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Background: The aim of this study was to determine whether physical activity volume and intensity in mid-childhood and early adolescence were associated with cardiometabolic risk factors at 13.5 years., Methods: Participants were recruited from the Mysore Parthenon observational birth cohort. At ages 6-10 and 11-13 years, volume and intensity of physical activity were assessed using AM7164 or GT1M actigraph accelerometers worn for ≥4 days, and expressed as mean counts per day and percentage time spent in light, moderate and vigorous physical activity according to criteria defined by Evenson et al. At 13.5 years, fasting blood samples were collected; lipids, glucose and insulin concentrations were measured and insulin resistance (HOMA) was calculated. Systolic and diastolic blood pressure were measured at the left arm using a Dinamap (Criticon). Anthropometry and bio-impedance analysis were used to assess body size and composition. Metabolic and anthropometric measures were combined to produce a metabolic syndrome risk score., Results: At 6-10 years, boys and girls respectively spent a median (IQR) of 1.1 (0.5, 2.0) % and 0.8 (0.4, 1.3) % of recorded time vigorously active. At 11-13 years, boys and girls respectively spent a median (IQR) of 0.8 (0.4, 1.7) % and 0.3 (0.1, 0.6) % of time vigorously active. All of the physical activity parameters were positively correlated between the 6-10 year and the 11-13 year measurements indicating that physical activity tracked from childhood to early adolescence. There were no associations between physical activity at 6-10 years and individual 13.5 year risk factors but % time vigorously active was inversely associated with metabolic syndrome score (B = -0.40, 95% CI -0.75, 0.05). Volume of physical activity at 11-13 years was inversely associated with 13.5 year HOMA and fat percentage and vigorous physical activity was associated with HOMA, fat percentage, sum of skinfolds, waist circumference and total: HDL cholesterol ratio. Vigorous physical activity was inversely associated with metabolic syndrome score (B = -0.51, 95% CI -0.94, -0.08)., Conclusions: Volume and intensity of physical activity in early adolescence were negatively associated with metabolic and anthropometric risk factors. Interventions that aim to increase adolescent physical activity, especially vigorous, may prevent cardiometabolic disease in later life.

Background: The mother is the only source of nutrition for fetal growth including brain development. Maternal nutritional status (anthropometry, macro- and micro-nutrients) before and/or during pregnancy is therefore a potential predictor of offspring cognitive function. The relationship of maternal nutrition to offspring cognitive function is unclear. This review aims to assess existing evidence linking maternal nutritional status with offspring cognitive function., Methods: Exposures considered were maternal BMI, height and weight, micronutrient status (vitamins D, B12, folate and iron) and macronutrient intakes (carbohydrate, protein and fat). The outcome was any measure of cognitive function in children aged <18 years. We considered observational studies and trials with allocation groups that differed by single nutrients. We searched Medline/PubMed and the Cochrane Library databases and reference lists of retrieved literature. Two reviewers independently extracted data from relevant articles. We used methods recommended by the Centre for Reviews and Dissemination, University of York and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement., Results: Of 16,143 articles identified, 38 met inclusion criteria. Most studies were observational, and from high-income settings. There were few randomized controlled trials. There was consistent evidence linking maternal obesity with lower cognitive function in children; low maternal BMI has been inadequately studied. Among three studies of maternal vitamin D status, two showed lower cognitive function in children of deficient mothers. One trial of folic acid supplementation showed no effects on the children's cognitive function and evidence from 13 observational studies was mixed. Among seven studies of maternal vitamin B12 status, most showed no association, though two studies in highly deficient populations suggested a possible effect. Four out of six observational studies and two trials (including one in an Iron deficient population) found no association of maternal iron status with offspring cognitive function. One trial of maternal carbohydrate/protein supplementation showed no effects on offspring cognitive function., Conclusions: Current evidence that maternal nutritional status during pregnancy as defined by BMI, single micronutrient studies, or macronutrient intakes influences offspring cognitive function is inconclusive. There is a need for more trials especially in populations with high rates of maternal undernutrition., Systematic Review Registration: Registered in PROSPERO CRD42013005702 .

Background: Size at birth is influenced by environmental factors, like maternal nutrition and parity, and by genes. Birth weight is a composite measure, encompassing bone, fat and lean mass. These may have different determinants. The main purpose of this paper was to use anthropometry and principal components analysis (PCA) to describe maternal and newborn body composition, and associations between them, in an Indian population. We also compared maternal and paternal measurements (body mass index (BMI) and height) as predictors of newborn body composition., Methods: Weight, height, head and mid-arm circumferences, skinfold thicknesses and external pelvic diameters were measured at 30 +/- 2 weeks gestation in 571 pregnant women attending the antenatal clinic of the Holdsworth Memorial Hospital, Mysore, India. Paternal height and weight were also measured. At birth, detailed neonatal anthropometry was performed. Unrotated and varimax rotated PCA was applied to the maternal and neonatal measurements., Results: Rotated PCA reduced maternal measurements to 4 independent components (fat, pelvis, height and muscle) and neonatal measurements to 3 components (trunk+head, fat, and leg length). An SD increase in maternal fat was associated with a 0.16 SD increase (beta) in neonatal fat (p < 0.001, adjusted for gestation, maternal parity, newborn sex and socio-economic status). Maternal pelvis, height and (for male babies) muscle predicted neonatal trunk+head (beta = 0. 09 SD; p = 0.017, beta = 0.12 SD; p = 0.006 and beta = 0.27 SD; p < 0.001). In the mother-baby and father-baby comparison, maternal BMI predicted neonatal fat (beta = 0.20 SD; p < 0.001) and neonatal trunk+head (beta = 0.15 SD; p = 0.001). Both maternal (beta = 0.12 SD; p = 0.002) and paternal height (beta = 0.09 SD; p = 0.030) predicted neonatal trunk+head but the associations became weak and statistically non-significant in multivariate analysis. Only paternal height predicted neonatal leg length (beta = 0.15 SD; p = 0.003)., Conclusion: Principal components analysis is a useful method to describe neonatal body composition and its determinants. Newborn adiposity is related to maternal nutritional status and parity, while newborn length is genetically determined. Further research is needed to understand mechanisms linking maternal pelvic size to fetal growth and the determinants and implications of the components (trunk v leg length) of fetal skeletal growth.