D J Grauman1, R E Tarone, S S Devesa, J F Fraumeni. 1. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA. dan_grauman@nih.gov
Abstract
BACKGROUND: Mapping techniques can highlight the spatial or temporal variations in rates of cancer mortality. In mapping geographic patterns of cancer mortality, spatial units are grouped into categories defined by specified rate ranges, and then the units in each category are assigned a particular color in the map. We examined the consequences of using different ranging methods when comparing maps over several time intervals. METHODS: Maps of mortality rates for cancers of the breast, lung (including the lung, trachea, bronchus, and pleura), and cervix uteri in the United States by county or state economic area are created for different time intervals between 1950 and 1994. Two ranging methods are employed: 1) Ranges are defined for individual time interval by the deciles of rates in that interval (ranging within intervals), and 2) constant ranges for all time intervals are defined by the deciles of rates for the entire 45-year period from 1950 through 1994 (ranging across intervals). The time intervals from 1950 through 1969 and from 1970 through 1994 were chosen to accommodate the availability of detailed county-level population estimates specifically for blacks starting in 1970. RESULTS: The ranging method has little impact on maps for breast cancer mortality, which changed little over time. For lung cancer, which increased over time, and cervix uteri cancer, which decreased over time, ranging within time intervals shows the geographic variability but does not convey the temporal trends. Trends are evident when ranging across time intervals is employed; however, geographic variability is partially obscured by the predominance of spatial units in the highest rate categories in the recent time intervals for lung cancer and in the early time intervals for cervix uteri cancer. CONCLUSIONS: Ranging within time intervals displays geographic patterns and changes in geographic patterns, regardless of time trends in rates. Ranging across time intervals shows temporal changes in rates but with some loss of information about geographic variability.
BACKGROUND: Mapping techniques can highlight the spatial or temporal variations in rates of cancer mortality. In mapping geographic patterns of cancer mortality, spatial units are grouped into categories defined by specified rate ranges, and then the units in each category are assigned a particular color in the map. We examined the consequences of using different ranging methods when comparing maps over several time intervals. METHODS: Maps of mortality rates for cancers of the breast, lung (including the lung, trachea, bronchus, and pleura), and cervix uteri in the United States by county or state economic area are created for different time intervals between 1950 and 1994. Two ranging methods are employed: 1) Ranges are defined for individual time interval by the deciles of rates in that interval (ranging within intervals), and 2) constant ranges for all time intervals are defined by the deciles of rates for the entire 45-year period from 1950 through 1994 (ranging across intervals). The time intervals from 1950 through 1969 and from 1970 through 1994 were chosen to accommodate the availability of detailed county-level population estimates specifically for blacks starting in 1970. RESULTS: The ranging method has little impact on maps for breast cancer mortality, which changed little over time. For lung cancer, which increased over time, and cervix uteri cancer, which decreased over time, ranging within time intervals shows the geographic variability but does not convey the temporal trends. Trends are evident when ranging across time intervals is employed; however, geographic variability is partially obscured by the predominance of spatial units in the highest rate categories in the recent time intervals for lung cancer and in the early time intervals for cervix uteri cancer. CONCLUSIONS: Ranging within time intervals displays geographic patterns and changes in geographic patterns, regardless of time trends in rates. Ranging across time intervals shows temporal changes in rates but with some loss of information about geographic variability.