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Cancer Control Research

5R01CA112451-03
Haas, Jennifer S.
RACIAL SEGREGATION & DISPARITIES IN CANCER OUTCOMES

Abstract

Cancer of the lung, colon, prostate and breast are the most common cancers in the United States. For each of these common cancers, there is evidence of persistent racial and ethnic disparities in stage at diagnosis, the use of cancer treatments, and/or mortality. Prior work examining cancer disparities has focused on individual characteristics, and has not fully explained the causes of cancer disparities. A growing literature suggests that the attributes of the place where an individual resides may be associated with health outcomes independent of individual characteristics. Residential segregation is one of the characteristics of the social environment that is likely to influence disparities in cancer treatments and outcomes. Segregation may be associated with the use of cancer treatments and outcomes through differences in access to care, the characteristics of providers and facilities where an individual seeks care, beliefs about medical treatments, exposure to stress, social support, socioeconomic deprivation, and access to goods and services. The Behavioral Model of Healthcare Utilization will be used as the conceptual framework for our hypotheses. Data from SEER and Medicare will be used to obtain individual demographic characteristics, clinical characteristics, and outcomes for individuals diagnosed with lung, colorectal, breast and prostate cancer. This individual-level data will be linked with area-level data about residential segregation. We will determine whether segregation is associated with cancer outcomes overall, and specifically for individuals who are white, African American or Hispanic. Additional data about the characteristics of the social and physical environment will be examined as potential mediators of the association between segregation and cancer outcomes. To examine the effects of segregation on disparities in cancer outcomes, regression models will account for the multi-level structure of the data. The proposed study would provide empirical evidence that could give impetus to area-based interventions to reduce cancer disparities.

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