Grantee Research Project Results
2024 Progress Report: Analysis of Climate Change Related Chemical and Non-Chemical Stressor Exposures: Cumulative Health Impacts and Risk Trajectories in Vulnerable Ohio Census Tracts
EPA Grant Number: R840471Title: Analysis of Climate Change Related Chemical and Non-Chemical Stressor Exposures: Cumulative Health Impacts and Risk Trajectories in Vulnerable Ohio Census Tracts
Investigators: Hood, Darryl , Langston, Michael A , Mouton, Charles P. , Miller, Harvey , Ard, Kerry , Thomas, Jason , Le, Huyen
Institution: Meharry Medical College , The Ohio State University , The University of Texas Medical Branch - Galveston , University of Tennessee -Knoxville
EPA Project Officer: Hahn, Intaek
Project Period: December 1, 2022 through May 8, 2025
Project Period Covered by this Report: December 1, 2023 through November 30,2024
Project Amount: $1,294,249
RFA: Cumulative Health Impacts at the Intersection of Climate Change, Environmental Justice, and Vulnerable Populations/Lifestages: Community-Based Research for Solutions (2021) RFA Text | Recipients Lists
Research Category: Endocrine Disruptors , Environmental Justice , Human Health , Watersheds
Objective:
The objective of The Ohio State University USEPA STAR award is to model and analyze the impact of weather-related chemical and non-chemical stressor exposures on the progression of disparate health and policy outcomes, over time, in residents living in the vulnerable communities of Ohio.
Progress Summary:
The collective outputs from the STAR award have documented; 1) a guiding framework for assessing the policy context in quantifying relationships between chemical and non-chemical stressor exposures with disparate health outcomes in residents from vulnerable census tracts. 2) a multilevel model that considers the 2,952 census tracts of Ohio and estimates trajectories of chronic disease health risks as a function of chemical and non-chemical stressor exposures that are nested within differential policy contexts. 3) a methodology that allows for capturing spatial and administrative variation in policy. Overall, this work serves as an exemplar demonstrating that the differential contexts in which local policies are made, have differential impacts on the spatial variation of exposures to chemical and non-chemical stressors that are linked and associated with accelerated risk trajectories for chronic disease outcomes in residents from vulnerable census tracts. The explanatory power of the model is attributable to the differential policy regimens and suggests that a primary point for mitigation of negative risk trajectories is at the local municipality policy level.
Future Activities:
During YR3 we will are focusing on coalescing the collected cohort survey data on preschoolers and the adult on-the-ground cohort into the analysis phase for modeling toward a determination of how the health outcomes of residents vary by policy boundaries. In the following year, w aim to complete the circle toward dissemination of population level model that will allow for estimating average risk trajectories to chronic disease outcomes. This analytical power comes as a result of being able to curate electronic health record data for each of the adult study participants at an individual level followed by the use of Clique-centric techniques to generate paracliques that will inform and reveal latent associations of risk of adverse health outcomes as a function of policy context that is associated with chemical and non-chemical stressor exposures in our study population.
Journal Articles on this Report : 4 Displayed | Download in RIS Format
| Other project views: | All 17 publications | 13 publications in selected types | All 13 journal articles |
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Wu J, McLain AC, Rosile P, Hood DB. Association between autism spectrum disorder and environmental quality in the United States. ISPRS International Journal of Geo-Information 2024;13(9):308. |
R840471 (2024) |
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Lake LM, Scott SB, Hood DB, Kellis M, Gardiner MM, Basta NT. Risk management approach using ash-based amendment blends for remediation of lead-contaminated urban soils and protection of public health. Soil & Environmental Health 2024;2(4):100102. |
R840471 (2024) |
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Hurd TC, Payton FC, Hood DB. Targeting machine learning and artificial intelligence algorithms in health care to reduce bias and improve population health. The Milbank Quarterly 2024;102(3):577-604. |
R840471 (2024) |
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Chauhan R, Dande S, Hood DB, Chirwa SS, Langston MA, Grady SK, Dojcsak L, Tabatabai M, Wilus D, Valdez RB, Al-Hamdan MZ. Particulate matter 2.5 (PM2.5)-associated cognitive impairment and morbidity in humans and animal models:a systematic review. Journal of Toxicology and Environmental Health, Part B 2025:1-31. |
R840471 (2024) |
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Supplemental Keywords:
exposomics, census tracts, vulnerable communities, policy contexts, multilevel and bivariate model, resilience, allostatic load, ICD-10 codesProgress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.