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Modeling Geospatial Patterns of Late-Stage Diagnosis of Breast Cancer in the US

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  • Lee R. Mobley

    (School of Public Health and Andrew Young School of Policy Studies, Georgia State University, 1 Park Place, Atlanta, GA 30304, USA)

  • Tzy-Mey Kuo

    (Lineberger Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA)

  • Lia Scott

    (School of Public Health, Georgia State University, Atlanta, GA 30304, USA)

  • Yamisha Rutherford

    (School of Public Health, Georgia State University, Atlanta, GA 30304, USA)

  • Srimoyee Bose

    (School of Public Health, Georgia State University, Atlanta, GA 30304, USA)

Abstract

In the US, about one-third of new breast cancers (BCs) are diagnosed at a late stage, where morbidity and mortality burdens are higher. Health outcomes research has focused on the contribution of measures of social support, particularly the residential isolation or segregation index, on propensity to utilize mammography and rates of late-stage diagnoses. Although inconsistent, studies have used various approaches and shown that residential segregation may play an important role in cancer morbidities and mortality. Some have focused on any individuals living in residentially segregated places (place-centered), while others have focused on persons of specific races or ethnicities living in places with high segregation of their own race or ethnicity (person-centered). This paper compares and contrasts these two approaches in the study of predictors of late-stage BC diagnoses in a cross-national study. We use 100% of U.S. Cancer Statistics (USCS) Registry data pooled together from 40 states to identify late-stage diagnoses among ~1 million new BC cases diagnosed during 2004–2009. We estimate a multilevel model with person-, county-, and state-level predictors and a random intercept specification to help ensure robust effect estimates. Person-level variables in both models suggest that non-White races or ethnicities have higher odds of late-stage diagnosis, and the odds of late-stage diagnosis decline with age, being highest among the

Suggested Citation

  • Lee R. Mobley & Tzy-Mey Kuo & Lia Scott & Yamisha Rutherford & Srimoyee Bose, 2017. "Modeling Geospatial Patterns of Late-Stage Diagnosis of Breast Cancer in the US," IJERPH, MDPI, vol. 14(5), pages 1-16, May.
    • Handle: RePEc:gam:jijerp:v:14:y:2017:i:5:p:484-:d:97675
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    References listed on IDEAS

    as
    1. Manfred M. Fischer & Arthur Getis (ed.), 2010. "Handbook of Applied Spatial Analysis," Springer Books, Springer, number 978-3-642-03647-7, September.
    2. Rima Wilkes & John Iceland, 2004. "Hypersegregation in the twenty-first century," Demography, Springer;Population Association of America (PAA), vol. 41(1), pages 23-36, February.
    3. Oakes, J. Michael, 2004. "The (mis)estimation of neighborhood effects: causal inference for a practicable social epidemiology," Social Science & Medicine, Elsevier, vol. 58(10), pages 1929-1952, May.
    4. Bell, Janice F. & Zimmerman, Frederick J. & Almgren, Gunnar R. & Mayer, Jonathan D. & Huebner, Colleen E., 2006. "Birth outcomes among urban African-American women: A multilevel analysis of the role of racial residential segregation," Social Science & Medicine, Elsevier, vol. 63(12), pages 3030-3045, December.
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    Cited by:

    1. Yanrong Qiu & Kaihuai Liao & Yanting Zou & Gengzhi Huang, 2022. "A Bibliometric Analysis on Research Regarding Residential Segregation and Health Based on CiteSpace," IJERPH, MDPI, vol. 19(16), pages 1-21, August.
    2. Gomes, Veronica & Wiese, Daniel & Stroup, Antoinette & Henry, Kevin A., 2023. "Ethnic enclaves and colon cancer stage at diagnosis among New Jersey Hispanics," Social Science & Medicine, Elsevier, vol. 328(C).
    3. Salamata Yoda & Laurie A. Theeke, 2022. "A Scoping Review of Factors Contributing to Late-Stage Diagnosis of Breast Cancer in Racial and Ethnic Minority (African American and Hispanic) Women," SAGE Open, , vol. 12(4), pages 21582440221, December.

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