Physical activity for future mental health

There is no doubt about the importance of mental health and, thus, several factors which could positively influence mental health have been studied. Physical activity is one of the most important contributors to mental health as it was shown that only little of it can improve our wellbeing. Physical activity is especially relevant in critical periods of mental health, such as in adolescence and young adulthood. Several studies have focused on total physical activity, light physical activity and on higher- intensity activities, also called moderate-to-vigorous physical activity. Some of these studies tried to find the link between the intensity of physical activity and anxiety and depressive symptoms. Unfortunately, there are only few longitudinal studies with robust measures of physical activity, such as accelerometers, available. Another problem is the complexity of the intensity information. Several highly inter-related variables are obtained by the accelerometer. This inter-relationship causes the problem that traditional statistical models cannot handle these variables. This leads to the major limitation that only broad intensity categories of physical activity, such as moderate- to-vigorous, are analyzed. A novel approach to tackle this problem is multivariate pattern analysis, which is often applied in other fields such as metabolomics. This analysis can handle many highly related variables and will help us to use data from the accelerometer more appropriately. Using this approach, we will be able to use more of the intensity information of physical activity. In fact, categories of both higher- and lower-intensity will be considered at the same time. Moreover, we can determine which intensity of physical activity is strongest related to mental health outcomes. This knowledge would be relevant for future physical activity guidelines, clinical practice and health promotion. Multivariate pattern analysis was first applied in physical activity research in 2018 but has never been used to study associations with mental health. In this project, we will use multivariate pattern analysis to study the longitudinal associations between physical activity, measured by the accelerometer, and anxiety and depressive symptoms in adolescents and young adults. For this, we will analyze data from one of the largest birth cohort studies worldwide, namely the Avon Longitudinal Study of Parents and Children (ALSPAC).