Medical geography applies the theory, methods and analysis tools of geography science to the study of human health, disease and health care systems. As the Geographic Information System (GIS) has evolved since the mid-twentieth century, its uses have spread in geographic-related knowledge. Medical geography also uses GIS in the study and analysis of health and diseases researches. Mental retardation (MR) is a subset of developmental delay (DD), a broader classification of childhood disability. Spatial analysis is useful for the identification of areas with MR people. Identification of clusters based on MR provides an important tool to investigate risk exposures. However, even though MR is a substantial public health problem, there are no previous analyses of spatial clustering of MR using individual case data. In this paper, we examine the use of the spatial analysis approach in the analysis of MR clustering. We used data from the 2006 census, which addresses the amount of MR data available on a county level. MR cases with unknown causes were identified in the study population. Local statistic indices were used to identify spatial clusters of MR, the corresponding P-value for each geo-coded location, and the P-value surface contoured as a heat image to identify the MR clusters. The characteristics of the study population were analyzed using Moran's I value and Getis-Ord Gi statistic and the results confirm that clustering does occur for MR. The shapes of the identified MR clusters were found in counties with a high illiteracy percentage. Also MR cluster were discovered in counties with a high rate of residence in rural areas.

Keywords: Mental retardation / mMedical geography / Spatial analysis / Local statistic indices / Spatial cluster.

Ali Goli, Assistant professor, Sociology and Social Planning Department, Social Science Faculty, Shiraz University, Shiraz

EMail: [email protected]


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  • Received: 15 May 2012
  • Accepted: 15 May 2012
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