Skip to main content

Advertisement

SpringerLink
Log in

Neighborhood foreclosures and self-rated health among breast cancer survivors

  • Published:
Quality of Life Research Aims and scope Submit manuscript

Abstract

Purpose

We determined the association of neighborhood foreclosure risk on the health status of a statewide sample of breast cancer survivors (n = 1047) and the extent to which covariates accounted for observed associations.

Methods

Measures of self-rated health and several covariates were obtained by telephone interview 1 year after diagnosis. We used the federal Housing and Urban Development agency’s estimated census-tract foreclosure-abandonment-risk score and multilevel, logistic regression to determine the association of foreclosure risk (high, moderate versus low) with self-rated health (fair-poor versus good, very good, excellent) and whether covariates could explain the observed association.

Results

Women who resided in high-foreclosure-risk (HFR) areas were 2.39 times (95% CI: 1.83–3.13) more likely to report being in fair-poor health than women who lived in low-foreclosure-risk areas. The odds ratio (OR) was reduced for women who lived in high-foreclosure-risk versus low-foreclosure-risk areas after adjusting for income (HFR OR: 1.78; 95% CI: 1.01–3.15), physical activity (HFR OR: 1.74; 95% CI: 0.98–3.08), and perceived neighborhood conditions (HFR OR: 1.76; 95% CI: 1.02–3.05).

Conclusions

Breast cancer survivors who lived in census tracts with high- versus low-foreclosure risk reported poorer health status. This association was explained by differences in household income, physical activity, and perceived neighborhood conditions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. Foreclosure: A situation in which a homeowner is unable to make principal and/or interest payments on his or her mortgage, so the lender, be it a bank or building society, can seize and sell the property as stipulated in the terms of the mortgage contract.

Abbreviations

OR:

Odds ratio

HUD:

Housing and urban development

BRFSS:

Behavioral risk factor surveillance system

CES-D:

Center for epidemiologic studies depression

References

  1. RealtyTrac Staff. (2009). 1.9 million foreclosure filings reported on more than 1.5 million US properties in first half of 2009. http://www.realtytrac.com/contentmanagement/pressrelease.aspx?channelid=9&accnt=0&itemid=6802. Accessed October 6, 2009.

  2. Schumer, C. E. (2009). Schumer on record home foreclosures report. http://jec.senate.gov/public/index.cfm?p=PressReleases&ContentRecord_id=5a01bd59-ab4f-3e18-eba8-c1914fb33982&ContentType_id=efc78dac-24b1-4196-a730-d48568b9a5d7&66d767ed-750b-43e8-b8cf-89524ad8a29e&14f995b9-dfa5-407a-9d35-56cc7152a7ed&Group_id=13cba799-f4a9-43ae-be11-76d2994d7042. Accessed October 6, 2009.

  3. Pollack, C. E., & Lynch, J. (2009). Health status of people undergoing foreclosure in the Philadelphia region. American Journal of Public Health, 99, 1833–1839.

    Article  PubMed  Google Scholar 

  4. Pevalin, D. J. (2009). Housing repossessions, evictions and common mental illness in the UK: Results from a household panel study. Journal of Epidemiology and Community Health, 63(11), 949–951.

    Article  PubMed  CAS  Google Scholar 

  5. Bennett, G. G., Scharoun-Lee, M., Tucker-Seeley, R. (2009). Will the public’s health fall victim to the home foreclosure epidemic? PLoS Medicine, 6(6), e1000087. Epub 2009 Jun 16.

  6. Reisen, W., Takahashi, R., Carroll, B., & Quiring, R. (2008). Delinquent mortgages, neglected swimming pools, and West Nile Virus, California. Emerging Infectious Diseases, 14, 1747–1749.

    Article  PubMed  Google Scholar 

  7. Riva, M., Gauvin, L., & Barnett, T. A. (2007). Toward the next generation of research into small area effects on health: A synthesis of multilevel investigations published since July 1998. Journal of Epidemiology and Community Health, 61(10), 853–861.

    Article  PubMed  Google Scholar 

  8. Idler, E. L., & Angel, R. J. (1990). Self-rated health and mortality in the NHANES-I epidemiologic follow-up study. American Journal of Public Health, 80(4), 446–452.

    Article  PubMed  CAS  Google Scholar 

  9. Idler, E. L., & Benyamini, Y. (1997). Self-rated health and mortality: A review of twenty-seven community studies. Journal of Health and Social Behavior, 38(1), 21–37.

    Article  PubMed  CAS  Google Scholar 

  10. Idler, E. L., Russell, L. B., & Davis, D. (2000). Survival, functional limitations, and self-rated health in the NHANES I epidemiologic follow-up study, 1992. American Journal of Epidemiology, 152(9), 874–883.

    Article  PubMed  CAS  Google Scholar 

  11. Hennessy, C. H., Moriarty, D. G., Zack, M. M., Scherr, P. A., & Brackbill, R. (1994). Measuring health-related quality of life for public health surveillance. Public Health Reports, 109(5), 665–672.

    PubMed  CAS  Google Scholar 

  12. Andresen, E. M., Catlin, T. K., Wyrwich, K. W., & Jackson-Thompson, J. (2003). Retest reliability of surveillance questions on health related quality of life. Journal of Epidemiology and Community Health, 57(5), 339–343.

    Article  PubMed  CAS  Google Scholar 

  13. Moriarty, D., Zack, M., & Kobau, R. (2003). The Centers for Disease Control and Prevention’s Healthy Days measures—Population tracking of perceived physical and mental health over time. Health and Quality of Life Outcomes, 1(1), 37.

    Article  PubMed  Google Scholar 

  14. Power, C., Matthews, S., & Manor, O. (1996). Inequalities in self rated health in the 1958 birth cohort: Lifetime social circumstances or social mobility? British Medical Journal, 313(7055), 449–453.

    Article  PubMed  CAS  Google Scholar 

  15. Shetterly, S. M., Baxter, J., Mason, L. D., & Hamman, R. F. (1996). Self-rated health among hispanic vs non-hispanic white adults: The San Luis Valley Health and Aging Study. American Journal of Public Health, 86(12), 1798–1801.

    Article  PubMed  CAS  Google Scholar 

  16. Finch, B. K., Hummer, R. A., Reindl, M., & Vega, W. A. (2002). Validity of self-rated health among Latino(a)s. American Journal of Epidemiology, 155(8), 755–759.

    Article  PubMed  Google Scholar 

  17. US Department of Housing and Urban Development. (2010). Neighborhood stabilization program data. HUD provided local level data. http://www.huduser.org/portal/datasets/nsp_foreclosure_data.html. Accessed May 5, 2010.

  18. Franzini, L., Caughy, M., Spears, W., & Eugenia Fernandez Esquer, M. (2005). Neighborhood economic conditions, social processes, and self-rated health in low-income neighborhoods in Texas: A multilevel latent variables model. Social Science and Medicine, 61(6), 1135–1150.

    Article  PubMed  Google Scholar 

  19. USDA Economic Research Service. (2010). Measuring rurality: Rural-urban commuting area codes. http://www.ers.usda.gov/briefing/rurality/ruralurbancommutingareas/. Accessed May 5, 2010.

  20. Castellino, S. M., Casillas, J., Hudson, M. M., Mertens, A. C., Whitton, J., Brooks, S. L., et al. (2005). Minority adult survivors of childhood cancer: A comparison of long-term outcomes, health care utilization, and health-related behaviors from the Childhood Cancer Survivor Study. Journal of Clinical Oncology, 23(27), 6499–6507.

    Article  PubMed  Google Scholar 

  21. Ross, C., & Mirowsky, J. (1999). Disorder and decay. The concept and measurement of perceived neighborhood disorder. Urban Affairs Review, 34, 412–432.

    Google Scholar 

  22. Sampson, R. J., Raudenbush, S. W., & Earls, F. (1997). Neighborhoods and violent crime, a multilevel study of collective efficacy. Science, 277, 918–924.

    Article  PubMed  CAS  Google Scholar 

  23. Ross, C., Reynolds, J., & Geis, K. (2000). The contingent meaning of neighborhood stability for residents’ psychological well-being. American Sociological Review, 65, 581–597.

    Article  Google Scholar 

  24. Krieger, N., Chen, J., Waterman, P., Soobader, M., Subramanian, S., & Carson, R. (2002). Geocoding and monitoring of socioeconomic inequalities in mortality and cancer incidence: does the choice of area-based measure and geographic level matter? American Journal of Epidemiology, 156, 471–482.

    Article  PubMed  Google Scholar 

  25. Sherbourne, C., & Stewart, A. (1991). The MOS social support survey. Social Science and Medicine, 32, 705–714.

    Article  PubMed  CAS  Google Scholar 

  26. Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health Social Behavior, 24(4), 385–396.

    Article  CAS  Google Scholar 

  27. McHorney, C. A., & Lerner, J. (1991). The 1990 NORC National Health Survey: Documentation and codebook. Chicago: National Opinion Research Council.

    Google Scholar 

  28. Kohout, F. J., Berkman, L. F., Evans, D. A., & Cornoni-Huntley, J. (1993). Two shorter forms of the CES-D (Center for Epidemiological Studies Depression) depression symptoms index. Journal on Aging and Health, 5(2), 179–193.

    Article  CAS  Google Scholar 

  29. Katz, J. N., Chang, L. C., Sangha, O., Fossel, A. H., & Bates, D. W. (1996). Can comorbidity be measured by questionnaire rather than medical record review? Medical Care, 34(1), 73–84.

    Article  PubMed  CAS  Google Scholar 

  30. Schag, C. A., Ganz, P. A., Polinsky, M. L., Fred, C., Hirji, K., & Petersen, L. (1993). Characteristics of women at risk for psychosocial distress in the year after breast cancer. Journal of Clinical Oncology, 11, 783–793.

    PubMed  CAS  Google Scholar 

  31. Schootman, M., Jeffe, D., West, M., & Aft, R. L. (2005). Comparison of self-reported breast cancer treatment and medical records among older women. Journal of Clinical Epidemiology, 58, 1316–1319.

    Article  PubMed  Google Scholar 

  32. Wolinsky, F. D., Andresen, E. M., Malmstrom, T. K., Schootman, M., Miller, J. P., & Miller, D. K. (2009). Three-year measured weight change in the African American Health Study. Journal of Aging and Health, 21(2), 231–243.

    Article  PubMed  Google Scholar 

  33. D’Agostino, R. B., Jr. (1998). Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group. Statistics in Medicine, 17(19), 2265–2281.

    Article  PubMed  Google Scholar 

  34. Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 41–55.

    Article  Google Scholar 

  35. Rubin, D. B. (1979). Using multivariate matched sampling and regression adjustment to control bias in observational studies. Journal of the American Statistical Association, 74(366), 318–328.

    Article  Google Scholar 

  36. Schuetz, J., Been, V., & Ellen, I. G. (2008). Neighborhood effects of concentrated mortgage foreclosures. Journal of Housing Economics, 17(4), 306–319.

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported in part by grants from the National Cancer Institute (CA112159, CA91842). The funders did not have any role in the design of the study; the analysis and interpretation of the data; the decision to submit the manuscript for publication; or the writing of the manuscript. We thank the Alvin J. Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine in St. Louis, Missouri, for the use of the Health Behavior, Communications, and Outreach Core. We also thank Jeannette Jackson-Thompson and the Missouri Cancer Registry for the identification of eligible women and data collection.

Author information

Authors and Affiliations

  1. Division of Health Behavior Research, Departments of Medicine and Pediatrics, Washington University School of Medicine, Box 8504, 4444 Forest Park Avenue, Saint Louis, MO, 63108, USA

    Mario Schootman, Anjali D. Deshpande, Sandi L. Pruitt & Donna B. Jeffe

  2. Alvin J. Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine, Saint Louis, MO, 63110, USA

    Mario Schootman, Anjali D. Deshpande & Donna B. Jeffe

Authors
  1. Mario Schootman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anjali D. Deshpande
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sandi L. Pruitt
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Donna B. Jeffe
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mario Schootman.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Schootman, M., Deshpande, A.D., Pruitt, S.L. et al. Neighborhood foreclosures and self-rated health among breast cancer survivors. Qual Life Res 21, 133–141 (2012). https://doi.org/10.1007/s11136-011-9929-0

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-011-9929-0

Keywords

Search

Navigation