Early environmental quality and life-course mental health effects
The Equal-Life project
Irene Van Kamp (Rijksinstituut voor Volksgezondheid en Milieu (RIVM))
Kerstin Persson Waye (University of Gothenburg)
Katja Kanninen (University of Eastern Finland - Kuopio Campus)
John Gulliver (University of Leicester)
A. Bozzon (TU Delft - Human-Centred Artificial Intelligence)
A. Psyllidis (TU Delft - Knowledge and Intelligence Design)
Hendriek Boshuizen (Rijksinstituut voor Volksgezondheid en Milieu (RIVM))
Jenny Selander (Karolinska Institutet)
Peter van den Hazel (International Network on Children’s Health, Environment and Safety)
Marco Brambilla (Politecnico di Milano)
undefined More Authors (External organisation)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
Background:
There is increasing evidence that a complex interplay of factors within environments in which children grows up, contributes to children’s suboptimal mental health and cognitive development. The concept of the life-course exposome helps to study the impact of the physical and social environment, including social inequities, on cognitive development and mental health over time.
Methods:
Equal-Life develops and tests combined exposures and their effects on children’s mental health and cognitive development. Data from eight birth-cohorts and three school studies (N = 240.000) linked to exposure data, will provide insights and policy guidance into aspects of physical and social exposures hitherto untapped, at different scale levels and timeframes, while accounting for social inequities. Reasoning from the outcome point of view, relevant stakeholders participate in the formulation and validation of research questions, and in the formulation of environmental hazards. Exposure assessment combines GIS-based environmental indicators with omics approaches and new data sources, forming the early-life exposome. Statistical tools integrate data at different spatial and temporal granularity and combine exploratory machine learning models with hypothesis-driven causal modeling.
Conclusions:
Equal-Life contributes to the development and utilization of the exposome concept by (1) integrating the internal, physical and social exposomes, (2) studying a distinct set of life-course effects on a child’s development and mental health (3) characterizing the child’s environment at different developmental stages and in different activity spaces, (4) looking at supportive environments for child development, rather than merely pollutants, and (5) combining physical, social indicators with novel effect markers and using new data sources describing child activity patterns and environments.
help_outline