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Expanding the environmental scope: an environment-wide association study for mental well-being

BACKGROUND: Identifying modifiable factors associated with well-being is of increased interest for public policy guidance. Developments in record linkage make it possible to identify what contributes to well-being from a myriad of factors. To this end, we link two large-scale data resources; the Geo...

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Detalles Bibliográficos
Autores principales: van de Weijer, Margot P., Baselmans, Bart M. L., Hottenga, Jouke-Jan, Dolan, Conor V., Willemsen, Gonneke, Bartels, Meike
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8920882/
https://www.ncbi.nlm.nih.gov/pubmed/34127788
http://dx.doi.org/10.1038/s41370-021-00346-0
Descripción
Sumario:BACKGROUND: Identifying modifiable factors associated with well-being is of increased interest for public policy guidance. Developments in record linkage make it possible to identify what contributes to well-being from a myriad of factors. To this end, we link two large-scale data resources; the Geoscience and Health Cohort Consortium, a collection of geo-data, and the Netherlands Twin Register, which holds population-based well-being data. OBJECTIVE: We perform an Environment-Wide Association Study (EnWAS), where we examine 139 neighbourhood-level environmental exposures in relation to well-being. METHODS: First, we performed a generalized estimation equation regression (N = 11,975) to test for the effects of environmental exposures on well-being. Second, to account for multicollinearity amongst exposures, we performed principal component regression. Finally, using a genetically informative design, we examined whether environmental exposure is driven by genetic predisposition for well-being. RESULTS: We identified 21 environmental factors that were associated with well-being in the domains: housing stock, income, core neighbourhood characteristics, livability, and socioeconomic status. Of these associations, socioeconomic status and safety are indicated as the most important factors to explain differences in well-being. No evidence of gene-environment correlation was found. SIGNIFICANCE: These observed associations, especially neighbourhood safety, could be informative for policy makers and provide public policy guidance to improve well-being. Our results show that linking databases is a fruitful exercise to identify determinants of mental health that would remain unknown by a more unilateral approach.