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APHA Scientific Session and Event Listing

Li Zhu, Department of Epidemiology and Biostatistics, Texas A&M System Health Science Center, TAMU 1266, College Station, TX 77843-1266u, 979-458-0079, lizhu@srph.tamhsc.edu and Cynthia Warrick, PhD, Institute of Public Health, Florida A&M University, Science Research Center Suite 207-B, Tallahassee, FL 32307.

Objective: The purpose of this study is to develop and test a method to identify African American communities at the greatest risk for late stage breast cancer diagnosis.

Methods: The study population is African American women Medicare beneficiaries in Texas Public Health Region 6/5 South who are 65 years of age and older. We will compare African American women Medicare beneficiaries who do not receive a mammogram every 1 to 2 years with those who do receive mammograms. Geographic information systems (GIS) are used to link Medicare mammography claims data to stage of breast cancer diagnosis data to target communities where mammography use is low and where the diagnosis of late stage of breast cancer is high. Cutting-edge Bayesian hierarchical modeling approaches are used to analyze the relationships between geographic variations in morbidity, mortality, and the community-level determinants for an enhanced understanding of the social and cultural factors related to mammography utilization and late-stage breast cancer diagnosis.

Conclusions: This study expands the uses of GIS to advance the early detection of breast cancer. The hypotheses are innovative because no studies in the literature have combined the analysis of mammography use and stage of breast cancer diagnosis in African American women. It introduces a new approach for incorporating environmental and neighborhood effects and cultural competency into screening research. It will provide a model for targeting communities at-risk for late-stage breast cancer diagnosis.

Learning Objectives:

• 1. Create a set of factors that are potential causes of breast cancer disparities, including social factors, health system utilization, access to care, economic status, environmental and neighborhood effects.
• 2. Expand the ability to predict and monitor breast cancer disparities through the collection of risk factors and screening data by geography, race, socioeconomic, and environmental characteristics.

Keywords: Geographic Information Systems, Health Disparities

Presenting author's disclosure statement:

Any relevant financial relationships? No