Genetic and biological drivers of physical activity and exercise participation (GEDROPA)

We will investigate how an individual's genetic background and biological mechanisms explain their engagement in physical activity and lifestyle interventions across age groups. Our aim is to find out why some people choose a health-promoting physically active lifestyle and others do not.
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Table of contents

Project duration
-
Core fields of research
Physical activity, health and wellbeing
Research areas
Well-being, health and physical activity (CIBR)
JYU.Well
Active ageing and care
Physical activity through life span
Behaviour change, health, and well-being across the lifespan
Physical activity, wellbeing and behaviour change across the life-span
Molecular mechanisms of exercise and health
Active aging
Faculty
Faculty of Sport and Health Sciences
Funding
Juho Vainio Foundation

Project description

Genetics is one of the most important factors explaining physical activity. Twin studies suggest that genes account for around 30-60% of the observed behaviour. The basis for the genetic regulation of physical activity behaviour is strong, going back to human evolution and the selection of traits that have contributed to survival in a world of limited resources. Due to methodological shortcomings, it has not been possible to study earlier the variation between individuals in this phenomenon and to explain why some are more active than others. Genetics may also explain why some people develop physical fitness more easily than others, or experience more pleasure from physical activity.

It is important to study the influence of genetics on the choice of a physically active lifestyle, as there is a risk that health-promoting activities will only activate those who are naturally active or who derive exceptional benefits from physical activity. This may even lead to an increase in health inequalities in the population. Only recent methodological and data infrastructure breakthroughs have enabled the study of genome-wide variation in individuals and physical activity at the population level. We use previously untapped large biobank datasets and their accelerometer-measured and self-reported physical activity data. We also make use of longitudinal lifestyle intervention studies in Finns of different ages.