Study Design and Participants
The current cross-sectional study was conducted among overweight and obese women who attended health centers in Tehran, Iran, in 2018. A random sample of 280 adults healthy overweight and obese aged between 18 and 50 years old women was selected from 20 various health centers by a multistage cluster random sampling method. Eligible criteria included body mass index in the range of 25-40 kg/m2 and good general health. Exclusion criteria included: a history of cardiovascular disease, hypertension, diabetes mellitus, hepatic or renal disease, and alcohol, smoking usage, medicine usage other than birth control pills, pregnancy or lactation, menopause, following a specific diet or bodyweight fluctuation over the past 1 year. Participants whose reported daily energy intake less than 800 kcal/d or more than 4200 kcal/d were also excluded. The study protocol had an ethical approval (ID: 95-03-161-33142), which was approved by the Ethics Commission of the Tehran University of Medical Sciences. Informed consent was obtained from all participants.
Participants’ dietary intake over the past year was assessed using a valid and reliable semi-quantitative food frequency questionnaire (FFQ) self-reported. This FFQ consists of 147 food items with standard serving sizes, and participants were asked to specify their consumption frequency for each food item for each item based on 4 predefined groups, including daily weekly, and monthly frequent consumption. The consumed foods portion sizes were converted to grams using household measurements. Then, nutrient and energy intakes were computed using NUTRITIONIST IV software (version 7.0; N-Squared Computing, Salem, OR), which was tailored for Iranian foods. For calculating EDII, all nutrient values were adjusted for energy intake using the residual method.
Dietary Inflammatory Index Calculation
Since not all food items are the same in all types of food frequency questionnaires, we should calculate the DII score according to the data of foods which are available in our food frequency questionnaire with the change in the method of Shivapa et al. To calculate EDII for the participants of this study, the dietary data were first linked to the regionally representative world database, which provided a robust estimate of a mean and standard deviation for each parameter. These then become the multipliers to express an individual’s exposure relative to the ‘standard global mean’ as a z-score. A z-score for each food consumed was calculated by subtracting the ‘standard mean’ from the actual food parameter value and divided by its standard deviation. Next, to minimize the effect of ‘right skewing’, this value was then converted to a centered percentile score, which was then multiplied by the respective food parameter inflammatory effect score to obtain the subject’s food parameter-specific EDII score. All of the food-parameter-specific EDII scores were then summed together to create an overall EDII score for every subject in the study . In total, the EDII computed based on this study’s FFQ includes data on 29 of the 45 possible food variables composing the EDII: energy, carbohydrate, protein, fat, fiber, cholesterol, trans fat, SFAs, MUFAs, PUFAs, omega-3, omega-6, niacin, thiamin, riboflavin, vitamin B-6, vitamin B-12, iron, magnesium, selenium, zinc, vitamin A, vitamin C, vitamin D, vitamin E, folic acid, b-carotene, caffeine, onion, and tea. The EDII was analyzed as a dichotomous variable, categorized based on the median value of the EDII. DII values were categorized according to the median (0.05). EDII ≤ 0.05 is considered an Anti-inflammatory diet group and, EDII > 0/06 is considered a pro-inflammatory diet.
Quality of Life Assessment
The SF-36 is a short-form, self-administered quality of life scoring questionnaire. It consists of 36 questions, 35 of which are compressed into eight multi-item scales including physical functioning (PF), role physical (RP), bodily pain (BP), general health (GH), vitality (VT), social functioning (SF), role emotional (RE), and mental health (MH)[22, 23]. The SF-36 also includes a question self-evaluating health changes in the past year (reported health), which does not belong to the eight dimensions or the total SF-36 score. Each of these 8 dimensions has a score between 0 (worst health) to 100 (best health). [24-26]
Blood samples were collected early in the morning after 12-hour night-time fasting at the Nutrition and the Biochemistry Laboratory of the School of Nutritional Sciences Dietetics, TUMS. Samples of blood collected in parent tubes containing 0.1 EDTA, was taken following the standard protocol in a sitting position. Samples of serum were centrifuged for serum collection 10 min at 300 rpm, diluted in 1 ml tubes, and stored at −80 °C until the analysis. Tests were analyzed utilizing the Auto-Analyzer BT 1500 (Selectra 2; Vital Scientific, Spankeren, Netherlands). Hypersensitive serum C-reactive protein levels were measured by an immunoturbidimetric test with the Pars Azmoon kit (Pars Azmoon Inc. Tehran, Iran).
Anthropometric measures, including body weight, body mass index, waist circumferences, and waist-hip ratio, were measured in an overnight fasting state, without shoes, with minimal clothing and by the use of a multi-frequency bioelectrical impedance analyzer In-body 770 scanner by trained dietitians (In-body Co., Seoul, Korea). Height was measured with a wall Seca 206 stadiometer (Hamburg, Germany), based on a standard protocol, their height was recorded to the nearest 0.2 cm.
Assessment of other Variables
The normality of variables distribution was checked using the Kolmogorov-Smirnov test. We had no missing data.. EDII (as dichotomous) was examined across the following characteristics: age, weight, height, economic status, BMI, waist circumference, waist-hip ratio, energy intake, physical activity, and quality of life measurements, via independent sample T-test analyses. Comparisons of different food group intakes across the EDII categories were analyzed through an independent sample T-test. Multivariable linear regression analyses of the continuous EDII score were conducted to determine the association of the EDII with quality of life and hs-CRP levels. Variables were adjusted for the following confounding factors: age, weight, physical activity, smoking, economic status, and employment status. The results are reported as a percentage change (β) with 95% confidence intervals (95% CI). Statistical analysis was performed using SPSS version 21 (SPSS Inc., Chicago, USA). Significance was set at a probability of <0.05 for all tests.