Determinants of Late-Stage Breast Cancer: Identifying Areas in Need of Targeted Screening Interventions

Rationale: Studies have shown that health care markets in the US do not adequately serve poor, less educated and uninsured women. Since mammography screening is widely used, requires medical intervention, and yields earlier breast cancer diagnosis, we chose late diagnostic stage as a proxy for inadequate medical services. Objectives: In previous research, we found that women living in poor, medically underserved, inner city Census Tracts in the US were at increased risk of a late-stage breast cancer diagnosis in 1990 and 2000. Our new research compares diagnostic outcomes based on residence at the Census Tract (CT) or Primary Care Service Area (PCSA). PCSAs were designed to represent actual patterns of primary care use, whereas CTs proxy neighborhood characteristics, but were not designed for health service analysis. We are interested in knowing whether the more physicians in an area, the lower the probability of a late-stage diagnosis. Methodology: We chose Atlanta, Detroit and San Francisco because these three major metropolitan areas have both income and racial-ethnic diversity. To explain late-stage diagnosis we used the percentage of the area population below poverty, not a high school graduate, non-white, in linguistically isolated households, in female-headed households, with less than 30 minutes commute, living in renter-occupied housing and the number of physicians. The 2000 PCSA and CT data were linked with individual data on breast cancer stage at diagnosis, race, age, martial status and city of residence from the 2000 SEER cancer registry. We present model-averaged parameter estimates derived from a bouquet of models using the minimum Akaike Information Criterion. Results: Individual age, marital status, race and residence in Detroit were important in both the CT and PCSA models, although only non-Hispanic black women were more likely to get a late-stage diagnosis at the CT level. At both levels of geography, the percentage of the population that lived in female-headed households and were not high school graduates positively affected the likelihood of a late-stage diagnosis. At the CT level, the percent of the population living below poverty positively contributed to a late-stage diagnoses. At the PCSA level, the percent of the population with travel time less than 30 minutes was a positive predictor. Finally, low primary care physician densities were associated with late-stage diagnosis in both models. Conclusion: There is a strong correspondence in the findings between the models. At both levels of geography, the greater the number of physicians, the lower the probability of late-stage diagnosis. However, our results suggest that health service markets are more local than the PCSA. Physicians are not located in impoverished CTs, exacerbating problems of undersupply and access in many underserved areas. These economically and socially disadvantaged areas are clearly identified in both the CT and PCSA findings. The variation in need within PCSAs suggest that for disease-specific outcomes such as ours, targeted medical interventions at the smaller, CT level are a practical and effective means for diagnosing breast cancer early.