The present study was a case-control designed study on 120 newly-diagnosed cases of PCOS and 120 healthy controls aged between 18–45 years in Khorramabad of Iran in 2019–2020. Participants were selected using consecutive random sampling method. All participants signed a written informed consent before data gathering. Rotterdam criteria was used for diagnosis of PCOS. The inclusion criteria in the current study were as age ranges of 18–45 years, no history of chronic diseases including diabetes, liver, thyroid, cardiovascular and kidney diseases, not following a special diet, no use of appetite suppressants or anti-obesity drugs, having PCOS with no more than 6 months after its diagnosis and no use of insulin and metformin. People with eating disorders, use from diet or exercise for weight loss, smoking, alcohol and use of any multivitamin and mineral supplements were excluded from the study. In order to increase the comparability between the study groups, we matched the case and control groups in terms of age (18–30, 31–35 and 36–45 year) and marital status and the effects of other confounding variables including BMI, education, physical activity, marital status and family history of PCOS were adjusted by including them into the different statistical models. This study was approved by the ethics committee of Lorestan University of Medical Sciences with the ethics code of: IR.LUMS.REC.1398.058.
A validated 168-item Food Frequency Questionnaire (FFQ) was used to assess dietary intakes of the study participants. FFQ presents a list of food items and a standard serving size for each one. Participants should report the frequency of their food consumption during the previous year (frequency of food items on daily, weekly, or monthly intake . Also, in order to calculate the dietary inflammatory index, it was necessary to have information about the intake of some foods such as spices including saffron, ginger, turmeric, black pepper, rosemary and thyme, which are not available in FFQ. As a result, some additional questions regarding the intake of these foods were asked of the interviewees. The questionnaire was completed by face-to-face interview. During the interview, the average size of each food item in the food frequency questionnaire was explained to the case and control groups. After completing the food frequency questionnaire for all individuals in the case and control groups, Software program Nutritionist IV was used for nutrient analysis which was modified for Iranian foods and the daily intake of each person in terms of total energy, protein, carbohydrates, fiber, total fat, fatty acids PUFA, MUFA, SFA and food groups were determined.
The DII was calculated based on the intakes of 45 food parameters obtained from the FFQ whose inflammatory score, mean and SD of the global intake of each nutritional parameter were calculated . To calculate the DII score, energy-adjusted values of these items were calculated, firstly. Then, the values obtained for each variable were subtracted from the corresponding mean global intake and divided by the global SD to obtain the z score. The z-score obtained was then converted to a centered percentile score in order to reduce skewness and this percentage score for each food parameter was multiplied by 2 and subtracting 1, So that its range is between − 1 to + 1. In the next step, the numbers obtained for each of the food parameters were multiplied by the corresponding inflammatory score and then the inflammation score of all of the food parameters were summed to obtain the total inflammatory score for each person. A higher DII score (more positive) indicates a pro-inflammatory diet and a lower score (more negative) indicates an anti-inflammatory diet. The minimum of the DII score is -8.87, while the maximum score is + 7.98 .
In this study, from a total of 45 nutrients, 36 dietary parameters were used to calculate the DII including energy, carbohydrates, protein, total fat, monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), saturated fatty acids (SFA), cholesterol, omega 3, omega 6, fiber, thiamine, riboflavin, niacin, vitamin B6, folic acid, vitamin B12, vitamin A, vitamin C, vitamin E, vitamin D, beta-carotene, iron, Selenium, zinc, magnesium, caffeine, tea, onion, garlic, turmeric, saffron, pepper, ginger, thyme and rosemary.
Anthropometric parameters of participating women, including weight, height, waist circumference, hip circumference and BMI were measured. Measurements were performed according to standard protocol. Height, without wearing shoes in a standing position, using a measuring tape was measured and recorded with an accuracy of 0.1 cm. Weight was measured while the subjects were light clothed and without wearing shoes, using a Seka scale (made in Germany) with an accuracy of 100 g. Waist circumference (WC) was measured using a flexible anthropometric tape in the midway between the lowest ribs margin and the iliac crest at the level of the umbilicus with the least possible coverage, with an accuracy of 0.1 cm and the hip circumference was measured using a flexible anthropometric tape in the widest part of the pelvis with the least possible coverage. Also, body mass index (BMI) was calculated by dividing weight by height squared (kg / m2).
A general questionnaire was used to collect additional variables such as socio-economic status information including age, education, occupation, monthly income, marital status, and drug use (any types of drugs) and intake of nutritional supplements (minerals, vitamins). The data related to physical activity data were collected using the International Physical Activity Questionnaire (IPAQ) [28–31].
The Kolmogorov–Smirnoff test was used to evaluate whether or not the distributions of the variables were normal. Mean values for cases and controls were compared using the Student’s T-test and the means of more than two groups values were assessed using analysis of variance (ANOVA) for normally distributed variables. The chi-square test was used for comparing distribution of categorical variables. Logistic regression test was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) which were adjusted for multiple covariates in different models. DII scores were analyzed as quartiles. Statistical tests were performed using SPSS software (SPSS 21). The p-values < 0.05 were considered as statistically significant.