This cross-sectional study was performed on a total of 264 stone former men (aged 18- 89 years) in Tehran, Iran in 2016. Participants were recruited from the Urology Research Center of Sina Hospital, Tehran, Iran. Inclusion criteria for this study were having a history of kind stone formation and age ≥ 18 years. People with a history of, thyroid disease, fatty liver disease, malignancy, stroke, diabetes, cardiovascular disease, and hypertension were excluded. Participants who were on medications such as corticosteroids, diuretics, anti-cancer drugs, multivitamins, potassium citrate, calcium, and vitamin D or C supplements were not eligible for this study. Furthermore, all alcohol drinkers and drugs abusers were excluded. Patients were included in the study after signing written informed consents.
Usual food intake of patients during the previous year was measured by a validated semi-quantitative 168-item food frequency questionnaire) FFQ( . DII was calculated using the method reported by Shivappa et al. . The DII is based on 1943 scientific papers scoring 45 food parameters based on whether they elevated (+1), reduced (−1) or had no impact (0) on six inflammatory biomarkers [C-reactive protein, interleukin (IL)-1 beta, IL-10, IL-4, IL-6, and tumor necrosis factor-alpha). As mentioned, Shivappa et al. calculated DII according to the 45 food parameters. As dietary patterns of different populations are different with each other, some food parameters used in the study by Shivappa may not be available in different FFQs. Hence, researchers calculate DII according to available foods in the FFQ by modification of the method used by Shivappa. et al . In the current study, the DII score was calculated using the corresponding 32 food parameters available from the FFQ used in our study. This approach has been used broadly in the previous studies . The DII score was calculated with the use of the corresponding 32 nutrients or food parameters available from the FFQ, including energy, protein, total fat, carbohydrate, dietary fiber, mono-unsaturated fatty acids, n-3 fatty acids, n-6 fatty acids, poly-unsaturated fatty acids, saturated fatty acids, cholesterol, trans fatty acids, vitamin A, thiamin, niacin, riboflavin, Vitamin B-6, folate, vitamin B-12, vitamin E, vitamin C, Vitamin D, b-carotene, iron, magnesium, zinc, selenium as well as caffeine, onion, green/black tea, paper, and garlic. The inflammatory effect scores for dietary components used for calculation of DII in this study are reported in Table S1. To calculate the DII score for each participant, the mean intake of each nutrient or food parameter was standardized by subtracting mean global intake of food items from the actual individual’s intake and dividing it by the global SD to create a z-score. These z-scores then were converted to proportions and centered by multiplying values by 2 and subtracting 1 to normalize the scoring system and to avoid skewness. The centered percentile values for food items were then multiplied by the corresponding food item-specific inflammatory effect scores to obtain the food item-specific DII scores. Calculation of DII for carbohydrate intake in a participant in our study as an example for DII calculation is presented in Table S2; similar approach was followed for the calculation of DII for other nutrients. Information about global daily mean intake, standard deviation for global intake, and overall inflammatory effect score of all nutrients/food items used for DII calculation is reported in the study by Shivappa et al. . The overall DII score for each individual was calculated by summing food item-specific DII scores . Higher DII scores indicate a more pro-inflammatory diet, while lower DII scores indicate a more anti-inflammatory diet.
Measurements of study outcomes
The 24-h urine samples were collected from all participants and urine was analyzed to evaluate urinary levels of calcium, citrate, creatinine, oxalate, and uric acid by using an AutoAnalyzer as described previously . Hyperoxaluria was defined as the urinary oxalate ˃ 40 mg/day, hypocitraturia as urinary citrate of <450 mg/day, hyperuricosuria as urinary uric acid over 0.8 g/day, hypercreatininuria as urinary creatinine of ˃ 24 mg/day, and hypercalciuria as a urinary calcium ≥ 250 mg/day .
Measurement of other variables
Information on education level, age, marital status and occupation was obtained using interview by a trained interviewer. Physical activity was measured using of the International Physical Activity Questionnaires (IPAQ) . Body weight was measured in minimal clothing after removal of shoes by a digital scale (Seca, Germany) with a precision about 0.1 kg. Height of individuals was assessed in standing position, without shoes, using a calibrated stadiometer (Seca, Germany) to the nearest 0.1 cm. BMI was calculated as weight divided by the square of height (kg/ m2).
DII was categorized into tertiles: T1 (- 3.72 to - 0.74); T2 (- 0.73 to 0.92); T3 (0.93 to 3.99). Analysis of variance (ANOVA) and chi-square tests were used to compare continuous and nominal/ordinal variables across tertiles of DII, respectively. Continuous variables are reported as mean ± SE and nominal/ordinal variables as frequency. Odds ratio (OR) and 95% confidence interval (CI) for the relation of DII to study outcomes was calculated using the logistic regression analysis. Statistical significance was set at p ≤ 0.05 for all tests. All analyses were undertaken using the statistical Package for Social Science (Version 22.0; SPSS Inc., Chicago IL, USA).