Application of the Public Health Exposome Framework to Estimate Phenotypes of Resilience in a Model Ohio African-American Women’s Cohort
We report integration of the United States Environmental Protection Agency’s (USEPA) United States Environmental Justice Screen (EJSCREEN) database with our Public Health Exposome dataset to interrogate 9232 census blocks to model the complexity of relationships among environmental and socio-demographic variables toward estimating adverse pregnancy outcomes [low birth weight (LBW) and pre-term birth (PTB)] in all Ohio counties. Using a hill-climbing algorithm in R software, we derived a Bayesian network that mapped all controlled associations among all variables available by applying a mapping algorithm. The results revealed 17 environmental and socio-demographic variables that were represented by nodes containing 69 links accounting for a network with 32.85% density and average degree of 9.2 showing the most connected nodes in the center of the model. The model predicts that the socio-economic variables low income, minority, and under age five populations are correlated and associated with the environmental variables; particulate matter (PM2.5) level in air, proximity to risk management facilities, and proximity to direct discharges in water are linked to PTB and LBW in 88 Ohio counties. The methodology used to derive significant associations of chemical and non-chemical stressors linked to PTB and LBW from indices of geo-coded environmental neighborhood deprivation serves as a proxy for design of an African-American women’s cohort to be recruited in Ohio counties from federally qualified community health centers within the 9232 census blocks. The results have implications for the development of severity scores for endo-phenotypes of resilience based on associations and linkages for different chemical and non-chemical stressors that have been shown to moderate cardio-metabolic disease within a population health context.
KeywordsParticulate matter 2.5 μm United States Environmental Protection Agency United States Environmental Justice Screen Low birth weight Pre-term birth Infant mortality Cardiovascular CV Cardiovascular disease Public participatory geographical information system Toxic release inventory facility
Particulate matter at 2.5 μm
United States Environmental Protection Agency
United States Environmental Justice Screen
low birth weight
South Side Health Advisory Committee
public participatory geographical information system
toxic release inventory
risk management plan
- NPL site
national priorities list site
The authors would like to thank the entire Interdisciplinary Cardio-metabolic Exposome Team (ICE Tea) for critical review and comments. This work was supported, in part, by start-up package received from the Ohio State University College of Public Health and US EPA STAR Award RD83927501 (DBH and PDJ). Support was also from a start-up package received from Meharry Medical College for the Health Disparities Research Center of Excellence (PDJ).
- 1.Greater columbus infant mortality task force final report and implementation plan. Available online: http://gcinfantmortality.org/wp content/uploads/2014/01/IMTF-2014 Final-Report-v10.pdf. Accessed 1 June 2016.
- 3.Reece J, Olinger J, Holley K. Social capital and equitable neighborhood revitalization on Columbus southside. Available online: http://kirwaninstitute.osu.edu/wp-content/uploads/2014/10/01410-southside.pdf. Accessed 11 Aug 2015.
- 11.U.S. Environmental Protection Agency. Learn about the toxics release inventory. https://www.epa.gov/toxics-release-inventory-tri-program/learn-about-toxics-release-inventory (November 9).
- 14.EPA. EJSCREEN: Environmental Justice Screening and Mapping Tool. Available online: http://www2.epa.gov/ejscreen. Accessed 15 June 2015.
- 17.Healthy People 2020 [Internet]. Washington, DC: U.S. Department of Health and Human Services, Office of Disease Prevention and Health Promotion. Available from: http://www.healthypeople.gov/2020/default.aspx. Accessed 24 Apr 2017.
- 26.Kaufman JD, Adar SD, Barr RG, et al. Association between air pollution and coronary artery calcification within six metropolitan areas in the USA (the Multi-Ethnic Study of Atherosclerosis and Air Pollution): a longitudinal cohort study. Lancet. 2016;388(10045):696–704. https://doi.org/10.1016/S0140-6736(16)00378-0.
- 29.Juarez PD, Hood DB, Rogers GL, Baktash SH, Saxton AM, Matthews-Juarez P, et al. A novel approach to analyzing lung cancer mortality disparities: using the exposome and a graph-theoretical toolchain. Environ Dis. 2017;2:33–44.Google Scholar
- 34.Kamrath HJ, Osterholm E, Stover-Haney R, George T, O'Connor-Von S, Needle J. Lasting legacy: maternal perspectives of perinatal palliative care. J Palliat Med. 2018; https://doi.org/10.1089/jpm.2018.0303.
- 38.Francisco A, El-Sayed A. National income inequality and ineffective health insurance in 35 low and middle income countries. Health Policy Plan. 2017;32:487–92.Google Scholar
- 40.Dourson M, Price P, Unrine J. Health risks from eating contaminated fish. Comments Toxicol. 2002;8(4–6):399–419. https://doi.org/10.1080/08865140215061.
- 41.Anderson PD, Dourson M, Unrine J, Sheeshka J, Murkin E, Stober J. Framework and case studies. Comments Toxicol. 2002;8(4–6):431–502. https://doi.org/10.1080/08865140215066.