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Online Program

324706
Urban race-based residential segregation and health equity: Variations by geographic scale selection and implication for policy making


Wednesday, November 4, 2015 : 9:10 a.m. - 9:30 a.m.

Graciela Mentz, PhD, Department of Health Behavior and Health Education, University of Michigan, Ann Arbor, MI
Dawn M. Richardson, DrPH, MPH, School of Community Health, Portland State University, Portland, OR
Jamila Kwarteng, PhD, Medicine, Medical College of Wisconsin, Milwaukee, WI
Carmen A. Stokes, PhD, FNP-BC, RN, CNE, McAuley School ofNursing, University of Detroit Mercy, Detroit, MI
Amy Schulz, MPH, MSW, PhD, Health Behavior and Health Education, University of Michigan, Ann Arbor, MI
Ricardo de Majo, Health Behavior and Health Education, University of Michigan School of Public Health, Ann Arbor, MI
Background. Research links race-based residential segregation to racial disparities in health.  Previous studies have reported associations with indicators of health including, for example, cardiovascular risk and obesity. Efforts to measure and describe patterns of segregation depends on the choice of a geographical scale (Kaplan and Holloway, 2001, Reardon et al., 2008). Disentangling the effects of segregation across different geographic scales will help us to understand the extent to which differences of segregation within residential areas may contribute to health disparities (Bellatore, et al,  2011). In this paper we examine associations between race based residential segregation, assessed at two geographic scales, census block group (or BG) and non-census based buffers at the block level (or rooks) and cumulative biological risk (CBR) as an indicator of health.

Data, Methods and Measures.  We use data from the Healthy Environments Partnership (HEP) survey, approved by the University of Michigan’s Institutional Review Board in 2001. We used GIS techniques to assess the spatial dissimilarity index (Wong, 1993) at two scales, and multilevel multivariate models to test for associations between segregation and cumulative biological risk (CBR). Models adjust for individual level demographics and neighborhood conditions.

Results. Our results suggest that spatial residential segregation is positively associated with CBR at the rook level (beta=1.2, p-value=0.06), but not atthe BG  level (beta=0.11, p=0.0.91).

Conclusions. Here we find that segregation, at the rook level is associated with CBR. Our findings are consistent with results reported elsewhere (Acevedo-Garcia et al.(2008,2003)) linking census tract level segregation with self-rated health.

Learning Areas:

Basic medical science applied in public health
Public health or related research

Learning Objectives:
Describe patterns of spatial racial segregation as measures by the dissimilarity index in the case of Detroit, MI Assess the impact of segregation on cumulative biological risk in a on cumulative biological risk in a multi-ethnic city

Keyword(s): Health Disparities/Inequities, Policy/Policy Development

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have been the co-investigator of multiple federally funded grants focusing on the epidemiology of Cardiovascular disease and it's risk factors such as Cumulative Biological Risk.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

Back to: 5033.0: Statistical Methods in Health Equity