Related Experiment Video
Updated: Jul 29, 2025

Comparison of Three Different Methods for Determining Cell Proliferation in Breast Cancer Cell Lines
Published on: September 3, 2016
A novel method for measuring the burden of breast cancer in neighborhoods
Russell K McIntire1, Hee-Soon Juon2, Scott W Keith3
1Jefferson College of Population Health, Thomas Jefferson University, 901 Walnut St., 10 Floor, Philadelphia, PA 19107, United States.
Abstract:
Community-based breast cancer prevention efforts often focus on women who live in the same neighborhoods, as they tend to have similar demographic characteristics, health behaviors, and environmental exposures; yet little research describes methods of selecting neighborhoods of focus for community-based cancer prevention interventions. Studies frequently use demographics from census data, or single breast cancer outcomes (e.g., mortality, morbidity) in order to choose neighborhoods of focus for breast cancer interventions, which may not be optimal. This study presents a novel method for measuring the burden of breast cancer among neighborhoods that could be used for selecting neighborhoods of focus. In this study, we 1) calculate a metric composed of multiple breast cancer outcomes to describe the burden of breast cancer in census tracts Philadelphia, PA, USA; 2) map the neighborhoods with the greatest breast cancer burden; and 3) compare census tracts with the highest burden of breast cancer to those with demographics sometimes used for geo-based prioritization, i.e., race and income. The results of our study showed that race or income may not be appropriate proxies for neighborhood breast cancer burden; comparing the breast cancer burden with demographics at the census tract level, we found few overlaps with the highest percentage African American or the lowest median incomes. Agencies implementing community-based breast cancer interventions should consider this method to inform the selection of neighborhoods for breast cancer prevention interventions, including education, screening, and treatment.
Related Concept Videos
Cancer Survival Analysis
Statistical Methods for Analyzing Epidemiological Data
Bias in Epidemiological Studies

