Our study examined area-level and individual-level effects on mammography use for women in Los Angeles County. Gumpertz et al. had found that a longer distance from the population center of the census tract to the nearest mammography facility predicted more advanced disease for Latina and White women after controlling for other important factors [14
]. This led us to hypothesize that a lack of nearby mammography facilities would lead to less mammography use, which in turn would lead to a later-stage diagnosis of breast cancer. Consistent with this hypothesis, we found an increased use of mammography when many facilities were nearby. At the same time, our study confirmed the significance of individual characteristics found to be important predictors of mammography use in other studies [42
Our most striking and unexpected findings were revealed by the interactions. Not surprisingly, women aged 40–49 were less likely to have had a mammogram than women aged 50–64—an age group for which mammography is recommended by evidence-based guidelines in the United States [47
]. For women under 65 not covered by Medicare, lack of usual source of care is usually strongly associated with lower mammography rates. However, among the 50–64 years old group who had a usual source of health care in Los Angeles, we found that women with limited or no English proficiency were more
likely than English-proficient women to obtain a mammogram. These unexpected findings were consistent across all the models.
To help explain this finding, we examined data on 127,000 women screened in Los Angeles during 1999–2001 by their race-ethnicity from the Cancer Detection Section (CDS) of the California Department of Health Services. Comparing the percent of eligible women who actually used the program to those eligible, we found proportional underrepresentation among whites (18% eligible and 7% users of program) and blacks (9% eligible and 3% users); and overrepresentation among Latinas (64% eligible and 70% users) and Asian/Pacific Islanders (API) (9 percent eligible and 11 percent users). Further investigation showed that the Every Women Counts Program (EWC), directed by a community-based organization in Los Angeles County, had conducted outreach between 1999 and 2001 that targeted Spanish-speaking Latinas. The EWC program, co-funded by the CDC BCCEDP and California state, provides subsidized breast and cervical cancer screening services to low income underinsured residents. The program’s education and outreach to Spanish-speaking Latinas comprised a number of different strategies including an “over 50 task force” and a “grandmother’s campaign” with community participation on task forces and committees (Brian Montano, personal communication, 1 May 2008).The program sponsored a Mother’s Day campaign in which providers were given reminder cards to use with their patients. Providers were encouraged to emphasize the importance of screening and re-screening to community members. The program also helped providers participating in the EWC Program develop manual and computerized tracking systems to notify women that they were due for screening (Patricia Smith Francis, personal communication, 29 August 2008). This reliance on health care providers to encourage women to be screened, with a particular emphasis on Latinas over age 50, is probably why English fluency, age, and usual source of care significantly interacted to predict mammography use in our models.
Our results suggest that this campaign succeeded in reaching communities in need. The communities targeted in the outreach campaigns were the same ones that Gumpertz reported were disproportionately impacted by late stage breast cancer. Previous literature has shown that organized communities and social networks can effectively promote use of services, including cancer screening [48
]. Our findings for LA County in the context of the community-based outreach program to promote mammography among Latinas confirmed this.
Our analysis confirmed low use of mammography by Asian women, women 40–49 and lower-income women in Los Angeles [50
]. We confirmed greater use by women in the 50–64 and 65–84 age groups, those with a personal history of breast cancer, and those with a usual source of care and health insurance coverage. Previous findings have shown these individual variables are correlated with recent mammography use both for the nation and for Los Angeles [52
Our study is the first to show an association between use of mammography and density of mammography facilities within 2 miles of a woman’s residence. We also examined an alternative measure, distance of mammography facilities in relation to a respondent’s residence. This is the measure used in the Gumpertz et al. article; however, odds ratios using this measure were small and not statistically significant (data not shown) so we used the mammography density measure instead.
Our study benefitted from having an address for each woman and for each mammography facility, from which more precise locations and associations could be measured [54
]. Most previous studies, including that of Gumpertz et al. have assigned respondents to aggregated geographic units, such as Census tracts, counties, or zip codes. Krieger et al. have shown that it is important to compare socioeconomic status using small geographic units such as tracts in order to identify health inequalities [55
The above finding suggests that a woman’s proximity to the closest facility may not be as important as living in an area with a greater density of facilities. As indicated in the methods section, the density variable potentially captures more aspects of access than the proximity variable and may explain why only the density variable is associated with mammography use. Another possible explanation is that using the exact location of residence as we did in our study is a more accurate measure compared with using a Census tract centroid in the calculation of proximity, the address surrogate used in the Gumpertz study. Our finding that density of mammography facilities is an important determinant of mammography use suggests that examining the supply of mammography facilities, including capacity, location and staffing, needs additional study.
The geocoded location of each woman was based on her reported nearest street intersection, not her exact address. The geocoding process has been shown to introduce some positional inaccuracies, but resulting locations are generally within 100 m of the true location [56
]. Because most of LA County is very urban, we expect that most of the geocoded locations are very close to the actual residence. However, location of workplace was not available from the CHIS survey. It is likely that some women who work would find it convenient to have their mammograms at facilities close to their workplace, especially if there were few facilities available near their home.
Transit data throughout LA County were incomplete because data on rail lines run by Municipal Operators and Foothill Transit in LA County were not available. However, the Metro Transit Authority (MTA) estimates that these rail lines would add only 15% more rail stops to the present analysis (Dr. Jesse Simmon, personal communication, 24 January 2005).
The distribution of data was not adequate at all levels of geography. This limited our ability to test some variables. Though we do not know exactly how this limitation affected our analysis, it is likely that the sample of physician practice characteristics was too small to provide adequate power to detect differences in Los Angeles. In addition, CHIS data are self-reported and previous analyses have shown that mammography may be over-reported in surveys, particularly among racial/ethnic groups [57