Subjects and Methods
Study Design and Population
This case-control study was performed on the population of women with and without PCOS at the reproductive age (18–45 years) referred to the obstetrics and gynecology wards and PCOS clinic of Taleghani, Shohada, and Arash hospitals, Tehran, Iran, during 2019–2020. To generalise the results, the study population was selected from several hospitals. The case group population (PCOS new cases) who have been referred to obstetrics and gynaecologist wards and PCOS clinic due to menstrual problems, infertility or skin, and hair disorders from the endocrine clinic as well, was selected based on the approval and diagnosis of an expert gynecologist and also having two or three of the Rotterdam standard criteria, including: clinical or biochemical hyperandrogenism, menstrual irregularities, and ovaries with multiple cysts. The control group was also selected from healthy women with regular menstruation who were attended in the same hospital as accompanied person with the patients, by using a modified Ferriman–Gallwey score of <8. Individuals with a history of hypothyroidism, hyperprolactinemia, Cushing's syndrome, adrenal hyperplasia, drug use including contraceptive pills, hormonal drugs, and glucocorticoids, taking mineral supplements and vitamins, having a special diet for the past 6 months, smoking, alcohol intake, subjects more than a year has passed since their diagnosis of PCOS, and pregnant or lactating women have not been included in the study. In addition, in case of underreporting or overreporting of energy intake (less than 800 kcal and more than 4200 kcal) and not answering more than 40 items in the food frequency questionnaire (FFQ), subjects were excluded from the study. Demographic, anthropometric and lifestyle and physical activity characteristics were completed separately by two trained nutritionists using valid questionnaire. The required sample size was calculated Fleiss formula with continuity correction model. To increase the study power and due to the limited access to the number of samples in the case group, the number of participants in the control group was considered 1.5 times that of the case group. A total of 510 people (210 case group and 300 control group) was estimated that at the end and after complete data collection and exclusion criteria, 16 participants were removed from the study process due to overreporting of energy intake (more than 4200 kcal). Finally, statistical analysis was performed for 494 samples (203 in the case group and 291 in the control group). This study was approved by Iran National Committee for Ethics in Biomedical Research (NO: IR.IAU.SRB.REC.1398.027). All the participants signed the written informed consent and they were assured that all the information would be kept private.
The anthropometric measurements were obtained using standardised protocols. Weight was measured while the participants were wearing light indoor clothing without shoes by employing a digital Seca scale (model 707; Seca) with the accuracy of 100 g. Height was measured in standing position without shoes, using a stadiometer, to the nearest 0.1 cm (model 208 Portable Body Metre Measuring Device; Seca). The body mass index (BMI) was calculated as weight (kg) divided by the square of the height (m2). The waist circumference (WC) was measured immediately above the hipbone, without any pressure to body surface, using a nonelastic tap.
Dietary intake over the previous year was obtained by a validated semiquantitative FFQ which encompassed 147 food items. The FFQ consisted of a list of usual Iranian dietary items with standard serving sizes. For each food item, the average portion size consumed and frequency of intake were obtained from self-report on the FFQ. Frequency of intake for each food item included: never, 2–3 times/month, 1 time/week, 2–4 times/week, 5–6 times/week, and daily. Portion sizes were changed to gram by using standard Iranian household measures. Daily nutrient consumptions for each person were measured by application of the United States Department of Agriculture's (USDA) national nutrient databank. Nutritionist IV software was used to calculate the daily energy and nutrient intake for each participant.
Calculation of DII Index
The DII calculation was performed using the article of Shivapa et al. In the process of calculating the DII, to reduce between-subject variation, dietary intakes were energy-adjusted using the residual method proposed by Willett and Stampfer. Then the Z-score for each of the items was calculated using the following formula (two global mean and SD numbers were extracted from Shivapa article table)
Z-score = (Mean intake - global mean)/SD for global mean
In the next step, the Z-score is converted to percentiles and then the obtained percentiles are multiplied by the coefficients of the overall inflammatory effect score in the Shivapa article table. Finally, all the scores obtained are added together to calculate the DII. The overall score must be between negative 10 and positive 10. The flavonoid content of dietary parameters was calculated using USDA data. In general, a higher DII score indicates a proinflammatory diet, while a lower DII score indicates an anti-inflammatory diet. Finally, in this study, 36 dietary parameters were extracted from the FFQ including energy, protein, total fat, saturated fat, monounsaturated fatty acid (MUFA), PUFA, trans-fatty acid, omega-3 fatty acids, omega-6 fatty acids, cholesterol, carbohydrates, fibre, caffeine, vitamin A, beta-carotene, thiamine, riboflavin, niacin, vitamin B6, folate, vitamin B12, vitamin C, vitamin D, vitamin E, iron, magnesium, selenium, zinc, garlic, onion, Flavan-3-ol, flavones, flavonols, flavonones, anthocyanidins, and isoflavones were used to calculate the DII index.
All statistical analyses were performed by using SPSS software (version 19.0; SPSS Inc). The normality of variables was evaluated by Shapiro–Wilk tests. Mean values of more than two groups were assessed using analysis of variance for normal distribution variables. Moreover, for comparing categorical variables, the χ 2 test was used. Binary logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) adjusted for multiple covariates in a different model. The data were presented as mean ± standard deviation and OR with 95% CI, and in all results, the significance level was determined as p < .05.
A dose-response effect was confirmed with the test for trend (p for trend) as a means of verifying whether or not there was a significant association for any particular level of exposure. The results were adjusted in three models, which included: 1—age and BMI, 2—Model 1 and weight, WC, education status, marital status, physical activity, and use of multivitamin mineral supplements, vitamin D supplements, folic acid supplements, and omega 3 supplements.
Clin Endocrinol. 2022;96(5):698-706. © 2022 Blackwell Publishing