Spatial analysis of tuberculosis in four main ethnic communities in Taiwan during 2005 to 2009

Pui-Jen Tsai

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DOI: 10.4236/ojpm.2011.13017                

Abstract

The aim of the present study was to assess spatial features of tuberculosis prevalence and their relationships with four main ethnic communities in Taiwan. Methods of spatial analysis were clustering pattern determination (such as global version of Moran’s test and local version of G_i*(d) statistic), using logistic regression calculations to identify spatial distributions over a contiguous five years and identify significant similarities, discriminant analysis to classify variables, and geographically weighted regression (GWR) to determine the strength of relationships between tuberculosis prevalence and ethnic variables in spatial features. Tuberculosis demonstrated decreasing trends in prevalence in both genders during 2005 to 2009. All results of the global Moran’s tests indicated spatial heterogeneity and clusters in the plain and mountainous Aboriginal townships. The G_i*(d) statistic calculated z-score outcomes, categorized as clusters or non-clusters, at at 5% significance level. According to the stepwise Wilks’ lambda discriminant analysis, in the Aborigines and Hoklo communities townships with clusters of tuberculosis cases differentiated from townships without cluster cases, to a greater extent than in the other communities. In the GWR models, the explanatory variables demonstrated significant and positive signs of parameter estimates in clusters occurring in plain and mountainous aboriginal townships. The explanatory variables of both the Hoklo and Hakka communities demonstrated significant, but negative, signs of parameter estimates. The Mainlander community did not significantly associate with cluster patterns of tuberculosis in Taiwan. Results indicated that locations of high tuberculosis prevalence closely related to areas containing higher proportions of the Aboriginal community in Taiwan. This information is relevant for assessment of spatial risk factors, which, in turn, can facilitate the planning of the most advantageous types of health care policies, and implementation of effective health care services.

Keywords

Tuberculosis; Taiwanese Ethnicity; Global Moran’s Test; Local G_i*(d) Statistic; Logistic Regression; Discriminant Analysis; Geographically Weighted Regression

Conflicts of Interest

The authors declare no conflicts of interest.

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