2012 Progress Report: Improving Environmental Health Disparities: A Fundamental Cause ApproachEPA Grant Number: NIMHD002
Title: Improving Environmental Health Disparities: A Fundamental Cause Approach
Investigators: Calhoun, Elizabeth , Kim, Seijeoung
Institution: University of Illinois at Chicago
EPA Project Officer: Hahn, Intaek
Project Period: August 1, 2011 through July 31, 2014
Project Period Covered by this Report: September 22, 2011 through September 21,2012
Project Amount: $819,428
RFA: Transdisciplinary Networks of Excellence on the Environment and Health Disparities (2012) RFA Text | Recipients Lists
Research Category: Environmental Justice , Environmental Health Disparities , Health
The Center of Excellence in Eliminating Disparities Environmental Supplement established an Environmental Core, which operates in conjunction with other Cores of the UIC Center for Excellence in Eliminating Disparities maximizing the Center's environmental health disparities research capacity. Data generated from this project is deposited into the Data Core and made available to collaborating health disparities researchers and partners.
This core supports a research project that explores mechanisms explaining racial differences in exposure to environmental hazards and access to care, and in health outcomes. To achieve this objective, we are compiling relevant neighborhood-level data on environmental hazards and access to care in Cook County, and linking them to other social determinants data compiled in the data repository. We are using three approaches to examine the associations:
- We are examining the effect of racial residential segregation on the physical and social environment variables (the presence of environmental hazards and access to health care facilities).
- We are examining incidence and late stage diagnosis of breast, cervical, and lung cancer in relation to environmental risk factors.
- We are examining changes in environmental conditions on health outcomes, we are exploring the effect of changes in racial composition and socioeconomic status between 2000 and 2010 (relocation of racial/ethnic minorities who moved from inner-city Chicago to suburban Cook County).
The primary tasks of the first year of the research are to: 1) complete the IRB review and approval; 2) establish Environmental Core, and to develop a formal collaborative linkage with existing Data Core of the Center (Dr. Kim, Core PI); 3) compile essential data elements for the proposed study; and 4) begin to generate preliminary/intermediate findings utilizing the proposed conceptual and methodological framework.
As we planned, we completed the primary tasks for the first year including: 1) the IRB approval; 2) established Environmental Core, and the collaborative linkage with existing Data Core of the Center; and 3) compiled essential data elements for the proposed study.
For the second year, we focus on analysis of the data, submitting manuscripts peer reviewed journals, and presenting findings at scientific meetings. We expanded envirnomental risk data since the last report. All data are housed in a password protected server managed by the Center, which we restructured to better meet the needs of the center investigators.
The Environmental Core manages the following datasets:
Environmental hazards data--the complied rate of point sources which is the rate of cumulative superfund sites, brownfield sites, toxic release inventory data 1990-2009 per square miles and per 100,000 residents;
Environmental cancer risk--the total cancer risk (National Scale Air Toxics Assessments), and its six subdomains;
Health outcome measures--we calculated the rates of breast, cervical, lung, brain and cancers by zip code. We then converted the rates by census tract using the U.S. Department of Housing and Urban Development (HUD) crosswalk file. The reason for this is that geographic units of zip code and census tract do not match, while some data are available at zip code and some are at census tract. We were able to convert from zip to census and vice versa. In addition, we were able to get 16 major health outcome measures by community area level from the Chicago Department of Public Health, which includes asthma and other environmental related health measures.
We successfully established data cooperation between the University of Illinois at Chicago School of Public Health (UIC SPH) and the Ilinois Department of Public Health. We now have a liaison who coordinates data acquisition process between the two institutions.
Health care access data We established the distributions of hospitals, federally qualified health clinics, and community health centers. We also included the Medically Underserved Area designation (MUAs) and the Healthcare Profession Shortage Areas (HPSAs).
Demographic data social capital measure, racial compositions, neighborhood disadvantage measure, and housing value, and the proportion of rental homes. Additionally, our request for the Cook County Assessors database which includes land use has been approved, and we will be receiving the data.
Our Environmental Core weekly meeting has been very productive. We were able to develop two manuscripts that are ready for submission for publication. We hired a program coordinator and a GIS expert. With the expertise, we completed all maps for environmental risk rates, health outcomes, and demographic distributions. Chloropleth maps were generated in ArcGIS software based on the variables of interest outlined above to visualize descriptive statistics. Box plots with a hinge value of 1.5 created in Geoda software examined possible outliers within the data. Exploratory data analysis including scatterplots and parallel coordinate plots looked at multivariate and bivariate relationships as a precursor to investigating spatial randomness. Geographically spatial weights based on a queen matrix took into consideration contiguity issues. Global Morans I with permutation inference examined negative and positive spatial correlation with a standardized z-value. This method investigated clustering to decide if a spatial relationship exists and if so, to justify further research with local spatial autocorrelation and spatial regression.
As a group we have submitted seven abstracts so far to scientific meetings including: American Public Association annual meeting, American Industrial Hygiene Association annual meeting, and Academy Health annual meeting (Appendix: publication/presentation list). We also presented at the UIC SPH GIS day, demonstrating our work on environmental health disparities and GIS.
As we described above, we hypothesized that historically disadvantaged minority neighborhoods lacking social capital would be more likely to be exposed to environmental hazards. Increased environmental risks in neighborhoods would then drive out middle class residents, resulting increased disadvantage, which consequently result in even worse social capital in recent years: a vicious cycle of environmental disparities and neighborhood disadvantage. Interestingly however, our preliminary findings indicate that the NATA cancer risk does not predict the cancer incidence. Moreover, demographic characteristics (racial composition and income) do not correlate with the cancer risk. From our GIS spatial analysis however, we do see clusters of cancer risk, which means cancer risks and environmental hazard scores are spatially clustered, but unlike findings from other studies, not by race and income in Cook County, IL. This finding is quite significant and calls for further investigation based on subdomain risks, which we are currently working on.
Specific aims of the study are to examine the interactions between exposure to environmental hazards, racial residential segregation and access to care; and the direct and indirect effects of such environmental factors on incidence and delay in diagnosis of breast, cervical, and lung cancer. In addition, neighborhood environment and social factors are known to be associated with risk exposure, screening patterns and access to care, thus an association with environmental risk exposure and late stage of diagnosis can be expected. Although various cancer types have been documented to be associated with environmental hazards, no clear associations between environmental (air) cancer risk and actual cancer incidences are established. Particularly, preliminary findings from this grant so far indicate that there is no distinct association between environmental cancer risk (EPA NATA measure based on air pollution) and the distribution of cancer incidences. Furthermore, the NATA cancer risk does not correlate with neighborhood racial composition and income. This is a very interesting finding that needs to be further evaluated because we do see the spatial cluster of NATA cancer risk, and yet race and income do not explain the cluster.
To better understand this patter and identify potential factors for the cancer risk and the link between the risk and cancer incidences, a series of OLS and spatial regression analyses will be modeled at the census tract level in Cook County, IL. A Geographic Information System (GIS) will be used to visually demonstrate distributions of environmental hazards, health care facilities, (SES), and racial segregation