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A Multilevel Study of Socioeconomic Predictors of Regular Mammography Use Among African-American Women

¹ Slone Epidemiology Center, Boston University, Boston; ² Mathematics Department, Smith College, Northampton, Massachusetts; and ³ Howard University Cancer Center, Washington, D.C.

Requests for reprints: Lynn Rosenberg, Slone Epidemiology Center, Boston University, 1010 Commonwealth Avenue, Boston, MA 02215. Phone: 617-734-6006; Fax: 617-738-5119. E-mail: lrosenberg{at}slone.bu.edu

	Abstract

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Background: Little is known about the predictors of adherence to mammography guidelines by African-American women. We assessed individual-level and group-level socioeconomic predictors of regular mammography use in a large cohort of African-American women.

Methods: We included 14,706 participants in the Black Women's Health Study who were 40 to 69 years of age at baseline in 1995. Data were obtained through mail questionnaires at entry and biennially during three 2-year follow-up periods until 2001. We linked the women's addresses to census block (neighborhood) socioeconomic data. With multilevel multivariable regression analysis, we assessed the relation of individual-level and neighborhood socioeconomic factors to "regular" mammography use (use in all three follow-up periods) relative to nonregular use, with control for other predictors.

Results: Most participants had health insurance and almost half had graduated college. Having health insurance was the socioeconomic variable most strongly associated with regular mammography use (odds ratio, 3.59; 95% confidence interval 3.02-4.28); the association was present at all levels of educational attainment, household income, and neighborhood socioeconomic status. Regular mammography use increased with individual household income: odds ratio, 2.00 (95% confidence interval, 1.58-2.53) for household income >$100,000 relative to <$15,001. Regular mammography use did not vary across level of education. Higher neighborhood socioeconomic status was significantly associated with regular mammography use before, but not after, control for household income.

Conclusions: Access to health insurance is strongly associated with regular mammography use among African-American women, even at higher levels of educational attainment and socioeconomic status. Neighborhood socioeconomic characteristics do not materially influence regular use.

	Introduction

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Breast cancer is the most commonly diagnosed cancer and the second most common cause of cancer mortality among African-American women (1-3) Although incidence rates after age 45 years are lower among Black women than among White women, mortality rates are higher in Black women at all ages (4). Black women tend to be diagnosed at more advanced stages of breast cancer compared with White women (5). Regular mammography screening could lead to earlier diagnosis and treatment and possibly reduce mortality (6-12). In 1997, the National Cancer Institute adopted new mammography screening guidelines: the previous recommendation that women ages 50 years who are at average breast cancer risk should be screened every 1 to 2 years was changed to include women ages 40 to 49 years (13). Mammography use by African-Americans has increased greatly in recent years and now equals that of White women (14-16).

There have been numerous studies of socioeconomic factors associated with ever and recent mammography use. National data collected in the Behavioral Risk Factor Surveillance System (17, 18) and the National Health Interview Survey (19) indicate that health insurance or access to medical care, higher income, higher level of education, and higher neighborhood socioeconomic status (SES) are important correlates of ever and recent use. Thus far, no study has assessed all of these factors simultaneously. In addition, little is known about factors that influence regular mammography use among African-American women (20).

We previously reported a cross-sectional analysis of recent mammography use in relation to age, education, and several breast cancer risk factors at baseline in the Black Women's Health Study (BWHS), a national follow-up study of the health of African-American women (21). In the present article, we report a prospective multilevel study of the influence of individual-level and group-level (neighborhood) socioeconomic factors on regular mammography use. The individual- and group-level socioeconomic factors were assessed simultaneously while also taking into account other potential predictors of regular mammography use.

	Materials and Methods

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The BWHS began in 1995 when African-American women ages 21 to 69 years from across the U.S. completed mailed health questionnaires (22-24). Most respondents were subscribers to Essence magazine, a general readership magazine targeted to African-American women, and a small proportion were friends and relatives of early respondents or members of selected professional organizations. The median age of respondents at baseline was 38 years, 97% had competed high school, and 45% had completed college or a higher level of education. The 59,084 respondents whose addresses were judged to be valid 1 year after entry were sent follow-up mail questionnaires every 2 years; follow-up rates of 80% were achieved in each follow-up cycle. The BWHS was approved by the Institutional Review Boards of Boston University Medical Center and Howard University Cancer Center.

The 1995 baseline questionnaire collected information on many factors, including when the participant had her most recent mammogram (never, <1 year ago, 1-2 years ago, 3-4 years ago, and 5+ years ago). The 1997, 1999, and 2001 follow-up questionnaires asked about disease and risk factors in the preceding 2 years, including whether the participant had a mammogram.

We assessed potential predictors of mammography use during three 2-year follow-up periods, 1995 to 1997 (1997 questionnaire data), 1997 to 1999 (1999 questionnaire data), and 1999 to 2001 (2001 questionnaire data). Among the 25,717 women who were ages 40 years and cancer-free at baseline in 1995, 18,075 (70.3% of age-eligible women) completed all three follow-up questionnaires; among the latter, 15,862 (61.7% of age-eligible women) completed the mammography questions on all three follow-up questionnaires. The latter women were linked to 2000 census block data by geocoding their 1995 addresses; the addresses of 1,156 women could not be geocoded, leaving a final study group of 14,706 women (57.2% of age-eligible women).

The individual-level socioeconomic factors assessed were health insurance status, years of education completed, having a second job, and household income. Neighborhood socioeconomic factors assessed were percentage of households below the poverty level, percentage of residents ages 25 years who had completed college, percentage of employed persons ages 16 years in white collar occupations, median housing value, percentage of households with dividend, rental, or interest income ("nonsalary" income), and percentage of residents who were African-American.

We also assessed individual-level factors that could confound the associations of the socioeconomic factors with mammography use. These included demographic variables (age, geographic region of residence, marital status), breast cancer risk factors (fibrocystic breast disease, breast cancer in a mother or sister, body mass index (kg/m²), parity, menopausal status), health habits and behaviors (participation in strenuous physical activity, cigarette smoking, alcohol use, use of multivitamins, use of female hormone supplements, breast self-exam, Pap screening), and child care responsibilities.

Data on all individual-level factors were derived from the 1995 baseline questionnaire with the exception of health insurance status, which was taken from the 1997 questionnaire, and household income, which was taken from the 2003 questionnaire.

The analysis was conducted in three stages. First, with multiple logistic regression analysis (SAS version 8.02; ref. 25), we assessed the associations of all individual-level factors except household income with "regular" mammography use (use in all three 2-year follow-up periods) relative to nonregular use (26). We included educational attainment and geographic region in all models, but other factors were kept in the model only if the odds ratio for at least one category of the variable was statistically significant at the 0.05 level. Second, with control of the individual-level factors that remained from the first stage, we assessed the association of each of the census block variables with regular mammography use in multilevel models (27) that considered each census block variable separately (MLWIN version 2.1e; ref. 28). Multilevel models account for clustering of two or more women within a census block. Of the census variables, the only ones found to be associated with regular mammography use were the percentage who had completed college and the percentage with nonsalary income (P for trend <0.05 for each considered as a continuous variable). These two variables were combined into a neighborhood SES score, derived as follows. For each of the two census variables, a Z-score for each census block was calculated by subtracting the mean of all census blocks in the sample from the value for the particular block group and dividing by the SD; the neighborhood score was the sum of the Z-scores for the two census variables, with higher scores indicating higher SES (29). In the final stage of the analysis, we included the individual factors and the neighborhood SES score in the multilevel model. We were interested in whether there would be an effect of neighborhood SES after control for individual-level SES. Therefore, we ran the final analysis with and without control for individual household income. Results from the final analyses are presented.

The above analyses were confined to women who completed the mammography questions on all three follow-up questionnaires from 1997 to 2001. To assess whether these women differed from potentially eligible women who were excluded because of failure to meet that criterion, we compared the included and excluded women. Similar proportions of included and excluded women reported having health insurance in 1997 (95% versus 93%). Greater proportions of included women than excluded women reported household incomes >$50,000 (55% versus 48%), lived in neighborhoods in the top quartile of the neighborhood SES score (28% versus 22%), and had completed 16 years of education (49% versus 40%). We also compared the proportion of included women who reported mammography use on each of the questionnaires with the proportion among excluded women who had answered those questions. The proportions of included and excluded women who reported having undergone mammography were 94% and 90% on the 1995 questionnaire, 95% and 93% on the 1997 questionnaire, 93% and 91% on the 1999 questionnaire, and 91% and 82% on the 2001 questionnaire, respectively.

	Results

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Among the 14,706 women studied, distributed over 10,484 census blocks, mammography use in all three 2-year follow-up periods was reported by 79.8%, use in two periods only by 14.0%, use in one period only by 3.9%, and no use in any period by 2.3%.

As shown in Table 1, health insurance was the socioeconomic factor most strongly associated with regular mammography use. With control for individual-level factors other than household income, the odds ratio was 4.00 (95% confidence interval (CI), 3.38-4.73). After control for household income, the estimate was attenuated by 10% to 3.59 (95% CI, 3.02-4.28). Household income was also associated with regular mammography use: with control for all other factors, the odds ratio was 2.00 (95% CI, 1.58-2.53) for income >$100,000 relative to income <$15,001. Neighborhood SES was significantly associated with regular mammography use when family income was not controlled: odds ratio, 1.25 (95% CI, 1.10-1.42) for the highest quartile of score relative to the lowest (P trend = 0.0013). After control for family income, the corresponding estimate was smaller, 1.15, and no longer statistically significant (95% CI, 1.00-1.31; P trend = 0.064). The results for neighborhood SES were similar when we restricted the analysis to women who had not moved between 1995 and 2001. Level of education was not associated with regular mammography use, whether or not household income was controlled.

	Discussion

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Among the well-insured African-American women assessed here, more than three quarters reported regular mammography use, i.e., use in all three of the 2-year follow-up periods studied. The proportion of women in other studies who adhered to mammography guidelines has varied greatly because of differences in the definition of adherence, differences in the populations studied, and secular increases in mammography use over time (20, 30-47). In their 2003 review of such studies, Jones et al. concluded that all ethnic groups, including African-Americans, had lower than recommended rates of regular mammography use (20). For example, the Mammography Attitudes and Usage Studies found that only 48% of African-American women were in compliance with screening guidelines in 1995. However, that frequency was about double the frequency in 1992 (35, 43).

Among the socioeconomic characteristics studied in the BWHS, having health insurance was most strongly associated with regular mammography use, and the association was observed at all the levels of educational attainment, household income, and neighborhood SES studied. Recent Pap smear and female hormone use, indicators of access to the medical care system, were also associated with regular use. Previous studies have found health insurance to be a major correlate of mammography use (17, 19, 44, 47, 48). Regular mammography use in the BWHS was positively associated with household income but not with level of education. Neighborhood SES was weakly and significantly associated with regular mammography use before control for individual-level household income. However, after control for income, the association was attenuated and not statistically significant. Some studies have found lower educational level to be associated with decreased use of mammography (16, 20, 30, 31, 47). However, there was little variation across level of education beyond high school in two recent studies of regular mammography use, one conducted in Colorado (44) and the other in Maryland, New York, Ohio, and Texas (45). Regular mammography use was associated with median income per ZIP code in the Colorado study (44) and with higher personal income in a health maintenance organization study in Michigan (41) and in the National Health Interview Survey (48), but these studies did not have data on both neighborhood and individual-level SES.

With respect to other variables, we found that women ages 50 years reported regular mammography use more frequently than younger women, as in earlier reports (16, 19, 20); the recommendation for screening of women ages 40 to 49 years was made relatively recently (13). "Healthy" behaviors, such as breast self-examination, multivitamin use, and nonsmoking were also associated with regular use, as expected (19). Consistent with previous results (47), BWHS participants with breast cancer risk factors—fibrocystic breast disease or a family history of breast cancer—were more likely to have regular mammography use than women without these factors. A potential barrier to regular mammography use, having childcare responsibilities, was associated with decreased mammography use, but only weakly.

The present study is much larger than any previous study of mammography use in Black women. The rich database permitted the assessment of a wide range of potential predictors of use. The multilevel assessment of SES took into account individual-level and group-level socioeconomic factors simultaneously, made allowance for the clustering of women within neighborhoods, and controlled for other correlates of mammography use. It seems that mammography use is reported accurately, although there is a tendency to underestimate the time interval since last screening (49, 50). The prospective design of the BWHS, with follow-up every 2 years, allowed for timely reporting of mammography use; that and the high level of education would have contributed to reporting accuracy. Some of the mammograms reported by women who developed breast cancer may have been for diagnostic purposes rather than for screening, but because the percentage of women who developed breast cancer during the 6 years of follow-up was small (2%), their reports could not have materially distorted the results. There have been numerous changes of address by women in the BWHS (51), and misclassification of the neighborhood characteristics of women who had moved during the follow-up period would have tended to weaken associations with neighborhood SES. However, the results were similar to those presented when we restricted the analysis to women who had not moved. We had information on health insurance status in 1997 only, and on income in 2003. These variables are likely to have changed over the course of follow-up. Misclassification of these variables, if unrelated to mammography use, would have resulted in underestimation of associations.

The women included in the present analysis were a select group of BWHS respondents insofar as they had completed all three follow-up questionnaires and the mammography questions in them. A comparison with women of the same ages who were excluded indicated that the included women were better educated and had higher incomes than the excluded women, but the differences were not large. The included women reported greater use of mammography than those excluded, but use in both groups was high. We are unable to postulate any mechanism by which the exclusions could have accounted for the associations seen in the present study. Moreover, subgroup analyses among women in different education and SES strata produced similar results.

The BWHS is not a representative sample of African-American women. Virtually all BWHS participants have completed high school, whereas the corresponding percentage nationally among Black women of the same ages is 83% (52). More than twice as many BWHS participants completed college compared with Black women nationally. The participants who completed health questionnaires in all three of the 2-year follow-up cycles assessed in this report are the most cooperative members of the BWHS cohort. It is noteworthy that in this educated and health-conscious group of Black women, health insurance was the most important correlate of mammography use. The implication of this finding is that loss of health insurance, which is a growing problem nationally (53), can be expected to adversely affect adherence to mammography guidelines in the future, even among women who have a higher SES and who are aware of the benefits of regular screening (54, 55). For poor and underserved women, it will be important to continue programs such as the Centers for Disease Control's National Breast and Cervical Cancer Early Detection Program in order to assure their access to mammography screening.

	Acknowledgments

 
This work would not have been possible without the dedication of BWHS participants and staff.

	Footnotes

 
Grant support: National Cancer Institute (CA 58420).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received 6/15/05; revised 8/15/05; accepted 8/31/05.

	References

Top Abstract Introduction Materials and Methods Results Discussion References

 

1. Haynes MA, Smedley BC, editors. The unequal burden of cancer: cancer research among minorities and the medically underserved. Institute of Medicine; National Academy Press; 1999.
2. Wingo PA, Ries LA, Rosenberg HM, Miller DS, Edwards BK. Cancer incidence and mortality 1973–1995: a report card for the U.S. Cancer 1998;82:1197–207.[CrossRef][Medline]
3. Howe HL, Wingo PA, Thun MJ, et al. Annual report to the nation on the status of cancer (1973 through 1998), featuring cancers with recent increasing trends. J Natl Cancer Inst 2001;93:824–42.[Abstract/Free Full Text]
4. Ries LAG, Eisner MP, Rosary CL, et al. SEER cancer statistics review, 1973–1997. Bethesda: National Cancer Institute; 2000.
5. Ghafoor A, Jemal A, Ward E, Cokkinides V, Smith P, Thun M. Trends in breast cancer by race and ethnicity. CA Cancer J Clin 2003;53:342–55.[Abstract/Free Full Text]
6. Olsen O, Gotzsche PC. Cochrane reviewing on screening for breast cancer with mammography. Lancet 2001;358:1340–42.[CrossRef][Medline]
7. Fletcher SW, Black W, Harris R, Rimer BK, Shapiro S. Report of the international workshop on screening for breast cancer. J Natl Cancer Inst 1993;85:1644–56.[Abstract/Free Full Text]
8. Hendrick RE, Smith RA, Rutledge JH III, Smart CR. Benefit of screening mammography in women aged 40–49: a new meta-analysis of randomized controlled trials. J Natl Cancer Inst Monogr 1997;22:87–92.
9. Li CI, Malone KE, Daling JR. Differences in breast cancer hormone receptor status and histology by race and ethnicity among women 50 years of age and older. Cancer Epidemiol Biomarkers Prev 2002;11:301–7.
10. Joslyn SA. Hormone receptors in breast cancer: racial differences in distribution and survival. Breast Cancer Res Treat 2002;73:45–59.[CrossRef][Medline]
11. Elledge RM, Clark GM, Chamness GC, Osborne CK. Tumor biologic factors and breast cancer prognosis among White, Hispanic, and Black women in the United States. J Natl Cancer Inst 1994;86:1352–3.[Free Full Text]
12. Middleton LP, Chen V, Perkins GH, Pinn V, Page D. Histopathology of breast cancer among African-American women. Cancer 2003;97:253–7.[CrossRef][Medline]
13. Eastman P. NCI adopts new mammography screening guidelines for women. J Natl Cancer Inst 1997;89:538–9.[Free Full Text]
14. Hoffman-Goetz L, Breen NL, Meissner H. The impact of social class on the use of cancer screening within three racial/ethnic groups in the United States. Ethn Dis 1998;8:43–51.[Medline]
15. Blackman DK, Bennett Em, Miller DS. Trends in self-reported use of mammograms (1989–1997) and Papanicolaou tests (1991–1997)—Behavioral Risk Factor Surveillance System, 1997. MMWR CDC Surveill Summ 1999;48:1–22.[Medline]
16. Centers for Disease Control. National Center for Health Statistics. Use of mammography for women 40 years of age or older, according to selected characteristics: selected years, 1987–2000. Bethesda: Centers for Disease Control; 2002.
17. Qureshi M, Thacker HL, Litaker DG, Kippes C. Difference in breast cancer screening rates: an issue of ethnicity of socioeconomics? J Womens Health Gend Based Med 2000;9:1025–31.[CrossRef][Medline]
18. Schootman M, Jeffe DB, Reschke A, Aft R. Disparities related to socioeconomic status and access to medical care remain in the United States among women who never had a mammogram. Cancer Causes Control 2003;14:419–25.[CrossRef][Medline]
19. Selvin E, Brett KM. Breast and cervical cancer screening: sociodemographic predictors among White, Black, and Hispanic women. Am J Public Health 2003;93:618–23.[Abstract/Free Full Text]
20. Jones BA, Patterson EA, Calvocoressi L. Mammography screening in African-American women. Cancer 2003;97 Suppl:258–72.[CrossRef][Medline]
21. Cozier Y, Palmer JR, Rosenberg L, Adams-Campbell LL. Recent mammography use among African-American women. Ethn Dis 2001;11:188–91.[Medline]
22. Rosenberg L, Adams-Campbell L, Palmer JR. The Black Women's Health Study: a follow-up study for causes and preventions of illness. J Am Med Womens Assoc 1995;50:56–8.
23. Adams-Campbell LL, Rosenberg L, Rao RS, Palmer JR. Strenuous physical activity and breast cancer risk in African-American women. J Natl Med Assoc 2001;93:267–75.[Medline]
24. Palmer JP, Wise LA, Horton NJ, Adams-Campbell LL, Rosenberg L. Dual effect of parity on breast cancer risk in African-American women. J Natl Cancer Inst 2003;95:478–83.[Abstract/Free Full Text]
25. SAS Institute Inc. SAS/STAT User's Guide, Version 8.02. Cary (NC): SAS Institute; 2002.
26. Schesselman JJ. Case-control studies: design, conduct, analysis. New York (NY): Oxford University Press; 1982.
27. Liang KY, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika 1986;73:13–22.
28. Rasbash J, Steele F, Browne W, Prosser B. A user's guide to MLWIN version 2.1e. London (UK): University of London; 2004.
29. Diez-Roux AV, Merkin SS, Arnett D, et al. Neighborhood of residence and incidence of coronary heart disease. N Engl J Med 2001;345:99–106.[Abstract/Free Full Text]
30. Pearlman DN, Rakowski W, Ehrich B, Clark MA. Breast screening practices among Black, Hispanic, and White women: reassessing differences. Am J Prev Med 1996;12:327–37.[Medline]
31. Phillips JM, Wilbur J. Adherence to breast cancer screening guidelines among African-American women of differing employment status. Cancer Nurs 1995;18:258–69.[Medline]
32. Lerman C, Rimer B, Trock B, Balsham A, Engstrom PF. Factors associated with repeat adherence to breast cancer screening. Prev Med 1990;19:279–90.[CrossRef][Medline]
33. Whitman S, Ansell D, Lacey L, et al. Patterns of breast and cervical cancer screening at three public health centers in an inner-city urban area. Am J Public Health 1991;81:1651–3.[Abstract/Free Full Text]
34. Mickey RM, Durski MS, Worden JK, Danigelis NL. Breast cancer screening and associated factors for low-income African-American women. Prev Med 1995;24:467–76.[CrossRef][Medline]
35. Lee JR, Vogal VG. Who uses screening mammography regularly? Cancer Epidemiol Biomarkers Prev 1995;4:901–6.[Abstract]
36. Horton JA, Cruess DF, Romans MC. Compliance with mammography screening guidelines: 1995 mammography attitudes and usage study report. Womens Health Issues 1996;6:239–45.[CrossRef][Medline]
37. Miller AM, Champion VL. Attitudes about breast cancer and mammography: racial, income, and educational differences. Women Health 1997;26:41–63.[CrossRef][Medline]
38. Taylor VM, Thompson B, Montano DE, Mahloch J, Johnson K, Li S. Mammography use among women attending an inner-city clinic. J Cancer Educ 1998;13:96–101.[Medline]
39. Song L, Fletcher R. Breast cancer rescreening in low-income women. Am J Prev Med 1998;15:128–33.[CrossRef][Medline]
40. Evans JL, Nasca PC, Baptiste MS, et al. Factors associated with repeat mammography in a New York State public health screening program. J Public Health Manag Pract 1998;4:63–71.[Medline]
41. Ulcickas Yood M, McCarthy BD, Lee NC, Jacobsen G, Johnson CC. Patterns and characteristics of repeat mammography among women 50 years and older. Cancer Epidemiol Biomarkers Prev 1999;8:595–9.[Abstract/Free Full Text]
42. Reisch LM, Barton MD, Fletcher SW, Kreuter W, Elmore JG. Breast cancer screening use by African Americans and Whites in an HMO. J Gen Intern Med 2000;15:229–34.[Medline]
43. Romans MC. Utilization of mammography. Social and behavioral trends. Cancer 1993;72:1475–7.[Medline]
44. Rahman SMM, Dignan MB, Shelton BJ. Factors influencing adherence to guidelines among women aged 40 years and older. Ethn Dis 2003;13:477–84.[Medline]
45. Bobo JK, Shapiro JA, Schulman J, Wolters CL. On-schedule mammography rescreening in the National Breast and Cervical Cancer Early Detection Program. Cancer Epidemiol Biomarkers Prev 2004;13:620–30.[Abstract/Free Full Text]
46. Clark MA, Rakowski W, Bonacore LB. Repeat mammography: prevalence estimates and considerations for assessment. Ann Behav Med 2003;26:202–11.
47. Rakowski W, Breen N, Meissner H, et al. Prevalence and correlates of repeat mammography among women aged 55–79 in the year 2000 National Health Interview Survey. Prev Med 2004;39:1–10.[Medline]
48. Swan J, Breen N, Coates RJ, Rimer BK, Lee NC. Progress in cancer screening practices in the United States. Results from the 2000 National Health Interview Survey. Cancer 2003;97:1528–40.[CrossRef][Medline]
49. Caplan LS, McQueen DV, Qualters JR, Leff M, Garrett C, Calonge N. Validity of women's self-reports of cancer screening test utilization in a managed care population. Cancer Epidemiol Biomarkers Prev 2003;12:1182–7.[Abstract/Free Full Text]
50. Zapka JG, Bigelow C, Hurley T. Mammography use among sociodemographically diverse women: the accuracy of self report. Am J Public Health 1996;86:1016–21.[Abstract/Free Full Text]
51. Russell C, Palmer JR, Adams-Campbell LL, Rosenberg L. Follow-up of a large cohort of Black women. Am J Epidemiol 2001;154:845–53.[Abstract/Free Full Text]
52. Educational attainment in the United States. Current population reports. Series P-20, No. 513. Washington, DC: U.S. Department of Commerce; 1998.
53. Krugman P. Ailing health care. New York Times; April 11, 2005.
54. Makuc DM, Breen N, Freid V. Low income, race, and the use of mammography. Health Serv Res 1999;34:229–39.[Medline]
55. Rutten LJF, Nelson DE, Meissner HI. Examination of population-wide trends in barriers to cancer screening from a diffusion of innovation perspective (1987–2000). Prev Med 2004;38:258–68.[Medline]

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