Periodic Reporting for period 2 - WELL-BEING (The dynamics underlying Well-being; Understanding the Exposome-Genome interplay)
Reporting period: 2019-12-01 to 2021-05-31
In this project, I will cross disciplinary boundaries to initiate the urgently needed integration of multiple layers of influence in the study of WB.
The key objectives are to
(1) identify, quantify, and integrate static and dynamic environmental and social exposures to build the well-being exposome,
(2) understand the multi-layer interplay of the genome, the epigenome, and the exposome, and
(3) integrate the empirical findings into a novel comprehensive framework of WB.
I will employ an interdisciplinary approach, using association, real-life, and network methodology to assess the dynamics underling WB. To apply these state-of-the-art techniques, I will bring together publically available data, longitudinal twin-family data, molecular genetic data, and big data from satellite positioning (GPS), bluetooth beacons, geographical information systems (GIS), ambulatory assessment, and social network linkage. This project will mark a shift in scientific approach and enables the development of interdisciplinary academic theories and health, social, and economic policies to maintain, facilitate, and build WB to withstand our demanding and rapidly changing world.
A large and growing body of literature has investigated the potential environmental correlates of well-being. Most studies, though, are based on a pick and choice approach with respect to the environmental variables under study. We applied a pre-registered data-driven, hypothesis-free approach to investigate associations between well-being and 146 environmental correlates. Well-being and postal-code based environmental data were available for over 7000 individuals from a Dutch population-based sample. With this novel environment-wide association approach, we identified 23 associations with well-being that fall in the following 6 domains: housing stock, income, key figures, livability, population and households, and SES scores. There is no evidence for gene-environment correlation indicating that exposure to the environmental correlates is independent of an individual’s genetic predisposition for well-being. We conclude that, at the postal-code level, the most important correlates of well-being are socioeconomic factors. Our results show that effects of the environmental correlates are small, and we recommend that combining small environmental effects is necessary to develop more personalized prevention and intervention strategies for well-being.
Project 2: The lingonome for wellbeing
One promisingly way to assess mental health is via the language individuals use. Within this project we are setting up a study to investigate social media language in a genetically informative design. We will invite twin-families to share there social media logins. We applied for and obtained approval of the Medical Ethical Committee at the VU medical center and the Ethical Review Board (VCWE) of the faculty of Behavior and Movement Sciences. The data will be collected over the coming year.
Project 3: Ecological momentary assessment of Wellbeing
Feelings of well-being and happiness fluctuate over time and contexts. Ecological Momentary Assessment (EMA) studies can capture fluctuations, momentary behavior, and experiences by assessing these multiple times per day. Traditionally, EMA was performed using pen and paper. Recently, due to technological advances EMA studies can be easier conducted with smartphones, a device ubiquitous present in our society. The goal of this review was to evaluate the literature on smartphone-based EMA in well-being (WB) research in healthy subjects.
The systematic review was conducted according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. Searching PubMed and Web of Science, we identified 47 studies using smartphone-based EMA of well-being. Studies were heterogeneous in designs, context, and measures. The average study duration was 14.2 days, with well-being assessed 2-12 times per day. Half of the studies included objective data (e.g. location). Only 42.5% reported compliance, indicating a mean of 71.5%. Momentary well-being fluctuated daily and weekly, with higher well-being in evenings and weekends. These fluctuations disappeared when location and activity were included. On average, being in a natural environment and physical activity relates to higher well-being. Working relates to lower well-being, but workplace and company influence well-being.
Smartphone-based EMA research is feasible to gain insight in WB fluctuations and its determinants. Most studies currently focus on group comparisons, while studies on (causes of) individual differences in well-being patterns and fluctuations are largely lacking. Based on the findings, we provide recommendations for future EMA research regarding measures, objective data and analyses.
the next step in this project is to finalize our protocol for a wellbeing EMA study in twins.
The details of each of these projects can be found under achievement, where I in detail describe the current status and the achievements so far