Study population
In this cross-sectional study, we used the baseline data of RaNCD that is one of the sub-studies of the national Prospective Epidemiological Research Studies in IrAN (PERSIAN) cohort [14]. Ravansar is one of the western cities of Kermanshah Province with a population of about 50,000 in the west of Iran. The details of RaNCD study have already been published [15]. All participants aged 35-65 years in the bassline phase of RaNCD entered this study (10,000 individuals). According to the purpose of the present study, subjects with cancer and pregnant woman were excluded from the study. The final study population included 9,811 adults (Fig 1).
Data collection
Socio-demographic characteristics including age, sex, marital status, residence place and information on personal habits (smoking status and alcohol consumption) was collected face to face using digital questionnaires.
The socio-economic status (SES) was measured, using 18 items (including housing, car based on its price, dishwasher, freezer, washing machine, computer, laptop, internet access, motorcycle, color TV, TV type, bathroom, cell phone, vacuum cleaner, area per capita, room per capita, education level and residence place) by principal component analysis (PCA) method; finally, the SES was classified from the poorest to the richest in five groups [16].
Physical activity questionnaire (including 22 questions) standardized cohort study was used to assess participants’ physical activity, based on met/hour per week and divided into three groups (light, moderate, high).
To measure biochemical markers including triglyceride (TG), low-density lipoprotein Cholesterol (LDL-C), high-density lipoprotein Cholesterol (HDL-C), and Total cholesterol (T-C) and fasting blood sugar (FBS); blood samples were collected after a 12 hours fasting.
Height (with 0.1 cm precision) was measured using a BSM 370 (Biospace Co,Seoul, Korea), Weight and other anthropometric indices including body mass index (BMI), body fat mass (BFM) and visceral fat area (VFA), (with 0.5 kg precision) were measured using a Bio Impedance Analyzer BIA (InBody 770 Biospace, Korea). Waist circumference (WC) and waist to hip ratio (WHR) were measured by standard methods. Blood pressure (BP) measured by a manometer cuff and stethoscope after 10 minutes of rest from arm in the seated position.
Assessment of the dietary inflammatory index
The DII scores was calculated using items of Food Frequency Questionnaire (FFQ). Participants responded to questions about amounts and frequencies of consumption of food groups. For help estimate portion sizes the photo in the booklet were shown to them.
Shivappa et al. have reported 45 foods items were associated with one or more of the inflammatory including Interleukin-1b (IL-1b), Interleukin- 6 (IL-6), Tumor Necrosis Factor-a (TNF-a) or C-reactive protein (CRP) or anti-inflammatory markers including Interleukin-4 (IL-4) and Interleukin-10 (IL-10). Based on the Shivappa et al. method, on the basis of mean and standard deviation (SD) of global intake, Zscore was determined for each parameter. In the next step the Z-score became a percentile. The inflammatory score for each of the food parameters was calculated using this method, and finally the inflammatory score of all parameters was summed to calculate the total DII score. The more positive DII scores indicate more pro-inflammatory diets and more negative scores imply more anti-inflammatory diets [17, 18]. DII scores were categorized into four groups (quartile) to assess associations. The first and fourth quartiles had the lowest and highest DII scores, respectively. For the present study out of 45 food parameters, 31 parameters were used to calculate DII, including; carbohydrate, protein, total fat, trans fat, monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), cholesterol, saturated fat, omega-3, omega-6, vitamins of A, B6, B12, C, D, E, selenium, zinc, energy, iron, magnesium, niacin, riboflavin, thiamine, beta-carotene, fiber, folic acid, caffeine, garlic, onion and tea.
Hypertension and type 2 diabetes mellitus assessment
Hypertension was defined as having a systolic blood pressure (SBP) ≥140 mmHg and/or diastolic blood pressure (DBP) ≥90 mmHg, and/or currently taking antihypertensive drugs [19]. T2DM was defined as having an FBS (fasting blood sugar) of ≥126mg/dl and/or being on diabetes medication and/or if the diabetes was confirmed by a health practitioner [20].
Statistical Analysis
Descriptive analysis including mean ± standard deviation and frequency (percentage) by quartiles of DII was done for quantitative and qualitative variables, respectively. In addition, mean ± standard deviation of anthropometric and biochemical characteristics was compared by one-way ANOVA among four studied groups. Logistic regression model was used to determine the association between DII and hypertension and T2DM. The crude and adjusted odds ratios with 95% confidence interval were reported. All analyses were done with STATA software version 14.2 (Stata Corp, College Station, Tex).