Interdisciplinary data science to advance environmental health research and improve birth outcomes.

Autor: Stingone JA; Department of Epidemiology, Columbia University's Mailman School of Public Health, 722 West 168th St, Room 1608, New York, NY, 10032, USA. Electronic address: j.stingone@columbia.edu., Triantafillou S; Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA., Larsen A; Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA., Kitt JP; Departments of Chemistry and Biomedical Informatics, University of Utah, Salt Lake City, UT, USA., Shaw GM; Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA., Marsillach J; Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA.
Jazyk: angličtina
Zdroj: Environmental research [Environ Res] 2021 Jun; Vol. 197, pp. 111019. Date of Electronic Publication: 2021 Mar 15.
DOI: 10.1016/j.envres.2021.111019
Abstrakt: Rates of preterm birth and low birthweight continue to rise in the United States and pose a significant public health problem. Although a variety of environmental exposures are known to contribute to these and other adverse birth outcomes, there has been a limited success in developing policies to prevent these outcomes. A better characterization of the complexities between multiple exposures and their biological responses can provide the evidence needed to inform public health policy and strengthen preventative population-level interventions. In order to achieve this, we encourage the establishment of an interdisciplinary data science framework that integrates epidemiology, toxicology and bioinformatics with biomarker-based research to better define how population-level exposures contribute to these adverse birth outcomes. The proposed interdisciplinary research framework would 1) facilitate data-driven analyses using existing data from health registries and environmental monitoring programs; 2) develop novel algorithms with the ability to predict which exposures are driving, in this case, adverse birth outcomes in the context of simultaneous exposures; and 3) refine biomarker-based research, ultimately leading to new policies and interventions to reduce the incidence of adverse birth outcomes.
(Copyright © 2021 Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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