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.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8920882 | PMC |
http://dx.doi.org/10.1038/s41370-021-00346-0 | DOI Listing |
Sci Adv
November 2024
School of Data Science, Fudan University, Shanghai, China.
Cancer
January 2025
Department of Urology, Stanford University School of Medicine, Stanford, California, USA.
Background: Prostate cancer is the most common cancer among men in the United States, yet modifiable risk factors remain elusive. In this study, the authors investigated the potential role of agricultural pesticide exposure in prostate cancer incidence and mortality.
Methods: For this environment-wide association study (EWAS), linear regression was used to analyze county-level associations between the annual use of 295 distinct pesticides (measured in kg per county) and prostate cancer incidence and mortality rates in the contiguous United States.
Transl Psychiatry
October 2024
Department of Nephrology and Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
Sci Rep
September 2024
Institute for Biomedical Informatics, Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Sex and gender differences play a crucial role in health and disease outcomes. This study used data from the National Health and Nutrition Examination Survey to explore how environmental exposures affect health-related traits differently in males and females. We utilized a sex-stratified phenomic environment-wide association study (PheEWAS), which allowed the identification of associations across a wide range of phenotypes and environmental exposures.
View Article and Find Full Text PDFChemosphere
September 2024
Institute of Precision Medicine, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China; Department of Gastroenterology and Hepatology, UMCG, University of Groningen, Groningen, the Netherlands. Electronic address:
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