Abstract
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.
Highlights
Since the release of the Secretary’s Task Force Report on Black and Minority Health [1] the health disparities burden borne by racial/ethnic and other underserved populations has shown little improvement.Since 2003, Blacks have shown no significant change in disparities compared to Whites on 60 of the 73 measures of health care quality and access tracked and measured by the Agency for HealthcareResearch and Quality [2], while for two, disparities increased
A glossary of trans-disciplinary terms is presented in Appendix 1. The objectives of this manuscript are to: (1) present the public health exposome as an integrated model for examining exogenous and endogenous source-exposure-disease relationships across the life cycle and the influence of those relationships on health disparities at a population level; (2) describe the public health exposome database, a 30-year, longitudinal repository that integrates health and environmental databases; (3) provide an overview of the transdisciplinary methods and analytics we have developed to help unravel the complex interactions between environmental stressors and bio-psycho-social systems at the individual, community, and social-ecological systems levels, as those relate to personal health and population level disparities; (4) discuss the use of emergent sources of exposure data and the interface with bioinformatics and community engagement; and
We have found it advantageous to apply multiple types of analytics to address the complex relationships between environmental exposures and health disparities
Summary
Since the release of the Secretary’s Task Force Report on Black and Minority Health [1] the health disparities burden borne by racial/ethnic and other underserved populations has shown little improvement. The Center engaged a transdisciplinary group of investigators representing a broad array of disciplines and skills, including: (1) the physical, built, social and policy environments; (2) health disparities content areas; (3) a range of statistical models and analytic techniques including multi-level analysis, predictive modeling, spatial analysis, and graph theory/combinatorial analysis to analyze the complex relationships between health disparities and environmental factors; (4) bioinformatics, and (5) decision support tools for engaging community members in the research process, including data collection This new approach has implications for how we conceptualize health disparities and conduct health disparities research, and for strategies to improve health outcomes and eliminate disparities in vulnerable subpopulations. (4) discuss the use of emergent sources of exposure data and the interface with bioinformatics and community engagement; and (5) examine the implications of the public health exposome paradigm for future health disparities research
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