부산대학교 도서관

Background: Spatial analysis is one of the required tools of epidemiology and public health sciences. This study intends to detect significant clusters of breast cancer cases in Kurdistan Province, Iran. Methods: We obtained data that pertained to breast cancer cases during 2005-2014 from the Health Deputy at Kurdistan University of Medical Sciences. After application of spatial scan statistics to detect the purely spatial (aggregation of cases in particular locations of space) and space-time (diseases clusters in space that depend on the time period) clusters, we calculated the population attribution risk (%) values to better distinguish the detected clusters. Results: We observed that the second secondary purely spatial cluster (P=0.0051) had the highest population attribution risk (%) of 3.8 and the primary space-time unadjusted cluster (P=0.0019) had the lowest population attribution risk (%) of 0.67 of all the detected clusters. Before we applied the adjustment, both the space-time and purely spatial clusters had similar locations. However, after adjustment for age, the space-time clusters location shifted and population attribution risk (%) values changed (between 0.02 and 0.4). Conclusion: Population attribution risk (%) value differences and clusters' temporal and spatial variations before and after adjustments can represent disease interventions impact. Additional studies should be conducted to strengthen the registering and reporting system to determine other influencing factors. [ABSTRACT FROM AUTHOR]