  Google Scholar 

  6. Chavarro JE, Rich-Edwards JW, Rosner BA, Willett WC. Caffeinated and alcoholic beverage intake in relation to ovulatory disorder infertility. Epidemiol. 2009;20(3):374–81.

    Article  Google Scholar 

  7. Broughton DE, Moley KH. Obesity and female infertility: potential mediators of obesity’s impact. Fertil Steril. 2017;107(4):840–7.

    Article  PubMed  Google Scholar 

  8. Chavarro JE, Rich-Edwards JW, Rosner BA, Willett WC. Diet and lifestyle in the prevention of ovulatory disorder infertility. Obstet Gynecol. 2007;110(5):1050–8.

    Article  PubMed  Google Scholar 

  9. Environment ft, Team RHS. Serum 25-hydroxyvitamin D concentrations and treatment outcomes of women undergoing assisted reproduction. Am J Clin Nutr. 2016;104(3):729–35.

    Article  Google Scholar 

  10. Vannuccini S, Clifton VL, Fraser IS, Taylor HS, Critchley H, Giudice LC, et al. Infertility and reproductive disorders: impact of hormonal and inflammatory mechanisms on pregnancy outcome. Hum Reprod Update. 2016;22(1):104–15.

    Article  CAS  PubMed  Google Scholar 

  11. Davis JS. Connecting female infertility to obesity, inflammation, and maternal gut dysbiosis. Endocrinology. 2016;157(5):1725–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Chiu Y-H, Chavarro JE, Souter I. Diet and female fertility: doctor, what should I eat? Fertil Steril. 2018;110(4):560–9.

    Article  PubMed  Google Scholar 

  13. Cavicchia PP, Steck SE, Hurley TG, Hussey JR, Ma Y, Ockene IS, et al. A new dietary inflammatory index predicts interval changes in serum high-sensitivity C-reactive protein. J Nutr. 2009;139(12):2365–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Abdollahzad H, Pasdar Y, Nachvak SM, Rezaeian S, Saber A, Nazari R. The Relationship between the Dietary Inflammatory Index and metabolic syndrome in Ravansar Cohort Study. Diabetes, metabolic syndrome and obesity: targets and therapy. 2020;13:477–87.

  15. Moludi J, Moradinazar M, Hamzeh B, Najafi F, Soleimani D, Pasdar Y. Depression relationship with dietary patterns and dietary inflammatory index in women: result from ravansar cohort study. Neuropsychiatr Dis Treat. 2020;16:1595–603.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Darbandi M, Hamzeh B, Ayenepour A, Rezaeian S, Najafi F, Shakiba E, et al. Anti-inflammatory diet consumption reduced fatty liver indices. Sci Rep. 2021;11(1):1–8.

    Article  Google Scholar 

  17. Jam SA, Rezaeian S, Najafi F, Hamzeh B, Shakiba E, Moradinazar M, et al. Association of a pro-inflammatory diet with type 2 diabetes and hypertension: results from the Ravansar non-communicable diseases cohort study. Arch Public Health. 2022;80(1):1–8.

    Article  Google Scholar 

  18. Moran LJ, Ranasinha S, Zoungas S, McNaughton SA, Brown WJ, Teede HJ. The contribution of diet, physical activity and sedentary behaviour to body mass index in women with and without polycystic ovary syndrome. Hum Reprod. 2013;28(8):2276–83.

    Article  CAS  PubMed  Google Scholar 

  19. Stamets K, Taylor DS, Kunselman A, Demers LM, Pelkman CL, Legro RS. A randomized trial of the effects of two types of short-term hypocaloric diets on weight loss in women with polycystic ovary syndrome. Fertil Steril. 2004;81(3):630–7.

    Article  CAS  PubMed  Google Scholar 

  20. Douglas CC, Norris LE, Oster RA, Darnell BE, Azziz R, Gower BA. Difference in dietary intake between women with polycystic ovary syndrome and healthy controls. Fertil Steril. 2006;86(2):411–7.

    Article  PubMed  Google Scholar 

  21. Pasdar Y, Najafi F, Moradinazar M, Shakiba E, Karim H, Hamzeh B, et al. Cohort profile: Ravansar Non-Communicable Disease cohort study: the first cohort study in a kurdish population. Int J Epidemiol. 2019;48(3):682–3 f.

    Article  PubMed  Google Scholar 

  22. Poustchi H, Eghtesad S, Kamangar F, Etemadi A, Keshtkar A-A, Hekmatdoost A, et al. Prospective epidemiological research studies in Iran (the PERSIAN Cohort Study): rationale, objectives, and design. Am J Epidemiol. 2017;187(4):647–55.

    Article  PubMed Central  Google Scholar 

  23. Poustchi H, Eghtesad S, Kamangar F, Etemadi A, Keshtkar A-A, Hekmatdoost A, et al. Prospective epidemiological research studies in Iran (the PERSIAN Cohort Study): rationale, objectives, and design. Am J Epidemiol. 2018;187(4):647–55.

    Article  PubMed  Google Scholar 

  24. Larson-Meyer DE. A systematic review of the Energy cost and metabolic intensity of yoga. Med Sci Sports Exerc. 2016;48(8).

  25. Jetté M, Sidney K, Blümchen G. Metabolic equivalents (METS) in exercise testing, exercise prescription, and evaluation of functional capacity. Clin Cardiol. 1990;13(8):555–65.

    Article  PubMed  Google Scholar 

  26. Moradi S, Pasdar Y, Hamzeh B, Najafi F, Nachvak SM, Mostafai R, et al. Comparison of 3 nutritional questionnaires to Determine Energy Intake Accuracy in iranian adults. Clin Nutr Res. 2018;7(3):213–22.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Mirmiran P, Esfahani FH, Mehrabi Y, Hedayati M, Azizi F. Reliability and relative validity of an FFQ for nutrients in the Tehran lipid and glucose study. Public Health Nutr. 2010;13(5):654–62.

    Article  PubMed  Google Scholar 

  28. Shivappa N, Steck SE, Hurley TG, Hussey JR, Hébert JR. Designing and developing a literature-derived, population-based dietary inflammatory index. Public Health Nutr. 2014;17(8):1689–96.

    Article  PubMed  Google Scholar 

  29. Jahangirifar M, Taebi M, Nasr-Esfahani MH, Askari G. Dietary patterns and the outcomes of assisted reproductive techniques in women with primary infertility: a prospective cohort study. Int J Fertil Steril. 2019;12(4):316–23.

    PubMed  Google Scholar 

  30. Unisa S, Negi K, Pujari S, Chaurasia V. Do dietary patterns and morbidities have a relationship with primary infertility among women? A study from NFHS-4 (2015–16), India. J Biosoc Sci. 2021:1–16.

  31. Halton TL, Willett WC, Liu S, Manson JE, Stampfer MJ, Hu FB. Potato and french fry consumption and risk of type 2 diabetes in women. Am J Clin Nutr. 2006;83(2):284–90.

    Article  CAS  PubMed  Google Scholar 

  32. Harasym J, Oledzki R. Effect of fruit and vegetable antioxidants on total antioxidant capacity of blood plasma. Nutr. 2014;30(5):511–7.

    Article  CAS  Google Scholar 

  33. Rasheed HAM, Hamid P. Inflammation to infertility: panoramic view on endometriosis. Cureus. 2020;12(11):e11516.

    Google Scholar 

  34. Lin Y-H, Chen Y-H, Chang H-Y, Au H-K, Tzeng C-R, Huang Y-H. Chronic niche inflammation in endometriosis-associated infertility: current understanding and future therapeutic strategies. Int J Mol Sci. 2018;19(8):2385.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

RaNCD is part of PERSIAN national cohort and we would like to thank Professor Reza Malekzadeh Deputy of Research and Technology at the Ministry of Health and Medical Education of Iran and Director of the PERSIAN cohort and also Dr.Hossein Poustchi Executive Director of PERSIAN cohort for all their supports during design and running of RaNCD.

Funding

This study was supported by the Ministry of Health and Medical Education of Iran and Kermanshah University of Medical Sciences Grant no 4010332.

Author information

Authors and Affiliations

  1. Department of Nutritional Sciences, Faculty of Nutritional Sciences and Food Technologies, Kermanshah University of Medical Sciences, Isar Sq., across from Farabi Hospital, P.O. Box 6719851552, Kermanshah, Iran

    Jalal Moludi, Negin Kamari, Shima Moradi, Yahya Pasdar & Amir Saber

  2. Student Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran

    Negin Kamari & Shima Moradi

  3. Research Center for Environmental Determinants of Health (RCEDH), Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran

    Mitra Darbandi, Shayan Mostafaei, Yahya Pasdar & Farid Najafi

  4. Department of Biostatistics, Faculty of Health, Kermanshah University of Medical Sciences, Kermanshah, Iran

    Shayan Mostafaei

  5. Clinical Research Development Center, Imam Khomeini Hospital, Kermanshah University of Medical Sciences, Kermanshah, Iran

    Jafar Navabi

Authors
  1. Jalal Moludi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Negin Kamari
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mitra Darbandi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shayan Mostafaei
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Shima Moradi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yahya Pasdar
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Farid Najafi
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jafar Navabi
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Amir Saber
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

YP, FN, SM, JN, and MD contributed to the conception, design of the study, data acquisition, and statistical analyses. AS and JM developed the research plan and visualized the data, investigated the study, and edited the manuscript. NK, and SM performed validation and wrote the original draft. All authors have approved the final manuscript submission and have agreed to be fully accountable for their contributions. AS is the corresponding author and is primarily responsible for writing and editing the manuscript.

Corresponding author

Correspondence to Amir Saber.

Ethics declarations

Ethics approval and consent to participate

The Research and Technology Deputy and the Ethical Committee of Kermanshah University of Medical Sciences approved the study protocol (Ethical Number: IR.KUMS.REC.1401.218). Participants provided oral and written informed consent. Written informed consent was obtained from all subjects prior to enrollment in the study and all methods were carried out in accordance with relevant guidelines and regulations.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Moludi, J., Kamari, N., Darbandi, M. et al. Association between dietary inflammatory index and infertility of women; Results from RaNCD Cohort Study. Nutr J 22, 35 (2023). https://doi.org/10.1186/s12937-023-00865-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12937-023-00865-6

Keywords

Nutrition Journal

ISSN: 1475-2891

Contact us