OBJECTIVE: The purpose of our study was to assess the relationship between nutrient intake, partitioning of food intake, parents' overweight and adiposity in a group of children. SUBJECTS: 530 7 ± 11-year-old children: 278 males, 252 females. METHODS: Energy intake, nutrient intake and percentage distribution of the intake of energy among the different meals were assessed by means of diet history. Body composition was obtained by measuring skinfold thickness. RESULTS: We identi®ed the relationship between the children's adiposity and their parents' body mass index (BMI) mother: r 0.12, P`0.01; father: r 0.13; P`0.01), carbohydrate (r 7 0.15, P`0.001) and fat intake (r 0.14, P`0.002), and the proportion of energy taken at dinner (r 0.1, P`0.05). A multiple regression analysis was run with a stepwise procedure using relative adiposity as the dependent variable and parents' BMI, dinner intake (percentage of energy intake), EIaBMR ratio (an index of energy intake validity), and sex (dummy variable) as independent variables. All the independent variables, except percentage of fat intake, were included in the ®nal model. The equation was able to explain % 19% (R 0.44, P`0.001) of inter-individual fat mass percentage variability. CONCLUSIONS: Diet composition did not contribute to explain the children's adiposity when the parents' overweight (BMI) was taken into account. However, the percentage distribution of the intake of energy among the different meals, particularly at dinner, contributed to explain inter-individual variance of fatness in children of both sexes.

Recent studies indicate the existence of a complex microbiome in the meconium of newborns that plays a key role in regulating many host health-related conditions. However, a high variability between studies has been observed so far. In the present study, the meconium microbiome composition and the predicted microbial metabolic pathways were analysed in a consecutive cohort of 96 full-term newborns. The effect of maternal epidemiological variables on meconium diversity was analysed using regression analysis and PERMANOVA. Meconium microbiome composition mainly included Proteobacteria (30.95%), Bacteroidetes (23.17%) and Firmicutes (17.13%), while for predicted metabolic pathways, the most abundant genes belonged to the class “metabolism”. We observed a significant effect of maternal Rh factor on Shannon and Inverse Simpson indexes (p = 0.045 and p = 0.049 respectively) and a significant effect of delivery mode and maternal antibiotic exposure on Jaccard and Bray–Curtis dissimilarities (p = 0.001 and 0.002 respectively), while gestational age was associated with observed richness and Shannon indexes (p = 0.018 and 0.037 respectively), and Jaccard and Bray–Curtis dissimilarities (p = 0.014 and 0.013 respectively). The association involving maternal Rh phenotype suggests a role for host genetics in shaping meconium microbiome prior to the exposition to the most well-known environmental variables, which will influence microbiome maturation in the newborn.

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