In the current study, 276 adults (118 men and 152 women) have participated. Participants were recruited through a recruitment message placed in the social network. Subjects were chosen by convenience sampling. The research criteria included apparently healthy adults with age range of 18-50, having a desire to take part in the study, and being rsident in Tehran. We excluded those who had extreme values of dietary intake (less than 800 kcal/d or more than 4200 kcal/d, respectively), suffering from kidney, liver, and lung diseases and other conditions affecting the body composition status or infectious and active inflammatory diseases, pregnancy, lactation, routine supplement or drug use, such as weight loss, hormonal, sedative drugs, thermogenic supplements like caffeine and green tea, conjugated linoleic acid (CLA), etc. After removing 3 subjects due to the above-mentioned reasons, only 270 participants remained for statistical analysis. All necessary explanations about project were given to the participants. All procedures were in accord with the ethical standards of the Tehran University of Medical Sciences (Ethics Number: IR.TUMS.VCR.REC.1396.4085), which approved the protocol and informed consent form. All participants signed a written informed consent prior to the start of the study.
The height of participants was measured without shoes by a wall stadiometer with precision close to of millimeter (Seca, Germany). We determined waist circumference (WC) by a non-elastic tape fixed in the middle of the iliac crest and the lowest rib on the exhale. Body composition including weight, fat mass (FM), fat free mass (FFM), lean body mass (LBM) and body mass index (BMI) was measured by InBody (InBody720, Biospace, Tokyo, Japan) with following protocol: avoid food ingestion for at least 4 hours, minimum intake of 2 liters of water the day before, no coffee or alcoholic beverage consumption during at least 12 hours. Subjects were asked to empty their bladder immediately before the test .
Assessment of other variables
Subjects completed a self-administered questionnaire to assess the participants' demographic including age, gender (male/female), smoking (not smoking/quit smoking/smoking) and education (under diploma/diploma/educated). Physical activity was assessed using the international physical activity questionnaire (IPAQ). Subjects were quantified into three categories including very low (<600 MET-minute/week), low (600-3000 MET-minute/week), moderate and high (>3000 MET-minute/week) calculated based on Metabolic Equivalents (METs).
A validated 147-item semi-quantitative food frequency questionnaire was utilized to evaluate habitual food intake . Nutritional data was gathered by experienced and trained nutritionists through duly interviews. Participants reported their intake frequency for each food item during the past year on a daily, weekly, monthly, or yearly basis. Portion sizes of consumed foods that were reported in household measures were converted to grams. The food items were analyzed for their energy content using the Nutritionist 4 software (version 7.0; N-Squared Computing, Salem, OR, USA), modified for Iranian foods.
Resting metabolic rate
An indirect calorimetric method (Cortex Metalyser 3B, Leipzig, Germany) was used to estimate resting metabolic rate (RMR). It is based on calculating the amount of oxygen consumed by the body. First, a ventilated hood was given to individuals, to inhale the respiratory air into the lungs, then the device determines the amount of oxygen consumed by the body according to the amount of metabolism using the volume of oxygen concentration. The calculation of RMR was under the following conditions:1) fasting over the past 12 hours 2) abstention from alcohol, caffeine, for at least 4 hours although. It is considered an ideal period of 12 hours to ensure that the body is resting and after digestion and absorption. 3) Subjects trained that rested in a supine position for 15 min also 5 minutes added to time .
Cardiorespiratory fitness testing
VO2max by the treadmill and the respiratory gas analyzer (Cortex Metabolizer 3B) was measured according to the Bruce protocol . This protocol is divided into successive 3-minute stages, that starts at a speed of 2.7 km·h−1 and an incline of 10% gradient for 3 minutes and becomes faster based on the participant’s tolerance.
Indications for terminating the test include if the patient request to stop due to chest pain, shortness of breath, or fatigue, when participants had more than 90% maximum heart rate predicted for age, a respiratory exchange ratio ≥ 1.10, and when a plateau is identified (<150 ml x min−1 increase) in V̇O2max contrary to an increment in speed. Two of the three criteria should meet. After that individuals cool down with 3 minutes-4 km/h walk and stretching exercises.
DII score was determined by multiplying the dietary inflammatory weights  of 29-item nutrients or food. Afterward, these values were summed. First, the daily intake of macro-and micronutrients (carbohydrate, protein, total fat, cholesterol, saturated fatty acids, monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), n-3 fatty acids, n-6 fatty acids, β-carotene, vitamin A, vitamin C, vitamin D, vitamin E, vitaminB6, vitaminB12, fiber, folic acid, niacin, riboflavin, thiamin, iron, zinc, selenium, magnesium, onion, caffeine) were computed to lessen the between-person variation in dietary intake; due to lack of some nutrients in our documents (trans FAs, flavan-3-ol, flavones, flavonols, flavanones, anthocyanidins, isoflavones, pepper, thyme/oregano, rosemary, garlic, ginger, saffron, and turmeric and tea), we excluded these items. Adjusted intake of food parameters for each individual was standardized to its corresponding global mean and standard deviation. The derived Z score values were converted to percentile and centered, by doubling the values and subtracting one, to normalize the scoring system and to avoid skewness. The centered percentile value for each food parameter is then multiplied by its respective overall food parameter score to obtain the food parameter-specific DII score. Finally, the DII score was determined by summing all of the food parameter-specific DII score. The greater the DII score, the more pro-inflammatory diet, and more negative scores demonstrate a more anti-inflammatory diet.
The normality of distributions was checked using Kolmogorov-Smirnov and Shapiro-Wilk statistical test. All variables had normal distributions. Then subjects were categorized based on median values of DII score and RMR both separately. In the next step, we merged these dichotomized groups of DII and RMR to compute four independent groups (low DII/ low RMR, low DII/ high RMR, high DII/ low RMR and high DII/ high RMR). To compare general characteristics across the four groups, we used one-way analysis of variance (ANOVA) and chi-square tests for quantitative and qualitative variables, respectively. To compare participants’ dietary intakes within four groups, analysis of covariance (ANCOVA) to adjust for energy intake. We used ANOVA to examine significant differences across the four above mention groups. Post hoc Tukey test was used to compare pairwise mean differences. Analysis of covariance test was performed to compare the mean of CRF among DII/RMR groups after adjusting for potential confounders such as age, sex, smoking status, energy intake, physical activity, and BMI. CRF values were then transformed into binary variables according to their median values. Binary logistic regression was performed to find the association of CRF with DII/RMR categories in various models. First, we adjusted age and sex. Then we additionally controlled for smoking and physical activity status. In the final model, we moreover adjusted BMI. To obtain the overall trend of odds ratios across the combined effect of DII and RMR, we considered these classifications as an ordinal variable in the logistic regression models and the first tertiles regarded as the reference group. All statistical analysis was performed with the SPSS (Statistical Package for Social Sciences) for Windows 25.0 software package (SPSS, Chicago, IL). The level of statistical significance was pre-set at p< 0.05.