The role of poverty rate and racial distribution in the geographic clustering of breast cancer survival among older women: A geographic and multilevel analysis

American Journal of Epidemiology

Volumn 169, Issue 5, 2009, Pages 554-561

  Schootman, Mario ^a,b   Jeffe, Donna B ^a,b   Lian, Min ^a   Gillanders, William E ^a,b   Aft, Rebecca ^a,b,c  

^a WASHINGTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b USA   (United States)

^c VETERANS AFFAIRS MEDICAL CENTER   (United States)

Author keywords

Breast neoplasms; Cluster analysis; Geography; Population groups; Poverty; Survival

Indexed keywords

CANCER; CENSUS; CLUSTER ANALYSIS; EPIDEMIOLOGY; GEOGRAPHICAL VARIATION; GIS; POVERTY; STATISTICAL ANALYSIS; SURVIVAL; TUMOR; WOMENS HEALTH;

AFRICAN AMERICANS; AGED; AGED, 80 AND OVER; BREAST NEOPLASMS; CENSUSES; FEMALE; GEOGRAPHIC INFORMATION SYSTEMS; HEALTH STATUS DISPARITIES; HUMANS; MAMMOGRAPHY; MEDICARE; NEOPLASM STAGING; POVERTY; PROPORTIONAL HAZARDS MODELS; RISK FACTORS; SEER PROGRAM; SMALL-AREA ANALYSIS; SURVIVAL ANALYSIS; TIME FACTORS; UNITED STATES; URBAN POPULATION;

ATLANTA; DETROIT; GEORGIA; MICHIGAN; NORTH AMERICA; UNITED STATES;

EID: 60149111694     PISSN: 00029262     EISSN: 14766256     Source Type: Journal    
DOI: 10.1093/aje/kwn369     Document Type: Article

References (53)

1. American Cancer Society. Breast Cancer Facts & Figures, 2005-2006. Atlanta, GA: American Cancer Society, Inc; 2005.
2. National Cancer Institute. Estimated U.S. Cancer Prevalence. Bethesda, MD: National Cancer Institute; 2005.
3. Goldhirsch A, Glick JH, Gelber RD, et al. Meeting highlights: international expert consensus on the primary therapy of early breast cancer 2005. Ann Oncol. 2005;16(10):1569-1583.
4. Subramaniam DS, Isaacs C. Utilizing prognostic and predictive factors in breast cancer. Curr Treat Options Oncol. 2005;6(2):147-159.
5. MacKinnon JA, Duncan RC, Huang Y, et al. Detecting an association between socioeconomic status and late stage breast cancer using spatial analysis and area-based measures. Cancer Epidemiol Biomarkers Prev. 2007;16(4):756-762.
6. Robert SA, Strombom I, Trentham-Dietz A, et al. Socioeconomic risk factors for breast cancer: distinguishing individual- and community-level effects. Epidemiology. 2004;15(4):442-450.
7. Rosenberg L, Wise LA, Palmer JR, et al. A multilevel study of socioeconomic predictors of regular mammography use among African-American women. Cancer Epidemiol Biomarkers Prev. 2005;14(11 pt 1):2628-2633.
8. Grann V, Troxel AB, Zojwalla N, et al. Regional and racial disparities in breast cancer-specific mortality. Soc Sci Med. 2006;62(2):337-347.
9. Kravdal Ø. Does place matter for cancer survival in Norway? A multilevel analysis of the importance of hospital affiliation and municipality socio-economic resources. Health Place. 2006;12(4):527-537.
10. Sturgeon SR, Schairer C, Gail M, et al. Geographic variation in mortality from breast cancer among white women in the United States. J Natl Cancer Inst. 1995;87(24):1846-1853.
11. Devesa SS, Grauman DJ, Blot WJ, et al. Atlas of Cancer Mortality in the United States, 1950-94. (NIH publication no. 99-4564). Bethesda, MD: National Institutes of Health; 1999.
12. Hall HI, Rogers JD, Weir HK, et al. Breast and cervical carcinoma mortality among women in the Appalachian region of the US, 1976-1996. Cancer. 2000;89(7):1593-1602.
13. Baak JP, Wisse-Brekelmans EC, Kurver PH, et al. Regional differences in breast cancer survival are correlated with differences in differentiation and proliferation. Hum Pathol. 1992;23(9):989-992.
14. Karjalainen S. Geographical variation in cancer patient survival in Finland: chance, confounding or effect of treatment. J Epidemiol Community Health. 1990;44(3):210-214.
15. Gatta G, Buiatti E, Conti E, et al. Variations in the survival of adult cancer patients in Italy. Tumori. 1997;83(1):497-504.
16. Mettlin CJ, Schoenfeld ER, Natarajan N, et al. Interhospital differences in cancer survival. J Chronic Dis. 1987;40(2):157-164.
17. Agency for Healthcare Research and Quality. Guide to Clinical Preventive Services. Rockville, MD: Agency for Healthcare Research and Quality; 2006.
18. Zaza S, Briss P, Harris K. The Guide to Community Preventive Services. What Works to Promote Health? New York, NY: Oxford University Press; 2005.
19. Fried L, Barron J. Older adults: guardians of our cities. In: Galea S, Vlahov D, eds. Handbook of Urban Health. Populations, Methods, and Practice. New York, NY: Springer Publishing Company; 2005:177-200.
20. Potosky AL, Riley GF, Lubitz JD, et al. Potential for cancer related health services research using a linked Medicare-tumor registry database. Med Care. 1993;31(8):732-748.
21. Krieger N, Chen J, Waterman P, et al. Geocoding and monitoring of socioeconomic inequalities in mortality and cancer incidence: does the choice of area-based measure and geographic level matter? Am J Epidemiol. 2002;156(5):471-482.
22. Charlson ME, Pompei P, Ales K, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-383.
23. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992;45(6):613-619.
24. Warren JL, Harlan LC, Fahey A, et al. Utility of the SEER-Medicare data to identify chemotherapy use. Med Care. 2002;40(8 suppl):IV-55-IV-61.
25. Du X, Goodwin JS. Increase of chemotherapy use in older women with breast carcinoma from 1991 to 1996. Cancer. 2001;92(4):730-737.
26. Culler SD, Parchman ML, Przybylski M. Factors related to potentially preventable hospitalizations among the elderly. Med Care. 1998;36(6):804-817.
27. Parchman ML, Culler SD. Preventable hospitalizations in primary care shortage area. An analysis of vulnerable Medicare beneficiaries. Arch Fam Med. 1999;8(6):487-491.
28. Weissman JS, Gatsonis C, Epstein AM. Rates of avoidable hospitalization by insurance status in Massachusetts and Maryland. JAMA. 1992;268(17):2388-2394.
29. Earle CC, Burstein HJ, Winer EP, et al. Quality of non-breast cancer health maintenance among elderly breast cancer survivors. J Clin Oncol. 2003;21(8):1447-1451.
30. Rao S, Kubisiak J, Gilden D. Cost of illness associated with metastatic breast cancer. Breast Cancer Res Treat. 2004;83(1):25-32.
31. Nattinger A, Schapira M, Warren J, et al. Methodological issues in the use of administrative claims data to study surveillance after cancer treatment. Med Care. 2002;40(8 suppl):IV-69-IV-74.
32. Blustein J. Medicare coverage, supplemental insurance, and the use of mammography by older women. N Engl J Med. 1995;332(17):1138-1143.
33. May DS, Trontell AE. Mammography use by elderly women: a methodological comparison of two national data sources. Ann Epidemiol. 1998;8(7):439-444.
34. Randolph WM, Mahnken JD, Goodwin JS, et al. Using Medicare data to estimate the prevalence of breast cancer screening in older women: comparison of different methods to identify screening mammograms. Health Serv Res. 2002;37(6):1643-1657.
35. Randolph WM, Goodwin JS, Mahnken JD, et al. Regular mammography use is associated with elimination of age-related disparities in size and stage of breast cancer at diagnosis. Ann Intern Med. 2002;137(10):783-790.
36. Cooper GS, Schultz L, Simpkins J, et al. The utility of administrative data for measuring adherence to cancer surveillance care guidelines. Med Care. 2007;45(1):66-72.
37. Kulldorff M, Huang L, Pickle LW, et al. An elliptic spatial scan statistic. Stat Med. 2006;25(22):3929-3943.
38. Huang L, Pickle LW, Stinchcomb D, et al. Detection of spatial clusters: application to cancer survival as a continuous outcome. Epidemiology. 2007;18(1):73-87.
39. Krull JL, MacKinnon DP. Multilevel modeling of individual and group level mediated effects. Multivariate Behav Res. 2001;36(2):249-277.
40. Goldstein H. Restricted unbiased iterative generalized least-squares estimation. Biometrika. 1989;76(3):622-623.
41. Goldstein H. Multilevel Statistical Models. 2nd ed. London, United Kingdom: Edward Arnold Publishers; 1995.
42. Rasbash J, Browne W, Healy M, et al. MLwiN Beta Version 2.0. London, United Kingdom: Multilevel Models Project, Institute of Education, University of London; 2003.
43. Brawley OW. Disaggregating the effects of race and poverty on breast cancer outcomes. J Natl Cancer Inst. 2002;94(7):471-473.
44. Blackman DJ, Masi CM. Racial and ethnic disparities in breast cancer mortality: are we doing enough to address the root causes? J Clin Oncol. 2006;24(14):2170-2178.
45. Bradley CJ, Given CW, Roberts C. Race, socioeconomic status, and breast cancer treatment and survival. J Natl Cancer Inst. 2002;94(7):490-496.
46. Baker EA, Schootman M, Barnidge E, et al. The role of race and poverty in access to foods that enable individuals to adhere to dietary guidelines. Prev Chronic Dis. 2006;3(3):A76. (http://www.cdc.gov/pcd/issues/2006/jul/ pdf/05-0217.pdf).
47. Chlebowski RT, Blackburn GL, Thomson CA, et al. Dietary fat reduction and breast cancer outcome: interim efficacy results from the Women's Intervention Nutrition Study. J Natl Cancer Inst. 2006;98(24):1767-1776.
48. Reiche EM, Nunes SO, Morimoto HK. Stress, depression, the immune system, and cancer. Lancet Oncol. 2004;5(10):617-625.
49. Garssen B, Goodkin K. On the role of immunological factors as mediators between psychosocial factors and cancer progression. Psychiatry Res. 1999;85(1):51-61.
50. Institute of Medicine. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC: The National Academies Press; 2002. (http://www.iom.edu/CMS/3740/4475.aspx).
51. Warren JL, Klabunde CN, Schrag D, et al. Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population. Med Care. 2002;40(8 suppl):IV-3-IV-18.
52. Soerjomataram I, Louwman M, Ribot J, et al. An overview of prognostic factors for long-term survivors of breast cancer. Breast Cancer Res Treat. 2008;107(3):309-330.
53. Acevedo-Garcia D, Lochner K. Residential segregation and health. In: Kawachi I, Berkman L, eds. Neighborhoods and Health. Oxford, United Kingdom: Oxford University Press; 2003:265-287.