1. Residential Segregation: A Key Connector Between Race and Environmental Health Disparities Jennifer Davis, Sacoby Wilson, Muhammad Salaam, Rahnuma Hassan Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina AbstractMethods Conclusion Objectives Contact County level data was obtained from the 2000 U.S. Census on several demographic variables, including race, age, education, income, poverty status, employment status, and housing. We then included information on residential segregation, poverty status, and information on health outcomes (i.e., all-cause mortality, infant mortality, cancer, and heart disease). All data management, data linkages, and statistical analyses were done using SAS (version 9.2; SAS Institute, Inc., Cary, NC).  Dissimilarty Index used to measure Residential Segregation  Counties were grouped into three categories, rural, urban, and mixed (semi-urban).  Statistical Analysis: PROC GENMOD used to generate Prevalence Odds Ratios.  ArcGIS used to create Segregation and Urban-Rural Influence Maps. Our study seeks to determine the role that residential segregation plays in driving the distribution of ecologic salutogens (i.e., factors that promote health) and pathogens (i.e., factors that impede health) in neighborhoods across the nation, ultimately driving health disparities in diverse populations. Currently, there is considerable debate concerning specific mechanisms culminating in a “health disparity”. Limited research purports that residential segregation is a critical starting point to gain better insight into the origins and persistence of environmental health disparities and may be part of the causal pathway leading to health disparities in exposure risks. In this study we aim to determine the variability in the distribution of salutogens and pathogens across levels of residential racial segregation. This cross-sectional study uses county-level data to describe the distribution of salutogenic (i.e., number of schools, health facilities, banks, religious institutions, and social/community service facilities) and pathogenic ( i.e., number of fast food places, gas stations, liquor stores, pawn shops, owned vs. rented housing, waste treatment facilities) determinants of health on a national scale. The dissimilarity index (D) was used to measure residential segregation for whites, blacks, and Hispanics. We found that a disproportionate amount of salutogens were present in white neighborhoods, while black and Hispanic neighborhoods housed a disproportionate number of pathogens. Highly racially segregated neighborhoods shoulder a disproportionate burden of pathogenic exposures and these exposure disparities may modify risk factors for adverse health outcomes. Furthermore, we found that pathogenic exposures were especially pronounced in high poverty and highly segregated neighborhoods. Discuss the role that segregation plays in driving the spatial distribution of salutogens and pathogens. Describe the role that segregation plays in driving environmental health disparities. Analyze environmental health at the community level using epidemiologic methods. Table 1: Descriptive Characteristics of National, Urban, Mixed, and Rural Counties Across the U.S. National (N= 3143) Urban (N= 1305) Mixed (N= 1126) Rural (N= 712) Population (millions)281.4240.133.5 7.8 Race (%) - White - Black - Hispanic 69.1 12.1 12.5 66.9 12.7 13.8 81.2 8.9 5.8 87.7 6.6 4.3 Gender (%) - Males - Females 49.1 50.9 48.9 50.9 50.0 51.2 49.5 50.5 Below Poverty (%) 12.1 11.614.316.0 Average Income ($US)35,36340,54632,42730,509 Education < H.S. (%) 2.7 2.4 2.5 Unemployed (%) 3.6 3.7 3.6 Housing - Median home value ($US)84,340104,76973,85163,469 Prevalence Rate (per 10,000) - All Cause Mortality - Heart Disease - Cancer - Infant Mortality 285.4 81.9 62.1 2.1 119.4 34.6 26.9 0.92 103.1 30.1 22.4 0.79 62.9 17.2 12.8 0.35 Background Environmental Justice (EJ) efforts have consistently demonstrated the unequal distribution of environmental hazards and unhealthy land uses across marginalized racial, ethnic, and social groups.  Siting of Hazardous Waste Landfills  Their Correlation with Racial and Economic Status of Surrounding Communities Segregation, SES, and Health Limited research purports that residential segregation is a critical starting point to gain better insight into the origins and persistence of environmental health disparities and may be part of the causal pathway leading to disparities in health risks. Counties with high percentages of AAs showed the highest prevalence for adverse health outcomes, illustrating the influence that race and concentrated poverty has on these health outcomes. The individual influence of poverty and segregation differed, revealing stronger associations among high poverty and low to moderate levels of segregation. Geographical comparisons displayed stronger associations among rural and mixed counties. This study is novel because to date no other study has looked at the effects of both segregation and poverty on adverse health outcomes at the county level. NEXT STEPS Future research with multi-level analysis is needed to understand the effects of segregation and poverty at the metropolitan, census track and individual levels. Research uncovering the reasons behind urban, rural, and mixed differences is needed. Future studies using segregation analysis should incorporate multi-ethnic comparisons, including Hispanics, Asians, and Native Americans. Jennifer Davis, MSPH, PhD (c) davisjr6@gmail.com Table 2. Prevalence Odd Ratios of the Poverty Distribution for Rural, Urban, and, Mixed Counties (Blacks only). Blacks (National) PovertyLowModerateHigh All Cause Mortality Low Moderate High 1.00 1.03 (1.03-1.04) 1.15 (1.15-1.16) 1.06(1.06-1.07) 1.13 (1.13-1.14) 1.19 (1.18-1.20) 1.12 (1.11-1.13) 1.21 (1.21-1.22) 1.30 (1.30-1.31) Heart Disease Low Moderate High 1.00 1.04 (1.03-1.05) 1.21 (1.20-1.22) 1.06 (1.05-1.07) 1.16 (1.15-1.17) 1.23 (1.22-1.24) 1.12 (1.11-1.13) 1.22 (1.21-1.23) 1.36 (1.35-1.37) Cancer Low Moderate High 1.00 1.00 (0.99-1.01) 1.10 (1.08-1.11) 1.04 (1.03-1.05) 1.07 (1.06-1.08) 1.08 (1.08-1.09) 1.07 (1.05-1.08) 1.13 (1.12-1.14) 1.15 (1.14-1.16) Infant Mortality Low Moderate High 1.00 1.05 (0.98-1.12) 1.18 (1.10-1.27) 0.93 (0.88-0.99) 1.07 (1.01-1.13) 1.14 (1.07-1.21) 1.06 (0.99-1.13) 1.25 (1.18-1.32) 1.48 (1.41-1.56) Blacks (National) SegregationLowModerateHigh All Cause Mortality Low Moderate High 1.00 1.00 (1.00-1.01) 1.08 (1.08-1.09) 1.07 (1.07-1.08) 1.10 (1.09-1.11) 1.11 (1.10-1.11) 1.22 (1.22-1.23) 1.23 (1.22-1.24) 1.16 (1.16-1.17) Heart Disease Low Moderate High 1.00 1.08 (1.07-1.09) 1.13 (1.12-1.14) 1.08 (1.07-1.09) 1.16 (1.15-1.17) 1.19 (1.18-1.20) 1.28 (1.27-1.29) 1.30 (1.28-1.31) 1.22 (1.21-1.23) Cancer Low Moderate High 1.00 1.01 (1.00-1.02) 1.04 (1.03-1.06) 1.04 (1.03-1.05) 1.05 (1.04-1.06) 1.07 (1.06-1.08) 1.12 (1.11-1.14) 1.13 (1.12-1.14) 1.11 (1.10-1.12) Infant Mortality Low Moderate High 1.00 1.06 (0.99-1.13) 1.11 (1.04-1.19) 0.98 (0.93-1.04) 1.02 (0.96-1.09) 1.05 (0.99-1.11) 1.35 (1.28-1.43) 1.27 (1.20-1.35) 1.25 (1.18-1.33) Results