Inulin might improve body composition in obese children. We aimed to determine the effects of inulin supplementation on body composition and metabolic outcomes in obese children. A randomized, double-blinded placebo-controlled study was conducted in obese Thai children aged 7–15 years. Participants were assigned to 3 treatment groups for 6 months: 13 g of extracted inulin powder from Thai Jerusalem artichoke, isocaloric maltodextrin, and dietary fiber advice groups. Body composition was assessed by bioelectrical impedance analysis. One-hundred and fifty-five children completed the study (mean age 10.4 ± 2.2 years, BMI z-score 3.2 ± 1.0, 59% male). The drop-out rate was 6%. The inulin extract yielded more than 90% compliance without significant gastrointestinal side effects. All three groups demonstrated a significant decrease in BMI z-score, fat mass index (FMI), and trunk FMI, but the differences between groups were not observed. Fat-free mass index significantly increased only in the inulin group (16.18 ± 1.90 vs. 16.38 ± 1.98 kg/m2, P = 0.009). There were no significant differences in the metabolic profiles between groups. Despite showing no substantial effect on adiposity, inulin may increase fat-free mass in obese children. Further research in the change of gut microbiota composition is needed to determine inulin’s impact on host-microbe interaction in pediatric obesity.

Introduction. Iron deficiency (ID) is the most common nutritional deficiency found in pediatric practice. A higher prevalence of ID may be found in children with obesity. Obesity is a chronic low-grade inflammatory condition. It is postulated that inflammation increases hepcidin, a regulator of iron homeostasis. The aim of this study was to investigate the associations between iron status, hepcidin, and BMI-standard deviation score (BMI-SDS) in children with and without obesity. Methods. A cross-sectional study of Thai children with obesity (5 to 15 years old) versus age- and sex-matched, nonobese controls was conducted. A total of 63 children with obesity and 27 controls were enrolled. Complete blood count, serum iron, ferritin, transferrin saturation, and total iron binding capacity were analyzed. Serum hepcidin-25 was assayed using a hepcidin ELISA Kit (Human Hepc25). Results. There were 63 children with obesity, the median age (IQR) being 10 (9–13) years, and 27 controls. The median (IQR) BMI-SDS of the obese group was 2.3 (2.0–2.6) vs. −0.5 ((−1.3)−0.4) of the control group. ID was diagnosed in 27 children in the obese group (42.9%); 4 of the children with obesity and ID had anemia. Serum hepcidin-25 levels of the children with ID vs. without ID in the obese group were not significantly different (median (IQR) 25 (12.9–49.2) and 26.4 (12.6–43.6), respectively) but both of them were significantly higher than controls (19.7 (8.3–25.5) ng/ml, p  = 0.04). BMI-SDS was positively correlated with hepcidin-25 (r = 0.28, p  = 0.001). Conclusion. Prevalence of iron deficiency in Thai children with obesity and serum hepcidin-25 was higher than controls. Further study in a larger population, preferably with interventions such as weight loss program, is warranted to clarify this association.

Background. Dysbiosis of intestinal microbiota may be linked to pathogenesis of obesity and metabolic disorders. Objective. This study compared the gut microbiome of obese Thai children with that of healthy controls and examined their relationships with host lifestyle, adiposity, and metabolic profiles. Methods. This cross-sectional study enrolled obese children aged 7–15. Body composition was evaluated using bioelectrical impedance analysis. Stool samples were analyzed by 16S rRNA sequencing using the Illumina MiSeq platform. Relative abundance and alpha- and beta-diversity were compared with normal-weight Thai children from a previous publication using Wilcoxon rank-sum test and ANOSIM. Relationships of gut microbiota with lifestyle activity, body composition, and metabolic profiles were assessed by canonical correlation analysis (CCA) and Spearman correlation. Results. The study enrolled 164 obese children with a male percentage of 59%. Mean age was 10.4 ± 2.2 years with a BMI z-score of 3.2 ± 1. The abundance of Bacteroidetes and Actinobacteria were found to be lower in obese children compared to nonobese children. Alpha-diversity indices showed no differences between groups, while beta-diversity revealed significant differences in the family and genus levels. CCA revealed significant correlations of the relative abundance of gut microbial phyla with sedentary lifestyle and certain metabolic markers. Univariate analysis revealed that Actinobacteria and Bifidobacterium were positively correlated with HDL-C and negatively correlated with body weight and screen time. Additionally, Actinobacteria was also negatively associated with fasting insulin and HOMA-IR. Lactobacillus showed positive correlation with acanthosis nigricans and adiposity. Cooccurrence analysis revealed 90 significant bacterial copresence and mutual exclusion interactions among 43 genera in obese children, whereas only 2 significant cooccurrences were found in nonobese children. Conclusions. The composition and diversity of gut microbiota in obese Thai children were different from those of their normal-weight peers. Specific gut microbiota were associated with lifestyle, adiposity, and metabolic features in obese children. An interventional study is needed to support causality between specific gut microbiota and obesity.