ReviewEnvironmental research2021
Semantic standards of external exposome data.
Review in Environmental research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 23 citations in OpenAlex.
- Maternal prenatal co-exposure to air pollution and psychological distress shapes the neonatal gut: microbiota-mediated pathways to early neurodevelopment.Gut microbes · 2026Article
- Global research trends on the human exposome: a bibliometric analysis (2005-2024).Environmental science and pollution research international · 2025Review
- Leveraging Administrative Health Databases to Address Health Challenges in Farming Populations: Scoping Review and Bibliometric Analysis (1975-2024).JMIR public health and surveillance · 2025Article
- Advancing social determinants of health research and practice: Data, tools, and implementation.Journal of clinical and translational science · 2025Article
- A fair individualized polysocial risk score for identifying increased social risk in type 2 diabetes.Nature communications · 2024Article
- Geospatial Science for the Environmental Epidemiology of Cancer in the Exposome Era.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2024Article
- A Fair Individualized Polysocial Risk Score for Identifying Increased Social Risk in Type 2 Diabetes.Research square · 2023Article
- Seminar: Scalable Preprocessing Tools for Exposomic Data Analysis.Environmental health perspectives · 2023Article
- Systematic design and data-driven evaluation of social determinants of health ontology (SDoHO).Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Enriching Real-world Data with Social Determinants of Health for Health Outcomes and Health Equity: Successes, Challenges, and Opportunities.Yearbook of medical informatics · 2023Article
- The impact of social and environmental factors on cancer biology in Black Americans.Cancer causes & control : CCC · 2023Review
- Enabling data sharing and utilization for African population health data using OHDSI tools with an OMOP-common data model.Frontiers in public health · 2023Article
- Methodological Challenges in Spatial and Contextual Exposome-Health Studies.Critical reviews in environmental science and technology · 2023Article
- A Narrative Literature Review of Natural Language Processing Applied to the Occupational Exposome.International journal of environmental research and public health · 2022Review
- The OneFlorida Data Trust: a centralized, translational research data infrastructure of statewide scope.Journal of the American Medical Informatics Association : JAMIA · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
An individual's health and conditions are associated with a complex interplay between the individual's genetics and his or her exposures to both internal and external environments. Much attention has been placed on characterizing of the genome in the past; nevertheless, genetics only account for about 10% of an individual's health conditions, while the remaining appears to be determined by environmental factors and gene-environment interactions. To comprehensively understand the causes of diseases and prevent them, environmental exposures, especially the external exposome, need to be systematically explored. However, the heterogeneity of the external exposome data sources (e.g., same exposure variables using different nomenclature in different data sources, or vice versa, two variables have the same or similar name but measure different exposures in reality) increases the difficulty of analyzing and understanding the associations between environmental exposures and health outcomes. To solve the issue, the development of semantic standards using an ontology-driven approach is inevitable because ontologies can (1) provide a unambiguous and consistent understanding of the variables in heterogeneous data sources, and (2) explicitly express and model the context of the variables and relationships between those variables. We conducted a review of existing ontology for the external exposome and found only four relevant ontologies. Further, the four existing ontologies are limited: they (1) often ignored the spatiotemporal characteristics of external exposome data, and (2) were developed in isolation from other conceptual frameworks (e.g., the socioecological model and the social determinants of health). Moving forward, the combination of multi-domain and multi-scale data (i.e., genome, phenome and exposome at different granularity) and different conceptual frameworks is the basis of health outcomes research in the future.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.