Calculation of Heart Disease Death Rates
Our study population
consisted of women and men aged 35 years and older who resided in the
United States during 1991–1995. County maps of heart disease mortality
were created for six groups: American Indian and Alaska Natives, Asian and
Pacific Islanders, blacks, Hispanics, whites, and all racial and ethnic
groups combined. We calculated heart disease death rates at the county
level for each group by using death certificate data from the National
Vital Statistics System and population data collected by the Bureau of the
Census. We defined a heart disease death as any death for which the
underlying cause of death recorded on the death certificate fell into the
category "diseases of the heart," as defined by the National Center
for Health Statistics. This category included deaths coded 390–398, 402,
404–429 under the Ninth Revision of the International Classification of
Diseases (see Data Sources).
Important
methodological issues had to be resolved before we could map geographic
patterns of heart disease mortality. Analyses at the county level provide
a high degree of spatial specificity but are also subject to potential
statistical biases. Specifically, for counties with sparse populations and
small numbers of heart disease deaths, the estimated death rates were
likely to have large variances which could result in many counties having
estimated rates that were spuriously high or low. The issue of small
populations was particularly relevant for examining patterns of heart
disease mortality by race and ethnicity, because racial and ethnic
populations tend to be concentrated in certain geographic regions and
sparse in other regions. For all races and ethnicities, populations are
more sparse in rural than in urban counties.
One of the challenges in mapping heart disease death rates at the county
level is the uneven distribution of population among counties. For
counties with small populations, death rates can vary substantially from
year to year based on a small change in the number of deaths. These death
rates are considered unstable and mapping them can result in
misrepresentations of the true geographic patterns.1 We
employed two approaches to reduce the statistical variability of the
county mortality rates for heart disease: 1) temporal aggregation of the
data for the five year period 1991–1995, and 2) application of a
statistical procedure known as spatial
smoothing.
Spatial smoothing
involves calculating spatial moving averages for all counties.1
Heart disease deaths (numerators) and population counts (person–year
denominators) for each county were summed together with the deaths and
populations of the immediate neighboring counties (i.e. contiguous
counties) and then divided to produce an average rate. Stated another way,
the rate shown on the map for a single county represents an average of the
heart disease mortality experience of that county and all its contiguous
neighbors (see Spatial Smoothing of Heart
Disease Mortality Rates).
All rates were
age–adjusted, with the 1970 U.S. population used as the standard, and are
presented as deaths per 100,000 population (see
Spatial Smoothing of Heart Disease Mortality Rates). On each map,
counties were grouped into five categories of approximately equal number
(quintiles) based on the county distribution of smoothed heart disease
death rates. Counties were first ranked from lowest to highest based on
heart disease death rates. The lowest one–fifth of counties were assigned
to the first quintile; counties with death rates between the 20th and 40th
percentiles were assigned to the second quintile; between the 40th and
60th percentiles to the third quintile; between the 60th and 80th
percentiles to the fourth quintile; and the highest one–fifth of counties
were assigned to the highest quintile. The use of quintiles for mapping is
appropriate for smoothed death rates and helps the reader avoid
over–interpreting the data.
Because the severity of
heart disease mortality varied by race and ethnicity, the quintile
cutpoints are different for each of the national and state maps, and the
range of values represented by a given quintile varies from map to map.
Therefore, comparisons of the spatial patterns of heart disease mortality
across the maps should be limited to comparing relative differences among
different groups of women and men. To determine whether the mortality
rates were absolutely higher or lower for one race and ethnicity group
than for another, the reader must study the relevant legends and compare
the cutpoints. It is well worth making a mental note of the range of
county heart disease death rates for each group when comparing geographic
patterns across maps.
Reference
1. Cressie N. Statistics for Spatial Data. New York: Wiley, 1991.
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Date last reviewed:
05/12/2006
Content source: Division for Heart Disease and Stroke
Prevention,
National Center for Chronic Disease Prevention and
Health Promotion |
