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

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          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.

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          Advances in fields of inquiry as diverse as neuroscience, molecular biology, genomics, developmental psychology, epidemiology, sociology, and economics are catalyzing an important paradigm shift in our understanding of health and disease across the lifespan. This converging, multidisciplinary science of human development has profound implications for our ability to enhance the life prospects of children and to strengthen the social and economic fabric of society. Drawing on these multiple streams of investigation, this report presents an ecobiodevelopmental framework that illustrates how early experiences and environmental influences can leave a lasting signature on the genetic predispositions that affect emerging brain architecture and long-term health. The report also examines extensive evidence of the disruptive impacts of toxic stress, offering intriguing insights into causal mechanisms that link early adversity to later impairments in learning, behavior, and both physical and mental well-being. The implications of this framework for the practice of medicine, in general, and pediatrics, specifically, are potentially transformational. They suggest that many adult diseases should be viewed as developmental disorders that begin early in life and that persistent health disparities associated with poverty, discrimination, or maltreatment could be reduced by the alleviation of toxic stress in childhood. An ecobiodevelopmental framework also underscores the need for new thinking about the focus and boundaries of pediatric practice. It calls for pediatricians to serve as both front-line guardians of healthy child development and strategically positioned, community leaders to inform new science-based strategies that build strong foundations for educational achievement, economic productivity, responsible citizenship, and lifelong health.
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            Multilevel analyses of neighbourhood socioeconomic context and health outcomes: a critical review.

            Interest in the effects of neighbourhood or local area social characteristics on health has increased in recent years, but to date the existing evidence has not been systematically reviewed. Multilevel or contextual analyses of social factors and health represent a possible reconciliation between two divergent epidemiological paradigms-individual risk factor epidemiology and an ecological approach. Keyword searching of Index Medicus (Medline) and additional references from retrieved articles. All original studies of the effect of local area social characteristics on individual health outcomes, adjusted for individual socioeconomic status, published in English before 1 June 1998 and focused on populations in developed countries. The methodological challenges posed by the design and interpretation of multilevel studies of local area effects are discussed and results summarised with reference to type of health outcome. All but two of the 25 reviewed studies reported a statistically significant association between at least one measure of social environment and a health outcome (contextual effect), after adjusting for individual level socioeconomic status (compositional effect). Contextual effects were generally modest and much smaller than compositional effects. The evidence for modest neighbourhood effects on health is fairly consistent despite heterogeneity of study designs, substitution of local area measures for neighbourhood measures and probable measurement error. By drawing public health attention to the health risks associated with the social structure and ecology of neighbourhoods, innovative approaches to community level interventions may ensue.
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              Bringing context back into epidemiology: variables and fallacies in multilevel analysis.

              A large portion of current epidemiologic research is based on methodologic individualism: the notion that the distribution of health and disease in populations can be explained exclusively in terms of the characteristics of individuals. The present paper discusses the need to include group- or macro-level variables in epidemiologic studies, thus incorporating multiple levels of determination in the study of health outcomes. These types of analyses, which have been called contextual or multi-level analyses, challenge epidemiologists to develop theoretical models of disease causation that extend across levels and explain how group-level and individual-level variables interact in shaping health and disease. They also raise a series of methodological issues, including the need to select the appropriate contextual unit and contextual variables, to correctly specify the individual-level model, and, in some cases, to account for residual correlation between individuals within contexts. Despite its complexities, multilevel analysis holds potential for reemphasizing the role of macro-level variables in shaping health and disease in populations.
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                Author and article information

                Contributors
                Role: External Editor
                Role: External Editor
                Role: External Editor
                Role: External Editor
                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                11 December 2014
                December 2014
                : 11
                : 12
                : 12866-12895
                Affiliations
                [1 ]Research Center on Health Disparities, Equity, and the Exposome, University of Tennessee Health Science Center, 66 N. Pauline, Memphis, TN 38105, USA; E-Mail: pmatthe3@ 123456uthsc.edu
                [2 ]Department of Environmental Health Sciences, College of Public Health, Ohio State University, Columbus, OH 43210, USA; E-Mail: hood.188@ 123456osu.edu
                [3 ]Vertices, Inc., 317 George Street 411, New Brunswick, NJ 08901, USA; E-Mail: wansooim@ 123456gmail.com
                [4 ]Department of Family & Community Medicine, Meharry Medical College, Nashville, TN 37208, USA; E-Mails: rlevine@ 123456mmc.edu (R.S.L.); vagboto@ 123456mmc.edu (V.K.A.)
                [5 ]Department of Sociology, Tennessee State University, Nashville, TN 37209, USA; E-Mail: bkilbourne@ 123456tnstate.edu
                [6 ]Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA; E-Mail: langston@ 123456eecs.utk.edu
                [7 ]National Space Science and Technology Center, Universities Space Research Association, NASA Marshall Space Flight Center, Huntsville, AL 35805, USA; E-Mails: mohammad.alhamdan@ 123456nasa.gov (M.Z.A.); bill.crosson@ 123456nasa.gov (W.L.C.); maury.estes@ 123456nsstc.uah.edu (M.G.E.); sue.m.estes@ 123456nasa.gov (S.M.E.)
                [8 ]National Space Science and Technology Center, University of Alabama, Huntsville, AL 35805, USA; E-Mail: maury.estes@ 123456nsstc.uah.edu
                [9 ]Department of Ophthalmology, Charles R. Drew University of Medicine and Science, Los Angeles, CA 90059, USA; E-Mail: paulrobinson@ 123456cdrewu.edu
                [10 ]Maryland Institute for Applied Environmental Health, School of Public Health, University of Maryland, College Park, MA 20742, USA; E-Mail: swilson2@ 123456umd.edu
                [11 ]Department of Global Environmental Health Sciences, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, New Orleans, LA 70112, USA; E-Mail: mlichtve@ 123456tulane.edu
                Author notes
                [†]

                These authors contributed equally to this work.

                [* ]Author to whom correspondence should be addressed; E-Mail: pjuarez@ 123456uthsc.edu ; Tel.: +1-901-448-2016.
                Article
                ijerph-11-12866
                10.3390/ijerph111212866
                4276651
                25514145
                bff33224-9a9b-4bba-b66e-a97dd3f4b04d
                © 2014 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 29 August 2014
                : 12 November 2014
                : 27 November 2014
                Categories
                Concept Paper

                Public health
                exposome,public health,health disparities,trans-disciplinary,exposure science,social-ecological,combinatorial analysis,cbpr,geographical information systems,ppgis

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