Methodology r visualizing community health disparities

Background: Disparities 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. Results: The 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. Conclusion: Cumulative 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. Background Disparities in health outcomes across communities are a central concern in public health and epidemiology. Methods of exploratory data analysis and geovisualization are commonly used to provide insight into the patterns of the health outcomes. 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 now supported by geographic information systems. These maps display the Published: 24 September 2009 International Journal of Health Geographics 2009, 8:52 doi:10.1186/1476-072X-8-52 Received: 10 July 2009 Accepted: 24 September 2009 This article is available from: http://www.ij-healthgeographics.com/content/8/1/52 © 2009 Cromley and Cromley; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. oropleth map legend design fo