Spatial autocorrelation analysis of health care hotspots in Taiwan in 2006

Abstract

Background: Spatial analytical techniques and models are often used in epidemiology to identify spatial anomalies (hotspots) in disease regions. These analytical approaches can be used to not only identify the location of such hotspots, but also their spatial patterns.

Methods: In this study, we utilize spatial autocorrelation methodologies, including Global Moran's I and Local Getis-Ord statistics, to describe and map spatial clusters, and areas in which these are situated, for the 20 leading causes of death in Taiwan. In addition, we use the fit to a logistic regression model to test the characteristics of similarity and dissimilarity by gender.

Results: Gender is compared in efforts to formulate the common spatial risk. The mean found by local spatial autocorrelation analysis is utilized to identify spatial cluster patterns. There is naturally great interest in discovering the relationship between the leading causes of death and well-documented spatial risk factors. For example, in Taiwan, we found the geographical distribution of clusters where there is a prevalence of tuberculosis to closely correspond to the location of aboriginal townships.

Conclusions: Cluster mapping helps to clarify issues such as the spatial aspects of both internal and external correlations for leading health care events. This is of great aid in assessing spatial risk factors, which in turn facilitates the planning of the most advantageous types of health care policies and implementation of effective health care services.

Figure 1

Map of urban areas and aboriginal townships in the study area. Map of the study area divided into 349 administrative districts including 7 urban areas and an integrated area of 29 aboriginal townships.

Figure 2

Results of the analysis of the connectivity distributions of neighboring administrative district boundaries in Taiwan.

Figure 3

Spatial clusters (hotspots) of the 20 leading causes of death from top 1 to 6 in Taiwan in 2006. Maps showing the spatial clusters of the 20 leading causes of death from top 1 to 6 in Taiwan in 2006: malignant neoplasms are designated by A; cerebrovascular disease, B; heart disease, C; diabetes mellitus, D; accidents and adverse effects, E; pneumonia, F. Gender is indicated by a number, where male is 1 and female is 2.

Figure 4

Spatial clusters (hotspots) of the 20 leading causes of death from top 7 to 14 in Taiwan in 2006. Maps showing the spatial clusters of the 20 leading causes of death from top 7 to 14 in Taiwan in 2006: chronic liver disease and cirrhosis are designated by G; nephritis, nephritic syndrome and nephrosis, H; suicide, I; hypertensive disease, J; bronchitis, emphysema and asthma, K; septicaemia, L; tuberculosis, M; ulcer of stomach and duodenum, N. Gender is indicated by a number, where male is 1 and female is 2.

Figure 5

Spatial clusters (hotspots) of the 20 leading causes of death from top 15 to 20 in Taiwan in 2006. Maps showing the spatial clusters of the 20 leading causes of death from top 15 to 20 in Taiwan in 2006: certain conditions originating in the perinatal period are designated by O; congenital anomalies, P; anaemias, Q; homicide, R; meningitis, S; and other protein-calorie malnutrition, T. Gender is indicated by a number, where male is 1 and female is 2.

Figure 6

Map of cross tabulations with consistency rates for the top 20 leading health care problems in Taiwan, 2006.