Approved research

DYNAMO - DailY Nutrition, Muscle Mass and MObility and in an Ageing Population

Lay summary

This project intends to investigate the associations between everyday nutrition and physiological outcomes, and the subsequent associations with maintaining health in an ageing population. Specifically we intend to examine the nutritional composition of respondents? reported diet and to ascertain to what degree this correlates to body composition measures, including muscle mass and strength, bone density and also cognitive function. We will then relate these physiological measures to reported health outcomes, and investigate the extent to which this relationship varies with the age distribution, socio-economic indicators, such as income and educational attainment and engagement with preventive health services (e.g. cancer screening). To our knowledge this will be the first interdisciplinary study to examine the associations between nutrition/diet, physical outcomes, socio-economic characteristics, ageing and preventive health service engagement using the data drawn from the UK Biobank. The project may yield insights important to public policy formation by providing the evidence base for nutritional guidelines and advice specific to older adults. The project also has the potential to inform the Healthy Ageing in Scotland (HAGIS) study, based at the University of Stirling, in regard to developing questions for a dedicated diet and physical activity module. In the research project we will perform secondary data analysis using a dataset drawn from existing variables in the UK Biobank study. We will first calculate the nutritional composition, in terms of percentage protein, fats, carbohydrates etc, of each respondent?s average weekly diet. We will then use statistical techniques, such as regression analysis, to examine the associations between a) nutritional composition and physiological outcomes; b) physiological outcomes and health behaviours; and c) nutritional composition and healthy life indicators. The focus of our analysis will be how these associations vary along dimensions such as age, gender, socio-economic indicators and cognitive function. Full cohort