Abstract A75: Racial and ethnic differences in travel time to mammography facilities in 5 US cities
Authors: Graham Shannon , Lewis Brian , Flanagan Barry , Watson Meg , Peipins Lucy 
Published: May 2015

Abstract
Introduction: Screening by mammography is one component of an overall strategy to identify early breast cancer and reduce breast cancer mortality. While women in rural areas may be at a disadvantage in accessing mammography, urban residents who depend on public transportation can also face barriers to mammography services, despite generally shorter travel distances. We examined travel time using public transportation from census tracts to mammography facilities in Boston, Philadelphia, San Antonio, San Diego and Seattle.
Methods: Data sources included: U.S. 2010 census data used to identify women 40 years of age and older, and race/ethnicity groups by census tract in each city; American Community Survey data to determine household availability of a private vehicle; NAVTEQ street network for each metropolitan area; and FDA's certification and inspection records of U.S. mammography facilities. Using the public transportation option on Google Trip Planner we obtained the travel time from the centroid of each census tract to the nearest mammography facility. A standard trip time of 11:00 am on weekdays was used for all searches. We calculated tract percentages of households with no vehicle availability and percentage blacks, whites, Asians and Hispanics for each metropolitan area. Median travel times were obtained by summing travel time by vehicle access and race/ethnicity across all census tracts in the metropolitan area. Finally, we calculated overall mammography capacity ratios (number of machines * estimated number of mammograms per machine / population of women 40 years of age and older) for each city.
Results: Overall, median travel times to the closest mammography facilities by public transportation were 21 minutes in Philadelphia, 27 minutes in Boston, 33 minutes in Seattle, 34 minutes in San Antonio, and 35 minutes in San Diego. Across all cities, travel time increased as availability of a private vehicle increased indicating a suburban effect. Focusing on census tracts with low private vehicle availability we saw little differences in median travel time by race/ethnicity in Philadelphia (13 to 14 minutes) and Boston (14 to 15 minutes) while in Seattle, whites had the shortest travel time (23 minutes) compared to blacks, Asians, and Hispanics (30 minutes). In San Antonio and San Diego, blacks had the longest travel times (33 minutes and 28 minutes) compared to the other groups. Maximum travel times in tracts with low vehicle availability ranged from 86 minutes to over two hours. There was less variability in travel times for census tracts classified as having high vehicle availability.
Conclusion: Our results reveal a geographic pattern of wide-ranging travel times within and across the five metropolitan areas with regard to low-vehicle-availability populations. The Eastern cities of Boston and Philadelphia, with well-developed train systems, had travel times to the nearest mammography facility that were almost 10 to 15 minutes (21% to 39%) shorter than the western cities of San Diego, San Antonio and Seattle. Across all metropolitan areas in the low vehicle availability category, white census tracts tended to have among the shortest travel times. In the Western cities only black census tracts consistently had longer travel times than whites while Hispanic and Asian travel times varied relative to that of whites. Although mammography capacity was adequate at the metropolitan level, we found maximum travel times of more than two hours for residents of some census tracts having low private vehicle availability.
Citation Format: Shannon Graham, Brian Lewis, Barry Flanagan, Meg Watson, Lucy Peipins. Racial and ethnic differences in travel time to mammography facilities in 5 US cities. [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 A75. doi:10.1158/1538-7755.DISP13-A75