The association between the Mediterranean Diet and the Prime Diet Quality Score and polycystic ovary syndrome: a case control study

Abstract

Introduction

Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder affecting women of reproductive age, characterized by hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology. This study aims to investigate the association between adherence to the Mediterranean Diet (Med-Diet) and the Prime Diet Quality Score (PDQS) and the risk of PCOS.

Method

This case-control study included 472 women aged 18–45, with 180 PCOS cases and 292 controls. PCOS diagnosis was based on the Rotterdam criteria. Dietary intake was assessed using a validated food frequency questionnaire, and adherence to the Med-Diet and PDQS was calculated. Statistical analyses included logistic regression to examine associations between diet quality and PCOS.

Results

Higher adherence to both the Med-Diet and PDQS was significantly associated with lower odds of PCOS. Participants in the highest quartile of the Med-Diet score had a 41% reduced risk of PCOS in the crude model (OR = 0.59, 95% CI: 0.48–0.67) and a 32% reduced risk in the fully adjusted model (OR = 0.68, 95% CI: 0.57–0.79), after adjusting for potential confounders, including age, body mass index (BMI), physical activity, and total energy intake. Similarly, those in the highest PDQS quartile showed a 53% reduced risk in the crude model (OR = 0.47, 95% CI: 0.35–0.56) and a 43% reduced risk in the fully adjusted model (OR = 0.57, 95% CI: 0.44–0.68), accounting for the same confounders.

Conclusion

The findings suggest that higher adherence to the Med-Diet and PDQS is associated with a reduced risk of developing PCOS. Further research is warranted to explore the underlying biological mechanisms and to establish causality through prospective cohort studies and randomized controlled trials.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40795-025-01067-5.

Introduction

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders, affecting approximately 6–20% of women of reproductive age worldwide, depending on the diagnostic criteria used [1]. PCOS is diagnosed based on the Rotterdam criteria [2], which require the presence of at least two of the following three features: hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology, after excluding other causes of hyperandrogenism [3, 4]. Women with PCOS often experience menstrual irregularities, infertility, insulin resistance (IR), and an increased risk of developing type 2 diabetes(T2DM), cardiovascular disease, and metabolic syndrome [5]. The etiology of PCOS is multifactorial and involves a complex interplay of genetic, environmental, and lifestyle factors [6].

Diet and nutrition have been increasingly recognized as crucial modifiable factors in the management and prevention of PCOS. Studies have shown that dietary patterns rich in whole foods, such as the Mediterranean diet, can improve insulin sensitivity, reduce androgen levels, and regulate menstrual cycles in women with PCOS [7]. Furthermore, reducing refined carbohydrates and increasing fiber intake has been associated with improved metabolic and reproductive outcomes in PCOS patients [8]. Evidence suggests that dietary patterns and nutrient intake can influence the metabolic and hormonal imbalances characteristic of PCOS, potentially impacting disease progression and symptom severity [9]. In particular, dietary patterns that emphasize high intake of refined carbohydrates, saturated fats, and processed foods have been associated with worsening insulin resistance, inflammation, and androgen levels, thereby exacerbating PCOS symptoms [10]. Conversely, diets rich in whole foods, fiber, antioxidants, and healthy fats have shown promise in improving insulin sensitivity, reducing inflammation, and promoting hormonal balance in women with PCOS [11, 12].

The Med-Diet, characterized by a high intake of fruits, vegetables, whole grains, legumes, nuts, olive oil, and moderate consumption of fish and poultry, has been extensively studied for its health benefits, including its role in reducing the risk of cardiovascular diseases, T2DM, and metabolic syndrome [13]. The Med-Diet score, while valuable, faces challenges in implementation. Cultural variations in dietary practices can hinder adherence among non-Mediterranean populations. Additionally, economic factors may limit access to certain Med-Diet components in middle- or low-income countries [14, 15].

To address the limitations of the Med-Diet score, alternative food-based healthy diets and diet quality indexes (DQIs) have been developed, such as the Prime Diet Quality Score (PDQS). These DQIs offer a more practical approach for clinical use, as they do not require specialized software or nutrient analysis [16, 17]. Similar to other DQIs, PDQS was used to assess overall diet quality. Previous studies have validated PDQS against other established dietary indices, such as the Healthy Eating Index (HEI) and the Alternative Healthy Eating Index (AHEI), showing significant correlations with nutrient-based dietary quality assessments derived from software-based nutritional analysis. These validations demonstrate PDQS as a reliable tool for estimating diet quality while reducing the complexity associated with nutrient-level calculations [18–21].

While research has examined the link between PDQS and certain chronic diseases, its association with PCOS remains unexplored. This study aimed to investigate the relationship between both the Med-Diet and PDQS and the odds of PCOS, and to compare the strength of these associations.

Method

Design of the study

This case-control study included women with and without PCOS of reproductive age (18–45 years). Participants in the case group were selected from patients with PCOS who referred to the Reproductive Health Center at Zabol University of Medical Science between March and June 2024 if they met the inclusion criteria. Only patients who have been diagnosed as a new case (incident case) were selected. These individuals presented with menstrual irregularities, infertility, or skin and hair issues, often with prior endocrine evaluation.

PCOS diagnosis was confirmed by an expert gynecologist based on the fulfillment of at least two out of three Rotterdam criteria: clinical or biochemical hyperandrogenism, menstrual irregularities, and polycystic ovarian morphology, after excluding other potential causes of hyperandrogenism [22]. The control group consisted of healthy women with regular menstrual cycles who attended the same hospital as companions to the patients [23].

Participants were recruited from Reproductive Health Center at Zabol University of Medical Science and categorized into two groups: cases (PCOS) and controls (healthy women).

1. PCOS Cases: Women aged 18–45 years diagnosed with Polycystic Ovary Syndrome (PCOS) based on at least two out of three Rotterdam criteria, including:

• Clinical or biochemical hyperandrogenism,

• Ovulatory dysfunction, and.

• Polycystic ovarian morphology on ultrasound.

• Additionally, participants had no history of metabolic or endocrine disorders other than PCOS.

2. Control Group: Healthy women aged 18–45 years who:

• Had regular menstrual cycles (21–35 days),

• Had no clinical or biochemical signs of hyperandrogenism,

• Did not have PCOS (confirmed by clinical assessment), and.

• Had no history of metabolic or endocrine disorders.

• Controls were selected from companions of patients attending the same hospital.

Exclusion criteria included pregnancy or lactation, not answering more than 40 items in the food frequency questionnaire (FFQ) and participants that reported total energy consumption outside established thresholds (less than 700 kcal or more than 4000 kcal) [24].

Prior to enrollment, all participants provided written informed consent. The study protocol received ethical approval from the Zabol University of Medical Sciences ethics committee (Ethics No: IR.ZBMU.REC.1401.103) and adhered to the tenets of the Declaration of Helsinki.

Demographic and anthropometric evaluation

Demographic information of the participants was completed through a pre-prepared form. Body weight and height were measured using a calibrated scale and stadiometer, with participants wearing light clothing and no shoes. BMI was calculated as weight (kg) divided by height (m²). Based on the World Health Organization (WHO) classification, BMI was categorized as follows:

Underweight: BMI < 18.5 kg/m².

Normal weight: BMI 18.5–24.9 kg/m².

Overweight: BMI 25.0–29.9 kg/m².

Obese: BMI ≥ 30.0 kg/m².

Waist circumference (WC) was measured at the midpoint between the lowest rib and the iliac crest using a non-stretchable tape measure, following standard protocols.

Dietary assessment

Dietary intake over the preceding twelve months was assessed using a validated, semi-quantitative FFQ comprising 147 food items, which has been previously validated for the Iranian population [25]. The FFQ featured a list of typical Iranian food items with standardized portion sizes. Participants reported their average consumption frequency and portion size for each item. Consumption frequency ranged from never to daily intake. Standard Iranian household measurements were used to convert reported portion sizes to grams. The daily nutrient consumption data was gathered using the United States Department of Agriculture’s (USDA) national nutrient databank. This databank is a comprehensive resource that provides detailed information about the nutritional content of various foods. Dietary energy and nutrient intake for each participant was computed using the Nutritionist IV software application.

Med-Diet score was assessed using a modified approach based on the methodology of Trichopoulou et al. [26]. Participants were assigned one point for each of the following dietary components: consuming daily quantities of vegetables, whole grains, fish, legumes, and nuts that were at least equivalent to the sex-specific median intake; maintaining a ratio of monounsaturated fatty acids (MUFA) to saturated fatty acids (SFA) that was equal to or exceeded the median; and consuming daily quantities of meats (poultry, red meat, and processed meats) and dairy products that were below the median intake. The final Med-Diet score, derived from the summation of these individual component scores, ranged from 0 to 9 points. A higher score indicated greater adherence to the Mediterranean dietary pattern.

The PDQS is a validated dietary quality index (DQI) based on food consumption patterns [16]. It comprises 14 healthy food groups (e.g., dark green leafy vegetables, cruciferous vegetables, carrots, other vegetables, citrus fruits, other fruits, legumes, nuts, poultry, fish, eggs, whole grains, low-fat dairy, and liquid vegetable oils) and seven unhealthy food groups (e.g., red meat, processed meats, potatoes, refined grains and baked goods, sugar-sweetened beverages, fried foods away from home, and sweets and ice cream) [16]. The PDQS score was determined by evaluating the frequency of intake for each food item within these groups.

A point system was employed, with higher points assigned for greater consumption of healthy foods and lower points for greater consumption of unhealthy foods. For instance, in the healthy group, 0, 1, and 2 points were allocated for consuming 0–1, 2–3, and ≥ 4 servings per week, respectively. Conversely, in the unhealthy group, 2, 1, and 0 points were allocated for the same intake levels. The final PDQS score, calculated by summing the individual component scores, ranged from 0 to 42 points, with a higher score indicative of a healthier diet.

Statistical analysis

The Med-Diet score and PDQS were analyzed in quartile form. Continuous variables were expressed as the mean ± standard deviation (SD), while categorical variables were presented as frequency with percentages. To compare the mean quantitative variables between the quartiles of PDQS and the Med-Diet score in both the PCOS and control groups, a one-way analysis of variance (ANOVA) was employed. For the categorical variables among different groups, a chi-square test was used. To investigate the association between PCOS and PDQS, as well as the relationship between PCOS and Med-diet quartiles, a univariate logistic regression analysis was performed. This statistical method utilized a logit link function to model the probability of PCOS occurrence. The results of the unadjusted and adjusted models are presented as odds ratios (OR) with 95% confidence intervals (CI). The lowest quartile of PDQS and Med-diet intake served as the reference group. The unadjusted model estimated the association without considering any confounding factors. The first model adjusted for age and energy intake. Further adjustments in the second model were made for education, socioeconomic status and smoking. Additional adjustments in the final model were made for body mass index (Kg/ m²) and physical activity. Statistical analysis was conducted using a 5% error via SPSS for Windows version 23 (SPSS Inc, Chicago, IL, USA). Potential confounders were selected based on biological plausibility, previous literature, and statistical considerations. We identified confounders that have been previously associated with both dietary intake and PCOS risk, including:

• Demographic factors: Age, socioeconomic status.

• Anthropometric variables: Body mass index (BMI), waist circumference.

• Lifestyle factors: Physical activity, smoking status.

• Dietary intake variables: Total energy intake.

We did not initially use a Directed Acyclic Graph (DAG) to select confounders. However, as suggested by the reviewer, we constructed a DAG to visualize potential causal relationships and identify the minimal sufficient adjustment set for unbiased effect estimation. The constructed DAG is now included as Supplementary Fig. 1.

Results

Study participants and baseline characteristics

As shown in the flow chart 1 (Fig. 1), a total of 472 participants (180 cases and 292 controls) were included in the final analysis. The baseline characteristics of participants were summarized in Table 1. The mean age of patients in the case group was 28.46 ± 8.16 years old and in the control, group was 29.35 ± 9.18, which was not statistically significant (P = 0.82). Participants in the case group had a significantly higher mean weight (72.23 ± 13.17 kg vs. 67.46 ± 10.34 kg, P < 0.001) and waist circumference (89.45 ± 12.83 cm vs. 81.47 ± 10.53 cm, P = 0.003), along with differences in sociodemographic factors and physical activity compared to the control group. The mean score of the PDQS in the case group was 21.65 ± 0.76 and in the control group was 23.93 ± 1.47, and there was a significant difference between the two groups (P = 0.01). Also, we found a significant differences between two groups in term of Med-Diet score (P = 0.003).

Fig. 1.

Flowchart of the study design

Table 1.

The baseline characteristics of the people participating in the case and control groups

Variables	PCOS (n = 180)	Control (n = 292)	P_value*
Age (years)	28.46 ± 8.16	29.35 ± 9.18	0.82
Weight(kg)	72.23 ± 13.17	67.46 ± 10.34	< 0.001
BMI (kg/m2)	27.36 ± 5.39	25.55 ± 4.93	< 0.001
Waist circumference (cm)	89.45 ± 12.83	81.47 ± 10.53	0.003
Marital status			< 0.001
Single	91(51%)	136(46%)
Married	76 (42%)	146(48%)
Separated	13(7%)	18(6%)
Pregnancy history			< 0.001
Yes	51(28%)	98(33%)
No	129(72%)	202(67%)
Education status, n (%)			< 0.001
Less than a diploma	41(23%)	74(25%)
Diploma	63(35%)	97(32%)
Bachelor	55(31%)	92(31%)
Higher than a bachelor	21(11%)	37(12%)
Current Smoker			< 0.001
Yes	28(16%)	37(12%)
No	152(84%)	263(88%)
SES¶	13.76 ± 1.19	14.25 ± 1.37	0.12
Physical activity (MET. min/d)	107.43 ± 31.56	153.45 ± 37.65	< 0.001
Energy intake (kcal/day)	2465.23 ± 326.33	2389.44 ± 289.54	0.38
PDQS	21.65 ± 0.76	23.93 ± 1.47	0.01
Med-Diet score	3.37 ± 1.34	4.79 ± 1.82	0.003

BMI, body mass index; MET, metabolic equivalent; PCOS, polycystic ovary syndrome; SES, socioeconomic status; PDQS: Prime diet quality score; Med-Diet: Mediterranean diet; WHR, waist-to-hip ratio. For quantitative variables mean ± SD; and for qualitative variables frequency (%) were used. * Independent t test for quantitative variables and x² test for categorical variables conducted. ^¶ SES score was assessed based on education level, job, home status, and income level

Characteristics of the study subjects according to PDQS and Med-Diet score quartiles

The sociodemographic characteristics, anthropometry variables, and dietary intake of the study participants in the PDQS and Med-Diet score quartiles are demonstrated in Table 2. Among those who showed better dietary quality intake (higher PDQS and Med-Diet quartile, Q4), there were more inactive and tended to have lower waist circumference. Also, participants in the higher quartile of PDQS and Med-Diet score consumed significantly higher amounts of energy, protein, carbohydrate, total fat, low-fat dairy products, fiber, fruits, vegetables, legumes, whole grains, fishes and shrimps and nuts and lower amounts of high fat dairy products, refined grains, red and processed meats and fast foods (P < 0.001).

Table 2.

Sociodemographic characteristics, anthropometry variables, and dietary intake across quartiles of PDQS and Med-Diet¹

Characteristics	PDQS					Med-Diet
	Q1	Q2	Q3	Q4	P	Q1	Q2	Q3	Q4	P 2
Age (year)	30.27 ± 9.23	28.44 ± 8.73	29.12 ± 8.91	28.73 ± 8.67	0.13	30.15 ± 9.15	28.63 ± 8.77	28.90 ± 9.97	29.24 ± 9.07	0.15
Weight(kg)	71.64 ± 12.50	69.73 ± 11.95	70.31 ± 12.34	68.34 ± 11.20	0.29	71.43 ± 12.34	69.30 ± 11.45	70.19 ± 11.45	68.85 ± 11.31	0.27
BMI (kg/m2)	26.87 ± 5.64	25.93 ± 4.85	26.17 ± 5.71	25.65 ± 4.36	0.17	26.70 ± 5.64	25.69 ± 5.01	26.32 ± 5.49	25.54 ± 4.89	0.19
Waist circumference (cm)	88.43 ± 12.52	82.36 ± 10.89	84.55 ± 11.32	82.17 ± 10.74	< 0.001	88.65 ± 12.64	83.14 ± 11.12	85.19 ± 11.56	82.23 ± 10.79	< 0.001
Energy (Kcal/ day)	2476.52 ± 345.62	2267.42 ± 290.98	2369.33 ± 321.68	2513.29 ± 370.42	< 0.001	2429.93 ± 374.42	2373.66 ± 312.76	2385.26 ± 346.7	2489.35 ± 368.79	< 0.001
Carbohydrate (g/d)	352.23 ± 106.70	307.84 ± 91.63	319.45 ± 96.43	360.62 ± 110.53	0.002	347.46 ± 97.49	315.56 ± 88.12	320.72 ± 91.74	358.19 ± 105.77	0.005
Protein (g/d)	94.32 ± 30.81	81.55 ± 24.68	83.19 ± 25.42	97.76 ± 35.44	0.004	95.18 ± 32.84	82.47 ± 26.39	84.18 ± 25.30	96.41 ± 31.63	0.003
Total Fat(g/d)	86.17 ± 34.75	75.49 ± 27.38	79.18 ± 28.34	93.37 ± 39.73	0.001	84.22 ± 30.60	73.69 ± 23.44	77.12 ± 30.45	97.19 ± 41.57	< 0.001
High-fat dairy products (g/ day)	123.46 ± 5.19	102.83 ± 4.17	83.25 ± 3.88	65.95 ± 3.15	< 0.001	117.32 ± 5.10	97.39 ± 4.48	77.26 ± 3.89	58.43 ± 3.38	< 0.001
Low-fat dairy products (g/ day)	225.34 ± 7.26	248.33 ± 6.98	267.55 ± 6.43	293.15 ± 7.40	< 0.001	219.46 ± 5.88	237.73 ± 6.19	262.31 ± 6.43	287.17 ± 7.32	< 0.001
Fiber (g/ day)	19.34 ± 0.22	22.65 ± 0.28	23.31 ± 0.19	27.33 ± 0.21	< 0.001	18.51 ± 0.23	20.69 ± 0.21	22.14 ± 0.22	25.23 ± 0.24	< 0.001
Vegetables (g/ day)	234.73 ± 5.12	258.43 ± 4.32	284.36 ± 5.60	327.65 ± 6.32	< 0.001	239.15 ± 4.89	261.44 ± 5.19	294.71 ± 5.46	342.57 ± 6.39	< 0.001
Fruits (g/ day)	172.43 ± 7.19	205.49 ± 6.14	239.72 ± 5.42	273.92 ± 7.40	< 0.001	163.29 ± 5.43	192.33 ± 6.23	241.83 ± 5.45	268.37 ± 6.42	< 0.001
Legumes (g/ day)	38.45 ± 1.34	53.45 ± 1.63	62.72 ± 1.81	74.29 ± 1.69	< 0.001	42.75 ± 1.13	56.31 ± 1.39	65.17 ± 1.71	79.63 ± 1.88	< 0.001
Whole grains (g/ day)	97.43 ± 6.43	112.35 ± 4.38	125.88 ± 3.65	141.42 ± 4.26	< 0.001	95.32 ± 5.85	107.43 ± 4.72	119.45 ± 5.21	138.41 ± 4.76	< 0.001
Refined grains (g/ day)	263.46 ± 5.26	244.73 ± 4.35	227.73 ± 5.19	205.17 ± 4.77	< 0.001	258.39 ± 4.64	239.55 ± 5.28	221.37 ± 5.19	207.34 ± 4.94	< 0.001
Red and processed meats (g/ day)	38.27 ± 1.32	35.44 ± 1.09	29.73 ± 1.13	23.34 ± 1.29	< 0.001	40.28 ± 1.27	37.43 ± 1.49	30.78 ± 1.58	20.69 ± 1.20	< 0.001
Fishes and shrimps (g/ day)	9.32 ± 1.07	13.19 ± 1.65	15.40 ± 1.49	19.33 ± 1.76	< 0.001	10.33 ± 1.28	12.54 ± 1.38	15.89 ± 1.47	21.89 ± 1.76	< 0.001
Fast food (g/ day)	28.43 ± 2.13	20.37 ± 1.89	14.18 ± 2.34	7.93 ± 1.45	< 0.001	30.67 ± 1.75	24.61 ± 1.47	15.35 ± 1.65	9.47 ± 1.11	< 0.001
Total nuts and seeds (g/ day)	6.74 ± 1.15	7.38 ± 1.32	10.27 ± 0.93	12.34 ± 1.15	< 0.001	6.39 ± 0.86	7.59 ± 1.07	9.64 ± 1.38	11.89 ± 1.45	< 0.001

¹Values are means ± SD adjusted for age and energy except for Energy variable which was justified for age

²Derived from ANCOVA

PDQS: Prime diet quality score; Med-Diet: Mediterranean diet; P: P-value

Cross-sectional association between PDQS and Med-Diet score with odds of PCOS

We fitted a multiple univariate logistic regression to evaluate the association between PDQS and Med-Diet score with PCOS and the result showed in Table 3. Results of crude model showed that participants in the higher quartile of PDQS had 53% lower odds of PCOS than subjects in the first quartile (OR = 0.47, 95%CI:0.35 to 0.56; P for trend = 0.013). In the fully adjusted model, after controlling for age, BMI, energy intake, and other potential confounders, higher adherence to the PDQS was associated with 43% lower odds of PCOS (OR = 0.57, 95% CI = 0.44–0.68).

Table 3.

Odds ratio (OR) and 95% confidence interval (CI) for PCOS based on quartiles of PDQS and Med-Diet

Model	PDQS					Med-Diet
	Q1	Q2	Q3	Q4	P for trend1	Q1	Q2	Q3	Q4	P for trend1
Crude model	1 (Ref.)	0.64 (0.54–0.78)	0.53 (0.43–0.61)	0.47 (0.35–0.56)	0.013	1 (Ref.)	0.71(0.61–0.83)	0.67 (0.53–0.75)	0.59 (0.48–0.67)	0.01
Model 1	1 (Ref.)	0.67 (0.57–0.81)	0.58(0.47–0.67)	0.50(0.39–0.59)	0.018	1 (Ref.)	0.74 (0.62–0.87)	0.69(0.49–0.78)	0.61 (0.52–0.69)	0.015
Model 2	1 (Ref.)	0.69 (0.59–0.83)	0.61 (0.48–0.72)	0.55 (0.41–0.63)	0.023	1 (Ref.)	0.82 (0.65–0.93)	0.73 (0.53–0.84)	0.64 (0.54–0.73)	0.024
Model 3	1 (Ref.)	0.73 (0.62–0.93)	0.65 (0.51–0.75)	0.57 (0.44–0.68)	0.029	1 (Ref.)	0.85 (0.67–0.98)	0.75 (0.55–0.87)	0.68 (0.57–0.79)	0.027

¹Derived from Mantel-Haenszel test

Model 1: Adjusted for age and energy (Kcal/ day)

Model 2: Model 1 + education, socioeconomic status and smoking

Model 3: Model 2 + body mass index (Kg/ m²) and physical activity

PDQS: Prime diet quality score; Med-Diet: Mediterranean diet; P: P-value

In term of Med-Diet score, we found that subjects in the higher quartile of Med-Diet score experienced 41% lower odds of PCOS in the crude model (OR = 0.59, 95%CI: 0.48 to 0.67; P for trend = 0.01) and 32% lower odds of PCOS in the full adjusted model (OR = 0.68, 95% CI = 0.57 to 0.79; P for trend = 0.027).

Discussion

The present case-control study aimed to investigate the association between adherence to the Med-Diet and PDQS with the odds of PCOS among women of reproductive age. Our findings suggest that higher adherence to both the Med-Diet and PDQS is significantly associated with lower odds of developing PCOS.

PCOS is a prevalent endocrine metabolic disease affecting reproductive-age women. A hallmark characteristic of PCOS is insulin resistance (IR), which triggers the body to produce excessive insulin to compensate [27]. This excessive insulin can lead to hyperinsulinemia (HI), a condition that further exacerbates hyperandrogenism, anovulation, and the formation of polycystic ovaries [28]. PCOS as a chronic disease associated with insulin resistance as well as increased levels of inflammation and oxidative stress is correlated with various lifestyle and nutritional factors [29, 30]. Inflammation is one of the main reasons related to IR and PCOS [30]. Some studies showed the beneficial effects of the MED on inflammatory factors and IR. In the study of Mei et al., they evaluated the effects of 12 weeks intervention with a MED plus low carbohydrate diet and they found a significant improvement in the reproductive endocrine levels, the degree of IR and lipid metabolism-related indicators [31].

While Iran is geographically outside the Mediterranean region, its traditional dietary patterns share several similarities with the Med-Diet. The Iranian diet is rich in whole grains, legumes, vegetables, fruits, and nuts, which align closely with the core principles of Med-Diet. Additionally, olive oil, dairy products, and moderate fish consumption—key components of Med-Diet —are also present in certain Iranian dishes, particularly in regions with historical Mediterranean influence [32].

However, differences exist, particularly in higher consumption of red meat and refined grains in modern Iranian dietary habits. The shift toward Westernized dietary patterns in urban areas has led to increased consumption of processed foods, sugar-sweetened beverages, and saturated fats, which contrasts with the healthier fat profile and plant-based emphasis of Med-Diet [33].

Several studies have investigated adherence to Med-Diet in Iran, showing moderate to high adherence in certain populations [34, 35]. Given the well-documented health benefits of Med-Diet, promoting its adoption in non-Mediterranean countries like Iran could be a strategic approach to improving public health outcomes. Encouraging a shift toward Med-Diet -like dietary patterns—by emphasizing whole foods, healthy fats, and plant-based nutrition—could help reduce the rising burden of obesity, metabolic syndrome, and chronic diseases in the Iranian population [36].

Given the primary concern of weight and body fat loss for overweight individuals with PCOS, the Med-Diet offers a promising approach to address these challenges [37]. In the present study, we found that patients with PCOS group compared than control group had a significant higher BMI. One potential mechanism through which the Med-Diet can reduce PCOS risk is by improving insulin sensitivity [38, 39]. Obesity is often associated with insulin resistance, a condition in which the body’s cells become less responsive to insulin. Insulin resistance can contribute to hyperandrogenism, a key feature of PCOS [40, 41].

The Med-Diet, through its high intake of fiber, antioxidants, and healthy fats, has been shown to improve insulin sensitivity [42]. By enhancing insulin sensitivity, the Med-Diet may help to reduce androgen levels and regulate menstrual cycles, thereby decreasing the risk of PCOS [43]. Another potential mechanism is the Med-Diet’s impact on inflammation. Obesity is linked to chronic low-grade inflammation, which can contribute to PCOS [44]. The Med-Diet is rich in anti-inflammatory compounds, such as polyphenols and omega-3 fatty acids. By reducing inflammation, the Med-Diet may help to improve metabolic health and reduce the risk of PCOS [45]. Additionally, the Med-Diet’s emphasis on healthy fats, particularly monounsaturated fatty acids (MUFA), may play a role in reducing PCOS risk. The elevated levels of olive oil, a primary component of the Med-Diet, contribute to its beneficial effects on PCOS [46]. Olive oil is a rich source of MUFA and polyphenols, known for their anti-inflammatory and antioxidant properties. These compounds have been shown to lower lipid levels and improve endothelial function, collectively reducing the risk of cardiovascular disease [47]. These fatty acids have been shown to improve lipid profiles and reduce the risk of metabolic syndrome, a cluster of conditions that often co-occurs with PCOS. By improving metabolic health, the Med-Diet may help to reduce the risk of PCOS [48].

Patients with PCOS frequently experience disruptions in the hypothalamic-pituitary-ovarian (HPO) axis [49]. These disturbances involve abnormal secretion of gonadotropin-releasing hormone (GnRH), heightened pituitary sensitivity, and increased production of luteinizing hormone (LH) [50, 51]. The excessive levels of LH bind to receptors on granulosa cells, stimulating excessive androgen production within the follicular membrane. In PCOS, the absence of progesterone’s antagonistic effect on estrogen leads to excessive endometrial proliferation, resulting in irregular or absent menstruation [50]. Several studies have demonstrated the Med-Diet effectiveness in reducing LH levels, consequently lowering androgen production and restoring regular menstrual cycles in PCOS patients [52]. Plant-based foods, including peanuts, soybeans, and various soybean derivatives, commonly found in Med-diet, can stimulate the production of sex hormone binding globulin (SHBG) in the liver. SHBG binds to circulating free androgens, reducing their bioavailability and effectively lowering androgen levels in the body. This mechanism contributes to the androgen-reducing effects associated with the Med-diet [50].

Our study’s findings demonstrated a significant inverse relationship between adherence to the PDQS and the risk of PCOS, indicating that women with higher PDQS had a lower likelihood of developing PCOS. Very few studies have evaluated the relationship of PDQS with the risk of chronic diseases. Cano-Ibáñez et al. in a cross-sectional study found an inverse correlation between PDQS with depressive symptoms [19, 53].

The PDQS, which evaluates dietary quality based on the frequency of consumption of healthy and unhealthy food groups, offers a comprehensive assessment of an individual’s overall dietary pattern. Several potential mechanisms can explain how higher PDQS adherence could contribute to reducing the risk of PCOS [54]. The PDQS places a significant emphasis on the intake of healthy food groups, such as vegetables, fruits, whole grains, legumes, nuts, poultry, fish, eggs, low-fat dairy, and vegetable oils. These foods are rich in essential nutrients, including vitamins, minerals, fiber, and phytochemicals, which play a crucial role in maintaining metabolic health and reducing inflammation [55]. Also, the PDQS discourages the consumption of unhealthy food groups, such as red and processed meats, refined grains, sugar-sweetened beverages, fried foods, and sweets. These foods are known to contribute to chronic inflammation, insulin resistance, and metabolic dysregulation, which are risk factors for PCOS [56].

It has been reported that adherence to a high PDQS diet, rich in fiber and healthy fats, promotes better insulin sensitivity. The slow digestion of fiber-rich foods helps stabilize blood sugar levels, reducing the risk of insulin spikes and subsequent insulin resistance. Additionally, foods high in omega-3 fatty acids, such as fish and nuts, enhance insulin signaling pathways, further reducing the risk of insulin resistance—a core issue in PCOS development. Moreover, high PDQS adherence ensures a balanced intake of nutrients that are critical for hormonal health. For instance, micronutrients like magnesium, zinc, and vitamin D, which are abundant in a high-quality diet, play roles in the synthesis and regulation of hormones. Ensuring adequate intake of these nutrients through a high PDQS diet may help normalize hormonal imbalances that contribute to PCOS [16].

While this study provides strong evidence for an association between diet quality and PCOS risk, future prospective studies are needed to establish a causal relationship and explore the underlying biological mechanisms. It’s possible that the relationship could be bidirectional, meaning that changes in dietary habits might influence PCOS symptoms, but conversely, PCOS itself could lead to altered dietary patterns. In an attempt to avoid this possible bias in the relationship between PDQS and Med-diet with PCOS, we included newly diagnosed patients, because patients who have been aware of their disease for a long time may have changed their diet.

This study has several strengths. First, the use of validated dietary assessment tools, including the Med-Diet score and the PDQS, ensures the reliability and validity of the dietary intake data. These tools have been extensively used in nutritional epidemiology and are effective in capturing overall dietary patterns that are linked to health outcomes. Second, our study controlled for various potential confounders, such as age, energy intake, body mass index, and physical activity, thereby strengthening the robustness of the observed associations. Finally, including only newly diagnosed PCOS patients helps reduce potential biases arising from long-term dietary changes post-diagnosis, which could affect the association between diet and PCOS risk. Despite these strengths, the study has several limitations.

First, this study is subject to recall bias and limitations inherent in a cross-sectional design. Additionally, as our sample was drawn from a single geographic location, future research should aim to include diverse populations to determine whether these findings are consistent across different ethnic and cultural groups. Second, while we have controlled for numerous confounders, residual confounding by other unmeasured factors (e.g., genetic predispositions or environmental influences) cannot be entirely ruled out. Third, the cross-sectional nature of the dietary assessment limits the ability to infer causality from the observed associations. It remains unclear whether adherence to the Med-Diet and PDQS influences the risk of developing PCOS or if the presence of PCOS leads to dietary changes. Fourth, the study’s generalizability may be limited as participants were recruited from a single geographic location and may not represent the broader population of women with PCOS. Additionally, the exclusion of women with pre-existing chronic conditions or those on specific restrictive diets may limit the applicability of findings to a more diverse cohort. Lastly, the use of self-reported measures for some variables, including physical activity and smoking, may introduce measurement errors and misclassification biases.

Conclusion

In summary, our study highlights a significant association between adherence to the Mediterranean Diet and Prime Diet Quality Score with COVID-19 severity. Higher adherence to these dietary patterns was linked to a lower risk of severe disease, reinforcing the potential role of diet quality in COVID-19 outcomes. These findings underscore the importance of dietary strategies in public health efforts to mitigate disease severity. Future studies with longitudinal designs are needed to establish causal relationships and further explore underlying mechanisms.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Author contributions

MR conceived the study, MR, ZA, GB and RA collected and analyzed the data. MR, and FB interpreted the statistical analyses and MR wrote the first draft of the manuscript. PM contributed to the manuscript revising and editing. All of the authors critically revised the manuscript. The author(s) read and approved the final manuscript.

Funding

No funding.

Data availability

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available because of privacy or ethical restrictions.

Declarations

Competing interests

The authors declare no competing interests.

Clinical trial number

not applicable.

Disclosure of potential conflicts of interest

The authors have no competing interests to declare that are relevant to the content of this article.

Ethics statement

This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. Ethical approval was obtained from Zabol University of Medical Sciences, with approval number: IR.ZBMU.REC.1401.103]. All participants provided written informed consent prior to their inclusion in the study. Before participating in the study, each patient was required to give written informed consent, demonstrating their voluntary willingness to engage after receiving comprehensive information regarding the study’s objectives, methodologies, potential risks, and advantages.

Consent to publish

Not applicable.

Transparency declaration

The lead author asserts that this manuscript provides a truthful, precise, and transparent representation of the reported studies. Furthermore, the lead author confirms that no significant elements of the studies have been excluded and that any deviations from the originally intended studies have been adequately clarified.

Clinical trial number

Not applicable.