Spatial equity in facilities providing low- or no-fee screening mammography in Chicago neighborhoods

Abstract

Recent research suggests living in an economically disadvantaged neighborhood is associated with decreased likelihood of undergoing mammography and increased risk of late-stage breast cancer diagnosis. Long distances and travel times to facilities offering low- or no-fee mammography may be important barriers to adherence to mammography screening recommendations for women living in economically disadvantaged urban neighborhoods, in which African-Americans are disproportionately represented. The purpose of this study was to examine whether the spatial distribution of facilities providing low- or no-fee screening mammography in Chicago, Illinois, is equitable on the basis of neighborhood socioeconomic and racial characteristics. We found that distance and travel times via automobile and public transportation to facilities generally decrease as neighborhood poverty increases. However, we also found that the strength of the association between neighborhood poverty level and two of the spatial accessibility measures-distance and public transportation travel time-is less strong in African-American neighborhoods. Among neighborhoods with the greatest need for facilities (i.e., neighborhoods with the highest proportions of residents in poverty), African-American neighborhoods have longer travel distances and public transportation travel times than neighborhoods with proportionately fewer African-American residents. Thus, it appears that the spatial accessibility of low- and no-fee mammography services is inequitable in Chicago. In view of persistent social disparities in health such as breast cancer outcomes, these findings suggest it is important for researchers to examine the spatial distribution of health resources by both the socioeconomic and racial characteristics of urban neighborhoods.

Figure

Predicted values¹ of distance to the nearest facility (natural log) for neighborhoods with low, medium, and high proportion of African–American (AA) residents.^{2 1}Predicted values were calculated based on OLS regression results. We used the group-specific minimum and maximum values of percentage in poverty and the group-specific means of percent African–American, percentage Latino, percentage other race/ethnicity, population density, and land area. ²African–American (AA) residents: low African–American (<20%), medium African–American (20–80%), high African–American (>80%).