Abstract B72: Timely breast cancer diagnostic resolution: Effects of individual and neighborhood characteristics

Background: Disparities occur throughout the breast cancer continuum. African American women are more likely to be diagnosed with cancer at later stages, which results in poorer outcomes. In fact, despite lower incidence, the mortality rates are higher among black women. While timely follow-up of abnormal breast cancer diagnostic test results could lead to early diagnosis and better treatment outcomes, a myriad of factors may influence timely diagnostic resolution, even with patient navigation in place. Individual and neighborhood socioeconomic characteristics affect access to care, quality, and timeliness of care, which consequently affect health outcomes. In this study, we focus on the effects of neighborhood racial composition and poverty on timeliness of diagnostic test in African American women living in relatively poor neighborhoods in Chicago, IL. Purpose: The purpose of this study is to examine the effects of individual and neighborhood characteristics on timely resolution of breast cancer diagnostic tests among African American women who received breast cancer screening and diagnostic tests from three community hospitals in disadvantaged neighborhoods in Chicago. Methods: The analysis utilized a total of 405 African American women who participated in the Patient Navigation in Medically Underserved Areas Project in Chicago. Participating women were recruited from three hospitals. We created an indicator variable for timely diagnostic resolution (completion of follow-up tests within 60 days). We geo-coded participants9 home addresses, and calculated distance from home to clinic in miles. We added census tract level data from the American Community Survey 2005-2009, including racial composition and % poverty. In addition, we used Medically Underserved Area (MUA) designation (affluent; MUA designated poor; MUA undesignated poor). Individual characteristics were: age, education, distance to clinic, marital status, and health care distrust. We used Hierarchical Linear Model (HLM) to perform two-level models explaining diagnostic resolution timeliness. Results: The average age of participants was 60 years old. Over 92% completed high school education and 81% lived in MUA designated and undesignated but poor areas (vs. 19% living in affluent areas that are not eligible for MUA). On average, women traveled 5.5 miles to clinics. The mean % whites and % poverty were respectively 11% and 32%, respectively, which differed from overall % whites (32%) and % poverty in Chicago (21%). Women living in areas with a higher % of white residents were more likely to complete diagnostic tests within 60 days, controlling for all other variables. On the other hand, women living in areas with a higher % of African American residents were less likely to have timely diagnostic resolution, controlling for % poverty and all other individual level characteristics. Neighborhood poverty level was not significantly associated with diagnostic test completion. Conclusions: Even though all participants were African American women, living in neighborhoods with a higher proportion of whites was associated with timely diagnostic test resolution. Ethnic minority women seem to benefit from living in more racially integrated neighborhood environment, regardless of the level of poverty or MUA designation. While MUA designation and poverty are known to affect access to care, which is expected to influence timeliness of diagnostic test, racial composition of neighborhoods was shown to have a significant independent effect on timeliness of diagnostic test. The mechanisms of racial residential segregation on timeliness of diagnostic tests need to be further evaluated. Citation Format: Seijeoung Kim, Yamile Molina, Nerida Berriors, Elizabeth Calhoun. Timely breast cancer diagnostic resolution: Effects of individual and neighborhood characteristics. [abstract]. In: Proceedings of the Sixth AACR Conference: The Science of Cancer Health Disparities; Dec 6–9, 2013; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2014;23(11 Suppl):Abstract nr B72. doi:10.1158/1538-7755.DISP13-B72