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Showing papers by "Rowett Research Institute published in 2014"


Journal ArticleDOI
TL;DR: When studied in a laboratory environment and EB was closely monitored, subjects under-reported their food intake and decreased the actual intake when they were aware that their intake was being monitored.
Abstract: Acknowledgements The present study was funded by the Food Standards Agency, UK. The Food Standards Agency had no role in the design, analysis or writing of this article. The authors’ responsibilities were as follows: R. J. S., L. M. O’R. and G. W. H. designed the research; L. M. O’R. and Z. F. conducted the research and analysed the data; G. W. H. performed the statistical analyses; P. R. carried out the DLW analysis; R. J. S. had primary responsibility for the final content; R. J. S., L. M. O’R., Z. F., S. W. and M. B. E. L. wrote the paper.

75 citations


Journal ArticleDOI
TL;DR: Exercise increases neural responses in reward-related regions of the brain in response to images of low-Calorie foods and suppresses activation during the viewing of high-calorie foods, associated with exercise-induced changes in peripheral signals related to appetite-regulation and hydration status.

59 citations


Journal ArticleDOI
TL;DR: The evolution of sophisticated differentiations of the gastro-intestinal tract enabled herbivorous mammals to digest dietary cellulose and hemicellulose with the aid of a complex anaerobic microbiota.

35 citations


Book ChapterDOI
01 Jan 2014
TL;DR: Dietary interventions designed to manipulate the microbiota (e.g. with probiotics or prebiotics) might provide approaches for controlling adiposity, weight and metabolic health.
Abstract: The microbial communities in our intestine have the potential to influence many aspects of our physiology via the production of metabolites, by fermenting dietary and host-derived substrates, and via interactions of microbial cells with host tissues. The possible impact of the gut microbiota upon obesity has been the subject of much intriguing research, but still remains to be clarified. While microbes contribute to the recovery of energy from the diet by fermenting otherwise non-digestible carbohydrates, it is not established that obese humans gain a greater proportion of their energy by this route than people of normal weight. In general, there is increasing evidence that the species composition of the gut microbiota in humans can be altered by dietary intake in the short- and long-term, and microbiota composition changes in individuals following weight-loss diets, or after bariatric surgery. Furthermore, experiments using rodents indicate that certain gut bacterial species may influence fat metabolism, energy intake and energy expenditure. This suggests that dietary interventions designed to manipulate the microbiota (e.g. with probiotics or prebiotics) might provide approaches for controlling adiposity, weight and metabolic health.

4 citations


Journal ArticleDOI
TL;DR: These findings support the evidence linking SGA with cardiovascular indicators, even very early in life, and demonstrate the feasibility and acceptability of measuring PWV in early infancy.
Abstract: Background In adults, pulse wave velocity (PWV) is regarded as a predictor of cardiovascular disease. 1 However, associations in infants are not well established. One study has linked neonatal aortic PWV, at 1–3 days, with birthweight and maternal blood pressure. 2 Aim To examine the relationship between infant brachio-femoral PWV and size at birth. Methods Baby VIP study recruited 362 newborn babies from the Leeds Teaching Hospitals Trust, including 64 small for gestational age (SGA) (18%). PWV was measured non-invasively from each baby at a follow-up home visit 2–6 weeks after recruitment, using the Vicorder kit. Birthweight and other covariables were collected from the delivery and antenatal medical notes. Individualised birthweight centiles were calculated using the GROW-Centile calculator taking into account maternal weight, height, parity, ethnicity, gestational age and baby’s sex. 3 Results Mean birthweight was 3329 g (standard deviation [sd] 632). Mean infant PWV was 6.7 m/s (sd 1.3). In univariable analysis, SGA babies had, on average, lower PWV by 0.4 m/s (95% confidence interval 0.0, 0.9, P = 0.04). This association persisted after adjusting for pregnancy factors including maternal smoking, pre-eclampsia, gestational diabetes, blood pressure at booking and 36 weeks, and infant factors including type of feeding, baby’s age, position and whether asleep or awake at the time of measurement (0.5 m/s lower, 0.1, 0.9, P = 0.02). Conclusion This study has demonstrated the feasibility and acceptability of measuring PWV in early infancy. SGA was associated with a lower PWV. These findings support the evidence linking SGA with cardiovascular indicators, even very early in life.

1 citations