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Carlin DJ, Rider CV. Combined Exposures and Mixtures Research: An Enduring NIEHS Priority. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:75001. [PMID: 38968090 PMCID: PMC11225971 DOI: 10.1289/ehp14340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 04/25/2024] [Accepted: 06/12/2024] [Indexed: 07/07/2024]
Abstract
BACKGROUND The National Institute of Environmental Health Sciences (NIEHS) continues to prioritize research to better understand the health effects resulting from exposure to mixtures of chemical and nonchemical stressors. Mixtures research activities over the last decade were informed by expert input during the development and deliberations of the 2011 NIEHS Workshop "Advancing Research on Mixtures: New Perspectives and Approaches for Predicting Adverse Human Health Effects." NIEHS mixtures research efforts since then have focused on key themes including a) prioritizing mixtures for study, b) translating mixtures data from in vitro and in vivo studies, c) developing cross-disciplinary collaborations, d) informing component-based and whole-mixture assessment approaches, e) developing sufficient similarity methods to compare across complex mixtures, f) using systems-based approaches to evaluate mixtures, and g) focusing on management and integration of mixtures-related data. OBJECTIVES We aimed to describe NIEHS driven research on mixtures and combined exposures over the last decade and present areas for future attention. RESULTS Intramural and extramural mixtures research projects have incorporated a diverse array of chemicals (e.g., polycyclic aromatic hydrocarbons, botanicals, personal care products, wildfire emissions) and nonchemical stressors (e.g., socioeconomic factors, social adversity) and have focused on many diseases (e.g., breast cancer, atherosclerosis, immune disruption). We have made significant progress in certain areas, such as developing statistical methods for evaluating multiple chemical associations in epidemiology and building translational mixtures projects that include both in vitro and in vivo models. DISCUSSION Moving forward, additional work is needed to improve mixtures data integration, elucidate interactions between chemical and nonchemical stressors, and resolve the geospatial and temporal nature of mixture exposures. Continued mixtures research will be critical to informing cumulative impact assessments and addressing complex challenges, such as environmental justice and climate change. https://doi.org/10.1289/EHP14340.
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Affiliation(s)
- Danielle J. Carlin
- Division of Extramural Research and Training, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA
| | - Cynthia V. Rider
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA
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Manning ER, Duan Q, Taylor S, Ray S, Corley AMS, Michael J, Gillette R, Unaka N, Hartley D, Beck AF, Brokamp C. Development of a multimodal geomarker pipeline to assess the impact of social, economic, and environmental factors on pediatric health outcomes. J Am Med Inform Assoc 2024; 31:1471-1478. [PMID: 38733117 PMCID: PMC11187418 DOI: 10.1093/jamia/ocae093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 03/05/2024] [Accepted: 04/15/2024] [Indexed: 05/13/2024] Open
Abstract
OBJECTIVES We sought to create a computational pipeline for attaching geomarkers, contextual or geographic measures that influence or predict health, to electronic health records at scale, including developing a tool for matching addresses to parcels to assess the impact of housing characteristics on pediatric health. MATERIALS AND METHODS We created a geomarker pipeline to link residential addresses from hospital admissions at Cincinnati Children's Hospital Medical Center (CCHMC) between July 2016 and June 2022 to place-based data. Linkage methods included by date of admission, geocoding to census tract, street range geocoding, and probabilistic address matching. We assessed 4 methods for probabilistic address matching. RESULTS We characterized 124 244 hospitalizations experienced by 69 842 children admitted to CCHMC. Of the 55 684 hospitalizations with residential addresses in Hamilton County, Ohio, all were matched to 7 temporal geomarkers, 97% were matched to 79 census tract-level geomarkers and 13 point-level geomarkers, and 75% were matched to 16 parcel-level geomarkers. Parcel-level geomarkers were linked using our exact address matching tool developed using the best-performing linkage method. DISCUSSION Our multimodal geomarker pipeline provides a reproducible framework for attaching place-based data to health data while maintaining data privacy. This framework can be applied to other populations and in other regions. We also created a tool for address matching that democratizes parcel-level data to advance precision population health efforts. CONCLUSION We created an open framework for multimodal geomarker assessment by harmonizing and linking a set of over 100 geomarkers to hospitalization data, enabling assessment of links between geomarkers and hospital admissions.
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Affiliation(s)
- Erika Rasnick Manning
- Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States
| | - Qing Duan
- Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States
| | - Stuart Taylor
- Office of Population Health, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States
| | - Sarah Ray
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45219, United States
| | - Alexandra M S Corley
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45219, United States
- Division of General and Community Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States
| | - Joseph Michael
- James M Anderson Center for Health Systems Excellence, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States
| | - Ryan Gillette
- Office of Population Health, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States
| | - Ndidi Unaka
- Office of Population Health, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45219, United States
- Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States
| | - David Hartley
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45219, United States
- James M Anderson Center for Health Systems Excellence, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States
| | - Andrew F Beck
- Office of Population Health, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45219, United States
- Division of General and Community Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States
- James M Anderson Center for Health Systems Excellence, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States
- Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States
- Michael Fisher Child Health Equity Center, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States
| | - Cole Brokamp
- Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45219, United States
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Kingsbury C, Buzzi M, Chaix B, Kanning M, Khezri S, Kiani B, Kirchner TR, Maurel A, Thierry B, Kestens Y. STROBE-GEMA: a STROBE extension for reporting of geographically explicit ecological momentary assessment studies. Arch Public Health 2024; 82:84. [PMID: 38867286 PMCID: PMC11170886 DOI: 10.1186/s13690-024-01310-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 05/16/2024] [Indexed: 06/14/2024] Open
Abstract
CONTEXT While a growing body of research has been demonstrating how exposure to social and built environments relate to various health outcomes, specific pathways generally remain poorly understood. But recent technological advancements have enabled new study designs through continuous monitoring using mobile sensors and repeated questionnaires. Such geographically explicit momentary assessments (GEMA) make it possible to link momentary subjective states, behaviors, and physiological parameters to momentary environmental conditions, and can help uncover the pathways linking place to health. Despite its potential, there is currently no review of GEMA studies detailing how location data is used to measure environmental exposure, and how this in turn is linked to momentary outcomes of interest. Moreover, a lack of standard reporting of such studies hampers comparability and reproducibility. AIMS The objectives of this research were twofold: 1) conduct a systematic review of GEMA studies that link momentary measurement with environmental data obtained from geolocation data, and 2) develop a STROBE extension guideline for GEMA studies. METHOD The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Inclusion criteria consisted of a combination of repeated momentary measurements of a health state or behavior with GPS coordinate collection, and use of these location data to derive momentary environmental exposures. To develop the guideline, the variables extracted for the systematic review were compared to elements of the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) and CREMAS (CRedibility of Evidence from Multiple Analyses of the Same data) checklists, to provide a new guideline for GEMA studies. An international panel of experts participated in a consultation procedure to collectively develop the proposed checklist items. RESULTS AND DEVELOPED TOOLS: A total of 20 original GEMA studies were included in the review. Overall, several key pieces of information regarding the GEMA methods were either missing or reported heterogeneously. Our guideline provides a total of 27 categories (plus 4 subcategories), combining a total of 70 items. The 22 categories and 32 items from the original STROBE guideline have been integrated in our GEMA guideline. Eight categories and 6 items from the CREMAS guideline have been included to our guideline. We created one new category (namely "Consent") and added 32 new items specific to GEMA studies. CONCLUSIONS AND RECOMMENDATIONS This study offers a systematic review and a STROBE extension guideline for the reporting of GEMA studies. The latter will serve to standardize the reporting of GEMA studies, as well as facilitate the interpretation of results and their generalizability. In short, this work will help researchers and public health professionals to make the most of this method to advance our understanding of how environments influence health.
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Affiliation(s)
- Célia Kingsbury
- École de santé publique, Université de Montréal (ESPUM), 7101 Av. du Parc, Montréal, H3N 1X9, Québec, Canada.
- Centre de recherche de santé publique (CReSP), 7101, Av. du Parc, Montréal, H3N 1X9, Québec, Canada.
| | - Marie Buzzi
- Université de Lorraine, INSERM, INSPIIRE, Nancy, F-54000, France
| | - Basile Chaix
- Université de Sorbonne, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, Nemesis Team, Faculté de Médecine Saint-Antoine, 27 rue Chaligny, Paris, 75012, France
| | - Martina Kanning
- Department of Social and Health Sciences in Sport Science, University of Konstanz, Universitätsstraße 10, 78464, Konstanz, Baden-Wuerttemberg, Germany
| | - Sadun Khezri
- École de santé publique, Université de Montréal (ESPUM), 7101 Av. du Parc, Montréal, H3N 1X9, Québec, Canada
- Centre de recherche de santé publique (CReSP), 7101, Av. du Parc, Montréal, H3N 1X9, Québec, Canada
| | - Behzad Kiani
- Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Brisbane St Lucia, QLD, 4072, Australia
| | - Thomas R Kirchner
- Department of Social and Behavioral Sciences, New York University School of Global Public Health, 726 Broadway, New York, NY, 10012, USA
- Center for Urban Science and Progress, New York University Tandon School of Engineering, 6 MetroTech Center, Brooklyn, NY, 11201, USA
| | - Allison Maurel
- École de santé publique, Université de Montréal (ESPUM), 7101 Av. du Parc, Montréal, H3N 1X9, Québec, Canada
- Centre de recherche de santé publique (CReSP), 7101, Av. du Parc, Montréal, H3N 1X9, Québec, Canada
| | - Benoît Thierry
- École de santé publique, Université de Montréal (ESPUM), 7101 Av. du Parc, Montréal, H3N 1X9, Québec, Canada
- Centre de recherche de santé publique (CReSP), 7101, Av. du Parc, Montréal, H3N 1X9, Québec, Canada
| | - Yan Kestens
- École de santé publique, Université de Montréal (ESPUM), 7101 Av. du Parc, Montréal, H3N 1X9, Québec, Canada
- Centre de recherche de santé publique (CReSP), 7101, Av. du Parc, Montréal, H3N 1X9, Québec, Canada
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Abad S, Badilla P, Marshall AT, Smith C, Tsui B, Cardenas-Iniguez C, Herting MM. Lifetime residential history collection and processing for environmental data linkages in the ABCD study. Health Place 2024; 87:103238. [PMID: 38677137 PMCID: PMC11132178 DOI: 10.1016/j.healthplace.2024.103238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 03/01/2024] [Accepted: 03/28/2024] [Indexed: 04/29/2024]
Abstract
By using geospatial information such as participants' residential history along with external datasets of environmental exposures, ongoing studies can enrich their cohorts to investigate the role of the environment on brain-behavior health outcomes. However, challenges may arise if clear guidance and key quality control steps are not taken at the outset of data collection of residential information. Here, we detail the protocol development aimed at improving the collection of lifetime residential address information from the Adolescent Brain Cognitive Development (ABCD) Study. This protocol generates a workflow for minimizing gaps in residential information, improving data collection processes, and reducing misclassification error in exposure estimates.
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Affiliation(s)
- Shermaine Abad
- Department of Radiology, University of California, San Diego, USA
| | - Paola Badilla
- Institute for Behavioral Genetics, University of Colorado, Boulder, USA
| | - Andrew T Marshall
- Department of Pediatrics (Division of Neurology), Children's Hospital Los Angeles, USA
| | - Calen Smith
- Department of Psychiatry, University of California, San Diego, USA
| | - Brandon Tsui
- Department of Radiology, University of California, San Diego, USA
| | - Carlos Cardenas-Iniguez
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, USA
| | - Megan M Herting
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, USA; Department of Pediatrics, Children's Hospital Los Angeles, USA.
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Kammerer M, Iverson AL, Li K, Goslee SC. Not just crop or forest: an integrated land cover map for agricultural and natural areas. Sci Data 2024; 11:137. [PMID: 38278830 PMCID: PMC10817889 DOI: 10.1038/s41597-024-02979-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 01/16/2024] [Indexed: 01/28/2024] Open
Abstract
Due to the key role surrounding landscape plays in ecological processes, a detailed characterization of land cover is critical for researchers and conservation practitioners. Unfortunately, in the United States, land cover data are split across thematic datasets that emphasize agricultural or natural vegetation, but not both. To address this gap, we merged two datasets, the LANDFIRE National Vegetation Classification (NVC) and USDA-NASS Cropland Data Layer (CDL), to produce integrated 'Spatial Products for Agriculture and Nature' (SPAN). Our workflow leveraged strengths of the NVC and the CDL to create detailed rasters comprising both agricultural and natural land-cover classes. We generated SPAN annually from 2012-2021 for the conterminous United States, quantified agreement and accuracy of SPAN, and published the complete computational workflow. In our validation analyses, we found that approximately 5.5% of NVC agricultural pixels conflicted with the CDL, but we resolved most conflicts, leaving only 0.6% of agricultural pixels unresolved in SPAN. These ready-to-use rasters characterizing both agricultural and natural land cover will be widely useful in environmental research and management.
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Affiliation(s)
- Melanie Kammerer
- USDA-ARS Pasture Systems and Watershed Management Research Unit, University Park, PA, 16802, USA.
- Oak Ridge Institute for Science and Education, Oak Ridge, TN, 37830, USA.
| | - Aaron L Iverson
- Department of Environmental Studies, St. Lawrence University, Canton, NY, 13617, USA
| | - Kevin Li
- School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Sarah C Goslee
- USDA-ARS Pasture Systems and Watershed Management Research Unit, University Park, PA, 16802, USA.
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Stingone JA, Geller AM, Hood DB, Makris KC, Mouton CP, States JC, Sumner SJ, Wu KL, Rajasekar AK. Community-level exposomics: a population-centered approach to address public health concerns. EXPOSOME 2023; 3:osad009. [PMID: 38550543 PMCID: PMC10976977 DOI: 10.1093/exposome/osad009] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2024]
Abstract
Environmental factors affecting health and vulnerability far outweigh genetics in accounting for disparities in health status and longevity in US communities. The concept of the exposome, the totality of exposure from conception onwards, provides a paradigm for researchers to investigate the complex role of the environment on the health of individuals. We propose a complementary framework, community-level exposomics, for population-level exposome assessment. The goal is to bring the exposome paradigm to research and practice on the health of populations, defined by various axes including geographic, social, and occupational. This framework includes the integration of community-level measures of the built, natural and social environments, environmental pollution-derived from conventional and community science approaches, internal markers of exposure that can be measured at the population-level and early responses associated with health status that can be tracked using population-based monitoring. Primary challenges to the implementation of the proposed framework include needed advancements in population-level measurement, lack of existing models with the capability to produce interpretable and actionable evidence and the ethical considerations of labeling geographically-bound populations by exposomic profiles. To address these challenges, we propose a set of recommendations that begin with greater engagement with and empowerment of affected communities and targeted investment in community-based solutions. Applications to urban settings and disaster epidemiology are discussed as examples for implementation.
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Affiliation(s)
- Jeanette A. Stingone
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Andrew M. Geller
- Office of Research and Development, Environmental Protection Agency, RTP, NC, USA
| | - Darryl B. Hood
- Division of Environmental Health Sciences, The Ohio State University, Columbus, OH, USA
| | - Konstantinos C. Makris
- Cyprus International Institute for Environmental and Public Health, Cyprus University of Technology, Limassol, Cyprus
| | - Charles P. Mouton
- Department of Family Medicine, University of Texas Medical Branch Galveston, TX, USA
| | - J. Christopher States
- Center for Integrative Environmental Health Sciences, Department of Pharmacology and Toxicology University of Louisville School of Medicine, Louisville, KY, USA
| | - Susan J. Sumner
- Department of Nutrition, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
| | - K. Lily Wu
- California Environmental Protection Agency—Office of Environmental Health Hazard Assessment, Sacramento, CA, USA
| | - Arcot K Rajasekar
- School of Information and Library Science, University of North Carolina, Chapel Hill, Chapel Hill, NC, USA
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