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Geographic methods for understanding and responding to disparities in mammography use in Toronto, Canada

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Abstract

OBJECTIVE: To use spatial and epidemiologic analyses to understand disparities in mammaography use and to formulate interventions to increase its uptake in low-income, high-recent immigration areas in Toronto, Canada.

DESIGN: We compared mammography rates in four income-immigration census tract groups. Data were obtained from the 1996 Canadian census and 2000 physician billing claims. Risk ratios, linear regression, multilayer maps, and spatial analysis were used to examine utilization by area for women age 45 to 64 years.

SETTING: Residential population of inner city Toronto, Canada, with a 1996 population of 780,000.

PARTICIPANTS: Women age 45 to 64 residing in Toronto’s inner city in the year 2000.

MEASUREMENTS AND MAIN RESULTS: Among 113,762 women age 45 to 64, 27,435 (24%) had received a mammogram during 2000 and 91,542 (80%) had seen a physician. Only 21% of women had a mammogram in the least advantaged group (low income-high immigration), compared with 27% in the most advantaged group (high income-low immigration) (risk ratio, 0.79; 95% confidence interval, 0.75 to 0.84). Multilayer maps demonstrated a low income-high immigration band running through Toronto’s inner city and low mammography rates within that band. There was substantial geographic clustering of study variables.

CONCLUSIONS: We found marked variation in mammography rates by area, with the lowest rates associated with low income and high immigration. Spatial patterns identified areas with low mammography and low physician visit rates appropriate for outreach and public education interventions. We also identified areas with low mammography and high physician visit rates appropriate for interventions targeted at physicians.

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References

  1. Billings J, Zeitel L, Lukomnik J, Carey TS, Blank AE, Newman L. Impact of socioeconomic status on hospital use in New York City. Health Aff (Millwood). 1993;12:162–73.

    Article  CAS  Google Scholar 

  2. Marmot MG, Shipley MJ, Rose G. Inequalities in death-specific explanations of a general pattern? Lancet. 1984;1:1003–6.

    Article  PubMed  CAS  Google Scholar 

  3. Marmot MG, Smith DG, Stansfeld S, et al. Health inequalities among British civil servants: the Whitehall II study. Lancet. 1991;337:1387–93.

    Article  PubMed  CAS  Google Scholar 

  4. Lieu TA, Newacheck PW, McManus MA. Race, ethnicity, and access to ambulatory care among US adolescents. Am J Public Health. 1993;83:960–5.

    PubMed  CAS  Google Scholar 

  5. Cowie MR, Fahrenbruch CE, Cobb LA, Hallstrom AP. Out-of-hospital cardiac arrest: racial differences in outcome in Seattle. Am J Public Health. 1993;83:955–9.

    PubMed  CAS  Google Scholar 

  6. Carr W, Zeitel L, Weiss K. Variations in asthma hospitalizations and deaths in New York City. Am J Public Health. 1992;82:59–65.

    PubMed  CAS  Google Scholar 

  7. 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.

    Article  PubMed  CAS  Google Scholar 

  8. DeMers MN. Fundamentals of Geographic Information Systems. New York: John Wiley & Sons; 2000:7–16.

    Google Scholar 

  9. Cromley EK. GIS and Public Health. New York: Guilford Press; 2002:35–7.

    Google Scholar 

  10. Phillips RL, Kinman EL, Schnitzer PG, Lindbloom EJ, Ewigman B. Using geographic information systems to understand health care access. Arch Fam Med. 2000;9:971–8.

    Article  PubMed  Google Scholar 

  11. Backman AM, Rigby JM, Rice MD, Rivers LM. Locating community health care centres in rural Saskatchewan: the case of the Living Sky Health District. Health Manage Forum. 1995;8:52–61.

    Article  CAS  Google Scholar 

  12. Fosgate GT, Carpenter TE, Chomel BB, Case JT, DeBess EE, Reilly KF. Time-space clustering of human brucellosis, California, 1973–1992. Emerg Infect Dis. 2002;8:672–8.

    PubMed  Google Scholar 

  13. Buckeridge DL, Glazier R, Harvey BJ, Escobar M, Amrhein C, Frank J. Effect of motor vehicle emissions on respiratory health in an urban area. Environ Health Perspect. 2002;110:293–300.

    Article  PubMed  Google Scholar 

  14. Bird JA, McPhee SJ, Ha NT, Le B, Davis T, Jenkins CN. Opening pathways to cancer screening for Vietnamese-American women: Lay health workers hold a key. Prev Med. 1998;27:821–9.

    Article  PubMed  CAS  Google Scholar 

  15. Caplan LS, Wells BL, Haynes S. Breast cancer screening among older racial/ethnic minorities and whites: barriers to early detection. J Gerontol. 1992;47:101–10.

    PubMed  Google Scholar 

  16. Wells BL, Horm JW. Targeting the underserved for breast and cervical cancer screening: the utility of ecological analysis using the National Health Interview Survey. Am J Public Health. 1998;88:1484–9.

    Article  PubMed  CAS  Google Scholar 

  17. U.S. Preventive Services Task Force (USPSTF). Available at: http://www.ahcpr.gov/clinic/3rduspstf/breastcancer/brcanrr.htm. Accessed January 7, 2004.

  18. Canadian Taskforce on Preventive Health Care. Available at: http://www.ctfphc.org. Accessed January 7, 2004.

  19. Katz SJ, Hofer TP. Socieconomic disparities in preventive care persist despite universal coverage. Breast and cervical cancer screening in Ontario and the United States. JAMA. 1994;272:530–4.

    Article  PubMed  CAS  Google Scholar 

  20. Katz SJ, Zemencuk JK, Hofer TP. Breast cancer screening in the United States and Canada, 1994: socioeconomic gradients persist. Am J Public Health. 2000;90:799–803.

    PubMed  CAS  Google Scholar 

  21. Mercer SL, Goel V. Factors associated with the use of mammography: the Ontario Health Survey. Cancer Prev Control. 1997;1:144–51.

    PubMed  CAS  Google Scholar 

  22. Hyndman J, Holman CD, Jamrozik K. The effect of spatial definition on the allocation of clients to screening clinics. Soc Sci Med. 1997;45:331–40.

    Article  PubMed  CAS  Google Scholar 

  23. Roche LM, Skinner R, Weinstein RB syste. Use of a geographic information m to identify and characterize areas with high proportions of distant stage breast cancer. Public Health Manag Pract. 2002;8:26–32.

    Google Scholar 

  24. Wanner P, Raymond L, Bouchardy C. Geographical disparities in self-reported use of mammography and breast self-examination according to the Swiss Health Survey. Ann Oncol. 2001;12:573–4.

    Article  PubMed  CAS  Google Scholar 

  25. Citizenship and Immigration Canada. Facts and Figures, 2000—Immigration Overview. Ottawa: Strategic Policy, Planning and Research, Citizenship and Immigration Canada; 2001. Minister of Public Works and Government Services, Canada.

  26. Fotheringham AS, Brunsdon C, Charlton M. Quantitative Geography Perspectives on Spatial Data Analysis. London: SAGE Publications Ltd; 2002:237–40.

    Google Scholar 

  27. Dent BD. Cartography: Thematic Map Design. 5th ed. Dubuque, IA: Wm. C. Brown; 1999:138–86.

    Google Scholar 

  28. Jones CB. Geographic Information Systems and Computer Cartography. Harlow, Essex: Addison Wesley Longman Ltd; 1997:197–208.

    Google Scholar 

  29. Davison AC, Hinkley DV. Bootstrap Methods and Their Applications. New York: Cambridge Press; 1997.

    Google Scholar 

  30. Bailey TC, Gatrell AC. Interactive Spatial Data Analysis. New York: Longman Scientific & Technical Publications; 1995:274–89.

    Google Scholar 

  31. Freeman HP, Muth BJ, Kerner JF. Expanding access to cancer screening and clinical follow-up among the medically underserved. Cancer Pract. 1995;3:19–30.

    PubMed  CAS  Google Scholar 

  32. Yabroff KR, Mandelblatt JS. Interventions targeted toward patients to increase mammography use. Cancer Epidemiol Biomarkers Prev. 1999;8:749–57.

    PubMed  CAS  Google Scholar 

  33. Mandelblatt JS, Yabroff KR. Effectiveness of interventions designed to increase mammography use: a meta-analysis of provider-targeted strategies. Cancer Epidemiol Biomarkers Prev. 1999;8:759–67.

    PubMed  CAS  Google Scholar 

  34. Bickell NA. Race, ethnicity, and disparities in breast cancer: victories and challenges. Womens Health Issues. 2002;12:238–51.

    Article  PubMed  Google Scholar 

  35. Hubbell FA, Chavez LR, Mishra SI, Magana JR, Valdez R. From ethnography to intervention: developing a breast cancer control program for Latinas. Monogr Natl Cancer Inst. 1995;18:109–15.

    PubMed  Google Scholar 

  36. Mazmanian PE, Davis DA. Continuing medical education and the physician as a learner: guide to the evidence. JAMA. 2002;288:1057–60.

    Article  PubMed  Google Scholar 

  37. Glazier RH, Creatore MI, Agha M, Steele LS. Socioeconomic mis-classification in Ontario’s health care registry. Can J Public Health. 2003;94:140–3.

    PubMed  Google Scholar 

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Correspondence to Richard Henry Glazier MD, MPH.

Additional information

For the Toronto Inner City Health Time Trends Working Group: Mohammad M. Agha (Inner City Health Research Unit, St. Michael’s Hospital), Elizabeth M. Badley (Public Health Sciences, University of Toronto), Eleanor Boyle (Inner City Health Research Unit, St. Michael’s Hospital), Maria I. Creatore (Inner City Health Research Unit, St. Michael’s Hospital), Yu Ding (Inner City Health Research Unit, St. Michael’s Hospital), Richard H. Glazier (Inner City Health Research Unit, St. Michael’s Hospital), Piotr Gozdyra (Inner City Health Research Unit, St. Michael’s Hospital), Stephen Hwang (Inner City Health Research Unit, St. Michael’s Hospital), Flora Matheson (Inner City Health Research Unit, St. Michael’s Hospital), Rahim Moineddin (Family and Community Medicine, University of Toronto), Dianne Patychuk (Toronto Public Health), Lorraine Purdon (Southeast Toronto Project), Anne Rhodes (Inner City Health Research Unit, St. Michael’s Hospital), and Leah S. Steele (Inner City Health Research Unit, St. Michael’s Hospital).

Supported by the Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada, and the Ontario Ministry of Health and Long-Term Care. The opinions, results, and conclusions are those of the authors and no endorsement by the Ministry is intended or should be inferred.

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Glazier, R.H., Creatore, M.I., Gozdyra, P. et al. Geographic methods for understanding and responding to disparities in mammography use in Toronto, Canada. J GEN INTERN MED 19, 952–961 (2004). https://doi.org/10.1111/j.1525-1497.2004.30270.x

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  • DOI: https://doi.org/10.1111/j.1525-1497.2004.30270.x

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