The Public Health Exposome: A Population-Based, Exposure Science Approach to Health Disparities Research

Paul D. Juarez,Patricia Matthews-Juarez, Darryl B. Hood, Wansoo Im, Robert S. Levine, Barbara J. Kilbourne, Michael A. Langston, Mohammad Z. Al-Hamdan, William L. Crosson, Maurice G. Estes, Sue M. Estes, Vincent K. Agboto, Paul Robinson, Sacoby Wilson and Maureen Y. Lichtveld

Int. J. Environ. Res. Public Health 2014, 11(12), 12866-12895
Published: 11 December 2014

Abstract / Resumen:

The lack of progress in reducing health disparities suggests that new approaches are needed if we are to achieve meaningful, equitable, and lasting reductions. Current scientific paradigms do not adequately capture the complexity of the relationships between environment, personal health and population level disparities. The public health exposome is presented as a universal exposure tracking framework for integrating complex relationships between exogenous and endogenous exposures across the lifespan from conception to death. It uses a social-ecological framework that builds on the exposome paradigm for conceptualizing how exogenous exposures “get under the skin”. The public health exposome approach has led our team to develop a taxonomy and bioinformatics infrastructure to integrate health outcomes data with thousands of sources of exogenous exposure, organized in four broad domains: natural, built, social, and policy environments. With the input of a transdisciplinary team, we have borrowed and applied the methods, tools and terms from various disciplines to measure the effects of environmental exposures on personal and population health outcomes and disparities, many of which may not manifest until many years later. As is customary with a paradigm shift, this approach has far reaching implications for research methods and design, analytics, community engagement strategies, and research training.

Keywords / Palabras-clave: Exposome; public health; health disparities; trans-disciplinary; exposure science; social-ecological; combinatorial analysis; CBPR; geographical information systems; PPGIS

 Language Idioma: English

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