Abstract

BackgroundIdentifying 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.ObjectiveWe perform an Environment-Wide Association Study (EnWAS), where we examine 139 neighbourhood-level environmental exposures in relation to well-being.MethodsFirst, 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.ResultsWe 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.SignificanceThese 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.

Highlights

  • Demographic factors are widely recognized as important for people’s functioning and mental health

  • While it was previously assumed that the higher schizophrenia prevalence was explained by increased environmental stress in urbanized areas, this study revealed that part of why schizophrenia is more prevalent in cities is because of an increased genetic predisposition [10]

  • Polygenic risk score analysis The well-being spectrum polygenic score predicted well-being in our sample (R2 = 0.007, P = 5.11 × 10−12), but it did not predict any of the environmental correlates (Table 4)

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Summary

Introduction

Demographic factors are widely recognized as important for people’s functioning and mental health. Research into urbanization and schizophrenia showed that individuals with a higher genetic predisposition to schizophrenia tend to live in urbanized areas. Research into urbanization and schizophrenia showed that individuals with increased genetic predisposition for schizophrenia tend to live in more urbanized areas. OBJECTIVE: We perform an Environment-Wide Association Study (EnWAS), where we examine 139 neighbourhood-level environmental exposures in relation to 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. 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

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