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Related Experiment Videos

Alternate ranging methods for cancer mortality maps.

D J Grauman1, R E Tarone, S S Devesa

  • 1Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA. dan_grauman@nih.gov

Journal of the National Cancer Institute
|April 6, 2000
PubMed
Summary

Comparing cancer mortality maps requires careful selection of ranging methods. Ranging across intervals reveals temporal trends but can obscure geographic patterns, while ranging within intervals highlights geographic variations but masks trends.

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Geographic Information Systems (GIS)

Background:

  • Cancer mortality mapping visualizes spatial and temporal variations in disease rates.
  • Standard mapping involves categorizing spatial units by rate ranges and assigning colors.
  • This study investigates the impact of different ranging methods on cancer mortality map comparisons across time.

Purpose of the Study:

  • To evaluate the consequences of using distinct ranging methods for comparing cancer mortality maps across multiple time intervals.
  • To determine how different ranging techniques affect the visualization of geographic patterns and temporal trends in cancer mortality data.

Main Methods:

  • Cancer mortality rates for breast, lung, and cervix uteri cancers in the US (1950-1994) were mapped by county or state economic area.

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  • Two ranging methods were applied: 1) 'ranging within intervals' (deciles per interval) and 2) 'ranging across intervals' (constant deciles for the entire period).
  • Time intervals (1950-1969 and 1970-1994) were chosen for population data availability, particularly for Black populations.

    • Main Results:

    • Ranging method had minimal impact on breast cancer maps due to stable mortality rates.
    • For lung (increasing rates) and cervix uteri (decreasing rates) cancers, 'ranging within intervals' showed geographic variability but obscured temporal trends.
    • 'Ranging across intervals' revealed temporal trends but partially obscured geographic variability, especially with rate shifts.

    Conclusions:

    • 'Ranging within intervals' effectively displays geographic patterns and their changes, irrespective of rate trends.
    • 'Ranging across intervals' highlights temporal rate changes but may reduce the clarity of geographic variability information.