Flagship

Summary

Lifestyle factors such as physical activity, diet and sleep are crucial for an individual’s health throughout life. To ensure lifestyle interventions are more successful at improving health, an individual-based approach should be adopted, taking into account an individual’s diverse and changing characteristics, such as life stage and socio-economic status, and their attributes such as personal goals and preferences.

The overall objective of ALIVE is to contribute to the development of more effective, individual-based lifestyle interventions by establishing a research infrastructure, by focusing on individual characteristics and attributes across the lifecourse, and by developing strategies to improve existing interventions in order to maintain and/or acquire health. As combined knowledge, technologies and resources across academic disciplines are needed to achieve this objective, ALIVE is a collaboration of TU Delft, Erasmus MC and Erasmus University. Although our long-term aim is to provide the tools to improve any type of health, we will focus on brain and mental health within the first 5 years, creating transferable knowledge, skills and a research infrastructure.

Our aims are to:

1. Create a data science network to collect, combine and provide data to support cross-study (e.g., cohorts, registries, national databases) and multidisciplinary research collaborations.

2. Develop new and improve existing quantification methods for lifestyle behaviors across individuals using state-of-the-art device-employed measures to more precisely estimate associations with health.

3. Unravel the multidimensional interactions between lifestyle and their effects on maintaining and acquiring health across individuals over the lifecourse.

4. Design tools to identify individual attributes, such as personal goals and preferences regarding optimal health and lifestyle, as well as tools to address those attributes in health interventions.

5. (Re-)evaluate existing interventions and policies using a novel individual-based approach and new (combinations of) data to develop recommendations, guidelines for practitioners, and applications across health care and policy.