| | Mammography Capacity: Impact on Screening Rates and Breast Cancer Stage at Diagnosis published online 15 June 2009. BackgroundMammography capacity in the U.S. reportedly is adequate, but has not been examined in nonmetropolitan areas. This study examined the relationships between in-county mammography facilities and rates of mammography screening and late-stage diagnosis of breast cancers. MethodsThe association between a mammography facility in the county of residence (2002–2004) and the odds of screening within 2 years were examined (in 2007) among Texas women aged >40 years who responded to the 2004 Behavioral Risk Factor Surveillance System survey, using multivariate logistic regression to control for age, race, ethnicity, education, income, self-reported health, insurance, and usual source of care. Similarly, the association between an in-county mammography facility and the odds of diagnosis with locally advanced or disseminated disease was examined among Texas women aged >40 years who developed breast cancer in 2004. ResultsHalf of the 254 counties in Texas had no mammography facility. After controlling for confounding factors, an in-county facility was associated with significantly higher odds of screening (OR=3.27; p=0.03) and lower odds of late-stage breast cancer at diagnosis (OR=0.36; 95% CI=0.26–0.51; p<0.001). The risks of late-stage diagnosis were higher for African-American women (OR=1.52; 95% CI=1.22–1.89; p<0.001) and Hispanic women (OR=1.23; 95% CI=0.99–1.53; p=0.06) than for white women. ConclusionsAlthough mammography capacity in the U.S. may be adequate on average, the unequal distribution of facilities results in large rural areas without facilities. Screening rates in these areas are suboptimal and are associated with late-stage diagnosis of breast cancer. Introduction  Screening mammography has been shown to reduce breast cancer mortality by approximately 20%, although its value among women aged <50 years and >75 years is the subject of ongoing debate.1, 2 Nevertheless, the annual or biannual screening of women aged >40 years is recommended by the American Cancer Society, the National Cancer Institute, and the U.S. Preventive Services Task Force.3, 4, 5 Owing to these findings and recommendations, Medicare, the nation's largest purchaser of healthcare services, began providing coverage of annual mammography for female beneficiaries in 1991. Because mammography's effectiveness is a direct result of its quality, in 1994 Congress enacted the Mammography Quality Standards Act, which provides for oversight and licensure of mammography facilities by the Food and Drug Administration.6 These efforts led to increased demand for mammography services, which has been compounded by the aging of the American population.7, 8 Consolidation among healthcare service providers has occurred during the same time period, and mammography service providers have not been immune to this trend.9 Thus, the demand for mammography has increased while supply has decreased. Reacting to reports of long waiting times for mammography services in some areas of the U.S., the Senate Special Committee on Aging requested that the U.S. General Accounting Office (GAO) determine whether the nation's capacity to provide mammography services was adequate and assess the effect of the consolidation of service providers on access to services. The GAO report,10 published in 2002, indicated that while capacity generally was adequate, there were metropolitan areas in which access was a problem. After a second request from Congress, GAO re-examined this issue in 2006.11 Again, GAO found that capacity generally was adequate but pointed out that “loss or absence of machines had affected access for some women.” They also suggested that problems could exist in rural areas, which often had no access to mammography facilities. However, data from rural counties were lacking in this study. Similar findings were reported by the U.S. Food and Drug Administration (FDA) in 2001.12 Based on a large literature pointing to the importance of close geographic proximity to the utilization of healthcare services,13, 14 including mammography services,15, 16, 17, 18, 19 it was hypothesized that the presence of a mammography facility in a county would be associated with (1) a higher percentage of women who receive mammography screening and, in turn, with (2) a lower risk of cancer diagnosis at a late stage of breast cancer. This hypothesis was examined by studying counties in Texas, a state characterized by several large urban counties and many remote rural counties. Methods The association between in-county mammography facilities (between 2002 and 2004) and two breast cancer outcomes (in 2004)—mammography screening and diagnosis of breast cancer at a late stage—was examined. The study was determined to be exempt from review by the IRB at M.D. Anderson Cancer Center. Data Sources and Linkage The addresses of all licensed, mobile, or fixed mammography facilities in Texas between 2002 and 2004 were obtained from the FDA. The facilities were mapped to counties by matching their ZIP codes (or street address in the case where ZIP codes overlapped counties) to county Federal Information Processing System (FIPS) codes. Using this method, 100% of facilities were mapped to a county. Mammography-screening data were obtained from the Behavioral Risk Factor Surveillance System (BRFSS) survey that was fielded in 2004 and were linked to facility data using county FIPS codes. Screening information was discarded for 49 (1.9%) respondents whose county information was missing or unknown. The BRFSS telephone health survey tracks health conditions, the use of preventive screening tests, and risk behaviors in the U.S. It is conducted annually by each of the 50 state health departments in the U.S. and in U.S. territories. The resulting data are representative of the U.S. population with telephones (87%–98% of the total U.S. population). The 2004 BRFSS survey in Texas had a response rate of 43.3%, an intermediate value among all states in the U.S.20 Incident breast cancer cases diagnosed among women aged >40 years between January 1, 2004, and December 31, 2004, by stage at diagnosis, were obtained from the Texas Cancer Registry (Texas Department of State Health Services) and linked to mammography-facility and -screening data using the county FIPS code for each woman's residence. Cases from any location in the breast and any stage (in situ–Stage IV) were included. Incident cases of lobular carcinoma in situ were excluded because their clinical significance is the subject of scientific debate. Cases of ductal carcinoma in situ were included, because they generally are considered precursors of invasive disease and are treated surgically.21, 22, 23 The demographic, geographic, and socioeconomic characteristics of each county were obtained from the 2000 U.S. Census Summary File 3 and linked to the remaining data using the county FIPS code. Summary File 3 consists of social, economic, and housing data from a sample of approximately 19 million households (approximately one in six U.S. households) that received the Census 2000 long-form questionnaire.24 Demographic characteristics included the percentage of women aged >40 years who were white, African American, Hispanic, and the percentage of women aged >80 years. Geographic characteristics included the size of the county (measured in square miles) and its location in the state, characterized by public health region. Socioeconomic factors included the percentages of the population who graduated from high school, spoke English at home, had access to a car, lived below the federal poverty line, and the mean annual family income. Estimates for the percentage of the population with healthcare insurance were obtained from the U.S. Census model-based small-area health insurance estimates for counties and states.25 Two analytic files were constructed from the sources described above, corresponding with the two hypotheses. The first consisted of person-level data for all female BRFSS respondents aged >40 years who resided in Texas. To each BRFSS respondent's record, a variable was added reflecting the presence or absence of a mammography facility in the county of residence as well as characteristics of the county from census data. The second file was similarly constructed from person-level data about each case of ductal carcinoma in situ or invasive breast cancer among women aged >40 years residing in Texas. To each of these records were added the mammography-facility data and area census data, based on county of residence at diagnosis. Analysis Two analyses were conducted, in 2007, corresponding to the two data files described above. In the first, multivariate logistic regression was used to examine the odds of mammography screening within 2 years among female respondents to the BRFSS aged >40 years in counties with and without mammography facilities, adjusting for each woman's age, race, ethnicity, education, income, insurance status, self-reported health, household, and usual source of health care, as well as the number of active physicians per capita, as these factors are known to be associated with mammography screening and access to care, particularly in rural areas.7, 26, 27, 28, 29 In the second analysis, the risk of cancer per 10,000 women aged >40 years was calculated, by stage, for two groups: those who resided in counties with and without facilities. The relative odds of diagnosis either at a late stage of breast cancer (defined as locally advanced or disseminated disease) or very early stage (defined as ductal carcinoma in situ) were examined among women aged >40 years who developed breast cancer in 2004. Multinomial logistic regression (with diagnosis with local disease as the referent) was used to examine the impact of residence in counties with and without mammography facilities on the relative odds of diagnosis at each stage, controlling for each woman's age, race, and ethnicity at diagnosis. Because more than one woman resided in each county, hierarchical analyses—with women nested within counties—were used to correct for within-county correlation in both analyses. Results Disparities in Mammography Capacity Of the 254 counties in Texas, only 125 (49%) had mammography facilities in 2002 (Figure 1). A mammography facility was located in a county adjacent to 109 (84%) of the 129 counties without facilities. The remaining 20 counties (8% of all counties) had neither in-county nor adjacent-county mammography facilities. Between 2002 and 2004, facility closures outpaced openings. By 2004, two (2%) of the counties without facilities in 2002 had gained a facility for the first time, while eight (6%) of the counties with one or more facilities in 2002 lost all mammography facilities. An additional 15 counties (12%) lost some, but not all, of their facilities. Eight counties (6%) with facilities in 2002 gained additional facilities by 2004. Counties lacking mammography facilities often were populated by those least able to compensate for this disparity. Compared with counties with facilities, counties without facilities were more sparsely populated, and their populations were less affluent and less likely to have healthcare insurance, to speak English, and to graduate from high school (Table 1). Some of these differences were quite striking. For example, the mean annual family income in counties without facilities was $26,727 (95% CI=$24,347–$29,107) compared with $40,632 (95% CI=$39,190–$42,070) in counties with facilities. Only 64% (95% CI=60%–69%) of adults in counties without facilities had graduated from high school compared with 77% (95% CI=76%–79%) in counties with facilities. Counties without facilities had larger Hispanic populations. | | |  | | County mammography facility | |
|---|
| Characteristic | None in county M (95% CI)a | None in county: adjacent, fixed M (95% CI)a | None in county: adjacent, mobile M (95% CI)a | In-county M (95% CI)a | |
|---|
| No. counties | 20 | 97 | 12 | 125 | | | No. women aged >40 years | 1858 (1478–2238) | 4981(3967–5965) | 5414(3759–7069) | 217,047(176,898–257,197) | | | Women aged >80 years(%) | 11(9–12) | 11(10–11) | 9(7–11) | 8(7–8) | | | Whiteb(%) | 78(75–81) | 81(79–83) | 79(72–87) | 71(69–73) | | | African Americanb(%) | 3(2–4) | 8(6–9) | 11(5–18) | 12(10–13) | | | Hispanicb(%) | 46(36–56) | 26(20–31) | 15(4–26) | 32(28–35) | | | Annual family incomec($) | 26,727(24,347–29,107) | 31,044(29,490–32,597) | 41,598(32,564–50,632) | 40,632(39,190–42,074) | | | Un-insuredc(%) | 24(22–26) | 21(19–22) | 18(15–21) | 18(18–19) | | | High school graduatesc(%) | 64(60–69) | 70(68–72) | 76(72–81) | 77(76–79) | | | Speaking Englishc(%) | 61(52–71) | 79(74–83) | 90(85–95) | 76(72–79) | | | Below povertyc(%) | 21(19–24) | 19(17–20) | 14(10–18) | 14(13–15) | | | With access to carc(%) | 93(92–94) | 92(91–93) | 94(93–96) | 93(92–93) | | | Area(square miles) | 2270(1393–3147) | 816(743–889) | 723(301–1144) | 1102(1027–1177) | | | | |
| a Unless otherwise noted bFrom among women aged >40 years cFrom among the entire population |
Impact of Capacity on Mammography Screening A total of 2418 women, representing 4,471,887 women aged >40 years in Texas, responded to the survey. Only 38.6% of women who lived in counties without facilities reported screening within 2 years compared with 62.9% of women with facilities in an adjacent county and 67.8% of women in counties with facilities (p=0.02). However, non-Hispanic white women and those aged <80 years, with a college education, higher income, healthcare insurance, in good health, and with a usual source of care were significantly more likely to report screening (Table 2). After accounting for these factors in multivariate analysis, women who lived in counties with facilities were significantly more likely to report screening within 2 years (OR=3.27; p=0.03; Table 3). The percentages screened, adjusted for other factors, were 42% in women living in counties without facilities, 66% in those with facilities in an adjacent county, and 70% among women living in counties with facilities. | | | | Characteristic | With characteristic % (95% CI) | Screened within 2 years % (95% CI) | p-value | |
|---|
| Mammography facility | | | | | | In-county | 90(89,91) | 67.8(65.3,70.1) | 0.02 | | | Adjacent county | 9(8,10) | 62.9(55.3,69.8) | | | None | 1(<1,2) | 38.6(18.8,63.1) | | | Race | | | | | | Non-Hispanic white | 65(63,68) | 71(68,73) | 0.004 | | | Hispanic | 22(20,25) | 59(53,64) | | | African American | 8(6,9) | 66(57,74) | | | Other | 5(4,6) | 56(43,67) | | | Age(years) | | | | | | 40–79 | 94(94,95) | 68(65,70) | 0.09 | | | >80 | 6(5,7) | 59(50,68) | | | Self-reported health | | | | | | Good | 71(69,74) | 71(69,74) | <0.0001 | | | Poor | 29(26,31) | 57(52,61) | | | Insurance | | | | | | Yes | 81(79,83) | 73(70,75) | <0.0001 | | | No | 19(17,21) | 42(37,48) | | | Usual source of care | | | | | | Yes | 88(86,89) | 71(69,73) | <0.0001 | | | No | 12(11,14) | 38(32,46) | | | Annual family income($) | | | | | | <20,000 | 23(21,25) | 57(52,61) | <0.0001 | | | 20,000–50,000 | 47(45,50) | 66(62,69) | | | >50,000 | 30(28,32) | 77(73,81) | | | Education | | | | | | None or primary only | 10(8,11) | 53(44,62) | <0.0001 | | | Secondary | 37(34,39) | 64(60,67) | | | Some college | 26(24,28) | 66(62,71) | | | College graduate | 28(26,30) | 77(73,80) | | | | |
| | | | Factor | OR (95% CI) | p-value | |
|---|
| In-county facility | 3.27(1.11,9.60) | 0.03 | | | Adjacent county facility | 2.67(0.89,8.09) | 0.08 | | | African-American race | 1.28(0.72,2.27) | 0.41 | | | Hispanic ethnicity | 1.38(1.06,1.79) | 0.02 | | | Education | 1.10(0.98,1.24) | 0.11 | | | Family income | 1.34(1.15,1.55) | <0.001 | | | Poor self-reported health | 0.58(0.47,0.71) | <0.001 | | | Usual source of care | 2.58(1.82,3.66) | <0.001 | | | Health insurance | 2.22(1.59,3.10) | <0.001 | | | Age | 1.03(1.02,1.05) | <0.001 | | | Aged >80 years | 0.30(0.20,0.45) | <0.001 | | | Physicians in county | 0.99(0.95,1.04) | 0.66 | | | | |
Reflecting the lower benefits of screening in these populations, women in poor health and those aged >80 years were significantly less likely to be screened within 2 years. In contrast, having healthcare insurance and a usual source of healthcare were associated with significantly higher odds of screening. Accounting for the impact of age, education, income, poor health, healthcare insurance, a usual source of care, and the availability of facilities in the county eliminated the disparate odds of screening observed among African-American and Hispanic women. After accounting for these factors, Hispanic women were significantly more likely to be screened than their non-Hispanic counterparts (Table 3). Impact of Capacity on Late-Stage Diagnosis of Breast Cancer In 2004, a total of 12,469 of the 4,639,842 women aged >40 years in Texas (risk: 26.87 per 10,000 women aged >40 years; 95% CI=26.4–27.3) were diagnosed with either invasive breast cancer or ductal carcinoma in situ. The risk of diagnosis at early and late stages varied significantly between counties with and without facilities (Table 4). The diagnosis of ductal carcinoma in situ was significantly more common among women who lived in counties with facilities compared with those who lived in counties without facilities (risk ratio=1.27; 95% CI=1.07–1.5; p=0.005). In contrast, a diagnosis of locally advanced or distant disease was more common among women who resided in counties without facilities (risk ratio=0.81; 95% CI=0.66–0.98; p=0.04). | | | | Stage at diagnosis | Risk cases per 10,000 women aged >40 years (95% CI) | Risk ratio (95% CI) | p-value | |
|---|
| In-county facility | No facility in county | |
|---|
| DCIS | 4.88(4.67,5.09) | 3.85(3.25,4.52) | 1.27(1.07,1.5) | 0.005 | | | Local disease | 18.83(18.42,19.25) | 17.60(16.3,18.98) | 1.07(.99,1.16) | 0.09 | | | With regional nodes | 6.96(6.71,7.22) | 6.23(5.47,7.08) | 1.12(0.98,1.27) | 0.10 | | | Locally advanced or distant disease | 2.07(1.93,2.21) | 2.57(2.09,3.13) | 0.81(0.66,0.98) | 0.04 | | | | |
After accounting for confounding by age, race, and ethnicity, multivariate analysis confirmed that women who lived in counties with facilities were more likely to be diagnosed with carcinoma in situ than their counterparts who lived in counties without facilities (OR=1.32; 95% CI=0.98–1.77; p=0.06). Most importantly, women who lived in counties with facilities were significantly less likely to be diagnosed at an advanced stage than their counterparts who lived in counties without facilities (OR= 0.36; 95% CI=0.26–0.51; p<0.001; Table 5). These differences were observed despite adjustment for higher probabilities of advanced disease among African-American and Hispanic women. Women who lived in counties with facilities in an adjacent county had lower odds of diagnosis at a late stage, although this difference did not reach significance (OR=0.80; 95% CI=0.53–1.23; p=0.32). | | | | Factor | Relative risk (95% CI) | p-value | |
|---|
| Factors associated with diagnosis of DCIS compared with local disease | | | In-county facility | 1.32(0.98,1.77) | 0.06 | | | Adjacent county facility | 1.14(0.82,1.60) | 0.42 | | | Age at diagnosis | 0.99(0.991,1.00) | 0.33 | | | Aged >80 years at diagnosis | 0.63(0.49,0.80) | <0.001 | | | African-American race | 1.11(0.97,1.27) | 0.13 | | | Hispanic ethnicity | 0.93(0.80,1.09) | 0.38 | | | Factors associated with diagnosis with locally advanced or disseminated disease compared with local disease | | | In-county facility | 0.36(0.26,0.51) | <0.001 | | | Adjacent county facility | 0.80(0.53,1.23) | 0.32 | | | Age at diagnosis | 1.01(1.01,1.02) | <0.001 | | | Aged >80 years at diagnosis | 1.37(1.09,1.72) | 0.006 | | | African-American race | 1.52(1.22,1.90) | <0.001 | | | Hispanic ethnicity | 1.23(0.99,1.53) | 0.06 | | | | |
Discussion Persuasive evidence was found linking in-county mammography facilities to significantly higher odds of mammography screening. Further, the presence of a mammography facility in an adjacent county moderated the negative effect of lack of facilities to some extent. These findings may reflect a causal association that results from the impact of traveling distance, which has been shown to affect the utilization of healthcare services, including mammography services in metropolitan areas.15, 16, 18, 19 Meta-analyses of interventions used successfully in metropolitan counties also support the value of improving access and reducing inconvenience, often through the use of mobile mammography facilities.30, 31 An alternative explanation for these findings is that women who live in counties without facilities are different in ways that this study did not measure from women who live in counties with facilities. For example, they could be less motivated to seek screening. Absent person-level information about specific reasons for failure to screen, this explanation of the findings of this study cannot be ruled out. The expanding utilization of mammography services over the last 3 decades has been associated with an increase in the diagnosis of in situ breast cancers.22, 32 Women with lobular carcinoma in situ were excluded from this study owing to the controversy about its clinical significance.23 As expected, a significantly higher rate of diagnosis with ductal carcinoma in situ was observed in counties with mammography facilities. There is consensus that ductal carcinoma in situ is a pre-invasive cancer in a significant percentage of women affected. Thus, early diagnosis and treatment should benefit women by reducing the number of invasive and potentially fatal breast cancers. However, some cases of ductal carcinoma in situ might never progress to invasive disease if left untreated. In such cases, increased utilization of mammography screening could have negative effects on some women. In contrast to in situ cancers, there is no debate about the clinical significance of the diagnosis of invasive locally advanced or disseminated breast cancer. While the prognosis for women diagnosed at Stage IV has improved in recent years, this remains a fatal disease, with fewer than 30% of women surviving more than 5 years.33 A significantly lower risk of diagnosis at advanced stages is the justification for mammography screening,2 and the findings of this study substantiate those claims. The association of an in-county facility with a significantly lower risk of diagnosis at late stages points to an opportunity to affect breast cancer outcomes. As described in previous studies,15, 27, 29 African Americans and Hispanics were significantly more likely to be diagnosed with locally advanced or disseminated disease. Accounting for lack of access to in-county mammography facilities did not eliminate this disparity. It is possible that non-insurance or under-insurance and lack of a usual source of care, which are more prevalent in these populations than in their non-Hispanic white counterparts, may have led to delays in diagnosis. Lower median family income, higher poverty rates, and lower educational attainment, which also are more frequent in these populations, may have caused or compounded delays in diagnosis. It is also possible that women in these populations develop higher grade or more aggressive forms of the disease owing to some shared predisposition or exposure. Unfortunately, this study cannot shed light on the mechanism for this problem but, like previous studies, it does highlight its significance. Limitations There are several limitations to the current effort. First, as is the case with all studies using the BRFSS, these results can be generalized only to those women who have telephones in their homes. A comparison of information from the BRFSS telephone survey (fielded in most counties in the U.S.) and the nontelephone National Health Interview Survey (fielded in a few counties in the U.S.) showed that screening rates in households without telephones were significantly lower than in households with telephones.34 The 2000 Census showed that 3.2% of households in Texas lacked telephone access.35 However, if lack of telephone access is more common in counties without mammography facilities among rural households, it is possible that the odds of screening were over-estimated among women in rural Texas counties, which often lack mammography facilities. If present, this bias would have caused under-estimates of the differences between counties with and without mammography facilities. Second, lacking access to the addresses of BRFSS respondents and women diagnosed with breast cancer, access to same-county facilities was used as a surrogate for close geographic proximity. This is an imprecise measure of proximity owing to the differences in the size of counties. This same problem limited investigators' ability to examine border effects. Finally, a county was considered to have a facility if it had at least one facility at any time during the study period (2002–2004). In a few cases, counties acquired a facility for the first time late in the study period, with limited time for utilization prior to the BRFSS survey. This would bias the results toward no difference between counties with and without mammography facilities. Policy Implications Results of this study suggest that delivering mammography-screening services in the county of residence may benefit women who are currently underserved. There is a need to build capacity in underserved counties. In pleasant contrast to the delivery of other healthcare services, capacity can be increased in underserved counties without building permanent facilities and without the permanent relocation of healthcare professionals to rural counties. Digital mobile mammography facilities could be based in metropolitan centers, used primarily to augment capacity in underserved inner-city areas, and deployed to nearby rural counties several times annually. However, while this strategy could achieve screening objectives, it also could significantly increase demand for diagnostic and treatment services in remote rural counties. The careful design of strategies to enhance timely follow-up of positive mammograms and the provision of treatment services would be critical to achieving the improved outcomes associated with diagnosis at an earlier stage. Conclusion Significant associations were demonstrated in this study between the absence of in-county mammography facilities and both low odds of screening and high odds of diagnosis at a late stage of breast cancer. If this is confirmed in studies of other states, the provision of mammography services in every county should be implemented. Mobile mammography may provide a practical means of building capacity in rural areas. The authors thank Michele Sussman Walsh, MEd, CHES, for the BRFSS data used for the project. Data on incident cancer cases were provided by the Texas Cancer Registry, Cancer Epidemiology and Surveillance Branch, Texas Department of State Health Services, 1100 W. 49th Street, Austin TX 78756, www.dshs.state.tx.us/tcr/default.shtm or (512) 458-7523. The authors gratefully acknowledge the assistance of David Risser, PhD, Paul Betts, and Melanie Williams, PhD, in obtaining these data. The study was supported in part by grant DISP0707435 from Susan G. Komen for the Cure. Susan G. Komen for the Cure had no role in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; or in the preparation, review, or approval of the manuscript. Presented in part at the Annual Meeting of Texas Public Health Association April 25, 2006, Plano Texas. No financial disclosures were reported by the authors of this paper. References 1. 1Gotzsche PC, Nielsen M. Screening for breast cancer with mammography. Cochrane Database Syst Rev. 2006;(4):CD001877. 2. 2Smith RA, Duffy SW, Gabe R, Tabar L, Yen AM, Chen TH. The randomized trials of breast cancer screening: what have we learned?. Radiol Clin North Am. 2004;42:793–806. Abstract | Full Text |
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