Choropleth map legend design for visualizing community health disparities

Robert G Cromley,Ellen K Cromley

doi:10.1186/1476-072x-8-52

Abstract

BackgroundDisparities in health outcomes across communities are a central concern in public health and epidemiology. Health disparities research often links differences in health outcomes to other social factors like income. Choropleth maps of health outcome rates show the geographical distribution of health outcomes. This paper illustrates the use of cumulative frequency map legends for visualizing how the health events are distributed in relation to social characteristics of community populations. The approach uses two graphs in the cumulative frequency legend to highlight the difference between the raw count of the health events and the raw count of the social characteristic like low income in the geographical areas of the map. The approach is applied to mapping publicly available data on low birth weight by town in Connecticut and Lyme disease incidence by town in Connecticut in relation to income. The steps involved in creating these legends are described in detail so that health analysts can adopt this approach.ResultsThe different health problems, low birth weight and Lyme disease, have different cumulative frequency signatures. Graphing poverty population on the cumulative frequency legends revealed that the poverty population is distributed differently with respect to the two different health problems mapped here.ConclusionCumulative frequency legends can be useful supplements for choropleth maps. These legends can be constructed using readily available software. They contain all of the information found in standard choropleth map legends, and they can be used with any choropleth map classification scheme. Cumulative frequency legends effectively communicate the proportion of areas, the proportion of health events, and/or the proportion of the denominator population in which the health events occurred that falls within each class interval. They illuminate the context of disease through graphing associations with other variables.

Highlights

Disparities in health outcomes across communities are a central concern in public health and epidemiology
Choropleth maps of health outcome rates calculated for administrative units at a variety of scales have long been used in public health and epidemiology, and their preparation is supported by geographic information systems
The data range for each class interval in the cumulative frequency legend is given using both numbers and length--a high-level perceptual task for visually decoding information [17]-whereas the range for each class interval in the standard legend is only given by numbers

Summary

Introduction

Disparities in health outcomes across communities are a central concern in public health and epidemiology. The approach uses two graphs in the cumulative frequency legend to highlight the difference between the raw count of the health events and the raw count of the social characteristic like low income in the geographical areas of the map. Choropleth maps of health outcome rates calculated for administrative units at a variety of scales have long been used in public health and epidemiology, and their preparation is supported by geographic information systems. The purpose of this research is to improve the communicative efficiency of choropleth maps of health outcomes through an enhanced legend design This design approach uses different combinations of cumulative frequency graphs in the map legend to highlight alternatively the underlying statistical distribution, the difference between the raw count of the numerator and the raw count of the denominator, and contextual information regarding characteristics of the areas being mapped.

Objectives

Results

Conclusion