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Continuous Rural-Urban Coding for Cancer Disparity Studies: Is It Appropriate for Statistical Analysis?

Author

Listed:
  • Lusine Yaghjyan

    (Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL 32601, USA)

  • Christopher R. Cogle

    (Division of Hematology and Oncology, Department of Medicine, College of Medicine, University of Florida, Gainesville, FL 32601, USA)

  • Guangran Deng

    (Department of Geography, College of Liberal Arts and Sciences, University of Florida, Gainesville, FL 32601, USA)

  • Jue Yang

    (Department of Geography, College of Liberal Arts and Sciences, University of Florida, Gainesville, FL 32601, USA)

  • Pauline Jackson

    (Division of Hematology and Oncology, Department of Medicine, College of Medicine, University of Florida, Gainesville, FL 32601, USA)

  • Nancy Hardt

    (College of Medicine, University of Florida, Gainesville, FL 32601, USA)

  • Jaclyn Hall

    (Institute for Child Health Policy, College of Medicine, University of Florida, Gainesville, FL 32601, USA)

  • Liang Mao

    (Department of Geography, College of Liberal Arts and Sciences, University of Florida, Gainesville, FL 32601, USA)

Abstract

Background : The dichotomization or categorization of rural-urban codes, as nominal variables, is a prevailing paradigm in cancer disparity studies. The paradigm represents continuous rural-urban transition as discrete groups, which results in a loss of ordering information and landscape continuum, and thus may contribute to mixed findings in the literature. Few studies have examined the validity of using rural-urban codes as continuous variables in the same analysis. Methods : We geocoded cancer cases in north central Florida between 2005 and 2010 collected by Florida Cancer Data System. Using a linear hierarchical model, we regressed the occurrence of late stage cancer (including breast, colorectal, hematological, lung, and prostate cancer) on the rural-urban codes as continuous variables. To validate, the results were compared to those from using a truly continuous rurality data of the same study region. Results : In term of associations with late-stage cancer risk, the regression analysis showed that the use of rural-urban codes as continuous variables produces consistent outcomes with those from the truly continuous rurality for all types of cancer. Particularly, the rural-urban codes at the census tract level yield the closest estimation and are recommended to use when the continuous rurality data is not available. Conclusions : Methodologically, it is valid to treat rural-urban codes directly as continuous variables in cancer studies, in addition to converting them into categories. This proposed continuous-variable method offers researchers more flexibility in their choice of analytic methods and preserves the information in the ordering. It can better inform how cancer risk varies, degree by degree, over a finer spectrum of rural-urban landscape.

Suggested Citation

  • Lusine Yaghjyan & Christopher R. Cogle & Guangran Deng & Jue Yang & Pauline Jackson & Nancy Hardt & Jaclyn Hall & Liang Mao, 2019. "Continuous Rural-Urban Coding for Cancer Disparity Studies: Is It Appropriate for Statistical Analysis?," IJERPH, MDPI, vol. 16(6), pages 1-14, March.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:6:p:1076-:d:217172
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    References listed on IDEAS

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