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Spatial Exploratory Data Analysis of Birth Defect Risk Factors' Identification

Objective To acquire effective clues for identification of environmental risk factors to birth defects. Methods Spatial autocorrelation statistics Moran's I and spatial hotspots detect method Getis's G statistics was used to identify birth defect risk factor. Results The different kinds of birth defects have different spatial distribution. Neural tube birth defects have the properties of spatial autocorrelation and different clustering phenomena in different spatial scales. Two typical spatial patterns were discovered in spatial scales of about 6.84 kilometers and 22.8 kilometers. Conclusion Using spatial autocorrelation probing technique, we find that there may be some common environmental teratogenetic factors which affect birth defects occurring ratio in the study area. By hotspots analysis of the clustering phenomena, the risk factors leading to birth defect were further resolved.