The current cross-sectional study was carried out on 378 children and adolescents affected by overweight and obesity (body mass index (BMI) Z-score ≥ 1 according to age- and sex-specific World Health Organization criteria ) aged 6–13 years. The sample size was calculated based on a previous study of the DASH score and components of MetS (TG), with a standard deviation of 4.3 for the DASH score and 55 mg/dL for TG [12, 17]. Considering α = 0.5, power = 0.995, design effect = 1.2, and standard deviation of those variables, the minimum sample size required was 322 individuals. Participants were randomly selected from students with excess weight studying in primary schools located in three main districts of Tehran, Iran, using random number tables to select schools and students. Individuals were deemed eligible for inclusion if they were not on special diets, had no diagnosed illnesses such as diabetes, liver, or kidney diseases, and were not taking any pharmaceutical agents that affect glucose and lipid metabolism or any dietary supplements. Participants with incomplete dietary data (n = 12), and those who over- or under-reported their dietary intake were excluded (n = 16). To define over- and under-reports, the energy intake was divided by the estimated energy requirement according to equations proposed by the Institute of Medicine ; those not within the ±2SD range were deemed over- and under-reports. Additionally, subjects who had key missing biochemical or anthropometric values were also excluded (n = 9). Finally, statistical analyses were performed on 341 participants.
Written informed consent was obtained from children’s parents or legal guardians. Protocols of the study were approved by the institutional ethics committee of the Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences (Ethics approval ID: IR.SBMU.ENDOCRINE.REC.1395.373).
Anthropometrics, biochemical assay, and other measurements
Trained nutritionists with high experience in the paediatric field recorded anthropometric measurements according to standard methods. Weight was recorded to the nearest 0.1 kg while subjects were barefoot and in light clothing, using the scale function of GAIA 359 PLUS body composition analyser (Jawon Medical Co. Ltd., Shinsang, Korea). Height was measured to the nearest 0.5 cm, while standing with shoulders in normal alignment and barefoot, using a stadiometer. BMI was calculated as weight (in kilograms) divided by height (in meters) squared (kg/m2). Waist circumference (WC) was measured to the nearest 0.5 cm using a nonelastic tape, midway between the iliac crest and the lowest rib, after gentle respiration in standing position, and without any pressure to the body surface. Arterial blood pressure was measured manually on the right arm using a mercury sphygmomanometer with a suitable cuff size after 15 min of rest, by the Korotkoff sound technique. Systolic blood pressure (SBP) was determined by the onset of the tapping sound, and diastolic blood pressure (DBP) was determined at the disappearance of the sound. It was measured twice, at least one minute apart, with the average considered as the subject’s blood pressure.
Information on physical activity was collected using the Modifiable Activity Questionnaire (MAQ), to calculate metabolic equivalent task (MET) hours per week; high reliability (97%) and moderate validity (49%) have previously been ascertained for the Persian translated MAQ in adolescents .
Blood samples were drawn between 7:00 and 9:00 AM, after 12–14 h of overnight fasting, and centrifuged within 30–45 min of collection and analysed on the same day. Fasting plasma glucose (FPG) and serum triglycerides (TG) concentrations were measured by the enzymatic colorimetric method, using glucose oxidase and glycerol phosphate oxidase, respectively. High-density lipoprotein cholesterol (HDL-C) was measured after precipitation of the apolipoprotein B-containing lipoproteins with phosphotungstic acid. All kits were provided by Pars Azmoon, Tehran, Iran, and adapted to a Selectra auto analyser (Vital Scientific, Spankeren, The Netherlands). Inter- and intra-assay coefficients of variation (CV) were 1.1 and 1.4% for FPG, 1.1 and 3.1% for HDL-C, and 1.5 and 3.7% for TG, respectively.
Fasting serum insulin was determined by the electrochemiluminescence immunoassay (ECLIA) method, using Roche Diagnostics kits and the Roche/Hitachi Cobas e-411 analyser (Roche Diagnostics, GmbH, Mannheim, Germany). Intra- and inter-assay CV were 1.3 and 2.5%, respectively.
Pubertal status was assessed by a paediatric endocrinologist and according to Tanner stages, dividing the participants into the following two groups based on breast and genital growth stages: pre-pubertal (boys at genital stage I, girls at breast stage I) and pubertal (boys at genital stage ≥II, girls at breast stage ≥II).
Regular dietary intakes of the participants were assessed in face-to-face interviews by trained dietitians, using a valid and reliable semi-quantitative food frequency questionnaire (FFQ). The validity and reliability of the FFQ have previously been reported [20, 21]. Participants were asked to designate how frequently they consumed each food item during the previous year on a daily, weekly, or monthly basis. The US Department of Agriculture (USDA) serving sizes were specified for each food item on the FFQ whenever possible; otherwise, household measures were reported and then converted to grams and servings. In case children had difficulty recalling, mothers were asked about the type and quantity of meals and snacks. Since the Iranian Food Composition Table (FCT) is incomplete, the USDA FCT was used ; for special or traditional foods not listed in the USDA FCT, the Iranian FCT was used alternatively .
Iranian diet contains varying amounts of grains, legumes, plant and animal protein, vegetables, fruits, dairy products, nuts and seeds, fast and processed food, sweetened beverages, and sodium , all of which are evaluated in the DASH score. Moreover, previous paediatric studies in Iran have been able to observe associations between the DASH score and cardiometabolic RFs [12, 13]. Taking these facts into account, the DASH score was deemed a relevant and practical diet quality index in the context of the Iranian diet. Initially, to neutralise the effect of energy intakes on the eight components of the DASH score, each food group intake was calculated per 1000 kcal. Then the DASH score was computed according to Fung et al. . In short, the DASH score rewards points for high intakes of the five food groups, including fruits, vegetables, nuts and seeds and legumes, low-fat dairy products, and whole grains according to quintile rankings (i.e., participants in the lowest quintiles receive 1 point, those in the 2nd, 3rd, and 4th quintiles receive 2, 3, and 4 points respectively, and the highest quintiles, 5 points). Regarding the intakes of sodium, sweetened beverages, and red and processed meat, which are minimised in the DASH diet, participants in the lower quintiles of intakes scored higher points (i.e., the lowest quintiles are assigned 5 points and the highest quintiles, 1 point). We then summed up the eight component scores to obtain the overall DASH score of a participant, ranging from 8 to 40.
Overweight was defined as being between 1SD and 2SD, and obesity as being above 2SD in sex-specific BMI-for-age (5–19 years) charts of the World Health Organization .
Two definitions were used to categorise MHO/MUO. The first one was based on metabolic RFs, in which MUO was defined as having two or more of the following cardiometabolic abnormalities: WC ≥90th percentile for age and sex according to national reference curves ; SBP and DBP ≥90th percentile for sex, age, and height based on the National Heart, Lung, and Blood Institute’s recommended cut-off points ; FPG ≥100 mg/dL according to the recommendations of the American Diabetes Association ; fasting TG ≥110 mg/dL; and HDL-C < 40 mg/dL .
The second definition was based on a homeostatic model assessment of insulin resistance (HOMA-IR), using the cut-point proposed by Prince et al., by which participants with a HOMA-IR score ≥ 3.16 were deemed MUO .
All statistical analyses were conducted using the Statistical Package for Social Sciences version 15.0 (SPSS Inc., Chicago, IL, USA). Normality of distribution was assessed using histogram charts and Kolmogorov–Smirnov analysis. Characteristics of participants were expressed as mean ± SD or median and interquartile range (IQR) for normal and skewed distributions, respectively, and percentages for categorical variables. Linear regression and chi-square analyses were used to test the trend of continuous and categorical variables, respectively, across tertiles of the DASH score.
To examine the association of obesity phenotypes in each tertile of the DASH score, logistic regression models were used; odds ratios (ORs) and 95% confidence intervals (CIs) were reported. In this analysis, in addition to the crude model, the confounding effects of sex, puberty status, physical activity, BMI Z-score, and passive smoking were controlled in model 2, and further adjustments for the intakes of energy, saturated fatty acids, and monounsaturated fatty acids were performed in model 3. P-values < 0.05 were considered significant.