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Access to screening mammography may be limited by the availability of facilities and machines, and nationwide mammography capacity has been declining. We assessed nationwide capacity at state and county levels from 2003 to 2009, the most recent year for which complete data were available. Using mammography facility certification and inspection data from the Food and Drug Administration, we geocoded all mammography facilities in the United States and determined the total number of fully accredited mammography machines in each US County. We categorized mammography capacity as counties with zero capacity (i.e., 0 machines) or counties with capacity (i.e.,≥1 machines), and then compared those two categories by sociodemographic, health care, and geographic characteristics. We found that mammography capacity was not distributed equally across counties within states and that more than 27 % of counties had zero capacity. Although the number of mammography facilities and machines decreased slightly from 2003 to 2009, the percentage of counties with zero capacity changed little. In adjusted analyses, having zero mammography capacity was most strongly associated with low population density (OR = 11.0; 95 % CI 7.7-15.9), low primary care physician density (OR = 8.9; 95 % CI 6.8-11.7), and a low percentage of insured residents (OR = 3.3; 95 % CI 2.5-4.3) when compared with counties having at least one mammography machine. Mammography capacity has been and remains a concern for a portion of the US population--a population that is mostly but not entirely rural.

To a great extent, research on geographic accessibility to mammography facilities has focused on urban-rural differences. Spatial accessibility within urban areas can nonetheless pose a challenge, especially for minorities and low-income urban residents who are more likely to depend on public transportation. To examine spatial and temporal accessibility to mammography facilities in the Atlanta metropolitan area by public and private transportation, we built a multimodal transportation network model including bus and rail routes, bus and rail stops, transfers, walk times, and wait times. Our analysis of travel times from the population-weighted centroids of the 282 census tracts in the 2-county area to the nearest facility found that the median public transportation time was almost 51 minutes. We further examined public transportation travel times by levels of household access to a private vehicle. Residents in tracts with the lowest household access to a private vehicle had the shortest travel times, suggesting that facilities were favorably located for women who have to use public transportation. However, census tracts with majority non-Hispanic black populations had the longest travel times for all levels of vehicle availability. Time to the nearest mammography facility would not pose a barrier to women who had access to a private vehicle. This study adds to the literature demonstrating differences in spatial accessibility to health services by race/ethnicity and socioeconomic characteristics. Ameliorating spatial inaccessibility represents an opportunity for intervention that operates at the population level.