Background: Inequity in megacities is a real concern in public health perspective. Tehran is a megacity with more than 8 million population
that is divided into 22 regions (counties) with considerable diversity in socioeconomic status. On the other hand, spatial cluster detection
is an important tool in disease surveillance for identifying areas of elevated risk and generating hypotheses about disease or mortality
etiology. The present research aims to identify KLJKRUORZULVNFOXVWHUVIRU¿YHQRQFRPPXQLFDEOHOHDGLQJcauses of death in 22 regions of
Tehran province.
Methods: &DXVHVSHFL;¿FPRUWDOLW\UDWHVZHUHH[WUDFWHGIURP%HKHVKWH=DKUDregistry system for Tehran province in 2011. Spatial scan
statistic was chosen as the most common method in spatial cluster detection to detect clusters with elevated risk of death. Given the obVHUYHGDQGH[SHFWHGQXPEHUGHDWKLQHDFKUHJLRQD
log likelihood ratio (LLR) criterion was used to test whetherDFOXVWHULVVLJQL¿FDQW
Result: Two high-risk and two low-risk clusters were detected for each cause of GHDWK$OOWKHVHFOXVWHUVZHUHVWDWLVWLFDOO\VLJQL¿FDQWZLWK
P values less than 0.05. Mapping these clusters shows substantial differences between regions in Tehran. For mortality due to ischemic
heart diseases, cerebrovascular diseases, hypertensive diseases, respiratory diseases, and stomach cancer, the high-risk clusters concentrated
in the southern half of Tehran and low-risk clusters were in the northern half of Tehran. In the most situations, regions 2, 3, and 5
seemed to have lower rates of death compared with other regions. On the other hand, regions, 16, 19, and 20 were in the high rate clusters.
Conclusion: There was substantial GLVSDULW\EHWZHHQUHJLRQVRI7HKUDQIRU¿YHQRQFRPPXQLFDEOHFDXVHVof death studied in this article.
Identifying factors affecting the observed differences is useful to set effective preventive interventions and can be investigated in future
researches.