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Introduction: Carbohydrate intake and physical activity are related to glucose homeostasis, both being influenced by individual genetic makeup. However, the interactions between these 2 factors, as affected by genetics, on glycaemia have been scarcely reported. Objective: We focused on analysing the interplay between carbohydrate intake and physical activity levels on blood glucose, taking into account a genetic risk score (GRS), based on SNPs related to glucose/energy metabolism. Methods: A total of 1,271 individuals from the Food4Me cohort, who completed the nutritional intervention, were evaluated at baseline. We collected dietary information by using an online-validated food frequency questionnaire, a questionnaire on physical activity, blood biochemistry by analysis of dried blood spots, and by analysis of selected SNPs. Fifteen out of 31 SNPs, with recognized participation in carbohydrate/energy metabolism, were included in the component analyses. The GRS included risk alleles involved in the control of glycaemia or energy-yielding processes. Results: Data concerning anthropometric, clinical, metabolic, dietary intake, physical activity, and genetics related to blood glucose levels showed expected trends in European individuals of comparable sex and age, being categorized by lifestyle, BMI, and energy/carbohydrate intakes, in this Food4Me population. Blood glucose was inversely associated with physical activity level (β = −0.041, p = 0.013) and positively correlated with the GRS values (β = 0.015, p = 0.047). Interestingly, an interaction affecting glycaemia, concerning physical activity level with carbohydrate intake, was found (β = −0.060, p = 0.033), which also significantly depended on the genetic background (GRS). Conclusions: The relationships of carbohydrate intake and physical activity are important in understanding glucose homeostasis, where a role for the genetic background should be ascribed.

BACKGROUND: National guidelines emphasize healthy eating to promote wellbeing and prevention of non-communicable diseases. The perceived healthiness of food is determined by many factors affecting food intake. A positive perception of healthy eating has been shown to be associated with greater diet quality. Internet-based methodologies allow contact with large populations. Our present study aims to design and evaluate a short nutritional perception questionnaire, to be used as a screening tool for assessing nutritional status, and to predict an optimal level of personalisation in nutritional advice delivered via the Internet. METHODS: Data from all participants who were screened and then enrolled into the Food4Me proof-of-principle study (n = 2369) were used to determine the optimal items for inclusion in a novel screening tool, the Nutritional Perception Screening Questionnaire-9 (NPSQ9). Exploratory and confirmatory factor analyses were performed on anthropometric and biochemical data and on dietary indices acquired from participants who had completed the Food4Me dietary intervention (n = 1153). Baseline and intervention data were analysed using linear regression and linear mixed regression, respectively. RESULTS: A final model with 9 NPSQ items was validated against the dietary intervention data. NPSQ9 scores were inversely associated with BMI (β = -0.181, p < 0.001) and waist circumference (Β = -0.155, p < 0.001), and positively associated with total carotenoids (β = 0.198, p < 0.001), omega-3 fatty acid index (β = 0.155, p < 0.001), Healthy Eating Index (HEI) (β = 0.299, p < 0.001) and Mediterranean Diet Score (MDS) (β = 0. 279, p < 0.001). Findings from the longitudinal intervention study showed a

BACKGROUND: Sarcopenia seems to be attributed to a blunted muscle protein synthetic response to food intake and exercise. This blunted response could be the result of impaired protein digestion and absorption kinetics and lead to lower postprandial plasma amino acid availability. OBJECTIVE: The objective was to compare in vivo dietary protein digestion and absorption kinetics and subsequent postprandial muscle protein synthesis rates at rest and after exercise between young and elderly men. DESIGN: Young and elderly men consumed a 20-g bolus of intrinsically L-[1-(13)C]phenylalanine-labeled protein at rest or after exercise. Continuous infusions with L-[ring-(2)H(5)]phenylalanine were applied, and blood and muscle samples were collected to assess in vivo protein digestion and absorption kinetics and subsequent postprandial muscle protein synthesis rates. RESULTS: Exogenous phenylalanine appearance rates expressed over time did not differ between groups. No differences were observed in plasma phenylalanine availability between the young (51 ± 2%) and elderly (51 ± 1%) men or between the rest (52 ± 1%) and exercise (49 ± 1%) conditions. Muscle protein synthesis rates calculated from the oral tracer were 0.0620 ± 0.0065%/h and 0.0560 ± 0.0039%/h for the rest condition and 0.0719 ± 0.0057%/h and 0.0727 ± 0.0040%/h for the exercise condition in young and elderly men, respectively (age effect: P = 0.62; exercise effect: P < 0.05; interaction of age and exercise: P = 0.52). CONCLUSIONS: Dietary protein digestion and absorption kinetics are not impaired after exercise or at an older age. Exercising before protein intake allows for a greater use of dietary protein-derived amino acids for de novo muscle protein synthesis in both young and elderly men. This trial was registered at clinicaltrials.gov as NCT00557388.

Objective The aim of the EC Concerted Action PASSCLAIM was to develop a set of methods and procedures for assessing the scientific support for function-enhancing and health-related claims for foods and food components. This paper presents a critical review of the existing methods to evaluate the different aspects of physical performance and fitness needed to support claims on foods and food ingredients intended to enhance specific physiological functions. Design and Results Based on an inventory of labelling claims on available sport nutrition products, seven physiological functions in the field of physical performance and fitness were identified: 1) strength and power, 2) endurance, energy supply and recovery, 3) hydration/re-hydration, 4) flexibility, 5) tissue growth, 6) free radical scavenger capacity and 7) immune function. For each function the existing methodology was reviewed critically and judged on suitability to generate scientific support for physiological function claims on foods. Conclusions A database of methods including advantages and disadvantages of use has been generated for considering the scientific support of claims on foods and food ingredients relating to physical performance and fitness. It will contribute to the formulations of guidelines for assessing the scientific support of enhanced function or reduced disease risk claims on foods.