Using G*Power 3.1 software (Universität Düsseldorf, Düsseldorf, Germany), the needed total sample size to assure statistical power of 0.8 and effect size of 0.35 was calculated 84 participants. In total, 91apparently healthy children in different weight categories (normal weight: 33, overweight: 33, obesity: 25) aged 5-18 years were randomly selected from the registered population at National Food and Nutrition Surveillance Program (NFNS), a population-based survey conducted periodically in Iran by the National Nutrition and Food Technology Research Institute (NNFTRI) in collaboration with the Deputy of Health of Iran Ministry of Health and Medical Education and United Nations Children’s Fund (UNICEF) as described elsewhere (34). The groups were matched based on age and sex. The inclusion criteria were having no history of hepatic or renal disease and taking no vitamin D supplements or medications affecting vitamin D metabolism such as anticonvulsant or corticosteroids at least 2 months prior to the study. The study protocol and objectives were clarified for all participants and their parents or their legal guardians before they signed a written informed consent. The study protocol and procedures were approved by Ethics Committee of NNFTRI.
Anthropometric measurements
Height was measured to the nearest of 0.1 cm using a wall-mounted stadiometer (Seca 206, Seca Company, Hamburg, Germany). Weight was measured while participants wearing light clothing and no shoes with a digital scale accurate to the nearest of 0.1 kg (Seca 840, Seca Company, Hamburg, Germany). Both instruments were calibrated daily. Body mass index (BMI), which has a strong correlation with adiposity in children (35), was defined as weight (kg)/height (m)2. Overweight and obesity were categorized using the BMI for age z-score (1-2 and >2, respectively).
Laboratory investigations
Blood samples drawn in the morning (08:00–10:00 hours) after an overnight fast were centrifuged at room temperature for 10 minutes at 800 g to separate sera, which were then aliquoted and stored at -80oC immediately until the day of analysis.
Total cholesterol, triglycerides, low-density lipoprotein-cholesterol (LDL-C) and high-density lipoprotein-cholesterol (HDL-C) concentrations were measured by using enzymatic methods (Pars-Azmoon, Tehran, Iran) and an auto-analyzer (Selecta E; Vitalab, Holliston, the Netherlands).
To determine serum concentrations of 25(OH)D, a commercial kit of direct enzyme immune-assay (EIA) was used (DIAsource, Louvain-la-Neuve, Belgium). The intra- and inter-assay variations were 2.5-7.8% (for values of 13.7-203 nmol/L) and 4.3-9.2% (for values 44.25-213.7 nmol/L), respectively, according to the manufacturer's manual. The accuracy of measurements of 25(OH)D concentrations were ensured using high-performance liquid chromatography (36) in the Laboratory of Nutrition Research, NNFTRI, that has been participating in the Vitamin D External Quality Assessment Scheme (DEQAS) since 2012.
Anti-adenovirus 36 antibody (anti-ADV-36-Ab) was assayed using EIA kit (Zellbio, Veltlinerweg, Ulm, Germany). Briefly, 50 µL pre-diluted serum samples (1:5), control sera (ready to use negative and positive, both included in the kit) followed by enzyme conjugate were transferred to the antibody coated microwells of a plate. After incubation and washing, a color reaction was developed following adding a chromogen to the wells. The reaction was halted using a stop solution. In this assay, the amount of absorbance at 450 nm is proportional to the absolute amount of specific antibody. We generated a standard curve using serially diluted positive control serum. The concentration of anti-ADV-36-Ab was expressed using arbitrary (arb) unit (Figure 1). The intra- and inter-assay variations were <10% and <12%, according to the manufacturer.
Statistical analyses
Continuous characteristics were expressed as mean±standard deviation (SD); categorical variables were displayed as frequencies. Normality of distribution was checked for all variables using Shapirio-Wilk test. Tests for differences of continuous variables among three BMI categories were performed using analysis of variance (ANOVA) or Kruskal-Wallis. Levene's test was used to evaluate homogeneity of between-group variances. For those variables with statistically unequal variances, Dunnett's T3 was applied for pair wise multiple comparisons. The analysis of covariate test was used to compare anti-ADV-36-Ab among BMI categories by adjusting serum 25(OH)D concentrations. Pearson’s correlation coefficient and multiple linear and logistic regression analysis were used to assess relationships between variables. A 2-tailed p<0.05 was considered significant. Analyses were performed using Statistical Package for Social Sciences 21.0 for Windows (SPSS Inc., Chicago, IL, USA).